4.7 Article

A Distributed Integrated Control Architecture of AFS and DYC Based on MAS for Distributed Drive Electric Vehicles

Journal

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 70, Issue 6, Pages 5565-5577

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2021.3076105

Keywords

Vehicles; Asymptotic stability; Vehicle dynamics; Optimization; Stability criteria; Centralized control; Tires; AFS; DYC; A multi-agent system; Pareto-optimality theory; Terminal constraints

Funding

  1. National Natural Science Foundation (NNSF) of China [51975118, 52025121]
  2. Key R&D Program of Jiangsu Province [BE2019004]
  3. Achievements Transformation Project of Jiangsu Province [BA2018023, BA2020068]

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The paper proposes a novel distributed control architecture for integrated control of AFS and DYC systems, using MAS to construct a general framework and applying Pareto optimality theory to obtain cooperative control strategies for the two agents. Virtual simulations demonstrate that the proposed control architecture can effectively maintain vehicle stability and reduce driver workload.
Reconstitution of control architecture creates a great challenge for distributed drive electric vehicles (DDEV), due to the emergence of a new distributed driving strategy. To this end, a novel distributed control architecture is proposed in this paper for integrated control of active front steering (AFS) system and direct yaw moment (DYC) system. First, a multi-agent system (MAS) is employed to construct a general framework, where AFS and DYC act as agents that work together to improve vehicle lateral stability and simultaneously reduce workloads of drivers during path tracking. The cooperative control strategies of two agents are obtained through Pareto-optimality theory to ensure optimal control performance of AFS and DYC. Then, on the basis of dynamic interaction between agents, terminal constraints, including terminal cost function and terminal input with local static feedback, are designed to guarantee the asymptotic stability of the close-loop system. Finally, virtual simulations are conducted to evaluate the proposed controller. The results indicate that the proposed control architecture can effectively preserve vehicle stability and reduce workloads of drivers, especially for the inexperienced driver. Furthermore, the hardware-in-loop (HIL) test results also demonstrate the feasibility of the proposed controller.

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