A hybrid observer for SOC estimation of lithium-ion battery based on a coupled electrochemical-thermal model. Issue 15 (8th December 2019)

• Record Type: Journal Article
• Authors: Xu, Xing; Lin, Yuzhen; Wang, Feng; Yang, Shichun; Zhou, Zhiguang
• Is Part Of: International journal of green energy. Volume 16:Issue 15(2019)
• Page Start: 1527
• Page End: 1538
• Publication Date: 2019-12-08
• Subjects: A coupled electrochemical-thermal model -- a hybrid observer -- extended Kalman filter -- lithium-ion battery -- smooth variable structure filter -- state of charge estimation; Power resources -- Research -- Periodicals; Energy industries -- Periodicals; Energy development -- Periodicals; 333.79
• DOI: 10.1080/15435075.2019.1671423
• Languages: English
• ISSNs: 1543-5075

Abstract

ABSTRACT: An accurate prediction of the state of charge (SOC) of lithium-ion battery provides crucial information for the Battery Management System (BMS). In this paper, a simplified uneven electrochemical model coupled to a bulk thermal model of Lithium-ion battery is built up. The parameters of battery model identified in previous research can provide a more accurate description of the battery dynamic characteristics. This implementation of the coupled model is then applied to amalgamation with the extend Kalman filter combined with smoothing variable structure filter (EK-SVSF) to obtain an accurate and robust SOC result. MATLAB/Simulink and experiments, including 1C pulse discharge and NEDC cycle tests are adopted to evaluate the performance of the proposed hybrid algorithm. The simulation results indicate that the SOC error is less than 2%, therefore the algorithm is suitable for the new energy vehicle power BMS.