A Novel Multi-model Probability Based Battery State-of-charge Fusion Estimation Approach. (June 2016)

• Record Type: Journal Article
• Authors: Mu, Hao; Xiong, Rui; Sun, Fengchun
• Is Part Of: Energy procedia. Volume 88(2016)
• Page Start: 840
• Page End: 846
• Publication Date: 2016-06
• Subjects: Electric vehicles -- batteries -- state estimation -- multi-model probability -- H infinity; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2016.06.061
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: Accurate state of charge (SoC) estimation is very important for managing battery with safety and efficiency. In order to improve the reliability and redundancy of the SoC estimation, the multi-model probability fusion estimation (MMPFE) method is presented. Considering that the estimation results being dependent on models, the MMPFE method is utilized to fuse the SoC results gained by different equivalent circuit models (ECMs). LFP type battery are tested to verify the effectiveness of the method. Results indicate that the proposed approach can achieve accurate battery SoC estimation with good robust and reliability.