The problem of state estimation during antilock braking in the real vehicle is addressed in this work. The proposed nonlinear observer based on the unscented Kalman filter theory can provide the necessary information for the antilock control despite the presence of measurement noise, uncertainties in the model parameters, the road friction coefficient, and the road inclination. In the observer design, a LuGre tire model and a vehicle model deduced from the quarter car model are used as design model. Furthermore, an observability analysis is carried out for the plant in order to prove the observability of defined state variables with respect to the measured signals. The practical applicability of the proposed nonlinear observer is shown by means of experimental studies relying on the measurement data.
PetersenIJohansenTKalkkuhlJ. Nonlinear wheel slip control in ABS brakes using gain scheduled constrained LQR. In: Proceedings of 16th IEEE Mediterranean Conference on Control and Automation, Ajaccio-Corsica, France, 25–27 June 2008. New York: IEEE.
2.
De VriesEFehnARixenD. Flatness-based model inverse for feed-forward braking control. Vehicle Syst Dyn2010; 48: 353–372.
3.
SunFLolenkoKRudolphJ. Nonlinear observer design for state estimation during anti-lock braking. In: Proceedings of 13th Mechatronics Forum International Conference, Linz, Austria, 17–19 September 2012. Linz: TRAUNER.
4.
Pasillas-LépineW. Hybrid modeling and limit cycle analysis for a class of five-phase anti-lock brake algorithms. Vehicle Syst Dyn2006; 44(2): 173–188.
5.
TanelliMOsorioGdi BernardoM. Limit cycles analysis in hybrid anti-lock braking systems. In: Proceedings of 46th IEEE Conference on Decision and Control, New Orleans, LA, USA, 12–14 December 2007. New York: IEEE.
6.
BreulerBEichhornURothJ. Measurement of tyre/road friction ahead of the car and inside the tyre. In: Proceedings of the International Symposium on AVEC, Yokohama, Japan, 14–17 September 1992. Tokyo: JSAE.
PacejkaH. Tyre and vehicle dynamics. Oxford: Elsevier—Butterworth-Heinemann, 2006.
9.
MitschkeMWallentowitzH. Dynamik der Kraftfahrzeuge. Berlin: Springer, 2004.
10.
YiJAlvarezLClaeysX. Emergency braking control with an observer-based dynamic tire/road friction model and wheel angular velocity information. In: Proceedings of American control conference, Arlington, VA, USA, 25–27 June 2001. New York: IEEE.
11.
PatelNEdwardsCSpurgeonSK. An analysis of two nonlinear observers in the presence of noise. In: Proceedings of American control conference, Seattle, WA, USA, 11–13 June 2008. New York: IEEE.
12.
Canudas de WitCHorowitzR. Observers for tire/road contact friction using only wheel angular velocity information. In: Proceedings of 38th IEEE conference on decision and control, Phoenix, AZ, USA, 7–10 December 1999. New York: IEEE.
13.
PatelNEdwardsCSpurgeonSK. A sliding mode observer for tyre friction estimation during braking. In: Proceedings of American control conference, Minneapolis, MN, USA, 14–16 June 2006. New York: IEEE.
14.
AlvarezLYiJHorowitzR. Dynamic friction model-based tire-road friction estimation and emergency braking control. J Dyn Sys: T ASME2005; 127(1): 22–32.
15.
VelenisETsiotrasPde WitCC. Dynamic tire friction models for combined longitudinal and lateral vehicle motion. Vehicle Syst Dyn2005; 43: 3–29.
16.
KienckeUNielsenL. Automotive control systems. Berlin: Springer, 2005.
17.
BirkJ. Rechnergestützte Analyse und Lösung nichtlinearer Beobachtungsaufgaben. PhD Dissertation, Institut für Systemdynamik und Regelungstechnik, Universität Stuttgart, Stuttgart; VDI Verlag, Berlin, 1992.
18.
SimonD. Optimal state estimation. Hoboken, NJ: Wiley-Interscience, 2006.
19.
KandepuRFossBImslandL. Applying the unscented Kalman filter for nonlinear state estimation. J Process Contr2008; 18(7): 753–768.
20.
KandepuRImslandLFossB. Constrained state estimation using the unscented Kalman filter. In: Proceedings of 16th IEEE Mediterranean Conference on Control and Automation, Ajaccio-Corsica, France, 25–27 June 2008. New York: IEEE.
21.
AntonovSFehnAKugiA. Unscented Kalman filter for vehicle state estimation. Vehicle Syst Dyn2011; 49: 1497–1520.
