Content 1: Next-Generation V2X Architecture and Intelligent Diagnosis Methods

To meet the requirements of cooperative perception and reliable interconnection among multi-source heterogeneous nodes in complex traffic environments, this research studies a new-generation IoV communication architecture based on the integration of 5G/6G C-V2X and in-vehicle TSN. It explores the modeling approach of deterministic low-latency cyber-physical systems with the integration of vehicle-road-cloud-human.On this basis, in accordance with AUTOSAR and UDS standards, it investigates multi-level intelligent diagnosis theories for ECU monitoring, communication link evaluation and traffic anomaly identification, and explores the construction of evolvable and highly trustworthy diagnosis models, so as to realize real-time cognition and active early warning of vehicle and system health status.

Content 2: Vehicle Energy Intelligent Management and Optimal Control Theory

Aiming at the efficient utilization of vehicle energy in the integrated environment of Internet of Vehicles and intelligent transportation systems, this research studies energy management strategies based on real-time V2X traffic information. It explores the influence mechanism of multi-source disturbances from human-road-cloud on the dynamic energy balance, and investigates adaptive energy compensation and robust control theories under small disturbances. By integrating deep reinforcement learning and model predictive control, it studies the vehicle-road-cloud coordinated energy optimization mechanism and the collaborative regulation rules of key components, so as to improve the economy, power performance and driving range of the vehicle.