A Review on Rapid State of Health Estimation of Lithium-ion Batteries in Electric Vehicles

Zuolu Wang, Xiaoyu Zhao, Lei Fu, Dong Zhen, Fengshou Gu, Andrew Ball

Research output: Contribution to journalReview articlepeer-review

9 Citations (Scopus)

Abstract

Lithium-ion battery has presented a rapid growth as the power source of electric vehicles (EVs). The state of health (SOH) estimation plays an important role in ensuring the safe operation of the battery system. Currently, the model-based and data-driven methods have been comprehensively reviewed by considering strengths and drawbacks. However, these approaches present high complexity due to the complex test, modelling and processing algorithm. Developing rapid SOH estimation methods based on the simple test can help suppress the estimation cost and improve the estimation efficiency. However, there is no work to review the development of the rapid SOH estimation for EV batteries and the traditional classification needs to be updated to align with the current state of research. This paper reviews and discusses the state-of-the-art of rapid SOH estimation techniques for EV batteries over the past decade. Particularly, it gives the reclassifications and working principles of the current estimation techniques. Moreover, their advantages and disadvantages when applied to the practice are discussed by incorporating experimental studies. Eventually, this paper gives meaningful suggestions on both practical applications and future development of rapid estimation methods. It is considered that this review work can suggest valuable guidance for academic investigation and engineering applications.
Original languageEnglish
Article number103457
Number of pages16
JournalSustainable Energy Technologies and Assessments
Volume60
Early online date17 Sep 2023
DOIs
Publication statusPublished - 1 Dec 2023

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