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.

Today’s ECUs (Electronic Control Units) face a high-power density mounted in a very small volume due to miniaturisation, available space, and weight limitations. For this reason, the resulting heat dissipation has become increasingly difficult to manage and continuous efforts are being made to optimize thermal management in this direction. This paper shows an improvement in heat dissipation by finding an optimal configuration between the fan speed and the distance between the cooling fins using the Design for Six Sigma methods. The focus was on finding a reliable transfer function that could predict the influence of the identified critical design parameters. Two transfer functions were derived and analysed in parallel; one based on Design of Experiments (DoE) and another based on simplified thermal theory. The accuracy of the transfer function and predictions were compared with the results of thermal simulations performed in the Ansys Icepack program. This shows that the use of the DoE method based on a small number of simulations is sufficient to estimate the behaviour of the ECU, without using a more complex theoretical approach.