| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1508869 | Energy Procedia | 2016 | 8 Pages |
Abstract
Errors of a battery model will dramatically enlarge as the internal parameters of a battery varying. To reduce the systematic errors, a parameter adaptive battery model is proposed. Based on it, sliding mode algorithm is adopted to estimate the SOC of a battery. The experimental platform is constructed and the UDDS driving cycles is used to verify the method. The results show the error of SOC estimation is less than 2% and it indicates the monitoring algorithm is of great value to power batteries which are generally used in variable environment.
Related Topics
Physical Sciences and Engineering
Energy
Energy (General)
Authors
Bo Ning, Jun Xu, Binggang Cao, Bin Wang, Guangcan Xu,