Control strategy of hybrid power system for Fuel Cell Electric Vehicle based on neural network optimization

Fuel cell electric vehicle has very good application foreground for it has some advantages, such as high efficiency and little emission, etc. In order to characterize the structure of hybrid power system for fuel cell electric vehicle, the project of parallel hybrid power system was brought forward, which consisted of fuel cell, NIH battery and DC/DC converter. The power flow of hybrid power system was analyzed, and besides , the issue for energy management of power system was converted to combinatorial optimization problem. The energy management strategy based on neural network optimization was designed by applying three-layer neural network optimization control structure and optimizing neural network connect weight via genetic algorithms. In the end, the simulation results were presented, which show the effectiveness of the control strategy, for it can improve economy performance of vehicles in comparison with fuzzy control strategy.