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dc.contributor.authorParra, Alberto
dc.contributor.authorTavernini, Davide
dc.contributor.authorGruber, Patrick
dc.contributor.authorSorniotti, Aldo
dc.contributor.authorZubizarreta, Asier
dc.contributor.authorPerez, Joshue
dc.date.accessioned2021-03-01T16:08:51Z
dc.date.available2021-03-01T16:08:51Z
dc.date.issued2021-01
dc.identifier.citationParra, Alberto, Davide Tavernini, Patrick Gruber, Aldo Sorniotti, Asier Zubizarreta, and Joshue Perez. “On Nonlinear Model Predictive Control for Energy-Efficient Torque-Vectoring.” IEEE Transactions on Vehicular Technology 70, no. 1 (January 2021): 173–188. doi:10.1109/tvt.2020.3022022.en
dc.identifier.issn0018-9545en
dc.identifier.urihttp://hdl.handle.net/11556/1088
dc.description.abstractA recently growing literature discusses the topics of direct yaw moment control based on model predictive control (MPC), and energy-efficient torque-vectoring (TV) for electric vehicles with multiple powertrains. To reduce energy consumption, the available TV studies focus on the control allocation layer, which calculates the individual wheel torque levels to generate the total reference longitudinal force and direct yaw moment, specified by higher level algorithms to provide the desired longitudinal and lateral vehicle dynamics. In fact, with a system of redundant actuators, the vehicle-level objectives can be achieved by distributing the individual control actions to minimize an optimality criterion, e.g., based on the reduction of different power loss contributions. However, preliminary simulation and experimental studies – not using MPC – show that further important energy savings are possible through the appropriate design of the reference yaw rate. This paper presents a nonlinear model predictive control (NMPC) implementation for energy-efficient TV, which is based on the concurrent optimization of the reference yaw rate and wheel torque allocation. The NMPC cost function weights are varied through a fuzzy logic algorithm to adaptively prioritize vehicle dynamics or energy efficiency, depending on the driving conditions. The results show that the adaptive NMPC configuration allows stable cornering performance with lower energy consumption than a benchmarking fuzzy logic TV controller using an energy-efficient control allocation layer.en
dc.language.isoengen
dc.publisherIEEEen
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleOn Nonlinear Model Predictive Control for Energy-Efficient Torque-Vectoringen
dc.typearticleen
dc.identifier.doi10.1109/tvt.2020.3022022en
dc.rights.accessRightsopenAccessen
dc.subject.keywordsTorque-vectoringen
dc.subject.keywordsNonlinear model predictive controlen
dc.subject.keywordsPowertrain power lossen
dc.subject.keywordsTire slip power lossen
dc.subject.keywordsReference yaw rateen
dc.subject.keywordsControl allocationen
dc.subject.keywordsWeight adaptationen
dc.identifier.essn1939-9359en
dc.issue.number1en
dc.journal.titleIEEE Transactions on Vehicular Technologyen
dc.page.final188en
dc.page.initial173en
dc.volume.number70en


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    Attribution 4.0 InternationalExcept where otherwise noted, this item's license is described as Attribution 4.0 International