Battery (electricity)

Quantum mechanics

Algorithm

Control (management)

Voltage

Composite number

Engineering

State of charge

Materials science

Applied mathematics

Power (physics)

Computer science

Factor (programming language)

Current (fluid)

Thermodynamics

Physics

Mathematics

Artificial intelligence

Kalman filter

Programming language

Control theory (sociology)

Ampere

State (computer science)

Electrical engineering

International Journal of Energy Research

International Journal of Energy ResearchVolume 44, Issue 14 p. 11385-11404 RESEARCH ARTICLE A novel practical state of charge estimation method: an adaptive improved ampere-hour method based on composite correction factor Xin Xiong, School of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaSearch for more papers by this authorShun-Li Wang, Corresponding Author 497420789@qq.com orcid.org/0000-0003-0485-8082 School of Information Engineering, Southwest University of Science and Technology, Mianyang, China Correspondence Shun-Li Wang. School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China. Email: 497420789@qq.comSearch for more papers by this authorCarlos Fernandez, School of Pharmacy and Life Sciences, Robert Gordon University, Aberdeen, UKSearch for more papers by this authorChun-Mei Yu, School of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaSearch for more papers by this authorChuan-Yun Zou, School of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaSearch for more papers by this authorCong Jiang, orcid.org/0000-0002-7654-0375 School of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaSearch for more papers by this author Xin Xiong, School of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaSearch for more papers by this authorShun-Li Wang, Corresponding Author 497420789@qq.com orcid.org/0000-0003-0485-8082 School of Information Engineering, Southwest University of Science and Technology, Mianyang, China Correspondence Shun-Li Wang. School of Information Engineering, Southwest University of Science and Technology, Mianyang 621010, China. Email: 497420789@qq.comSearch for more papers by this authorCarlos Fernandez, School of Pharmacy and Life Sciences, Robert Gordon University, Aberdeen, UKSearch for more papers by this authorChun-Mei Yu, School of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaSearch for more papers by this authorChuan-Yun Zou, School of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaSearch for more papers by this authorCong Jiang, orcid.org/0000-0002-7654-0375 School of Information Engineering, Southwest University of Science and Technology, Mianyang, ChinaSearch for more papers by this author First published: 20 August 2020 https://doi.org/10.1002/er.5758Citations: 4 Funding information: National Natural Science Foundation of China, Grant/Award Number: 61801407 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Summary The research of the real-time state of charge (SOC) estimation method for lithium-ion battery is developing towards the trend of model diversification and algorithm complexity. However, due to the limitation of computing ability in the actual battery management system, the traditional ampere-hour (Ah) method is still widely used. First, temperature, charge-discharge current, and battery aging are considered as the main factors, which affect the estimation accuracy of the Ah method under the condition that detection accuracy of the current sensor is determined. Second, the relationship between the SOC and battery open-circuit voltage at different temperatures is analyzed, which is used to modify the initial SOC. Third, the influence mechanism of main factors on the effect of the Ah method is analyzed, and proposes a capacity composite correction factor to reflect the influence of charge-discharge efficiency, coulomb efficiency, and battery aging comprehensively, and then update its value in real-time. Lastly, the adaptive improved Ah formula and the complete SOC estimation model is designed, and the estimation effect of this model is verified by comparing with other SOC estimation methods in the experiment of dynamic cycle test. The results show that the estimation error of the adaptive improved method is less than 2% under two comprehensive working conditions, while the error of the traditional method is 5% to 10%, and compared with an extended kalman filter algorithm, it also gets a better SOC estimation performance, which proves that this method is scientific and effective. Citing Literature Volume44, Issue14November 2020Pages 11385-11404 RelatedInformation

A novel practical state of charge estimation method: an adaptive improved ampere‐hour method based on composite correction factor