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Advances in Manufacturing

, Volume 7, Issue 4, pp 389–400 | Cite as

Indirect measurement technology of new energy vehicles’ braking force under dynamic braking conditions

  • Sen-Ming Zhong
  • Gui-Xiong LiuEmail author
  • Jia-Jian Wu
  • Bo Zeng
Article
  • 17 Downloads

Abstract

Currently, direct braking-force measurement under dynamic conditions requires a considerable modification to the vehicles and has poor compatibility because there are many types of vehicles. Thus, in this paper, an indirect measurement method of new-energy vehicles’ braking force under dynamic braking conditions is proposed. The mechanical wheel and axle model at low/idling/high speeds is established using the piston-pressure formula, force transfer in the brake-wheel cylinder, relative movement between the wheel and the roller, among others. On this basis, the relationship between wheel braking force and roller-linear acceleration is further derived. Our method does not alter existing vehicle structures or sensor types. The standard sealing bolt is temporarily replaced with a hydraulic sensor for coefficient calibration. Afterward, the braking force can be indirectly calculated using the roller-linear velocity data. The method has characteristics of efficiency and high accuracy without refitting vehicles.

Keywords

Braking force Indirect measurement technology Vehicles Dynamic braking condition Electromagnetic interference (EMI) test 

Notes

Acknowledgements

This research is supported by the Guangzhou Science and Technology Project (Grant No. 201504010037). We thank the useful discussion with engineers of AVL List GmbH and their support, as well as the discussion with some experts of CISPR and Chinese National Technical Committee of Auto Standardization. The hydraulic sensor is supplied by Guangzhou Huamao sensing instrument Co. Ltd.

References

  1. 1.
    Yan LX, Zhang YS, He Y et al (2016) Hazardous traffic event detection using Markov Blanket and sequential minimal optimization (MB-SMO). Sensors 16(7):1084CrossRefGoogle Scholar
  2. 2.
    Yuan XL, Liu X, Zuo J (2015) The development of new energy vehicles for a sustainable future: a review. Renew Sustain Energy Rev 42:298–305CrossRefGoogle Scholar
  3. 3.
    Wang QD, Liu QS (2016) Estimation of parasitic parameters and EMI improvement of a full-bridge PWM converter system in the electric vehicle. Electron World 122:24–29Google Scholar
  4. 4.
    CISPR 12:2009. Vehicles, boats and internal combustion engines—radio disturbance characteristics—limits and methods of measurement for the protection of off-board receiversGoogle Scholar
  5. 5.
    ECE 10.05. Uniform provisions concerning the approval of vehicles with regard to electromagnetic compatibilityGoogle Scholar
  6. 6.
    SAE J551-5-2012. Performance levels and methods of measurement of magnetic and electric field strength from electric vehicles, 150 kHz to 30 MHzGoogle Scholar
  7. 7.
    Zeng B, Deng JY, Lin DQ et al (2016) Comparison of below 30 MHz electric vehicle EMI measurements method standard. Zhongguo Ceshi 42(9):11–14Google Scholar
  8. 8.
    Guo YJ, Wang LF, Liao CL (2013) Modeling and analysis of conducted electromagnetic interference in electric vehicle power supply system. Prog Electromagn Res 139:193–209CrossRefGoogle Scholar
  9. 9.
    Tondato F, Bazzell J, Schwartz L et al (2016) Safety and interaction of patients with implantable cardiac defibrillators driving a hybrid vehicle. Int J Cardiol 227:318–324CrossRefGoogle Scholar
  10. 10.
    Chun Y, Park S, Kim J et al (2014) Electromagnetic compatibility of resonance coupling wireless power transfer in on-line electric vehicle system. IEICE Trans Commun E97B(2):416–423CrossRefGoogle Scholar
  11. 11.
    Bayar K, Biasini R, Onori S et al (2012) Modelling and control of a brake system for an extended range electric vehicle equipped with axle motors. Int J Veh Des 58(2–4):399–426CrossRefGoogle Scholar
  12. 12.
    Fieldhouse J (2009) Measurement of the dynamic centre of pressure of the disk/pad interface during a braking operation (II). Int J Veh Des 51(1–2):73–104CrossRefGoogle Scholar
  13. 13.
    Hoseinnezhad R, Saric S, Bab-Hadiashar A (2006) Estimation of clamp force in brake-by-wire systems: a step-by-step identification approach. SAE Tech Pap Ser 1:1154Google Scholar
  14. 14.
    Xu G, Su J, Chen R et al (2014) Measurement performance assessment: dynamic calibration compared with static calibration method for roller tester of vehicle brake force. Adv Mech Eng 6:162435CrossRefGoogle Scholar
  15. 15.
    Gajek A (2016) Diagnostics monitor of the braking efficiency in the on board diagnostics system for the motor vehicles. IOP Conf Ser Mater Sci Eng 148:012038CrossRefGoogle Scholar
  16. 16.
    Zhong SM, Huang J, Wu JJ et al (2017) Frame design and key technical analysis of EMI test system for new energy vehicle dynamic condition. Zhongguo Ceshi 43(8):76–79Google Scholar
  17. 17.
    Yong JW, Gao F, Ding NG et al (2017) Design and validation of an electro-hydraulic brake system using hardware-in-the-loop real-time simulation. Int J Auto Tech-Kor 18(4):603–612CrossRefGoogle Scholar
  18. 18.
    Gu YF, Zhao Y, Lv RQ et al (2016) A practical FBG sensor based on a thin-walled cylinder for hydraulic pressure measurement. IEEE Photonics Technol Lett 28(22):2569–2572CrossRefGoogle Scholar

Copyright information

© Shanghai University and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Sen-Ming Zhong
    • 1
  • Gui-Xiong Liu
    • 1
    Email author
  • Jia-Jian Wu
    • 1
  • Bo Zeng
    • 2
  1. 1.School of Mechanical and Automotive EngineeringSouth China University of TechnologyGuangzhouPeople’s Republic of China
  2. 2.State Key Laboratory of Environmental Adaptability for Industrial ProductsGuangzhouPeople’s Republic of China

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