Mitigating pressure fluctuations in a faulty axial piston pump using rearrangement of pistons

Axial piston pumps (APP) are prone to internal leakage due to tight clearances between slipper–swash plate, piston–cylinder, and barrel–port plate, which can deteriorate the pump performance significantly. This study proposes a novel method of enabling reusability of the APP with leakage fault in single and multiple cylinders. Using a model-based approach is presented to identify the best rearrangement of faulty piston–cylinders that results in the lowest peak-to-peak pressures fluctuations at the outlet of an APP. The system network model consisting of an APP is developed in MATLAB Simulink, which can simulate the pump response as a function of the number of faulty piston–cylinders and the different levels of leakage. In this study, three possible geometrical arrangements of faulty piston–cylinders, namely inline, random, and unform, are analyzed at three levels of leakage fault, i.e., an annular clearance of 20 µm, 60 µm, and 100 µm are validated with an experimental study from the literature. The arrangement of faulty piston–cylinders is defined based on their relative position in the cylinder barrel in terms of the configuration ratio, which is the normalized linear distance between them (for two or less) and the normalized area of an enclosed polygon in case of more than two faulty piston–cylinder. It is shown that the uniformly distributed faulty piston–cylinders are characterized by the highest configuration ratio and exhibit minimum peak-to-peak pressure fluctuations, which represents the best case under fault conditions. In contrast the inline arrangement represents the worst case while the random arrangement represents the intermediate case between the two. The results demonstrate that the faulty piston–cylinders can be repositioned in a uniform arrangement to minimize the pressure fluctuations resulting and the associate vibration effects. This can help improve the utility of an otherwise faulty pump, thereby reducing the maintenance downtime and the associated costs.