Hierarchical creep control and a dynamic-response-oriented parameter tuning method for multi-axle distributed electric vehicles

Vehicle creep control is widely used for vehicle following in congested traffic and maneuvering in confined areas, and it can greatly ease the burden of driving in these situations, especially for heavy vehicles. In this paper, a hierarchical creep control strategy is proposed for multi-axle distributed electric vehicles. To address the problem of multiple operating conditions and external disturbances, the upper level establishes an event-triggered gain scheduling controller to obtain the required creep torque. The lower level proposes a torque distribution strategy that takes into account motor faults and achieves adaptive fault-tolerant torque distribution to ensure that there is no degradation of the dynamic response of the vehicle under creep conditions. Furthermore, a cost function incorporating the expected dynamic response constraints is designed, and the relationship between interpretability coefficients and dynamic response constraints is established. Controller parameters that achieve the expected creep dynamic response are obtained offline by adjusting the interpretability coefficients. Simulations and real-vehicle experiments show that the proposed control strategy and parameter tuning method can allow the vehicle to achieve the desired dynamic response constraints of creep.