State of charge estimation framework for lithium-ion batteries based on square root cubature Kalman filter under wide operation temperature range
Jiangwei Shen
Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China
Search for more papers by this authorJian Xiong
Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China
Search for more papers by this authorXing Shu
Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China
Search for more papers by this authorGuang Li
School of Engineering and Materials Science, Queen Mary University of London, London, UK
Search for more papers by this authorYuanjian Zhang
School of Mechanical and Aerospace Engineering, Queen's University Belfast, Belfast, UK
Search for more papers by this authorCorresponding Author
Zheng Chen
Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China
School of Engineering and Materials Science, Queen Mary University of London, London, UK
Correspondence
Zheng Chen, Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China.
Email: [email protected]
Yonggang Liu, State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing 400044, China.
Email: [email protected]
Search for more papers by this authorCorresponding Author
Yonggang Liu
State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing, China
Correspondence
Zheng Chen, Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China.
Email: [email protected]
Yonggang Liu, State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing 400044, China.
Email: [email protected]
Search for more papers by this authorJiangwei Shen
Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China
Search for more papers by this authorJian Xiong
Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China
Search for more papers by this authorXing Shu
Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China
Search for more papers by this authorGuang Li
School of Engineering and Materials Science, Queen Mary University of London, London, UK
Search for more papers by this authorYuanjian Zhang
School of Mechanical and Aerospace Engineering, Queen's University Belfast, Belfast, UK
Search for more papers by this authorCorresponding Author
Zheng Chen
Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China
School of Engineering and Materials Science, Queen Mary University of London, London, UK
Correspondence
Zheng Chen, Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China.
Email: [email protected]
Yonggang Liu, State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing 400044, China.
Email: [email protected]
Search for more papers by this authorCorresponding Author
Yonggang Liu
State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing, China
Correspondence
Zheng Chen, Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China.
Email: [email protected]
Yonggang Liu, State Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing 400044, China.
Email: [email protected]
Search for more papers by this authorFunding information: H2020 Marie Skłodowska-Curie Actions, Grant/Award Number: 845102; National Natural Science Foundation of China, Grant/Award Number: 61763021; National Key R&D Program of China, Grant/Award Numbers: 2018YFB0104500, 2018YFB0104000
Summary
Due to the significant influence of temperature on battery charging and discharging performance, exact evaluation of state of charge (SOC) under complex temperature environment becomes increasingly important. This paper develops an advanced framework to estimate the SOC for lithium-ion batteries with consideration of temperature variation. First, an accurate electrical model with wide temperature compensation is established, and a series of experiments are carried out under wide range time-varying temperature from −20°C to 60°C. Then, the genetic algorithm is leveraged to identify the temperature-dependent model parameters. On this basis, the battery SOC is accurately estimated based on the square root cubature Kalman filter algorithm. Finally, the availability of the proposed method at different temperatures is validated through a complicated mixed working cycle test, and the experimental results manifest that the devised framework can accurately evaluate SOC under wide time-varying temperature range with the maximum error of less than 2%.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding authors upon reasonable request.
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