Intelligent Energy Management Strategy for a Parallel Hybrid Vehicle

Rashad Mustafa; Mirko Schulze; Peter Eilts; Ferit Küçükay

doi:10.4271/2014-01-1909

Hybrid electric vehicles (HEV's) are facing increasing challenges in optimizing the energy flow through a vehicle system, in order to improve both fuel economy and vehicle emissions. Energy management of HEV's is a difficult task due to the complexity of the total system in terms of electrical, mechanical and thermal behavior.

In this paper, an advanced control strategy for a parallel hybrid vehicle is developed. Four main steps are presented, particularly to achieve a reduction in fuel consumption. The first step is the development of a highly complex HEV model, including dynamic and thermal behavior. Second, a heuristical control strategy is developed to determine the HEV modes and third, a State of Charge (SoC) leveling is developed with the interaction of a fuzzy logic controller. It is proposed to calculate the load point shifting of the Internal Combustion Engine (ICE) and the desired battery SoC.

Fourth, novel multi-objective optimization techniques, such as a genetic algorithm, are used for the optimization of the fuzzy logic controller and the heuristical control strategy. The simulation results show a potential fuel reduction relative to the baseline control strategy.

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Intelligent Energy Management Strategy for a Parallel Hybrid Vehicle 2014-01-1909

SAE MOBILUS