A Critical Review of the State Estimation Methods of Power Batteries for Electric Vehicles

Qi Zhang (), Hailin Rong, Daduan Zhao, Menglu Pei and Xing Dong ()
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Qi Zhang: School of Control Science and Engineering, Shandong University, Jinan 250061, China
Hailin Rong: School of Control Science and Engineering, Shandong University, Jinan 250061, China
Daduan Zhao: School of Control Science and Engineering, Shandong University, Jinan 250061, China
Menglu Pei: School of Control Science and Engineering, Shandong University, Jinan 250061, China
Xing Dong: School of Control Science and Engineering, Shandong University, Jinan 250061, China

Energies, 2025, vol. 18, issue 14, 1-20

Abstract: Power batteries and their management technology are crucial for the safe and efficient operation of electric vehicles (EVs). The life and safety issues of power batteries have always plagued the EV industry. To achieve an intelligent battery management system (BMS), it is crucial to accurately estimate the internal state of the power battery. The purpose of this review is to analyze the current status of research on multi-state estimation of power batteries, which mainly focuses on the estimation of state of charge (SOC), state of energy (SOE), state of health (SOH), state of power (SOP), state of temperature (SOT), and state of safety (SOS). Moreover, it also analyzes and prospects the research hotspots, development trends, and future challenges of battery state estimation. It is a significant guide for designing BMSs for EVs, as well as for achieving intelligent safety management and efficient power battery use.

Keywords: battery management system (BMS); critical overview; electric vehicles (EVs); power batteries; state estimation; state of energy (SOE); state of health (SOH) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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