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dc.contributor.authorJalali, Kiumars
dc.contributor.authorUchida, Thomas
dc.contributor.authorMcPhee, John
dc.contributor.authorLambert, Steve 18:53:06 (GMT) 18:53:06 (GMT)
dc.descriptionReplicated with permission by SAE Copyright © 2017 SAE International. Further distribution of this material is not permitted without prior permission from SAE.en
dc.description.abstractA two-passenger, all-wheel-drive urban electric vehicle (AUTO21EV) with four direct-drive in-wheel motors has been designed and developed at the University of Waterloo. An advanced genetic-fuzzy active steering controller is developed based on this vehicle platform. The rule base of the fuzzy controller is developed from expert knowledge, and a multi-criteria genetic algorithm is used to optimize the parameters of the fuzzy active steering controller. To evaluate the performance of this controller, a computational model of the AUTO21EV is driven through several standard test maneuvers using an advanced path-following driver model. As the final step in the evaluation process, the genetic-fuzzy active steering controller is implemented in a hardware- and operator-in-the-loop driving simulator to confirm its performance and effectiveness.en
dc.description.sponsorshipFunding for this work was provided by the Natural Sciences and Engineering Research Council of Canada and agrant from AUTO21, a Canadian Network of Centres of Excellenceen
dc.publisherSAE Internationalen
dc.titleDevelopment of an Advanced Fuzzy Active Steering Controller and a Novel Method to Tune the Fuzzy Controlleren
dcterms.bibliographicCitationJalali, K., Uchida, T., Lambert, S., & McPhee, J. (2013). Development of an Advanced Torque Vectoring Control System for an Electric Vehicle with In-Wheel Motors using Soft Computing Techniques. SAE International Journal of Alternative Powertrains, 2(2), 261–278.
uws.contributor.affiliation1Faculty of Engineeringen
uws.contributor.affiliation2Systems Design Engineeringen

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