Comparing fuzzy rule-based MPPT techniques for fuel cell stack applications

Abstract

The process of maximum power extraction from alternative energy systems was at the first instance applied to systems such as photovoltaic and wind power technologies. Both systems operate on the principle of conversion of either solar or wind energy into electrical energy. Thus, the generated powers depend directly on the solar radiation level and the cell temperature for photovoltaic systems and on the wind speed for wind generators. To avoid inefficient system operations, the power outputs are optimized through maximum power point tracking techniques. Fuel cells are also candidates for maximum power extraction as their output powers are affected by internal limitations and operating parameters. At each operating time, the system needs to be constrained through MPPT controllers to provide continuously as much power as possible to avoid low efficiency and excessive fuel use. Various techniques can be employed for MPPT controllers design. This paper investigates MPPT controllers based on fuzzy inference system techniques, the objective is to compare Mamdani and Sugeno controllers’ time response. The investigation is conducted on a 50 kW PEMFC stack coupled to a power electronics converter and a DC load. The simulation is carried out under Matlab/Simulink environment.