Submit your paper 
Download Template JOURNAL DETAIL
Soc Estimation of Li-ion Battery Based on Adaptive CKF Algorithm
Paper Type  |
Contributed Paper |
Title |
Soc Estimation of Li-ion Battery Based on Adaptive CKF Algorithm |
Author |
Zhengjun Huang, Yu Chen and Meifang Zhou |
Email |
465074730@qq.com |
|
Abstract: A second-or der RC equivalent circuit model was established to improve the estimation accuracy of state of charge (SOC) of power Li-ion batteries, and the model parameters were identified by the recursive least square method with forgetting factor (FFRLS). On this basis, an adaptive cubature kalman filter (ACKF) algorithm was proposed to adaptively modify the process noise covariance matrix and the measurement noise covariance matrix to improve the SOC estimation accuracy. Finally, the SOC estimation algorithm was verified by MATLAB simulations. The results show that compared with UKF and CKF algorithms, the proposed algorithm has higher estimation accuracy and robustness, and can meet the application requirements. |
|
Article ID |
e2023063 |
Received Date |
2023-03-17 |
Revised Date |
2023-07-06 |
Accepted Date |
2023-09-01 |
Full Text |
Download |
Keyword |
Li-ion battery, state of charge, second-order RC model, adaptive cubature kalman filter |
Volume |
Vol.50 No.6 (November 2023) |
DOI |
https://doi.org/10.12982/CMJS.2023.063 |
Citation |
Huang Z., Chen Y. and Zhou M., Soc Estimation of Li-ion Battery Based on Adaptive CKF Algorithm, Chiang Mai Journal of Science, 2023; 50(6): e2023063. DOI 10.12982/CMJS.2023.063. |
SDGs |
|
| View:499 Download:324 | |
Copyrights © Since 2021 All Rights Reserved by Chiang Mai Journal of Science