Joint Estimation Method with Multi-Innovation Unscented Kalman Filter Based on Fractional-Order Model for State of Charge and State of Health Estimation

Yonghong Xu, Cheng Li, Xu Wang, Hongguang Zhang (), Fubin Yang, Lili Ma and Yan Wang
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Yonghong Xu: Key Laboratory of Enhanced Heat Transfer and Energy Conservation of MOE, Beijing Key Laboratory of Heat Transfer and Energy Conversion, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
Cheng Li: China Automotive Technology and Research Center Co., Ltd., Tianjin 300300, China
Xu Wang: China Automotive Technology and Research Center Co., Ltd., Tianjin 300300, China
Hongguang Zhang: Key Laboratory of Enhanced Heat Transfer and Energy Conservation of MOE, Beijing Key Laboratory of Heat Transfer and Energy Conversion, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
Fubin Yang: Key Laboratory of Enhanced Heat Transfer and Energy Conservation of MOE, Beijing Key Laboratory of Heat Transfer and Energy Conversion, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
Lili Ma: Key Laboratory of Enhanced Heat Transfer and Energy Conservation of MOE, Beijing Key Laboratory of Heat Transfer and Energy Conversion, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China
Yan Wang: Key Laboratory of Enhanced Heat Transfer and Energy Conservation of MOE, Beijing Key Laboratory of Heat Transfer and Energy Conversion, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China

Sustainability, 2022, vol. 14, issue 23, 1-25

Abstract: This study simulates the polarization effect during the process of battery charging and discharging, and investigates the characteristics of the process. A fractional-order model (FOM) is established and the parameters of the FOM are identified with the adaptive genetic algorithm. As Kalman filter estimation causes error accumulation over time, using the fractional-order multi-innovation unscented Kalman filter (FOMIUKF) is a better choice for state of charge (SOC) estimation. A comparative study shows that the FOMIUKF has higher accuracy. A multiple timescales-based joint estimation algorithm of SOC and state of health is established to improve SOC estimation precision and reduce the amount of computation. The FOMIUKF algorithm is used for SOC estimation, while the UKF algorithm is used for SOH estimation. The joint estimation algorithm is then compared and analyzed alongside other Kalman filter algorithms under different dynamic operating conditions. Experimental results show that the joint estimation algorithm possesses high estimation accuracy with a mean absolute error of under 1% and a root mean square error of 1.35%.

Keywords: fractional-order model; parameter identification; multi-innovation; state of charge; joint estimation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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