Wheel Force Transducer Research Articles

An Interpretable Nonlinear Decoupling and Calibration Approach to Wheel Force Transducers

An Interpretable Nonlinear Decoupling and Calibration Approach to Wheel Force Transducers

Investigation into high-performance tire characteristics at the limits of handling

This paper presents an investigation into high-performance tire characteristics at handling limits. Analysis of the tire characteristics has been conducted using the data obtained from indoor test rigs and vehicle tests. The test rig utilised a flat track test platform to obtain tire forces with precise controllability and measurability. As for the vehicle tests, driving data of a professional driver was obtained for repeatability through a high-performance test vehicle equipped with a wheel force transducer (WFT) at each wheel and a Differential Global Positioning System (DGPS). This study is primarily focused on obtaining a deeper insight into vehicle control through an analysis of tire force characteristics at handling limits. The analysis of indoor test data utilised the Magic Formula to obtain an appropriate model capable of describing real-world tire characteristics. An optimisation-based friction ellipse has been proposed to describe the tire force limits in particular. The solution of the proposed optimisation problem allows for an envelope to be generated that accurately reflects the tire force limits. Additionally, a normalised friction circle model has been proposed to quantify tire friction usage based on the proposed friction ellipse, providing a methodology to monitor the friction use of each wheel.

Finite Element modeling of force amplification at the spindle due to a tire's cavity mode: experimental verification

Reduction of tire-road noise is an important issue when developing luxury cars and electric vehicles. In this context, the air-cavity mode is an important source of spindle forces transmitted to the suspension that then increase interior noise levels. When a tire rotates, the cavity mode near 200 Hz splits into two adjacent modes due to a Doppler effect and tire deformation. That split can lead to increased levels of both longitudinal and vertical spindle forces at the spindle since the two acoustic modes each contribute to both forces when the tire rotates. Thus, it is important to develop tools to identify the contributions of the split air-cavity modes to the spindle force. A FE simulation of the spindle force for a steady-state rolling has been verified by a comparison with laboratory test results obtained by using a wheel-force transducer mounted on Purdue's Tire Pavement Test Apparatus. It was observed that the frequency split expands as the rotation speed increases and that the vertical spindle force increases when aligned with an odd-numbered circumferential structural mode. By using the correlated simulation model, parametric studies have been carried out focused on minimizing the vertical spindle force due to air-cavity mode near 200 Hz.

A New Approach to Predict Dynamic Loads Considering Highway Alignment Using Data Mining Techniques

Premature damage to heavy-duty pavement has been found to be significantly caused by the vehicle–highway alignment interaction, especially in mountainous regions. This phenomenon was further verified by field pavement damage investigations and field tests. In order to elucidate the potential mechanism of this interaction, it is important to address the vehicle dynamic loads generated by the interaction between vehicle and pavement. Based on this, the paper realizes a new method of vehicle dynamic load prediction using data mining techniques, namely artificial neural network (ANN) and support vector machine (SVM)). The data, including dynamic loads and highway geometric characteristics, were collected by a wheel force transducer (WFT) and global positioning system (GPS), respectively. The coefficient of determination (R2) and root mean square error (RMSE) were used to evaluate the performance of the prediction models. The results showed that the proposed dynamic load prediction model established by ANN was better than that by SVM. Moreover, the model implied that dynamic loads were highly correlated with curvature and longitudinal grade, and furthermore, curvature was found to have a larger effect. The proposed dynamic load prediction technique provides a feasible and rapid approach to identify pavement damage under complex vehicle–highway alignment interactions.

Dynamic input loads evaluation of a recreational vehicle frame using multibody dynamics hybrid modeling validated with experimental and full analytical modeling data

Knowledge of frame loads at the limits of the intended driving conditions is important during the design process of a vehicle structure. Yet, retrieving these loads is not trivial as the load path between the road and the frame mounting point is complex. Fortunately, recent studies have shown that multibody dynamic (MBD) simulations could be a powerful tool to estimate these loads. Two main categories of MBD simulations exist. Firstly, full analytical simulations, which have received great attention in the literature, are run in a virtual environment using a tire model and a virtual road. Secondly, hybrid simulations, also named semi analytical, uses experimental data from Wheel Force Transducers and Inertial Measurement Units to replace the road and tire models. It is still unclear how trustworthy semi analytical simulations are for frame load evaluation. Both methods were tested for three loads cases. It was found that semi analytical simulations were slightly better in predicting vehicle dynamic and frame loads than the full analytical simulations for frequencies under the MF-Tyre model valid frequency range (8 Hz) with accuracy levels over 90%. For faster dynamic maneuvers, the prediction accuracy was lower, in the 50%–80% range, with semi analytical simulations showing better results.

Structural optimization of a wheel force transducer component for more realistic acquisition of vehicle load data and fracture mechanical evaluation

Special measuring wheels are used to record vehicle load data. It is important that the data is recorded unaltered and as true to the original as possible. Due to the sensor technology, the measuring wheels are usually heavier than standard rims, which results in an influence on the recorded measurement data.In this paper an approach is shown to develop a structure with the same performance but reduced mass by using CAD and numerical analysis. Due to the geometrically complex structure, the selective laser melting process is chosen as the manufacturing method for the optimized part. The lightweight construction potential can be fully exploited by homogeneously stressing the optimized part and by using the Ti6–4 alloy, which has a higher Young's modulus than the aluminum alloy used so far. The interaction of the methods of technical mechanics, CAD, FEM, and additive manufacturing results in a safety-relevant component that has a mass reduced by almost 40% compared to the previously used component while maintaining the same stiffness. A final crack growth simulation confirms the operationally safe design. Finally, the component was first tested experimentally on a test rig and then installed in a vehicle. All tests were passed successfully.

Rapid Road Friction Estimation using Independent Left/Right Steering Torque Measurements

Sensing the friction coefficient between the tyres of an automobile and the road surface is a key challenge in automotive control. Accurate estimation of this parameter enables higher performance and safer operation of vehicles, whether human-operated, assisted or autonomously controlled. Previous approaches have utilised braking or lateral excitation to generate estimates but are limited by the conflict between generating sufficient excitation and preserving ride comfort and efficient operation. Further complicating the problem is the need to provide the friction estimate without adding costly sensors to the vehicle. This paper presents an approach to friction estimation that leverages separate measurements of the left and right steering torques to generate an estimate of the surface friction through direct model inversion. Uncertainty of the method is explored using experimental sensor properties and analysis of the inverted model. The method is shown to be sensitive to reduced friction coefficients and can identify sudden changes before travelling a full contact patch length. Experimental validation of the approach is demonstrated with calibrated wheel force transducers as well as low-cost sensors suitable for incorporation into production vehicles.

Structure design of six-component strain-gauge-based transducer for minimum cross-interference via hybrid optimization methods

Cross-interference is an important performance index for multi-channel strain-gauge-based transducer. In this study, a comprehensive optimization model for minimum cross-interference while satisfying constraints of principal sensitivity and cross-sensitivity is presented for a six-component wheel force transducer (WFT) structure design. The WFT structure has a “T”-type elastic body other than the conventional Maltese cross-type. Based on structure finite element analysis and circuit analysis, the quantified principal sensitivity, cross-sensitivity, and cross-interference are discussed. Then, a mechanical-electrical multidisciplinary optimization model is constructed which has a complex objective function and many constraints. Trial computations show that this model has multiple local optimal points. Hybrid optimization methods including simulated annealing (SA) algorithm and sequence quadratic programming (SQP) algorithm are then adopted to obtain a better design. The optimization results reveal that, for the studied “T”-type transducer structure, relatively stronger lateral beam and weaker longitudinal beam are helpful to achieve low cross-interference. The performance of the optimized structure is verified by comparison with the benchmark structure and by stepwise loading. The presented comprehensive optimization model has good generality applicable to different-type multi-channel strain-gauge-based transducer structure design.

Modified Quasi-Newton Optimization Algorithm-Based Iterative Learning Control for Multi-Axial Road Durability Test Rig

The iterative learning control (ILC) based on the linear frequency-domain model has been employed to replicate the road conditions for the vehicle durability testing in the laboratory. Generally, the vehicle and the multi-axial hydraulic test rig behave strong nonlinearities, which requires a large number of iterations to correct the tracking error. Hence, the process of drive file (i.e., the input signals which drive the actuators of the test rig) generation is time-lengthy and tedious. A method that combines the ILC with the Quasi-Newton algorithm over the complex space (QNILC) is developed to speed up the drive file construction for the multi-axial vibration test rig. The impedance matrix can be updated with Broyden’s method to reduce the modeling errors and make the iteration more robust. An auxiliary estimating loop is inserted into the iteration process to attain an optimal learning gain. The convergence of the proposed method has been proven to be monotonic. This approach is validated through simulation, where the target signals are the real-life spindle forces gathered from the wheel force transducer. The simulation results demonstrate that the QNILC can improve the convergence rate and increase the tracking accuracy than the current offline ILC. The QNILC reduces the iteration number from nine down to five to converge to the desirable index compared with the offline ILC using gain 0.5. The new method based on the optimization algorithm can extend to other repetitive tracking processes.

On tyre force virtual sensing for future Automated Vehicle-Based Objective Tyre Testing (AVBOTT)

ABSTRACTIn this paper, a novel Automated Vehicle-Based Objective Tyre Testing (AVBOTT) concept is introduced. In brief, AVBOTT pursues the development of inexpensive automated testing vehicles capable of executing a set of standardised manoeuvres and generate large amounts of tyre data rapidly and inexpensively. Naturally, the costs associated with current vehicle instrumentation and, in particular, with Wheel Force Transducers (WFT) prevent this concept from realisation at the moment. In order to overcome this limitation, a cost-effective alternative to WFT is proposed in this paper to estimate the tyre forces using indirect measurement techniques. Specifically, for the first time, the validity of random-walk virtual tyre force sensors for vehicle-based objective tyre testing is studied comprehensively. Moreover, the suitability of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to extract relevant tyre attributes in a systematic manner from lateral and longitudinal dynamics manoeuvres is analysed in detail. The proposed solutions are assessed in a complete tarmac tyre testing program carried out at IDIADA with a fully instrumented experimental vehicle. Additional winter testing activities performed at Revi facilities (Sweden) complete the experimental evaluation at different mu levels.

Iterative learning control with complex conjugate gradient optimization algorithm for multiaxial road durability test rig

Service load replication performed on multiaxial hydraulic test rigs has been widely applied in automotive engineering for durability testing in laboratory. The frequency-domain off-line iterative learning control is used to generate the desired drive file, i.e. the input signals which drive the actuators of the test rig. During the iterations an experimentally identified linear frequency-domain system model is used. As the durability test rig and the specimen under test have a strong nonlinear behavior, a large number of iterations are needed to generate the drive file. This process will cause premature deterioration to the specimen unavoidably. In order to accelerate drive file construction, a method embedding complex conjugate gradient algorithm into the conventional off-line iterative learning control is proposed to reproduce the loading conditions. The basic principle and monotone convergence of the method is presented. The drive signal is updated according to the complex conjugate gradient and the optimal learning gain. An optimal learning gain can be obtained by an estimate loop. Finally, simulations are carried out based on the identified parameter model of a real spindle-coupled multiaxial test rig. With real-life spindle forces from the wheel force transducer in the proving ground test to be replicated, the simulation results indicate that the proposed conventional off-line iterative learning control with complex conjugate gradient algorithm allows generation of drive file more rapidly and precisely compared with the state-of-the-art off-line iterative learning control. Few have been done about the proposed method before. The new method is not limited to the durability testing and can be extended to other systems where repetitive tracking task is required.

Design of adaptive filter for the wheel force transducer

Wheel force transducers (WFTs) are widely used in the car and commercial vehicle industry to determine forces of vehicles in operation, relevant for multiple tasks within the development process of the manufacturers (Sankarganesh and Pawar, 2015). Due to the uncertainty and randomness of the wheel forces, it is crucial to design a suitable real-time filter for the WFT to obtain the high-accuracy forces data. Considering the diversity of the wheel forces, models for different dynamic ranges are established. And a two-step adaptive filter is proposed in this paper. In the first step, the wheel forces’ actual dynamic is evaluated by the interacting multiple model (IMM) algorithm, then a suitable model is chosen to match the evaluated dynamic of the wheel force for data denoising in the second step. Simulations in different driving conditions are carried out to demonstrate the effectiveness of the proposed filter. Furthermore, the results of data test show that the adaptive filter can be successfully used in practice to get high-accuracy wheel forces.

Estimation of Wheel-Ground Contact Normal Forces: Experimental Data Validation

Recent control and stabilization algorithms in driving security systems are based on the knowledge of vertical vehicle dynamics. In this article, a new methodology to estimate wheel-ground contact normal forces is presented. The proposed method use measurements from available sensors, like accelerometers, to update the static vertical forces while the vehicle is performing a mission, and suspension deflection sensors to determine the initial weight distribution. The primary goal of this study is the estimation of wheel-ground contact normal forces accurately while diminishing its dependence on the deflection sensors. One characteristic of this approach is the initial weight computation on each tire based on a multi-model technique and the Kalman filter. The algorithm’s response is validated with wheel force transducers measurements from a real experiment.

Structure Optimization of Wheel Force Transducer Based on Natural Frequency and Comprehensive Sensitivity

The current research of wheel force transducer (WFT) mainly focuses on test signal processing and decoupling methods based on signal itself, while the WFT structure optimization research related to decreasing the mass and increase the natural frequency and comprehensive sensitivity is not enough. In order to improve the WFT test accuracy, a structure optimization method based on natural frequency and comprehensive sensitivity indicators is put forward. The WFT with 8-beam elastic body is used for the finite element modeling (FEM), in which the following variations are taken into consideration: the connection type of elastic body with modified rim, the number of connection holes, and the respects of strain beam including the shape, the cross sectional area and the length, etc.. The test results shows that the natural frequency of the connecting block type is increased by 65.5% compared with the connecting seat type of elastic body & modified rim, and the main channel sensitivity is improved as well. The results show that the connecting block type will achieve the best comprehensive performance when the number of connecting holes between the elastic body and the modified rim is 20. And the thinner and longer strain beam with smaller cross section area is preferable within the scope of elastic body mechanical strength. This research proposes a novel structure optimization method for WFT which contributes to improve the measurement performance of WFT.

Damage evaluation of driving events for agricultural tractors

Durability is the capacity of a machine to maintain the functionality during its intended service life, under the recommended conditions and the prescribed levels of maintenance. A durable machine has to be designed with a sufficient fatigue resistance that can be accomplished only if its service loads are well known. Tractors are characterized by few large load oscillations and these are of most interest in the evaluation of the fatigue damage accumulated by the structural elements. These oscillations are caused by driving events, defined as any major change in vehicle speed, attitude or operating condition. In this paper, a signal processing methodology to automatically identify the highly damage events for axle housings is described. An agricultural tractor was equipped with four Wheel Force Transducers (WFTs) and a CAN-Bus based data logger in order to acquire axle housing loads and the driver’s operation signals. Signals were acquired for three different applications as ploughing, subsoiling and implement transportation. The loading events were identified through the analysis of the pairwise Time-Varying Correlation Coefficient (TVCC) between the driver’s operation signals and the WFT signals. A driving event was classified as a pattern of TVCCs and for each, the Time-Varying Pseudo-Damage (TVPD) was calculated. Using this methodology, it has been found that the most damaging event for the axle housings occur during the headland turn due to full load accelerations and vertical load transfer between front and rear axles. For these reasons in-field operations were more damaging than off-road transportation. The outlined signal processing methodology should be considered as a first step into the development of a health monitoring methodology for tractors.

Custom Design Multi-Axial Engine Mount Load-Cell Development for Road Load Identification and Fatigue Life Estimation

Copyright © 2016 SAE International. Internal combustion engines are attached on the vehicle body using engine mounts composed of two cast iron brackets and a rubber isolator connecting them. Engine mount road load identification during vehicle durability tests on proving ground is a critical task for engine mount development. Using standard multi-axial load-cell is not possible unless major design revisions on the vehicle body or engine block are done. Using wheel force transducers and vehicle dynamic simulation tools need extensive model tuning work to get accurate load information. Hence, a custom multi-axial load-cell design is preferred for the engine mount load identification of a BCar I4 engine. The developed load-cell engine mount bracket can be installed without doing any design changes on the vehicle. Design, durability analysis, instrumentation, calibration and vehicle installation of custom designed six degree of freedom multi-axial load cell have been performed. Strain and acceleration measurements have been conducted on vehicle durability test track. Data have been processed to obtain forces and moments in six degree of freedom on the engine mounts. The loading information was used for fatigue life estimation.

A Measuring Instrument for Off-road Vehicle Performance Testing

An overall description of a measuring instrument, wheel force transducer (WFT), developed for off-road vehicle performance testing is presented in the paper. For the research of off-road vehicle performance, it is important to determine the forces and torques as a response of the interaction between the wheel and the terrain. The WFT developed provides a solution of the direct measurement of the physical quantities. The WFT was designed as an automatic real-time data acquisition device with the wireless transmission technology. In the aspect of mechanical structure, only minor modifications of the wheel rim and two flanges were required for the installation of the WFT. The elastomeric of the sensor was designed with excellent mechanical strength for wheeled vehicles of weights ranging from 1.2 to 15 ton. Field tests were conducted after static calibration and dynamic calibration. The WFT was installed on the two front wheels of a 1.6-tone weight car. In preliminary field test, various vehicle maneuvers were executed for the validation of the validity, reliability and accuracy of the whole system, which was demonstrated by the test results. Six kinds of special testing pavements were selected to simulate the off-road situations. From the results, great potential of the WFT system is indicated in the application of off-road vehicle performance testing.

Angle error compensation in wheel force transducer

Wheel force transducers (WFTs) have performance characteristics that make them attractive for applications in endurance evaluation of road vehicles, ride and handling optimization, tire development and vehicle dynamics. Since the WFT is mounted on the wheel and rotates with it, the rotational angle of the wheel is indispensable to calculate the real wheel forces. Unfortunately, an angle error caused by the steering of the vehicle will be incorporated into the measurement of the rotational angle, resulting in great error in the wheel force calculation. A new compensation algorithm is proposed in this paper to eliminate this angle error. In this algorithm, the GPS speed has been introduced to modify the measurement of the rotational angle in real time. Simulations with designed vehicle movement are carried out to demonstrate the effectiveness of the compensation algorithm. Furthermore, the results of real vehicle test show that this algorithm can be successfully used in practice to get more reasonable wheel loads.

The inertial effect of acceleration fields on a self-decoupled wheel force transducer

Wheel force transducer (WFT) is a tool which can measure the three-axis forces and three-axis torques applied to the wheel in vehicle testing applications. However, the transducer is generally mounted on the wheel of a moving vehicle, when abruptly accelerating or braking, the mass/inertia of the transducer itself has extra effects on the sensor response so that inertia/mass loads will be detected and coupled into the signal outputs. This is the inertia coupling effect that decreases the sensor accuracy and should be avoided. In this paper, the inertia coupling problem induced by six dimensional accelerations is investigated for a universal WFT. Inertia load distribution of the WFT is solved based on the principle of equivalent mass and rotary inertia firstly, thus then its impact can be identified with the theoretical derivation. FEM simulation and experimental verification are performed as well. 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. The relative errors are acceptable within less than 5% and the maximum impact of inertia loads on the signal output is about 1.5% in the measuring range.

Design of real-time filter for the wheel force transducer

Purpose – Wheel force transducers (WFTs) have performance characteristics that make them attractive for applications in endurance evaluation of road vehicles, ride and handling optimization, tire development and vehicle dynamics. As a WFT is mounted on the the driven wheel, the loads on the wheel and the outputs of WFTs are usually nonlinearly related. Thus, a real-time filter is needed to measure the true loads on the wheel. Design/methodology/approach – In this paper, a new nonlinear filtering algorithm utilizing quadrature Kalman filter (QKF) is proposed to track the actual loads in real time through establishing the specific observation equations with Singer models. Findings – The simulation results show that the accuracy and the rapidity of QKF outperforms the capability of the unscented Kalman filter (UKF). Then, the dynamic tests on the MTS testing platform give the comparisons between the real-time QKF and the wavelet transform, where the former has superior dynamic accuracy. Finally, the practical tests of shifting and braking on a real vehicle confirm the effectiveness of QKF, which further validates the proposed method fitting reality. Originality/value – In this paper, a newly improved algorithm with QKF for WFT has been proposed and tested experimentally. As the wheel loads are always time-varying and complex, introducing Gaussian noise in the outputs of the transducer, WFT-suitable Singer model and WFT measurement equation base on a QKF are established. The experiment results show that QKF has advanced performance than the traditional UKF. Also, the road wheel test bed produced by MTS has been exploited as the test platform to demonstrate the dynamic efficiency of the proposed real-time filter under various operating conditions for a wide range of loads. And, the practical tests with the real vehicle are accomplished to verify the value and effectiveness of the proposed method.