Hydrogen vehicles are facing significant challenges, including safety risks in the event of leakage, high costs associated with physical testing, and fuel cell inefficiency under dynamic conditions; to address these concerns, we propose VR-H2Safe, a cyber-physical platform that combines high-fidelity simulation, physics-informed reinforcement learning (RL), and secure vehicle-to-everything (V2X) communication. Using ANSYS Fluent Large Eddy Simulation (LES) to train real-time predictive models, the platform's digital twin simulates hydrogen leakage with 92% spatio-temporal correlation compared to high-fidelity LES-CFD benchmarks at key monitoring points. Furthermore, we introduce the H2-LEAK protocol, which extends the SAE J2735 standard with a 128-bit risk vector and blockchain authentication, which provides hazard warnings in less than 2 s with 95% spoofing resistance. In addition, our physics-informed AI system optimizes the fuel cell performance, achieving a 10% increase in energy efficiency and a 58% reduction in thermal violations during hardware verification. The experimental findings of urban, tunnel, and road conditions prove that VR-H2Safe accelerates the process of safety verification and reduces the engineering validation phase from 14 to 10 weeks.
BaniSalman et al. (Tue,) studied this question.