Identification of Pacejka’s Coefficients Through Full Vehicle Experimental Tests

2007 ◽  
Author(s):  
Federico Cheli ◽  
Francesco Braghin ◽  
Ferruccio Resta ◽  
Edoardo Sabbioni
Keyword(s):  
Experimental Data ◽  
Kalman Filter ◽  
Steady State ◽  
Extended Kalman Filter ◽  
Experimental Tests ◽  
Constrained Minimization ◽  
Identification Procedure ◽  
Tyre Model ◽  
Full Vehicle ◽  
Minimization Approach

A methodology aimed at identifying the MF-Tyre model coefficients for the steady-state pure cornering condition is presented in this paper. Only the measurements carried out on board vehicle during standard handling manoeuvres (step-steer) are considered by the identification procedure. The proposed methodology is made of three subsequent steps. During the first phase the axles cornering forces are identified through an extended Kalman filter. Then the vertical loads and the slip angles at each tire are estimated. The results of these two steps are passed as an input to the last phase, during which through a constrained minimization approach, the MF coefficients are identified. The identification procedure has been applied to the experimental data collected on an instrumented sport car.

Identification of Tire Model Parameters Through Full Vehicle Experimental Tests

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
Francesco Braghin ◽  
Federico Cheli ◽  
Edoardo Sabbioni
Keyword(s):  
Laboratory Tests ◽  
Experimental Tests ◽  
Contact Forces ◽  
Lateral Acceleration ◽  
Design Stage ◽  
Model Parameters ◽  
Tire Model ◽  
Identification Procedure ◽  
Sideslip Angle ◽  
Tyre Model

Individual tire model parameters are traditionally derived from expensive component indoor laboratory tests as a result of an identification procedure minimizing the error with respect to force and slip measurements. These parameters are then transferred to vehicle models used at a design stage to simulate the vehicle handling behavior. A methodology aimed at identifying the Magic Formula-Tyre (MF-Tyre) model coefficients of each individual tire for pure cornering conditions based only on the measurements carried out on board vehicle (vehicle sideslip angle, yaw rate, lateral acceleration, speed and steer angle) during standard handling maneuvers (step-steers) is instead presented in this paper. The resulting tire model thus includes vertical load dependency and implicitly compensates for suspension geometry and compliance (i.e., scaling factors are included into the identified MF coefficients). The global number of tests (indoor and outdoor) needed for characterizing a tire for handling simulation purposes can thus be reduced. The proposed methodology is made in three subsequent steps. During the first phase, the average MF coefficients of the tires of an axle and the relaxation lengths are identified through an extended Kalman filter. Then the vertical loads and the slip angles at each tire are estimated. The results of these two steps are used as inputs to the last phase, where, the MF-Tyre model coefficients for each individual tire are identified through a constrained minimization approach. Results of the identification procedure have been compared with experimental data collected on a sport vehicle equipped with different tires for the front and the rear axles and instrumented with dynamometric hubs for tire contact forces measurement. Thus, a direct matching between the measured and the estimated contact forces could be performed, showing a successful tire model identification. As a further verification of the obtained results, the identified tire model has also been compared with laboratory tests on the same tire. A good agreement has been observed for the rear tire where suspension compliance is negligible, while front tire data are comparable only after including a suspension compliance compensation term into the identification procedure.

Application of Linear Observers to Estimate States of a Roll Simulator

2014 ◽  
Author(s):  
Scott B. Zagorski ◽  
Gary J. Heydinger ◽  
Dennis A. Guenther
Keyword(s):  
Nonlinear Dynamics ◽  
Experimental Data ◽  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Kalman Filters ◽  
Disturbance Observer ◽  
Gain Scheduling ◽  
System Parameters ◽  
Scheduling Scheme

In this research, a variety of Kalman Filters are implemented in an effort to estimate sled speed of a Roll Simulator. An Extended Kalman Filter (EKF) is incorporated to capture the nonlinear dynamics of the sled-platform assembly to estimate sled speed for the entire motion, as a linear Kalman Filter was found to be inadequate. When applied to experimental data, the EKF over-estimates sled speed, which is due to a disturbance force and/or uncertainty in system parameters. In combination with the disturbance observer, the Kalman Filter adequately estimates sled speed for experimental data. For lower speed/payload applications, a Kalman Filter using an accelerometer and measured drum speed is able to accurately track sled speed when a gain scheduling scheme is employed.

Extended Kalman Filter for Reconstruction of a Nonlinear Thermofluid System

1986 ◽  
Vol 108 (2) ◽  
pp. 156-158 ◽  
Author(s):  
R. Shoureshi ◽  
K. McLaughlin
Keyword(s):  
Experimental Data ◽  
Kalman Filter ◽  
Heat Pump ◽  
Extended Kalman Filter ◽  
Eigenvalue Distribution ◽  
Integration Time ◽  
Time Step ◽  
Filter Technique ◽  
Gain Matrix ◽  
Good Agreement

Extended Kalman filter technique is used to develop an observer for a nonlinear thermofluid system, namely a heat pump. The observer’s optimal gain matrix is designed based on the eigenvalue distribution, integration time step, and stability of the system along a desired trajectory. The observer response is compared with experimental data and very good agreement is obtained.

Automotive Battery Prognostics Using Dual Extended Kalman Filter

2009 ◽  
Author(s):  
Matteo Rubagotti ◽  
Simona Onori ◽  
Giorgio Rizzoni
Keyword(s):  
Experimental Data ◽  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Remaining Useful Life ◽  
State Of Charge ◽  
Future Evolution ◽  
On Line ◽  
Automotive Batteries ◽  
Useful Life ◽  
Simulation Results

This paper proposes a strategy for estimating the remaining useful life of automotive batteries based on dual Extended Kalman Filter. A nonlinear model of the battery is exploited for the on-line estimation of the State of Charge, and this information is used to evaluate the actual capacity and predict its future evolution, from which an estimate of the remaining useful life is obtained with suitable margins of uncertainty. Simulation results using experimental data from lead-acid batteries show the effectiveness of the approach.

Validation of vehicle-based tyre testing methods

2018 ◽  
Vol 233 (1) ◽  
pp. 18-27
Author(s):  
Anton Albinsson ◽  
Fredrik Bruzelius ◽  
Bengt Jacobson ◽  
Shenhai Ran
Keyword(s):  
Steady State ◽  
Development Process ◽  
Simulation Models ◽  
Operating Conditions ◽  
Road Surface ◽  
Model Verification ◽  
Slip Angle ◽  
Tyre Model ◽  
Vehicle Simulation ◽  
Full Vehicle

The development process for passenger cars is both time- and resource-consuming. Full vehicle testing is an extensive part of the development process that consumes large amount of resources, especially within the field of vehicle dynamics and active safety. By replacing physical testing with complete vehicle simulations, both the development time and cost can potentially be reduced. This requires accurate simulation models that represent the real vehicle. One major challenge with full vehicle simulation models is the representation of tyres in terms of force and moment generation. The force and moment generation of the tyres is affected by both operating conditions and road surface. Vehicle-based tyre testing offers a fast and efficient way to rescale force and moment tyre models to different road surfaces, in this study the Pacejka 2002 model. The resulting tyre model is sensitive to both the operating conditions during testing and the road surface used. This study investigates the influence of the slip angle sweep rate and road surface on the lateral tyre force characteristics of the fitted tyre model. Tyre models fitted to different manoeuvres are compared and the influence on the full vehicle behaviour is investigated in IPG Carmaker. The results show that by using the wrong road surface, the resulting tyre model can end up outside the tolerances specified by the ISO standard for vehicle simulation model verification in steady-state cornering. The use of Pacejka 2002 models parameterized in a steady-state manoeuvre to simulate the vehicle behaviour in sine-with-dwell manoeuvres is also discussed.

scholarly journals COMPARISON BETWEEN RGB AND RGB-D CAMERAS FOR SUPPORTING LOW-COST GNSS URBAN NAVIGATION

2018 ◽  
Vol XLII-2 ◽  
pp. 991-998 ◽  
Author(s):  
L. Rossi ◽  
C. I. De Gaetani ◽  
D. Pagliari ◽  
E. Realini ◽  
M. Reguzzoni ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Urban Areas ◽  
Ad Hoc ◽  
Focal Length ◽  
Low Cost ◽  
Experimental Tests ◽  
Microsoft Kinect ◽  
Visual Data ◽  
Data Accessibility

A pure GNSS navigation is often unreliable in urban areas because of the presence of obstructions, thus preventing a correct reception of the satellite signal. The bridging between GNSS outages, as well as the vehicle attitude reconstruction, can be recovered by using complementary information, such as visual data acquired by RGB-D or RGB cameras. In this work, the possibility of integrating low-cost GNSS and visual data by means of an extended Kalman filter has been investigated. The focus is on the comparison between the use of RGB-D or RGB cameras. In particular, a Microsoft Kinect device (second generation) and a mirrorless Canon EOS M RGB camera have been compared. The former is an interesting RGB-D camera because of its low-cost, easiness of use and raw data accessibility. The latter has been selected for the high-quality of the acquired images and for the possibility of mounting fixed focal length lenses with a lower weight and cost with respect to a reflex camera. The designed extended Kalman filter takes as input the GNSS-only trajectory and the relative orientation between subsequent pairs of images. Depending on the visual data acquisition system, the filter is different because RGB-D cameras acquire both RGB and depth data, allowing to solve the scale problem, which is instead typical of image-only solutions. The two systems and filtering approaches were assessed by ad-hoc experimental tests, showing that the use of a Kinect device for supporting a u-blox low-cost receiver led to a trajectory with a decimeter accuracy, that is 15 % better than the one obtained when using the Canon EOS M camera.

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