Implementation of high step up converter using RBFN MPPT controller for fuel cell based electric vehicle application

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Automotive Technology

Background:

• Electric vehicles (EVs) face challenges integrating low-voltage fuel cell power sources due to stringent emission regulations.
• Proton Exchange Membrane Fuel (PEMF) cells require efficient power conversion to match EV drive system voltage requirements.

Purpose of the Study:

• To propose a novel non-isolated high step-up DC-DC converter topology for seamless PEMF cell integration into EV powertrains.
• To develop and validate a Neural Network (NN)-based Maximum Power Point Tracking (MPPT) controller for optimizing PEMF cell energy extraction.

Main Methods:

• A modified Single-Ended Primary Inductor Converter (m-SEPIC) combined with coupled inductors was designed for high voltage gain and efficiency.
• A Radial Basis Function Network (RBFN) approach was employed for the MPPT controller, outperforming the Perturb & Observe (P&O) method.
• The system was validated through simulations and real-time implementation using a dSPACE 1104 controller with a 200W BLDC motor drive.

Main Results:

• The proposed converter achieved a high voltage gain, boosting 24V to 240V with minimized losses and high power density.
• The RBFN MPPT controller demonstrated effective performance under varying fuel cell temperature conditions.
• Real-time implementation confirmed the converter's functionality and suitability for EV applications.

Conclusions:

• The novel high step-up DC-DC converter topology effectively integrates PEMF cells with EV motor drives.
• The RBFN-based MPPT controller ensures optimal power extraction from PEMF cells, enhancing overall system efficiency.
• The validated system shows significant promise for advancing fuel cell electric vehicle technology.