An enhanced maximum power point tracking and voltage control for proton exchange membrane fuel cell using predictive model control techniques

Abstract

Proton Exchange Membrane Fuel Cells serve as sustainable devices for converting renewable energy sources into electricity, offering advantages such as rapid startup, high power density, and operation at low temperatures. They are highly efficient and environmentally friendly energy sources, yet their non-linear output characteristics under variable conditions present challenges in maximizing power output. Furthermore, they generates direct current, while many electrical devices rely on alternating current. This research addresses the necessity of enhancing the performance and efficiency through the development of an advanced maximum power point tracking technique and voltage control strategy. A modified finite-control-set model predictive control technique is proposed for both maximum power point tracking and voltage control. Specifically, a finite-control-set model predictive control technique approach is employed to modulate the switching signal for both the DC-DC boost converter and the DC-AC inverter. The DC-DC boost converter step up the fuel cell output voltage to the desired level, ensuring it reaches the maximum power point, and a DC-AC inverter to convert the direct current voltage to a pure sinusoidal alternating waveform. The investigation demonstrates the effectiveness of the proposed method in achieving its objectives. The proposed maximum power point tracking technique accuracy achieved the maximum power with a rate of 97 % with excellent respond time within 7 ms. For alternating current power, only less than 1.5 % of total harmonic distortion is recorded. The study evaluates the control scheme under robust operating conditions, demonstrating its effectiveness in optimizing PEMFC output and providing high-quality AC voltage.