Multi-objective optimization of circular-toothed gerotors for kinematics and wear by genetic algorithm

Abstract

A multi-objective optimization of circular-toothed gerotor gear geometry by genetic algorithm is presented that minimizes the size, flow ripple, adhesive wear, and subsurface fatigue wear (pitting) of the pump, insofar as the geometry is concerned, subject to the constraints to guarantee a feasible profile. Three pump geometries available to the authors used in automotive applications were compared to the optimization results. A clear Pareto front was established that gives insight into the design space of circular-toothed gerotors. The optimization identified that the industry reference pumps were very near to or on the Pareto front, so this work demonstrates mathematically that some circular-toothed gerotors in industry have reached an optimal solution. Another pump geometry is also identified that could be a better compromise between the objective functions than the reference pumps. The methodology presented here can be readily extended to other profile types and the results can serve as a benchmark for comparison.