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Transportation electrification is a promising solution to meet the ever-rising energy demand and realize sustainable development. Lithium-ion batteries, being the most predominant energy storage devices, directly affect the safety, comfort, driving range, and reliability of many electric mobilities. Nevertheless, thermal-related issues of batteries such as potential thermal runaway, performance degradation at low temperatures, and accelerated aging still hinder the wider adoption of electric mobilities. To ensure safe, efficient, and reliable operations of lithium-ion batteries, monitoring their thermal states is critical to safety protection, performance optimization, as well as prognostics, and health management. Given insufficient onboard temperature sensors and their inability to measure battery internal temperature, accurate and timely temperature estimation is of particular importance to thermal state monitoring. Toward this end, this paper provides a comprehensive review of temperature estimation techniques in battery systems regarding their mechanism, framework, and representative studies. The potential metrics used to characterize battery thermal states are discussed in detail at first considering the spatiotemporal attributes of battery temperature, and the strengths and weaknesses of applying such metrics in battery management are also analyzed. Afterward, various temperature estimation methods, including impedance/resistance-based, thermal model-based, and data-driven estimations, are elucidated, analyzed, and compared in terms of their strengths, limitations, and potential improvements. Finally, the key challenges to battery thermal state monitoring in real applications are identified, and future opportunities for removing these barriers are presented and discussed.
Bibliographical noteFunding Information:
This work was supported in part by the Villum Foundation for Smart Battery project (No. 222860 ), the National Natural Science Foundation of China (No. 52111530194 ) and the Fundamental Research Funds for the Central Universities ( 2022CDJDX-006 ).
Xiaosong Hu received the Ph.D. degree in automotive engineering from the Beijing Institute of Technology, Beijing, China, in 2012. He did scientific research and completed the Ph.D. dissertation in Automotive Research Center at the University of Michigan, Ann Arbor, MI, USA, between 2010 and 2012. He is currently a Professor with the Department of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China. He was a Postdoctoral Researcher with the Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA, between 2014 and 2015, as well as at the Swedish Hybrid Vehicle Center and the Department of Signals and Systems at Chalmers University of Technology, Gothenburg, Sweden, between 2012 and 2014. He was also a Visiting Postdoctoral Researcher with the Institute for Dynamic Systems and Control at Swiss Federal Institute of Technology (ETH), Zurich, Switzerland, in 2014. His research interests include modeling and control of alternative powertrains and energy storage systems. Dr. Hu has been the recipient of numerous prestigious awards/honors, including Web of Science Highly-Cited Researcher by Clarivate Analytics, SAE Environmental Excellence in Transportation Award, IEEE ITSS Young Researcher Award, SAE Ralph Teetor Educational Award, Emerging Sustainability Leaders Award, EU Marie Currie Fellowship, ASME DSCD Energy Systems Best Paper Award, and Beijing Best Ph.D. Dissertation Award. He is an IET Fellow.
© 2023 The Authors
- Battery management
- Electric mobility
- Lithium-ion batteries
- Temperature estimation
- Thermal state monitoring