Abstract
Induction motors are extensively used for efficient energy utilization and dynamic control in high-performance drive applications. Accurate knowledge of induction motor parameters is crucial for optimal drive performance through control methods. Mismatched motor and drive parameters can lead to degraded drive performance, especially in cases of motor replacement, necessitating labor-intensive parameter adjustments and trial and error testing, resulting in time and cost overheads. MathWorks offers methods via MATLAB software to modify drive parameters, albeit with manual adjustments and time-consuming trial and error. This paper introduces a novel model for estimating induction motor and drive parameters, utilizing MathWorks Simscape™ Power Systems library models' AC3 block. The model employs the motor's nominal power rating to automatically update drive parameters upon motor replacement. Validation of MathWorks models and diverse operating conditions demonstrated the model's efficiency in rapidly delivering satisfactory results. The approach targets scenarios with sudden power and control shifts, promising streamlined parameter estimation and modification. This model holds the potential to enhance efficiency and reduce downtime and maintenance costs in high-performance drive systems.
Original language | English |
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Title of host publication | International Conference on Maintenance and Intelligent Asset Management |
Subtitle of host publication | ICMIAM 2023 |
Publication status | Accepted/In press - 7 Nov 2023 |
Event | 4th International Conference on Maintenance and Intelligent Asset Management - Ballarat, Australia Duration: 6 Dec 2023 → 8 Dec 2023 Conference number: 4 |
Conference
Conference | 4th International Conference on Maintenance and Intelligent Asset Management |
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Abbreviated title | ICMIAM 2023 |
Country/Territory | Australia |
City | Ballarat |
Period | 6/12/23 → 8/12/23 |