Energy Mutual Aid Converter with Fractional-Order Model Predictive Control for Field Medical Electric Vehicles

Although electric vehicles have been widely adopted in recent years, insufficient charging infrastructure in remote areas may still compromise the continuity of emergency operations involving field medical electric vehicles (EVs). Motivated by the need for temporary DC energy support from a donor vehicle to a field medical EV, this paper investigates an isolated DC–DC energy-sharing converter based on a series-resonant dual-active-bridge (SRDAB) topology and its associated control method. First, the SRDAB converter is employed to satisfy the requirements of low-voltage input, galvanic isolation, voltage step-up, and DC power transfer. Based on the fundamental harmonic approximation (FHA), a steady-state power relationship and a control-oriented dynamic model are derived to characterize the coupling between the phase-shift angle, transferred power, and output voltage. Subsequently, a fractional-order model predictive control strategy tuned offline using the grey wolf optimizer (GWO-FOMPC) is developed to address donor-side input-voltage variations, recipient-side equivalent-load disturbances, and the nonlinear power-transfer characteristics of the SRDAB converter. In this strategy, a fractional-order proportional–integral outer loop generates the reference transferred power, while a fractional-order predictive inner loop analytically determines the phase-shift command online. Finally, simulations and converter-level experiments validate the dynamic regulation performance of the proposed control strategy under emulated energy-sharing conditions for field medical EVs.

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Publication Details

Journal
Fractal and Fractional
Published
2026-07-27
DOI
https://doi.org/10.3390/fractalfract10080511
Primary Topic
Wireless Power Transfer Systems
Type
article
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article

Energy Mutual Aid Converter with Fractional-Order Model Predictive Control for Field Medical Electric Vehicles

Xiaozhi Liu, Chuang Huang
Fractal and Fractional
Wireless Power Transfer Systems
article

Energy Mutual Aid Converter with Fractional-Order Model Predictive Control for Field Medical Electric Vehicles

Xiaozhi Liu, Chuang Huang
article en

Abstract

Although electric vehicles have been widely adopted in recent years, insufficient charging infrastructure in remote areas may still compromise the continuity of emergency operations involving field medical electric vehicles (EVs). Motivated by the need for temporary DC energy support from a donor vehicle to a field medical EV, this paper investigates an isolated DC–DC energy-sharing converter based on a series-resonant dual-active-bridge (SRDAB) topology and its associated control method. First, the SRDAB converter is employed to satisfy the requirements of low-voltage input, galvanic isolation, voltage step-up, and DC power transfer. Based on the fundamental harmonic approximation (FHA), a steady-state power relationship and a control-oriented dynamic model are derived to characterize the coupling between the phase-shift angle, transferred power, and output voltage. Subsequently, a fractional-order model predictive control strategy tuned offline using the grey wolf optimizer (GWO-FOMPC) is developed to address donor-side input-voltage variations, recipient-side equivalent-load disturbances, and the nonlinear power-transfer characteristics of the SRDAB converter. In this strategy, a fractional-order proportional–integral outer loop generates the reference transferred power, while a fractional-order predictive inner loop analytically determines the phase-shift command online. Finally, simulations and converter-level experiments validate the dynamic regulation performance of the proposed control strategy under emulated energy-sharing conditions for field medical EVs.

Fractal and FractionalVol. 10(8)
Northeastern University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 16%
Wireless Power Transfer Systems
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Energy Mutual Aid Converter with Fractional-Order Model Predictive Control for Field Medical Electric Vehicles — Xiaozhi Liu, Chuang Huang · Fractal and Fractional (2026) | TGRS Research Map | TGRS