Robust control strategy for intelligent connected electric vehicles facing cybersecurity threats

Abstract

This study investigates robust control strategies for Intelligent Connected Electric Vehicles (ICEVs) under cybersecurity threats, with the objective of enhancing both operational safety and energy efficiency in electrified vehicular systems. The proposed framework integrates three key innovations: (1) A hierarchical control architecture combining H ∞ robust control for actuator-level resilience with adaptive Kalman filter to mitigate sensor anomalies caused by cyberattacks; (2) An energy-aware distributed control algorithm that optimizes torque distribution in heterogeneous platoons while maintaining cybersecurity constraints; (3) A novel pre-post filter mechanism for safety-critical systems that provides additional protection layers against false data injection and ECU intrusions. This study combines H ∞ control with blockchain verification for the first time to solve the problem of dynamic delay attacks in V2X communication, and proposes a distributed collaborative control architecture to address the coupling problem between malicious node identification and energy allocation in heterogeneous fleets. The response speed is 40% faster than centralized control. Experimental validation demonstrates significant improvements: Cybersecurity performance 18.7% higher penetration test scores compared to conventional systems. Energy efficiency 12.2% reduction in energy consumption for electric vehicles in mixed platoons through coordinated control. Control robustness Maintains 98.3% trajectory tracking accuracy under simulated GNSS spoofing attacks. The results establish that the proposed strategy simultaneously addresses cybersecurity vulnerabilities and operational optimization in ICEVs, providing a unified solution for next-generation vehicle safety and sustainability.