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Title: Steady-State Convergence of Discrete Time State-Space Modeling with State-Dependent Switching
Steady-state modeling plays an important role in the design of advanced power converters. Typically, steady-state modeling is completed by time-stepping simulators, which may be slow to converge to steady-state, or by dedicated analysis, which is time-consuming to develop across multiple topologies. Discrete time state-space modeling is a uniform approach to rapidly simulate arbitrary power converter designs. However, the approach requires modification to capture state-dependent switching, such as diode switching or current programmed modulation. This work provides a framework to identify and correct state-dependent switching within discrete time state-space modeling and shows the utility of the proposed method within the power converter design process.  more » « less
Award ID(s):
1751878
NSF-PAR ID:
10211924
Author(s) / Creator(s):
;
Date Published:
Journal Name:
2020 IEEE 21st Workshop on Control and Modeling for Power Electronics (COMPEL)
Page Range / eLocation ID:
1 to 8
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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