• Manish N. Bawangade
• Prof. Vaishali Malekar

As a result of stricter regulations on carbon emissions and fuel economy, Fuel Cell Electric Vehicles (FCEV) vehicles are becoming increasingly popular in the automotive industry. This paper presents the neural network Maximum Power Point Tracking (MPPT) controller of the 1.26 kW Proton Exchange Membrane Fuel Cell (PEMFC), which provides the electric vehicle's powertrain using DC-DC power converters. The proposed neural network MPPT controls using the Radial Basis Function Network (RBFN) PEMFC Maximum Power Point (MPP) tracking algorithm. High frequency switching and high DC-DC converting power are important for the continuation of FCEV. For maximum power gain, the three- phase power supply Interleaved Boost Converter (IBC) is also designed for the FCEV system. The interleaving process reduces the current input pressure and power pressure on the semiconductor

Fuelcellelectricvehicle,high voltagegainIBC,PEMFC,MPPT,RBFN.

"Neural Network Based MPPT Controller with Boost Converter For Fuel Cell Based Electric Vehicle Applications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 12, page no.62-68, December-2020, Available :http://www.jetir.org/papers/JETIREJ06017.pdf

"Neural Network Based MPPT Controller with Boost Converter For Fuel Cell Based Electric Vehicle Applications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 12, page no. pp62-68, December-2020, Available at : http://www.jetir.org/papers/JETIREJ06017.pdf