Machine Learning-Based Performance Evaluation of a Solar-Powered Hydrogen Fuel Cell Hybrid in a Radio-Controlled Electric Vehicle

TL;DR

This study evaluates a solar-powered hydrogen fuel cell hybrid system in a radio-controlled electric vehicle, demonstrating improved performance, reliability, and predictive modeling capabilities using machine learning techniques under various conditions.

Contribution

The paper introduces a comprehensive experimental analysis and machine learning-based predictive modeling of a solar-powered hydrogen fuel cell hybrid system in small electric vehicles, highlighting its potential for off-grid applications.

Findings

Enhanced voltage stability and fewer faults with hybrid system

Effective use of Temporal Convolutional Networks for voltage prediction

Potential for off-grid hydrogen fueling with solar electrolyzers

Abstract

This paper presents an experimental investigation and performance evaluation of a hybrid electric radio-controlled car powered by a Nickel-Metal Hydride battery combined with a renewable Proton Exchange Membrane Fuel Cell system. The study evaluates the performance of the system under various load-carrying scenarios and varying environmental conditions, simulating real-world operating conditions including throttle operation. In order to build a predictive model, gather operational insights, and detect anomalies, data-driven analyses using signal processing and modern machine learning techniques were employed. Specifically, machine learning techniques were used to distinguish throttle levels with high precision based on the operational data. Anomaly and change point detection methods enhanced voltage stability, resulting in fewer critical faults in the hybrid system compared to battery-only operation. Temporal Convolutional Networks were effectively employed to predict voltage behavior, demonstrating potential for use in planning the locations of fueling or charging stations. Moreover, integration with a solar-powered electrolyzer confirmed the system's potential for off-grid, renewable hydrogen use. The results indicate that integrating a Proton Exchange Membrane Fuel Cell with Nickel-Metal Hydride batteries significantly improves electrical performance and reliability for small electric vehicles, and these findings can be a potential baseline for scaling up to larger vehicles.