Innovative Control and Energy Management of DC Microgrids with Hybrid Storage: Enabling E-Mobility and Hydrogen Energy Solutions

The present work is mainly divided into two major parts. The first part deals with the basic overview of MGs, advanced power converter topologies for ESSs integration with MGs, and three case studies of DC MGs aiming to power the e-mobility sector. Similarly, in the second part, HESS applications for EV electrification are presented using advanced control algorithms and market analysis of EV fast-charging products. The present work is structured into chapters organized as follows.Chapter One: presents a general overview of the DC MG structure and the current state of the art regarding the focus of the thesis (energy management system and controls). The chapter summarizes the general perspective and existing work in the field of EMS and control of DC MGs.Chapter Two: presents advanced control strategies for four-switch single inductor buck-boost converters (FSIBB) and FSIBB DC-DC interleaving converters advised for energy storage systems for e-mobility and MGs. A dual-loop non-linear control design is proposed to enhance voltage regulation, current control, and stability. Real-time performance is validated through simulation (Simulink, PLECS) and controller hardware-in-loop (C-HIL) testing, demonstrating the effectiveness of these converters and controllers in practical applications.In Chapter Three, a two-layer control system designed for efficient power sharing and stability in DC microgrids for EV charging, incorporating energy storage systems and bidirectional converters. The upper layer employs an improved droop control for load distribution, while a nonlinear barrier-based sliding mode control provides robust voltage and current tracking for converters. Real-time validation through hardware-in-loop (HIL) testing and MATLAB simulations confirm the effectiveness of the system in various load scenarios.In Chapter Four an advanced control strategy for a DC microgrid based on photovoltaic batteries is designed to power an electrolyzer-based hydrogen production system. Employing a three-phase interleaved topology and a cascaded hybrid non-linear controller, the chapter addresses efficient power sharing, maximum power extraction from PV, and robust voltage regulation. Stability and performance are confirmed through MATLAB simulations and real-time experimental testing, ensuring reliable power delivery for hydrogen generation.Chapter Five presents a neurofuzzy energy management system designed to integrate renewable sources (PV and fuel cells) with battery supercapacitor storage in microgrids to charge electric vehicles. The system ensures a balanced bidirectional power flow with the grid, adapting dynamically to variable load demands and generation levels. Through simulation testing, the approach demonstrates effective energy distribution, optimizing grid interaction by drawing or supplying power as needed to maintain stability in the microgrid.Chapter Six deals with managing and controlling a hybrid energy storage system (HESS) using a master-slave control strategy. A fuzzy rule-based algorithm optimizes power sharing, with the master control guiding a synergetic terminal slave controller for precise tracking. Stability is validated through Lyapunov analysis, and the proposed method is rigorously tested in MATLAB/Simulink under the World-wide Harmonized Light Vehicle Test Procedure (WLTP), ensuring its effectiveness in real-world scenarios.In Chapter Seven work carried out during the industrial period is summarized. The technical aspects and workings of the different products, such as "OMHERO" and "PRY-CAM," are explained. A detailed study of electric vehicle charging systems and a benchmark market analysis of electric vehicle chargers is discussed, which can be used for further product development. Finally, real-time data of a domestic home load are considered to study the impact of EV wallbox and photovoltaics on energy communities.