Thermal and EMI Modeling and Analysis of a Boost PFC Circuit Designed Using a Genetic-based Optimization Algorithm

• Main Author: Hertz, Erik M.
• Other Authors: Electrical and Computer Engineering
• Format: Others
• Published: Virginia Tech 2014
• Subjects: power factor correction (PFC); electromagnetic interference (EMI); genetic algorithms; temperature rise; per unit analysis; optimization
• Online Access: http://hdl.handle.net/10919/34234; http://scholar.lib.vt.edu/theses/available/etd-07292001-191001/

The boost power factor correction (PFC) circuit is a common circuit in power electronics. Through years of experience, many designers have optimized the design of these circuits for particular applications. In this study, a new design procedure is presented that guarantees optimal results for any application. The algorithm used incorporates the principles of evolution in order to find the best design. This new design technique requires a rethinking of the traditional design process. Electrical models have been developed specifically for use with the optimization tool. One of the main focuses of this work is the implementation and verification of computationally efficient thermal and electro-magnetic interference (EMI) models for the boost PFC circuit. The EMI model presented can accurately predict noise levels into the 100's of kilohertz range. The thermal models presented provide very fast predictions and they have been adjusted to account for different thermal flows within the layout. This tuning procedure results in thermal predictions within 10% of actual measurement data. In order to further reduce the amount of analysis that the optimization tool must perform, some of the converter design has been performed using traditional methods. This part of the design is discussed in detail. Additionally, a per unit analysis of EMI and thermal levels is introduced. This new analysis method allows EMI and thermal levels to be compared on the same scale thus highlighting the tradeoffs between the both behaviors. === Master of Science