The development and numerical verification of a compromised real time optimal control algorithm for hybrid electric vehicle

Abstract

Hybrid electric vehicles (HEV) have been recognized as a viable technology to significantly improve the fuel economy of on-road vehicles operated in urban areas featuring frequent stop-and-go operation. The optimization of the HEV control strategy is a dynamic optimal problem involving a nonlinear cost function and several nonlinear constraints. To take advantage of the global optimality of dynamic programming (DP) and the real-time capability of the equivalent consumption minimization strategy (ECMS) in optimizing the HEV operation strategy, a model that combines ECMS with DP is proposed in this paper, which is defined as ECMSwDP. Using this approach, the optimal equivalent factor λ for ECMS is derived using DP under various driving conditions and the different grades of synthetic driving cycle. The fuel economy simulated using the ECMSwDP control strategy is comparable to the optimal solution derived using DP. The potential of the real-time control strategy developed using ECMSwDP to improve fuel economy is demonstrated using a transit hybrid electric bus as an example.