A New Method for Predicting Crosstalk of Hand-Assembled Cable Bundles

Authors

  • Chengpan Yang School of Electrical and Automation Nanjing Normal University, Nanjing, Jiangsu, 210097, China
  • Wei Yan School of Electrical and Automation Nanjing Normal University, Nanjing, Jiangsu, 210097, China
  • Yang Zhao School of Electrical and Automation Nanjing Normal University, Nanjing, Jiangsu, 210097, China
  • Shishan Wang Jiangsu Key Laboratory of New Energy Generation and Power Conversion Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, 210016, China
  • Qiangqiang Liu School of Electrical and Automation Nanjing Normal University, Nanjing, Jiangsu, 210097, China

Keywords:

Crosstalk, finite-difference time-domain (FDTD), multiconductor transmission line (MTL), neural network, random bundles

Abstract

Hand-assembled cable bundles are random harness whose crosstalk is difficult to obtain accurately. A crosstalk prediction method of hand-assembled cable bundles is proposed in this paper. The harness is modeled by means of the mean pseudo-random number based on the cascade method. The factors considered in the model include the random exchange of wires position in the wiring harness cross section and the random rotation of the cross section to the ground. A mathematical description of the random exchange of wires position is made by using the row and column transformation of the per unit length RLCG parameter matrix. BP neural network with strong nonlinear mapping ability is introduced to describe the random rotation of wiring harness to the ground. Combined with the finitedifference time-domain (FDTD) method, the crosstalk of the wiring harness is predicted. Experimental results show that the new method has good accuracy in predicting crosstalk of hand-assembled cable bundles. The higher the twisting degree of the wiring harness is, the more concentrated the crosstalk is.

Downloads

Download data is not yet available.

References

S. Chabane, P. Besnier, and M. Klingler, “A modified enhanced transmission line theory applied to multiconductor transmission lines,” IEEE Trans. on Electromagn. Compat., vol. 59, no. 2, pp. 518-528, Apr. 2017.

Y. Wang, Y. S. Cao, D. Liu, R. W. Kautz, N. Altunyurt, and J. Fan, “A generalized multiplescattering method for modeling a cable harness with ground connections to a nearby metal surface,” IEEE Trans. Electromagn. Compat., vol. 61, no. 1, pp. 261-270, Feb. 2019.

C. R. Paul, Analysis of Multiconductor Transmission Lines. Wiley, New York, 1994.

S. Shiran, B. Reiser, and H. Cory, “A probabilistic method for the evaluation of coupling between transmission lines,” IEEE Trans. Electromagn. Compat., vol. 35, no. 3, pp. 387-393, Aug. 1993.

C. R. Paul, “Sensitivity of crosstalk to variations in wire position in cable bundles,” 1987 IEEE International Symposium Electromagnetic Compatibility, Atlanta, GA, pp. 1-5, Aug. 1987.

Z. Fei, Y. Huang, J. Zhou, and Q. Xu, “Uncertainty quantification of crosstalk using stochastic reduced order models,” IEEE Trans. Electromagn. Compat., vol. 59, no. 1, pp. 228-239, Feb. 2017.

G. Spadacini, F. Grassi, and S. A. Pignari, “Fieldto-wire coupling model for the common mode in random bundles of twisted-wire pairs,” IEEE Trans. Electromagn. Compat., vol. 57, no. 5, pp. 1246-1254, Oct. 2015.

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, Nov. 2017.

M. Gonser, C. Keller, J. Hansen, and R. Weigel, “Advanced simulations of automotive EMC measurement setups using stochastic cable bundle models,” 2010 Asia-Pacific International Symposium on Electromagnetic Compatibility, Beijing, China, pp. 590-593, Apr. 2010.

A. Ciccolella and F. G. Canavero, “Stochastic prediction of wire coupling interference,” Proceedings of International Symposium Electromagnetic Compatibility., Atlanta, GA, pp. 51-56, Aug. 1995.

P. Manfredi, D. De Zutter, and D. V. Ginste, “Analysis of coupled exponential microstrip lines by means of a multi-step perturbation technique,” IEEE 20th Workshop on Signal and Power Integrity (SPI), Turin, Italy, pp. 1-4, May 2016.

D. Bellan and S. A. Pignari, “Statistical superposition of crosstalk effects in cable bundles,” China Communications, vol. 10, no. 11, pp. 119- 128, Nov. 2013.

J. C. Pincenti and P. L. E. Uslenghi, “Incident field excitation of random cables,” Radio Science, vol. 42, no. 06, pp. 1-10, Dec. 2007.

D. Bellan and S. A. Pignari, “Efficient estimation of crosstalk statistics in random wire bundles with lacing cords,” IEEE Trans. Electromagn. Compat., vol. 53, no. 1, pp. 209-218, Feb. 2011.

S. Sun, G. Liu, J. L. Drewniak, and D. J. Pommerenke, “Hand-assembled cable bundle modeling for crosstalk and common-mode radiation prediction,” IEEE Trans. Electromagn. Compat., vol. 49, no. 3, pp. 708-718, Aug. 2007.

M. Wu, D. Beetner, T. Hubing, Haixin Ke, and S. Sun, “Estimation of the statistical variation of crosstalk in wiring harnesses,” 2008 IEEE International Symposium on Electromagnetic Compatibility, Detroit, MI, pp. 1-7, Aug. 2008.

M. Wu, D. G. Beetner, T. H. Hubing, H. Ke, and S. Sun, “Statistical prediction of “Reasonable WorstCase” crosstalk in cable bundles,” IEEE Trans. Electromagn. Compat., vol. 51, no. 3, pp. 842-851, Aug. 2009.

S. Salio, F. Canavero, D. Lecointe, and W. Tabbara, “Crosstalk prediction on wire bundles by Kriging approach,” IEEE International Symposium on Electromagnetic Compatibility, Washington, DC, vol. 1, pp. 197-202, Aug. 2000.

A. Tatematsu, F. Rachidi, and M. Rubinstein, “A technique for calculating voltages induced on twisted-wire pairs using the FDTD method,” IEEE Trans. Electromagn. Compat., vol. 59, no. 1, pp. 301-304, Feb. 2017.

V. R. Kumar, B. K. Kaushik, and A. Patnaik, “An accurate FDTD model for crosstalk analysis of CMOS-Gate-Driven coupled RLC interconnects,” IEEE Trans. Electromagn. Compat., vol. 56, no. 5, pp. 1185-1193, Oct. 2014.

T. Rashid, Make Your Own Neural Network, Charleston. Create Space Independent Publishing Platform, Charleston, 2016.

M. Hassoun, Fundamentals of Artificial Neural Networks, Bradford Book, Cambridge, 2003.

F. Dai, G. Bao, and D. Su, “Crosstalk prediction in non-uniform cable bundles based on neural network,” Proceedings of the 9th International Symposium on Antennas, Propagation and EM Theory, Guangzhou, China, pp. 1043-1046, Nov. 2010.

L. Brančík and N. Al-Zubaidi R-Smith, “Comparative simulations of hybrid systems with nonuniform MTLs via Wendroff and NILT based techniques,” 2016 Progress in Electromagnetic Research Symposium (PIERS), Shanghai, China, pp. 4067-4072, Aug. 2016.

Z. Zhang, S. Wang, and L. Zhao, “Prediction of crosstalk probability distribution in cable bundles,” Transactions of China Electrotechnical Society, vol. 32, no. 7, pp. 203-214, Apr. 2017.

Downloads

Published

2020-03-01

How to Cite

[1]
Chengpan Yang, Wei Yan, Yang Zhao, Shishan Wang, and Qiangqiang Liu, “A New Method for Predicting Crosstalk of Hand-Assembled Cable Bundles”, ACES Journal, vol. 35, no. 3, pp. 305–313, Mar. 2020.

Issue

2020: Vol 35 Iss 3

Section

Articles