Efficient Kalman Filter-Based Battery Pack SOC Estimation Using Bar Delta Filtering
- 提供方法
- 本サイト上にてダウンロード・閲覧可
- 形態
- 価格
- 一般価格(税込):¥1,100 会員価格(税込):¥880
- 文献番号
- 20266078
- 文献・情報種別
- 学術講演会予稿集(秋)
No.108-26
- 掲載ページ
- 1-7(Total 7 p)
- 発行年月
- 2026年 10月
- 出版社
- (公社)自動車技術会
- 言語
- 英語
- イベント
- 2026年秋季大会
書誌事項
| 著者 | 1) Seyedmehdi Hosseininasab, 2) Changwei Lin, 3) Lennart Bauer, 4) Tsuyoshi Horiba, 5) Yasutaka Ikawa |
|---|---|
| 著者(英) | 1) Seyedmehdi Hosseininasab, 2) Changwei Lin, 3) Lennart Bauer, 4) Tsuyoshi Horiba, 5) Yasutaka Ikawa |
| 勤務先 | 1) FEV Europe, 2) FEV Europe, 3) FEV Europe, 4) FEV Japan, 5) FEV Japan |
| 勤務先(英) | 1) FEV Europe, 2) FEV Europe, 3) FEV Europe, 4) FEV Japan, 5) FEV Japan |
| 抄録(英) | Accurate estimation of SOC in lithium-ion battery packs is essential for safe reliable and optimized BMS in electric vehicles and energy storage. This study presents an efficient framework combining a lightweight Kalman filter with the Bar-Delta method for series-connected LFP cells. A simulation model with realistic cell-to-cell variations evaluates performance. The method estimates pack average SOC and cell deviations with lower computational cost. Results show comparable accuracy to full Kalman filtering while significantly reducing computation, enabling real-time embedded applications. It is suitable for resource-constrained hardware and scalable pack monitoring deployments today. 翻訳 |