Paper Info
Title
Investigation of suction flow characteristic in the inertance hydraulic converters for efficiency improvement
Abstract
The inertance hydraulic converter relies on fluid inertance to modulate flow or pressure and is considered to be a competitive alternative to the conventional proportional hydraulic system due to its potential advantage in efficiency. As the quantification of fluid inertance, the suction flow characteristic is the crucial performance indicator for efficiency improvement. To explore the discrepancy between the passive inertance hydraulic converter featured by the check valve and the active inertance hydraulic converter driven by an equivalent 2/3 way fast switching valve in regard to suction flow characteristics, analytical models of the inertance hydraulic converters were established in MATLAB/Simulink. The validated models of the respective suction components were incorporated in the overall analytical models and their suction flow characteristics were theoretically and experimentally discussed. The analytical predictions and experimental measurements for the current configurations indicated that the active inertance hydraulic converter yields a larger transient suction flow rate than that of the passive inertance hydraulic converter due to the difference of the respective suction components. The suction flow characteristic can be modulated using the supply pressure and duty cycle, which was confirmed by experimental measurements. In addition, the suction flow characteristics are heavily affected by the resistance of the suction flow passage and switching frequency. There is a compromise between the resistance and switching frequency for inertance hydraulic converters to achieve large suction flow rate.
Year
DOI
Venue
2022
10.1177/09596518211024878
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING
Keywords
DocType
Volume
Inertance hydraulic converter, fluid inertance, suction flow characteristic, equivalent fast switching valve, analytical model
Journal
236
Issue
ISSN
Citations 
1
0959-6518
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Xiaoming Chen100.34
Yuchuan Zhu200.34
Travis Wiens300.34
Doug Bitner400.34
Minghao Tai500.34
Yulei Jiang600.34