Fast and Accurate Three-Dimensional Thermal Model Based on Discrete Green's Function for Power Electronics
A fast and accurate three-dimensional thermal modeling methodology based on discrete Green's function (DGF) is investigated innovatively for power electronics. Due to the demand of high robustness of power electronic systems, power devices require a fast and accurate thermal prediction or monitoring method. DGF is presented as a promising temperature prediction method, especially when facing new challenges in the complex chip packaging of power devices or the multichip layout of power modules. A detailed simulation algorithm is developed, and comparative simulations is conducted, demonstrating that the DGF method reduces computation time by more than 78% compared to the finite element method (FEM), with the same accuracy. In a double chip simulation, the result of DGF method closely matches the FEM's, demonstrating its superior accuracy in dealing with thermal coupling effects compared to traditional thermal network. Finally, an infrared thermography experiment is designed, validating the high accuracy, which indicated by the R-squared value that is over 0.98 between the results of the DGF method and experimental observations.
Authors
- Yuqiao Zhang (ORCID: https://orcid.org/0009-0003-2482-8873)
- Yourun Zhang (ORCID: https://orcid.org/0000-0002-8474-2559)
- Bo Zhang (ORCID: https://orcid.org/0000-0003-1288-1549)
- Wan‐Li Ma (ORCID: https://orcid.org/0000-0001-6822-8587)
- Maojiu Luo (ORCID: https://orcid.org/0000-0002-1469-5494)
- Li Li (ORCID: https://orcid.org/0009-0009-9137-9127)
Institutions
- University of Electronic Science and Technology of China (CN)
- National Engineering Research Center of Electromagnetic Radiation Control Materials (CN)
- Gree (China) (CN)
Publication Details
- Journal
- IEEE Transactions on Power Electronics
- Published
- 2025-02-13
- DOI
- https://doi.org/10.1109/tpel.2025.3537984
- Citations
- 2
- Primary Topic
- Engineering Applied Research
- Type
- article
- Field-Weighted Citation Impact
- 1.91
Funders
- National Natural Science Foundation of China