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 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.

[1]  Gabriel A. Wainer,et al.  M/CD++: modeling continuous systems using Modelica and DEVS , 2005, 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.

[2]  François E. Cellier,et al.  Linearly implicit quantization-based integration methods for stiff ordinary differential equations , 2013, Simul. Model. Pract. Theory.

[3]  Bernard P. Zeigler,et al.  On the stability and performance of discrete event methods for simulating continuous systems , 2007, J. Comput. Phys..

[4]  Ernesto Kofman,et al.  A stand-alone quantized state system solver for continuous system simulation , 2014, Simul..

[5]  Francis Labrique,et al.  Switch-Mode Power Supplies , 1993 .

[6]  François E. Cellier,et al.  Quantization-Based New Integration Methods for Stiff ODEs. , 2012 .

[7]  Michael Tiller,et al.  Introduction to Physical Modeling with Modelica , 2001 .

[8]  François E. Cellier,et al.  Continuous System Simulation , 2006 .

[9]  Peter A. Fritzson,et al.  Principles of object-oriented modeling and simulation with Modelica 2.1 , 2004 .

[10]  Ernesto Kofman,et al.  A Third Order Discrete Event Simulation Method for Continuous System Simulation , 2006 .

[11]  Simon S. Ang.  Power-Switching Converters , 1995 .

[12]  KofmanErnesto,et al.  Quantized-state systems , 2001 .

[13]  J. H. Alimeling,et al.  PLECS-piece-wise linear electrical circuit simulation for Simulink , 1999, Proceedings of the IEEE 1999 International Conference on Power Electronics and Drive Systems. PEDS'99 (Cat. No.99TH8475).

[14]  Christophe Basso,et al.  Switch-Mode Power Supplies Spice Simulations and Practical Designs , 2008 .

[15]  Federico Bergero,et al.  PowerDEVS: a tool for hybrid system modeling and real-time simulation , 2011, Simul..

[16]  Paul W. Tuinenga,et al.  SPICE: A Guide to Circuit Simulation and Analysis Using PSpice , 1988 .

[17]  Ernesto Kofman,et al.  Discrete Event Simulation of Hybrid Systems , 2004, SIAM J. Sci. Comput..

[18]  Mamadou Kaba Traoré,et al.  VLE: a multimodeling and simulation environment , 2007, SCSC.

[19]  Ernesto Kofman,et al.  Quantized-state systems: a DEVS Approach for continuous system simulation , 2001 .

[20]  Peter Fritzson,et al.  Principles of Object-Oriented Modeling and Simulation with Modelica 3.3: A Cyber-Physical Approach , 2014 .

[21]  François E. Cellier,et al.  Quantised State System Simulation in Dymola/Modelica using the DEVS Formalism , 2006 .

[22]  Ernesto Kofman,et al.  A Second-Order Approximation for DEVS Simulation of Continuous Systems , 2002, Simul..

[23]  Ernesto Kofman,et al.  Quantized state simulation of spiking neural networks , 2012, Simul..

[24]  Bernard P. Zeigler,et al.  The Activity-tracking paradigm in discrete-event modeling and simulation: The case of spatially continuous distributed systems , 2011, Simul..

[25]  François E. Cellier,et al.  Quantization-based new integration methods for stiff ordinary differential equations , 2012, Simul..