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

Peer Mohamed A; K R M Vijaya Chandrakala; Saravanan S; Umashankar Subramaniam; Dhafer Almakhles

doi:10.1038/s41598-024-79857-3

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

Sci Rep. 2024 Nov 26;14(1):29364. doi: 10.1038/s41598-024-79857-3.

Authors

Peer Mohamed A¹, K R M Vijaya Chandrakala², Saravanan S¹, Umashankar Subramaniam³, Dhafer Almakhles³

Affiliations

¹ Department of Electrical and Electronics Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India.
² Department of Electrical and Electronics Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India. krm_vijaya@cb.amrita.edu.
³ Renewable Energy Lab, Communications and Networks Department, College of Engineering, Prince Sultan University, Riyadh, 11586, Saudi Arabia.

Abstract

Fuel cell-based electric vehicles (EVs) are gaining popularity in the automotive industry due to strict carbon emissions and fuel efficiency regulations. Fuel cells have inherently low voltage characteristics, making it challenging to interface with EV drive systems. This work proposes a unique topology implementing a non-isolated high step-up DC-DC converter to integrate the Proton Exchange Membrane Fuel (PEMF) cell with the EV motor drive. The converter combines a modified Single-Ended Primary Inductor Converter (m-SEPIC) with two winding-coupled inductors, enabling high voltage gain, minimizing conduction losses, and ensuring high efficiency. The output power of a fuel cell is highly dependent on cell temperature and membrane water content, making a maximum power point tracking controller essential for extracting optimal power from the fuel cell stack. The optimum power point of the PEMF cell is identified using a Neural Network (NN)-based Maximum Power Point Tracking (MPPT) technique, employing the Radial Basis Function Network (RBFN) approach compared to the Perturb & Observe (P&O) method. The performance of the RBFN MPPT method is validated under various temperature conditions of the fuel cell system. An extensive analysis and comparison with alternative converters validate the efficacy of the proposed system. The converter is designed for an input voltage of 24 V and boosts it to an output voltage of 240 V, with high static voltage gain, high power density, and minimized total losses. The system is tested and validated through both simulation and real-time implementation using the dSPACE 1104 real-time controller. A 200 W, 3000 rpm, 240 V VSI-based BLDC motor drive integrated with the proposed converter topology is developed as a real-time setup in the laboratory which would confirm the converter's functionality. Both theoretical analysis and real-time outcomes affirm the suitability of the proposed converter topology for electric vehicle applications.

Keywords: Electric vehicle; Fuel cell; High step-up DC–DC converter; Maximum power point tracking; Radial basis function network.

Abstract

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