Vehicle Dynamics Virtual Sensing Using Unscented Kalman Filter: Simulations and Experiments in a Driver-in-the-loop setup

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

Chassis Active Safety Systems require access to a set of vehicle dynamics motion states which measurement is neither trivial nor cost-effective (e.g. lateral velocity). In this work, virtual sensing is applied to vehicle dynamics and proposed as a cost-effective solution to infer the vehicle planar motion states and three-axis tyre forces from signals measured by inexpensive sensors. Specifically, the tyre longitudinal forces are estimated using Adaptive Random-Walk Linear Kalman Filters and the vehicle planar motion states are determined in a hybrid state estimator formed by an Unscented Kalman Filter and Feedforward Neural Networks. The tyre vertical forces are estimated using a quasi-static weight transfer approach and Recursive Least Squares. The complete structure is integrated into a modular fashion and tested experimentally using a driver-in-the-loop setup. An extensive catalogue of manoeuvres is executed by a real driver to evidence the performance of the proposed virtual sensor at the limits of handling.
Original languageEnglish
Title of host publicationInformatics in Control, Automation and Robotics
Subtitle of host publication14th International Conference, ICINCO 2017 Madrid, Spain, July 26-28, 2017 Revised Selected Papers
PublisherSpringer Verlag
Pages582-602
Number of pages21
ISBN (Electronic)978-3-030-11292-9
ISBN (Print)978-3-030-11291-2
DOIs
Publication statusE-pub ahead of print - 18 Apr 2019
Event14th International Conference on Informatics in Control, Automation and Robotics - Madrid, Spain
Duration: 26 Jul 201728 Jul 2017
http://www.ieee-ras.org/component/rseventspro/event/1040-icinco-2017-international-conference-on-informatics-in-control-automation-and-robotics

Publication series

NameLecture Notes in Electrical Engineering
Volume495
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference14th International Conference on Informatics in Control, Automation and Robotics
Abbreviated titleICINCO 2017
CountrySpain
CityMadrid
Period26/07/1728/07/17
Internet address

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  • Cite this

    Acosta, M., Kanarachos, S., & Fitzpatrick, M. (2019). Vehicle Dynamics Virtual Sensing Using Unscented Kalman Filter: Simulations and Experiments in a Driver-in-the-loop setup. In Informatics in Control, Automation and Robotics: 14th International Conference, ICINCO 2017 Madrid, Spain, July 26-28, 2017 Revised Selected Papers (pp. 582-602). (Lecture Notes in Electrical Engineering; Vol. 495). Springer Verlag. https://doi.org/10.1007/978-3-030-11292-9