An integrated path-tracking and control allocation method for autonomous racing electric vehicles

Date

2023-08-08

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Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Taylor & Francis

Department

Type

Article

ISSN

0042-3114

Format

Citation

Li B, Lin C, Ahmadi J, et al., (2024) An integrated path-tracking and control allocation method for autonomous racing electric vehicles, Vehicle System Dynamics, Volume 62, Issue 6, June 2024, pp. 1517-1540

Abstract

In recent years, path-tracking controllers for autonomous passenger vehicles and Control Allocation (CA) methods for handling and stability control have both received extensive discussion in the literature. However, the integration of the path-tracking control with CA methods for autonomous racing vehicles has not attracted much attention. In this study, we design an integrated path-tracking and CA method for a prototype autonomous racing electric vehicle with a particular focus on the maximising the turning speed in tight cornering. The proposed control strategy has a hierarchical structure to improve the computational efficiency: the high-level path-tracking Model Predictive Control (MPC) based on a rigid body model is designed to determine the virtual control forces according to the desired path and desired maximum velocity profile, while the low-level CA method uses a Quadratically Constrained Quadratic Programming (QCQP) formulation to distribute the individual control actuator according to the desired virtual control values. The proposed controller is validated in a high-fidelity simulation vehicle model with the computational time of the optimisation controller presented to demonstrate the real-time control performance.

Description

Software Description

Software Language

Github

Keywords

Autonomous vehicle, control allocation, MPC, path-tracking

DOI

Rights

Attribution 4.0 International

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Relationships

Supplements

Funder/s

Innovate UK: AID-CAV