Model-Based Adaptive Joint Estimation of the State of Charge and Capacity for Lithium–Ion Batteries in Their Entire Lifespan
In this paper, a co-estimation scheme of the state of charge (SOC) and available capacity is proposed for lithium−ion batteries based on the adaptive model-based algorithm. A three-dimensional response surface (TDRS) in terms of the open circuit voltage, the SOC and the available capacity...
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| Format: | Article |
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MDPI AG
2020-03-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/6/1410 |
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| author | Zheng Chen Jiapeng Xiao Xing Shu Shiquan Shen Jiangwei Shen Yonggang Liu |
| author_facet | Zheng Chen Jiapeng Xiao Xing Shu Shiquan Shen Jiangwei Shen Yonggang Liu |
| author_sort | Zheng Chen |
| collection | DOAJ |
| description | In this paper, a co-estimation scheme of the state of charge (SOC) and available capacity is proposed for lithium−ion batteries based on the adaptive model-based algorithm. A three-dimensional response surface (TDRS) in terms of the open circuit voltage, the SOC and the available capacity in the scope of whole lifespan, is constructed to describe the capacity attenuation, and the battery available capacity is identified by a genetic algorithm (GA), together with the parameters related to SOC. The square root cubature Kalman filter (SRCKF) is employed to estimate the SOC with the consideration of capacity degradation. The experimental results demonstrate the effectiveness and feasibility of the co-estimation scheme. |
| first_indexed | 2024-04-11T12:51:35Z |
| format | Article |
| id | doaj.art-3f1fd034a382498f99f2cc9dd16c1bab |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T12:51:35Z |
| publishDate | 2020-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-3f1fd034a382498f99f2cc9dd16c1bab2022-12-22T04:23:12ZengMDPI AGEnergies1996-10732020-03-01136141010.3390/en13061410en13061410Model-Based Adaptive Joint Estimation of the State of Charge and Capacity for Lithium–Ion Batteries in Their Entire LifespanZheng Chen0Jiapeng Xiao1Xing Shu2Shiquan Shen3Jiangwei Shen4Yonggang Liu5Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaFaculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, ChinaState Key Laboratory of Mechanical Transmissions & School of Automotive Engineering, Chongqing University, Chongqing 400044, ChinaIn this paper, a co-estimation scheme of the state of charge (SOC) and available capacity is proposed for lithium−ion batteries based on the adaptive model-based algorithm. A three-dimensional response surface (TDRS) in terms of the open circuit voltage, the SOC and the available capacity in the scope of whole lifespan, is constructed to describe the capacity attenuation, and the battery available capacity is identified by a genetic algorithm (GA), together with the parameters related to SOC. The square root cubature Kalman filter (SRCKF) is employed to estimate the SOC with the consideration of capacity degradation. The experimental results demonstrate the effectiveness and feasibility of the co-estimation scheme.https://www.mdpi.com/1996-1073/13/6/1410state of chargeavailable capacityadaptive model-based algorithmsquare root cubature kalman filterjoint estimation |
| spellingShingle | Zheng Chen Jiapeng Xiao Xing Shu Shiquan Shen Jiangwei Shen Yonggang Liu Model-Based Adaptive Joint Estimation of the State of Charge and Capacity for Lithium–Ion Batteries in Their Entire Lifespan Energies state of charge available capacity adaptive model-based algorithm square root cubature kalman filter joint estimation |
| title | Model-Based Adaptive Joint Estimation of the State of Charge and Capacity for Lithium–Ion Batteries in Their Entire Lifespan |
| title_full | Model-Based Adaptive Joint Estimation of the State of Charge and Capacity for Lithium–Ion Batteries in Their Entire Lifespan |
| title_fullStr | Model-Based Adaptive Joint Estimation of the State of Charge and Capacity for Lithium–Ion Batteries in Their Entire Lifespan |
| title_full_unstemmed | Model-Based Adaptive Joint Estimation of the State of Charge and Capacity for Lithium–Ion Batteries in Their Entire Lifespan |
| title_short | Model-Based Adaptive Joint Estimation of the State of Charge and Capacity for Lithium–Ion Batteries in Their Entire Lifespan |
| title_sort | model based adaptive joint estimation of the state of charge and capacity for lithium ion batteries in their entire lifespan |
| topic | state of charge available capacity adaptive model-based algorithm square root cubature kalman filter joint estimation |
| url | https://www.mdpi.com/1996-1073/13/6/1410 |
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