State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles
AbstractSate of charge (SOC) accurate estimation is one of the most important functions in a battery management system for battery packs used in electrical vehicles. This paper focuses on battery SOC estimation and its issues and challenges by exploring different existing estimation methodologies. The key technologies of lithium-ion battery state estimation methodologies of the electrical vehicles categorized under five groups, such as the conventional method, adaptive filter algorithm, learning algorithm, nonlinear observer, and the hybrid method, are explored in an in-depth analysis. Lithium-ion battery characteristic, battery model, estimation algorithm, and cell unbalancing are the most important factors that affect the accuracy and robustness of SOC estimation. Finally, this paper concludes with the challenges of SOC estimation and suggests other directions for possible research efforts. View Full-Text
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Zhang, R.; Xia, B.; Li, B.; Cao, L.; Lai, Y.; Zheng, W.; Wang, H.; Wang, W. State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles. Energies 2018, 11, 1820.
Zhang R, Xia B, Li B, Cao L, Lai Y, Zheng W, Wang H, Wang W. State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles. Energies. 2018; 11(7):1820.Chicago/Turabian Style
Zhang, Ruifeng; Xia, Bizhong; Li, Baohua; Cao, Libo; Lai, Yongzhi; Zheng, Weiwei; Wang, Huawen; Wang, Wei. 2018. "State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles." Energies 11, no. 7: 1820.
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