Optimization Based Power Control of CHB EV Charging Station with Integrated BES

Environmental concerns and the increasing adoption of electric vehicles (EVs) are driving the need for extreme fast-charging (XFC) stations capable of delivering high power in short time intervals. However, such infrastructures impose significant stress on the power grid. Traditional low-voltage (LV) charging systems struggle to meet ultra-high-power requirements due to excessive current demands and limited scalability. To address these challenges, medium-voltage (MV) multiport architectures based on cascaded H-bridge (CHB) converters have emerged as a promising solution. Although such architectures offer high power capability and improved power quality, maintaining power balance among multiple charging ports while ensuring stable operation remains a critical challenge. A cascaded H-bridge (CHB)-based multiport architecture integrated with distributed battery energy storage (BES) modules is considered a promising solution for extreme-fast charging stations for electric vehicles. It not only enables high-power EV charging but also mitigates power imbalance among charging ports. However, the BES modules in this architecture undergo frequent high-power charge–discharge cycles to compensate for dynamic load variations, thereby accelerating battery degradation and reducing system lifetime. To address this issue, an optimized control framework is proposed for the integrated BES modules to reduce battery stress while ensuring fast convergence of state of charge (SoC) across all distributed units. The proposed optimization-based BES power management strategy is based on the intrinsic power-imbalance limits of the CHB rectifier submodules. These limits are analytically derived as a function of the total duty cycle and subsequently incorporated as constraints in a quadratic optimization problem. The objective is to minimize BES power utilization by using the BES module's battery power only when necessary, while maintaining the SoC of all modules close to their reference values. The effectiveness of the proposed control strategy is validated through detailed MATLAB/ Simulink simulations under highly dynamic EV charging scenarios, including random arrival and departure of vehicles with varying power demands. Furthermore, the proposed approach is experimentally verified on a laboratory-scale prototype, demonstrating agreement with simulation results. Both simulation and experimental findings confirm that the proposed method successfully maintains CHB operation within the feasible region, ensures stable DC-link voltage balancing, and significantly reduces unnecessary BES power cycling while achieving reliable SoC regulation.