Embedded Real-Time Nonlinear Model Predictive Control for the Thermal Torque Derating of an Electric Vehicle. Issue 6 (2021)

• Record Type: Journal Article
• Authors: Winkler, Alexander; Frey, Jonathan; Fahrbach, Timm; Frison, Gianluca; Scheer, René; Diehl, Moritz; Andert, Jakob
• Is Part Of: IFAC-PapersOnLine. Volume 54:Issue 6(2021)
• Page Start: 359
• Page End: 364
• Publication Date: 2021
• Subjects: nonlinear model predictive control -- real-time control -- automotive control -- optimal control -- permanent magnet motors -- embedded systems -- temperature control; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2021.08.570
• Languages: English
• ISSNs: 2405-8963

Abstract

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.