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Abstract:In this paper, a review on road friction virtual sensing approaches is provided. In particular, this work attempts to address whether the road grip potential can be estimated accurately under regular driving conditions in which the vehicle responses remain within low longitudinal and lateral excitation levels. This review covers in detail the most relevant effect-based estimation methods; these are methods in which the road friction characteristics are inferred from the tyre responses: tyre slip, tyre vibration, and tyre noise. Slip-based approaches (longitudinal dynamics, lateral dynamics, and tyre self-alignment moment) are covered in the first part of the review, while low frequency and high frequency vibration-based works are presented in the following sections. Finally, a brief summary containing the main advantages and drawbacks derived from each estimation method and the future envisaged research lines are presented in the last sections of the paper.

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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This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

This paper demonstrates the use of an extended Kalman filter (KF) as a virtual sensor for non-measurable vehicle states and unknown vehicle parameters. The purpose of obtaining these values is to make them available within the control algorithms of the various automotive stability systems. Based on an extensive four-wheel vehicle model, an estimator is implemented on data from a test vehicle. Using available reference data, the suitability of the extended KF technique as a virtual sensor is demonstrated.