【作者】 张宇；

【导师】 尹晓静； 左锋；

【作者基本信息】 长春工业大学 ， 机械硕士（专业学位）， 2023， 硕士

【摘要】 汽车制动器是车辆制动系统中的关键部件,其直接决定车辆的行驶安全性与可靠性。摩擦片作为盘式制动器和鼓式制动器的重要零件,也是制动过程中提供制动力的主要零件。在因不能提供有效制动而导致车辆发生事故的情况中,很大比例是摩擦片性能状态不佳引起的,对汽车制动器摩擦片性能状态进行准确的评估及预测,是减少此类事故发生的手段之一。制动器摩擦片性能状态受速度、载荷等因素的影响较大,开展考虑多因素影响下摩擦片性能状态预测研究,对提高制动器摩擦片性能状态预测的合理性与准确性有积极作用。本文对汽车制动器摩擦片相关摩擦磨损理论与性能状态预测方法进行研究,分析影响因素和性能评价指标之间的关系,开展多因素影响下汽车制动器摩擦片性能状态预测研究,准确、全面的反映汽车制动器摩擦片性能状态。本文主要研究内容如下:分析制动器摩擦片在制动过程中涉及到的摩擦形式以及摩擦力的组成,同时对制动器摩擦片的磨损类型及磨损阶段进行分析。通过对制动器摩擦片性能状态进行理论分析及有限元仿真分析,确定制动器摩擦片的影响因素及性能评价指标。在分析制动器摩擦片影响因素与性能评价指标的基础上,通过对某型摩擦片进行摩擦磨损性能分析,研究影响因素对摩擦片性能评价指标的影响,给出了速度等因素对摩擦片性能评价指标的影响趋势及机理,并基于最小二乘法建立各影响因素与性能评价指标之间的关系模型。提出一种基于证据推理算法(Evidence Reasoning,ER)的多因素影响下汽车制动器摩擦片性能状态预测方法。为了更加准确、合理的对汽车制动器摩擦片性能状态进行预测,结合基于最小二乘法建立的速度等因素与摩擦片性能评价指标的关系模型,考虑各影响因素对性能评价指标的影响,建立基于证据推理算法的制动器摩擦片性能状态预测模型,提高多因素影响下摩擦片性能状态预测精度。最后,设计开发了汽车制动器摩擦片性能状态预测软件,提高对汽车制动器摩擦片进行性能状态预测的人机交互性。更多还原

【Abstract】 Automotive brakes are the key components of the vehicle braking system,which directly determine the driving safety and reliability of the vehicle.Friction pads,as important parts of disc brakes and drum brakes,are also the main parts that provide braking force during the braking process.A large percentage of accidents caused by vehicles that fail to provide effective braking are caused by the poor performance of the friction pads,and an accurate assessment and prediction of the performance of the brake pads is one of the means to reduce such accidents.The performance state of brake friction pads is greatly influenced by speed,load and other factors,and the study on the prediction of friction pad performance state considering the influence of multiple factors will have a positive effect on improving the rationality and accuracy of brake friction pad performance state prediction.This paper investigates the friction and wear theory and performance state prediction methods related to automotive brake friction pads,analyzes the relationship between the influencing factors and performance evaluation indexes,and carries out research on the prediction of the performance state of automotive brake friction pads under the influence of multiple factors to accurately and comprehensively reflect the performance state of automotive brake friction pads.The main research contents of this paper are as follows:The friction form and the composition of friction force involved in the braking process of brake friction pads are analyzed,and the types and stages of wear of brake friction pads are also analyzed.Through theoretical analysis and finite element simulation analysis of the brake friction pad performance state,the performance influencing factors and performance evaluation indexes of the brake friction pad are determined.Based on the analysis of brake friction pad influencing factors and performance evaluation indexes,the influence of influencing factors on friction pad performance evaluation indexes is studied by analyzing the friction and wear performance of a certain type of friction pad,giving the trend and mechanism of the influence of speed and other factors on friction pad performance evaluation indexes,and establishing the relationship model between each influencing factor and performance evaluation indexes based on the least squares method.A method for predicting the performance state of automobile brake friction plate under the action of multiple factors based on Evidence Reasoning(ER)algorithm is proposed.In order to predict the performance state of automotive brake friction pads more accurately and reasonably,the relationship model between speed and other factors and friction pad performance evaluation indexes based on the least squares method is combined,and the influence of each influencing factor on the performance evaluation index is considered to establish a prediction model of brake friction pad performance state based on the Evidence Reasoning algorithm to improve the prediction accuracy of friction pad performance state under the influence of multiple factors.Finally,we designed and developed the automotive brake friction pad performance state prediction software to improve the human-computer interaction for the performance state prediction of automotive brake friction pads.更多还原