Research on the uniform temperature of heat dissipation for the reverse oblique microchannel

As the power density of power devices/modules increases, power devices/modules are more demanding for heat dissipation. Liquid-cooled microchannels have strong heat transfer capabilities and will become an important way for high-power electronic devices/modules to dissipate heat. However, uneven heat dissipation of microchannels will cause excessive temperature gradients and local high temperature hot spots, and long-term operation will lead to power module solder layers fatigue, aging and degradation of its own heat dissipation capacity, which will affect the reliability of power devices/modules for long-term operation under complex working conditions. Therefore, it is of great significance to strengthen the heat dissipation capacity of the microchannel and improve the temperature uniformity of the liquid-cooled microchannel heat dissipation. In this paper, based on the microchannel enhanced heat transfer technology, We have designed a new type of liquid-cooled the ROMC(reverse oblique microchannel). Firstly, the heat dissipation characteristics of the ROMC and the RSMC (rectangular straight microchannel) are compared through experiments, and it is found that the heat transfer capacity and heat dissipation uniformity of the ROMC are significantly better than the RSMC. Next analyze the flow, heat transfer characteristics and wall temperature uniformity of the ROMC by means of numerical simulation. The results showed that: (1)When Re number, the number of oblique channel and the oblique spacing are constant, reducing the oblique angle and increasing the oblique distance can enhance heat transfer and improve the heat dissipation capacity and wall temperature uniformity of the ROMC. (2)When the number of oblique channel, oblique angle, oblique distance and oblique spacing are constant, increasing Re number can significantly improve the heat dissipation capacity and wall temperature uniformity of the ROMC. Finally, this paper uses the MOGA (multi-objective genetic algorithm) to optimize the wall temperature, temperature difference of the ROMC. Compared with the model before optimization, the maximum bottom wall temperature of the ROMC is 323.33K, the reduction rate is 0.75%, and the wall temperature difference is 10.50 K, the reduction rate is 17.52%.