The development of a fully automated tool that is used to optimize the design of a hybrid switch soft-switching inverter using a library of dynamic electro-thermal component models parameterized in terms of electrical, structural and material properties is presented. A multi-scale electro-thermal simulation approach is developed allowing for a large number of parametric studies involving multiple design variables to be considered, drastically reducing simulation time.

Traditionally, electro-thermal simulation and analysis has been used to predict the behavior of pre-existing designs. While the traditional approach to electro-thermal analysis can help shape cooling requirements and heat sink designs to maintain certain junction temperatures, there is no guarantee that the design under study is the most optimal. This dissertation uses electro-thermal simulation to guarantee an optimal design and thus truly minimizing cooling requirements and improving device reliability.

The proposed optimization tool is used to provide a step-by-step design optimization of a two-coupled magnetic hybrid soft-switching inverter. The soft-switching inverter uses a two-coupled magnetic approach for transformer reset condition [1], a variable timing control for achieving ZVS over the entire load range [2], and utilizes a hybrid switch approach for the main device [3]. Design parameters such as device chip area, gate drive timing control and external resonant capacitor and inductor are used to minimize device loss subject to design constraints such as converter minimum on-time, maximum device chip area, and transformer reset condition. Since the amount of heat that is dissipated has been minimized, the optimal cooling requirements can be determined by reducing the cooling convection coefficients until desired junction temperatures are achieved.

The optimized design is then compared and contrasted with an already existing design from the Virginia Tech freedom car project using the generation II module. It will be shown that the proposed tool improves the baseline design by 16% in loss and reduces the cooling requirements by 42%. Validation of the device model against measured data along with the procedures for device parameter extraction is also provided. Validation of the thermal model against measured data is also provided.