Research on Yaw Stability Control of Multi-axle Electric Vehicle with In-Wheel Motors Based on Fuzzy Sliding Mode Control

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Authors Abstract
Content
This research develops a hierarchical control strategy to improve the stability of multi-axle electric vehicles with in-wheel motors while driving at high speed or on low adhesion-coefficient roads. The yaw rate and sideslip angle are chosen as the control parameters, and the direct yaw-moment control (DYC) method is employed to ensure the yaw stability of the vehicle. On the basis of this methodology, a hierarchical yaw stability control architecture that consists of a state reference layer, a desired moment calculation layer, a longitudinal force calculation layer, and a torque distribution layer is proposed. The ideal vehicle steering state is deduced by the state reference layer according to a linear two-degree-of-freedom (2-DOF) vehicle dynamics model. In line with the deviation between the ideal and the actual states of the vehicle, the desired moment calculation layer introduces an adaptive variable exponential approaching rate on the basis of the fuzzy sliding mode control (FSMC) algorithm to calculate the desired moment exactly. And the longitudinal force calculation layer figures out the desired longitudinal force to meet the drivers’ longitudinal speed requirements. The torque distribution layer distributes the torques of actuators via the optimal control theory based on a quadratic programming (QP) algorithm and the solution method of weighted least squares (WLS) so as to maximally enhance vehicle stability and maneuverability. Furthermore, typical extreme driving conditions were set to validate the effectiveness of the proposed yaw stability control architecture.
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DOI
https://doi.org/10.4271/02-15-03-0014
Pages
15
Citation
Zeng, X., Li, Y., Zhou, J., Song, D. et al., "Research on Yaw Stability Control of Multi-axle Electric Vehicle with In-Wheel Motors Based on Fuzzy Sliding Mode Control," Commercial Vehicles 15(3):259-273, 2022, https://doi.org/10.4271/02-15-03-0014.
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Publisher
Published
Dec 22, 2021
Product Code
02-15-03-0014
Content Type
Journal Article
Language
English