@inproceedings{dd6295bf70014a1187c7ae7eccb37310,
title = "Model-free learning-based online management of hybrid electrical energy storage systems in electric vehicles",
abstract = "To improve the cycle efficiency and peak output power density of energy storage systems in electric vehicles (EVs), supercapacitors have been proposed as auxiliary energy storage elements to complement the mainstream Lithium-ion (Li-ion) batteries. The performance of such a hybrid electrical energy storage (HEES) system is highly dependent on the implemented management policy. This paper presents a model-free reinforcement learning-based approach to dynamically manage the current flows from and into the battery and supercapacitor banks under various scenarios (combinations of EV specs and driving patterns). Experimental results demonstrate that the proposed approach achieves up to 25% higher efficiency compared to a Li-ion battery only storage system and outperforms other online HEES system control policies in all test cases.",
keywords = "Electric vehicle, Hybrid energy storage systems, Reinforcement learning",
author = "Siyu Yue and Yanzhi Wang and Qing Xie and Di Zhu and Massoud Pedram and Naehyuck Chang",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.",
year = "2014",
month = feb,
day = "24",
doi = "10.1109/IECON.2014.7048959",
language = "English (US)",
series = "IECON Proceedings (Industrial Electronics Conference)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3142--3148",
booktitle = "IECON Proceedings (Industrial Electronics Conference)",
}