Wear map-based wear prediction method for the piston–cylinder interface in axial piston machines

Journal of Zhejiang University. Science A, vol. 27, pp. 569–582

Abstract

Understanding the wear behavior of the piston–cylinder interface (PCI) is critical for improving the reliability and service life of axial piston machines (APMs). Existing PCI wear prediction methods often rely on one or two predefined wear models, for example, the Archard model with simplified mechanism switching. However, the PCI inherently experiences multiple coexisting contact states. In this paper, we propose a wear map-based wear prediction method. The operating conditions that can comprehensively represent the contact states across the entire interface are simulated by a mixed lubrication model and are then used as a matrix input into tribometer tests to measure a map of the wear rate. The wear map establishes the quantitative correlations between the contact states and the wear rate and can be embedded into an existing PCI wear prediction framework. An APM wear test showed that our proposed method could track the wear evolution process and capture the wear redistribution in the end region of the cylinder bore under the investigated operating conditions.

Authors 8

1. Fei Lyu Aachen Institute for Fluid Power Drives and Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Fluid Power Drives and Systems (ifas), RWTH Aachen University, Aachen, 52074, Germany

2. Xudong Shen Aachen Institute for Fluid Power Drives and Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Fluid Power Drives and Systems (ifas), RWTH Aachen University, Aachen, 52074, Germany

3. Felix Schlegel Aachen Institute for Fluid Power Drives and Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Fluid Power Drives and Systems (ifas), RWTH Aachen University, Aachen, 52074, Germany

4. Xiaolong Zhang Aachen Institute for Fluid Power Drives and Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Fluid Power Drives and Systems (ifas), RWTH Aachen University, Aachen, 52074, Germany

5. Liangyu Song Aachen Institute for Fluid Power Drives and Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Fluid Power Drives and Systems (ifas), RWTH Aachen University, Aachen, 52074, Germany

6. Junhui Zhang Aachen Institute for Fluid Power Drives and Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Fluid Power Drives and Systems (ifas), RWTH Aachen University, Aachen, 52074, Germany

7. Katharina Schmitz Aachen Institute for Fluid Power Drives and Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Fluid Power Drives and Systems (ifas), RWTH Aachen University, Aachen, 52074, Germany

8. Bing Xu Aachen Institute for Fluid Power Drives and Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Fluid Power Drives and Systems (ifas), RWTH Aachen University, Aachen, 52074, Germany