Design, Control Optimisation, and Real-Time Hardware-in-the-Loop Validation of a Self-Sustained 50 kW EV Fast-Charging DC Microgrid

This manuscript has successfully presented the mathematical modelling, control loop optimisation, and real-time solver conditioning of an off-grid, hybrid 50 kW Level 3 EV fast-charging microgrid infrastructure. By implementing a zero-order Sugeno Fuzzy Logic Controller, the system overcomes the fractional-averaging and switch chattering limitations of conventional Mamdani fuzzy implementations. The controller yields deterministic, binary gating signals that route power smoothly across Solar PV, high-fidelity PEMFC, and BESS assets. Crucially, the study provides practical solutions for common simulation instability bottlenecks in high-power Simscape networks. The use of a discrete $1/z$ unit delay block effectively broke high-frequency algebraic loops within the fluidic fuel cell loops. Concurrently, optimised parallel RC snubber boundaries successfully suppressed destructive overvoltage spikes during aggressive switching transitions. Operating at a rigid fixed step ofwith a discrete solver setting, the model maintains absolute numerical convergence under all dynamic load profiles. The immediate future scope of this research involves compiling the verified model directly onto an OPAL-RT HIL hardware target. This step will allow for the empirical capture of physical execution latencies, computational task-allocation mapping across multi-core processors, and real-time communication interface latency validations under physical hardware stress constraints.

[1] X. Liu, "Microgrid Energy Management with Energy Storage Systems: A Review," IEEE Transactions on Smart Grid, vol. 15, no. 2, pp. 1120–1135, Mar. 2024. [2] B. Kanouni, A. E. Badoud, S. Mekhilef, M. Bajaj, and I. Zaitsev, "Advanced efficient energy management strategy based on state machine control for multi-sources PV-PEMFC-batteries system," Scientific Reports, vol. 14, no. 1, Art. no. 10997, Apr. 2024. [3] N. Castañeda-Arias, "Energy Management in Microgrid Systems: A Comprehensive Review Toward Bio-Inspired Approaches for Enhancing Resilience and Sustainability," Electricity, vol. 6, no. 4, pp. 73–95, Dec. 2025. [4] M. A. Hannan, M. S. Lipu, P. J. Ker, and K. M. Muttaqi, "Fuzzy Logic Control Applications in Microgrids and Renewable Energy Systems: A Systematic Review," IEEE Access, vol. 12, pp. 44510–44532, May 2024. [5] M. Cavus, D. Dissanayake, and M. Bell, "Deep-Fuzzy Logic Control for Optimal Energy Management: A Predictive and Adaptive Framework for Grid-Connected Microgrids," Energies, vol. 18, no. 4, Art. no. 995, Feb. 2025. [6] I. F. Davoudkhani et al., "Performance Evaluation of Fuzzy Logic-Based Energy Management Systems in Microgrids with Electric Vehicle Integration," Intelligent and Fuzzy Systems, vol. 3, pp. 20–29, Jul. 2025. [7] A. Prajapati, V. Bharadwaj, and K. Chaudhary, "Isolated DC microgrid operation with hybridization of PV, FC, and Battery," in Proc. IEEE Transportation Electrification Conference, Dec. 2023, pp. 1–6. [8] S. L. Chakravarty and K. Chaudhary, "Sliding Mode Control Based Analysis of Photovoltaic and Fuel Cell Integrated Hybrid Electric System," in Proc. IEEE SeFet, Jul. 2025, pp. 112–117. [9] M. S. Lipu, "Energy Intelligence: A Systematic Review of Artificial Intelligence and Hierarchical Control Architectures for Stable DC Microgrids," Applied Sciences, vol. 14, no. 23, Art. no. 11112, Dec. 2024. [10] D. Tejada, A. Castro, A. Monterroso, and M. A. Ridao, "Hydrogen and Battery–Based Energy Storage System (ESS) for Future DC Microgrids," Journal of Energy Storage, vol. 92, Art. no. 112104, Jul. 2025.