@Article{ee.2025.069764,
AUTHOR = {Wan Chen, Zhi Liu, Yingxue Ma, Cuicui Wang, Xinfa Gu, Baolian Liu, Lei Shen, Hui Huang, Jie Ji},
TITLE = {Hardware-Algorithm Co-Design: SiC Bidirectional Converters with MPC-Fuzzy Logic Control for Robust Operation of Solar-Powered EV Hubs},
JOURNAL = {Energy Engineering},
VOLUME = {123},
YEAR = {2026},
NUMBER = {3},
PAGES = {--},
URL = {http://www.techscience.com/energy/v123n3/66412},
ISSN = {1546-0118},
ABSTRACT = {In order to solve the problems of slow dynamic response and difficult multi-source coordination of solar electric vehicle charging stations under intermittent renewable energy, this paper proposes a hardware-algorithm co-design framework: the T-type three-level bidirectional converter (100 kHz switching frequency) based on silicon carbide (SiC) MOSFET is deeply integrated with fuzzy model predictive control (Fuzzy-MPC). At the hardware level, the switching trajectory and resonance suppression circuit (attenuation resonance peak 18 dB) are optimized, and the total loss is reduced by 23% compared with the traditional silicon-based IGBT. At the algorithm level, the adaptive parameter update mechanism and multi-objective rolling optimization are adopted, and the 5 ms level dynamic power allocation is realized by relying on edge computing. Experiments on 800 V DC microgrid (including 600 kW photovoltaic and 150 A·h energy storage) built based on MATLAB/Simulink hardware-in-the-loop (HIL) platform show that the system shortens the battery charging time from 42 to 28 min (the charging speed is increased by 33%). Through the 78% valley power utilization rate, the power purchase cost of high-priced power grids was significantly reduced, and the levelized electricity price decreased by 10.3%; Under the irradiation fluctuation, the renewable energy consumption rate increases by 10.1%, and the DC bus voltage fluctuation is stable within ±10 V when the load step is ±30%. The co-design provides an economically feasible and dynamically robust solution for the efficient integration of PV-ESG-EV in the smart grid.},
DOI = {10.32604/ee.2025.069764}
}