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Daniel Lechner - One of the best experts on this subject based on the ideXlab platform.

  • An Estimation Process for Tire-Road Forces and Sideslip Angle for Automotive Safety Systems
    Informatics in Control Automation and Robotics, 2020
    Co-Authors: Guillaume Baffet, Daniel Lechner, Ali Charara, Damien Thomas
    Abstract:

    This study focuses on the estimation of car dynamic variables for the improvement of vehicle safety, handling characteristics and comfort. More specifically, a new estimation process is proposed to estimate longitudinal/lateral tire-road forces, velocity, sideslip angle and wheel Cornering Stiffness. This\break method uses measurements from currently available standard sensors (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities). The estimation process is separated into two blocks: the first block contains an observer whose principal role is to calculate tire-road forces without a descriptive force model, while in the second block an observer estimates sideslip angle and Cornering Stiffness with an adaptive tire-force model. The different observers are based on an Extended Kalman Filter (EKF). The estimation process is applied and compared to real experimental data, notably sideslip angle and wheel force measurements. Experimental results show the accuracy and potential of the estimation process.

  • estimation of vehicle sideslip tire force and wheel Cornering Stiffness
    Control Engineering Practice, 2009
    Co-Authors: Guillaume Baffet, Ali Charara, Daniel Lechner
    Abstract:

    Abstract This paper presents a process for the estimation of tire–road forces, vehicle sideslip angle and wheel Cornering Stiffness. The method uses measurements (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities) only from sensors which can be integrated or have already been integrated in modern cars. The estimation process is based on two blocks in series: the first block contains a sliding-mode observer whose principal role is to calculate tire–road forces, while in the second block an extended Kalman filter estimates sideslip angle and Cornering Stiffness. More specifically, this study proposes an adaptive tire-force model that takes variations in road friction into account. The paper also presents a study of convergence for the sliding-mode observer. The estimation process was applied and compared to real experimental data, in particular wheel force measurements. The vehicle mass is assumed to be known. Experimental results show the accuracy and potential of the estimation process.

  • Estimation of vehicle sideslip, tire force and wheel Cornering Stiffness
    Control Engineering Practice, 2009
    Co-Authors: Guillaume Baffet, Daniel Lechner
    Abstract:

    This paper presents a process for the estimation of tire-road forces, vehicle sideslip angle and wheel Cornering Stiffness. The method uses measurements (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities) only from sensors which can be integrated or have already been integrated in modern cars. The estimation process is based on two blocks in series: the first block contains a sliding-mode observer whose principal role is to calculate tire-road forces, while in the second block an extended Kalman filter estimates sideslip angle and Cornering Stiffness. More specifically, this study proposes an adaptive tire-force model that takes variations in road friction into account. The paper also presents a study of convergence for the sliding-mode observer. The estimation process was applied and compared to real experimental data, in particular wheel force measurements. The vehicle mass is assumed to be known. Experimental results show the accuracy and potential of the estimation process. © 2009 Elsevier Ltd. All rights reserved.

  • An estimation process for tire-road forces and sideslip angle for automotive safety systems
    Lecture Notes in Electrical Engineering, 2009
    Co-Authors: Guillaume Baffet, Daniel Lechner, Damien Thomas
    Abstract:

    This study focuses on the estimation of car dynamic variables for the improvement of vehicle safety, handling characteristics and comfort. More specifically, a new estimation process is proposed to estimate longitudinal/lateral tire-road forces, velocity, sideslip angle and wheel Cornering Stiffness. This method uses measurements from currently available standard sensors (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities). The estimation process is separated into two blocks: the first block contains an observer whose principal role is to calculate tire-road forces without a descriptive force model, while in the second block an observer estimates sideslip angle and Cornering Stiffness with an adaptive tire-force model. The different observers are based on an Extended Kalman Filter (EKF). The estimation process is applied and compared to real experimental data, notably sideslip angle and wheel force measurements. Experimental results show the accuracy and potential of the estimation process.

  • Experimental evaluation of observers for tire–road forces, sideslip angle and wheel Cornering Stiffness
    Vehicle System Dynamics, 2008
    Co-Authors: Guillaume Baffet, Daniel Lechner, Ali Charara, Damien Thomas
    Abstract:

    This paper proposes a new estimation process to estimate tire–road forces, sideslip angle and wheel Cornering Stiffness. This method uses measurements from currently–available standard sensors. The estimation process is separated into two blocks: the first block contains an observer whose principal role is to calculate tire–road forces without a descriptive force model, while in the second block an observer estimates sideslip angle and Cornering Stiffness with an adaptive tire-force model. The different observers are based on an Extended Kalman Filter method. Concerning the vehicle model, for observability reasons, the rear longitudinal forces are neglected relative to the front longitudinal forces. The estimation process was applied and compared to real experimental data, notably wheel force measurements. Experimental results show the accuracy and potential of the estimation process, and a limitation in the estimation of the Cornering Stiffness.

Guillaume Baffet - One of the best experts on this subject based on the ideXlab platform.

  • An Estimation Process for Tire-Road Forces and Sideslip Angle for Automotive Safety Systems
    Informatics in Control Automation and Robotics, 2020
    Co-Authors: Guillaume Baffet, Daniel Lechner, Ali Charara, Damien Thomas
    Abstract:

    This study focuses on the estimation of car dynamic variables for the improvement of vehicle safety, handling characteristics and comfort. More specifically, a new estimation process is proposed to estimate longitudinal/lateral tire-road forces, velocity, sideslip angle and wheel Cornering Stiffness. This\break method uses measurements from currently available standard sensors (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities). The estimation process is separated into two blocks: the first block contains an observer whose principal role is to calculate tire-road forces without a descriptive force model, while in the second block an observer estimates sideslip angle and Cornering Stiffness with an adaptive tire-force model. The different observers are based on an Extended Kalman Filter (EKF). The estimation process is applied and compared to real experimental data, notably sideslip angle and wheel force measurements. Experimental results show the accuracy and potential of the estimation process.

  • estimation of vehicle sideslip tire force and wheel Cornering Stiffness
    Control Engineering Practice, 2009
    Co-Authors: Guillaume Baffet, Ali Charara, Daniel Lechner
    Abstract:

    Abstract This paper presents a process for the estimation of tire–road forces, vehicle sideslip angle and wheel Cornering Stiffness. The method uses measurements (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities) only from sensors which can be integrated or have already been integrated in modern cars. The estimation process is based on two blocks in series: the first block contains a sliding-mode observer whose principal role is to calculate tire–road forces, while in the second block an extended Kalman filter estimates sideslip angle and Cornering Stiffness. More specifically, this study proposes an adaptive tire-force model that takes variations in road friction into account. The paper also presents a study of convergence for the sliding-mode observer. The estimation process was applied and compared to real experimental data, in particular wheel force measurements. The vehicle mass is assumed to be known. Experimental results show the accuracy and potential of the estimation process.

  • Estimation of vehicle sideslip, tire force and wheel Cornering Stiffness
    Control Engineering Practice, 2009
    Co-Authors: Guillaume Baffet, Daniel Lechner
    Abstract:

    This paper presents a process for the estimation of tire-road forces, vehicle sideslip angle and wheel Cornering Stiffness. The method uses measurements (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities) only from sensors which can be integrated or have already been integrated in modern cars. The estimation process is based on two blocks in series: the first block contains a sliding-mode observer whose principal role is to calculate tire-road forces, while in the second block an extended Kalman filter estimates sideslip angle and Cornering Stiffness. More specifically, this study proposes an adaptive tire-force model that takes variations in road friction into account. The paper also presents a study of convergence for the sliding-mode observer. The estimation process was applied and compared to real experimental data, in particular wheel force measurements. The vehicle mass is assumed to be known. Experimental results show the accuracy and potential of the estimation process. © 2009 Elsevier Ltd. All rights reserved.

  • An estimation process for tire-road forces and sideslip angle for automotive safety systems
    Lecture Notes in Electrical Engineering, 2009
    Co-Authors: Guillaume Baffet, Daniel Lechner, Damien Thomas
    Abstract:

    This study focuses on the estimation of car dynamic variables for the improvement of vehicle safety, handling characteristics and comfort. More specifically, a new estimation process is proposed to estimate longitudinal/lateral tire-road forces, velocity, sideslip angle and wheel Cornering Stiffness. This method uses measurements from currently available standard sensors (yaw rate, longitudinal/lateral accelerations, steering angle and angular wheel velocities). The estimation process is separated into two blocks: the first block contains an observer whose principal role is to calculate tire-road forces without a descriptive force model, while in the second block an observer estimates sideslip angle and Cornering Stiffness with an adaptive tire-force model. The different observers are based on an Extended Kalman Filter (EKF). The estimation process is applied and compared to real experimental data, notably sideslip angle and wheel force measurements. Experimental results show the accuracy and potential of the estimation process.

  • Experimental evaluation of observers for tire–road forces, sideslip angle and wheel Cornering Stiffness
    Vehicle System Dynamics, 2008
    Co-Authors: Guillaume Baffet, Daniel Lechner, Ali Charara, Damien Thomas
    Abstract:

    This paper proposes a new estimation process to estimate tire–road forces, sideslip angle and wheel Cornering Stiffness. This method uses measurements from currently–available standard sensors. The estimation process is separated into two blocks: the first block contains an observer whose principal role is to calculate tire–road forces without a descriptive force model, while in the second block an observer estimates sideslip angle and Cornering Stiffness with an adaptive tire-force model. The different observers are based on an Extended Kalman Filter method. Concerning the vehicle model, for observability reasons, the rear longitudinal forces are neglected relative to the front longitudinal forces. The estimation process was applied and compared to real experimental data, notably wheel force measurements. Experimental results show the accuracy and potential of the estimation process, and a limitation in the estimation of the Cornering Stiffness.

Junmin Wang - One of the best experts on this subject based on the ideXlab platform.

  • Automatic vehicle trajectory tracking control with self-calibration of nonlinear tire force function
    2017 American Control Conference (ACC), 2017
    Co-Authors: Zitian Yu, Junmin Wang
    Abstract:

    Trajectory tracking capability is important for automatic vehicle guidance. One difficulty for realizing accurate trajectory tracking is the requirement of knowing the tire Cornering Stiffness under linear tire force range or the nonlinear tire force function when tire force becomes large. In this study, the vehicle trajectory tracking problem is firstly formulated in the vehicle's local frame. Then an adaptive control methodology is adopted here to tune the discretized nonlinear Cornering Stiffness function. The method also has the advantage of avoiding the direct usage of vehicle's lateral velocity in generating the steering control signal. In the simulation result part, the performance of the method considering the nonlinear tire force effect is compared with a linear one. Simulation results in CarSim® illustrate that the proposed method considering the nonlinear tire force effect can show improved performance over the method only considers the linear tire force model.

  • ACC - Automatic vehicle trajectory tracking control with self-calibration of nonlinear tire force function
    2017 American Control Conference (ACC), 2017
    Co-Authors: Zitian Yu, Junmin Wang
    Abstract:

    Trajectory tracking capability is important for automatic vehicle guidance. One difficulty for realizing accurate trajectory tracking is the requirement of knowing the tire Cornering Stiffness under linear tire force range or the nonlinear tire force function when tire force becomes large. In this study, the vehicle trajectory tracking problem is firstly formulated in the vehicle's local frame. Then an adaptive control methodology is adopted here to tune the discretized nonlinear Cornering Stiffness function. The method also has the advantage of avoiding the direct usage of vehicle's lateral velocity in generating the steering control signal. In the simulation result part, the performance of the method considering the nonlinear tire force effect is compared with a linear one. Simulation results in CarSim® illustrate that the proposed method considering the nonlinear tire force effect can show improved performance over the method only considers the linear tire force model.

  • Tire–road friction coefficient and tire Cornering Stiffness estimation based on longitudinal tire force difference generation
    Control Engineering Practice, 2012
    Co-Authors: Rongrong Wang, Junmin Wang
    Abstract:

    Abstract A sequential tire Cornering Stiffness coefficient and tire–road friction coefficient (TRFC) estimation method is proposed for some advanced vehicle architectures, such as the four-wheel independently-actuated (FWIA) electric vehicles, where longitudinal tire force difference between the left and right sides of the vehicle can be easily generated. Such a tire force difference can affect the vehicle yaw motion, and can be utilized to estimate the tire Cornering Stiffness coefficient and TRFC. The proposed tire Cornering Stiffness coefficient and TRFC identification method has the potential of estimating these parameters without affecting the vehicle desired motion control and trajectory tracking objectives. Simulation and experimental results with a FWIA electric vehicle show the effectiveness of the proposed estimation method.

  • Tyre-road friction coefficient and tyre Cornering Stiffness estimation based on longitudinal tyre force difference generation
    Control Engineering Practice, 2012
    Co-Authors: Rongrong Wang, Junmin Wang
    Abstract:

    A sequential tire Cornering Stiffness coefficient and tire–road friction coefficient (TRFC) estimation method is proposed for some advanced vehicle architectures, such as the four-wheel independently-actuated (FWIA) electric vehicles, where longitudinal tire force difference between the left and right sides of the vehicle can be easily generated. Such a tire force difference can affect the vehicle yaw motion, and can be utilized to estimate the tire Cornering Stiffness coefficient and TRFC. The proposed tire Cornering Stiffness coefficient and TRFC identification method has the potential of estimating these parameters without affecting the vehicle desired motion control and trajectory tracking objectives. Simulation and experimental results with a FWIA electric vehicle show the effectiveness of the proposed estimation method.

Christian J. Gerdes - One of the best experts on this subject based on the ideXlab platform.

  • Experimental Vehicle Handling Modification through Steer-by-Wire and Differential Drive
    2007 American Control Conference, 2007
    Co-Authors: Jared W. Brown, R. K. Maclean, Shad Laws, Chris Gadda, Christian J. Gerdes
    Abstract:

    This paper investigates the possibility of controlling a vehicle equipped with steer-by-wire and differential drive to emulate the handling characteristics of another vehicle. Using linear bicycle models of the steer-by-wire testbed and the emulated vehicle, the controller determines the steering angle and differential drive moment based on the yaw rate and sideslip angle. Through simulations and experimental tests, the capability of differential drive and steer-by-wire to modify the handling of a vehicle is explored, and limiting factors such as tire friction and specific vehicle parameters are identified. Changes to vehicle parameters such as the front tire Cornering Stiffness can be effected easily, while changes to rear tire Cornering Stiffness and weight distribution are more difficult to emulate. Since the differential moment advances tire saturation in the rear, the ability to emulate cars with radically different rear tires or weight distribution is limited.

  • Integrating INS Sensors With GPS Measurements for Continuous Estimation of Vehicle Sideslip, Roll, and Tire Cornering Stiffness
    IEEE Transactions on Intelligent Transportation Systems, 2006
    Co-Authors: D.m. Bevly, Christian J. Gerdes
    Abstract:

    This paper details a unique method for estimating key vehicle states-body sideslip angle, tire sideslip angle, and vehicle attitude-using Global Positioning System (GPS) measurements in conjunction with other sensors. A method is presented for integrating Inertial Navigation System sensors with GPS measurements to provide higher update rate estimates of the vehicle states. The influence of road side-slope and vehicle roll on estimating vehicle sideslip is investigated. A method using one GPS antenna that estimates accelerometer errors occurring from vehicle roll and sensor drift is first developed. A second method is then presented utilizing a two-antenna GPS system to provide direct measurements of vehicle roll and heading, resulting in improved sideslip estimation. Additionally, it is shown that the tire sideslip estimates can be used to estimate the tire Cornering Stiffnesses. The experimental results for the GPS-based sideslip angle measurement and Cornering Stiffness estimates compare favorably to theoretical predictions, suggesting that this technique has merit for future implementation in vehicle safety systems

D.m. Bevly - One of the best experts on this subject based on the ideXlab platform.

  • Integrating INS Sensors With GPS Measurements for Continuous Estimation of Vehicle Sideslip, Roll, and Tire Cornering Stiffness
    IEEE Transactions on Intelligent Transportation Systems, 2006
    Co-Authors: D.m. Bevly, Christian J. Gerdes
    Abstract:

    This paper details a unique method for estimating key vehicle states-body sideslip angle, tire sideslip angle, and vehicle attitude-using Global Positioning System (GPS) measurements in conjunction with other sensors. A method is presented for integrating Inertial Navigation System sensors with GPS measurements to provide higher update rate estimates of the vehicle states. The influence of road side-slope and vehicle roll on estimating vehicle sideslip is investigated. A method using one GPS antenna that estimates accelerometer errors occurring from vehicle roll and sensor drift is first developed. A second method is then presented utilizing a two-antenna GPS system to provide direct measurements of vehicle roll and heading, resulting in improved sideslip estimation. Additionally, it is shown that the tire sideslip estimates can be used to estimate the tire Cornering Stiffnesses. The experimental results for the GPS-based sideslip angle measurement and Cornering Stiffness estimates compare favorably to theoretical predictions, suggesting that this technique has merit for future implementation in vehicle safety systems

  • Estimation of tire Cornering Stiffness using GPS to improve model based estimation of vehicle states
    IEEE Proceedings. Intelligent Vehicles Symposium 2005., 2005
    Co-Authors: R. Anderson, D.m. Bevly
    Abstract:

    This paper demonstrates a method of obtaining key vehicle states using GPS and INS measurements with an adaptive model based estimator. A dual antenna GPS attitude system is used to estimate tire Cornering Stiffness. This estimated parameter is updated in the estimator model to provide more accurate estimates of the vehicle states. The experimental results for the estimate of sideslip and yaw rate using the updated estimator model compare favorable to values predicted by the theoretical model.

  • Integrating INS sensors with GPS velocity measurements for continuous estimation of vehicle sideslip and tire Cornering Stiffness
    Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148), 2001
    Co-Authors: D.m. Bevly, R. Sheridan, J.c. Gerdes
    Abstract:

    This paper details a unique method for measuring key vehicle states-body sideslip angle, and tire sideslip angle-using GPS velocity information in conjunction with other sensors. A method for integrating inertial navigation system (INS) sensors with GPS measurements to provide higher update rate estimates of the vehicle states is presented. Additionally, it is shown that the tire sideslip estimates can be used to estimate the tire Cornering Stiffnesses. The experimental results for the GPS velocity-based sideslip angle measurement and Cornering Stiffness estimates compare favorably to theoretical predictions, suggesting that this technique has merit for future implementation in vehicle safety systems.