Quantization-based simulation of switched mode power supplies

In this article we study the performance of quantized state system algorithms in the simulation of switched mode power supplies. Under realistic modeling assumptions, these models are stiff and exhibit frequent discontinuities, making them difficult to simulate with classic solvers. However, there a...

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Detalles Bibliográficos
Autores: Migoni, Gustavo Andres, Kofman, Ernesto Javier, Bergero, Federico, Fernandez, Joaquin
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/15250
Acceso en línea:http://hdl.handle.net/11336/15250
Access Level:acceso abierto
Palabra clave:Hybrid Systems Simulation
Quantized State Systems
Switched Mode Power Supplies
https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
Descripción
Sumario:In this article we study the performance of quantized state system algorithms in the simulation of switched mode power supplies. Under realistic modeling assumptions, these models are stiff and exhibit frequent discontinuities, making them difficult to simulate with classic solvers. However, there are linearly implicit quantized state system methods that can efficiently handle these types of systems, providing faster and more accurate results. In order to corroborate these features, we first built the models corresponding to the different topologies of switched mode power supplies, and then analyzed the resulting equation structures in order to establish whether they can be efficiently simulated by linearly implicit quantized state system algorithms. Finally, we compared the simulation performance of linearly implicit quantized state systems with the widely used DASSL solver. The results showed that the linearly implicit quantized state systems were 3–200 times faster and noticeably more accurate than the differential algebraic system solver.