Hierarchical Adaptive Sliding Mode Control with Deep Reinforcement Learning for Solar-Assisted Fuel Cell Hybrid Electric Vehicles

Abstract

This repository contains the MATLAB files associated with the paper entitled “Hierarchical Adaptive Sliding Mode Control with Deep Reinforcement Learning for Solar-Assisted Fuel Cell Hybrid Electric Vehicles.” The deposited files support the numerical simulations and performance evaluation reported in the manuscript. They implement the proposed hierarchical energy-management and control framework for a solar-assisted fuel cell hybrid electric vehicle integrating a fuel cell, battery, ultracapacitor, and photovoltaic source. The MATLAB files include the main simulation routines, vehicle and powertrain models, adaptive sliding-mode control algorithms, constrained gain adaptation, deep reinforcement learning-based power-sharing logic, photovoltaic power integration, roadway-preview information processing, and the evaluation procedures used for the considered driving cycles. The repository also includes the routines required to reproduce the principal numerical comparisons, ablation-study scenarios, voltage-regulation results, hydrogen-consumption calculations, state-of-charge evolution, chattering assessment, and photovoltaic-utilization analysis. The code is intended to support the reproducibility of the numerical results presented in the paper, including simulations under standard and unseen driving cycles such as WLTP and FTP-75. The deposited MATLAB implementation corresponds to the computational framework described in the manuscript and can be used to reproduce and further investigate the proposed hierarchical adaptive SMC–DRL methodology. Associated paper:Hierarchical Adaptive Sliding Mode Control with Deep Reinforcement Learning for Solar-Assisted Fuel Cell Hybrid Electric Vehicles Keywords: Fuel Cell Electric Vehicles; Hybrid Energy Storage Systems; Sliding Mode Control; Deep Reinforcement Learning; Adaptive Control; Photovoltaic Integration; Energy Management; MATLAB; Energy Management System; Hybrid Electric Vehicles.