Tire-road forces estimation using extended Kalman filter and sideslip angle evaluation

Dakhlallah, Jamil; Glaser, Sébastien; Mammar, Saïd; Sebsadji, Yazid

doi:10.1109/acc.2008.4587220

Cited by 99 publications

(59 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The FWVM is widely used to describe transversal vehicle dynamic behavior [3], [4], [6]. In this study, we adopt the following simplified assumptions:…”

Section: Vehicle-road Model a Four-wheel Vehicle Modelmentioning

confidence: 99%

See 1 more Smart Citation

Estimation of vehicle lateral tire-road forces: A comparison between extended and unscented Kalman filtering

Doumiati

Victorino²,

Charara³

et al. 2009

2009 European Control Conference (ECC)

View full text Add to dashboard Cite

Abstract-Extensive research has shown that most of road accidents occur as a result of driver errors. A close examination of accident data reveals that losing the vehicle control is responsible for a huge proportion of car accidents. Preventing such kind of accidents using vehicle control systems, requires certain input data concerning vehicle dynamic parameters and vehicle road interaction. Unfortunately, some parameters like tire-road forces and sideslip angle, which have a major impact on vehicle dynamics, are difficult to measure in a car. Therefore, this data must be estimated. Due to the system nonlinearities and unmodeled dynamics, two observers derived from extended and unscented Kalman filtering techniques are proposed and compared. The estimation process method is based on the dynamic response of a vehicle instrumented with cheap, easily-available standard sensors. Performances are tested and compared to real experimental data acquired using the INRETS-MA Laboratory car. Experimental results demonstrate the ability of this approach to provide accurate estimations, and show its practical potential as a low-cost solution for calculating lateral-tire forces and sideslip angle.

show abstract

“…The FWVM is widely used to describe transversal vehicle dynamic behavior [3], [4], [6]. In this study, we adopt the following simplified assumptions:…”

Section: Vehicle-road Model a Four-wheel Vehicle Modelmentioning

confidence: 99%

“…Several studies have been conducted regarding the estimation of tire-road forces and sideslip angle [2]- [9]. For example, in [2] and [3], the authors estimate the vehicle dynamic state for a four-wheel vehicle model. Consequently, tire forces are calculated based on the estimated states and using tire models.…”

Section: Introductionmentioning

confidence: 99%

Estimation of vehicle lateral tire-road forces: A comparison between extended and unscented Kalman filtering

Doumiati

Victorino²,

Charara³

et al. 2009

2009 European Control Conference (ECC)

View full text Add to dashboard Cite

show abstract

“…Likewise, directly measuring tire slips also requires expensive sensors such as speed over ground sensor as mentioned in [1], [2]. Therefore, many researches have been proposed to reduce the cost.…”

Section: Introductionmentioning

confidence: 99%

“…Section 3 presents the settings that are made to represent actual slip behaviors and this data is partially reflected by the actual test data from [1], [6], in which the sideslip angle is behaving approximately same as yaw rate. Section 4 discusses the system and measurement equations and states the noise for each system and measurement, and the slip parameters which are being estimated.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of EKF and UKF for Estimating Tire Longitudinal and Side Angle Slip

Song

Ahn²,

Kim³

et al. 2016

MATEC Web Conf.

View full text Add to dashboard Cite

Abstract. Accurate tire slip estimation might be regarded as a small portion of the vehicle safety but is important criterion. Furthermore, as an autonomous vehicle system gets sophisticated, this type of technique will be more necessary. In this paper performance analysis for slip estimation in various situations is presented with several commonly known filter-extended Kalman filter (EKF) and unscented Kalman filter (UKF). Tire slip behaves differently depending on the surface type, the motion of the robot, and other environmental factors. Therefore, different kinds of situations and conditions are considered to estimate more accurate tire slip. Also as far as the tire slip is not based on actual data, it will be assumed to imitate the real tire slip behavior based on other study data. Finally, the performances of two filtering algorithms are compared to find more adequate algorithm with respect to the given condition for the future experimental results.

show abstract

“…Ray [10] developed the EKF method based on a 8 degrees of freedom (DOFs) vehicle dynamics model. Dakhlallah et al [11] proposed an EKF estimation method based on a simpler vehicle dynamics model, which only considers vehicle longitudinal dynamics, lateral dynamics and yaw dynamics.…”

Section: Introductionmentioning

confidence: 99%

A novel cost effective method for vehicle tire-road friction coefficient estimation

2013

2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

View full text Add to dashboard Cite

The tire-road friction coefficient is critical to vehicle longitudinal, lateral and roll dynamics and control because tire is the only contact part between the vehicle body and the road. However, direct measurement of tire-road friction coefficient is impossible in practice. This paper presents a novel cost effective method for vehicle tire-road friction coefficient estimation. This method only needs the measurements of the wheel angular velocity, the traction/brake torque and the longitudinal acceleration, which are all available from the commonly installed sensors in ordinary passenger vehicles, and can be used to estimate the individual tireroad friction coefficient. There are three steps in the proposed method. Firstly, the longitudinal slip ratio is estimated by using a nonlinear filter with the measured wheel angular velocity. Then the tire longitudinal force is estimated by using a Kalman filter with the measured traction/brake torque and longitudinal acceleration. At last, the friction coefficient is estimated by using the recursive least squares (RLS) method and the results obtained from the first two steps. Numerical simulations are provided to validate the effectiveness of the proposed method. It is shown by the simulation results that the proposed method is effective in estimating the tire-road friction coefficient. Abstract-The tire-road friction coefficient is critical to vehicle longitudinal, lateral and roll dynamics and control because tire is the only contact part between the vehicle body and the road. However, direct measurement of tire-road friction coefficient is impossible in practice. This paper presents a novel cost effective method for vehicle tire-road friction coefficient estimation. This method only needs the measurements of the wheel angular velocity, the traction/brake torque and the longitudinal acceleration, which are all available from the commonly installed sensors in ordinary passenger vehicles, and can be used to estimate the individual tire-road friction coefficient. There are three steps in the proposed method. Firstly, the longitudinal slip ratio is estimated by using a nonlinear filter with the measured wheel angular velocity. Then the tire longitudinal force is estimated by using a Kalman filter with the measured traction/brake torque and longitudinal acceleration. At last, the friction coefficient is estimated by using the recursive least squares (RLS) method and the results obtained from the first two steps. Numerical simulations are provided to validate the effectiveness of the proposed method. It is shown by the simulation results that the proposed method is effective in estimating the tire-road friction coefficient.

show abstract

Tire-road forces estimation using extended Kalman filter and sideslip angle evaluation

Cited by 99 publications

References 6 publications

Estimation of vehicle lateral tire-road forces: A comparison between extended and unscented Kalman filtering

Estimation of vehicle lateral tire-road forces: A comparison between extended and unscented Kalman filtering

Performance Analysis of EKF and UKF for Estimating Tire Longitudinal and Side Angle Slip

A novel cost effective method for vehicle tire-road friction coefficient estimation

Contact Info

Product

Resources

About