High-Performance Tracking for Proton Exchange Membrane Fuel Cell System PEMFC Using Model Predictive Control

Abstract

Proton exchange membrane (PEM) fuel cell has recently attracted broad attention from many researchers due to its cleanliness, high efficiency and soundless operation. The obtention of high-performance output characteristics is required to overcome the market restrictions of the PEMFC technologies. Therefore, the main aim of this work is to maintain the system operating point at an adequate and efficient power stage with high-performance tracking. To this end, a model predictive control (MPC) based on a global minimum cost function for a two-step horizon was designed and implemented in a boost converter integrated with a fuel cell system. An experimental comparative study has been investigated between the MPC and a PI controller to reveal the merits of the proposed technique. Comparative results have indicated that a reduction of 15.65% and 86.9%, respectively, in the overshoot and response time could be achieved using the suggested control structure.

Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System

“…𝑉 𝐶 (𝑡) = 𝑉 𝑑 × 𝑒 − 𝑡 𝑅𝐶 (24) where 𝑉 𝐶 is the capacitor voltage, 𝑉 𝑑 is the capacitor voltage to be discharged, 𝑅 is the resistance value, and 𝐶 is the capacitance value. The capacitor time constant is equal to the product of the resistance and capacitance value.…”

“…Derbeli et al [24] introduced another high-performance tracking method for PEMFC by MPC. This method is not an MPPT but a stable performance tracking technique.…”

“…The algorithm of the proposed predictive MPPT technique is different from the method in [23]. However, it is similar to the method in [24] with an MPPT algorithm that can track the MPP. It predicts the PEMFC output current and power for the next sampling step.…”

Machine Learning Approach for Modeling and Control of a Commercial Heliocentris FC50 PEM Fuel Cell System

“…These values can be adjusted via the increase/decrease of the output load resistance value. We have avoided operating currents above 9A since the fuel cell used in this study (Heliocentris FC50) is occupied with a security system that turns off the fuel cell in case of higher currents/temperatures [29][30][31]. To obtain data for different operating conditions, variations in temperature, humidity, hydrogen and airflow are required.…”

Fast Model Predictive Control of PEM Fuel Cell System Using the L1 Norm

“…Hierarchical techniques can also be applied to develop a comprehensive energy management strategy consisting of high-level control, which is based on fuzzy logic technique as well as adaptive control loop and low-level control that generates a pulse-width-modulation signal so that appropriate power distribution is achieved and the operating voltage of the powertrain is stabilised [15]. In recent years, applications of MPC algorithms [16][17][18] to PEM fuel cells have been reported. A linear model can be used for MPC prediction [19].…”