Host
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Client & task
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Objectives
The increasing adoption of wide-bandgap (WBG) semiconductors in power converters has led to operation at higher switching frequencies with steep voltage and current transitions. These conditions introduce complex multi-harmonic behaviour, rapid transient dynamics, and strong electromagnetic-thermal couplings that are challenging to capture with traditional time-stepping finite-element (FE) solvers. Steady-state analysis, in particular, becomes computationally expensive when considering high-frequency PWM waveforms or non-sinusoidal excitation.
Harmonic-balance (HB) simulation, combining sinusoidal and PWM time-domain basis functions, provides a powerful alternative for efficiently modelling steady-state behaviour, while enabling accurate assessment of losses in magnetic cores, windings, and circuit parasitics. Integrating multi-scale material models and homogenisation techniques further enhances predictive accuracy, capturing core, skin, and proximity effects. This project develops a multi-physical HB FE and circuit simulator that bridges the gap between component-level magnetic characterisation and system-level converter performance, validated on real industrial power supplies.
Objectives 1
Develop a harmonic-balance (multi-harmonic) FE and circuit simulator for PE converters, integrating (co)sinusoidal and PWM time-domain basis functions (multirate) for steady-state analysis.
Objectives 2
Incorporate dedicated material laws and multi-scale/homogenisation techniques to account for core, skin, and proximity-effect losses in magnetics.
Objectives 3
Perform ad hoc numerical characterisations of materials and windings, considering all relevant time-domain basis functions (slow and fast dynamics).
Objectives 4
Extend the analysis to transient states with optimised magneto-thermal coupling.
Objectives 5
Apply the developed models and techniques in practical industrial test cases, including real-life power supply systems.
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Expected Results
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67%
Associated core material and winding numerical characterisation.
260%
Validation via several test cases.
Sed fringilla gravida lorem, id rhoncus justo egestas sed. Nulla sagittis vel ante sit amet neque non tellus interdum tincidunt eget eu odio. Awesome!
