On Nonlinear Model Predictive Control for Energy-Efficient Torque-Vectoring

A 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...

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Veröffentlicht in:	IEEE transactions on vehicular technology Jg. 70; H. 1; S. 173 - 188
Hauptverfasser:	Parra, Alberto, Tavernini, Davide, Gruber, Patrick, Sorniotti, Aldo, Zubizarreta, Asier, Perez, Joshue
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Actuators Algorithms Configuration management control allocation Cornering Cost function Driving conditions Electric vehicles Energy conservation Energy consumption Energy efficiency Fuzzy control Fuzzy logic Mechanical power transmission Nonlinear control nonlinear model predictive control Optimality criteria Optimization Powertrain powertrain power loss Predictive control reference yaw rate Resource management tire slip power loss Tires Torque Torque-vectoring weight adaptation Wheels Yawing moments
ISSN:	0018-9545, 1939-9359
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Abstract	A 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.
AbstractList	A 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.
Author	Gruber, Patrick Parra, Alberto Tavernini, Davide Perez, Joshue Sorniotti, Aldo Zubizarreta, Asier
Author_xml	– sequence: 1 givenname: Alberto orcidid: 0000-0002-3269-214X surname: Parra fullname: Parra, Alberto email: alberto.parra@tecnalia.com organization: Tecnalia Research and Innovation, Basque Research and Technology Alliance, Donostia-San Sebastián, Spain – sequence: 2 givenname: Davide orcidid: 0000-0001-5171-8803 surname: Tavernini fullname: Tavernini, Davide email: d.tavernini@surrey.ac.uk organization: University of Surrey, Guildford, U.K – sequence: 3 givenname: Patrick orcidid: 0000-0003-1030-6655 surname: Gruber fullname: Gruber, Patrick email: p.gruber@surrey.ac.uk organization: University of Surrey, Guildford, U.K – sequence: 4 givenname: Aldo orcidid: 0000-0002-4848-058X surname: Sorniotti fullname: Sorniotti, Aldo email: a.sorniotti@surrey.ac.uk organization: University of Surrey, Guildford, U.K – sequence: 5 givenname: Asier orcidid: 0000-0001-6049-2308 surname: Zubizarreta fullname: Zubizarreta, Asier email: asier.zubizarreta@ehu.eus organization: University of the Basque Country, Bilbao, Spain – sequence: 6 givenname: Joshue orcidid: 0000-0002-0974-5303 surname: Perez fullname: Perez, Joshue email: joshue.perez@tecnalia.com organization: Tecnalia Research and Innovation, Basque Research and Technology Alliance, Donostia-San Sebastián, Spain
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Cites_doi	10.1016/j.ymssp.2015.03.024 10.1016/j.conengprac.2019.104256 10.1007/978-0-85729-501-9 10.1016/S0957-4158(02)00036-3 10.1109/TCST.2017.2753169 10.1115/1.1758257 10.1016/j.mechatronics.2019.02.006 10.1016/j.ymssp.2015.11.028 10.1080/00423114.2015.1064972 10.1109/TVT.2019.2933229 10.1109/TIE.2016.2540584 10.1109/TVT.2019.2935617 10.1016/j.conengprac.2014.01.005 10.1177/0954407013516106 10.1007/978-1-84628-469-4_2 10.1007/s12239-017-0079-4 10.1109/TVT.2014.2361860 10.1155/2018/7030184 10.1016/j.automatica.2011.08.020 10.1080/00423114.2014.902973 10.1115/1.4037003 10.1109/TMECH.2013.2249591 10.1109/TVT.2014.2339401 10.1016/j.conengprac.2015.12.012 10.1080/00423114.2016.1246737 10.1109/ITSC.2016.7795958 10.1109/TIE.2013.2271596 10.1109/TVT.2014.2305475 10.1049/iet-its.2018.5089 10.1016/j.scitotenv.2004.04.070 10.1016/j.mechatronics.2015.12.005 10.1016/j.rser.2015.07.010 10.1007/s12239-018-0078-0 10.1109/VPPC.2016.7791737 10.1109/ACCESS.2019.2917313 10.1016/j.ymssp.2019.03.012 10.1109/TVT.2018.2808186 10.1109/IECON.2019.8926854 10.1016/j.mechatronics.2014.12.003 10.1080/00423114.2019.1585557 10.1016/j.enpol.2012.05.081 10.1016/j.ymssp.2018.08.037
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References	ref13 ref56 ref12 ref15 ref14 ref52 ref55 ref11 ref10 (ref2) 2020 ref17 ref16 ref19 ref18 milliken (ref47) 1996 blej (ref51) 2016; 5 li (ref32) 2018; 11 ref50 smith (ref9) 0 ref48 ref42 ref41 ref43 ref49 ref8 (ref45) 2020 ref7 ref4 ref6 ref5 ref35 ref34 kobayashi (ref24) 2017; 56 ref37 ref36 pacejka (ref44) 2006 ref31 ref30 ref33 ref1 ref39 ref38 (ref53) 0 (ref54) 2020 gillespie (ref46) 1996 ref23 ref26 ref25 ref20 ref22 ref21 (ref40) 2020 ref28 ref27 (ref3) 2020 ref29
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SubjectTerms	Actuators Algorithms Configuration management control allocation Cornering Cost function Driving conditions Electric vehicles Energy conservation Energy consumption Energy efficiency Fuzzy control Fuzzy logic Mechanical power transmission Nonlinear control nonlinear model predictive control Optimality criteria Optimization Powertrain powertrain power loss Predictive control reference yaw rate Resource management tire slip power loss Tires Torque Torque-vectoring weight adaptation Wheels Yawing moments
Title	On Nonlinear Model Predictive Control for Energy-Efficient Torque-Vectoring
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