Research progress of SOC estimation methods of power lithium battery for energy storage

Jian Huang; Keqin Ji; Yuxiao Jiang; Weiming Chen; Yihang Liu

doi:10.1117/12.2641085

19 October 2022 Research progress of SOC estimation methods of power lithium battery for energy storage

Jian Huang, Keqin Ji, Yuxiao Jiang, Weiming Chen, Yihang Liu

Proceedings Volume 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering; 1229451 (2022) https://doi.org/10.1117/12.2641085
Event: 7th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2022), 2022, Xishuangbanna, China

Abstract

In order to meet the working requirements of power lithium battery energy storage system and provide the necessary basis for energy conversion and distribution, it is imperative for battery management system (BMS) to accurately estimate state of charge (SOC) of battery pack. This paper systematically shows the significance and basic theory of SOC estimation, summarizes and compares advantages and disadvantages of existing methods such as open circuit voltage method, support vector regression and system filtering method, even puts forward the development trend of SOC estimation methods in the future.

Citation Download Citation

Jian Huang, Keqin Ji, Yuxiao Jiang, Weiming Chen, and Yihang Liu "Research progress of SOC estimation methods of power lithium battery for energy storage", Proc. SPIE 12294, 7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, 1229451 (19 October 2022); https://doi.org/10.1117/12.2641085

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available