Induction Motor Parameter Estimation Using Sparse Grid Optimization Algorithm
Journal article
Duan, F, Zivanovic, R, Al-Sarawi, S and Mba, D (2016). Induction Motor Parameter Estimation Using Sparse Grid Optimization Algorithm. IEEE Transactions on Industrial Informatics. PP (99). https://doi.org/10.1109/TII.2016.2573743
Authors | Duan, F, Zivanovic, R, Al-Sarawi, S and Mba, D |
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Abstract | Inaccurate motor parameters can lead to an inefficient motor control. Although several motor estimation methods have been utilized to estimate motor parameters, it is still challenging to ensure a good level of confidence in the estimation. In this paper, we propose a novel offline induction motor parameter estimation method based on sparse grid optimization algorithm. The estimation is achieved by matching the response of machines mathematical model with recorded stator current and voltage signals. This approach is non-invasive as it uses external measurements, resulting in reduced system complexity and cost. A globally optimal point was found by sampling on the sparse grid, which was created using the hyperbolic cross points (HCPs) and additional heuristics. This has resulted in reducing the total number of search points and provided the best match between the mathematical model and measurement data. The estimated motor parameters can be further refined by using any local search method. The experimental results indicate a very good agreement between estimated values and reference values. |
Keywords | Induction motor; parameter estimation; global optimization; sparse grid; hyperbolic cross point |
Year | 2016 |
Journal | IEEE Transactions on Industrial Informatics |
Journal citation | PP (99) |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
ISSN | 1551-3203 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TII.2016.2573743 |
Publication dates | |
26 May 2016 | |
Publication process dates | |
Deposited | 12 Aug 2016 |
Accepted | 08 Feb 2016 |
Accepted author manuscript | License File description licence File Access Level Open |
Additional information | (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. |
https://openresearch.lsbu.ac.uk/item/87406
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Accepted author manuscript
Repository deposit licence.docx | ||
License: CC BY-NC-ND 4.0 | ||
File access level: Open |
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