You searched for +publisher:"Michigan Technological University" +contributor:("Bo Chen").
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Michigan Technological University
1.
Liu, Chuanliangzi.
DEVELOPMENT OF HARDWARE-IN-THE-LOOP SIMULATION SYSTEM FOR ELECTRIC POWER STEERING CONTROLLER TESTING.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2015, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etds/992 
► The Electronic Control Unit (ECU) of an Electric Power Steering (EPS) system is a core device to decide how much assistance an electric motor…
(more)
▼ The Electronic Control Unit (ECU) of an Electric Power Steering (EPS) system is a core device to decide how much assistance an electric motor applies on steering wheel. EPS ECUs play an important role in EPS systems. The effectiveness of EPS ECUs needs to be thoroughly tested before mass production. Hardware-in-the-loop (HIL) simulation provides an efficient way for the development and testing of embedded controllers. This report focuses on the development of HIL system for testing EPS controllers. The hardware of the HIL system employs a dSPACE HIL simulator. The EPS plant model is an integrated model consisting of Vehicle Dynamics model of the dSPACE Automotive Simulation Model (ASM) and the Nexteer model. The report presents the design of EPS HIL system, the simulation of sensors and actuators, the functions of ASM Vehicle Dynamics model, and the integration method of ASM Vehicle Dynamics model with Nexteer model. The offline simulation of the integrated model is performed and the results for different driving maneuvers are presented. The real-time HIL testing will be conducted in the future to examine the performance of an entire HIL system.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Electro-Mechanical Systems; Mechanical Engineering
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APA (6th Edition):
Liu, C. (2015). DEVELOPMENT OF HARDWARE-IN-THE-LOOP SIMULATION SYSTEM FOR ELECTRIC POWER STEERING CONTROLLER TESTING. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etds/992
Chicago Manual of Style (16th Edition):
Liu, Chuanliangzi. “DEVELOPMENT OF HARDWARE-IN-THE-LOOP SIMULATION SYSTEM FOR ELECTRIC POWER STEERING CONTROLLER TESTING.” 2015. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etds/992.
MLA Handbook (7th Edition):
Liu, Chuanliangzi. “DEVELOPMENT OF HARDWARE-IN-THE-LOOP SIMULATION SYSTEM FOR ELECTRIC POWER STEERING CONTROLLER TESTING.” 2015. Web. 08 Mar 2021.
Vancouver:
Liu C. DEVELOPMENT OF HARDWARE-IN-THE-LOOP SIMULATION SYSTEM FOR ELECTRIC POWER STEERING CONTROLLER TESTING. [Internet] [Masters thesis]. Michigan Technological University; 2015. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etds/992.
Council of Science Editors:
Liu C. DEVELOPMENT OF HARDWARE-IN-THE-LOOP SIMULATION SYSTEM FOR ELECTRIC POWER STEERING CONTROLLER TESTING. [Masters Thesis]. Michigan Technological University; 2015. Available from: https://digitalcommons.mtu.edu/etds/992
Michigan Technological University
2.
Li, Yang.
Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2013, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etd-restricted/168
► The development of embedded control systems for a Hybrid Electric Vehicle (HEV) is a challenging task due to the multidisciplinary nature of HEV powertrain…
(more)
▼ The development of embedded control systems for a Hybrid Electric Vehicle (HEV) is a challenging task due to the multidisciplinary nature of HEV powertrain and its complex structures. Hardware-In-the-Loop (HIL) simulation provides an open and convenient environment for the modeling, prototyping, testing and analyzing HEV control systems. This thesis focuses on the development of such a HIL system for the hybrid electric vehicle study. The hardware architecture of the HIL system, including dSPACE eDrive HIL simulator, MicroAutoBox II and MotoTron Engine Control Module (ECM), is introduced. Software used in the system includes dSPACE Real-Time Interface (RTI) blockset, Automotive Simulation Models (ASM), Matlab/Simulink/Stateflow, Real-time Workshop, ControlDesk Next Generation, ModelDesk and MotoHawk/MotoTune. A case study of the development of control systems for a single shaft parallel hybrid electric vehicle is presented to summarize the functionality of this HIL system.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: dSPACE; ECMS; HEV; HIL; powertrain control; Mechanical Engineering
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APA (6th Edition):
Li, Y. (2013). Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etd-restricted/168
Chicago Manual of Style (16th Edition):
Li, Yang. “Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study.” 2013. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etd-restricted/168.
MLA Handbook (7th Edition):
Li, Yang. “Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study.” 2013. Web. 08 Mar 2021.
Vancouver:
Li Y. Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study. [Internet] [Masters thesis]. Michigan Technological University; 2013. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etd-restricted/168.
Council of Science Editors:
Li Y. Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study. [Masters Thesis]. Michigan Technological University; 2013. Available from: https://digitalcommons.mtu.edu/etd-restricted/168
Michigan Technological University
3.
Wu, Baifan.
STUDY OF HYBRID ELECTRIC VEHICLE BATTERY MODELING AND CONTROL USING AUTONOMIE.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2013, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etd-restricted/174
► This report presents the research results of battery modeling and control for hybrid electric vehicles (HEV). The simulation study is conducted using plug-and-play powertrain…
(more)
▼ This report presents the research results of battery modeling and control for hybrid electric vehicles (HEV). The simulation study is conducted using plug-and-play powertrain and vehicle development software, Autonomie. The base vehicle model used for testing the performance of battery model and battery control strategy is the Prius MY04, a power-split hybrid electric vehicle model in Autonomie. To evaluate the battery performance for HEV applications, the Prius MY04 model and its powertrain energy flow in various vehicle operating modes are analyzed. The power outputs of the major powertrain components under different driving cycles are discussed with a focus on battery performance. The simulation results show that the vehicle fuel economy calculated by the Autonomie Prius MY04 model does not match very well with the official data provided by the department of energy (DOE). It is also found that the original battery model does not consider the impact of environmental temperature on battery cell capacities. To improve battery model, this study includes battery current loss on coulomb coefficient and the impact of environmental temperature on battery cell capacity in the model. In addition, voltage losses on both double layer effect and diffusion effect are included in the new battery model. The simulation results with new battery model show the reduced fuel economy error to the DOE data comparing with the original Autonomie Prius MY04 model.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Mechanical Engineering
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APA (6th Edition):
Wu, B. (2013). STUDY OF HYBRID ELECTRIC VEHICLE BATTERY MODELING AND CONTROL USING AUTONOMIE. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etd-restricted/174
Chicago Manual of Style (16th Edition):
Wu, Baifan. “STUDY OF HYBRID ELECTRIC VEHICLE BATTERY MODELING AND CONTROL USING AUTONOMIE.” 2013. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etd-restricted/174.
MLA Handbook (7th Edition):
Wu, Baifan. “STUDY OF HYBRID ELECTRIC VEHICLE BATTERY MODELING AND CONTROL USING AUTONOMIE.” 2013. Web. 08 Mar 2021.
Vancouver:
Wu B. STUDY OF HYBRID ELECTRIC VEHICLE BATTERY MODELING AND CONTROL USING AUTONOMIE. [Internet] [Masters thesis]. Michigan Technological University; 2013. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etd-restricted/174.
Council of Science Editors:
Wu B. STUDY OF HYBRID ELECTRIC VEHICLE BATTERY MODELING AND CONTROL USING AUTONOMIE. [Masters Thesis]. Michigan Technological University; 2013. Available from: https://digitalcommons.mtu.edu/etd-restricted/174
Michigan Technological University
4.
Agashe, Pushkar Vivek.
MODEL-BASED DESIGN AND HARDWARE-IN-THE-LOOP SIMULATION OF INTERNAL COMBUSTION ENGINE CONTROL SYSTEMS.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2013, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etd-restricted/254
► This report studies model-based embedded system design for the control of Internal Combustion (IC) engines. The advantages of model-based design and the development tools…
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▼
This report studies model-based embedded system design for the control of Internal Combustion (IC) engines. The advantages of model-based design and the development tools are discussed. The application of this method for IC engine control is the focus of the first part of the report. In the second part, the Hardware-In-the-Loop (HIL) simulation is introduced with emphasis on the engine controller and its modification for lean operation control. For the IC engine control, the control functionalities of an engine electronic control unit (ECU) in dSPACE Automotive Simulation Models (ASM) are analyzed. The lean combustion control model is implemented in a hardware engine ECU - MotoTron Engine Control Module (ECM) and validated by a HIL simulator. The HIL simulator used for the simulation study is dSPACE E-Drive HIL simulator. The HIL simulation result shows that the developed lean combustion control strategy can reduce fuel consumption. The lean operation at a lambda value of 1.2 is seen to have the lowest injection duration while still producing the same amount of torque. It is also found that the implemented method is able to meet the required torque better at the lower load operating conditions. The variation in the output torque is increased at the higher load conditions.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Acoustics, Dynamics, and Controls; Automotive Engineering; Mechanical Engineering
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APA (6th Edition):
Agashe, P. V. (2013). MODEL-BASED DESIGN AND HARDWARE-IN-THE-LOOP SIMULATION OF INTERNAL COMBUSTION ENGINE CONTROL SYSTEMS. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etd-restricted/254
Chicago Manual of Style (16th Edition):
Agashe, Pushkar Vivek. “MODEL-BASED DESIGN AND HARDWARE-IN-THE-LOOP SIMULATION OF INTERNAL COMBUSTION ENGINE CONTROL SYSTEMS.” 2013. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etd-restricted/254.
MLA Handbook (7th Edition):
Agashe, Pushkar Vivek. “MODEL-BASED DESIGN AND HARDWARE-IN-THE-LOOP SIMULATION OF INTERNAL COMBUSTION ENGINE CONTROL SYSTEMS.” 2013. Web. 08 Mar 2021.
Vancouver:
Agashe PV. MODEL-BASED DESIGN AND HARDWARE-IN-THE-LOOP SIMULATION OF INTERNAL COMBUSTION ENGINE CONTROL SYSTEMS. [Internet] [Masters thesis]. Michigan Technological University; 2013. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etd-restricted/254.
Council of Science Editors:
Agashe PV. MODEL-BASED DESIGN AND HARDWARE-IN-THE-LOOP SIMULATION OF INTERNAL COMBUSTION ENGINE CONTROL SYSTEMS. [Masters Thesis]. Michigan Technological University; 2013. Available from: https://digitalcommons.mtu.edu/etd-restricted/254
Michigan Technological University
5.
Badgujar, Pankaj Prabhakar.
INTEGRATION OF GT-POWER ENGINE MODEL WITH DSPACE VEHICLE MODEL FOR CO-SIMULATION AND VALIDATION.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2014, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etd-restricted/206
► Mean value engine modeling (MVEM) is vital for control design to test advanced internal combustion engines. dSPACE ASM (Automotive Simulation Models) Gasoline Engine model…
(more)
▼ Mean value engine modeling (MVEM) is vital for control design to test advanced internal combustion engines. dSPACE ASM (Automotive Simulation Models) Gasoline Engine model implements the same approach for engine simulation using maps for performance estimation. Although the mean value engine models provide sufficiently accurate trends, it is in many cases required to have detailed subsystem models to test individual components of the engine. Gamma Technology’s GT-POWER, a powerful 1-D detailed engine simulation commercial tool, is explored to provide detailed engine components. Although GT-POWER has multiple advantages such as modular design, high-accuracy, and user-friendly drag-and-drop approach for component design with definable boundary conditions, it provides limited control design options within itself. Therefore, the integration of detailed GT-POWER engine model with the ASM vehicle model is explored in this project. Model-based development approach was used to model, test, verify and validate the co-simulation and integration of the GT-POWER gasoline engine model into the dSPACE ASM vehicle model. The ASM gasoline engine model specifications were defined and used in GT-POWER modeling to replicate the functionality of ASM engine model using detailed components and models. The integration of the GT-POWER engine model into the ASM vehicle model was accomplished using s-function mapping and wrapper design for signal transition in order to demonstrate co-simulation and validation over the steady state speed and load conditions and finally over an FTP-75 drive cycle. A balance between the model accuracy and execution speed has to be considered according to the testing requirements. The next step to this SIL co-simulation should be similar implementation for dSPACE HIL platforms.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Mechanical Engineering
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APA (6th Edition):
Badgujar, P. P. (2014). INTEGRATION OF GT-POWER ENGINE MODEL WITH DSPACE VEHICLE MODEL FOR CO-SIMULATION AND VALIDATION. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etd-restricted/206
Chicago Manual of Style (16th Edition):
Badgujar, Pankaj Prabhakar. “INTEGRATION OF GT-POWER ENGINE MODEL WITH DSPACE VEHICLE MODEL FOR CO-SIMULATION AND VALIDATION.” 2014. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etd-restricted/206.
MLA Handbook (7th Edition):
Badgujar, Pankaj Prabhakar. “INTEGRATION OF GT-POWER ENGINE MODEL WITH DSPACE VEHICLE MODEL FOR CO-SIMULATION AND VALIDATION.” 2014. Web. 08 Mar 2021.
Vancouver:
Badgujar PP. INTEGRATION OF GT-POWER ENGINE MODEL WITH DSPACE VEHICLE MODEL FOR CO-SIMULATION AND VALIDATION. [Internet] [Masters thesis]. Michigan Technological University; 2014. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etd-restricted/206.
Council of Science Editors:
Badgujar PP. INTEGRATION OF GT-POWER ENGINE MODEL WITH DSPACE VEHICLE MODEL FOR CO-SIMULATION AND VALIDATION. [Masters Thesis]. Michigan Technological University; 2014. Available from: https://digitalcommons.mtu.edu/etd-restricted/206
Michigan Technological University
6.
Poramapojana, Poowanart.
Predictive control of hybrid vehicle powertrain for intelligent energy management.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2012, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etd-restricted/61
► This thesis studies the minimization of the fuel consumption for a Hybrid Electric Vehicle (HEV) using Model Predictive Control (MPC). The presented MPC –…
(more)
▼ This thesis studies the minimization of the fuel consumption for a Hybrid Electric Vehicle (HEV) using Model Predictive Control (MPC). The presented MPC – based controller calculates an optimal sequence of control inputs to a hybrid vehicle using the measured plant outputs, the current dynamic states, a system model, system constraints, and an optimization cost function. The MPC controller is developed using Matlab MPC control toolbox. To evaluate the performance of the presented controller, a power-split hybrid vehicle, 2004 Toyota Prius, is selected. The vehicle uses a planetary gear set to combine three power components, an engine, a motor, and a generator, and transfer energy from these components to the vehicle wheels. The planetary gear model is developed based on the Willis’s formula. The dynamic models of the engine, the motor, and the generator, are derived based on their dynamics at the planetary gear. The MPC controller for HEV energy management is validated in the MATLAB/Simulink environment. Both the step response performance (a 0 – 60 mph step input) and the driving cycle tracking performance are evaluated. Two standard driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET), are used in the evaluation tests. For the UDDS and HWFET driving cycles, the simulation results, the fuel consumption and the battery state of charge, using the MPC controller are compared with the simulation results using the original vehicle model in Autonomie. The MPC approach shows the feasibility to improve vehicle performance and minimize fuel consumption.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Engineering; Mechanical Engineering
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APA (6th Edition):
Poramapojana, P. (2012). Predictive control of hybrid vehicle powertrain for intelligent energy management. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etd-restricted/61
Chicago Manual of Style (16th Edition):
Poramapojana, Poowanart. “Predictive control of hybrid vehicle powertrain for intelligent energy management.” 2012. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etd-restricted/61.
MLA Handbook (7th Edition):
Poramapojana, Poowanart. “Predictive control of hybrid vehicle powertrain for intelligent energy management.” 2012. Web. 08 Mar 2021.
Vancouver:
Poramapojana P. Predictive control of hybrid vehicle powertrain for intelligent energy management. [Internet] [Masters thesis]. Michigan Technological University; 2012. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etd-restricted/61.
Council of Science Editors:
Poramapojana P. Predictive control of hybrid vehicle powertrain for intelligent energy management. [Masters Thesis]. Michigan Technological University; 2012. Available from: https://digitalcommons.mtu.edu/etd-restricted/61
Michigan Technological University
7.
Luo, Wei.
STUDY OF REAL-TIME STOCHASTIC KNOCK DETECTION AND CONTROL FOR SPARK-IGNITION ENGINES.
Degree: PhD, Department of Mechanical Engineering-Engineering Mechanics, 2014, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etd-restricted/286
► The ability to operate a spark-ignition (SI) engine near the knock limit provides a net reduction of engine fuel consumption. This work presents a…
(more)
▼ The ability to operate a spark-ignition (SI) engine near the knock limit provides a net reduction of engine fuel consumption. This work presents a real-time knock control system based on stochastic knock detection (SKD) algorithm. The real-time stochastic knock control (SKC) system is developed in Matlab Simulink, and the SKC software is integrated with the production engine control strategy through ATI's No-Hooks. The SKC system collects the stochastic knock information and estimates the knock level based on the distribution of knock intensities fit to a log-normal distribution. A desired knock level reference table is created under various engine speeds and loads, which allows the SKC to adapt to changing engine operating conditions. For the steady-state engine operation, a fixed-length weighted discrete FIR filter is used to estimate the knock factor (KF), an indicator of knock intensity level. Both offline simulation and engine dynamometer test result show that stochastic knock control with fixed length FIR filter has slow and excessive retard issue when significant knock event happens To enhance the knock control response, an integrated feed-forward and feedback knock control strategy is employed. For the heavy knock events, a combination of gain scheduling and a fast retard (FR) is applied based on the detected KF. In addition, a variable length FIR filter is used to reduce the KF estimation time. The performance of the developed knock detection and control system is then evaluated on a V6 3.5L turbocharged engine on a dynamometer test stand.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Control; Detection; Knock; SI Engine; Stochastic; Mechanical Engineering
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APA (6th Edition):
Luo, W. (2014). STUDY OF REAL-TIME STOCHASTIC KNOCK DETECTION AND CONTROL FOR SPARK-IGNITION ENGINES. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etd-restricted/286
Chicago Manual of Style (16th Edition):
Luo, Wei. “STUDY OF REAL-TIME STOCHASTIC KNOCK DETECTION AND CONTROL FOR SPARK-IGNITION ENGINES.” 2014. Doctoral Dissertation, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etd-restricted/286.
MLA Handbook (7th Edition):
Luo, Wei. “STUDY OF REAL-TIME STOCHASTIC KNOCK DETECTION AND CONTROL FOR SPARK-IGNITION ENGINES.” 2014. Web. 08 Mar 2021.
Vancouver:
Luo W. STUDY OF REAL-TIME STOCHASTIC KNOCK DETECTION AND CONTROL FOR SPARK-IGNITION ENGINES. [Internet] [Doctoral dissertation]. Michigan Technological University; 2014. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etd-restricted/286.
Council of Science Editors:
Luo W. STUDY OF REAL-TIME STOCHASTIC KNOCK DETECTION AND CONTROL FOR SPARK-IGNITION ENGINES. [Doctoral Dissertation]. Michigan Technological University; 2014. Available from: https://digitalcommons.mtu.edu/etd-restricted/286
Michigan Technological University
8.
Feng, Lei.
INCORPORATING DRIVER’S BEHAVIOR INTO PREDICTIVE POWERTRAIN ENERGY MANAGEMENT FOR A POWER-SPLIT HYBRID ELECTRIC VEHICLE.
Degree: PhD, Department of Mechanical Engineering-Engineering Mechanics, 2016, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/83
► The goal of this series of research is to advance hybrid electric vehicle (HEV) energy management by incorporating driver’s driving behavior and driving cycle…
(more)
▼ The goal of this series of research is to advance hybrid electric vehicle (HEV) energy management by incorporating driver’s driving behavior and driving cycle information. To reduce HEV fuel consumption, the objectives of this research are divided into the following three parts.
The first part of the research investigates the impact of driver’s behavior on the overall fuel efficiency of a hybrid electric vehicle and the energy efficiency of individual powertrain components under various driving cycles. Between the sticker number fuel economy and actual fuel economy, it is well known that a noticeable difference occur when a driver drives aggressively. To simulate aggressive driving, the input driving cycles are scaled up from the baseline driving cycles to higher levels of acceleration/deceleration. The simulation study is conducted using Autonomie®, a powertrain simulation and analysis software. The performance of the major powertrain components is analyzed when the HEV is operated at different level of aggressiveness.
In the second part of the study, the vehicle driving cycles affect the performance of a hybrid vehicle control strategy and the corresponding overall performance of the vehicle. By identifying the driving cycles of a vehicle, the HEV supervisor controller system will be dynamically adapt the control strategy to the changes of vehicle driving patterns. With pattern recognition method, a driving cycle is represented by feature vectors that are formed by a set of parameters to which the driving cycle is sensitive. To establish reference driving cycle database, the representative feature vectors of four federal driving cycles are generated using feature extraction method. The performance of the presented adaptive control strategy based on driving pattern recognition is evaluated using Autonomie.
In the last part of the study, a predictive control method is developed and investigated for hybrid electric vehicle energy management in effort to improve HEV fuel economy. Model Predictive Control (MPC), a predictive control method, is applied to improve the fuel economy of a power-split HEV. The study compares the performance of MPC method and conventional rule-base control method. A parametric study is conducted to understand the influence of 3 weighting factors in MPC formulation on the performance of the vehicles.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Model predictive control; hybrid electric vehicle; powertrain energy management; pattern recognition; SOC estimation; driver behavior; Acoustics, Dynamics, and Controls
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APA (6th Edition):
Feng, L. (2016). INCORPORATING DRIVER’S BEHAVIOR INTO PREDICTIVE POWERTRAIN ENERGY MANAGEMENT FOR A POWER-SPLIT HYBRID ELECTRIC VEHICLE. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/83
Chicago Manual of Style (16th Edition):
Feng, Lei. “INCORPORATING DRIVER’S BEHAVIOR INTO PREDICTIVE POWERTRAIN ENERGY MANAGEMENT FOR A POWER-SPLIT HYBRID ELECTRIC VEHICLE.” 2016. Doctoral Dissertation, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/83.
MLA Handbook (7th Edition):
Feng, Lei. “INCORPORATING DRIVER’S BEHAVIOR INTO PREDICTIVE POWERTRAIN ENERGY MANAGEMENT FOR A POWER-SPLIT HYBRID ELECTRIC VEHICLE.” 2016. Web. 08 Mar 2021.
Vancouver:
Feng L. INCORPORATING DRIVER’S BEHAVIOR INTO PREDICTIVE POWERTRAIN ENERGY MANAGEMENT FOR A POWER-SPLIT HYBRID ELECTRIC VEHICLE. [Internet] [Doctoral dissertation]. Michigan Technological University; 2016. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/83.
Council of Science Editors:
Feng L. INCORPORATING DRIVER’S BEHAVIOR INTO PREDICTIVE POWERTRAIN ENERGY MANAGEMENT FOR A POWER-SPLIT HYBRID ELECTRIC VEHICLE. [Doctoral Dissertation]. Michigan Technological University; 2016. Available from: https://digitalcommons.mtu.edu/etdr/83
Michigan Technological University
9.
Yin, Qinyuan.
LITHIUM-ION BATTERY CELL PERFORMANCE STUDY WITH BATTERY IN THE LOOP TESTING AND EQUIVALENT CIRCUIT MODEL.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2016, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/307
► As the rapid development of new energy vehicle technologies and the need for better battery performance and reliable batteries management system (BMS), research on…
(more)
▼ As the rapid development of new energy vehicle technologies and the need for better battery performance and reliable batteries management system (BMS), research on vehicle battery has become more and more important. Modeling and simulation of battery performance are commonly used in battery research. To model a battery accurately, obtaining battery characteristic parameters through real-time testing is critically needed.
This MS report studies the NCR18650B Lithium-ion battery performance with Real-Time BATTERY-IN-THE-LOOP testing. A custom battery test board is designed to hold the battery cell under the test and perform data acquisition. An equivalent circuit Lithium-ion battery model is developed using the battery parameters obtained from the real-time testing. The battery model is simulated and the simulation results are compared with the real-time testing results in the conclusion section.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Battery HIL Simulation; Automotive Engineering
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APA (6th Edition):
Yin, Q. (2016). LITHIUM-ION BATTERY CELL PERFORMANCE STUDY WITH BATTERY IN THE LOOP TESTING AND EQUIVALENT CIRCUIT MODEL. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/307
Chicago Manual of Style (16th Edition):
Yin, Qinyuan. “LITHIUM-ION BATTERY CELL PERFORMANCE STUDY WITH BATTERY IN THE LOOP TESTING AND EQUIVALENT CIRCUIT MODEL.” 2016. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/307.
MLA Handbook (7th Edition):
Yin, Qinyuan. “LITHIUM-ION BATTERY CELL PERFORMANCE STUDY WITH BATTERY IN THE LOOP TESTING AND EQUIVALENT CIRCUIT MODEL.” 2016. Web. 08 Mar 2021.
Vancouver:
Yin Q. LITHIUM-ION BATTERY CELL PERFORMANCE STUDY WITH BATTERY IN THE LOOP TESTING AND EQUIVALENT CIRCUIT MODEL. [Internet] [Masters thesis]. Michigan Technological University; 2016. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/307.
Council of Science Editors:
Yin Q. LITHIUM-ION BATTERY CELL PERFORMANCE STUDY WITH BATTERY IN THE LOOP TESTING AND EQUIVALENT CIRCUIT MODEL. [Masters Thesis]. Michigan Technological University; 2016. Available from: https://digitalcommons.mtu.edu/etdr/307
Michigan Technological University
10.
Bhat, Pradeep.
STUDY OF OPTIMAL VELOCITY TRAJECTORY FOR REAL-TIME PREDICTIVE CONTROL OF A MULTI-MODE PHEV.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2019, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/866
► This report presents the development of two algorithms that uses available velocity bounds and powertrain information to generate an optimal velocity trajectory over a…
(more)
▼ This report presents the development of two algorithms that uses available velocity bounds and powertrain information to generate an optimal velocity trajectory over a prediction horizon for a multi-mode plug-in hybrid electric vehicle. The objective of first optimization problem is to reduce dynamic losses, and required tractive force, while completing trip distance with a given travel time. Sequential Quadratic Programming (SQP) method is employed for this nonlinearly constrained optimization problem. This development illustrates the benefits of optimal velocity trajectories. Validation is completed using 2
nd generation GM Volt model in Autonomie. The objective of second optimization problem is to generate velocity trajectory within a prediction horizon to reduce tractive force while monitoring the overall travel time required for the trip. The defined optimization problem is solved incorporating distance-based traffic dynamics and road conditions as compared to time-based optimization in first method. The developed algorithm reduces energy consumption by avoiding wasteful driving maneuvers and utilizes the opportunities for regeneration. The algorithm is implemented by ACADO toolkit for real-time execution. The algorithm is validated using 2
nd generation Volt powertrain model developed at MTU.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Optimal Velocity Prediction; Optimal Control; Optimization; Intelligent Transportation Systems; Connected And Automated Vehicles; Acoustics, Dynamics, and Controls; Energy Systems
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APA (6th Edition):
Bhat, P. (2019). STUDY OF OPTIMAL VELOCITY TRAJECTORY FOR REAL-TIME PREDICTIVE CONTROL OF A MULTI-MODE PHEV. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/866
Chicago Manual of Style (16th Edition):
Bhat, Pradeep. “STUDY OF OPTIMAL VELOCITY TRAJECTORY FOR REAL-TIME PREDICTIVE CONTROL OF A MULTI-MODE PHEV.” 2019. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/866.
MLA Handbook (7th Edition):
Bhat, Pradeep. “STUDY OF OPTIMAL VELOCITY TRAJECTORY FOR REAL-TIME PREDICTIVE CONTROL OF A MULTI-MODE PHEV.” 2019. Web. 08 Mar 2021.
Vancouver:
Bhat P. STUDY OF OPTIMAL VELOCITY TRAJECTORY FOR REAL-TIME PREDICTIVE CONTROL OF A MULTI-MODE PHEV. [Internet] [Masters thesis]. Michigan Technological University; 2019. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/866.
Council of Science Editors:
Bhat P. STUDY OF OPTIMAL VELOCITY TRAJECTORY FOR REAL-TIME PREDICTIVE CONTROL OF A MULTI-MODE PHEV. [Masters Thesis]. Michigan Technological University; 2019. Available from: https://digitalcommons.mtu.edu/etdr/866
Michigan Technological University
11.
Aggarwal, Piyush.
DEVELOPMENT OF AN OPEN SOURCE OPENADR-BASED DEMAND RESPONSE SYSTEM FOR THE CHARGING CONTROL OF PLUG-IN ELECTRIC VEHICLES.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2016, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/252
► The concept of zero emission vehicles in terms of plug-in electric vehicles have raised questions about existing electrical distribution grid stability. Smart grid is…
(more)
▼ The concept of zero emission vehicles in terms of plug-in electric vehicles have raised questions about existing electrical distribution grid stability. Smart grid is an evolving branch of engineering with various methodologies which are considered to be a suitable solution to attain stable and sustainable electrical grid. This research studies the development and implementation of one such smart grid methodology named ‘Automated Demand Response’ to control load congestion on electrical grid. An open source and easy to implement Demand Response (DR) system based on OpenADR communication specification is developed. Node-Red is used as a development platform because of its open source nature as well as its ease of use for customized internet-based embedded system development. The developed system is used for electric vehicle charging rate control by using real-time pricing data from ComEd’s electrical utility web server in Chicago. The system is validated for functioning of electric vehicle charging control as well as the implemented services of OpenADR specification. The validation result shows that the implemented services are working as per specification and vehicle charging rate is in co-ordination with real-time electricity prices to reach desired battery state of charge (SOC).
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: OpenADR; Node-RED; Smart Grid; Internet of Things; EV Charging; Acoustics, Dynamics, and Controls; Automotive Engineering; Controls and Control Theory; Digital Communications and Networking; Power and Energy
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APA (6th Edition):
Aggarwal, P. (2016). DEVELOPMENT OF AN OPEN SOURCE OPENADR-BASED DEMAND RESPONSE SYSTEM FOR THE CHARGING CONTROL OF PLUG-IN ELECTRIC VEHICLES. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/252
Chicago Manual of Style (16th Edition):
Aggarwal, Piyush. “DEVELOPMENT OF AN OPEN SOURCE OPENADR-BASED DEMAND RESPONSE SYSTEM FOR THE CHARGING CONTROL OF PLUG-IN ELECTRIC VEHICLES.” 2016. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/252.
MLA Handbook (7th Edition):
Aggarwal, Piyush. “DEVELOPMENT OF AN OPEN SOURCE OPENADR-BASED DEMAND RESPONSE SYSTEM FOR THE CHARGING CONTROL OF PLUG-IN ELECTRIC VEHICLES.” 2016. Web. 08 Mar 2021.
Vancouver:
Aggarwal P. DEVELOPMENT OF AN OPEN SOURCE OPENADR-BASED DEMAND RESPONSE SYSTEM FOR THE CHARGING CONTROL OF PLUG-IN ELECTRIC VEHICLES. [Internet] [Masters thesis]. Michigan Technological University; 2016. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/252.
Council of Science Editors:
Aggarwal P. DEVELOPMENT OF AN OPEN SOURCE OPENADR-BASED DEMAND RESPONSE SYSTEM FOR THE CHARGING CONTROL OF PLUG-IN ELECTRIC VEHICLES. [Masters Thesis]. Michigan Technological University; 2016. Available from: https://digitalcommons.mtu.edu/etdr/252
Michigan Technological University
12.
Cao, Chong.
STUDY OF ELECTRIC VEHICLE CHARGING STRATEGIES AND ENERGY MANAGEMENT IN POWER DISTRIBUTION SYSTEMS.
Degree: PhD, Department of Electrical and Computer Engineering, 2019, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/867
► The goal of this research is to study the control approaches of the electric vehicle – grid integration systems in a power distribution grid…
(more)
▼ The goal of this research is to study the control approaches of the electric vehicle – grid integration systems in a power distribution grid to benefit the electric vehicle charging customers and the grid operation. To find the balance of both aspects, a series of modeling and simulation have been conducted to validate the effectiveness of the developed control approaches. The impact of the plug-in electric vehicle (PEV) charging activity on the distribution power grid is analyzed. The PEV charging behavior model is established through the statistical analysis of the National Highway Travel Survey. This charging behavior model is used to generate the PEV charging load profiles for the investigation of the PEV charging impacts on the local distribution transformer aging and the network voltage deviation. The simulation results indicate that the high penetration rate of PEV charging potentially leads to serious distribution transformer aging and voltage problems to the end users in the remote side of a distribution line. To mitigate the PEV charging impacts, scheduling methods are investigated based on the existing utility programs, such as the Time of Use and Direct Load Control, and optimization techniques. The charging scheduling shifts the PEV charging load to the grid off-peak period to flatten the load profile. Therefore, it mitigates the PEV charging resulted overloading, transformer aging, and voltage deviation problems. To improve the customer acceptance of PEV charging control, the PEV charging in a distribution grid form a competition game, which allows individual PEV charging xiii customers to pursue charging cost minimization while various grid and customer constraints are met. Due to that the individual objectives and constraints are related to the PEVs charging strategy selection, the charging game is considered as a generalized Nash Equilibrium problem (GNEP). The Nikaido-Isoda reformulation function is used to solve the GNEP. The obtained PEV charging strategies lead to the lowest PEV charging cost and guarantee the grid operation safety and customer requirement. The obtained solution strategies of this problem are regarded as the Nash Equilibriums of the game. To explore the possibility of providing grid services by using the PEV smart charging method, a study of distribution grid level vehicle - grid integration control with voltage regulation is conducted. In this study, the PEV charging control is designed at both Microgrid-level and distribution-level. The Microgrid controllers aim to optimally allocate the limited power to the charging PEVs. When a distribution grid voltage violation occurs, a distributed multi-Microgrids negotiation is triggered to find the best power curtailment values for individual Microgrids, which satisfy the voltage recovery requirement and have a minimal impact on the grid operation. The last part of the dissertation presents the effort of developing a real-time VGI simulation platform at distribution grid level in a real-time power system simulator, OPAL-RT. The…
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Electric Vehicle-Grid Integration; Plug-in Electric Vehicle Charging; Distribution Grid; Microgrid; Controls and Control Theory; Power and Energy
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MLA ·
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APA (6th Edition):
Cao, C. (2019). STUDY OF ELECTRIC VEHICLE CHARGING STRATEGIES AND ENERGY MANAGEMENT IN POWER DISTRIBUTION SYSTEMS. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/867
Chicago Manual of Style (16th Edition):
Cao, Chong. “STUDY OF ELECTRIC VEHICLE CHARGING STRATEGIES AND ENERGY MANAGEMENT IN POWER DISTRIBUTION SYSTEMS.” 2019. Doctoral Dissertation, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/867.
MLA Handbook (7th Edition):
Cao, Chong. “STUDY OF ELECTRIC VEHICLE CHARGING STRATEGIES AND ENERGY MANAGEMENT IN POWER DISTRIBUTION SYSTEMS.” 2019. Web. 08 Mar 2021.
Vancouver:
Cao C. STUDY OF ELECTRIC VEHICLE CHARGING STRATEGIES AND ENERGY MANAGEMENT IN POWER DISTRIBUTION SYSTEMS. [Internet] [Doctoral dissertation]. Michigan Technological University; 2019. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/867.
Council of Science Editors:
Cao C. STUDY OF ELECTRIC VEHICLE CHARGING STRATEGIES AND ENERGY MANAGEMENT IN POWER DISTRIBUTION SYSTEMS. [Doctoral Dissertation]. Michigan Technological University; 2019. Available from: https://digitalcommons.mtu.edu/etdr/867
Michigan Technological University
13.
Barik, Biswajit.
Designing a Real-time Velocity Predictor for Powertrain Optimization of Connected and Automated Vehicles.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2017, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/408
► Connected and Automated Vehicles (CAVs) coupled with Intelligent Transportation Systems (ITS) have been able to impact significantly to the transportation and automotive sector by…
(more)
▼ Connected and Automated Vehicles (CAVs) coupled with Intelligent Transportation Systems (ITS) have been able to impact significantly to the transportation and automotive sector by improving traffic mobility, increasing fuel efficiency and reducing emissions. The research intends to develop optimization algorithms by utilizing the velocity bounds provided by a traffic simulation program and generate an optimal velocity trajectory to reduce power-losses and improve drivability in vehicles.
The developed optimal velocity trajectory algorithms are modified for the applications of Eco –Approach and Departure (Eco A/D) at signalized intersections and Co-operative Adaptive Cruise Control (CACC). The fuel consumption during Eco-A/D is minimized by reducing idling times at traffic intersections. The CACC algorithm allows vehicles in a platoon to maintain a closer inter-vehicular gap and improve the efficiency of the platoon.
Lastly, the simulation results generated by test cases are presented and future work is discussed to translate the simulation-based results to real-world improvement.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Optimal Velocity Predictor; Eco Approach and Departure; Co-operative Adaptive Cruise Control; Optimization; Simulation; Calibration; Autonomie; Automotive Engineering
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APA (6th Edition):
Barik, B. (2017). Designing a Real-time Velocity Predictor for Powertrain Optimization of Connected and Automated Vehicles. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/408
Chicago Manual of Style (16th Edition):
Barik, Biswajit. “Designing a Real-time Velocity Predictor for Powertrain Optimization of Connected and Automated Vehicles.” 2017. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/408.
MLA Handbook (7th Edition):
Barik, Biswajit. “Designing a Real-time Velocity Predictor for Powertrain Optimization of Connected and Automated Vehicles.” 2017. Web. 08 Mar 2021.
Vancouver:
Barik B. Designing a Real-time Velocity Predictor for Powertrain Optimization of Connected and Automated Vehicles. [Internet] [Masters thesis]. Michigan Technological University; 2017. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/408.
Council of Science Editors:
Barik B. Designing a Real-time Velocity Predictor for Powertrain Optimization of Connected and Automated Vehicles. [Masters Thesis]. Michigan Technological University; 2017. Available from: https://digitalcommons.mtu.edu/etdr/408
Michigan Technological University
14.
Devaragudi, Sai Rajeev.
MPC-BASED AUTONOMOUS DRIVING CONTROL WITH LOCALIZED PATH PLANNING FOR OBSTACLE AVOIDANCE AND NAVIGATING SIGNALIZED INTERSECTIONS.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2019, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/790
► Connected and autonomous vehicles are becoming the major focus of research for the industry and academia in the automotive field. Many companies and research…
(more)
▼ Connected and autonomous vehicles are becoming the major focus of research for the industry and academia in the automotive field. Many companies and research groups have demonstrated the advantages and the requirement of such technology to improve the energy efficiency of vehicles, decrease the number of crash and road accidents, and control emissions.
This research delves into improving the autonomy of self-driving vehicles by implementing localized path planning algorithms to introduce motion control for obstacle avoidance during uncertainties. Lateral path planning is implemented using the A* algorithm combined with piecewise Bezier curve generation which provides an optimum trajectory reference to avoid a collision. Model Predictive Control (MPC) is used to implement longitudinal and lateral control of the vehicle. The data from vehicle-to-everything (V2X) communication infrastructure is used to navigate through multiple signalized intersections. Furthermore, a new method of developing Advanced Driver Assistance Systems (ADAS) algorithms and vehicle controllers using Model-In-the-Loop (MIL) testing is explored with the use of PreScan®. With PreScan®, various traffic scenarios are modeled and the sensor data are simulated by using physics-based sensor models, which are fed to the controller for data processing and motion planning. Obstacle detection and collision avoidance are demonstrated using the presented MPC controller. The results of the proposed controller and the scope of the future work conclude the research.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Autonomous Vehicles; Path Planning; Model Predictive Control; Self Driving; PreScan; MIL/SIL testing; Acoustics, Dynamics, and Controls; Navigation, Guidance, Control, and Dynamics
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APA (6th Edition):
Devaragudi, S. R. (2019). MPC-BASED AUTONOMOUS DRIVING CONTROL WITH LOCALIZED PATH PLANNING FOR OBSTACLE AVOIDANCE AND NAVIGATING SIGNALIZED INTERSECTIONS. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/790
Chicago Manual of Style (16th Edition):
Devaragudi, Sai Rajeev. “MPC-BASED AUTONOMOUS DRIVING CONTROL WITH LOCALIZED PATH PLANNING FOR OBSTACLE AVOIDANCE AND NAVIGATING SIGNALIZED INTERSECTIONS.” 2019. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/790.
MLA Handbook (7th Edition):
Devaragudi, Sai Rajeev. “MPC-BASED AUTONOMOUS DRIVING CONTROL WITH LOCALIZED PATH PLANNING FOR OBSTACLE AVOIDANCE AND NAVIGATING SIGNALIZED INTERSECTIONS.” 2019. Web. 08 Mar 2021.
Vancouver:
Devaragudi SR. MPC-BASED AUTONOMOUS DRIVING CONTROL WITH LOCALIZED PATH PLANNING FOR OBSTACLE AVOIDANCE AND NAVIGATING SIGNALIZED INTERSECTIONS. [Internet] [Masters thesis]. Michigan Technological University; 2019. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/790.
Council of Science Editors:
Devaragudi SR. MPC-BASED AUTONOMOUS DRIVING CONTROL WITH LOCALIZED PATH PLANNING FOR OBSTACLE AVOIDANCE AND NAVIGATING SIGNALIZED INTERSECTIONS. [Masters Thesis]. Michigan Technological University; 2019. Available from: https://digitalcommons.mtu.edu/etdr/790
Michigan Technological University
15.
Cheng, Ming.
STUDY OF BATTERY HEALTH CONSCIOUS POWERTRAIN ENERGY MANAGEMENT STRATEGIES FOR HYBRID ELECTRIC VEHICLES.
Degree: PhD, Department of Mechanical Engineering-Engineering Mechanics, 2017, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/325
► The goal of this research is to study the battery aging pattern for the application of hybrid electric vehicles (HEV) and advanced control algorithm…
(more)
▼ The goal of this research is to study the battery aging pattern for the application of hybrid electric vehicles (HEV) and advanced control algorithm to improve the performance of HEV energy management controller by maximizing fuel efficiency and minimizing battery aging speed at the same time. To achieve the combined goals, the tasks of this research can be laid out as follows.
The first part studies the HEV model provided by Autonomie software and the electrochemical battery model to be built and integrated with the whole vehicle model. The battery model integrated is an averaged single particle model with the battery thermal aging features added. The battery aging will be quantified as the increasing of SEI layer and decreasing of battery capacity. The battery model was able to simulate the aging performance under different temperature, charge current, SOC and other operational conditions. The simulation results of the vehicle following certain driving cycles and the simulation results of battery voltage output are presented.
The second part investigates the feasibility of the entire system to be running in a real-time hardware-in-the-loop system. The vehicle model together with the electrochemical battery model is built and loaded to the dSPACE simulator. The hybrid controller model is built and loaded to the dSPACE MicroAutoBox. The hybrid controller and dSPACE simulator communicate in real-time with vehicle components information coming from plant model and the control signals coming from the MicroAutoBox. The vehicle model together with the battery model is able to be running in Simulator with the battery model simulated correctly and providing battery aging features in real-time.
The third part of the research looks into the application of nonlinear model predictive control (NMPC) in the hybrid controller. To meet the goal of minimizing fuel consumption and battery aging speed, the nonlinear model predictive control without concern of battery aging is first studied. The predictive model is built to predict the dynamic performance of battery pack, the E-motors, the engine and the vehicle powertrain key part – planetary gear set. A cost function is built to provide the best control performance for our case. The performance of the NMPC is compared with the rule-based controller. And the performance of NMPC with different weighting factors is compared and analyzed.
Following the previous part, the NMPC with the concern of battery aging is also studied and simulated using the vehicle and battery model built and integrated into the first part. By changing the cost function of the NMPC, the battery aging performance is greatly improved compared with that of the previous part. The studied NMPC is able to maintain the fuel economy at similar or even better level compared with the NMPC without battery aging concern.
The last part of the research studies the modeling of a single shaft parallel hybrid electric vehicle built from the dSPACE Automotive Simulation Model (ASM) and the…
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Li-ion battery; Nonlinear Model Predictive Control; Battery Aging; Power-Split HEV; Electro-Mechanical Systems; Energy Systems
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APA (6th Edition):
Cheng, M. (2017). STUDY OF BATTERY HEALTH CONSCIOUS POWERTRAIN ENERGY MANAGEMENT STRATEGIES FOR HYBRID ELECTRIC VEHICLES. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/325
Chicago Manual of Style (16th Edition):
Cheng, Ming. “STUDY OF BATTERY HEALTH CONSCIOUS POWERTRAIN ENERGY MANAGEMENT STRATEGIES FOR HYBRID ELECTRIC VEHICLES.” 2017. Doctoral Dissertation, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/325.
MLA Handbook (7th Edition):
Cheng, Ming. “STUDY OF BATTERY HEALTH CONSCIOUS POWERTRAIN ENERGY MANAGEMENT STRATEGIES FOR HYBRID ELECTRIC VEHICLES.” 2017. Web. 08 Mar 2021.
Vancouver:
Cheng M. STUDY OF BATTERY HEALTH CONSCIOUS POWERTRAIN ENERGY MANAGEMENT STRATEGIES FOR HYBRID ELECTRIC VEHICLES. [Internet] [Doctoral dissertation]. Michigan Technological University; 2017. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/325.
Council of Science Editors:
Cheng M. STUDY OF BATTERY HEALTH CONSCIOUS POWERTRAIN ENERGY MANAGEMENT STRATEGIES FOR HYBRID ELECTRIC VEHICLES. [Doctoral Dissertation]. Michigan Technological University; 2017. Available from: https://digitalcommons.mtu.edu/etdr/325
Michigan Technological University
16.
Liu, Wenjia.
DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL.
Degree: PhD, Department of Electrical and Computer Engineering, 2012, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etds/614
► To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can…
(more)
▼ To analyze the characteristics and predict the dynamic
behaviors of complex systems over time, comprehensive
research to enable the development of systems that can
intelligently adapt to the evolving conditions and infer
new knowledge with algorithms that are not predesigned
is crucially needed. This dissertation research studies
the integration of the techniques and methodologies
resulted from the fields of pattern recognition,
intelligent agents, artificial immune systems, and
distributed computing platforms, to create technologies
that can more accurately describe and control the dynamics
of real-world complex systems. The need for such
technologies is emerging in manufacturing, transportation,
hazard mitigation, weather and climate prediction,
homeland security, and emergency response.
Motivated by the ability of mobile agents to dynamically
incorporate additional computational and control algorithms
into executing applications, mobile agent technology is
employed in this research for the adaptive sensing and
monitoring in a wireless sensor network. Mobile agents
are software components that can travel from one
computing platform to another in a network and carry
programs and data states that are needed for performing
the assigned tasks. To support the generation, migration,
communication, and management of mobile monitoring agents,
an embeddable mobile agent system (Mobile-C) is integrated
with sensor nodes. Mobile monitoring agents visit distributed
sensor nodes, read real-time sensor data, and perform
anomaly detection using the equipped pattern recognition
algorithms. The optimal control of agents is achieved by
mimicking the adaptive immune response and the application
of multi-objective optimization algorithms. The mobile agent
approach provides potential to reduce the communication load
and energy consumption in monitoring networks.
The major research work of this dissertation project
includes: (1) studying effective feature extraction methods
for time series measurement data; (2) investigating the
impact of the feature extraction methods and dissimilarity
measures on the performance of pattern recognition;
(3) researching the effects of environmental factors on the
performance of pattern recognition; (4) integrating an
embeddable mobile agent system with wireless sensor nodes;
(5) optimizing agent generation and distribution using
artificial immune system concept and multi-objective algorithms;
(6) applying mobile agent technology and pattern recognition
algorithms for adaptive structural health monitoring and
driving cycle pattern recognition; (7) developing a web-based
monitoring network to enable the visualization and analysis
of real-time sensor data remotely. Techniques and algorithms
developed in this dissertation project will contribute to
research advances in networked distributed systems operating
under changing environments.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Electrical and Computer Engineering; Engineering
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APA (6th Edition):
Liu, W. (2012). DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etds/614
Chicago Manual of Style (16th Edition):
Liu, Wenjia. “DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL.” 2012. Doctoral Dissertation, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etds/614.
MLA Handbook (7th Edition):
Liu, Wenjia. “DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL.” 2012. Web. 08 Mar 2021.
Vancouver:
Liu W. DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL. [Internet] [Doctoral dissertation]. Michigan Technological University; 2012. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etds/614.
Council of Science Editors:
Liu W. DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL. [Doctoral Dissertation]. Michigan Technological University; 2012. Available from: https://digitalcommons.mtu.edu/etds/614
Michigan Technological University
17.
Wu, Hao.
STUDY OF SPARK IGNITION ENGINE COMBUSTION MODEL FOR THE ANALYSIS OF CYCLIC VARIATION AND COMBUSTION STABILITY AT LEAN OPERATING CONDITIONS.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2013, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etds/662
► A fundamental combustion model for spark-ignition engine is studied in this report. The model is implemented in SIMULINK to simulate engine outputs (mass fraction…
(more)
▼ A fundamental combustion model for spark-ignition engine is studied in this report. The model is implemented in SIMULINK to simulate engine outputs (mass fraction burn and in-cylinder pressure) under various engine operation conditions. The combustion model includes a turbulent propagation and eddy burning processes based on literature [1]. The turbulence propagation and eddy burning processes are simulated by zero-dimensional method and the flame is assumed as sphere. To predict pressure, temperature and other in-cylinder variables, a two-zone thermodynamic model is used. The predicted results of this model match well with the engine test data under various engine speeds, loads, spark ignition timings and air fuel mass ratios. The developed model is used to study cyclic variation and combustion stability at lean (or diluted) combustion conditions. Several variation sources are introduced into the combustion model to simulate engine performance observed in experimental data. The relations between combustion stability and the introduced variation amount are analyzed at various lean combustion levels.
Advisors/Committee Members: Bo Chen.
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APA (6th Edition):
Wu, H. (2013). STUDY OF SPARK IGNITION ENGINE COMBUSTION MODEL FOR THE ANALYSIS OF CYCLIC VARIATION AND COMBUSTION STABILITY AT LEAN OPERATING CONDITIONS. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etds/662
Chicago Manual of Style (16th Edition):
Wu, Hao. “STUDY OF SPARK IGNITION ENGINE COMBUSTION MODEL FOR THE ANALYSIS OF CYCLIC VARIATION AND COMBUSTION STABILITY AT LEAN OPERATING CONDITIONS.” 2013. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etds/662.
MLA Handbook (7th Edition):
Wu, Hao. “STUDY OF SPARK IGNITION ENGINE COMBUSTION MODEL FOR THE ANALYSIS OF CYCLIC VARIATION AND COMBUSTION STABILITY AT LEAN OPERATING CONDITIONS.” 2013. Web. 08 Mar 2021.
Vancouver:
Wu H. STUDY OF SPARK IGNITION ENGINE COMBUSTION MODEL FOR THE ANALYSIS OF CYCLIC VARIATION AND COMBUSTION STABILITY AT LEAN OPERATING CONDITIONS. [Internet] [Masters thesis]. Michigan Technological University; 2013. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etds/662.
Council of Science Editors:
Wu H. STUDY OF SPARK IGNITION ENGINE COMBUSTION MODEL FOR THE ANALYSIS OF CYCLIC VARIATION AND COMBUSTION STABILITY AT LEAN OPERATING CONDITIONS. [Masters Thesis]. Michigan Technological University; 2013. Available from: https://digitalcommons.mtu.edu/etds/662
Michigan Technological University
18.
Oncken, Joseph.
REAL-TIME PREDICTIVE CONTROL OF CONNECTED VEHICLE POWERTRAINS FOR IMPROVED ENERGY EFFICIENCY.
Degree: PhD, Department of Mechanical Engineering-Engineering Mechanics, 2020, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/1128
► The continued push for the reduction of energy consumption across the automotive vehicle fleet has led to widespread adoption of hybrid and plug-in hybrid…
(more)
▼ The continued push for the reduction of energy consumption across the automotive vehicle fleet has led to widespread adoption of hybrid and plug-in hybrid electric vehicles (PHEV) by auto manufacturers. In addition, connected and automated vehicle (CAV) technologies have seen rapid development in recent years and bring with them the potential to significantly impact vehicle energy consumption. This dissertation studies predictive control methods for PHEV powertrains that are enabled by CAV technologies with the goal of reducing vehicle energy consumption.
First, a real-time predictive powertrain controller for PHEV energy management is developed. This controller utilizes predictions of future vehicle velocity and power demand in order to optimize powersplit decisions of the vehicle. This predictive powertrain controller utilizes nonlinear model predictive control (NMPC) to perform this optimization while being cognizant of future vehicle behavior.
Second, the developed NMPC powertrain controller is thoroughly evaluated both in simulation and real-time testing. The controller is assessed over a large number of standardized and real-world drive cycles in simulation in order to properly quantify the energy savings benefits of the controller. In addition, the NMPC powertrain controller is deployed onto a real-time rapid prototyping embedded controller installed in a test vehicle. Using this real-time testing setup, the developed NMPC powertrain controller is evaluated using on-road testing for both energy savings performance and real-time performance.
Third, a real-time integrated predictive powertrain controller (IPPC) for a multi-mode PHEV is presented. Utilizing predictions of future vehicle behavior, an optimal mode path plan is computed in order to determine a mode command best suited to the future conditions. In addition, this optimal mode path planning controller is integrated with the NMPC powertrain controller to create a real-time integrated predictive powertrain controller that is capable of full supervisory control for a multi-mode PHEV.
Fourth, the IPPC is evaluated in simulation testing across a range of standard and real-world drive cycles in order to quantify the energy savings of the controller. This analysis is comprised of the combined benefit of the NMPC powertrain controller and the optimal mode path planning controller. The IPPC is deployed onto a rapid prototyping embedded controller for real-time evaluation. Using the real-time implementation of the IPPC, on-road testing was performed to assess both energy benefits and real-time performance of the IPPC.
Finally, as the controllers developed in this research were evaluated for a single vehicle platform, the applicability of these controllers to other platforms is discussed. Multiple cases are discussed on how both the NMPC powertrain controller and the optimal mode path planning controller can be applied to other vehicle platforms in order to broaden the scope of this research.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Hybrid Electric Vehicles; Connected Vehicles; Optimal Control; Model Predictive Control; Acoustics, Dynamics, and Controls; Automotive Engineering; Controls and Control Theory; Electro-Mechanical Systems; Energy Systems
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APA (6th Edition):
Oncken, J. (2020). REAL-TIME PREDICTIVE CONTROL OF CONNECTED VEHICLE POWERTRAINS FOR IMPROVED ENERGY EFFICIENCY. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/1128
Chicago Manual of Style (16th Edition):
Oncken, Joseph. “REAL-TIME PREDICTIVE CONTROL OF CONNECTED VEHICLE POWERTRAINS FOR IMPROVED ENERGY EFFICIENCY.” 2020. Doctoral Dissertation, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/1128.
MLA Handbook (7th Edition):
Oncken, Joseph. “REAL-TIME PREDICTIVE CONTROL OF CONNECTED VEHICLE POWERTRAINS FOR IMPROVED ENERGY EFFICIENCY.” 2020. Web. 08 Mar 2021.
Vancouver:
Oncken J. REAL-TIME PREDICTIVE CONTROL OF CONNECTED VEHICLE POWERTRAINS FOR IMPROVED ENERGY EFFICIENCY. [Internet] [Doctoral dissertation]. Michigan Technological University; 2020. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/1128.
Council of Science Editors:
Oncken J. REAL-TIME PREDICTIVE CONTROL OF CONNECTED VEHICLE POWERTRAINS FOR IMPROVED ENERGY EFFICIENCY. [Doctoral Dissertation]. Michigan Technological University; 2020. Available from: https://digitalcommons.mtu.edu/etdr/1128
Michigan Technological University
19.
Sachdeva, Kovid.
Development of Optimal Operating Point Maps and Mode Shift Strategy for Chevrolet Volt Gen II Plug-In Hybrid Electric Vehicle.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2018, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/619
► This work discusses the architecture of the second generation Chevrolet Volt as well as its components. It presents the development of offline optimal operating…
(more)
▼ This work discusses the architecture of the second generation Chevrolet Volt as well as its components. It presents the development of offline optimal operating point maps for all the operating modes of the vehicle. It discusses the development of a novel term for defining the efficiency of the hybrid modes which was used as the cost function for the optimization. These maps were then used to create the best mode map for the hybrid modes and compared with the one from General Motors in one of their publications.
It also discusses the development of a real-time control strategy for mode selection if the predicted velocity for the next few seconds is known to the controller. The algorithm uses the OOP maps for simplifying the model predictive control problem and converting it into the best pathfinding problem. With the new mode selection algorithm, the results show that fuel consumption reductions are possible in both highway and urban drive cycles.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: HEV; mode selection; multi-mode; MPC; Acoustics, Dynamics, and Controls; Automotive Engineering
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APA (6th Edition):
Sachdeva, K. (2018). Development of Optimal Operating Point Maps and Mode Shift Strategy for Chevrolet Volt Gen II Plug-In Hybrid Electric Vehicle. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/619
Chicago Manual of Style (16th Edition):
Sachdeva, Kovid. “Development of Optimal Operating Point Maps and Mode Shift Strategy for Chevrolet Volt Gen II Plug-In Hybrid Electric Vehicle.” 2018. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/619.
MLA Handbook (7th Edition):
Sachdeva, Kovid. “Development of Optimal Operating Point Maps and Mode Shift Strategy for Chevrolet Volt Gen II Plug-In Hybrid Electric Vehicle.” 2018. Web. 08 Mar 2021.
Vancouver:
Sachdeva K. Development of Optimal Operating Point Maps and Mode Shift Strategy for Chevrolet Volt Gen II Plug-In Hybrid Electric Vehicle. [Internet] [Masters thesis]. Michigan Technological University; 2018. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/619.
Council of Science Editors:
Sachdeva K. Development of Optimal Operating Point Maps and Mode Shift Strategy for Chevrolet Volt Gen II Plug-In Hybrid Electric Vehicle. [Masters Thesis]. Michigan Technological University; 2018. Available from: https://digitalcommons.mtu.edu/etdr/619
Michigan Technological University
20.
Wang, Luting.
STUDY OF MODELING AND OPTIMAL CONTROL OF PLUG-IN ELECTRIC VEHICLES AND THE INTEGRATION WITH SMART GRID.
Degree: PhD, Department of Mechanical Engineering-Engineering Mechanics, 2018, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/696
► The rapid development of plug-in electric vehicles (PEV) brings both challenges and opportunities to the power system. This dissertation studies the modeling and optimal…
(more)
▼ The rapid development of plug-in electric vehicles (PEV) brings both challenges and opportunities to the power system. This dissertation studies the modeling and optimal control of vehicle-grid integration (VGI) system with the consideration of both grid-side and PEV owners’ benefits.
First of all, a phasor mode single-phase microgrid with PEVs and PV farm is modeled to study the cost effective optimal control of PEV charging / discharging, and cope with the power balancing problem. The linear programming (LP) and genetic algorithm (GA) are used to obtain optimized charging schedules. The time-of-use (TOU) price and discharge incentive are considered for cost minimization.
Secondly, the impacts of the bi-directional power flow on battery degradation are investigated. An energy-throughput battery degradation model is applied to simulate the daily lifetime degradation. Case studies with different battery capacities, depth of discharge, temperature, and charging regime are investigated.
Thirdly, a grid-tied charging system that enables both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) is designed using SimPowerSystems in Matlab/Simulink. The bi-directional AC-DC and DC-DC converters are designed with PWM-driven bridges. A predictive current control (PCC) is designed to control the AC-DC converter. The phase-lock loop (PLL) technology and band-stop filter is applied to reduce the total harmonic distortion (THD) on grid current.
In the previous studies, the control algorithms are designed base on phasor mode model and validated via offline simulation. To further investigate the optimal power management algorithm for real-time simulation, a detailed power electronics level VGI system is modeled with RT-Lab RTE-drive blocks. The real-time simulations with a rule-based algorithm are conducted in Hardware-In-The-Loop (HIL) enabled OPAL-RT simulator.
To deal with a large-scale of PEVs charging, a piecewise consensus-based distributed control is presented to minimize the charging power loss and maximize the utilization of PEVs for V2G services. The graph theory is applied to represent the communication network among neighboring PEVs. A metropolis stochastic matrix is applied to specify the communication topology. Case studies with ten PEVs and one hundred PEVs are conducted and analyzed respectively.
In the last, due to the rapid response of PEV batteries to the power change demand, PEVs are coordinated with a dual-level consensus-based frequency control method to support the primary frequency control (PFC). The upper-level control aims to minimize the frequency deviation of multi-area power system, and the lower-level control aims to minimize the frequency regulation cost and battery degradation cost for individual PEVs. The consensus-algorithm is applied to specify the information updating and exchange among neighboring individuals. The simulation with different load change are conducted and studied.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Plug-in Electric Vehicle (PEV); Vehicle-Grid-Integration (VGI); Optimal charging/discharging control; Vehicle-to-Grid (V2G); Distributed consensus algorithm; Battery degradation; Automotive Engineering; Controls and Control Theory; Dynamics and Dynamical Systems; Electrical and Electronics; Energy Systems; Power and Energy
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APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
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APA (6th Edition):
Wang, L. (2018). STUDY OF MODELING AND OPTIMAL CONTROL OF PLUG-IN ELECTRIC VEHICLES AND THE INTEGRATION WITH SMART GRID. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/696
Chicago Manual of Style (16th Edition):
Wang, Luting. “STUDY OF MODELING AND OPTIMAL CONTROL OF PLUG-IN ELECTRIC VEHICLES AND THE INTEGRATION WITH SMART GRID.” 2018. Doctoral Dissertation, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/696.
MLA Handbook (7th Edition):
Wang, Luting. “STUDY OF MODELING AND OPTIMAL CONTROL OF PLUG-IN ELECTRIC VEHICLES AND THE INTEGRATION WITH SMART GRID.” 2018. Web. 08 Mar 2021.
Vancouver:
Wang L. STUDY OF MODELING AND OPTIMAL CONTROL OF PLUG-IN ELECTRIC VEHICLES AND THE INTEGRATION WITH SMART GRID. [Internet] [Doctoral dissertation]. Michigan Technological University; 2018. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/696.
Council of Science Editors:
Wang L. STUDY OF MODELING AND OPTIMAL CONTROL OF PLUG-IN ELECTRIC VEHICLES AND THE INTEGRATION WITH SMART GRID. [Doctoral Dissertation]. Michigan Technological University; 2018. Available from: https://digitalcommons.mtu.edu/etdr/696
Michigan Technological University
21.
Wang, Huanqing.
DEVELOPMENT OF DYNAMIC PROGRAMMING AND RECEDING HORIZON CONTROL STRATEGIES FOR GM VOLT II MULTI-MODE HYBRID ELECTRIC VEHICLE.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2018, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/695
► This thesis presents three optimization-based powertrain control methods for powertrain control of multi-mode hybrid electric vehicle, as part of the “Next-Generation Energy Technologies for…
(more)
▼ This thesis presents three optimization-based powertrain control methods for powertrain control of multi-mode hybrid electric vehicle, as part of the “Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR)” project.
The control methods are Instantaneous Optimization, Global Optimization and Receding Horizon Control/Model Predictive Control. The Instantaneous Optimization utilizes ECMS method to determine the best operating points and best mode for powertrain control. Dynamic Programming (DP) is used in the global optimization method for optimal control. The experimentally determined mode shift fuel and electricity costs are incorporated in the algorithm to optimize the mode selection and power-split. The Receding Horizon Control utilizes the Dynamic Programming algorithm to create optimal solution within a moving prediction horizon, which has the potential for real time control.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Multi-mode HEV; ECMS; Dynamic Programming; MPC; Automotive Engineering
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APA ·
Chicago ·
MLA ·
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CSE |
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APA (6th Edition):
Wang, H. (2018). DEVELOPMENT OF DYNAMIC PROGRAMMING AND RECEDING HORIZON CONTROL STRATEGIES FOR GM VOLT II MULTI-MODE HYBRID ELECTRIC VEHICLE. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/695
Chicago Manual of Style (16th Edition):
Wang, Huanqing. “DEVELOPMENT OF DYNAMIC PROGRAMMING AND RECEDING HORIZON CONTROL STRATEGIES FOR GM VOLT II MULTI-MODE HYBRID ELECTRIC VEHICLE.” 2018. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/695.
MLA Handbook (7th Edition):
Wang, Huanqing. “DEVELOPMENT OF DYNAMIC PROGRAMMING AND RECEDING HORIZON CONTROL STRATEGIES FOR GM VOLT II MULTI-MODE HYBRID ELECTRIC VEHICLE.” 2018. Web. 08 Mar 2021.
Vancouver:
Wang H. DEVELOPMENT OF DYNAMIC PROGRAMMING AND RECEDING HORIZON CONTROL STRATEGIES FOR GM VOLT II MULTI-MODE HYBRID ELECTRIC VEHICLE. [Internet] [Masters thesis]. Michigan Technological University; 2018. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/695.
Council of Science Editors:
Wang H. DEVELOPMENT OF DYNAMIC PROGRAMMING AND RECEDING HORIZON CONTROL STRATEGIES FOR GM VOLT II MULTI-MODE HYBRID ELECTRIC VEHICLE. [Masters Thesis]. Michigan Technological University; 2018. Available from: https://digitalcommons.mtu.edu/etdr/695
Michigan Technological University
22.
Desouky, Mohammed.
ALGORITHMS AND OPTIMAL CONTROL FOR SPACECRAFT MAGNETIC ATTITUDE MANEUVERS.
Degree: PhD, Department of Mechanical Engineering-Engineering Mechanics, 2019, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/968
► This study focused on providing applicable control solutions for spacecraft magnetic attitude control system. Basically, two main lines are pursued; first, developing detumbling control…
(more)
▼ This study focused on providing applicable control solutions for spacecraft magnetic attitude control system. Basically, two main lines are pursued; first, developing detumbling control laws and second, an improvement in the three-axis attitude control schemes by extending magnetic rods activation time.
Spacecraft, after separation from the launching mechanism, experiences a tumbling phase due to an undesired angular momentum. In this study, we present a new efficient variant of the B-dot detumbling law by introducing a substitute of the spacecraft angular velocity, based on the ambient magnetic field data. This B-dot law preserves the orthogonality, among the applied torque, dipole moment and magnetic field vectors. Most of the existing variants of the B-dot law in the literature don't preserve this orthogonality. Furthermore, the problem of minimum-time spacecraft magnetic detumbling is revisited within the context of optimal control theory. Two formulations are presented; the first one assumes the availability of the angular velocity measurements for feedback. The second formulation assumes the availability of only the ambient magnetic field measurements in the feedback; the latter is considered another optimal-based B-dot law. A reduction in detumbling time is fulfilled by the proposed laws along with less power consumption for the proposed B-dot laws.
In magnetic attitude maneuvers, magnetic rods and magnetometers usually operate alternatively, to avoid the magnetic rods' noise effect on magnetometers measurements. Because of that, there will be no control authority over the spacecraft during the magnetometer measurement period. Hence longer maneuver times are usually experienced. In this study, a control scheme that enables the extension of the magnetic rods’ activation time is developed, regardless of the attitude control law. The key concept is replacing the real magnetic field measurement by a pseudo measurement, which is computed based on other sensors measurements. By applying a known command to the spacecraft and measuring the spacecraft response, it is possible to compute the ambient magnetic field around the spacecraft. The system mathematical singularity is solved using the Tikhonov regularization approach. Another developed approach estimates the magnetic field, using a relatively simple and fast dynamic model inside a Multiplicative Extended Kalman Filter. A less maneuver time with less power consumption are fulfilled. These control approaches are further validated using real telemetry data from CASSIOPE mission.
This dissertation develops a stability analysis for the spacecraft magnetic attitude control, taking into consideration the alternate operation between the magnetic rods and the magnetometers. It is shown that the system stability degrades because of this alternate operation, supporting the proposed approach of extending the operation time of the magnetic rods.
Advisors/Committee Members: Ossama Abdelkhalik, Bo Chen.
Subjects/Keywords: B-dot Law; Tikhonov Regularization; Three-axis Attitude Maneuver; Time-Optimal Detumbling Maneuver; Multiplicative Extended Kalman Filter; Intermittent Activation of Magnetic Rods; Navigation, Guidance, Control and Dynamics
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APA (6th Edition):
Desouky, M. (2019). ALGORITHMS AND OPTIMAL CONTROL FOR SPACECRAFT MAGNETIC ATTITUDE MANEUVERS. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/968
Chicago Manual of Style (16th Edition):
Desouky, Mohammed. “ALGORITHMS AND OPTIMAL CONTROL FOR SPACECRAFT MAGNETIC ATTITUDE MANEUVERS.” 2019. Doctoral Dissertation, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/968.
MLA Handbook (7th Edition):
Desouky, Mohammed. “ALGORITHMS AND OPTIMAL CONTROL FOR SPACECRAFT MAGNETIC ATTITUDE MANEUVERS.” 2019. Web. 08 Mar 2021.
Vancouver:
Desouky M. ALGORITHMS AND OPTIMAL CONTROL FOR SPACECRAFT MAGNETIC ATTITUDE MANEUVERS. [Internet] [Doctoral dissertation]. Michigan Technological University; 2019. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/968.
Council of Science Editors:
Desouky M. ALGORITHMS AND OPTIMAL CONTROL FOR SPACECRAFT MAGNETIC ATTITUDE MANEUVERS. [Doctoral Dissertation]. Michigan Technological University; 2019. Available from: https://digitalcommons.mtu.edu/etdr/968
Michigan Technological University
23.
Chen, Wei.
Impact of Spark Ignition Duration, Energy and Phasing on Combustion and Performance in a Gasoline Turbocharged Direct Injection Engine near the Dilute Limit.
Degree: PhD, Department of Mechanical Engineering-Engineering Mechanics, 2015, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/11
► High dilution combustion is a promising technology to continue improving gasoline spark-ignition (SI) engine fuel conversion efficiency and for the reduction of nitrogen oxide…
(more)
▼ High dilution combustion is a promising technology to continue improving gasoline spark-ignition (SI) engine fuel conversion efficiency and for the reduction of nitrogen oxide emissions. Dilution is principally limited in SI engines by ignition, flame kernel development, successful transition to the turbulent propagating flame during the bulk burn portion of combustion process and the resulting combustion stability. However, the SI gasoline turbocharged directed injection (GTDI) engine ignition requirements, especially at the combustion stability limit, are not well understood and must be better characterized to enable improved designs.
A multi-discharge, electronically control, inductive ignition system was employed on a multi-cylinder GTDI engine to control and quantify the ignition and combustion processes under high dilution operation. The ignition system, developed by Ford Motor Company and integrated on the engine, is a Variable Output Ignition System (VOIS) enabling flexible spark discharge patterns with control of ignition energy, duration, and phasing. In this study two coil discharges were examined under both continuous and discontinuous settings by delaying the second discharge with respect to the first. Ignition secondary voltage and current were measured with a high speed analog to digital recorder to measure and quantify the breakdown voltages, ignition duration, ignition energy, and other ignition metrics over 300 cycles of continuous engine operation. Simultaneously 300 cycles of crank-angle resolved cylinder pressure and other data was recorded to analyze cycle based work and combustion rates and to correlate ignition with combustion.
With respect to ignition analysis and correlations, the results show that the breakdown voltage of the second discharge was correlated to the second coil discharge timing. The second breakdown voltage increased when the second coil discharge timing was retarded. It was also found that the glow energy was highly correlated to the ignition duration on a cycle-by-cycle basis. The ignition duration decreases with higher ignition voltages during glow discharge giving higher total glow energy as a result of hypothesized arc stretching.
With respect to ignition and combustion correlations, the flame kernel development period was found to be weakly correlated to both the ignition duration and energy. The breakdown and arc energy of the second discharge had higher correlation to the combustion phasing than the glow energy of the second discharge.
With respect to engine performance in a dual-coil multi-discharge ignition, an optimal ignition energy phase delay time exists with a fixed total ignition energy. A delayed second coil discharge at the dilution limit can convert abnormal combustion cycles to normal burn cycles. The combustion phasing of these converted cycles is dependent on the phasing of the second discharge. The results also showed that combustion phasing was strongly correlated to the flame kernel development period. The gross…
Advisors/Committee Members: Jeffery D. Naber, Bo Chen.
Subjects/Keywords: Dual-coil Ignition System; EGR Limit; Direct Injection Spark Ignition Engine; Combustion Stability; Ignition Energy; Ignition Duration; Automotive Engineering
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APA (6th Edition):
Chen, W. (2015). Impact of Spark Ignition Duration, Energy and Phasing on Combustion and Performance in a Gasoline Turbocharged Direct Injection Engine near the Dilute Limit. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/11
Chicago Manual of Style (16th Edition):
Chen, Wei. “Impact of Spark Ignition Duration, Energy and Phasing on Combustion and Performance in a Gasoline Turbocharged Direct Injection Engine near the Dilute Limit.” 2015. Doctoral Dissertation, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/11.
MLA Handbook (7th Edition):
Chen, Wei. “Impact of Spark Ignition Duration, Energy and Phasing on Combustion and Performance in a Gasoline Turbocharged Direct Injection Engine near the Dilute Limit.” 2015. Web. 08 Mar 2021.
Vancouver:
Chen W. Impact of Spark Ignition Duration, Energy and Phasing on Combustion and Performance in a Gasoline Turbocharged Direct Injection Engine near the Dilute Limit. [Internet] [Doctoral dissertation]. Michigan Technological University; 2015. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/11.
Council of Science Editors:
Chen W. Impact of Spark Ignition Duration, Energy and Phasing on Combustion and Performance in a Gasoline Turbocharged Direct Injection Engine near the Dilute Limit. [Doctoral Dissertation]. Michigan Technological University; 2015. Available from: https://digitalcommons.mtu.edu/etdr/11
Michigan Technological University
24.
Wang, Xin.
A STUDY OF MODEL-BASED CONTROL STRATEGY FOR A GASOLINE TURBOCHARGED DIRECT INJECTION SPARK IGNITED ENGINE.
Degree: PhD, Department of Mechanical Engineering-Engineering Mechanics, 2020, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etdr/1116
► To meet increasingly stringent fuel economy and emissions legislation, more advanced technologies have been added to spark-ignition (SI) engines, thus exponentially increase the complexity…
(more)
▼ To meet increasingly stringent fuel economy and emissions legislation, more advanced technologies have been added to spark-ignition (SI) engines, thus exponentially increase the complexity and calibration work of traditional map-based engine control. To achieve better engine performance without introducing significant calibration efforts and make the developed control system easily adapt to future engines upgrades and designs, this research proposes a model-based optimal control system for cycle-by-cycle Gasoline Turbocharged Direct Injection (GTDI) SI engine control, which aims to deliver the requested torque output and operate the engine to achieve the best achievable fuel economy and minimum emission under wide range of engine operating conditions.
This research develops a model-based ignition timing prediction strategy for combustion phasing (crank angle of fifty percent of the fuel burned, CA50) control. A control-oriented combustion model is developed to predict burn duration from ignition timing to CA50. Using the predicted burn duration, the ignition timing needed for the upcoming cycle to track optimal target CA50 is calculated by a dynamic ignition timing prediction algorithm.
A Recursive-Least-Square (RLS) with Variable Forgetting Factor (VFF) based adaptation algorithm is proposed to handle operating-point-dependent model errors caused by inherent errors resulting from modeling assumptions and limited calibration points, which helps to ensure the proper performance of model-based ignition timing prediction strategy throughout the entire engine lifetime. Using the adaptive combustion model, an Adaptive Extended Kalman Filter (AEKF) based CA50 observer is developed to provide filtered CA50 estimation from cyclic variations for the closed-loop combustion phasing control.
An economic nonlinear model predictive controller (E-NMPC) based GTDI SI engine control system is developed to simultaneously achieve three objectives: tracking the requested net indicated mean effective pressure (IMEPn), minimizing the SFC, and reducing NOx emissions. The developed E-NMPC engine control system can achieve the above objectives by controlling throttle position, IVC timing, CA50, exhaust valve opening (EVO) timing, and wastegate position at the same time without violating engine operating constraints. A control-oriented engine model is developed and integrated into the E-NMPC to predict future engine behaviors. A high-fidelity 1-D GT-POWER engine model is developed and used as the plant model to tune and validate the developed control system. The performance of the entire model-based engine control system is examined through the software-in-the-loop (SIL) simulation using on-road vehicle test data.
Advisors/Committee Members: Bo Chen, Jeffrey D. Naber.
Subjects/Keywords: Automotive Engineering; Computer-Aided Engineering and Design; Controls and Control Theory; Mechanical Engineering
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APA (6th Edition):
Wang, X. (2020). A STUDY OF MODEL-BASED CONTROL STRATEGY FOR A GASOLINE TURBOCHARGED DIRECT INJECTION SPARK IGNITED ENGINE. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/1116
Chicago Manual of Style (16th Edition):
Wang, Xin. “A STUDY OF MODEL-BASED CONTROL STRATEGY FOR A GASOLINE TURBOCHARGED DIRECT INJECTION SPARK IGNITED ENGINE.” 2020. Doctoral Dissertation, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etdr/1116.
MLA Handbook (7th Edition):
Wang, Xin. “A STUDY OF MODEL-BASED CONTROL STRATEGY FOR A GASOLINE TURBOCHARGED DIRECT INJECTION SPARK IGNITED ENGINE.” 2020. Web. 08 Mar 2021.
Vancouver:
Wang X. A STUDY OF MODEL-BASED CONTROL STRATEGY FOR A GASOLINE TURBOCHARGED DIRECT INJECTION SPARK IGNITED ENGINE. [Internet] [Doctoral dissertation]. Michigan Technological University; 2020. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etdr/1116.
Council of Science Editors:
Wang X. A STUDY OF MODEL-BASED CONTROL STRATEGY FOR A GASOLINE TURBOCHARGED DIRECT INJECTION SPARK IGNITED ENGINE. [Doctoral Dissertation]. Michigan Technological University; 2020. Available from: https://digitalcommons.mtu.edu/etdr/1116
25.
Joshi, Shreyash.
MODELING AND HARDWARE-IN-THE-LOOP SIMULATION OF POWER-SPLIT HYBRID ELECTRIC VEHICLES.
Degree: MS, Department of Mechanical Engineering-Engineering Mechanics, 2013, Michigan Technological University
URL: https://digitalcommons.mtu.edu/etds/824
► Conventional vehicles are creating pollution problems, global warming and the extinction of high density fuels. To address these problems, automotive companies and universities are…
(more)
▼ Conventional vehicles are creating pollution problems, global warming and the extinction of high density fuels. To address these problems, automotive companies and universities are researching on hybrid electric vehicles where two different power devices are used to propel a vehicle. This research studies the development and testing of a dynamic model for Prius 2010 Hybrid Synergy Drive (HSD), a power-split device. The device was modeled and integrated with a hybrid vehicle model. To add an electric only mode for vehicle propulsion, the hybrid synergy drive was modified by adding a clutch to carrier 1. The performance of the integrated vehicle model was tested with UDDS drive cycle using rule-based control strategy. The dSPACE Hardware-In-the-Loop (HIL) simulator was used for HIL simulation test. The HIL simulation result shows that the integration of developed HSD dynamic model with a hybrid vehicle model was successful. The HSD model was able to split power and isolate engine speed from vehicle speed in hybrid mode.
Advisors/Committee Members: Bo Chen.
Subjects/Keywords: Mechanical Engineering
…Mechatronics and Embedded Systems Lab
colleagues at Michigan Technological University special thanks… …ACKNOWLEDGEMENTS
I thank my advisor Dr. Bo Chen, for support in this research work and guiding me for
my…
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APA (6th Edition):
Joshi, S. (2013). MODELING AND HARDWARE-IN-THE-LOOP SIMULATION OF POWER-SPLIT HYBRID ELECTRIC VEHICLES. (Masters Thesis). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etds/824
Chicago Manual of Style (16th Edition):
Joshi, Shreyash. “MODELING AND HARDWARE-IN-THE-LOOP SIMULATION OF POWER-SPLIT HYBRID ELECTRIC VEHICLES.” 2013. Masters Thesis, Michigan Technological University. Accessed March 08, 2021.
https://digitalcommons.mtu.edu/etds/824.
MLA Handbook (7th Edition):
Joshi, Shreyash. “MODELING AND HARDWARE-IN-THE-LOOP SIMULATION OF POWER-SPLIT HYBRID ELECTRIC VEHICLES.” 2013. Web. 08 Mar 2021.
Vancouver:
Joshi S. MODELING AND HARDWARE-IN-THE-LOOP SIMULATION OF POWER-SPLIT HYBRID ELECTRIC VEHICLES. [Internet] [Masters thesis]. Michigan Technological University; 2013. [cited 2021 Mar 08].
Available from: https://digitalcommons.mtu.edu/etds/824.
Council of Science Editors:
Joshi S. MODELING AND HARDWARE-IN-THE-LOOP SIMULATION OF POWER-SPLIT HYBRID ELECTRIC VEHICLES. [Masters Thesis]. Michigan Technological University; 2013. Available from: https://digitalcommons.mtu.edu/etds/824
. 
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