Model Predictive Control of DC-DC Boost Converter for PEM Fuel Cell Systems with Integrated MPPT

Abstract

This paper presents a model predictive control (MPC) strategy for proton exchange membrane fuel cell (PEMFC) systems coupled with DC-DC boost converters. PEMFCs exhibit nonlinear voltage-current characteristics requiring power electronic interfaces to regulate output voltage and maximize energy extraction. The proposed MPC approach simultaneously achieves DC bus voltage regulation and maximum power point tracking (MPPT) by formulating a discrete-time predictive controller based on linearized converter and fuel cell models. The control strategy minimizes a quadratic cost function incorporating voltage tracking error and control effort while explicitly handling operational constraints on duty cycle, inductor current, and switching frequency.

Comprehensive simulations in MATLAB/Simulink demonstrate the MPC's superior performance compared to conventional proportional-integral (PI) control under various operating scenarios. Results show 4.5 times reduction in integral absolute error (IAE) for voltage tracking, 15-18% reduction in voltage undershoot during load transients, and enhanced robustness against variations in fuel supply pressure, air supply pressure, and stack temperature. The MPC exhibits faster dynamic response, reduced voltage ripple, and improved overall system efficiency. The proposed control framework is validated under step changes in load demand and DC bus voltage, confirming its effectiveness for fuel cell-based microgrids, electric vehicles, and distributed generation applications.