Reduced Order Model for Modal Analysis of Electric Motors Considering Material and Dimensional Variations Loughborough University

Format:

Book

Conference/Event

Author/Creator:

Andreou, Panagiotis, author.

Contributor:

Hajjaj, Amal Z.

Mohammadpour, Mahdi

Ricardo Souza, Marcos

Theodossiades, Stephanos

Conference Name:

13th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference (2024-06-19 : Graz, Austria)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2024

Summary:

With the electrification of the automotive industry, electric motors have emerged as pivotal components. A profound understanding of their vibrational behaviour stands as a cornerstone for guaranteeing not only the optimal performance and reliability of vehicles in terms of noise, vibration, and harshness (NVH), but also the overall driving experience. The use of conventional finite element analysis (FEA) techniques for identification of the natural frequencies characteristics of electric motors often imposes significant computational loads, particularly when accurate material and geometrical properties and wider frequency ranges are considered. On the other hand, traditional reduced order vibroacoustic methodologies utilising simplified 2D representations, introduce several assumptions regarding boundary conditions and properties, leading to sacrifices in the accuracy of the results. To address these limitations, this study presents a novel electric motor modal analysis approach by employing a reduced order 3D thick cylindrical model that accommodates bi-directional variations in both material properties and dimensions, to accurately represent a real stator/ frame assembly. The model is derived directly from the 3D elasticity equations, and expressions are developed for different combinations of boundary conditions. The method's effectiveness is demonstrated through comparative studies with full FEA simulations data showing excellent agreement. The outcome of this study is a powerful yet highly computationally efficient, modal analysis tool, with reduced set-up complexity, that will ultimately aid engineers in the design and optimisation of electric powertrains in early prediction of the system's natural frequencies during initial design stages

Notes:

Vendor supplied data

Publisher Number:

2024-01-2945

Access Restriction:

Restricted for use by site license