RESEARCH ARTICLE

Fast scaling approach based on cavitation conditions to estimate the speed limitation for axial piston pump design

  • Qun CHAO 1 ,
  • Jianfeng TAO 1 ,
  • Junbo LEI , 1 ,
  • Xiaoliang WEI 1 ,
  • Chengliang LIU 1 ,
  • Yuanhang WANG 2 ,
  • Linghui MENG 2
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  • 1. State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • 2. China Electronic Product Reliability and Environmental Testing Research Institute, Guangzhou 510610, China

Received date: 02 Aug 2020

Accepted date: 29 Sep 2020

Published date: 15 Mar 2021

Copyright

2021 Higher Education Press

Abstract

The power density of axial piston pumps can benefit greatly from increased rotational speeds. However, the maximum rotational speed of axial piston machines is limited by the cavitation phenomenon for a given volumetric displacement. This paper presents a scaling law derived from an analytical cavitation model to estimate the speed limitations for the same series of axial piston pumps. The cavitation model is experimentally verified using a high-speed axial piston pump, and the scaling law is validated with open specification data in product brochures. Results show that the speed limitation is approximately proportional to the square root of the inlet pressure and inversely proportional to the cube root of volumetric displacement. Furthermore, a characteristic constant Cp is defined based on the presented scaling law. This constant can represent the comprehensive capacity of axial piston pumps free from cavitation.

Cite this article

Qun CHAO , Jianfeng TAO , Junbo LEI , Xiaoliang WEI , Chengliang LIU , Yuanhang WANG , Linghui MENG . Fast scaling approach based on cavitation conditions to estimate the speed limitation for axial piston pump design[J]. Frontiers of Mechanical Engineering, 2021 , 16(1) : 176 -185 . DOI: 10.1007/s11465-020-0616-0

Acknowledgements

This work was supported by the China National Postdoctoral Program for Innovative Talents (Grant No. BX20200210), the China Postdoctoral Science Foundation (Grant No. 2019M660086), and the Common Technology for Equipment Pre-research Project (Grant No. 41402050202).
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