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Sensing Systems in Intelligent Tires

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Intelligent Tire Systems

Abstract

Herein, various underlying technologies for tire condition monitoring systems (TCMSs) are briefly studied. The technologies that can be implemented in tire systems for sensing and energy harvesting are booming. In this chapter, the mainstream technologies reported to handle the above-mentioned applications are briefly described.

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References

  1. C. Daimler, “Apollo IST-2001-34372: intelligent tyre for accident-free traffic,” Eur. Comm. Inform. Society Tec, vol. 1, pp. 1–64, 2005.

    Google Scholar 

  2. A. J. Tuononen, “Optical position detection to measure tyre carcass deflections,” Vehicle System Dynamics, vol. 46, no. 6, pp. 471–481, 2008.

    Article  Google Scholar 

  3. A. Tuononen, “On-board estimation of dynamic tyre forces from optically measured tyre carcass deflections,” International journal of heavy vehicle systems, vol. 16, no. 3, pp. 362–378, 2009.

    Article  Google Scholar 

  4. A. Todoroki, S. Miyatani, and Y. Shimamura, “Wireless strain monitoring using electrical capacitance change of tire: part I with oscillating circuit,” Smart Materials and Structures, vol. 12, no. 3, p. 403, 2003.

    Article  Google Scholar 

  5. Todoroki, Akira and Miyatani, Shintaro and Shimamura, Yoshinobu, “Wireless strain monitoring using electrical capacitance change of tire: part II—passive,” Smart Materials and Structures, vol. 12, no. 3, p. 410, 2003.

    Article  Google Scholar 

  6. R. Matsuzaki and A. Todoroki, “Passive wireless strain monitoring of actual tire using capacitance–resistance change and multiple spectral features,” Sensors and Actuators A: Physical, vol. 126, no. 2, pp. 277–286, 2006.

    Article  Google Scholar 

  7. Matsuzaki, Ryosuke and Todoroki, Akira, “Wireless flexible capacitive sensor based on ultra-flexible epoxy resin for strain measurement of automobile tires,” Sensors and Actuators A: Physical, vol. 140, no. 1, pp. 32–42, 2007.

    Article  Google Scholar 

  8. C. Du, S. Dutta, P. Kurup, T. Yu, and X. Wang, “A review of railway infrastructure monitoring using fiber optic sensors,” Sensors and Actuators A: Physical, vol. 303, p. 111728, 2020.

    Article  Google Scholar 

  9. F. Coppo, G. Pepe, N. Roveri, and A. Carcaterra, “A multisensing setup for the intelligent tire monitoring,” Sensors, vol. 17, no. 3, p. 576, 2017.

    Article  Google Scholar 

  10. N. Roveri, G. Pepe, and A. Carcaterra, “OPTYRE–A new technology for tire monitoring: Evidence of contact patch phenomena,” Mechanical Systems and Signal Processing, vol. 66, pp. 793–810, 2016.

    Article  Google Scholar 

  11. J. G. Oh, B. Choi, and S. Y. Lee, “SAW based passive sensor with passive signal conditioning using MEMS A/D converter,” Sensors and Actuators A: Physical, vol. 141, no. 2, pp. 631–639, 2008.

    Article  Google Scholar 

  12. A. Pohl, G. Ostermayer, L. Reindl, and F. Seifert, “Monitoring the tire pressure at cars using passive SAW sensors,” in 1997 IEEE Ultrasonics Symposium Proceedings. An International Symposium (Cat. No. 97CH36118), vol. 1.   IEEE, 1997, pp. 471–474.

    Google Scholar 

  13. A. Pohl, R. Steindl, and L. Reindl, “The "intelligent tire" utilizing passive SAW sensors measurement of tire friction,” IEEE transactions on instrumentation and measurement, vol. 48, no. 6, pp. 1041–1046, 1999.

    Article  Google Scholar 

  14. V. Bachmann, M. Fach, and B. Breuer, “Future car-tires as provider of information for vehicle systems to enhance primary safety,” SAE Technical Paper, Tech. Rep., 1998.

    Google Scholar 

  15. O. Yilmazoglu, M. Brandt, J. Sigmund, E. Genc, and H. Hartnagel, “Integrated InAs/GaSb 3D magnetic field sensors for "the intelligent tire",” Sensors and Actuators A: Physical, vol. 94, no. 1-2, pp. 59–63, 2001.

    Article  Google Scholar 

  16. V. Magori and H. Walker, “Ultrasonic presence sensors with wide range and high local resolution,” IEEE transactions on ultrasonics, ferroelectrics, and frequency control, vol. 34, no. 2, pp. 202–211, 1987.

    Article  Google Scholar 

  17. V. Magori, V. R. Magori, and N. Seitz, “On-line determination of tyre deformation, a novel sensor principle,” in 1998 IEEE Ultrasonics Symposium. Proceedings (Cat. No. 98CH36102), vol. 1.   IEEE, 1998, pp. 485–488.

    Google Scholar 

  18. R. G. Longoria, R. Brushaber, and A. Simms, “An in-wheel sensor for monitoring tire-terrain interaction: Development and laboratory testing,” Journal of Terramechanics, vol. 82, pp. 43–52, 2019.

    Article  Google Scholar 

  19. F. Braghin, M. Brusarosco, F. Cheli, A. Cigada, S. Manzoni, and F. Mancosu, “Measurement of contact forces and patch features by means of accelerometers fixed inside the tire to improve future car active control,” Vehicle System Dynamics, vol. 44, no. sup1, pp. 3–13, 2006.

    Article  Google Scholar 

  20. A. Niskanen and A. J. Tuononen, “Three three-axis IEPE accelerometers on the inner liner of a tire for finding the tire-road friction potential indicators,” Sensors, vol. 15, no. 8, pp. 19 251–19 263, 2015.

    Google Scholar 

  21. R. Matsuzaki, K. Kamai, and R. Seki, “Intelligent tires for identifying coefficient of friction of tire/road contact surfaces using three-axis accelerometer,” Smart Materials and Structures, vol. 24, no. 2, p. 025010, 2014.

    Article  Google Scholar 

  22. N. Xu, Y. Huang, H. Askari, and Z. Tang, “Tire slip angle estimation based on the intelligent tire technology,” IEEE Transactions on Vehicular Technology, vol. 70, no. 3, pp. 2239–2249, 2021.

    Article  Google Scholar 

  23. A. J. Niskanen and A. J. Tuononen, “Detection of the local sliding in the tyre-road contact by measuring vibrations on the inner liner of the tyre,” Measurement Science and Technology, vol. 28, no. 5, p. 055007, 2017.

    Article  Google Scholar 

  24. H. Lee and S. Taheri, “Intelligent tires? A review of tire characterization literature,” IEEE Intelligent Transportation Systems Magazine, vol. 9, no. 2, pp. 114–135, 2017.

    Article  Google Scholar 

  25. H. J. Kim, J. Y. Han, S. Lee, J. R. Kwag, M. G. Kuk, I. H. Han, and M. H. Kim, “A road condition classification algorithm for a tire acceleration sensor using an artificial neural network,” Electronics, vol. 9, no. 3, p. 404, 2020.

    Article  Google Scholar 

  26. M. Matilainen and A. Tuononen, “Tyre contact length on dry and wet road surfaces measured by three-axial accelerometer,” Mechanical Systems and Signal Processing, vol. 52, pp. 548–558, 2015.

    Article  Google Scholar 

  27. N. Xu, H. Askari, Y. Huang, J. Zhou, and A. Khajepour, “Tire force estimation in intelligent tires using machine learning,” IEEE Transactions on Intelligent Transportation Systems, 2020.

    Google Scholar 

  28. H. Askari, E. Hashemi, A. Khajepour, M. B. Khamesee, and Z. L. Wang, “Tire condition monitoring and intelligent tires using nanogenerators based on piezoelectric, electromagnetic, and triboelectric effects,” Advanced Materials Technologies, vol. 4, no. 1, p. 1800105, 2019.

    Article  Google Scholar 

  29. H. Askari, A. Khajepour, M. B. Khamesee, and Z. L. Wang, “Embedded self-powered sensing systems for smart vehicles and intelligent transportation,” Nano Energy, vol. 66, p. 104103, 2019.

    Article  Google Scholar 

  30. X. Zhao, H. Askari, and J. Chen, “Nanogenerators for smart cities in the era of 5G and Internet of Things,” Joule, vol. 5, no. 6, pp. 1391–1431, 2021.

    Article  Google Scholar 

  31. H. Askari, N. Xu, B. H. G. Barbosa, Y. Huang, L. Chen, A. Khajepour, H. Chen, and Z. L. Wang, “Intelligent systems using triboelectric, piezoelectric, and pyroelectric nanogenerators,” Materials Today, 2022.

    Google Scholar 

  32. H. Askari, E. Hashemi, A. Khajepour, M. B. Khamesee, and Z. L. Wang, “Towards self-powered sensing using nanogenerators for automotive systems,” Nano energy, vol. 53, pp. 1003–1019, 2018.

    Article  Google Scholar 

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Correspondence to Nan Xu .

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Xu, N., Askari, H., Khajepour, A. (2022). Sensing Systems in Intelligent Tires. In: Intelligent Tire Systems. Synthesis Lectures on Advances in Automotive Technology. Springer, Cham. https://doi.org/10.1007/978-3-031-10268-4_3

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