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• W3200565315 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." @default.
• W3200565315 created "2021-09-27" @default.
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• W3200565315 date "2021-01-01" @default.
• W3200565315 modified "2023-09-25" @default.
• W3200565315 title "Embedded Real-Time Nonlinear Model Predictive Control for the Thermal Torque Derating of an Electric Vehicle" @default.
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• W3200565315 doi "https://doi.org/10.1016/j.ifacol.2021.08.570" @default.
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