Empirical modelling of hydraulic pumps and motors based upon the Latin hypercube sampling method. Issue 3 (2018) - Panwar, Pawan; Michael, Paul
The effectiveness of orthogonal and Latin hypercube (LHS) experimental design strategies was compared in axial piston pump and radial piston motor testing. Stratified sampling via LHS was used to create test plans of varying sample size. Pump flow and motor torque-loss models were derived from the experimental results based on a comprehensive list of physically significant terms. The effectiveness of the sampling plans was evaluated by tracking the evolution of model errors using progressively sequenced regression. Progressively sequenced regression identified the minimum sample size required to achieve data saturation by incrementally increasing the number of data points included in the regression analysis. It was found that LHS produced higher fidelity models but reached data saturation no sooner than the orthogonal method. These results demonstrate the merit of combining LHS with progressively sequenced regression to improve empirical model fidelity and determine minimum sample-size requirements in hydraulic pump and motor testing.