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A comprehensive review of modeling techniques for double-row tapered roller bearings

  • Jingyang Zheng
  • , Luhao Li
  • , Van Canh Tong
  • , Qing Ni
  • , Liyou Xu
  • , Ke Feng
  • , Michael Beer
  • , Ya an Hu
  • Henan University of Science and Technology
  • Ltd.
  • Samsung Display Vietnam
  • Northwestern Polytechnical University Xian
  • University of Liverpool
  • Leibniz University Hannover
  • Tongji University
  • Nanjing Hydraulic Research Institute

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations

Abstract

Double-Row Tapered Roller Bearings (DTRBs) possess notable advantages, including large load-carrying capacity, long service life, and the ability to withstand combined radial and axial loads, as well as bending moments. DTRBs are widely used in mechanical equipment and machinery, such as precision machine tools, automotive vehicles, railway vehicles, and wind turbines. The static and dynamic modeling of DTRBs plays a pivotal role in analyzing bearing tribological behavior and mechanical system performance, as well as in design and optimization. Over the past decades, extensive research has focused on DTRBs modeling and analysis to elucidate their tribological behavior and vibration mechanisms, thereby improving design and application. However, no comprehensive review has yet summarized the research progress on this topic. To fill this gap, this paper conducts a state-of-the-art review on DTRBs modeling and analysis, including the processes and differences in static modeling using traditional, multibody, and finite element methods, the techniques and implementation of dynamic modeling, and the current research progress in this field. This review also provides recommendations for future research, aiming to facilitate further development of DTRBs modeling and analysis.

Original languageEnglish
Article number111425
JournalTribology International
Volume215
DOIs
StatePublished - Mar 2026

Keywords

  • DTRBs
  • Dynamic modeling
  • Fatigue life
  • Finite element analysis
  • Static modeling

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