Neural Network Based MPPT Controller with Boost Converter For Fuel Cell Based Electric Vehicle Applications
1Chandrakant kanhekar , ²Prof.Rashmi s.Singh, ³Prof.Shibu K.K.Thomas.
1Department of Electrical Engineering vidarbha institute of technology Uti, umrer road, Nagpur
2Department of Electrical Engineering vidarbha institute of technology Uti, umrer road, Nagpur
Abstract -
Due to the strict guidelines on carbon emissions and the gas financial system, fuel cell electric motors (FCEV) motors are becoming an increasing number of famous inside the car enterprise. This paper offers the neural network most electricity point monitoring (MPPT) controller of the
1.26 kw proton change membrane gas mobile (PEMFC), which affords electric car powertrain the usage of dc-dc strength converters. The proposed neural network controls the MPPT radial basis feature community (RBFN) the usage of the PEMFC maximum powerpoint (MPP) tracking algorithm. High frequency switching and high dc-dc converted energy are vital for FCEV continuity. For maximum energy benefit, a 3-phase power deliver interleaved boost converter (IBC) is also designed for FCEV systems. The interleaving technique reduces the contemporary enter stress and electrical strain within the semiconductor electric tool. FCEV gadget overall performance analysis with RBFN based totally MPPT manage in comparison to fuzzy Logic controllers (FLC) on the MATLAB / Simulink platform.
Keywords: Fuel cell electric vehicle, high voltage gain IBC, PEMFC, MPPT, RBFN etc.
