State-of-Health Estimation Based on Differential Temperature for Lithium Ion Batteries
State-of-health (SOH) estimation is necessary for lithium ion batteries due to ineluctable battery ageing. Existing SOH estimation methods mainly focus on voltage characteristics without considering temperature variation in the process of health degradation. In this article, we propose a novel SOH e...
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| Published in | IEEE transactions on power electronics Vol. 35; no. 10; pp. 10363 - 10373 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.10.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | State-of-health (SOH) estimation is necessary for lithium ion batteries due to ineluctable battery ageing. Existing SOH estimation methods mainly focus on voltage characteristics without considering temperature variation in the process of health degradation. In this article, we propose a novel SOH estimation method based on battery surface temperature. The differential temperature curves during constant charging are analyzed and found to be strongly related to SOH. Part of the differential temperature curves in a voltage range is adopted to establish a relationship with SOH using support vector regression. The influence of battery discrepancy, voltage range, and sampling step are systematically discussed and the best combination of voltage range and sampling step is determined using leave-one-out validation. The proposed method is then validated and compared with an incremental capacity analysis (ICA)-based SOH estimation method using the Oxford and NASA datasets, which were collected from different cells under different conditions, respectively. The results show that the proposed method is capable of estimating SOH with the root-mean-square error less than 3.62% and 2.49%, respectively. In addition, the proposed method can improve the overall SOH estimation accuracy and robustness by combining with the ICA-based method with little computational burden. |
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| AbstractList | State-of-health (SOH) estimation is necessary for lithium ion batteries due to ineluctable battery ageing. Existing SOH estimation methods mainly focus on voltage characteristics without considering temperature variation in the process of health degradation. In this article, we propose a novel SOH estimation method based on battery surface temperature. The differential temperature curves during constant charging are analyzed and found to be strongly related to SOH. Part of the differential temperature curves in a voltage range is adopted to establish a relationship with SOH using support vector regression. The influence of battery discrepancy, voltage range, and sampling step are systematically discussed and the best combination of voltage range and sampling step is determined using leave-one-out validation. The proposed method is then validated and compared with an incremental capacity analysis (ICA)-based SOH estimation method using the Oxford and NASA datasets, which were collected from different cells under different conditions, respectively. The results show that the proposed method is capable of estimating SOH with the root-mean-square error less than 3.62% and 2.49%, respectively. In addition, the proposed method can improve the overall SOH estimation accuracy and robustness by combining with the ICA-based method with little computational burden. |
| Author | Shen, Weixiang Xiong, Rui Tian, Jinpeng |
| Author_xml | – sequence: 1 givenname: Jinpeng surname: Tian fullname: Tian, Jinpeng email: jtian@swin.edu.au organization: Department of Vehicle Engineering, School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China – sequence: 2 givenname: Rui orcidid: 0000-0003-4608-7597 surname: Xiong fullname: Xiong, Rui email: rxiong@bit.edu.cn organization: Department of Vehicle Engineering, School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China – sequence: 3 givenname: Weixiang orcidid: 0000-0002-4666-5126 surname: Shen fullname: Shen, Weixiang email: wshen@swin.edu.au organization: Engineering and Technology, Faculty of Science, Swinburne University of Technology, Melbourne, VIC, Australia |
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| Snippet | State-of-health (SOH) estimation is necessary for lithium ion batteries due to ineluctable battery ageing. Existing SOH estimation methods mainly focus on... |
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| SubjectTerms | Aging Batteries Battery ageing battery management Degradation differential temperature Differential thermal analysis Electric potential Estimation Ions Lithium lithium ion battery Lithium-ion batteries Rechargeable batteries Regression analysis Robustness (mathematics) Sampling state-of-health Support vector machines Temperature measurement Voltage |
| Title | State-of-Health Estimation Based on Differential Temperature for Lithium Ion Batteries |
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