Low-complexity online estimation for LiFePO4 battery state of charge in electric vehicles

JOURNAL OF POWER SOURCES

卷:395

Article

Meng, Jinhao¹  Ricco, Mattia²  Acharya, Anirudh Budnar³  Luo, Guangzhao¹  Swierczynski, Maciej⁴  Stroe, Daniel-Ioan²  Teodorescu, Remus² 

[1] NPU, Sch Automat, Xian 710072, Shaanxi, Peoples R China

[2] Aalborg Univ, Dept Energy Technol, DK-9220 Aalborg, Denmark

[3] Norwegian Univ Sci & Technol, Dept Elect Power Engn, N-7491 Trondheim, Norway

[4] Lithium Balance AS, DK-2765 Smorum, Denmark

关键词: State of charge;    LiFePO4 battery;    Online estimation;    Low-complexity;   

DOI  :  10.1016/j.jpowsour.2018.05.082

来源: Elsevier

【 摘 要 】

This paper proposes a low-complexity online state of charge estimation method for LiFePO4 battery in electrical vehicles. The proposed method is able to achieve accurate state of charge with less computational efforts in comparison with the nonlinear Kalman filters, and also can provide state of health information for battery management system. According to the error analysis of equivalent circuit model with two resistance and capacitance, two proportional-integral filters are designed to compensate the errors from inaccurate state of charge and current measurements, respectively. An error dividing process is proposed to tune the contribution of each filter to the finial estimation results, which enhances the validation and accuracy of the proposed method. Recursive least squares filter can provide the state of health information and updates the parameters of battery model online to eliminate the errors caused by parameters uncertainty. The proposed method is compared with extend Kalman filter in regards to accuracy and execution time. The execution time of the proposed method is measured on Zynq board platform to validate its suitability for online implementation. In this paper, the proposed method is able to obtain less than 1% error for state of charge estimation.

【 授权许可】

Free