Nonlinear model predictive control of battery electric vehicle with slope information

German Valenzuela, Taketoshi Kawabe, Masakazu Mukai

研究成果: 著書/レポートタイプへの貢献会議での発言

3 引用 (Scopus)

抜粋

This paper introduces a model predictive control approach for the energy management problem of a battery electric vehicle (BEV) system with slope information. The features of this study are as follows. The BEV physical constraints and the battery state of charge (SOC) are addressed in the cost function of optimal control problem with a model of the battery electric vehicle system. Nonlinear real-time optimal control problem in the BEV system is solved using numerical computation method: continuation and generalized minimum residual method. This approach in the BEV system uses terrain information from digital maps to calculate the desired SOC for better recuperation of free braking energy. We conclude that the model predictive control approach is effective for the application of battery management systems for BEV and has the potential for real-time implementation. The effectiveness of the proposed algorithm in the energy management of BEVs is compared with a proportional-integral control method approach.

元の言語英語
ホスト出版物のタイトル2014 IEEE International Electric Vehicle Conference, IEVC 2014
出版者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781479960750
DOI
出版物ステータス出版済み - 1 1 2014
イベント2014 IEEE International Electric Vehicle Conference, IEVC 2014 - Florence, イタリア
継続期間: 12 17 201412 19 2014

出版物シリーズ

名前2014 IEEE International Electric Vehicle Conference, IEVC 2014

その他

その他2014 IEEE International Electric Vehicle Conference, IEVC 2014
イタリア
Florence
期間12/17/1412/19/14

    フィンガープリント

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Automotive Engineering

これを引用

Valenzuela, G., Kawabe, T., & Mukai, M. (2014). Nonlinear model predictive control of battery electric vehicle with slope information. : 2014 IEEE International Electric Vehicle Conference, IEVC 2014 [7056104] (2014 IEEE International Electric Vehicle Conference, IEVC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEVC.2014.7056104