Model Predictive Speed and Headway Control with Energy Optimization for a Series Hybrid Vehicle with Range Extender

In this paper, a model predictive speed and headway control (MPSHC) with multi-input and multi-output (MIMO) is developed for a series hybrid vehicle with range extender (BEVx). The MPSHC calculates the optimal solutions of the efficient driving strategy and the efficient power supply, with the vehicle longitudinal dynamics and battery dynamics. It takes the driver’s demand, the legal speed limit, the driving behavior of the preceding object vehicle, the topography and the state of charge (SoC) into account. The energy consumption as the objective is minimized in the predictive horizon. The simulation results show that the proposed MPSHC algorithm has a good energy saving potential, compared with the conventional Adaptive Cruise Control (ACC) and the simple energy supply strategy.