SOC estimation of lithium-ion battery based on AEKF
Aiming at the problem that the noise information is fixed when the extended Kalman filter(EKF) algorithm estimates the state of charge(SOC) of lithium-ion battery, resulting in low estimation accuracy, an adaptive extended Kalman filter(AEKF) algorithm with automatic matching of noise information co...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
National Computer System Engineering Research Institute of China
2023-04-01
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| Series: | Dianzi Jishu Yingyong |
| Subjects: | |
| Online Access: | http://www.chinaaet.com/article/3000160456 |
| _version_ | 1797447928637292544 |
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| author | Wang Xiang Su Jianhui Lai Jidong Zhou Chenguang Su Zhipeng |
| author_facet | Wang Xiang Su Jianhui Lai Jidong Zhou Chenguang Su Zhipeng |
| author_sort | Wang Xiang |
| collection | DOAJ |
| description | Aiming at the problem that the noise information is fixed when the extended Kalman filter(EKF) algorithm estimates the state of charge(SOC) of lithium-ion battery, resulting in low estimation accuracy, an adaptive extended Kalman filter(AEKF) algorithm with automatic matching of noise information covariance is proposed. Firstly, the parameters are identified based on the dual polarization (DP)equivalent circuit model of the battery, and an accurate equivalent model is established. Then, the variation of noise covariance matrix of EKF filtering algorithm and AEKF filtering algorithm and the estimation effect of battery SOC are compared under dynamic stress test(DST) conditions. The results show that AEKF filtering algorithm has higher estimation accuracy. Finally, several groups of different SOC initial deviations are set to verify the strong robustness of AEKF filtering algorithm in estimating battery SOC. |
| first_indexed | 2024-03-09T14:03:01Z |
| format | Article |
| id | doaj.art-7e2d3c09bfa54bb1bdff71bedc3eacd2 |
| institution | Directory Open Access Journal |
| issn | 0258-7998 |
| language | zho |
| last_indexed | 2024-03-09T14:03:01Z |
| publishDate | 2023-04-01 |
| publisher | National Computer System Engineering Research Institute of China |
| record_format | Article |
| series | Dianzi Jishu Yingyong |
| spelling | doaj.art-7e2d3c09bfa54bb1bdff71bedc3eacd22023-11-30T05:41:31ZzhoNational Computer System Engineering Research Institute of ChinaDianzi Jishu Yingyong0258-79982023-04-01494576210.16157/j.issn.0258-7998.2233413000160456SOC estimation of lithium-ion battery based on AEKFWang Xiang0Su Jianhui1Lai Jidong2Zhou Chenguang3Su Zhipeng4(Engineering Research Center of Ministry of Education of Photovoltaic System， Hefei University of Technology， Hefei 230009， China)(Engineering Research Center of Ministry of Education of Photovoltaic System， Hefei University of Technology， Hefei 230009， China)(Engineering Research Center of Ministry of Education of Photovoltaic System， Hefei University of Technology， Hefei 230009， China)(Engineering Research Center of Ministry of Education of Photovoltaic System， Hefei University of Technology， Hefei 230009， China)(Engineering Research Center of Ministry of Education of Photovoltaic System， Hefei University of Technology， Hefei 230009， China)Aiming at the problem that the noise information is fixed when the extended Kalman filter(EKF) algorithm estimates the state of charge(SOC) of lithium-ion battery, resulting in low estimation accuracy, an adaptive extended Kalman filter(AEKF) algorithm with automatic matching of noise information covariance is proposed. Firstly, the parameters are identified based on the dual polarization (DP)equivalent circuit model of the battery, and an accurate equivalent model is established. Then, the variation of noise covariance matrix of EKF filtering algorithm and AEKF filtering algorithm and the estimation effect of battery SOC are compared under dynamic stress test(DST) conditions. The results show that AEKF filtering algorithm has higher estimation accuracy. Finally, several groups of different SOC initial deviations are set to verify the strong robustness of AEKF filtering algorithm in estimating battery SOC.http://www.chinaaet.com/article/3000160456 lithium-ion batterystate of charge estimationdual polarization equivalent circuit modeladaptive extended kalman filter |
| spellingShingle | Wang Xiang Su Jianhui Lai Jidong Zhou Chenguang Su Zhipeng SOC estimation of lithium-ion battery based on AEKF Dianzi Jishu Yingyong lithium-ion battery state of charge estimation dual polarization equivalent circuit model adaptive extended kalman filter |
| title | SOC estimation of lithium-ion battery based on AEKF |
| title_full | SOC estimation of lithium-ion battery based on AEKF |
| title_fullStr | SOC estimation of lithium-ion battery based on AEKF |
| title_full_unstemmed | SOC estimation of lithium-ion battery based on AEKF |
| title_short | SOC estimation of lithium-ion battery based on AEKF |
| title_sort | soc estimation of lithium ion battery based on aekf |
| topic | lithium-ion battery state of charge estimation dual polarization equivalent circuit model adaptive extended kalman filter |
| url | http://www.chinaaet.com/article/3000160456 |
| work_keys_str_mv | AT wangxiang socestimationoflithiumionbatterybasedonaekf AT sujianhui socestimationoflithiumionbatterybasedonaekf AT laijidong socestimationoflithiumionbatterybasedonaekf AT zhouchenguang socestimationoflithiumionbatterybasedonaekf AT suzhipeng socestimationoflithiumionbatterybasedonaekf |