車身高度調(diào)節(jié)中的滑?？刂粕窠?jīng)網(wǎng)絡消抖技術(shù)

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中圖分類號：TB9;U461.4 文獻標志碼：A 文章編號：1674-5124（2025）06-0150-10

The SMC neural network anti-vibration technology during vehicle height adjustment

ZHU Maoyuan1， ZHU Honglin1，LIU Xiaoya2，DING Weiping' （1. School ofMechanical Engineering， Southwest Jiaotong University， Chengdu 61oo31， China; 2. Sichuan Ningjiang Shanchuan Machinery Co.， Ltd.， Chengdu 61o1oo， China）

Abstract：The oscillatory phenomenon inherent in sliding mode control （SMC） has the potential to significantly degrade the precision of damping dynamics matching during vehicle height adjustment， consequently impacting the smoothnessof theride experience. Initially，itis posited that effective mitigationof these oscilations hinges upon the characteristics of the switching term within SMC，demanding atributes of continuity and adaptability.While the utilization of a continuous saturation function as the switching term， coupled with carefully designed boundary layer configurations， shows promise in atenuating oscilations， the inherent linearity of the control mechanism within the boundary layer poses limitations on adaptability and robustness.As a result， a novel methodology is proposed，entailing the integration of Radial Basis Function （RBF） neural networks into the SMC framework， denoted as SMC-RBF， where RBF serves as the pivotal switching term. Leveraging the nonlinear mapping capabilities of RBF ensures the continuity of the switching term， while harmessng its capacity for online weight updates via closed-loop feedback enables adaptation to time-varying systems. Consequently， this approach yields a seamlessly adjustable damping force curve， thus augmenting the precision of damping dynamics matching.Finally，from the vantage points of algorithmic oscillation suppression efficacy，as well as the ramifications of delays and dynamic factors on practical applications， comprehensive simulations encompassing 1/4 vehicle models， corresponding testing platforms， and full vehicle simulations are conducted.The results unequivocally demonstrate that， in comparison to conventional SMC and SMC-Fuzzy strategies， SMC-RBF affords superior oscillation suppression capabilities and，under conditions ensuring the preservation of handling stability，significantly enhances ride smoothness. Keywords： height active adjustment; damping dynamic matching; SMC; vibration; neural network

0 引言

車身高度與阻尼集成可調(diào)空氣懸架系統(tǒng)是一種有效協(xié)調(diào)汽車平順性與操穩(wěn)性的技術(shù)解決方案，備受學術(shù)界與工業(yè)界的關注。（剩余10631字）