UWSpace will be migrating to a new version of its software from July 29th to August 1st. UWSpace will be offline for all UW community members during this time.
Development of an Advanced Fuzzy Active Steering Controller and a Novel Method to Tune the Fuzzy Controller
dc.contributor.author | Jalali, Kiumars | |
dc.contributor.author | Uchida, Thomas | |
dc.contributor.author | McPhee, John | |
dc.contributor.author | Lambert, Steve | |
dc.date.accessioned | 2017-03-16 18:53:06 (GMT) | |
dc.date.available | 2017-03-16 18:53:06 (GMT) | |
dc.date.issued | 2013-04-08 | |
dc.identifier.uri | http://dx.doi.org/10.4271/2013-01-0688 | |
dc.identifier.uri | http://hdl.handle.net/10012/11524 | |
dc.description | Replicated with permission by SAE Copyright © 2017 SAE International. Further distribution of this material is not permitted without prior permission from SAE. | en |
dc.description.abstract | A 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.sponsorship | Funding 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 Excellence | en |
dc.language.iso | en | en |
dc.publisher | SAE International | en |
dc.title | Development of an Advanced Fuzzy Active Steering Controller and a Novel Method to Tune the Fuzzy Controller | en |
dc.type | Article | en |
dcterms.bibliographicCitation | Jalali, 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. https://doi.org/10.4271/2013-01-0698 | en |
uws.contributor.affiliation1 | Faculty of Engineering | en |
uws.contributor.affiliation2 | Systems Design Engineering | en |
uws.typeOfResource | Text | en |
uws.peerReviewStatus | Reviewed | en |
uws.scholarLevel | Faculty | en |