Abstract

The output power of the fuel cell (FC) is mainly depending on the membrane water content, temperature, the hydrogen and oxygen partial pressures. The polarization curve has one global maximum power to be tracked. Therefore, a robust maximum power point tracking (MPPT) is highly required to follow the optimal operating point under any operating conditions. In this article, a recent approach of forensic-based investigation (FBI) algorithm is proposed to identify the optimal parameters of fractional order PID-based MPPT with proton exchange membrane (PEM) fuel cell. FBI is selected due to its high accuracy and requirement of less computational efforts. The considered objective function to be minimized is the error between the voltage at maximum power (VMP) and the actual one at FC terminals. To prove the robustness of the proposed methodology, four cases of operating conditions are analyzed which are constant membrane water content and temperature, constant membrane water content with variable temperature, variable membrane water content with constant temperature, and variable membrane water content with variable temperature. The obtained results are compared to other approaches such as incremental resistance (INCR), particle swarm optimizer (PSO), invasive weed optimizer (IWO), sin-cosine algorithm (SCA), and artificial ecosystem optimizer (AEO). In case (1), the proposed FBI-FOPID succeeded in achieving maximum power of 5185.101 W. While the minimum objective functions in the second, third, and fourth cases are 2.5736 V, 1.4436 V, and 1.1568 V respectively obtained via the proposed approach. The comparison confirmed the superiority of the proposed FBI-based MPPT compared with other methods.

Highlights

  • Renewable energy sources (RESs) employed in many engineering applications as replacements to fossil fuels that have negative effects on the environment and result in global warming

  • The proposed forensic-based investigation (FBI) is applied to evaluate the optimal parameters of Fractional order proportionalintegral-derivative controller (FOPID) controller based maximum power point tracker (MPPT) for proton exchange membrane (PEM) fuel cell

  • To validate the proposed FBI approach, comparison to other approaches of incremental resistance (INCR), FOPID optimized via particle swarm optimizer (PSO), invasive weed optimizer (IWO), sin-cosine algorithm (SCA), and artificial ecosystem optimizer (AEO) is performed

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Summary

INTRODUCTION

Renewable energy sources (RESs) employed in many engineering applications as replacements to fossil fuels that have negative effects on the environment and result in global warming. Differential evolution (DE) approach has been presented to optimize Fuzzy logic based MPPT controller incorporated with PEMFC to enhance its performance via extracting the maximum power [6]. Fathy et al [8] employed salp swarm algorithm (SSA) to design PID controller based MPPT for searching the maximum power of PEM fuel cell. An adaptive neuro-Fuzzy inference system (ANFIS) based MPPT has been presented to enhance the performance of PEM fuel cell employed in electric vehicles [28]. This work addressed the deficiencies accompanied to the previous reported works by proposing a recent metaheuristic approach of forensic-based investigation (FBI) algorithm for designing a fractional order PID controller based MPPT for PEM fuel cell. A recent approach of forensic-based investigation (FBI) algorithm is proposed to simulate MPPT installed with PEM fuel cell. The rest of the paper is organized as follows: section 2 presents the model of PEM fuel cell, section 3 explains the principles of fractional order PID controller, section 4 introduces the forensic-based investigation algorithm, section 5 presents the proposed FPI-Fractional order PID based MPPT, section 6 shows the numerical analysis and discussion, and section 7 presents the conclusions

PROTON EXCHANGE MEMBRANE FC MODEL
DYNAMIC GAS TRANSPORTATION MODEL
RESULTS AND DISCUSSIONS
CASE 1
CASE 2
CASE 3
CASE 4
CONCLUSION
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