Wheel slip control with torque blending using linear and nonlinear model predictive control

Date

2017-03-31

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Taylor & Francis

Department

Type

Article

ISSN

0042-3114

Format

Free to read from

Citation

Basrah MS, Siampis E, Velenis E, Cao DP, Longo S, Wheel slip control with torque blending using linear and nonlinear model predictive control, Vehicle System Dynamics, Vol. 55, Issue 11, 2017, pp. 1665-1685

Abstract

Modern hybrid electric vehicles employ electric braking to recuperate energy during deceleration. However, currently anti-lock braking system (ABS) functionality is delivered solely by friction brakes. Hence regenerative braking is typically deactivated at a low deceleration threshold in case high slip develops at the wheels and ABS activation is required. If blending of friction and electric braking can be achieved during ABS events, there would be no need to impose conservative thresholds for deactivation of regenerative braking and the recuperation capacity of the vehicle would increase significantly. In addition, electric actuators are typically significantly faster responding and would deliver better control of wheel slip than friction brakes. In this work we present a control strategy for ABS on a fully electric vehicle with each wheel independently driven by an electric machine and friction brake independently applied at each wheel. In particular we develop linear and nonlinear model predictive control strategies for optimal performance and enforcement of critical control and state constraints. The capability for real-time implementation of these controllers is assessed and their performance is validated in high fidelity simulation.

Description

Software Description

Software Language

Github

Keywords

Hybrid electric vehicle, Real time, MPC, Nonlinear model predictive control, ABS, Slip control, Torque allocation

DOI

Rights

Attribution-NonCommercial 4.0 International

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