Fuel Cell Performance Matlab Simulation Data

This work develops an AI-enhanced digital twin framework for real-time modeling, optimization, and predictive management of Fuel Cell Electric Vehicles (FCEVs) integrated with a hydrogen storage system. The proposed embedded control system combines digital twin technology with machine learning algorithms to achieve optimal energy management, improved efficiency, extended component lifetime, and enhanced driving range under dynamic operating conditions.本研究构建了一款面向集成储氢系统的燃料电池电动汽车（Fuel Cell Electric Vehicles，FCEVs）的AI增强型数字孪生框架，用于其实时建模、优化与预测管理。所提出的嵌入式控制系统将数字孪生技术与机器学习算法相结合，可在动态运行工况下实现最优能源管理、提升系统效率、延长部件使用寿命并增加续航里程。