Abstract
Multiphase machines are complex multi-variable electro-mechanical systems that are receiving special attention from industry due to their better fault tolerance and power-per-phase splitting characteristics compared with conventional three-phase machines. Their utility and interest are restricted to the definition of high-performance controllers, which strongly depends on the knowledge of the electrical parameters used in the multiphase machine model. This work presents the proof-of-concept of a new method based on particle swarm optimization and standstill time-domain tests. This proposed method is tested to estimate the electrical parameters of a five-phase induction machine. A reduction of the estimation error higher than 2.5% is obtained compared with gradient-based approaches.
Highlights
Electromechanical systems such as multiphase variable speed drives have attracted the interest of the scientific community in recent times
The fitness function used to evaluate the quality of every particle in the population is the mean squared error (MSE) between the outputs given by the real system (the multiphase induction machine, yα and y x in Equation (18) and the outputs given by a modelled system
Unlike recently proposed gradient-based methods, this this proposal utilizes technique aproof-of-concept proof-of-conceptofofthe the application application of of meta-heuristic proposal utilizes the the technique as as meta-heuristic proposal utilizes the technique as aa proof-of-concept of the application of meta-heuristic optimization algorithms in the estimation of electrical parameters based on standstill methods
Summary
Electromechanical systems such as multiphase variable speed drives have attracted the interest of the scientific community in recent times. Many off-line and on-line methods have been proposed to obtain the electrical parameters of three-phase machines, where standstill identification techniques can be highlighted for being accurate and easy to apply in commercial variable frequency drives [5,6]. The identification procedure is applied to fit the real response with the simplified machine model, where adaptive filters, recursive least-squares (RLS)-based algorithms, or maximum likelihood methods have been used for this purpose [7] The extension of these methods for the multiphase case is barely found in the scientific literature. The PSO optimization technique is proposed to minimize the mean square error (MSE) in two operation subspaces, namely α–β and x–y, between the responses of the simulated and real systems in standstill configuration for a multi-variable electro-mechanical system like a five-phase induction machine.
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