Heat Transfer Optimization of an Electronic Control Unit Immersed in Forced Liquid Coolant

The current paper aims to present a cooling concept for future centralized platforms of ECUs (Electronic Control Units) from the automotive industry that involves grouping multiple electronic devices into a single system and cooling them with forced convection dielectric coolant. The enhancement consists of replacing the inside air of the module with a dielectric coolant that has a higher thermal conductivity than air and employing an additional prototype system that aids in forced liquid cooling. To meet automotive requirements, the experiments were exposed to an ambient temperature of 85 C-?. Temperature measurements on these solutions' hot spots were compared to those on a thermal paste-only reference electronic module. This study used DFSS (Design for Six Sigma) techniques to determine the ideal pump flow rate, fan air flow rate, and liquid volume in the housing, leading to an optimization in heat dissipation. Finding a trustworthy transfer function that could forecast the impact of the crucial design parameters that had been found was the main goal. The electronics cooled by forced convection coolant improved heat dissipation by up to 60% when compared to the reference module. This demonstrates that the DoE (Design of Experiments) method, which is based on a limited number of measurements, can estimate the behavior of the ECU without the need for a more involved theoretical framework.

Automated summary

This paper proposes a novel cooling concept for future centralized platforms of ECUs in the automotive industry by grouping multiple electronic devices into a single system and cooling them with forced convection dielectric coolant. The improvement is achieved by replacing the inside air with a dielectric coolant and employing an additional prototype system for forced liquid cooling. The study uses DFSS techniques to optimize heat dissipation and demonstrates that forced convection coolant can improve heat dissipation by up to 60% compared to reference modules.