ANFIS Based Parameter Estimating of a Two-Phase Interleaved Dual Cascaded DC-DC Boost Converter for Fuel Cell Supplied Electric Vehicles

Abstract

Fuel cells (FCs), one of the renewable energy sources, have started to be preferred as a power source in electric vehicles in recent years and research studies are continuing on designs in this direction. Although their efficiency is low <50%, they produce Direct Current (DC) electrical energy by electrochemical conversion without requiring battery systems, which can be used in electric vehicle drive systems. There are zero-emission effects such as water and temperature rise with waste and environmental aspects. One of the major disadvantages is the DC voltage amplitude they produce is inversely proportional to the temperature increase. In this context, parameter estimation is required to adapt the fluctuating FC voltage to a certain value adaptively with the DC-DC boost converter circuit. In this study, parametric simulation studies were carried out with Ansys-Electronics 2019-R3 software to determine the DC voltage level of a certain number of series and parallel connected FC cells depending on different temperature values. Duty ratio values of two-phase interleaved dual cascaded DC-DC boost converter circuit for desired output voltage were determined by using Adaptive Nero-Fuzzy Inference System (ANFIS) modeling of 1300 data determined by simulation studies. Thus, the output voltage of the converter is adaptively fixed at a certain value.

Keywords

• ANFIS
• Electric Vehicle
• Fuel Cell
• Interleaved Cascaded Boost Converter.

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