Performance optimisation of AC multiphase induction motor drive

Elgbaily, Mohamed 2024. Performance optimisation of AC multiphase induction motor drive. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

High-performance AC drives require accurate speed, magnetic flux, and torque estimations to provide a proper system operation. Thus, this thesis proposes a robust observer, i.e. Fuzzy logic control (FLC), to offer optimal estimations of these components with the aid of one of the artificial intelligence optimization techniques called Bees Algorithm (BA) in order to improve the dynamic performance of Direct Torque Control (DTC) of induction motor (IM) drives. The efficiency of motor drives is significantly impacted by a number of factors, including the selects of Voltage Vectors (VV) as well as their level of quality. Many improved IM drive optimization techniques involve only a single objective for the optimal estimation of speed without giving concern to the other variables. Furthermore, the optimization is performed on a complicated DTC structure. Nevertheless, in this study, both torque and flux are concurrently estimated. For several decades, a large number of automated design optimisation technologies have been used for the drive system of electric machines for different applications. The demand to look for interesting solutions to several optimisation problems has increased. The development of modern applications has highlighted the necessity for a new algorithm capable of accommodating constraint parameters and multi-objective functions. Therefore, this research will introduce one of the newest intelligence techniques by using an optimisation algorithm in the design of electric machines i.e. “Bees Algorithm” (BA). BA is a new optimization algorithm that mimics honeybees and has been adopted to solve many realistic engineering design problems. With the setting of six parameters, Bees Algorithm has the ability to perform both exploitative neighbourhood (local) search and explorative global search of an optimization problem. The algorithm is also reliable in handling complex multi-objective functions that satisfy the constraints quickly and efficiently. The interest in implementing FDTC using the BA optimisation technique has been presented and its outcomes were validated in both simulation and experimental platforms. The comparative performance data reveals that the suggested DTC based on BA-FDTC outperforms its counterparts in terms of reducing torque ripples and also both transient and steady-state responses. Compared to PSO-FDTC, FDTC, and DTC, the main feature achieved superiority by BA-FDTC is the torque ripples were III remarkably reduced by an average of 9 %, 12 %, 24 % and 55 % respectively, whereas the experimental validation findings notably reduced torque ripples by averages of 10%, 19%, 30%, and 41%, respectively.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Engineering
Uncontrolled Keywords:	1).Direct Torque control (DTC) 2). Fuzzy Logic Control (FLC) 3).Bees Algorithm (BA) 4).Induction motor 5) Particle Swarm Optimization (PSO) 6) Genatic Algorithm (BA)
Date of First Compliant Deposit:	15 November 2024
Last Modified:	15 Nov 2024 10:50
URI:	https://orca.cardiff.ac.uk/id/eprint/173996

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