An energy management strategy (EMS) considering both optimality and real-time performance has become a challenge for the development of hybrid electric vehicles (HEVs) in recent years. Previous EMSes based on the optimal control theory minimize the fuel consumption, but cannot be directly implemented in real-time because of the requirement for a prior knowledge of the entire driving cycle. This paper presents an innovative design concept and method to obtain a power management strategy for HEVs, which is independent of future driving conditions. A quadratic performance index is designed to ensure the vehicle drivability, maintain the battery energy sustainability and average and smooth the engine power and motor power to indirectly reduce fuel consumption. To further improve the fuel economy, two rules are adopted to avoid the inefficient engine operation by switching control modes between the electric and hybrid modes according to the required driving power. The derived power of the engine and motor are related to current vehicle velocity and battery residual energy, as well as their desired values. The simulation results over different driving cycles in Advanced Vehicle Simulator (ADVISOR) show that the proposed strategy can significantly improve the fuel economy, which is very close to the optimal strategy based on Pontryagin’s minimum principle.

This paper presents a single-degree-of-freedom energy optimization strategy to solve the energy management problem existing in power-split hybrid electric vehicles (HEVs). The proposed strategy is based on a quadratic performance index, which is innovatively designed to simultaneously restrict the fluctuation of battery state of charge (SOC) and reduce fuel consumption. An extended quadratic optimal control problem is formulated by approximating the fuel consumption rate as a quadratic polynomial of engine power. The approximated optimal control law is obtained by utilizing the solution properties of the Riccati equation and adjoint equation. It is easy to implement in real-time and the engineering significance is explained in details. In order to validate the effectiveness of the proposed strategy, the forward-facing vehicle simulation model is established based on the ADVISOR software (Version 2002, National Renewable Energy Laboratory, Golden, CO, USA). The simulation results show that there is only a little fuel consumption difference between the proposed strategy and the Pontryagin’s minimum principle (PMP)-based global optimal strategy, and the proposed strategy also exhibits good adaptability under different initial battery SOC, cargo mass and road slope conditions.