The rapid integration of electric vehicles (EVs) into urban power systems has introduced significant variability in energy demand and supply profiles, particularly within microgrids. To maintain grid stability, improve responsiveness, and optimize operational efficiency, the deployment of Hybrid Energy Storage Systems (HESS)-which combine complementary storage technologies such as lithium-ion batteries and supercapacitors-has emerged as a key enabler. However, the dynamic nature of EV charging patterns, diverse storage characteristics, and control constraints present critical challenges in coordinating such hybrid systems. This paper presents a comprehensive review of the technical challenges and state-of-the-art control strategies associated with HESS in EV-integrated microgrids. We identify major performance bottlenecks such as energy dispatch coordination, SoC imbalance, real-time control latency, and degradation asymmetry. We then survey a range of control architectures, including rule-based logic, Model Predictive Control (MPC), and AI-driven adaptive systems, and assess their effectiveness in simulation environments. Through a representative use case and comparative analysis, we demonstrate how optimized control strategies can enhance system resilience, reduce stress on storage components, and support the seamless integration of EV loads into distributed grid infrastructures. The insights presented here contribute toward the design of smarter, more reliable, and scalable microgrids capable of accommodating the accelerating shift to electrified transportation.
Md Shahiduzzaman Rabbi (Thu,) studied this question.