A Sliding Mode Observer SOC Estimation Method Based on Parameter Adaptive Battery Model. (June 2016)

• Record Type: Journal Article
• Authors: Ning, Bo; Xu, Jun; Cao, Binggang; Wang, Bin; Xu, Guangcan
• Is Part Of: Energy procedia. Volume 88(2016)
• Page Start: 619
• Page End: 626
• Publication Date: 2016-06
• Subjects: battery model -- parameter adaptive battery model -- sliding mode observer -- SOC estimation; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2016.06.088
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: Errors of a battery model will dramatically enlarge as the internal parameters of a battery varying. To reduce the systematic errors, a parameter adaptive battery model is proposed. Based on it, sliding mode algorithm is adopted to estimate the SOC of a battery. The experimental platform is constructed and the UDDS driving cycles is used to verify the method. The results show the error of SOC estimation is less than 2% and it indicates the monitoring algorithm is of great value to power batteries which are generally used in variable environment.