An Observer of Tire–Road Forces and Friction for Active Security Vehicle Systems

Baffet, Guillaume; Charara, Ali; Dherbomez, Gérald

doi:10.1109/tmech.2007.910099

Cited by 89 publications

(60 citation statements)

References 15 publications

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“…En (Baffet et al, 2007) se estima la CDS utilizando un modelo no lineal de neumático y un filtro extendido de Kalman (EKF). Los filtros de Kalman normalmente funcionan bien si se dispone de un buen modelo del sistema, pero considerando que el EKF utiliza un modelo linealizado para realizar la propagación del error, su desempeño podría verse afectado al alejarse del punto de linealización.…”

Section: Observador De La Máxima Fuerza Transmisibleunclassified

“…Además, la implementación de un EKF requiere el cálculo de una matriz inversa en tiempo real, lo cual lleva a un alto costo computacional. Porúltimo, el tiempo de estimación de la CDS presentada en (Baffet et al, 2007) es superior a la obtenida con el observador propuesto en el presente trabajo. Changsun et al (2013) proponen usar un observador no lineal para la estimación de la CDS utilizando un modelo de vehículo lateral, con el propósito de utilizarse para control de estabilidad (en maniobras de giro).…”

Section: Observador De La Máxima Fuerza Transmisibleunclassified

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Control de Tracción para un Vehículo Eléctrico basado en Observadores no Lineales

Aligia

Magallán

Angelo

2017

Rev. iberoam. autom. inform. ind.

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ResumenEn este trabajo se propone una estrategia de control de tracción para un vehículo eléctrico de cuatro ruedas, basada en observadores no lineales que permiten estimar la fuerza máxima que se puede transferir al suelo. El conocimiento de la fuerza máxima permite realizar un control del deslizamiento de los neumáticos de tracción, evitando que las ruedas patinen aún en superficies de baja adherencia. La estrategia propuesta permite además evitar que se produzca un momento de guiño no deseado en el vehículo cuando las condiciones de suelo a cada lado del mismo son diferentes. Con ello se logra mejorar la eficiencia y el control del vehículo, evitando posibles pérdidas de estabilidad que pueden resultar en riesgos para sus ocupantes. Tanto el observador como el control propuestos son diseñados en base a un modelo dinámico rotacional de la rueda y un modelo de fuerzas de brush. Se presentan resultados de simulación obtenidos empleando un modelo completo de vehículo sobre la plataforma Simulink/CarSim. Palabras Clave:Control de tracción, Condición de suelo, Coeficiente de rozamiento, Modelo de neumático brush, Linealización exacta por realimentación, Observador no lineal de Luenberger Traction control of an electric vehicle based on nonlinear observers Abstract A traction control strategy for a four-wheel electric vehicle is proposed in this paper. The strategy is based on nonlinear observers which allows estimating the maximum force that can be transmitted to the road. Knowledge of the maximum force allows controlling the slip of the driving wheels, preventing the wheel's slippage in low-grip surfaces. The proposed strategy also allows to avoid the undesired yaw moment in the vehicle which occurs when road conditions on either side of it are different. This improves the efficiency and the control of the vehicle, avoiding possible losses of stability that can result in risks for its occupants. Both the proposed observer and the control strategy are designed based on a dynamic rotational model of the wheel and a brush force model. Simulation results are obtained based on a complete vehicle model on the Simulink/CarSim platform.

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Section: Observador De La Máxima Fuerza Transmisibleunclassified

Control de Tracción para un Vehículo Eléctrico basado en Observadores no Lineales

Aligia

Magallán

Angelo

2017

Rev. iberoam. autom. inform. ind.

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“…Linear, Kalman, or nonlinear observers are used in such kinematic-based methods [1], [5], [6] without using a tire model. Kinematic-based estimation structure uses transformed kinematic equations at each corner with the following dynamics:…”

Section: A Kinematic-based Velocity Estimationmentioning

confidence: 99%

“…Furthermore, stabilizability of the pair [A k , G k ] leads to 6 exponential stability of the KF, where G k is an appropriate matrix obtained by…”

Section: Stability Of the Estimatormentioning

confidence: 99%

“…A Kalman observer is employed by Hsu and Bevly et al in [5], utilizing the same kinematic-based method and correction with GPS data, but the poor accuracy of the mostly practiced conventional GPSs and the loss of reception are primary concerns. The issue of reliance on a GPS is addressed with observer development around tire capacities and using the wheel speed, as investigated by G. Baffet and A. Charara [6], but this approach is incapable of predicting the lateral limit before it occurs. This drawback is eliminated in [7] by implementing a steer-by-wire system to determine the road Ehsan Hashemi, Saeid Khosravani, and Amir Khajepour are with the Department of Mechanical and Mechatronics Engineering, University of Waterloo, ON, Canada.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of longitudinal speed robust to road conditions for ground vehicles

Hashemi

Kasaiezadeh

Khosravani

et al. 2016

Vehicle System Dynamics

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Abstract-This article seeks to develop a longitudinal vehicle velocity estimator robust to road conditions by employing a tire model at each corner. Combining the lumped LuGre tire model and the vehicle kinematics, the tires internal deflection state is used to gain an accurate estimation. Conventional kinematicbased velocity estimators use acceleration measurements, without correction with the tire forces. However, this results in inaccurate velocity estimation because of sensor uncertainties which should be handled with another measurement such as tire forces that depend on unknown road friction. The new Kalman-based observer in this paper addresses this issue by considering tire nonlinearities with a minimum number of required tire parameters and the road condition as uncertainty. Longitudinal forces obtained by the unscented Kalman filter on the wheel dynamics is employed as an observation for the Kalman-based velocity estimator at each corner. The stability of the proposed time-varying estimator is investigated and its performance is examined experimentally in several tests and on different road surface frictions. Road experiments and simulation results show the accuracy and robustness of the proposed approach in estimating longitudinal speed for ground vehicles.

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Bibliography

2012

Vehicle Dynamics Estimation Using Kalman Filtering

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An Observer of Tire–Road Forces and Friction for Active Security Vehicle Systems

Cited by 89 publications

References 15 publications

Control de Tracción para un Vehículo Eléctrico basado en Observadores no Lineales

Control de Tracción para un Vehículo Eléctrico basado en Observadores no Lineales

Estimation of longitudinal speed robust to road conditions for ground vehicles

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