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You searched for subject:(auxiliary loads). Showing records 1 – 3 of 3 total matches.

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University of Waterloo

1. Lawrence, Christopher Paul. Improving Fuel Economy via Management of Auxiliary Loads in Fuel-Cell Electric Vehicles.

Degree: 2007, University of Waterloo

The automotive industry is in a state of flux at the moment. Traditional combustion engine technologies are becoming challenged by newer, more efficient and environmentally friendly propulsion methods. These include bio-fuel, hybrid, and hydrogen fuel-cell technologies. Propulsion alone, however, is not the only area where improvements can be made in vehicle efficiency. Current vehicle research and development focuses heavily on propulsion systems with relatively few resources dedicated to auxiliary systems. These auxiliary systems, however, can have a significant impact on overall vehicle efficiency and fuel economy. The objective of this work is to improve the efficiency of a Fuel Cell Electric Vehicle (FCEV) through intelligent auxiliary system control. The analysis contained herein is applicable to all types of vehicles and may find applications in many vehicle architectures. A survey is made of the various types of alternative fuels and vehicle architectures from conventional gasoline vehicles to hybrids and fuel cells. Trends in auxiliary power systems and previous papers on control of these systems are discussed. The FCEV developed by the University of Waterloo Alternative Fuels Team (UWAFT) is outlined and the design process presented. Its powertrain control strategy is analyzed with a proposal for modifications as well as the addition of an auxiliary control module to meet the aforementioned objectives. Simulations are performed to predict the efficiency and fuel economy gains that can potentially be realized using these proposed techniques. These gains prove to be significant, with an almost 2% improvement realized through intelligent control of the air conditioning compressor, and further gains possible through other auxiliary power reduction techniques.

Subjects/Keywords: Vehicle auxiliary loads; Fuel economy

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lawrence, C. P. (2007). Improving Fuel Economy via Management of Auxiliary Loads in Fuel-Cell Electric Vehicles. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/3275

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lawrence, Christopher Paul. “Improving Fuel Economy via Management of Auxiliary Loads in Fuel-Cell Electric Vehicles.” 2007. Thesis, University of Waterloo. Accessed July 09, 2020. http://hdl.handle.net/10012/3275.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lawrence, Christopher Paul. “Improving Fuel Economy via Management of Auxiliary Loads in Fuel-Cell Electric Vehicles.” 2007. Web. 09 Jul 2020.

Vancouver:

Lawrence CP. Improving Fuel Economy via Management of Auxiliary Loads in Fuel-Cell Electric Vehicles. [Internet] [Thesis]. University of Waterloo; 2007. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/10012/3275.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lawrence CP. Improving Fuel Economy via Management of Auxiliary Loads in Fuel-Cell Electric Vehicles. [Thesis]. University of Waterloo; 2007. Available from: http://hdl.handle.net/10012/3275

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

2. Mohagheghi Fard, Soheil. A New Regenerative Anti-Idling System for Service Vehicles: Load Identification, Optimal Power Management.

Degree: 2016, University of Waterloo

Service vehicles, such as refrigerator trucks and tour buses, are equipped with auxiliary devices, including refrigeration systems and cabin air conditioning systems, which consume significant amount of energy. The engine of these vehicles should idle to supply power for auxiliary devices when they stop for a long time, e.g. for loading and unloading goods. This study proposes a new anti-idling system for service vehicles that powers auxiliary devices by a battery pack and an engine-driven generator (or alternator). In addition to idle elimination which is the main objective of all current anti-idling systems, the proposed system called Regenerative Auxiliary Power System (RAPS) attempts to reduce fuel consumption by enabling regenerative braking and utilizing an optimal power management system. The objectives of this study are to identify drive and service loads of a service vehicle for component sizing of the RAPS and to develop an optimal power management system for more fuel saving. In order to determine the size of required components (a battery pack and a generator) for the RAPS, drive and service loads of a given service vehicle should be identified. The drive load is the amount of power that is required for moving the vehicle, and the service load is the power consumption of the auxiliary devices. To identify drive and service loads, all the parameters in power balance equation of the engine should be either measured or estimated. As two inputs with unknown variations in this equation, vehicle mass and torque of auxiliary devices are required to be estimated. This study proposes a model-based algorithm that utilizes available signals in the CAN bus of the vehicle as well as a signal from a GPS receiver (road grade information) for simultaneous estimation of the vehicle mass and torque of auxiliary devices. The power management system of the RAPS should determine the split ratio of auxiliary power demand between the generator and battery in order to minimize fuel consumption. It should also guarantee that the battery has enough energy for powering auxiliary devices at all the engine-OFF stops. To meet these objectives, a two-level control system is proposed in this study. In the high-level control system, a fast dynamic programming (DP) technique which utilizes extracted features of the predicted drive and service loads obtains an SOC trajectory. In the low-level control system, a refined Adaptive Equivalent Fuel Consumption Minimization (A-ECMS) technique is employed to track the SOC trajectory obtained by the high-level control scheme. Many numerical simulations are carried out to test the functionality of the proposed identification algorithm and power management system. Moreover, the numerical simulations are validated by Hardware-In-The-Loop (HIL) simulations. The results show the idling is completely eliminated and a significant amount of fuel is saved by implementing the RAPS on a service vehicle. Therefore, the cost of energy can be noticeably reduced and consequently the cost of RAPS is recouped…

Subjects/Keywords: Anti-Idling System; Vehicle Loads Identification; Optimal Power Management System; Hardware-In-The-Loop; Vehicle Loads Prediction; Regenerative Auxiliary Power System

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mohagheghi Fard, S. (2016). A New Regenerative Anti-Idling System for Service Vehicles: Load Identification, Optimal Power Management. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/10581

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mohagheghi Fard, Soheil. “A New Regenerative Anti-Idling System for Service Vehicles: Load Identification, Optimal Power Management.” 2016. Thesis, University of Waterloo. Accessed July 09, 2020. http://hdl.handle.net/10012/10581.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mohagheghi Fard, Soheil. “A New Regenerative Anti-Idling System for Service Vehicles: Load Identification, Optimal Power Management.” 2016. Web. 09 Jul 2020.

Vancouver:

Mohagheghi Fard S. A New Regenerative Anti-Idling System for Service Vehicles: Load Identification, Optimal Power Management. [Internet] [Thesis]. University of Waterloo; 2016. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/10012/10581.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mohagheghi Fard S. A New Regenerative Anti-Idling System for Service Vehicles: Load Identification, Optimal Power Management. [Thesis]. University of Waterloo; 2016. Available from: http://hdl.handle.net/10012/10581

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

3. Hosseini, Seyedmohammad. Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems.

Degree: 2019, University of Waterloo

In this study, an innovative energy management system (EMS) employing the promising reinforcement learning (RL) method is proposed. The EMS intelligently administrates the power flow between the main battery which is fed through the alternator and a solar-powered auxiliary battery which is used for the vehicle idle time reduction via providing energy for auxiliary loads which force the engine to be running, although the service vehicle is stopped. RL, which is an exquisite artificial intelligence technique, endeavors to offer a sub-optimal performance for this control problem compared to the really time consuming Dynamic Programming approach, which determines the optimal solution through exhaustive search. A service vehicle is modeled in the Matlab/Simulink environment. Different parts of the model are described in detail, and the dynamics of the considered vehicle are discussed. The simulation results express a better functionality compared to an existing rule-based controller and the idled engine case, turning the proposed RL-based EMS into an effective method for implementation in vehicular solar idle reduction (SIR) systems. Double DQN is also utilized to come up with the continuous observation space. The results are showing that Deep-RL can be a promising method in control tasks like the EMS of vehicular systems. Furthermore, a cost-effective and efficient data acquisition system is designed, tested, and implemented using the renowned Raspberry Pi board, and some sensors to collect voltage, current, and temperature data. The required electrical enclosures are also designed to keep the whole package safe. The validation of the system results is done and the process is discussed in detail. This data acquisition system can be employed to read the required information from vehicle and its loads, in order that the intelligent EMS system can wisely decide which action to take in a real-time manner.

Subjects/Keywords: energy management system; reinforcement learning; solar idle reduction; data acquisition; deep learning; global warming; service vehicles; auxiliary loads; hybrid vehicles

…off and SIR system provides the auxiliary loads with required electrical power… …utilize the electrical power achieved from the solar panels and feed the auxiliary loads of the… …than 2hp, but still the engine has to work in order to keep the auxiliary loads running [… …have different accessories. Various auxiliary loads on diverse types of vehicles make the… …for purposes other than vehicle propulsion. They are basically used for auxiliary loads such… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hosseini, S. (2019). Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15135

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hosseini, Seyedmohammad. “Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems.” 2019. Thesis, University of Waterloo. Accessed July 09, 2020. http://hdl.handle.net/10012/15135.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hosseini, Seyedmohammad. “Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems.” 2019. Web. 09 Jul 2020.

Vancouver:

Hosseini S. Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems. [Internet] [Thesis]. University of Waterloo; 2019. [cited 2020 Jul 09]. Available from: http://hdl.handle.net/10012/15135.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hosseini S. Designing Intelligent Energy Management and Cost-effective Data Acquisition for Vehicular Solar Idle Reduction Systems. [Thesis]. University of Waterloo; 2019. Available from: http://hdl.handle.net/10012/15135

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.