Vehicle sideslip estimation: A kinematic based approach

Selmanaj, Donald; Corno, Matteo; Panzani, Giulio; Savaresi, Sergio M.

doi:10.1016/j.conengprac.2017.06.013

Cited by 118 publications

(57 citation statements)

References 37 publications

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“…where and are constant parameters and is the tyreroad friction coefficient. Taking into account the standard linearised congruence equations [14]:…”

Section: Vehicle Modelmentioning

confidence: 99%

“…That is computed as a function of the measured four wheel speeds. Specifically, such values are corrected, as suggested by [14]:…”

Section: Filter With Rational Tyre Model and Tyre Parameter Estimamentioning

confidence: 99%

“…In some cases tyre force sensors are used to facilitate the estimation process [12], but that approach is not cost-effective for passenger cars and often tyre forces need to be estimated, too [13]. Some other studies propose kinematics-based techniques that do not need a tyre model [14][15]. More recent studies investigate the option of particle filters, which normally are rather demanding in terms of computational capability but can provide very good performance [16][17].…”

Section: Introductionmentioning

confidence: 99%

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Vehicle Sideslip Angle Estimation for a Heavy-Duty Vehicle via Extended Kalman Filter Using a Rational Tyre Model

2020

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Vehicle sideslip angle is a key state for lateral vehicle dynamics, but measuring it is expensive and unpractical. Still, knowledge of this state would be really valuable for vehicle safety systems aimed at enhancing vehicle safety, to help to reduce worldwide fatal car accidents. This has motivated the research community to investigate techniques to estimate vehicle sideslip angle, which is still a challenging problem. One of the major issues is the need for accurate tyre model parameters, which are difficult to characterise and subject to change during vehicle operation. This paper proposes a new method for estimating vehicle sideslip angle using an Extended Kalman Filter. The main novelties are: i) the tyre behaviour is described using a Rational tyre model whose parameters are estimated and updated online to account for their variation due to e.g. tyre wear and environmental conditions affecting the tyre behaviour; ii) the proposed technique is compared with two other methods available in the literature by means of experimental tests on a heavy-duty vehicle. Results show that: i) the proposed method effectively estimates vehicle sideslip angle with an error limited to 0.5 deg in standard driving conditions, and less than 1 deg for a high-speed run; ii) the tyre parameters are successfully updated online, contributing to outclassing estimation methods based on tyre models that are either excessively simple or with non-varying parameters. INDEX TERMS Kalman filter; sideslip angle; state estimation; Rational tyre model; vehicle dynamics. List of symbols Symbol Unit Quantity various Dynamic matrix m Vehicle semi-wheelbase m/s 2 Lateral acceleration various Matrix used to work out various Matrix used to work out N/rad Front cornering stiffness N/rad Rear cornering stiffness various Control input vector rad 2 Rational tyre model parameter N/rad Rational tyre model parameter

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“…where and are constant parameters and is the tyreroad friction coefficient. Taking into account the standard linearised congruence equations [14]:…”

Section: Vehicle Modelmentioning

confidence: 99%

“…That is computed as a function of the measured four wheel speeds. Specifically, such values are corrected, as suggested by [14]:…”

Section: Filter With Rational Tyre Model and Tyre Parameter Estimamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Vehicle Sideslip Angle Estimation for a Heavy-Duty Vehicle via Extended Kalman Filter Using a Rational Tyre Model

2020

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“… longitudinal velocity , which is calculated as an average of the longitudinal component of each wheel center velocity, as described in [17];  the yaw rate , which is provided by the gyro sensor.…”

Section: Kalman Filter Theory and Implementationmentioning

confidence: 99%

“…In particular, observers have been proposed which are based either on kinematic models or on dynamic models [4]. Selmanaj et al [17] present a kinematic-based model that uses a special parameter to define the mean longitudinal vehicle velocity. Chen et al [3] also propose a kinematic model, along with an adaptive procedure to update the process noise covariance matrix at each time step.…”

Section: Introductionmentioning

confidence: 99%

Advances in Italian Mechanism Science

2019

Mechanisms and Machine Science

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The knowledge of the vehicle sideslip angle provides useful information about the state of the vehicle and it is often considered to increase the performance of the car as well as to develop safety systems, especially in the vehicle equipped with Torque Vectoring control systems. This paper describes two methods, based on the use of Kalman filters, to estimate the vehicle sideslip angle and the tire forces of a vehicle starting from the longitudinal and yaw velocity data. In particular, these data refer to on-track testing of a Range Rover Evoque performing ramp steer maneuvers at constant speed. The results of the sideslip estimation method are compared with the actual vehicle sideslip measured by a Datron sensor and are also used to estimate the tire lateral forces.

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Observer‐based path following control for autonomous vehicles with localization errors and tire slip effects

Wang

Zhang

Quan

et al. 2022

Asian Journal of Control

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This paper investigates the problem of path following control for an autonomous vehicle subject to the localization errors and the tire slip effects. First, by analyzing the effects of localization errors, a loss‐of‐effectiveness actuator model is formulated, and a new chain form model is constructed for path following system of the vehicle. Then, the polytopic model is proposed to characterize the nonlinearity of the system, and an observer‐based path following controller is designed by satisfying both the H∞$$ {H}_{\infty } $$ criterion and L1$$ {L}_1 $$ criterion. Finally, the path following controller design problem is converted into an optimization problem, which can be solved readily through convex optimization techniques. The effectiveness of the proposed control strategy is verified by simulation results.

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Vehicle sideslip estimation: A kinematic based approach

Cited by 118 publications

References 37 publications

Vehicle Sideslip Angle Estimation for a Heavy-Duty Vehicle via Extended Kalman Filter Using a Rational Tyre Model

Vehicle Sideslip Angle Estimation for a Heavy-Duty Vehicle via Extended Kalman Filter Using a Rational Tyre Model

Advances in Italian Mechanism Science

Observer‐based path following control for autonomous vehicles with localization errors and tire slip effects

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