Open AccessTwo‐level global sensitivity analysis of the excitation contributions leading to acoustic noise in an electric motor for the purpose of robust optimisation
Author(s) -
Jeannerot Martin,
Ouisse Morvan,
Lanfranchi Vincent,
Dupont JeanBaptiste,
SadouletReboul Emeline
Publication year - 2021
Publication title -
iet electric power applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.815
H-Index - 97
eISSN - 1751-8679
pISSN - 1751-8660
DOI - 10.1049/elp2.12129
Subject(s) - sensitivity (control systems) , robustness (evolution) , electric motor , torque , noise (video) , control theory (sociology) , range (aeronautics) , computer science , engineering , physics , electronic engineering , electrical engineering , artificial intelligence , biochemistry , chemistry , control (management) , image (mathematics) , gene , aerospace engineering , thermodynamics
Abstract This study presents a sensitivity analysis methodology used for electric motor design. This innovative approach evaluates both global effects of parameter variations in their design range and of parameter deviations in their tolerance intervals on design objectives. For the purpose of robust optimisation, this method helps to select the most influent design parameters and uncertain parameters, which are not necessarily the same. Suitable for any design approach, this method is particularly useful in dealing with objectives defined by non‐linear and non‐regular functions, such as electric motor acoustic criteria. In this study, the method is applied to the sensitivity evaluation of electromagnetic tangential excitations responsible for acoustic emissions in an electric motor. The sensitivity of output mean torque is also investigated. The sensitivity analysis shows that acoustic criteria appear generally more sensitive to parameter deviations than mean torque. Parameter deviations can be even more influent on acoustic criteria than larger parameter variations in their design range. As can be expected from the sensitivity results, the study eventually shows that the acoustic optimisation of the electric motor faces robustness issues.