• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.3
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• pp.142-147
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• 2013

Over the past few years, intelligent tire is developed very actively for more accurate measurement of real-time tire forces generated during vehicle driving situation. Information on the force of intelligent tire could be used very usefully to chassis control systems of a vehicle. Intelligent tire is based on deformation of tire's inner surface from the waveform of a SAW, or Surface Acoustic Wave. The tire vertical force is estimated by using variance analysis of sensor signals. The estimated tire vertical force is compared with the tire vertical force generated during vehicle driving situation in real-time environment. The scope of this paper is a correlation study between the measured sensor signals and the tire vertical force generated during vehicle driving situation.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.5
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• pp.512-519
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• 2016

In this study, the tire road friction estimation(TRFE) algorithm for controlling the rear wheel driving force of a 4WD vehicle during acceleration is developed using a standard sensor in an ordinary 4WD passenger car and a speed sensor. The algorithm is constructed for the wheel shaft torque, longitudinal tire force, vertical tire force and maximum tire road friction estimation. The estimation results of shaft torque and tire force were validated using a torque sensor and wheel force transducer. In the algorithm, the current road friction is defined as the proportion calculated between longitudinal and vertical tire force. Slip slop methods using current road friction and slip ratio are applied to estimate the road friction coefficient. Based on this study's results, the traction performance, fuel consumption and drive shaft strength performance of a 4WD vehicle are improved by applying the tire road friction estimation algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1871-1877
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• 2000

Longitudinal and lateral forces acting at tire are known to be closely related to the tractive ability, braking characteristics, handling stability and maneuverability of ground vehicles. However, it is not feasible in the operating vehicles to measure the tire forces directly because of high cost of sensors, limitations in sensor technology, interference with the tire rotation and harsh environment. In this paper, in order to develop tire force monitoring system, a new vehicle dynamics monitoring model is proposed including the roll motion. Based on the monitoring model, tire force monitoring system is designed to estimate the lateral tire force acting at each tire. A newly proposed SKFMEC (Scaled Kalman Filter with Model Emr Compensator) method is developed utilizing the conventional EKF (Extended Kalman Filter) method. Tire force estimation performance of the SKFMEC method is evaluated in the Matlab simulations where true tire force data is generated from a 14 DOF vehicle model with a combined-slip Magic Formula tire model.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2352-2354
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• 2003

An apparatus and method for imposing a desired average radial force on tire by calculating the current average force between the tire and load wheel based on the average radial force and radial distance between the tire load wheel over the last previous complete revolution of the tire, the spring constant of the tire and the current radial distance between the tire and the load wheel.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.632-638
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• 2010

This paper presents an optimum tire force distribution method for 6WD/6WS(6-Wheel-Drive and 6-Wheel-Steering) electric vehicles. Using an independent steering and driving system, the performance of 6WD/6WS vehicles can be improved, as, for example, with respect to their maneuverability under low speed and their stability at high speed. Therefore, there should be a control strategy for finding the optimum tire forces that satisfy the driver's command and minimize energy consumption. From the driver's commands (steering angle and accelerator/brake pedal stroke), the desired yaw moment, the desired lateral force, and the desired longitudinal force were obtained. These three values were distributed to each wheel as the torque and the steering angle, based on the optimum tire force distribution method. The optimum tire force distribution method finds the longitudinal/lateral tire forces of each wheel that minimize the cost function, which is the sum of the normalized tire forces. Next, the longitudinal/lateral tire forces of each wheel are converted into the reference torque inputs and the steering wheel angle inputs. The proposed method was tested through a simulation, and its effectiveness was verified.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.33-38
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• 2021

This paper presents a comparative study between the parameter-optimized Pacejka model and artificial neural network model for the tire force estimation. The two different approaches are investigated and compared in this study. First, offline optimization is conducted based on Pacejka Magic Formula model to determine the proper parameter set for the minimization of tire force error between the model and test data set. Second, deep neural network model is used to fit the model to the tire test data set. The actual tire forces are measured using MTS Flat-Track test platform and the measurements are used as the reference tire data set. The focus of this study is on the applicability of machine learning technique to tire force estimation. It is shown via the regression results that the deep neural network model is more effective in describing the tire force than the parameter-optimized Pacejka model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.148-151
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• 2005

Roughness of a road is an important parameter which not only indicates vehicle's vibration and noise, but it is also related to the contact force of the tire which is induced by tire's deformation and vibration. Since tire noise indeed comes from this deformation and vibration, the estimation of the force is the key factor fur the reduction of tire noise. Because of the difficulty of directly measuring the contact force, the indirect estimation is enforced from the vibration signature measured on the tire support. This study suggests the "inverse filtering" technique well known in modern digital signal processing, so as to reform the tire contact force from monitored vibration signals.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.903-909
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• 2015

This article presents an integrated chassis control with electronic stability control (ESC) and active front steering (AFS) under saturation of front lateral tire force. Regardless of the use of AFS, the front lateral tire forces can be easily saturated. Under the saturated front lateral tire force, AFS cannot be effective to generate a control yaw moment needed for the integrated chassis control. In this paper, new integrated chassis control is proposed in order to limit the use of AFS in case the front lateral tire force is saturated. Weighed pseudo-inverse control allocation (WPCA) with variable weight is adopted to adaptively use the AFS. To check the effectiveness of the proposed scheme, simulation is performed on a vehicle simulation package, CarSim. From simulation, the proposed integrated chassis control is effective for vehicle stability control under saturated front lateral tire force.

• Journal of Institute of Convergence Technology
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• v.1 no.1
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• pp.9-12
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• 2011

Structural analysis of a tire is done using a commercial software, ANSYS Workbench. The properties of rubber of the tire is represented using a Mooney-Rivlin model. The bead in the tire is made of structural steel. 3D CAD model of the tire is obtained from a commercial CAD-specialized software, CATIA. Using an imported 3D CAD geometric model, a mesh system with fifty thousand nodes is constructed using ANSYS. A time-variant point force is applied to the rim of the tire, and the deformation of the tire is computed. It is found that both bending and twisting of the tire are observed where the point force is applied. The deformation of the tire is asymmetric, which results in the help of ripping the tire using the helper. It is also found that the deformation undergoes linearly with the applied force. When the force is larger than 1500N, then the deformation becomes larger than the half of the thickness of the tire. In the future, a more realistic rubber model will be applied and validated with the measured data.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.4
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• pp.169-176
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• 2000

Longitudinal and lateral forces acting on tires are known to be closely related to the tract-ability braking characteristics handling stability and maneuverability of ground vehicles. In thie paper in order to develop tire force monitoring systems a monitoring model is proposed utilizing not only the vehicle dynamics but also the roll motion. Based on the monitoring model three monitoring systems are developed to estimate the tire force acting on each tire. Two monitoring systems are designed utilizing the conventional estimation techniques such as SMO(Sliding Mode Observer) and EKF(Extended Kalman Filter). An additional monitoring system is designed based on a new SKFMEC(Scaled Kalman Filter with Model Error Compensator) technique which is developed to improve the performance of EKF method. Tire force estimation performance of the three monitoring systems is compared in the Matlab simulations where true tire force data is generated from a 14 DOF vehicle model with the combined-slip Magic Formula tire model. The built in our Lab. simulation results show that the SKFMEC method gives the best performance when the driving and road conditions are perturbed.