An MPPT Controller with a Modified Four-Leg Interleaved DC/DC Boost Converter for Fuel Cell Applications
DOI:
https://doi.org/10.37934/araset.53.1.219236Keywords:
Interleaved boost converter, Fuzzy controller, MPPT controller, Fuel cell system, Neural networkAbstract
A fuel cell system can produce electricity and water more efficiently while emitting near-zero emissions. Internal constraints and operating parameters such as hydrogen, temperature, humidity levels, and oxygen gas partial pressures trigger a nonlinear power characteristic in a typical fuel cell stack, resulting in reduced overall system efficiency. Consequently, it's critical to get the most power out of the fuel cell stack while minimizing fuel use. This study examines and proposes a radial basis function network (RBFN) based maximum power point tracking technique (MPPT) for a 6-kW proton exchange membrane fuel cell (PEMFC) system. The proposed MPPT algorithm modulates the duty cycle of the modified four-leg interleaved DC/DC boost converter (MFLIBC) to extricate the maximum power from the fuel cell system. To validate the execution of the proposed controller, the outcome is related to the various MPPT control strategies such as PID & Mamdani fuzzy inference systems. Finally, it was observed that the proposed RBFN controller has achieved an enhanced efficiency of 83.2 % relative to the PID and fuzzy logic controllers of 75.5 % and 77.4 % respectively. The efficiency of the proposed configuration is analysed using the MATLAB/Simulink platform.