An Autotuned Model Predictive Controller Design for Parallel Input Parallel output Modular DAB Converter For EV Charging Station

This paper proposed an adaptive model predictive controller for parallel input and parallel output (PIPO) modular dual active bridge (m-DAB) converter in electric vehicle charging applications. To obtain faster growth in charging conditions, two different control strategies i.e. PI and adaptive model predictive controller (AMPC) are compared to analyze and implement various phase shift techniques at different operating modes of operations. Also, detailed stability models are designed for both classical PI and AMPC with required frequency response analysis. In order to help with stability and robustness in operation, the proposed AMPC technique enables sufficient current and power-shifting among parallel modules. This approach significantly reduces current stress on power switches, simplifies control architecture, and mitigates thermal losses, thereby enhancing system lifespan. The extensive analysis for both clasical and proposed AMPC is verified in real-time simulation for different modes of operation.