Identification of Lateral Dynamics and Parameter Estimation of Heavy Vehicles

ISSN： 0888-3270

Source： Mechanical Systems and Signal Processing, Vol.12, Iss.5, 1998-09, pp. : 611-628

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Abstract

A system identification technique is applied to determine the lateral dynamics of an articulated freight vehicle subject to three different steering excitations and levels of measurement noise. An algorithm is proposed to extract an estimate of significant vehicle parameters considered to be uncertain. In addition to the commonly used ramp step (RS) and quasi-impulse (QI) steering inputs, a pseudo-random binary sequence (PRBS) excitation signal is proposed to stimulate all the important modes associated with the lateral directional dynamics of the vehicle. It is concluded that the vehicle transfer function can be characterised accurately under PRBS and QI excitations, and the signal-to-noise ratios superior to 20 dB. The low-order dynamics can be identified further under higher measurement noise levels. The proposed algorithm yields an accurate and robust estimate of uncertain vehicle parameters irrespective of the starting estimates and excitation signals. The algorithm provides the most effective estimates of the parameters to which lateral dynamics is most sensitive. The robustness of the proposed method is examined further using the data generated from a comprehensive yaw/roll non-linear model. From the results it is concluded that the directional dynamics of the vehicle is influenced mostly by the lateral and yaw dynamics, while the contributions due to roll dynamics are relatively small.