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Optimization design of a disc brake system with hybrid uncertainties

机译：具有混合不确定性的盘式制动系统的优化设计

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摘要

Squeal reduction of disc brake systems have been extensively investigated for both academic and industrial purposes. However, most of the existing optimization designs of squeal reduction are based on deterministic approaches which have not considered the uncertainties of material properties, loading conditions, geometric dimensions, etc. In this paper, a hybrid probabilistic and interval model is introduced to deal with the uncertainties existing in a disc brake system for squeal reduction. The uncertain parameters of the brake system with enough information are treated as probabilistic variables, while the parameters with limited information are treated as interval variables. To improve computational efficiency, the response surface methodology (RSM) is introduced to replace the time-consuming finite element (FE) simulations. By the hybrid uncertain model, an optimization design based on reliability and confidence interval is proposed to explore the optimal design for squeal reduction. In the proposed optimization, both the design objective and the design constraint are interval probabilistic functions due to the effects of hybrid uncertainties. In this case, the maximum of the upper bound of confidence interval of design objective is selected as the objective function, while the minimal value of the probabilistic constraint is selected as the constraint function. The combinational algorithm of Genetic Algorithm and Monte-Carlo method is employed to perform the optimization. The results of a numerical example demonstrate the effectiveness of the proposed optimization on reducing squeal propensity of the disc brake systems with hybrid uncertainties.
机译：出于学术和工业目的，已经广泛研究了盘式制动系统的啸叫减小。但是，大多数现有的减小尖叫声的优化设计都是基于确定性方法，这些方法没有考虑材料特性，载荷条件，几何尺寸等的不确定性。在本文中，引入了一种混合概率和区间模型来处理碟刹系统中存在的不确定性，以减少尖叫声。具有足够信息的制动系统的不确定参数被视为概率变量，而具有有限信息的参数被视为区间变量。为了提高计算效率，引入了响应面方法（RSM）来代替费时的有限元（FE）仿真。通过混合不确定模型，提出了一种基于信度和置信区间的优化设计，以探索减少尖叫的最佳设计。在提出的优化中，由于混合不确定性的影响，设计目标和设计约束都是区间概率函数。在这种情况下，选择设计目标的置信区间上限的最大值作为目标函数，而选择概率约束的最小值作为约束函数。采用遗传算法和蒙特卡洛方法相结合的算法进行优化。数值示例的结果证明了所提出的优化方法在降低具有混合不确定性的盘式制动系统的尖叫倾向方面的有效性。

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