Efficient PEEC-Based Simulations using Reluctance Method for Power Electronic Applications

Authors

  • Danesh Daroui Department of Computer Science, Electrical and Space Engineering Luleå University of Technology, Luleå, 971 87, Sweden
  • Jonas Ekman Department of Computer Science, Electrical and Space Engineering Luleå University of Technology, Luleå, 971 87, Sweden

Keywords:

PEEC, electromagnetic simulation, reluctance, GPU

Abstract

This paper presents a partial element equivalent circuit (PEEC)-based solver that has been accelerated to exploit the massively parallel structure of graphics processing unit (GPU) technology, in order to employ a reluctance-based method in an efficient way. A grouping algorithm is also presented which makes reluctance calculation efficient, suitable for GPUs, and feasible even for very large problems. It has been shown that by using the reluctance method, the coefficient matrix in the system equation can be safely sparsified whilst the required accuracy is maintained. Because the calculation of the reluctance matrix includes matrix inversion, which is a task with high computational complexity, GPUs as cooperative units are utilized to reduce computational costs by taking advantage of parallelism. Two test models have been simulated and analyzed to benchmark the solver, and the results have been compared with the previously developed solver. Furthermore, analyzing the results reveals that the reluctance method makes it possible to use a considerably sparser system and thereby solve large problems by decreasing the memory demands and the solution time. It is also proven that the solution is reliable and accurate, whereas the problem has become noticeably smaller.

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References

A. Nishizawa, M. Shimazaki, and S. Tanabe. “Ground Bouncing Analysis Using a Program Linking FDTD and SPICE,” In Proc. of Int. Symposium on Elctromagnetic Compatibility, Seattle, WA, USA, 1999.

A. E. Ruehli. “Equivalent Circuit Models for Three Dimensional Multiconductor Systems,” IEEE Transactions on Microwave Theory and Techniques, MTT-22, no. 3, pp. 216-221, March 1974.

A. E. Ruehli. “Inductance Calculations in a Complex Integrated Circuit Environment,” IBM Journal of Research and Development, vol. 16, no. 5, pp. 470-481, September 1972.

A. E. Ruehli, P. A. Brennan. “Efficient Capacitance Calculations for Three Dimensional Multiconductor Systems,” IEEE Transactions on Microwave Theory and Techniques, MTT-vol. 21 no. 2 pp. 76-82, February 1973.

Z. Song, F. Duval, D. Su, and A. Louis. “Stable Partial Inductance Calculation for Partial Element Equivalent Circuit Modeling,” Applied Computational Electromagnetics Society (ACES) Journal, vol. 25, no. 9, 2010.

G. Antonini, G. Miscione, and J. Ekman. “PEEC Modeling of Automotive Electromagnetic Problems,” Applied Computational Electromagnetics Society (ACES) Newsletter, vol. 23, no. 1, pp. 39-50, March 2008.

D. Daroui and J. Ekman. “Parallel Implementation of the PEEC Method,” Applied Computational Electromagnetics Society (ACES) Journal, vol. 25, no. 5, pp. 410-422, May 2010.

D. Daroui and J. Ekman. “Performance Analysis of Parallel Nonorthogonal PEEC-based Solver for EMC Applications,” Progress In Electromagnetics Research B, vol. 41, pp. 77-100, 2012.

H. Ji, A. Devgan, and W. Dai. “KSPICE: Efficient and Stable RKC Simulation for Capturing On-chip Inductance Effect,” Technical Report, University of California, April 2000.

Y. B. Tao, H. Lin, and H. J. Bao. “From CPU to GPU: GPU-based Electromagnetic Computing (GPUECO),” Progress In Electromagnetic Research, vol. 8, no. 1, pp. 1-19, 2008.

M. J. Inman and A. Z. Elsherbeni. “GPU Acceleration of Linear Systems for Computational Electromagnetic Simulations,” In Proc. of the IEEE Int. Symposium on Antennas and Propagation Society, Charleston, SC, USA, 2009.

M. Ujaldon. “Using GPUs for Accelerating Electromagnetic Simulations,” Applied Computational Electromagnetics Society (ACES) Journal, vol. 25, no. 4, 2010.

M. J. Inman and A. Z. Elsherbeni. “FDTD Calculations using Graphical Processing Units,” In Proc. of the IEEE Conf. on Wireless Communications and Applied Computational Electromagnetics, HI, USA, 2005.

V. Demir and A. Z. Elsherbeni. “Compute Unified Device Architecture (CUDA) Based FiniteDifference Time-domain (FDTD) Implementation,” Applied Computational Electromagnetics Society (ACES) Journal, vol. 25, no. 4, pp. 303-314, April 2010.

T. Topa, A. Karwowski, and A. Noga. “Using GPU with CUDA to Accelerate MoM-based Electromagnetic Simulation of Wire-grid Models,” IEEE Antennas and Wireless Propagation Letters, vol. 10, pp. 324-345, 2011.

S. Ramo, J. R. Whinnery and T. Van Duzer, Fields and Waves in Communication Electronics, John Wiley and Sons, 1994.

A.E. Ruehli, G. Antonini, J. Esch, A. Mayo J. Ekman, and A. Orlandi. “Non-orthogonal PEEC Formulation for Time and Frequency Domain EM and Circuit Modeling,” IEEE Transactions on Electromagnetic Compatibility, vol. 45, no. 2, pp. 167-176, May 2003.

C. Ho, A. Ruehli, P. Brennan. “The Modified Nodal Approach to Network Analysis,” IEEE Transactions on Circuits and Systems, pp. 504- 509, June 1975.

G. Antonini, J. Ekman, and A. Orlandi. “Full Wave Time Domain PEEC Formulation using a Modified Nodal Analysis Approach,” In Proc. of EMC Europe, Eindhoven, The Netherlands, 2004.

T.-H. Chen, C. Luk, H. Kim, C C.P. Chen. ”Inductwise: Inductance-wise Interconnect Simulator and Extractor,” In Proc. of the IEEE Int. Conf. on Computer Aided Design, pp. 215-220, San Jose, CA, Nov 2002.

H. Ji, A. Devgan, and W. Dai. “Ksim: A Stable and Efficient RKC Simulator for Capturing Onchip Inductance Effect,” In Proc. of Design Automation Conference, CA, USA, 2001.

C. Luk. “Efficient Inductance Extraction for Onchip Interconnect,” Technical report, University of Wisconsin-Madison, 2003.

S. Zenga, W. Yu, J. Shi X, Hong, and C. Cheng. “Efficient Partial Reluctance Extraction for Largescale Regular Power Grid Structures,” IEICE Transactions on Fundamentals, E92-A, no. 6, June 2009.

G. Zhong, C. Koh, V. Balakrishnan, and K. Roy, “An Adaptive Window-based Susceptance Extraction and its Efficient Implementation,” In Proc. of Design Automation Conference, IN, USA, 2003.

Intel Math Kernel Library (MKL). Online: http://software.intel.com/en-us/articles/intel-mkl/.

CULA A set of GPU-accelerated linear algebra libraries. Online: http://www.culatools.com/.

MUMPS A parallel sparse direct solver. Online: http://graal.ens-lyon.fr/MUMPS/.

M. L. Zitzmann. “Fast and Efficient Methods for Circuit-based Automotive EMC Simulation”, PhD thesis, University of Erlangen-Nürnberg, February 2007.

P. R. Amestoy, T. A. Davis, and I. S. Duff. “An Approximate Minimum Degree Ordering Algorithm,” SIAM Journal on Matrix Analysis and Applications, vol. 17, pp. 886-905, 1996.

METIS A Software Package for Partitioning Unstructured Graphs, Meshes, and Computing Fill-Reducing Orderings of Sparse Matrices. Online:http://glaros.dtc.umn.edu/gkhome/views/m etis/.

Iain S. Duff. “Developments in Matching and Scaling Algorithms,” Proc. of Appl. Math. Mech., vol. 7, no. 1, Aug 2007.

The Tesla M class GPU modules. Online: http://www.nvidia.com/object/preconfiguredclusters.html.

K. C. Huang, P. C. Wu, and F. J. Wang. “Parallelizing a Level 3 BLAS Library for LANConnected Workstations,” In Proc. of Second Symposium on Autonomous Decentralized Systems, Arizona, USA, April 1995.

S. Van Acker, P. Salenbien, and A. Cosaert. “Predictability of the Behavior of Power Distribution Components in Power Conversion Applications,” In PCIM Conference, Shanghai, China, March 2005.

A. Rodríguez, J. S. Lai, and F. Z. Peng. “Multilevel Inverters: A Survey of Topologies Controls, and Applications,” IEEE Transactions on Industrial Electronics, vol. 49, no. 4, August 2002.

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Published

2021-11-12

How to Cite

[1]
D. . Daroui and J. . Ekman, “Efficient PEEC-Based Simulations using Reluctance Method for Power Electronic Applications”, ACES Journal, vol. 27, no. 10, pp. 830–841, Nov. 2021.

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