Skip to main content

Advertisement

Log in

Accurate State Estimation for Electro-Mechanical Brake Systems

  • Original Article
  • Published:
Journal of Electrical Engineering & Technology Aims and scope Submit manuscript

Abstract

Electro-mechanical brake (EMB) system is an electric motor based braking force generation module, and it requires various sensors such as motor position, motor current and clamping force sensor for stable vehicle deceleration control. Because fault in these sensors can lead to degradation of the system performance, system monitoring is essential. To build a model based state estimator for the braking system, there are some requirements: the mathematical model presenting the nonlinearity and disturbance of the real system, fast response time and the accurate estimation. To solve this problem, this paper proposes a new EMB model which clamping force term is divided into the linear and nonlinear compensation part, and Kalman filter algorithm is applied to design the state estimator. The proposed model is simple and linear, and Kalman filter algorithm is robust to system noise and guarantees the fast computation time. Additionally, the braking direction aware and contact point aware clamping force estimation techniques are introduced, and they help to improve the accuracy of the state estimation. Lastly, the proposed approach is verified through experiments on the EMB test bench.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Schwarz R, Isermann R, Böhm J, Nell J, Rieth P (1998) Modeling and control of an electromechanical disk brake. SAE Tech. Paper 980600. https://doi.org/10.4271/980600

  2. Isermann Rolf, Schwarz Ralf, Stolzl Stefan (2002) Fault-tolerant drive-by-wire systems. IEEE Control Syst 22(5):64–81

    Article  Google Scholar 

  3. Hwang W, Han K, Huh K (2012) Fault detection and diagnosis of the electromechanical brake based on observer and parity space. Int J Automot Technol 13(5):845–851

    Article  Google Scholar 

  4. Hwang W, Han K, Huh K, Jung J, Kim M (2011) Model-based sensor fault detection algorithm design for electro-mechanical brake. In: 14th International IEEE conference on intelligent transportation systems (ITSC), 2011, pp. 962–967

  5. Choi Chinchul, Lee Kangseok, Lee Wootaik (2015) Observer-based phase-shift fault detection using adaptive threshold for rotor position sensor of permanent-magnet synchronous machine drives in electromechanical brake. IEEE Trans Ind Electron 62(3):1964–1974

    Article  Google Scholar 

  6. Cuibus M, Bostan V, Ambrosii S, Ilas C, Magureanu R (2000) Luenberger, Kalman and neural network observers for sensorless induction motor control. In: Proceedings in the third international power electronics and motion control conference, 2000 (IPEMC 2000), vol. 3, pp 1256–1261

  7. UmaMageswari A, Joseph Ignatious J, Vinodha R (2012) A comparitive study of Kalman filter, extended kalman filter and unscented Kalman filter for harmonic analysis of the non-stationary signals. Int J Sci Eng Res 3(7):1–9

    Google Scholar 

  8. Zhang Y, Zhao Z, Lu T, Yuan L, Xu W, Zhu J (2009) A comparative study of Luenberger observer, sliding mode observer and extended Kalman filter for sensorless vector control of induction motor drives. In:  Energy Conversion Congress and Exposition (ECCE), 2009. pp 2466–2473

  9. Zhong L et al (1997) Analysis of direct torque control in permanent magnet synchronous motor drives. IEEE Trans Power Electron 12(3):528–536

    Article  Google Scholar 

  10. Pillay P, Krishnan R (1989) Modeling, simulation, and analysis of permanent-magnet motor drives. I. The permanent-magnet synchronous motor drive. IEEE Trans Ind Appl 25(2):265–273

    Article  Google Scholar 

  11. Park H, Choi SB (2013) Development of a sensorless control method for a self-energizing brake system using noncircular gears. IEEE Trans Control Syst Technol 21(4):1328–1339

    Article  Google Scholar 

  12. Jo C, Hwang S, Kim H (2010) Clamping-force control for electromechanical brake. IEEE Trans Veh Technol 59:3205–3212

    Article  Google Scholar 

  13. Ki YH et al (2013) Design and implementation of a new clamping force estimator in electro-mechanical brake systems. Int J Automot Technol 14(5):739–745

    Article  Google Scholar 

  14. Saric Stephen, Bab-Hadiashar Alireza, Hoseinnezhad Reza (2008) Clamp-force estimation for a brake-by-wire system: a sensor-fusion approach. IEEE Trans Veh Technol 57(2):778–786

    Article  Google Scholar 

  15. Park Giseo, Choi Seibum, Hyun Dongyoon (2017) Clamping force estimation based on hysteresis modeling for electro-mechanical brakes. Int J Automot Technol 18(5):883–890

    Article  Google Scholar 

  16. Schwarz R, Isermann R, Böhm J, Nell J, Rieth P (1999) Clamping force estimation for a brake-by-wire actuator. (No. 1999-01-0482). SAE Technical Paper

  17. Park G, Choi SB (2018) Clamping force control based on dynamic model estimation for electromechanical brakes. Proceedings of the Institution of Mechanical Engineers, Part D. J Automob Eng 232(14):2000–2013

    Article  Google Scholar 

  18. Hoseinnezhad R, Bab-Hadiashar A, Rocco T (2008) Realtime clamp force measurement in electromechanical brake calipers. IEEE Trans Veh Technol 57:770–777

    Article  Google Scholar 

  19. Kalman RE (1960) A new approach to linear filtering and prediction problems. Trans ASME J Basic Eng 82(Series D):35–45

    Article  Google Scholar 

  20. Ross SM (2010) A first course in probability, 8th edn. Prentice-Hall, Englewood Cliffs

    MATH  Google Scholar 

  21. Maxon EC-4 pole 305015 200 W. https://www.maxonmotor.com/maxon/view/content/ec-4polemotors. Retrieved 10 Aug 2018

Download references

Acknowledgements

This work was supported by the DGIST R&D Program of the Ministry of Science and ICT (19-IT-01).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Daehyun Kum.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kwon, S., Lee, S., Lee, J. et al. Accurate State Estimation for Electro-Mechanical Brake Systems. J. Electr. Eng. Technol. 14, 889–896 (2019). https://doi.org/10.1007/s42835-019-00124-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42835-019-00124-x

Keywords

Navigation