IIUM Repository

Computationally efficient brushless permanent magnet motor modelling

Welford, J. and Apsley, J. and Forsyth, A. and Sophian, Ali (2014) Computationally efficient brushless permanent magnet motor modelling. In: 7th IET International Conference on Power Electronics, Machines and Drives (PEMD 2014), 8th-10th Apr. 2014, Manchester, United Kingdom.

[img] PDF - Published Version
Restricted to Repository staff only

Download (223kB) | Request a copy


Physically derived mathematical models of motors are frequently used to simulate system performance. These can be constructed at various levels of fidelity depending on the application requirements. To accurately capture the dynamics of brushless permanent magnet motors, the effects of electrical commutation should be included. Short time-step simulations are required to include electrical effects explicitly. If the experimental time durations are large, for example during thermal analysis, this type of model can take unacceptably long to run. This work develops a new motor model that includes commutation effects implicitly, and is therefore capable of operating using increased time-steps, significantly reducing simulation time. The effects of winding resistance and inductance within the model ensure that it produces similar results to a fully commutated 3-phase model. The new model is demonstrated through comparison against other models and real motor test results. This validation process is performed in the frequency domain.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 7258/57619
Uncontrolled Keywords: BLDC, average-value, modelling, permanent magnet, electrical machine
Subjects: T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Dr Ali Sophian
Date Deposited: 17 Jul 2017 13:09
Last Modified: 17 Jul 2017 13:09
URI: http://irep.iium.edu.my/id/eprint/57619

Actions (login required)

View Item View Item


Downloads per month over past year