Air Supply System Control of PEM Fuel Cell for Electric Vehicle Application Based on Multi-layer Prediction Strategy

Abstract

Proton exchange membrane (PEM) fuel cell engine has many advantages, including high energy density, high efficiency, low operation temperature, and zero emissions, which is a promising application to electric vehicles. In this paper, a multi-layer prediction control strategy for air supply system of a full-power PEM fuel cell electric vehicle is proposed, and a mathematical model of PEMF fuel cell engine air supply system is established in MATLAB/Simulink environment. The control scheme of the proposed multi-layer prediction strategy is that the top-layer model prediction is used for predicting the driving condition (speed of the vehicle) to obtain the desired air mass flow rate, and the bottom-layer air flow model prediction control (MPC) can adopt the top-layer airflow demand to regulate the oxygen excess ratio of PEM fuel cell engine. The proposed control strategy can meet the needs of the fuel cell stack reaction of oxygen as well as prevent air starvation that might occur in PEM fuel cell electric vehicle during driving conditions variation.