Abstract
This paper takes a hybrid electric vehicle (HEV) with a clutch as the power coupling device as the research object, and formulates a regular energy management strategy. Aiming at the problem that the rule-based energy management strategy relies on engineering experience severely, an optimized rule-based energy management strategy based on a particle swarm algorithm is proposed. The particle swarm algorithm takes the minimum fuel consumption as the fitness function, and uses the threshold of the car’s working mode switching and torque distribution as the optimization variables to optimize the regular energy management strategy. The simulation results show that the designed strategy can achieve electricity balance, and the optimized strategy improves the fuel economy by 6.4% compared with the before optimization.
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Acknowledgment
This research was supported by the 2020 Independent Research Project of Guangxi key laboratory of Automobile Components and Vehicle technology, Guangxi University of Science and Technology (2020GKLACVTZZ04), Guangxi Natural Science Foundation(No.2020GXNSFDA238011) and Innovation Project of Guangxi Graduate Education(YCSW2021302). Thanks for the support of these projects.
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Liu, S., Wu, M., Chen, J., Ding, L., Pang, D. (2022). Research of Energy Management Strategy for Hybrid HEV Based on Optimization Rules. In: He, J., Li, Y., Yang, Q., Liang, X. (eds) The proceedings of the 16th Annual Conference of China Electrotechnical Society. Lecture Notes in Electrical Engineering, vol 891. Springer, Singapore. https://doi.org/10.1007/978-981-19-1532-1_86
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DOI: https://doi.org/10.1007/978-981-19-1532-1_86
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