Optimal Genetic Algorithm Pontryagin Minimum Principle Approach for Equivalent Fuel Consumption Minimization in Hybrid Electric Vehicle

摘要

In present context, power management among various energy sources is the key requirement to achieve high efficiency in hybrid electric vehicle (HEV). The HEV usually utilizes the energy from fuel cell, battery and supercapcitor. Hence, the overall fuel consumption is required to be minimized by optimal strategy to identify optimal power distribution. The effectiveness of the strategy mainly depends on an accurate estimation of the equivalence factor to obtain the equivalent fuel consumption of the HEV. In the present work, estimation of equivalence factor using genetic algorithm (GA) tuned Pontryagin minimum principle (PMP) for optimal energy management is proposed. The proposed GA-PMP based method has the benefits of both GA and PMP. Simulation results show that the proposed GA-PMP approach outcomes more reduction in hydrogen consumption of fuel cell in comparison to PMP approach.