Application of the Multi-element Grid in EMC Uncertainty Simulation

Authors

  • Jinjun Bai College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China
  • Kaibin Guo College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China
  • Jingchao Sun Traction & Control State Key Lab, CRRC Dalian R& D Co., Ltd, Dalian, 116052, China
  • Ning Wang College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China

DOI:

https://doi.org/10.13052/2022.ACES.J.370408

Keywords:

Electromagnetic Compatibility, Uncertainty Analysis, Stochastic Collocation Method, Multi-Element Grid

Abstract

Uncertainty analysis is a research hotspot in the field of electromagnetic compatibility (EMC) simulation. The stochastic collocation method (SCM) is considered particularly suitable for uncertainty analysis in the EMC field because it is characterized by a high level of computational efficiency and accuracy while requiring no replacement solver. However, the post-processing process of the SCM is too complex, which will seriously limit its application in many industrial environments such as real-time simulation analysis. Multi-element grid (MEG) is a novel uncertainty analysis method recently for successful application in another area. It is proved that its calculation accuracy is same as the SCM, and its post-processing process is facile. This paper introduces the MEG to the EMC field and makes a detailed comparison between it and the SCM in performance, aiming to apply uncertainty analysis to solve more practical EMC engineering problems.

Downloads

Download data is not yet available.

Author Biographies

Jinjun Bai, College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China

Jinjun Bai received the B.Eng. degree in electrical engineering and automation in 2013, and the Ph.D. degree in electrical engineering in 2019 from the Harbin Institute of Technology, Harbin, China.

He is currently a Lecturer with Dalian Maritime University. His research interests include uncertainty analysis methods in EMC simulation, EMC problem of electric vehicles, and the validation of CEM.

Kaibin Guo, College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China

Kaibin Guo received the bachelor’s degree from Shandong Jiaotong University. He is currently studying at Dalian Maritime University for a master’s degree. His major is in electrical engineering. The main research direction is electric vehicle lithium battery SOC estimation.

Jingchao Sun, Traction & Control State Key Lab, CRRC Dalian R& D Co., Ltd, Dalian, 116052, China

Jingchao Sun received the B.Eng. and M.Eng. degrees in electrical engineering from Dalian Maritime University, Dalian, China, in 2009 and 2012, respectively, where she is currently working toward the Ph.D. degree.

She is currently an Electrical Engineer with the Dalian Electric Traction Research and Development Center, China CNR Corporation Ltd., Dalian, China. Her current research interests include unmanned crafts and their intelligent modeling and control.

Ning Wang, College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China

Jingchao Sun received the B.Eng. and M.Eng. degrees in electrical engineering from Dalian Maritime University, Dalian, China, in 2009 and 2012, respectively, where she is currently working toward the Ph.D. degree.

She is currently an Electrical Engineer with the Dalian Electric Traction Research and Development Center, China CNR Corporation Ltd., Dalian, China. Her current research interests include unmanned crafts and their intelligent modeling and control.

References

D. Xiu and G. E. Karniadakis, “The wIENER-aSKEY pOLYNOMIAL cHAOS FOR sTOCHASTIC dIFFERENTIAL eQUATIONS,” Journal on Scientific Computing, vol. 24, no. 2, pp. 619-644, 2002.

S. A. Pignari, G. Spadacini, and F. Grassi, “Modeling field-to-wire coupling in random bundles of wires,” IEEE Electromagnetic Compatibility Magazine, vol. 6, no. 3, pp. 85-90, 2017.

H. Xie, J. F. Dawson, J. Yan, AC. Marvin, and M. P. Robinson, “Numerical and analytical analysis of stochastic electromagnetic fields coupling to a printed circuit board trace,” IEEE Transactions on Electromagnetic Compatibility, vol. 62, no. 4, pp. 1128-1135, 2020.

Y. Zhang, C. Liao, H. Rui, Y. Shang, and H. Zhou, “Analysis of nonuniform transmission lines with a perturbation technique in time domain,” IEEE Transactions on Electromagnetic Compatibility, vol. 62, no. 2, pp. 542-548,2020.

P. Manfredi, D. V. Ginste, I. S. Stievano, D. D. Zutter, and F. G. Canavero, “Stochastic transmission line analysis via polynomial chaos methods: An overview,” IEEE Electromagnetic Compatibility Magazine, vol. 6, no. 3, pp. 77-84,2017.

F. Canavero, “Generalized decoupled polynomial chaos for nonlinear circuits with many random parameters,” IEEE Microwave & Wireless Components Letters, vol. 25, no. 8, pp. 505-507,2015.

Z. Zhang, T. A. El-Moselhy, I. M. Elfadel, et al., “Stochastic testing method for transistor-level uncertainty quantification based on generalized polynomial chaos,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 32, no. 10, pp. 1533-1545,2013.

R. S. Edwards, A. C. Marvin, and S. J. Porter, “Uncertainty analyses in the finite difference time domain method,” IEEE Transactions on Electromagnetic Compatibility, vol. 52, no. 1, pp. 155-163, 2010.

Z. Fei, Y. Huang, J. Zhou, and X. Qian, “Uncertainty quantification of crosstalk using stochastic reduced order models,” IEEE Transactions on Electromagnetic Compatibility, vol. 59, no. 1, pp. 228-239, 2016.

T. Wang, Y. Gao, and L. Gao, “Statistical analysis of crosstalk for automotive wiring harness via the polynomial chaos method,” Journal of the Balkan Tribological Association, vol. 22, no. 2, pp. 1503-1517, 2016.

J. Bai, G. Zhang, D. Wang, A. P. Duffy, and L. Wang, “Performance comparison of the SGM and the SCM in EMC simulation,” IEEE Transactions on Electromagnetic Compatibility, vol. 58, no. 6, pp. 1739-1746, 2016.

J. Bai, G. Zhang, A. P. Duffy, and L. Wang, “Dimension-reduced sparse grid strategy for a stochastic collocation method in EMC software,” IEEE Transactions on Electromagnetic Compatibility, vol. 60, no. 1, pp. 218-224,2018.

B. Jia, M. Xin, and Y. Cheng, “Uncertainty propagation via multi-element grid,” 2013 American Control Conference (ACC) Washington, DC, USA, Jun. 17-19, 2013.

A. P. Duffy, A. Orlandi, and G. Zhang, “Review of the feature selective validation method (FSV). Part I-theory,” IEEE Transactions on Electromagnetic Compatibility, vol. 60, no. 4, pp. 814-821,2018.

J. Bai, L. Wang, D. Wang, A. P. Duffy, and G. Zhang, “Validity evaluation of the uncertain EMC simulation results,” IEEE Transactions on Electromagnetic Compatibility, vol. 59, no. 3, pp. 797-804, 2017.

Downloads

Published

2022-04-01

How to Cite

[1]
J. . Bai, K. . Guo, J. . Sun, and N. . Wang, “Application of the Multi-element Grid in EMC Uncertainty Simulation”, ACES Journal, vol. 37, no. 04, pp. 428–434, Apr. 2022.