| Title: |
State of charge estimation of LiFePO4battery in AB hybrid battery packs |
| Authors: |
Cheng, Xingqun, Liu, Xiaolong, Deng, Huanyong, Lu, Jiahuan, Yu, Quanqing |
| Source: |
Jouranl of Energy Storage; February 2025, Vol. 108 Issue: 1 |
| Abstract: |
Breaking the limitations of the conventional single-system battery packs and improving the accuracy of battery state of charge (SOC) estimation are of great significance for the long-term development of new energy vehicles. However, in AB hybrid battery packs incorporating both LiFePO4and LiCoxNiyMn1-x-yO2cells, the estimation of SOC for LiFePO4batteries tends to exhibit significant errors, primarily contributed to the variability of the open circuit voltage (OCV) slope, particularly when the OCV is in the flat region. Therefore, this study proposes to update the SOC estimation algorithm automatically based on the variation of the OCV slope interval and to improve the SOC estimation stability using fusion as well as correction of the initial value. The SOC is estimated in the LiFePO4high slope interval using the unscented Kalman filter. During the LiFePO4flat-slope interval, the estimation method of the LiFePO4cell is mapped using the state of charge of the LiCoxNiyMn1-x-yO2cell which can avoid the effect of error accumulation in the LiFePO4cell. Furthermore, to accelerate the convergence of SOC estimation, the mapping results are employed to adjust the initial value of the unscented Kalman filter at the end of the discharge period. The results show that the proposed method is able to maintain the SOC estimation accuracy of lithium iron phosphate batteries within 1 %， and the combined algorithm can maintain the maximum error within 4 % under the analogue sensor error. |
| Database: |
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