An optimal control-based algorithm for Hybrid Electric Vehicle using preview route information

Control strategies for Hybrid Electric Vehicles (HEVs) are generally aimed at optimally choosing the power distribution between the internal combustion engine and the electric motor in order to minimize the fuel consumption and/or emissions. Using vehicle navigation systems in combination with Global Positioning Systems and Geographical Information Systems allow further optimization of the power distribution by utilizing the route information. In this paper, a new control algorithm based on a combination of dynamic programming and classical optimal control theory is proposed for the Energy Management System in parallel HEVs to improve the fuel economy over a preview route segment. The proposed algorithm optimizes not only the gear position and the engine power yet also the vehicle velocity. The vehicle is controlled to complete this route segment in a predefined time length. Using this method more than 11% fuel saving is computed on an optimized cycle compared to a standard city cycle with equal time length and average speed.