Bibliographic Details
| Title: |
Implementation of Non-Isolated High Gain Interleaved DC-DC Converter for Fuel Cell Electric Vehicle Using ANN-Based MPPT Controller. |
| Authors: |
Subbulakshmy, R., Palanisamy, R., Alshahrani, Saad, Saleel, C Ahamed |
| Source: |
Sustainability (2071-1050); Feb2024, Vol. 16 Issue 3, p1335, 26p |
| Abstract: |
A high conversion ratio DC-DC converter is crucial for fuel cell electric vehicles (FCEV). A fuel cell-based non-isolated high gain integrated DC-DC converter for electric vehicles is proposed in this paper. The system comprises an interleaved boost converter (IBC) at the source end, a switched capacitor cell, coupled inductors, a passive clamp circuit, and a voltage multiplier circuit (VMC). Its significance is to achieve the voltage conversion gain of 12.33 at a conversion ratio of 0.45. The idea is to use a proton exchange membrane fuel cell to power electric vehicles through a high-gain DC-DC converter. The use of an ineffective MPPT can result in lower energy conversion efficiency. Thus, this system incorporates a maximum power point tracking (MPPT) controller based on a neural network, which relies on the radial basis function network (RBFN) algorithm to track the maximum power point of the PEMFC accurately. The comparative study of the fuel cell electric vehicle (FCEV) structure with the RBFN-based MPPT technique was evaluated with that of the fuzzy logic technique using the MATLAB/Simulink platform (R2021b (MATLAB 9.11)). A 1.5 kW experimental prototype is designed with a switching frequency of 10 kHz to validate the design analysis, and its pursuance is compared between RBFN and FLC-based controllers. This manuscript will be a significant contribution towards evidencing a sustainable environment. [ABSTRACT FROM AUTHOR] |
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| Database: |
Complementary Index |