Parameter Identification of Lithium-ion Battery Equivalent Circuit Model Based on Limited Memory Recursive Least Squares Algorithm with Variable Forgetting Factor
Equivalent circuit method is the most widely used methodology in dynamic modeling of lithium-ion battery. An equivalent circuit with second-order RC network is used to model lithium-ion battery, and a limited memory recursive least square with variable forgetting factor (VFF-LMRLS) is proposed to id...
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| Vydané v: | Journal of physics. Conference series Ročník 2246; číslo 1; s. 12090 - 12099 |
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| Hlavní autori: | , , , , |
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| Jazyk: | English |
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Bristol
IOP Publishing
01.04.2022
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| ISSN: | 1742-6588, 1742-6596 |
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| Abstract | Equivalent circuit method is the most widely used methodology in dynamic modeling of lithium-ion battery. An equivalent circuit with second-order RC network is used to model lithium-ion battery, and a limited memory recursive least square with variable forgetting factor (VFF-LMRLS) is proposed to identify the model parameters in this paper. Firstly, based on the current and voltage data measured from the battery cyclic discharging experiment, the VFF-LMRLS algorithm is used to identify the time-varying parameters of equivalent circuit model. Then, the model verification system is constructed by taking the average value of the identification results in the stable stage as the component parameter value of the equivalent circuit. Finally, through the comparative experiment and analysis with the variable forgetting factor RLS (VFFRLS), it is verified that the terminal voltage error of the proposed method is smaller, indicating that the identified model parameters are closer to the actual parameters. |
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| AbstractList | Equivalent circuit method is the most widely used methodology in dynamic modeling of lithium-ion battery. An equivalent circuit with second-order RC network is used to model lithium-ion battery, and a limited memory recursive least square with variable forgetting factor (VFF-LMRLS) is proposed to identify the model parameters in this paper. Firstly, based on the current and voltage data measured from the battery cyclic discharging experiment, the VFF-LMRLS algorithm is used to identify the time-varying parameters of equivalent circuit model. Then, the model verification system is constructed by taking the average value of the identification results in the stable stage as the component parameter value of the equivalent circuit. Finally, through the comparative experiment and analysis with the variable forgetting factor RLS (VFFRLS), it is verified that the terminal voltage error of the proposed method is smaller, indicating that the identified model parameters are closer to the actual parameters. |
| Author | Yin, Jingyuan Sun, Longfei Wei, Tongzhen Peng, Xianghua Ye, Zeyu |
| Author_xml | – sequence: 1 givenname: Xianghua surname: Peng fullname: Peng, Xianghua organization: Institute of Electrical Engineering, Chinese Academy of Sciences , China – sequence: 2 givenname: Jingyuan surname: Yin fullname: Yin, Jingyuan organization: School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences , China – sequence: 3 givenname: Longfei surname: Sun fullname: Sun, Longfei organization: School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences , China – sequence: 4 givenname: Zeyu surname: Ye fullname: Ye, Zeyu organization: School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences , China – sequence: 5 givenname: Tongzhen surname: Wei fullname: Wei, Tongzhen organization: School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences , China |
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| SubjectTerms | Algorithms Dynamic models Electric potential Equivalent circuits Least squares Lithium Lithium-ion batteries Parameter identification Physics Rechargeable batteries Voltage |
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| Title | Parameter Identification of Lithium-ion Battery Equivalent Circuit Model Based on Limited Memory Recursive Least Squares Algorithm with Variable Forgetting Factor |
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