基于悬架振动参数的双模糊控制器的路面类型识别及仿真研究

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中图分类号：U463.1 文献标识码：A

Abstract： Vehicle semi-active/active suspension systems often lack timely access to road roughness information for accurate road identification. To address this issue， a road surface type recognition method based on suspension vibration parameters and utilizing a dual fuzzy controller is proposed. First，a four-wheel correlated random road profile model and a seven-degree-of-freedom full-vehicle vertical dynamics model are established. Using the root mean square amplitude of the unsprung mass vertical acceleration as the characteristic parameter，a dual fuzzy controller structure is designed to achieve real-time recognition of Class A to D road surfaces for both lowspeed and high-speed conditions. Based on the CarSim-Simulink co-simulation platform， simulation experiments are conducted under combined working conditions involving multiple road surface classes and vehicle speeds. The results show that the recognition accuracy of the dual fuzzy controller under typical conditions is approximately 98% ， effectively distinguishing between adjacent road surface classes，with misjudgments primarily occurring near class boundaries. Within a ±20% variation range of the sprung mass， the fluctuation in recognition accuracy is less than 1% . This method provides a structurally simple and practically feasible solution for acquiring road surface class feedforward information for semi-active/active suspensions and related chassis control systems.

Keywords： suspension vibration parameters; dual fuzzy controller; co-simulation; road type identification

车辆行驶过程中需要实时获取前方路面状态，为悬架、驱动和制动等执行系统提供前馈信息，因此，路面类型识别是提升车辆平顺性、操控稳定性和轮胎寿命的重要技术之一[1-2]。（剩余7674字）