Experimental study on the impact of variations in the friction material properties on the vibration behaviour of brake pads
Publish Year: 1402
نوع سند: مقاله ژورنالی
زبان: English
View: 147
This Paper With 18 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_TAVA-9-2_002
تاریخ نمایه سازی: 9 دی 1402
Abstract:
Brake noise is often caused by the coupling of the natural frequencies of the disc and pad. To prevent this, it is important to control the natural frequencies of these components, hence, the dispersion of natural frequency values is a critical factor in brake noise determination. This paper examines how the brake pad's natural frequencies and mode shapes are affected by its friction material properties, such as Poisson's ratio, Young's modulus, and shear modulus in different directions. Two brake pad designs from Land Rover are modelled and analysed using finite element analysis (FEA) and experimental modal analysis (EMA). A machine learning algorithm based on multiple-features linear regression is used to identify the main friction material parameters and their relationship to the natural frequencies. The results show that increasing the transverse Young's modulus or decreasing the longitudinal Young's modulus, shear modulus, or Poisson's ratio in all directions can increase the natural frequencies. Consequently, the paper suggests that Poisson's ratio and transverse Young's modulus should be considered when selecting friction compounds for brake pads.
Keywords:
Friction Material Properties , Brake pads , Finite Element Analysis (FEM) , natural frequency , Multiple-Features Linear Regression
Authors
Mohammad Ravanbod
Automotive Research Centre, Department of Mechanical and Energy Systems Engineering, University of Bradford, Bradford, UK
Salman Ebrahimi-Nejad
Assistant Professor, School of Automotive Engineering, Iran University of Science & Technology, Tehran, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :