BLDC-motor production process surveillance based on parameter identification method

Abstract

In the field of electric motors, electronically commutated PMSM or BLDC type machines due to their superior robustness and efficiency, supersede conventional DC motors. Mass production lines for these motors ask for tight and thorough quality control, in terms of individual characterization of every single output product as well as trend monitoring for the entire production process. Classical test procedures that involve the mechanical coupling of a load machine are expensive in terms of handling efforts and time-consuming test cycles. The paper describes an alternative model based approach. It avoids any external load coupling but instead exploits the inherent inertia of the unloaded test object. By adequate dynamic drive schemes, the machine can be exposed to all relevant load situations, which allow a model based estimation of a small set of machine parameters that fully characterize the specimen. This facilitates very economical quality control procedures that involve short test cycles, 100% fault detection and production process monitoring with analysis and quality statistics. The presented method is verified by a series of measurements with BLDC motors and the results are analyzed with respect to precision and reproducibility.