Weighted Orthogonal Distance Regression for Tire Models Parameters Identification

2015 ◽  
Author(s):  
JoseLuis Olazagoitia ◽  
Alberto López
Keyword(s):  
Test Data ◽  
Measured Data ◽  
Model Parameters ◽  
Tire Model ◽  
Optimum Parameters ◽  
Ordinate Axis ◽  
Orthogonal Distance Regression ◽  
Independent Variable ◽  
Tire Models ◽  
Least Squares Techniques

Determining the parameters in existing tire models (e.g. Magic Formula (MF)) for calculating longitudinal and lateral forces depending on the tire slip is often based on standard least squares techniques. This type of optimization minimizes the vertical differences in the ordinate axis between the test data and the chosen tire model. Although the practice is to use this type of optimization in adjusting those model parameters, it should be noted that this approach disregards the errors that have been committed in the measurement of tire slips. These inaccuracies in the measured data affect the optimum parameters of the model, producing non optimum models. This paper presents a methodology to improve the fitting of mathematical tire models on available test data, taking into account the vertical errors together with errors in the independent variable.

Radial-Interradial Spring Tire Models

1988 ◽  
Vol 110 (1) ◽  
pp. 70-75 ◽  
Author(s):  
J. M. Badalamenti ◽  
G. R. Doyle
Keyword(s):  
Test Data ◽  
Close Agreement ◽  
Tire Model ◽  
Drag Forces ◽  
Tire Models

Two radial-interradial spring tire models are developed to predict vertical and drag forces produced by a tire as it rolls over an obstacle. Interradial springs are used to interconnect radial linear or quadratic springs to make each tire element’s deflection dependent upon its adjacent element’s deflections. Forces predicted by these two models are compared with a previously developed quadratic radial spring tire model and test data. The newly developed quadratic radial-linear interradial spring tire model predicts vertical and drag forces that are in close agreement with the test data.

scholarly journals Efficient In-Plane Tire Mode Identification by Radial-Tangential Eigenvector Compounding

2015 ◽  
Vol 43 (1) ◽  
pp. 71-84
Author(s):  
Vasilis Tsinias ◽  
George Mavros
Keyword(s):  
Experimental Studies ◽  
Modal Testing ◽  
Mode Shapes ◽  
Model Parameters ◽  
Tire Model ◽  
Mode Identification ◽  
Tire Dynamics ◽  
Efficient Processing ◽  
Noise Vibration ◽  
Tire Models

ABSTRACT Tire modal testing is frequently used for validation of numerical tire models and identification of structural tire model parameters. Most studies focus primarily on in-plane dynamic tire behavior and adopt the approach of the fixed boundary condition at the wheel center. Here, an identification method of in-plane tire dynamics was developed for the case of a free tire-rim combination. This particular case is important when the aim is to construct a full tire model, capable of predicting ride and noise, vibration, and harshness involving the whole vehicle, all from modal testing. Key attributes of the proposed approach include ease of implementation and efficient processing of measurements. For each type of excitation, i.e., radial and tangential, both radial and tangential responses were recorded. Compounding of the corresponding radial/tangential eigenvectors, which, in the context of the present work, refers to expressing the motion of the tire belt as a combination of the radial and tangential responses, results in smooth mode shapes that were found to agree with those published in other analytical and experimental studies.

scholarly journals Optimal parameter estimation in semi-empirical tire models

2018 ◽  
Vol 233 (1) ◽  
pp. 73-87 ◽  
Author(s):  
Alberto López ◽  
José Luis Olazagoitia ◽  
Francisco Marzal ◽  
María Rosario Rubio
Keyword(s):  
Optimal Parameter ◽  
Nonlinear Least Squares ◽  
Model Parameters ◽  
Tire Model ◽  
Independent Variables ◽  
Optimal Parameter Estimation ◽  
Reliable Parameter ◽  
Test Points ◽  
Semi Empirical ◽  
Tire Models

Semi-empirical tire models are mathematical models, the parameters of which are identified after a process of error reduction to fit experimental data obtained in the laboratory. In this process, the algorithms used for estimating the model parameters are usually based on nonlinear least-squares fitting methods, in which only vertical residuals between the model and the test points are considered. Although extensively utilized, this type of fitting implicitly considers that errors in the slip data (horizontal residuals) are either nonexistent or negligible, which is not true. This paper introduces a new methodology to the identification of semi-empirical tire model parameters based on weighed orthogonal residuals, which takes into account possible errors inherent in the test measurements of dependent and independent variables. The results show that the methodology offers a reliable parameter identification providing an even fitting for all the zones of the mathematical semi-empirical tire model.

A Empirical Tire Model of Non-Steady State Cornering Properties Considering Carcass Elasticity

2000 ◽  
Author(s):  
Yongping Hou ◽  
Yujin Hu ◽  
Chenggang Li ◽  
Konghui Guo
Keyword(s):  
Steady State ◽  
High Precision ◽  
Test Data ◽  
Vehicle Dynamics ◽  
Low Frequency ◽  
Frequency Region ◽  
Tire Model ◽  
Yaw Angle ◽  
Tire Models

Abstract The purpose of this paper is to present two empirical tire models of non-steady state cornering property with respect to yaw angle input in low frequency region on the basis of existing tire model and considering the elasticity of the carcass. Verified by test, theoretical values meet well with test data. Comparing with existing tire models, the models described in the paper have more advantages, and they also have high precision. They can be applied for vehicle dynamics studies.

A Modified Dugoff Tire Model for Combined-slip Forces

2010 ◽  
Vol 38 (3) ◽  
pp. 228-244 ◽  
Author(s):  
Nenggen Ding ◽  
Saied Taheri
Keyword(s):  
Vehicle Dynamics ◽  
Tire Model ◽  
Magic Formula ◽  
Model Based ◽  
Proposed Model ◽  
Road Friction ◽  
On Line ◽  
Double Lane Change ◽  
Tire Forces ◽  
Tire Models

Abstract Easy-to-use tire models for vehicle dynamics have been persistently studied for such applications as control design and model-based on-line estimation. This paper proposes a modified combined-slip tire model based on Dugoff tire. The proposed model takes emphasis on less time consumption for calculation and uses a minimum set of parameters to express tire forces. Modification of Dugoff tire model is made on two aspects: one is taking different tire/road friction coefficients for different magnitudes of slip and the other is employing the concept of friction ellipse. The proposed model is evaluated by comparison with the LuGre tire model. Although there are some discrepancies between the two models, the proposed combined-slip model is generally acceptable due to its simplicity and easiness to use. Extracting parameters from the coefficients of a Magic Formula tire model based on measured tire data, the proposed model is further evaluated by conducting a double lane change maneuver, and simulation results show that the trajectory using the proposed tire model is closer to that using the Magic Formula tire model than Dugoff tire model.

A Double Interaction Brush Model for Snow Conditions

2019 ◽  
Vol 47 (2) ◽  
pp. 118-140
Author(s):  
Artem Kusachov ◽  
Fredrik Bruzelius ◽  
Mattias Hjort ◽  
Bengt J. H. Jacobson
Keyword(s):  
Low Complexity ◽  
Large Set ◽  
Tire Model ◽  
Vehicle Handling ◽  
Real Time Applications ◽  
Snow Conditions ◽  
Double Interaction ◽  
Tire Models ◽  
Force Characteristics ◽  
Model Approach

ABSTRACT Commonly used tire models for vehicle-handling simulations are derived from the assumption of a flat and solid surface. Snow surfaces are nonsolid and may move under the tire. This results in inaccurate tire models and simulation results that are too far from the true phenomena. This article describes a physically motivated tire model that takes the effect of snow shearing into account. The brush tire model approach is used to describe an additional interaction between the packed snow in tire tread pattern voids with the snow road surface. Fewer parameters and low complexity make it suitable for real-time applications. The presented model is compared with test track tire measurements from a large set of different tires. Results suggest higher accuracy compared with conventional tire models. Moreover, the model is also proven to be capable of correctly predicting the self-aligning torque given the force characteristics.

In-Plane Flexible Ring Tire Model—Part 1: Modeling and Parameter Identification

2018 ◽  
Vol 46 (3) ◽  
pp. 174-219 ◽  
Author(s):  
Bin Li ◽  
Xiaobo Yang ◽  
James Yang ◽  
Yunqing Zhang ◽  
Zeyu Ma
Keyword(s):  
Static Load ◽  
Model Parameters ◽  
Tire Model ◽  
Test Results ◽  
Lumped Mass ◽  
Virtual Test ◽  
Proposed Model ◽  
Particle Swarm Method ◽  
Vehicle Dynamic Simulation ◽  
Flexible Ring

ABSTRACT The tire model is essential for accurate and efficient vehicle dynamic simulation. In this article, an in-plane flexible ring tire model is proposed, in which the tire is composed of a rigid rim, a number of discretized lumped mass belt points, and numerous massless tread blocks attached on the belt. One set of tire model parameters is identified by approaching the predicted results with ADAMS® FTire virtual test results for one particular cleat test through the particle swarm method using MATLAB®. Based on the identified parameters, the tire model is further validated by comparing the predicted results with FTire for the static load-deflection tests and other cleat tests. Finally, several important aspects regarding the proposed model are discussed.

Pemberian Umpan Balik Dalam Meningkatkan Hasil Belajar dan Minat Belajar Mahasiswa

2015 ◽  
Vol 4 (3) ◽  
Author(s):  
Seruni Seruni ◽  
Nurul Hikmah
Keyword(s):  
Information Technology ◽  
Learning Outcomes ◽  
Test Data ◽  
Random Sampling ◽  
Covariance Matrices ◽  
Test Results ◽  
Immediate Feedback ◽  
Statistics Course ◽  
Independent Variable ◽  
Descriptive Statistical Analysis

<p>The purpose of this study is to find and analyze the effect of feedback on <br />learning outcomes in mathematics and an interest in basic statistics course. The <br />population in this study are affordable Information Technology Student cademic Year 2012/2013 Semester II Indraprasta PGRI University of South Jakarta. Sample The study sample was obtained through random sampling. This study used an experimental method to the analysis using the MANOVA test. This study has three variables, consisting of: one independent variable, namely the provision of feedback (immediate and delayed), and two dependent variable is the result of interest in the study of mathematics and basic statistics course. The data was collected for the test results to learn mathematics, and a questionnaire for the interest in basic statistics course. Collected data were analyzed using the MANOVA test. Before the data were analyzed, first performed descriptive statistical analysis and test data analysis requirements (test data normality and homogeneity of covariance matrices). The results show that the learning outcomes of interest in mathematics and basic statistics course for students who are given immediate feedback higher than students given feedback delayed. <br /><br /></p>

An improved nonlinear innovation-based parameter identification algorithm for ship models

2021 ◽  
pp. 1-9
Author(s):  
Baigang Zhao ◽  
Xianku Zhang
Keyword(s):  
Parameter Identification ◽  
Test Data ◽  
Stochastic Gradient ◽  
Least Square ◽  
Gradient Algorithm ◽  
Model Parameters ◽  
Identification Algorithm ◽  
Process Innovations ◽  
Stochastic Gradient Algorithm ◽  
Tangent Function

Abstract To solve the problem of identifying ship model parameters quickly and accurately with the least test data, this paper proposes a nonlinear innovation parameter identification algorithm for ship models. This is based on a nonlinear arc tangent function that can process innovations on the basis of an original stochastic gradient algorithm. A simulation was carried out on the ship Yu Peng using 26 sets of test data to compare the parameter identification capability of a least square algorithm, the original stochastic gradient algorithm and the improved stochastic gradient algorithm. The results indicate that the improved algorithm enhances the accuracy of the parameter identification by about 12% when compared with the least squares algorithm. The effectiveness of the algorithm was further verified by a simulation of the ship Yu Kun. The results confirm the algorithm's capacity to rapidly produce highly accurate parameter identification on the basis of relatively small datasets. The approach can be extended to other parameter identification systems where only a small amount of test data is available.

Multi-day flow forecasting using the Kalman filter

1991 ◽  
Vol 18 (2) ◽  
pp. 320-327 ◽  
Author(s):  
Murray A. Fitch ◽  
Edward A. McBean
Keyword(s):  
Kalman Filter ◽  
Prediction Model ◽  
Linear Prediction ◽  
Measured Data ◽  
System Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Forecasting Performance ◽  
Optimal Forecasting ◽  
Linear Prediction Model

A model is developed for the prediction of river flows resulting from combined snowmelt and precipitation. The model employs a Kalman filter to reflect uncertainty both in the measured data and in the system model parameters. The forecasting algorithm is used to develop multi-day forecasts for the Sturgeon River, Ontario. The algorithm is shown to develop good 1-day and 2-day ahead forecasts, but the linear prediction model is found inadequate for longer-term forecasts. Good initial parameter estimates are shown to be essential for optimal forecasting performance. Key words: Kalman filter, streamflow forecast, multi-day, streamflow, Sturgeon River, MISP algorithm.

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