| contributor author | Zhao, Dengfeng | |
| contributor author | Li, Haiyang | |
| contributor author | Fu, Zhijun | |
| contributor author | Liu, Zhaohui | |
| contributor author | Zhou, Fang | |
| contributor author | Zhong, Yudong | |
| contributor author | He, Wenbin | |
| date accessioned | 2026-08-20T20:54:35Z | |
| date available | 2026-08-20T20:54:35Z | |
| date copyright | 2025/07/30 | |
| date issued | 2025 | |
| identifier other | JTEPBS.TEENG-9086.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4313655 | |
| description abstract | AbstractAccurately estimating the state of charge (SOC) of electric bus batteries can effectively
improve driving safety and mileage. Due to the strong nonlinearity and time-varying
characteristics of batteries, it is difficult to estimate SOC through a ... | |
| publisher | American Society of Civil Engineers | |
| title | State of Charge Estimation for Electric Bus Batteries Based on Deep Learning Model with Parameters Fine-Tuning Method | |
| type | Journal Article | |
| journal volume | 151 | |
| journal issue | 10 | |
| journal title | Journal of Transportation Engineering, Part A: Systems | |
| identifier doi | 10.1061/JTEPBS.TEENG-9086 | |
| journal fristpage | 04025077-1 | |
| journal lastpage | 04025077-12 | |
| page | 12 | |
| tree | Journal of Transportation Engineering, Part A: Systems:;2025:;Volume ( 151 ):;issue: 010 | |
| contenttype | Fulltext | |
