Power Management for a Fuel cell/Battery and Supercapacitor based on Artificial Neural Networks for Electric Vehicles

Hydrogen electric vehicles are environmentally friendly and highly efficient. They derive their energy from fuel cell as a main component in addition to lithium-ion battery and supercapacitor as auxiliary elements. However, there are problems in securing the required power and the optimal power control strategy with different operating conditions. In order to solve these problems, we seek in our work to improve energy economy and continuity, make use of some of the energy that is often lost as heat, and increase system life. To with considering various operating restrictions. So, we adopted this hybrid energy storage system. A specialized strategy is designed for optimal control of energy sources. Therefore, an artificial neural network was trained using Matlab/Simulink software. The obtained results showed the effectiveness and accuracy of the proposed system. Which can be used in practice.