LAPSE:2023.27579
Published Article
LAPSE:2023.27579
Estimation for Battery State of Charge Based on Temperature Effect and Fractional Extended Kalman Filter
April 4, 2023
The electric vehicle has become an important development direction of the automobile industry, and the lithium-ion power battery is the main energy source of electric vehicles. The accuracy of state of charge (SOC) estimation directly affects the performance of the vehicle. In this paper, the first order fractional equivalent circuit model of a lithium iron phosphate battery was established. Battery capacity tests with different charging and discharging rates and open circuit voltage tests were carried out under different ambient temperatures. The conversion coefficient of charging and discharging capacity and the simplified open circuit voltage model considering the hysteresis characteristics of the battery were proposed. The parameters of the first order fractional equivalent circuit model were identified by using a particle swarm optimization algorithm with dynamic inertia weight. Finally, the recursive formula of a fractional extended Kalman filter was derived, and the battery SOC was estimated under continuous Dynamic Stress Test (DST) conditions. The results show that the estimation method has high accuracy and strong robustness.
Keywords
extended Kalman filter, fractional order, LiFePO4 battery, parameter identification, SOC estimation
Suggested Citation
Chang C, Zheng Y, Yu Y. Estimation for Battery State of Charge Based on Temperature Effect and Fractional Extended Kalman Filter. (2023). LAPSE:2023.27579
Author Affiliations
Chang C: College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China [ORCID]
Zheng Y: College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China [ORCID]
Yu Y: College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Journal Name
Energies
Volume
13
Issue
22
Article Number
E5947
Year
2020
Publication Date
2020-11-14
Published Version
ISSN
1996-1073
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PII: en13225947, Publication Type: Journal Article
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doi:10.3390/en13225947
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