Computer Science > Artificial Intelligence
arXiv:2212.09154 (cs)
[Submitted on 18 Dec 2022]
Title:Empirical Analysis of AI-based Energy Management in Electric Vehicles: A Case Study on Reinforcement Learning
Authors:Jincheng Hu,Yang Lin,Jihao Li,Zhuoran Hou,Dezong Zhao,Quan Zhou,Jingjing Jiang,Yuanjian Zhang
View a PDF of the paper titled Empirical Analysis of AI-based Energy Management in Electric Vehicles: A Case Study on Reinforcement Learning, by Jincheng Hu and 6 other authors
View PDFAbstract:Reinforcement learning-based (RL-based) energy management strategy (EMS) is considered a promising solution for the energy management of electric vehicles with multiple power sources. It has been shown to outperform conventional methods in energy management problems regarding energy-saving and real-time performance. However, previous studies have not systematically examined the essential elements of RL-based EMS. This paper presents an empirical analysis of RL-based EMS in a Plug-in Hybrid Electric Vehicle (PHEV) and Fuel Cell Electric Vehicle (FCEV). The empirical analysis is developed in four aspects: algorithm, perception and decision granularity, hyperparameters, and reward function. The results show that the Off-policy algorithm effectively develops a more fuel-efficient solution within the complete driving cycle compared with other algorithms. Improving the perception and decision granularity does not produce a more desirable energy-saving solution but better balances battery power and fuel consumption. The equivalent energy optimization objective based on the instantaneous state of charge (SOC) variation is parameter sensitive and can help RL-EMSs to achieve more efficient energy-cost strategies.
| Subjects: | Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| Cite as: | arXiv:2212.09154 [cs.AI] |
| (orarXiv:2212.09154v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2212.09154 arXiv-issued DOI via DataCite |
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View a PDF of the paper titled Empirical Analysis of AI-based Energy Management in Electric Vehicles: A Case Study on Reinforcement Learning, by Jincheng Hu and 6 other authors
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