Enhanced Fractional Cascaded Control and Multi-Tier Energy Management for Hybrid Electric Vehicles with Battery–Ultracapacitor–Fuel Cell Architectures

Abstract

The rapid adoption of electric mobility demands energy management systems that can efficiently coordinate multiple energy sources while maintaining vehicle stability, responsiveness, and sustainability. However, conventional rule-based, reinforcement-learning, and optimization-based strategies often face limitations in adapting to nonlinear load variations, transient power demands, regenerative braking, and the coupled dynamics of heterogeneous storage systems. To address these challenges, this study proposes an integrated hybrid energy management framework combining contextual drive-state fusion, multi-tier energy management, a cascaded fractional-order FOTPD-1+TFOID controller, and enhanced Starfish Optimization. The framework coordinates battery, ultracapacitor, and fuel-cell power according to driving conditions, source constraints, and predicted demand, while R³V-Bench evaluates electrical, dynamic, environmental, and economic performance. MATLAB/Simulink simulations were conducted under urban, highway, and aggressive driving cycles. The proposed framework achieved efficiencies of 92.4%, 95.2%, and 90.1%, respectively. Battery SOC deviation was reduced to 4.8%, peak battery current to 312 A, and hydrogen consumption to 0.62 g/km. Furthermore, speed-tracking RMSE reached 1.85 km/h, DC-link ripple 1.9%, response time 42ms, demand satisfaction 98.6%, and regenerative capture 84.9%. These results demonstrate improved efficiency, stability, durability, and sustainability for advanced hybrid electric propulsion systems.