Embedded Real-Time Nonlinear Model Predictive Control for the Thermal Torque Derating of an Electric Vehicle
IFAC-PapersOnLine, vol. 54, pp. 359–364
Abstract
This paper presents a real-time capable nonlinear model predictive control (NMPC) strategy to effectively control the driving performance of an electric vehicle (EV) while optimizing thermal utilization. The prediction model is based on an experimentally validated two-node lumped parameter thermal network (LPTN) and one-dimensional driving dynamics. An efficient solver for the trajectory tracking problem is exported using acados and deployed on a dSPACE SCALEXIO embedded system. The lap time of a high-load driving cycle compared to a state-of-the-art derating strategy improved by 2.56% with an energy consumption reduction of 2.43% while respecting the temperature constraints of the electric drive.
Authors 7
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Affiliation as printed
Teaching and Research Area for Mechatronics in Mobile Propulsion - RWTH Aachen University, Forckenbeckstraße 4, 52074 Aachen, Germany
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Jonathan Frey corresponding
Affiliation as printed
Department of Microsystems Engineering, Albert-Ludwigs-University of Freiburg, Georges-Köhler-Allee 103, 79110 Freiburg, Germany
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Timm Fahrbach Aachen
Affiliation as printed
Teaching and Research Area for Mechatronics in Mobile Propulsion - RWTH Aachen University, Forckenbeckstraße 4, 52074 Aachen, Germany
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Affiliation as printed
Department of Microsystems Engineering, Albert-Ludwigs-University of Freiburg, Georges-Köhler-Allee 103, 79110 Freiburg, Germany
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René Scheer Aachen
Affiliation as printed
Teaching and Research Area for Mechatronics in Mobile Propulsion - RWTH Aachen University, Forckenbeckstraße 4, 52074 Aachen, Germany
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Moritz Diehl corresponding
Affiliation as printed
Department of Microsystems Engineering, Albert-Ludwigs-University of Freiburg, Georges-Köhler-Allee 103, 79110 Freiburg, Germany
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Affiliation as printed
Teaching and Research Area for Mechatronics in Mobile Propulsion - RWTH Aachen University, Forckenbeckstraße 4, 52074 Aachen, Germany
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References 19
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W3207305612details pending0citations
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W3047366950details pending0citations
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W4288083057details pending0citations
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