Fuzzy Inference System for Enhanced Fuel and Air Delivery in Fuel Cell for High Power Electric Vehicle Applications

This article aims towards a detailed design of control systems used in a Proton Exchange Membrane (PEM) fuel cell system used for High Power Electric Vehicle (EV) applications. The PEM fuel cell comprises four controllers related to fuel, air supply systems, and pressure controllers which need to be operated optimally for efficient power delivery. The output of a PEM fuel cell depends on many parameters such as fuel flow rate, air flow rate, the supply pressure of hydrogen, and supply pressure of air. Using PID and fuzzy-based PID controllers, these parameters are optimally controlled to get maximum power requirement from the PEM fuel cell stack. The research intends to address the specific issues connected to fuel cell dynamics and improve their response to various operational situations by utilizing cutting-edge control algorithms, sensors, and actuators. The presented work focuses on the mathematical design and control aspect in the development of enhanced fuel cell vehicle control systems which include dynamic fuel flow response, accurate pressure control, required power delivery, improved efficiency, zero carbon footprint, and increased system durability. The development of the PEM fuel cell system suitable for TATA Nexon Electric Vehicle (EV) with operating specifications of 94 kW, 320 Vdc, 3796 rpm, 215 Nm are carried out using MATLAB/Simulink and the performances of the efficient controller are validated, and proposed.