Improved Gray Wolf Optimization tuned linear quadratic regulator for hybrid energy storage systems in electric vehicles: Performance enhancement and techno–economic optimization

Hybrid Energy Storage Systems that integrate batteries, supercapacitors, fuel cells, and electrolyzers offer a viable pathway to improve performance, reduce costs, and enhance sustainability in electric vehicles. The scientific aim of this work is to develop a robust and techno-economically efficient energy management strategy for multi-source hybrid electric vehicle applications. This study presents an Improved Gray Wolf Optimization tuned Linear Quadratic Regulator for advanced energy management, enabling precise voltage regulation, efficient power distribution, and hydrogen generation from surplus energy. The subject of the research is the optimal control and coordination of a hybrid energy storage unit comprising a regenerative fuel cell, electrolyzer, battery, and supercapacitor interconnected through power electronic converters on a common DC bus. The proposed control strategy reduces transient losses, minimizes component stress, and extends the operational life of storage devices, leading to lower lifecycle costs. This study extends existing research by jointly integrating metaheuristic-based LQR tuning, surplus-to-hydrogen utilization, and techno-economic performance evaluation within a unified energy management framework. Comparative simulations in MATLAB/Simulink and hardware-in-the-loop validation confirm substantial improvements over conventional proportional–integral control, including a 78% reduction in the integral of time-weighted absolute error, 50% reduction in overshoot, a 17.6% increase in energy efficiency, and a decrease in maintenance costs from 18.5 USD to 13.5 USD. Statistical analysis using one-way analysis of variance confirms the significance of these results with p-values less than 0.05. The integration of hydrogen production enhances energy autonomy and aligns with the Sustainable Development Goals on affordable and clean energy, industry and infrastructure, sustainable cities, and climate action. • IGWO-tuned LQR controller improves EV hybrid storage performance and efficiency. • Achieves 78% ITAE reduction and 50% overshoot reduction over PI control. • Integrates hydrogen production for enhanced sustainability and autonomy. • Demonstrates 17.6% efficiency gain and reduced maintenance cost. • Validated via simulations and hardware-in-the-loop (HIL) real-time execution.