A real-time nonlinear model predictive control strategy for stabilisation of an electric vehicle at the limits of handling
dc.contributor.author | Siampis, Efstathios | |
dc.contributor.author | Velenis, Efstathios | |
dc.contributor.author | Gariuolo, Salvatore | |
dc.contributor.author | Longo, Stefano | |
dc.date.accessioned | 2019-01-25T16:13:23Z | |
dc.date.available | 2019-01-25T16:13:23Z | |
dc.date.issued | 2018-10-09 | |
dc.description.abstract | In this paper, we propose a real-time nonlinear model predictive control (NMPC) strategy for stabilization of a vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear four-wheel vehicle model that neglects the wheel dynamics is coupled with a nonlinear tire model to design three MPC strategies of different levels of complexity that are implementable online: one that uses a linearized version of the vehicle model and then solves the resulting quadratic program problem to compute the necessary longitudinal slips on the rear wheels, a second one that employs the real-time iteration scheme on the NMPC problem, and a third one that applies the primal dual interior point method on the NMPC problem instead until convergence. Then, a sliding mode slip controller is used to compute the necessary torques on the rear wheels based on the requested longitudinal slips. After analyzing the relative tradeoffs in performance and computational cost between the three MPC strategies by comparing them against the optimal solution in a series of simulation studies, we test the most promising solution in a high-fidelity environment. | en_UK |
dc.identifier.citation | Efstathios Siampis, Efstathios Velenis, Salvatore Gariuolo and Stefano Longo. A real-time nonlinear model predictive control strategy for stabilisation of an electric vehicle at the limits of handling. IEEE Transactions on Control Systems Technology, Volume 26, Issue 6, November 2018, pp. 1982-1994 | en_UK |
dc.identifier.cris | 22645071 | |
dc.identifier.issn | 1063-6536 | |
dc.identifier.uri | https://doi.org/10.1109/TCST.2017.2753169 | |
dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/13855 | |
dc.language.iso | en | en_UK |
dc.publisher | IEEE | en_UK |
dc.rights | Attribution-NonCommercial 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | * |
dc.subject | Accident prevention | en_UK |
dc.subject | nonlinear control systems | en_UK |
dc.subject | predictive control | en_UK |
dc.subject | vehicle dynamics | en_UK |
dc.title | A real-time nonlinear model predictive control strategy for stabilisation of an electric vehicle at the limits of handling | en_UK |
dc.type | Article | en_UK |
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