Achieving High Voltage Gain in Electric Vehicle Applications with Soft-Switching Multiphase Interleaved Boost Converters

Abstract

Because coal and petrol have stricter emission regulations, the automobile industry is seeing an increase in the use of fuel cell electric automobiles or FCEVs. In this architecture, a 1.26 kW artificial network-based predominant feature presenting tracking (MPPT) controllers is suggested as a means of improving these vehicles\' performance. Using a DC-to-DC energy conversion unit, this controller is made to maximise the surface transmembrane of a proton exchange membranes fuel cell (PEMFC), supplying electricity for electric cars. The suggested MPPT guarantees effective energy conversion by utilising maximal power point tracker (MPP) and radial basis functions network (RBFN). High switching frequencies and effective DC conversion are necessary for FCEVs to continue operating. In order to accomplish this, the FCEV system integrates a three-phase alternative energy converter (IBC). Alternating voltage is used in semiconductor electrical circuits to provide voltage control. Using a MATLAB/Simulink platform, the end-to-end RBFN of the FCEV system is when juxtaposed with fuzzy logic controllers (FLCs) to assess its efficiency.

Introduction

The text discusses the development of Fuel Cell Electric Vehicles (FCEVs) as an alternative to conventional fossil-fuel-based vehicles due to environmental concerns and fuel depletion. Fuel cells provide clean energy, high efficiency, low noise operation, and reliable power generation. Among different fuel cell types, Proton Exchange Membrane Fuel Cells (PEMFCs) are widely preferred in automotive applications because of their fast startup time, low operating temperature, and effective performance in different weather conditions.

Fuel Cell Technology:
Fuel cells generate electricity through an electrochemical reaction between hydrogen and oxygen, producing electricity, water, and heat as outputs. FCEVs use hydrogen fuel stored in tanks to power electric motors and produce zero exhaust emissions. They also use regenerative braking systems to recover energy and improve efficiency. PEMFCs are mainly used because they provide high power density and suitability for vehicle applications.

MPPT (Maximum Power Point Tracking):
The system uses MPPT techniques to improve fuel cell power extraction and efficiency. Traditional Perturb and Observe (P&O) MPPT methods have limitations due to steady-state fluctuations. To overcome this, advanced control methods such as Radial Basis Function Neural Network (RBFN) and logic-based controllers are used to achieve better accuracy, stability, and power optimization.

Existing System Problems:
Traditional FCEV systems using fuel cells face challenges such as:

• Low and unstable DC output voltage from PEMFC.
• Requirement of complex DC-DC converters for voltage boosting.
• Reduced efficiency and reliability.
• High cost and larger system size.
• Limited power management capability.

Proposed System:
The proposed FCEV system includes:

• 1.26 kW PEM fuel cell
• Three-phase Interleaved Boost Converter (IBC)
• Voltage Source Inverter (VSI)
• BLDC motor
• RBFN-based MPPT controller

The three-phase IBC increases voltage gain, reduces switching losses, and improves fuel cell reliability. The inverter converts DC power into AC power to operate the BLDC motor, which drives the vehicle.

Working Principle:

1. Hydrogen fuel powers the PEMFC to generate DC electricity.
2. The DC output voltage is increased using the high-voltage gain IBC converter.
3. MPPT controller continuously tracks the maximum available fuel cell power.
4. The inverter converts DC power into suitable AC power.
5. The BLDC motor uses this power to provide vehicle movement.

Advantages of Proposed System:

• Clean and renewable energy production.
• High efficiency and improved reliability.
• Low noise operation.
• Higher voltage gain.
• Better fuel cell power utilization.
• Reduced system losses.

Simulation and Results:
The proposed FCEV model was tested using MATLAB/Simulink under different temperature conditions. The fuel cell produced different power outputs depending on temperature variations. The RBFN-based MPPT controller showed better performance compared to conventional controllers by improving DC link power output and maintaining stable operation.

The BLDC motor performance was analyzed under changing speed conditions, and the motor maintained stable torque despite variations in fuel cell temperature and speed.

Applications:

• Fuel cell electric vehicles
• Renewable energy-based transportation systems
• Solar and hydrogen energy applications

Conclusion

This study presents a high-gain DC for direct current (DC) with three phases of power that was specifically designed for fuel cell powered electric cars. (FCEV) software applications. Its main objectives are to reduce fuel cell current-injection implications and voltage stress for electricity semiconductor products switches. A membrane-based fuel-cell technology (PEMFC) system with a 1.26 kW proton transfer capacity is one of the configurations that is included. In particular, a Radial Basis pragmatic Network (RBFN)-based maximum power point the tracking system (MPPT) system has been created. This MPPT technique optimises fuel cell production of power at various operating temperatures. We present an analysis and comparisons of the conventional Fuzzy Logic The control unit (FLC) the MPPT controller and the proposed RBFN-based MPPT controller. The simulation results demonstrate the RBFN-based MPPT device controller outperforms its FLC equivalent in terms of evaluation the maximum power limit more quickly and accurately. Numerous performance parameters for a Brushless DC (BLDC) motor are also examined in the study, such as electromagnetic torque, speed, and the return electromotive force (EMF), across a range of operating settings that correlate to varied fuel cell system temperatures.

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Copyright

Copyright © 2026 Mr. Suraj Gaygowad, Dr. Nilesh Bodhane, Prof. Uttara Dudhpachare. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.