考虑混合不确定性的空气悬架系统动态特性分析
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1.广州城市理工学院汽车与交通工程学院;2.华南理工大学 机械与汽车工程学院;3.华南理工大学 机械与汽车工程学院 4.广东 广州

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国家自然科学基金项目(面上项目,重点项目,重大项目)


Dynamic characteristics analysis of the air suspension system considering hybrid uncertainties
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1.School of Automobile and Traffic Engineering,Guangzhou City University of Technology;2.School of Mechanical and Automotive Engineering,South China University of Technology

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    摘要:

    针对汽车悬架系统受多源不确定性因素影响的复杂情形,提出了一种考虑参数混合不确定性的空气悬架系统动态特性分析方法。首先,采用混合不确定模型描述空气悬架系统的多源不确定参数,将信息匮乏的参数处理为区间变量,而将信息充足的参数描述为随机变量;然后,利用衍生λ-PDF(λ probability density function)在统一的正交多项式展开理论框架内建立随机与区间混合不确定系统响应的正交多项式展开近似模型,并推导了一种能有效求解混合多项式系数的方法,通过所建混合多项式实现对空气悬架动态特性的快速计算;进一步,为验证所提出方法的有效性,基于蒙特卡洛法提出了一种参考方法。最后,结合算例分析验证了方法的有效性,并探究了不同不确定情形下的系统响应结果。分析结果表明,与基于蒙特卡洛模拟的参考方法相比,所提方法能够有效地求解系统动力学响应,并且具有较高的计算精度和效率;所提方法在系统响应均值与标准差边界的求解中整体优于现有的混合摄动子区间方法;若将系统中混合不确定情形按照单一不确定性处理,结果可能是不合理的。

    Abstract:

    Aiming at the complex situation of vehicle suspensions affected by multi-source uncertainties, a dynamic characteristic analysis method for the air suspension systems considering hybrid uncertain parameters is proposed. Firstly, a hybrid uncertain model was adopted to characterize the multi-source uncertain parameters of air suspension system. The parameters with insufficient information were treated as interval variables, while those with abundant information were described as random variables. Then, the orthogonal polynomial expansion approximate model of the random and interval mixed uncertainty system response was established within the unified orthogonal polynomial expansion theory framework using the derived λ-PDF, and a method that can effectively solve the mixed polynomial coefficients was derived. The dynamic characteristics of air suspension were quickly calculated through the constructed mixed polynomials. Furthermore, to verify the effectiveness of the proposed method, a reference method based on the Monte Carlo approach was presented. Finally, the effectiveness of the proposed method was verified by example analysis and the system response results under different uncertain situations were explored. The analysis results show that the proposed method can effectively solve the dynamic response of system and has higher computational accuracy and efficiency, compared with the reference method based on Monte Carlo simulation. The proposed method is superior to the existing hybrid perturbation subinterval method in solving the boundaries of the means and standard deviations of system response. If the hybrid uncertainties in the system are treated as single uncertainty, the obtained results may be unreasonable.

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  • 收稿日期:2025-09-21
  • 最后修改日期:2025-12-19
  • 录用日期:2026-01-27
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