4.6 Article

Real-Time Fuel Economy Optimization With Nonlinear MPC for PHEVs

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2016.2517130

关键词

Continuation/Generalized minimum residual (GMRES); fuel economy; nonlinear receding horizon control; plug-in hybrid electric vehicle (PHEV); real-time optimization

资金

  1. National Natural Science Foundation of China [61304128]
  2. Grants-in-Aid for Scientific Research [26289132] Funding Source: KAKEN

向作者/读者索取更多资源

This brief addresses the energy management problem with the framework of receding horizon optimization. For power-split plug-in hybrid electric vehicles (HEVs), the real-time power-split decision is formulated as a nonlinear receding horizon optimization problem. Then, an online iterative algorithm to solve the optimization problem is proposed based on the continuation/generalized minimum residual algorithm. It should be noted that the proposed energy management strategy aims for optimality of the targeted horizon, but the solution is not optimal for the full driving route, unlike many solutions presented using the dynamic programming approaches. At each decision step, only the initial value of the optimal solution is implemented according to the receding horizon optimization approach. Finally, to demonstrate a comparison of the proposed scheme with other schemes, numerical validations conducted on a full-scale GT-SUITE HEV simulator are presented.

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