Abstract
Vertical tire forces are essential for vehicle modelling and dynamic control. However, an evaluation of the vertical tire forces on a multi-axle truck is difficult to accomplish. The current methods require a large amount of experimental data and many sensors owing to the wide variation of the parameters and the over-constraint. To simplify the design process and reduce the demand of the sensors, this paper presents a practical approach to estimating the vertical tire forces of a multi-axle truck for dynamic control. The estimation system is based on a novel vertical force model and a proposed adaptive treble extend Kalman filter (ATEKF). To adapt to the widely varying parameters, a sliding mode update is designed to make the ATEKF adaptive, and together with the use of an initial setting update and a vertical tire force adjustment, the overall system becomes more robust. In particular, the model aims to eliminate the effects of the over-constraint and the uneven weight distribution. The results show that the ATEKF method achieves an excellent performance in a vertical force evaluation, and its performance is better than that of the treble extend Kalman filter.
Highlights
Vertical tire forces are essential in vehicle modelling and dynamic control
For validation of the proposed estimation method based on the adaptive treble extend Kalman filter (ATEKF), the estimation is jointly simulated using MATLAB/Simulink and Trucksim software, which can simulate a real truck used in the heavy vehicle industry
In this study, an estimation system was designed for the vertical tire forces of a four-axle truck used in vehicle dynamic control based on the proposed ATEKF
Summary
Vertical tire forces are essential in vehicle modelling and dynamic control. It is not difficult to determine the vertical tire forces for a two-axle vehicle. In this paper, a practical and accurate estimation method for an evaluation of the vertical tire forces of a four-axle truck based on an adaptive treble extend Kalman filter (ATEKF) is proposed. This method requires fewer sensors and experimental data, and a dynamic load transfer ratio is not needed. Only one wheel on the second axle is assumed to have vertical acceleration sensors implanted, and the vertical tire forces can be obtained using the 1/8 vehicle model based on the sensor data [27] Because this method has already been used commercially, during the estimation, this vertical force ( Fzl2 ) is considered to be known as the input of the ATEKF.
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