Parameter identification and state-of-charge estimation approach for enhanced lithium-ion battery equivalent circuit model considering influence of ambient temperatures

doi:10.1088/1674-1056/ab3af5

中国物理B ›› 2019, Vol. 28 ›› Issue (10): 108201-108201.doi: 10.1088/1674-1056/ab3af5

• INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇下一篇

Parameter identification and state-of-charge estimation approach for enhanced lithium-ion battery equivalent circuit model considering influence of ambient temperatures

Hui Pang(庞辉), Lian-Jing Mou(牟联晶), Long Guo(郭龙)

School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China

收稿日期:2019-05-29 修回日期:2019-07-24 出版日期:2019-10-05 发布日期:2019-10-05
通讯作者: Hui Pang E-mail:huipang@163.com
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No. 51675423).

Parameter identification and state-of-charge estimation approach for enhanced lithium-ion battery equivalent circuit model considering influence of ambient temperatures

Hui Pang(庞辉), Lian-Jing Mou(牟联晶), Long Guo(郭龙)

School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China

Received:2019-05-29 Revised:2019-07-24 Online:2019-10-05 Published:2019-10-05
Contact: Hui Pang E-mail:huipang@163.com
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No. 51675423).

摘要/Abstract

摘要： It is widely accepted that the variation of ambient temperature has great influence on the battery model parameters and state-of-charge (SOC) estimation, and the accurate SOC estimation is a significant issue for developing the battery management system in electric vehicles. To address this problem, in this paper we propose an enhanced equivalent circuit model (ECM) considering the influence of different ambient temperatures on the open-circuit voltage for a lithium-ion battery. Based on this model, the exponential-function fitting method is adopted to identify the battery parameters according to the test data collected from the experimental platform. And then, the extended Kalman filter (EKF) algorithm is employed to estimate the battery SOC of this battery ECM. The performance of the proposed ECM is verified by using the test profiles of hybrid pulse power characterization (HPPC) and the standard US06 driving cycles (US06) at various ambient temperatures, and by comparing with the common ECM with a second-order resistance capacitor. The simulation and experimental results show that the enhanced battery ECM can improve the battery SOC estimation accuracy under different operating conditions.

关键词: lithium-ion battery, parameter identification, state of charge, ambient temperature

Abstract: It is widely accepted that the variation of ambient temperature has great influence on the battery model parameters and state-of-charge (SOC) estimation, and the accurate SOC estimation is a significant issue for developing the battery management system in electric vehicles. To address this problem, in this paper we propose an enhanced equivalent circuit model (ECM) considering the influence of different ambient temperatures on the open-circuit voltage for a lithium-ion battery. Based on this model, the exponential-function fitting method is adopted to identify the battery parameters according to the test data collected from the experimental platform. And then, the extended Kalman filter (EKF) algorithm is employed to estimate the battery SOC of this battery ECM. The performance of the proposed ECM is verified by using the test profiles of hybrid pulse power characterization (HPPC) and the standard US06 driving cycles (US06) at various ambient temperatures, and by comparing with the common ECM with a second-order resistance capacitor. The simulation and experimental results show that the enhanced battery ECM can improve the battery SOC estimation accuracy under different operating conditions.

Key words: lithium-ion battery, parameter identification, state of charge, ambient temperature

中图分类号: (Lithium-ion batteries)

82.47.Aa

07.05.Tp (Computer modeling and simulation) 88.85.Hj (Electric vehicles (EVs))

庞辉, 牟联晶, 郭龙. Parameter identification and state-of-charge estimation approach for enhanced lithium-ion battery equivalent circuit model considering influence of ambient temperatures[J]. 中国物理B, 2019, 28(10): 108201-108201.

Hui Pang(庞辉), Lian-Jing Mou(牟联晶), Long Guo(郭龙). Parameter identification and state-of-charge estimation approach for enhanced lithium-ion battery equivalent circuit model considering influence of ambient temperatures[J]. Chin. Phys. B, 2019, 28(10): 108201-108201.

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Parameter identification and state-of-charge estimation approach for enhanced lithium-ion battery equivalent circuit model considering influence of ambient temperatures

Parameter identification and state-of-charge estimation approach for enhanced lithium-ion battery equivalent circuit model considering influence of ambient temperatures

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