Bidirectional reduced-order electrothermal modeling of power MOSFETs for electric vehicle thermal management applications
Thermal management of power MOSFETs in electric vehicle applications presents critical challenges due to nonlinear electrothermal coupling that invalidates conventional decoupled thermal models. This work develops a bidirectional electrothermal co-simulation framework combining experimental characte...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-10-01
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| Series: | Case Studies in Thermal Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X25010500 |
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| Summary: | Thermal management of power MOSFETs in electric vehicle applications presents critical challenges due to nonlinear electrothermal coupling that invalidates conventional decoupled thermal models. This work develops a bidirectional electrothermal co-simulation framework combining experimental characterization with reduced-order modeling using Proper Orthogonal Decomposition (POD) and Linear Time-Invariant (LTI) system identification. Comprehensive validation using TO-263 packaged MOSFETs under constant power, dynamic cycling, and standardized driving cycles (UDDS, US06, NYCC) demonstrates exceptional accuracy with maximum temperature errors below 5.1 % while achieving over 99 % computational reduction compared to CFD approaches. The framework successfully captures self-reinforcing thermal feedback, where on-state resistance increases 60 % (9.9 mΩ–15.9 mΩ) as junction temperature rises from 25 °C to 90 °C. Significantly, driving cycle analysis reveals counterintuitive behavior: highway driving (US06) generates higher average junction temperatures (33.7 °C) than aggressive urban driving (NYCC, 29.6 °C), challenging traditional worst-case thermal design methodologies. This demonstrates thermal accumulation depends more on sustained power demands than instantaneous peaks, revealing distinct reliability impacts through different degradation mechanisms. The validated framework enables real-time thermal-electrical parameter coupling, offering transformative potential for intelligent thermal management, digital twin integration, and energy conversion optimization in next-generation electric vehicle powertrains. |
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| ISSN: | 2214-157X |