Broad-Scale Converter Optimization Utilizing Discrete Time State-Space Modeling

Schematic-level optimization and steady-state loss modeling play a vital role in the design of advanced power converters. Recently, discrete time state-space modeling has shown merits in rapid analysis and generality to arbitrary circuit topologies but has not yet been utilized under rapid optimization techniques. In this work, we investigate methods for the incorporation of rapid gradient-based optimization techniques leveraging discrete time state-space modeling and showcase the utility of the approach for use in the converter design process.