The studies of coordinated control method for autonomous electric vehicles face two major challenges such as: I) Autonomous electric vehicles have the properties of uncertain nonlinearities and strong coupling, the platoon control system should effectively overcome these characteristics. II) Over-actuated tire actuators are equipped with in the autonomous electric vehicles to improve the system reliability, and reconfigurablity, the platoon control system should real-time handle the redundancy of tire actuators. This paper presents a novel nonlinear coordinated control scheme aimed at the improvement of the automatic driving performance of multiple autonomous electric vehicles in a platoon. First, a nonlinear mathematic model which perfectly describes the dynamic behaviors of autonomous electric vehicles is deduced using Newton-Euler theorem. Secondly, an adaptive coordinated control scheme is designed to manage the longitudinal and lateral motion of vehicles, which is a double level control framework. An adaptive backstepping sliding mode high-level control law is presented to determine the total forces and torque of vehicles, the uncertainties and switching function terms are accurately regulated by the neuro network. Third, a dynamic coordinated low-level control law is proposed, a SQP control allocation algorithm, which can achieve the fault tolerance and reconfiguration of the redundant tire actuation system, is presented to generate the desired longitudinal and lateral tire forces. Then, the dynamic regulators consisting of an inverse tire model and two inner loops for each wheel is designed to achieve its desired forces. Finally, simulation results illustrate that the presented coordinated control scheme has the excellent tracking properties under different driving conditions..


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    Title :

    Coordinated Longitudinal and Lateral Control of Autonomous Electric Vehicles in a Platoon


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE-TONGJI 2016 Driving Technology of Intelligent Vehicle Symposium ; 2016



    Publication date :

    2016-09-14




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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