Dual-Metric-Driven Thermal–Fluid Coupling Modeling and Thermal Management Optimization for High-Speed Electric Multiple Unit Electrical Cabinets

Yaxuan Wang, Cuifeng Xu (), Shushen Chen, Ziyi Deng and Zijun Teng
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Yaxuan Wang: School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541000, China
Cuifeng Xu: School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541000, China
Shushen Chen: School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541000, China
Ziyi Deng: School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541000, China
Zijun Teng: School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541000, China

Energies, 2025, vol. 18, issue 17, 1-23

Abstract: To address thermal management challenges in CR400BF high-speed EMU electrical cabinets—stemming from heterogeneous component integration, multi-condition dynamic thermal loads, and topological configuration variations—a dual-metric-driven finite element model calibration method is proposed using ANSYS Workbench. A multi-objective optimization function, constructed via the coefficient of determination ( R 2 ) and root mean square error ( R M S E ), integrates gradient descent to inversely solve key parameters, achieving precise global–local model matching. This establishes an equivalent model library of 52 components, enabling rapid development of multi-physical-field coupling models for electrical cabinets via parameterization and modularization. The framework supports temperature field analysis, thermal fault prediction, and optimization design for multi-topology cabinets under diverse operating conditions. Validation via simulations and real-vehicle tests demonstrates an average temperature prediction error ≤ 10 % , verifying reliability. A thermal management optimization scheme is further developed, constructing a full-process technical framework spanning model calibration to control for electrical cabinet thermal design. This advances precision thermal management in rail transit systems, enhancing equipment safety and energy efficiency while providing a scalable engineering solution for high-speed train thermal design.

Keywords: high-speed EMU; electrical cabinet; calibration of the dual-metric-driven model; multi-physical-field coupling simulation; thermal management optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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