par Pop, Adrian-Cornel 
;Pinto, Diogo ;Tuchsen, Johann;Koch, Matthias
Référence IEEE transactions on energy conversion, 35, 4, page (2201-2209), 9124638
Publication Publié, 2020-12
;Pinto, Diogo ;Tuchsen, Johann;Koch, MatthiasRéférence IEEE transactions on energy conversion, 35, 4, page (2201-2209), 9124638
Publication Publié, 2020-12
Article révisé par les pairs
| Résumé : | This article deals with highlighting some pragmatic approaches for determining the key-parameters that one has to monitor in order not to jeopardize the fulfillment of the customer specifications, due to the tolerances, that occur in large-scale mass production. For that, two parametrization models (symmetric vs. asymmetric) and two types of parameter distributions (uniform vs. normal) are compared when considering lamination, stack assembly and material properties tolerances. Results in different scenarios for both the motor (in open-circuit and under load), and the whole drive (with and without position sensor detection errors) are provided and compared with end-of-line measurements (where available) for a 12-slots 10-poles IPM-type PMSM with fractional slot concentrated winding. After including the effect of the temperature in the full asymmetric model, rather good agreements between calculations and measurements are reported for back-EMF and torque constant. Furthermore, it is shown that the interaction between the uncertainties of the motor parameters and the rest of the drive's components (e.g. position sensor) cause large inaccuracies into the system, and they are hardly predictable by taking the individual deviations separately. Finally, towards the end, attempts are made to reduce the computational and the modeling effort using various techniques and ultimately fitted artificial neural networks (ANNs) as surrogates. |
