Antilock Braking System Using Dynamic Speed Estimation

Authors

  • Fargham Sandhu Centre for Artificial Intelligence & Robotics, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Hazlina Selamat Centre for Artificial Intelligence & Robotics, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Yahaya Md Sam Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v72.3882

Keywords:

Slip, complementary filter, kinematic model, split mu system, kalman filter

Abstract

Antilock braking systems use slip to control braking, for which the velocity of the car and wheel speeds of the wheels are required. The wheel speeds can be measured directly but the velocity of the vehicle is difficult to measure. Although the wheel speed can be used to calculate the linear velocity of the vehicle using the tire characteristic function, it depends upon various environmental and time varying parameters. The dominant factor in the characteristic function is the road friction coefficient. Due to the difficulties in proper estimation of the road friction, most systems calculate the optimal values offline and apply them at different speeds using switching functions. By using the tire model and the optimal friction coefficients, the velocity of the vehicle is estimated and used for calculating the optimal braking force, resulting in inappropriate control of braking creating longer braking distances. In the method proposed in this paper, an estimator will be used to estimate the velocity, which is proved to be more accurate than calculated from the wheel speeds. The estimated velocity and the pitch angle will be used to schedule the braking forces in order to reduce the braking time. The braking time of the proposed system lies between the ideal braking time and the conventional reference wheel speed related braking time, indicating an improvement in reducing the braking distance.   

References

Georg F. M. 1995. A fuzzy Logic Controller for an ABS Braking System. IEEE Transections on Fuzzy Systems. 3(4): 381–388.

Yu, J. S. 1997. A Robust Adaptive Wheel-slip Controller for Antilock Brake System. Proceedings of the 36th Conference on Decision & Control. 3: 2545–2546.

Samuel, J. and Jimoh, O. P. 2013. Active Feedback Linearization for Hybrid Slip Control for Antilock Braking Systems. Acta Polytechnica Hungarica. 10(1): 81–99.

Kachroo, P. and Tomizuka, M. 1994. Vehicle Traction Control and Its Applications. Univ. California, Berkeley, Inst. Transportation, Tech. Rep. UIPRR-94-08

Enrico Suraci. 2006. Development and Road Tests of an ABS Control System. Vehicle System Dynamics. 44(1): 393–401.

Fargham Sandhu. 2013. State and Parameter Estimation for Navigation. In press.

Robert, I. L. and Virgil T. 2004. A New Rotational Speed Sensor Interface Circuit with Improved EMC Immunity. New Trends in Circuits.

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Published

2015-01-05

How to Cite

Antilock Braking System Using Dynamic Speed Estimation. (2015). Jurnal Teknologi (Sciences & Engineering), 72(2). https://doi.org/10.11113/jt.v72.3882