The wheel force transducer is an important device in the automotive testing field which can measure the force or torque applied to the wheel. Because existing wheel force transducers are almost commercial products, they are too expensive and technical information about them has not been made public; this slows down the development of the wheel force transducer to a certain extent. Accordingly a three-axis wheel force transducer is presented in this paper which is self-decoupled without calculating the decoupling matrix in theory. Its elastic body has a spoke structure with eight elastic beams, which means that it is easy to fabricate. This paper first introduces the overall elastic body structure of the proposed wheel force transducer. Then the strain gauge arrangement, the principle of strain measurement, the connection modes of the bridge circuits and the rotation decoupling principle for F_x and F_z are analysed, and the self-decoupled characteristics are depicted in detail. Finally, to verify the validity of the designed wheel force transducer, three kinds of experiment are carried out. In the static experiments the static performance and the self-decoupled characteristics of the wheel force transducer are verified; in the dynamic tests, a vehicle dynamics test system is adopted to verify the accuracy of the wheel force transducer in the dynamic environment; in road tests, the sensor is installed in the vehicle to verify whether the output of the proposed wheel force transducer can reflect the variation in the force applied to the wheel in practical applications. The results shows the following: first, the maximum non-linearity error, the maximum hysteresis error and the maximum repeatability error of the proposed wheel force transducer are 0.9% of the full scale, 1.1% of the full scale and 0.5% of the full scale respectively; second, the static coupling rate is about 0.08%, which means that the designed wheel force transducer is self-decoupled in theory; third, the proposed wheel force transducer can measure F_x, F_z and M_y effectively in real applications.

Purpose: – One of the major shortcomings in the data process of the traditional wheel force transducers (WFTs) is the theoretical errors of initial value determination. A new method to identify the initial values of the WFT for the solution of this problem is proposed in this paper. The paper aims to discuss these issues. Design/methodology/approach: – With this method, the initial values can be obtained by equations which are established based on multiple stops on horizontal road. Findings: – The calibration and contrast tests on the MTS calibration platform illustrate the better performance with the new method. Moreover, the real vehicle test confirms the effectiveness in practice. Originality/value: – The test results show that the new method of initial calibration has an advanced performance compared to the traditional one. In addition, it is effective in the brake test with a real vehicle.

Some initial values of the wheel force transducer (WFT) change after being mounted in the vehicle. The traditional static calibration is inadequate to fully obtain these initial values. Aiming to this problem, an online initial value calibration method is proposed. The method does not require any additional calibration equipment or manual operation and just requires the vehicle mounted with the WFT to be driven on a flat road with constant speed. In this way, an initial value mode is constructed and then converted to an optimization problem. To solve this problem and acquire the right initial value, an improved Memetic framework based on particle swarm optimization (PSO) and Levenberg-Marquardt (LM) is adopted. To verify the effect of the proposed method, the real WFT data is used and the comparative test is carried out. The experiment result shows that the proposed method is superior to the traditional one and can improve the measurement accuracy effectively.

Wheel force transducer (WFT), which measures the three-axis forces and three-axis torques applied to the wheel, is an important instrument in the vehicle testing field and has been extremely promoted by researchers with great interests. The transducer, however, is typically mounted on the wheel of a moving vehicle, especially on a high speed car, when abruptly accelerating or braking, the mass/inertia of the transducer/wheel itself will have an extra effect on the sensor response so that the inertia/mass loads will also be detected and coupled into the signal outputs. The effect which is considered to be inertia coupling problem will decrease the sensor accuracy. In this paper, the inertia coupling of a universal WFT under multi-axis accelerations is investigated. According to the self-decoupling approach of the WFT, inertia load distribution is solved based on the principle of equivalent mass and rotary inertia, thus then inertia impact can be identified with the theoretical derivation. The verification is achieved by FEM simulation and experimental tests. Results show that strains in simulation agree well with the theoretical derivation. The relationship between the applied acceleration and inertia load for both wheel force and moment is the approximate linear, respectively. All the relative errors are less than 5% which are within acceptable and the inertia loads have the maximum impact on the signal output about 1.5% in the measurement range.

The scientific and effective prediction of drawbar pull is of great importance in the evaluation of military vehicle trafficability. Nevertheless, the existing prediction models have demonstrated lots of inherent limitations. In this framework, a multiple-kernel relevance vector machine model (MkRVM) including Gaussian kernel and polynomial kernel is proposed to predict drawbar pull. Nonlinear decreasing inertia weight particle swarm optimization (NDIWPSO) is employed for parameter optimization. As the relations between drawbar pull and its influencing factors have not been tested on real vehicles, a series of experimental analyses based on real vehicle test data are done to confirm the effective influencing factors. A dynamic testing system is applied to conduct field tests and gain required test data. Gaussian kernel RVM, polynomial kernel RVM, support vector machine (SVM) and generalized regression neural network (GRNN) are also used to compare with the MkRVM model. The results indicate that the MkRVM model is a preferable model in this case. Finally, the proposed novel model is compared to the traditional prediction model of drawbar pull. The results show that the MkRVM model significantly improves the prediction accuracy. A great potential of improved RVM is indicated in further research of wheel-soil interactions.

Affected by external noise and various nature disturbances, Wheel Force Transducer (WFT) signal may be completely submerged, and the sensitivity and the reliability of measurement can be strongly decreased. In this paper, a new wavelet packet denoising method based on sparse representation is proposed to remove the noises from WFT signal. In this method, the problem of recovering the noiseless signal is converted into an optimization problem of recovering the sparsity of their wavelet package coefficients, and the wavelet package coefficients of the noiseless signals can be obtained by the augmented Lagrange optimization method. Then the denoised WFT signal can be reconstructed by wavelet packet reconstruction. The experiments on simulation signal and WFT signal show that the proposed denoising method based on sparse representation is more effective for denoising WFT signal than the soft and hard threshold denoising methods.