Optimal Energy Management and Velocity Control of Hybrid Electric Vehicles

An assessment study of a novel approach is presented that combines discrete state-space Dynamic Programming and Pontryagin's Maximum Principle for online optimal control of hybrid electric vehicles (HEV). In addition to electric energy storage, engine state and gear, kinetic energy, and travel time are considered states in this paper. After presenting the corresponding model using a parallel HEV as an example, a benchmark method with Dynamic Programming is introduced which is used to show the solution quality of the novel approach. It is illustrated that the proposed method yields a close-to-optimal solution by solving the optimal control problem over one hundred thousand times faster than the benchmark method. Finally, a potential online usage is assessed by comparing solution quality and calculation time with regard to the quantization of the state space.