Application of Battery Life Prediction Technology in EMUs
Reliability of electric multiple unit (EMU) batteries is related to the safety of trains. However, due to the unique memory effect of alkaline cadmium-nickel battery, there are few life prediction algorithms suitable for batteries in EMU, and there is currently no practical application in China. To...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Control and Information Technology
2021-01-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2021.05.400 |
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| Summary: | Reliability of electric multiple unit (EMU) batteries is related to the safety of trains. However, due to the unique memory effect of alkaline cadmium-nickel battery, there are few life prediction algorithms suitable for batteries in EMU, and there is currently no practical application in China. To this end, the paper proposes a battery remaining useful life prediction algorithm based on particle filter-extended Kalman filter (PF-EKF). The algorithm is compared to particle filter (PF) and extended Kalman filter (EKF). Experimental results show that the PF-EKF algorithm is simple in structure, easy to implement, and has the highest accuracy of battery life prediction, with an accuracy rate of 96.691%. |
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| ISSN: | 2096-5427 |