An adaptive sliding mode observer for lithium-ion battery state of charge and state of health estimation in electric vehicles. (September 2016)

• Record Type: Journal Article
• Authors: Du, Jiani; Liu, Zhitao; Wang, Youyi; Wen, Changyun
• Is Part Of: Control engineering practice. Volume 54(2016)
• Page Start: 81
• Page End: 90
• Publication Date: 2016-09
• Subjects: Adaptive sliding mode observer -- State of charge (SOC) estimation -- State of health (SOH) estimation; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2016.05.014
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: As the demand for electric vehicle (EV)'s remaining operation range and power supply life, Lithium-ion (Li-ion) battery state of charge (SOC) and state of health (SOH) estimation are important in battery management system (BMS). In this paper, a proposed adaptive observer based on sliding mode method is used to estimate SOC and SOH of the Li-ion battery. An equivalent circuit model with two resistor and capacitor (RC) networks is established, and the model equations in specific structure with uncertainties are given and analyzed. The proposed adaptive sliding mode observer is applied to estimate SOC and SOH based on the established battery model with uncertainties, and it can avoid the chattering effects and improve the estimation performance. The experiment and simulation estimation results show that the proposed adaptive sliding mode observer has good performance and robustness on battery SOC and SOH estimation. Highlights: A sliding mode observer with adaptive gain for state of charge (SOC) estimation of lithium-ion battery is proposed. An adaptive sliding mode observer is proposed to estimate state of charge (SOC) and state of health (SOH) of lithium-ion battery. The above two proposed observers can avoid the chattering effects and improve the estimation performance. The experimental results of a lithium-ion battery verify the effectiveness of the proposed two observers.