Enhancement of ABS Performance through On-Board Estimation of the Tires' Response by Means of Smart Tires

Cheli, Federico; Sabbioni, Edoardo; Sbrosi, Marco; Brusarosco, Massimo; Melzi, Stefano; d’Alessandro, V.

doi:10.4271/2011-01-0991

Cited by 18 publications

(8 citation statements)

References 11 publications

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“…Examples of vehicle control systems that can benefit from the knowledge of tire-road friction include anti-lock braking systems (ABS), electronic stability control (ESC), adaptive cruise control (ACC), and collision warning or collision avoidance systems (Braghin et al, 2009;Cheli, Leo, Melzi, & Sabbioni, 2010;Cheli et al, 2011aCheli et al, , 2011bErdogan, Hong, Borrelli, & Hedrick, * Corresponding author. Email: kbsingh@vt.edu 2011; Sabbioni, Kakalis, & Cheli, 2010;Singh, Arat, & Taheri, 2012.…”

Section: Introductionmentioning

confidence: 98%

Estimation of tire–road friction coefficient and its application in chassis control systems

Singh

Taheri

2014

Systems Science & Control Engineering

117

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Knowledge of tire-road friction conditions is indispensable for many vehicle control systems. In particular, friction information can be used to enhance the performance of wheel slip control systems, for example, knowledge of the current maximum coefficient of friction would allow an anti-lock brake system (ABS) controller to start braking with the optimal brake pressure, meaning the early cycles of operation are more efficient, resulting in shorter stopping distances. Also, from a passive safety perspective, it may be useful to present the driver with friction information so they can adjust their driving style to the road conditions. Hence, it is highly desirable to estimate friction using existing onboard vehicle sensor information. Many approaches for estimating tire-road friction estimation have been proposed in the literature with different sensor requirements and relative excitation levels. This paper aims at estimating the tire-road friction coefficient by using a well-defined model of the tire behavior. The model adopted for this purpose is the physically based brush tire model. In its simplest formulation, the brush model describes the relationship between the tire force and the slip as a function of two parameters, namely, tire stiffness and the tire-road friction coefficient. Knowledge of the shape of the force-slip characteristics of the tire, possibly obtained through the estimation of both friction and tire stiffness using the brush model, provides information about the slip values at which maximum friction is obtained. This information could be used to generate a target slip set point value for controllers, such as an ABS or a traction control system. It is also important to realize that a model-based approach is inherently limited to providing road surface friction information when the tire is exposed to an excitation with high utilization levels (i.e. under high-slip conditions). To be of greatest use to active safety control systems, an estimation method needs to offer earlier knowledge of the limits. In order to achieve the aforementioned objective, an integrated approach using an intelligent tire-based friction estimator and the brush tire model-based estimator is presented. An integrated approach gives us the capability to reliably estimate friction for a wider range of excitations (both low-slip and high-slip conditions).

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Section: Introductionmentioning

confidence: 98%

Estimation of tire–road friction coefficient and its application in chassis control systems

Singh

Taheri

2014

Systems Science & Control Engineering

117

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“…According to Matsuzaki and Todoroki, 78 the increased research interest in intelligent tyres is attributed to Bridgestone/Firestone in 2000. Since then, different solutions to measure the tyre forces have been proposed in the literature using strain gauges, 78,79 microelectromechanical system (MEMS) accelerometers, 11,12,41,42,80–82 optical sensors 4 or surface acoustic wave ( SAW ) sensors. 83 In other cases, the entire tyre structure has been treated as a measuring device.…”

Section: Direct Tyre Force Measurement Approachesmentioning

confidence: 99%

“…WFT are still too costly to be mounted in production vehicles 10 and their use is reduced to testing activities during vehicle development stages. 9 The smart tyre technology is still under development 11,12 and current results indicate that further investigations are required before this technology can be implemented in regular tyres. Finally, although SKF® or NSK® have developed different designs of LSB , these are still not commercially available.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Virtual tyre force sensors: An overview of tyre model-based and tyre model-less state estimation techniques

Acosta

Kanarachos

Blundell

2017

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper presents a comprehensive literature review on tyre force estimation and road grip recognition approaches. With the development of modern automotive control systems, a precise estimation of a large number of vehicle states is necessary to guarantee a robust actuation of the controller. Moreover, the estimation of these states must be carried out in a cost-effective and reliable way. The aim of this work is to provide a solid base for the development of automotive virtual sensors, and in particular, virtual tyre force sensors. An initial overview of the tyre force estimation problem is provided in the first section. Tyre and vehicle modelling, as well as observers for vehicle state estimation, are covered in detail in the second section. The third section introduces a brief discussion regarding the main limitations of direct tyre force measurement approaches. In the following sections, relevant works regarding three-axis tyre force estimation and road grip recognition are discussed. The review is structured around longitudinal force estimation, lateral force estimation, combined tyre force estimation, tyre self-alignment torque estimation and vertical tyre force estimation. Within each section, the most significant road grip identification approaches are introduced. An additional section, Road slope and bank angle compensation, describes relevant work on estimation methods for global chassis orientation. A brief summary of the presented approaches is provided in the section Summary of presented approaches. Finally, relevant conclusions and further research steps are given in the last section.

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“…In the last twenty years, research has moved towards a different approach [1,2,3,4,5,6,7,8,9,10,11,12], which is based on using newly conceived sensors [9,10] to pursue the measurement of some key variables involving the tire-road contact interface [13,14,15,16], such as pressure, temperature, contact-patch dimensions, or even better wheel load [17], acceleration, friction factor [18,19,20] or deformation [21,22]. These new hardware and related algorithms are capable of measuring new quantities and extract additional information with potential use for the enhancement of the performance of the vehicle control systems, also putting the basis for breakthrough in new control devices.…”

Section: Introduction and State Of The Art Of “Smart Tires”mentioning

confidence: 99%

A Multisensing Setup for the Intelligent Tire Monitoring

Coppo

Pepe

Roveri

et al. 2017

Sensors

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The present paper offers the chance to experimentally measure, for the first time, the internal tire strain by optical fiber sensors during the tire rolling in real operating conditions. The phenomena that take place during the tire rolling are in fact far from being completely understood. Despite several models available in the technical literature, there is not a correspondently large set of experimental observations. The paper includes the detailed description of the new multi-sensing technology for an ongoing vehicle measurement, which the research group has developed in the context of the project OPTYRE. The experimental apparatus is mainly based on the use of optical fibers with embedded Fiber Bragg Gratings sensors for the acquisition of the circumferential tire strain. Other sensors are also installed on the tire, such as a phonic wheel, a uniaxial accelerometer, and a dynamic temperature sensor. The acquired information is used as input variables in dedicated algorithms that allow the identification of key parameters, such as the dynamic contact patch, instantaneous dissipation and instantaneous grip. The OPTYRE project brings a contribution into the field of experimental grip monitoring of wheeled vehicles, with implications both on passive and active safety characteristics of cars and motorbikes.

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Enhancement of ABS Performance through On-Board Estimation of the Tires' Response by Means of Smart Tires

Cited by 18 publications

References 11 publications

Estimation of tire–road friction coefficient and its application in chassis control systems

Estimation of tire–road friction coefficient and its application in chassis control systems

Virtual tyre force sensors: An overview of tyre model-based and tyre model-less state estimation techniques

A Multisensing Setup for the Intelligent Tire Monitoring

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