Sequential Monte Carlo based Technique for SOC Estimation of LiFePO4 Battery Pack for Electric Vehicles
文献类型：会议论文
| 作者 | Taimoor Zahid; Feiyan Qin; Weimin Li; Kun Xu; Yimin Zhou |
| 出版日期 | 2016 |
| 会议名称 | ICIA 2016 |
| 会议地点 | 浙江宁波 |
| 英文摘要 | Battery energy storage management for electric vehicles and hybrid electric vehicles is the most critical enabling technology. A battery system is a complex electrochemical phenomenon whose performance degrades with ageing and the existence of varying material design. Moreover, it is very tedious and computationally very complex for monitoring and controlling the internal state of battery’s electrochemical systems. This paper presents a particle filtering method for state of charge estimation of LiFePO4 battery. Using different open circuit voltages the state of charge is estimated with respect to the estimation accuracy and convergence. It was demonstrated that particle filter can be utilized to estimate the SOC for Li ion battery. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/10084]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2016 |
| 推荐引用方式 GB/T 7714 | Taimoor Zahid,Feiyan Qin,Weimin Li,et al. Sequential Monte Carlo based Technique for SOC Estimation of LiFePO4 Battery Pack for Electric Vehicles[C]. 见:ICIA 2016. 浙江宁波. |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。