Particle Swarm Optimization for Optimal Powertrain parameters of parallel-series hybrid electric vehicles,"Presenter"
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- 形態
- 価格
- 一般価格(税込):¥1,100 会員価格(税込):¥880
- 文献番号
- 20181826
- 文献・情報種別
- AVEC
No.ThE1-3
- 掲載ページ
- 1-6(Total 6 p)
- 発行年月
- 2018年 7月
- 出版社
- その他・不明
- 言語
- 英語
- イベント
- AVEC '18
書誌事項
| カテゴリ(英) | Hybrid EV Control I 翻訳 |
|---|---|
| 著者(英) | 1) Tianjun Zhu |
| 抄録(英) | This paper proposes a powertrain parameters design approach based on particle swarm optimization (PSO) algorithm. The optimization objective is to optimize transmission ratio and final drive ratio to achieve the minimization of fuel consumption with optimal vehicle performance. The original multi-objective optimization problem is converted into a single-objective problem with a goal-attainment method, and the principal parameters of powertrain are set as the optimized variables by PSO algorithm, with the vehicle performance indexes of parallel-series hybrid electric vehicles (PHEVs) being defined as the constraint conditions. The proposed strategy has been verified by the driving cycle under the MATLAB/Simulink software environment. Simulation results indicate that the proposed PSO-based powertrain parameters optimization method can achieve better fuel efficiency compared with traditional strategies. 翻訳 |