Thermal placement optimization for embedded resistances based on orthogonal design and fuzzy genetic algorithm

Sheet resistance, resistor surface area, distance between the stack embedded resistor layers, distances between the surface of PCB and first layer of embedded resistor layers, distance between the stack embedded resistors in the same layer and current magnitude are selected as six key factors, which affect the temperature distribution. By using orthogonal array, the embedded resistor finite element analysis models which have different configuration parameters´ levels combinations are designed. Simulation analysis of temperature field are carried out by using these models. The data of temperatures of stacked embedded resistors are analyzed variance analysis. With 90% of confidence, sheet resistance has the most significant effect on the temperature. Therefore, the research object is sheet resistance layout of resistance element in embedded substrate, which is optimizated by Fuzzy Genetic Algorithm The optimization result has more equal distribution of temperature, both of the highest temperature and the maximum temperature difference have a significant decrease. The effectiveness of the algorithm is verified by testing the temperature distribution of experimental samples through the infrared thermometer.