An energy management strategy for a prototype P4 parallel hybrid Chevrolet Blazer is developed for the EcoCAR Mobility Challenge. The objective of the energy management strategy is to reduce energy consumption while maintaining the drive quality targets of a conventional vehicle. A comprehensive model of the hybrid powertrain and vehicle physics is constructed to aid in the development of the control strategy. To improve fuel efficiency, a Willans line model is developed for the conventional powertrain and used to develop a rule-based torque split strategy. The strategy maximizes high efficiency engine operation while reducing round trip losses. Calibratable parameters for the torque split operating regions allow for battery state of charge management. Torque request and filtering algorithms are also developed to ensure the hybrid powertrain can smoothly and reliably meet driver demand. Vehicle testing validates that the hybrid powertrain meets acceleration response targets while delivering an enjoyable driving experience. Simulation testing shows that the energy management strategy improved fuel economy in most drive cycles with improvements of 8.8% for US06, 9.8% for HWFET, and 0.1% for the EcoCAR Mobility Challenge Cycle. Battery state of charge management behavior is robust across a variety of drive cycles using inputs from both simulated and test drivers. The resulting energy management strategy delivers an efficient, responsive, and reliable hybrid electric vehicle. / Master of Science / A control strategy for a hybrid vehicle is developed to improve fuel efficiency without sacrificing vehicle responsiveness. Efficiency improvements are achieved by the strategy intelligently selecting to use the engine, motor, or a combination of the two to minimize fuel consumption. The strategy also handles the important tasks of maintaining the battery pack charge and smoothly transitioning between the engine and motor power. All together, this results in a hybrid vehicle with both improved fuel economy and an enjoyable driving experience.
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/111644 |
Date | 26 August 2022 |
Creators | Wu, Justin Quach |
Contributors | Mechanical Engineering, Nelson, Douglas J., Huxtable, Scott T., Southward, Steve C. |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Language | English |
Detected Language | English |
Type | Thesis |
Format | ETD, application/pdf |
Rights | Creative Commons Attribution-NonCommercial 4.0 International, http://creativecommons.org/licenses/by-nc/4.0/ |
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