Proton Exchange Membrane Fuel Cells: An Effective Neural Fuzzy System for Optimal Power Tracking

Abstract

The revolutionary future of proton-exchanging membrane fuel cells (PEMFC) has recently garnered a great deal of excitement, as has their green energy source. Maximizing the production of electricity from PEMFC is crucial to maintaining effectiveness. This research article thoroughly analyzes a research study using a strategy known as MPPT, or maximum power point tracking that uses the neuro-fuzzy method for PEMFC operating under diverse temperatures, pressures, and joining constraints. The neuro-fuzzy controller cleverly regulates the point of maximal operation of a hydrogen fuel cell system, allowing exact adherence to the highest possible power scale. According to simulation results, the neuro-fuzzy MPPT technique improves PEMFC validity across a wide range of operating scenarios.

Keywords

• proton exchange membrane (pem) fuel cell
• neuro-fuzzy
• pressure variation
• temperature variation
• maximum power point tracking