@inproceedings{b0445c5ee2674431a9bbbb656b9a01b3,
title = "A Pulse Impedance Technique for Fast State of Health Estimation of EV Lithium-Ion Batteries",
abstract = "As efficient energy storage devices, batteries have built a close connection with the world of human beings. The lifespan and safety of batteries have always been a major concern and received massive attention from researchers for online monitoring battery conditions. Moreover, as batteries are integrated into applications on a growing scale, and the energy density of the battery is increasing, any problem from a small cell has a greater potential to cause the entire battery pack to catch fire or even explode within a short period of time. Thus, an online method for rapid assessing the state of health (SOH) of a battery is highly valuable. This paper aims at developing more efficient techniques to monitor the lithium-ion battery SOH. In particular, a novel method is proposed based on dynamic responses of current and voltage transient spikes, rather than the static ones adopted in the conventional current pulse method. This method combines both static and dynamic responses through a fast impedance measurement based on pulse dynamic responses, which therefore is named as Pulse Impedance Technique (PIT). The fundamental theory and implementing procedure are presented along with preliminary evaluation results, demonstrating the performance of this impedance-based method allows SOH to be estimated effectively.",
keywords = "Battery impedance, EV battery, Pulse test, Rapid state of health estimation",
author = "Xiaoyu Zhao and Zuolu Wang and Li Eric and Fengshou Gu and Ball, {Andrew D.}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference of The Efficiency and Performance Engineering Network 2022, TEPEN 2022 ; Conference date: 18-08-2022 Through 21-08-2022",
year = "2023",
month = mar,
day = "4",
doi = "10.1007/978-3-031-26193-0_19",
language = "English",
isbn = "9783031261923",
volume = "129",
series = "Mechanisms and Machine Science",
publisher = "Springer, Cham",
pages = "220--233",
editor = "Hao Zhang and Yongjian Ji and Tongtong Liu and Xiuquan Sun and Ball, {Andrew David}",
booktitle = "Proceedings of TEPEN 2022",
address = "Switzerland",
}