Physics-based battery SOC estimation methods: Recent advances and future perspectives

The reliable prediction of state of charge (SOC) is one of the vital functions of advanced battery management system (BMS), which has great significance towards safe operation of electric vehicles. By far, the empirical model-based and data-driven-based SOC estimation methods of lithium-ion batteries have been comprehensively discussed and reviewed in various literatures. However, few reviews involving SOC estimation focused on electrochemical mechanism, which gives physical explanations to SOC and becomes most attractive candidate for advanced BMS. For this reason, this paper comprehensively surveys on physics-based SOC algorithms applied in advanced BMS. First, the research progresses of physical SOC estimation methods for lithium-ion batteries are thoroughly discussed and corresponding evaluation criteria are carefully elaborated. Second, future perspectives of the current researches on physics-based battery SOC estimation are presented. The insights stated in this paper are expected to catalyze the development and application of the physics-based advanced BMS algorithms. (c) 2023 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by ELSEVIER B.V. and Science Press. All rights reserved.

Automated summary

This paper presents a comprehensive survey on physics-based state of charge (SOC) algorithms applied in advanced battery management system (BMS). It discusses the research progresses of physical SOC estimation methods for lithium-ion batteries and presents future perspectives for this field.