Modeling plays a vital role in the design of advanced
power converters. Commonly, modeling is completed using either
dedicated hand analysis, which must be completed individually
for each topology, or time-stepping circuit simulations, which
are insufficiently rapid for broad analysis considering a wide
range of potential designs or operating points. Discrete time
state-space modeling of switching converters has shown merits
in rapid analysis and generality to arbitrary circuit topologies
but is hampered by difficulty incorporating nonlinear elements.
In this work, we investigate methods for the incorporation of
nonlinear elements into a generalized discrete time state-space
modeling framework and showcase the utility of the approach
for use in the converter design process.
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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.
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- Award ID(s):
- 1751878
- NSF-PAR ID:
- 10394230
- Date Published:
- Journal Name:
- IEEE Design Methodologies Conference (DMC)
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/DMC55175.2022.9906473
