Faculty of Electrical Engineering and Information Technologies

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Synthesis and analysis of a high‐performance low‐cost permanent magnet brushless DC motor
(Emerald, 2012-09-07)
Petkovska, Lidija
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Lefley, Paul
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Cvetkovski, Goga
The paper presents design development of a novel high‐performance low‐cost 6/4 pole permanent magnet brushless DC (PMBLDC) motor. The objective is to show how the cogging torque of this new design is minimised by determining the optimum stator pole arc length and the best shoe thickness. At the beginning a step‐by‐step design synthesis of a reference 6/4 pole PMBLDC motor with concentrated 3‐phase windings and asymmetric stator pole arcs is presented. It is followed by a full performance analysis of the reference motor. The FEM for electromagnetic field computation is employed. The characteristics of the motor are calculated and analysed. By simple variation of the stator pole geometry, two‐stage design optimisation for cogging torque minimisation is performed, and an optimised motor model is proposed. The comparative analyses of the reference and optimised motor models show the advantages of the proposed novel design. The focus is to show the sensitivity of the cogging torque due to changes in the stator pole shoe design parameters, such as arc length and thickness, which are discretely changed inside the prescribed constraints, and the solution matrix is derived. It was found the optimised stator pole design, providing minimum cogging torque, has the original arc length 85° and pole shoe thickness 4 mm. Thus, the peak‐cogging torque from 0.294 Nm is reduced to respectable value 0.142 Nm. The paper presents an original approach to synthesis of 6/4 PMBLDC new structured motor. A two‐step design procedure is introduced and optimised stator geometry is defined, minimising the cogging torque and, at the same time, improving the profile of back electromotive force (EMF) of the motor.
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Optimal design of single phase permanent magnet brushless DC motor using particle swarm optimisation
(Emerald, 2014-10-28)
Cvetkovski, Goga
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Petkovska, Lidija
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Lefley, Paul
The purpose of this paper is to perform an optimal design of single phase permanent magnet brushless DC motor (SPBLDCM) using efficiency of the motor as objective function. In the design procedure performed on SPBLDCM, particle swarm optimisation (PSO) as an optimisation tool is used. The created computer programme for optimal design of electrical machines is based on the PSO. According to the design characteristics of SPBLDCM, some of the motor parameters are chosen to be constant and others variable. A comparative analysis of both motor models based on the value of the objective function, as well as the values of the optimisation parameters, is performed. From the comparative data analysis of both motor models, it can be concluded that the main objective of the optimisation is realised, and it is achieved by an improvement of the efficiency of the motor. An optimisation technique based on PSO has been developed and applied to the design of SPBLDCM. According to the results it can be concluded that the PSO is a very suitable tool for design optimisation of SPBLDCM and electromagnetic devices in general. The quality of the PSO model has been proved through the data analysis of the prototype and optimised solution. At the end, the quality of the PSO solution has been again proved by comparative analysis of the two motor models using FEM as a performance analysis tool.
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Comparison between two target functions for optimization of single phase shaded-pole motor using method of genetic algorithms
(Elsevier BV, 2005-04)
Sarac, Vasilija
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Petkovska, Lidija
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Cundev, Milan
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Cvetkovski, Goga
Method of genetic algorithms (GAs) has been started to be widely used, as an optimization technique of electrical machines, in the recent years. In this paper the GA method will be applied on the shaded-pole motor, aiming towards an improvement of its operational and performance characteristics. The authors develop two new improved motor models, starting from the basic one. In the first motor model the electromagnetic torque, as a target function for optimization is suggested, while in the second one the optimization is based on the efficiency factor, used as a target function. The results gained from the both motor models are analyzed and compared to the basic model. The conclusions regarding the more favorable target function for optimization of a single phase shaded-pole motor are presented.
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Specific power as objective function in GA optimal design of permanent magnet disc motor
(Emerald, 2010-07-13)
Cvetkovski, Goga
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Petkovska, Lidija
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Gair, Sinclair
The application of the analysed permanent magnet disc motor (PMDM) is in electric vehicle and therefore there are several objectives that could be tackled in the design procedure, such as an increased efficiency, reduced total weight of the motor or increased power/weight ratio (specific power). The purpose of this paper is to perform an optimal design of a PMDM using specific power as objective function. In the design procedure performed on the PMDM, genetic algorithm (GA), as an optimisation tool is used. The created optimal design programme genetic algorithm for optimal design of electrical machines is using the GA as an optimisation tool. According to the design characteristics of PMDM, some of the parameters are chosen to be constant and some variable. A comparative analysis of both motor models based on the values of some specific parameters is performed. From the comparative data analysis of both motor models, it can be concluded that the main objective of the optimisation is realised, and that is achieved by a reduction of the total weight of the motor, as well as the increase of the torque, as a result of which the specific power is increased. An optimisation technique based on GAs has been developed and applied to the design of a PMDM. According to the results investigated above, it can be concluded that the GA is a very suitable tool for design optimisation of PMDM and electromagnetic devices in general. The quality of the GA optimised model has been proved through the data analysis of the prototype and optimised solution. At the end, the quality of the GA solution has been again proved by comparative analysis of the two motor models using FEM as a performance analysis tool.
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Performance characteristics improvement of a PM disk motor by using soft magnetic composite material
(IOS Press, 2002-12-17)
Cvetkovski, Goga
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Petkovska, Lidija
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Cundev, Milan
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Gair, Sinclair
The paper presents a comparison of the magnetic ﬁeld and magnetic characteristics of a PM disk motor with laminated magnetic stator open slot core, laminated magnetic stator closed slot core with soft magnetic composite and soft magnetic composite stator core. The data for this analysis is provided by a 2D FEM calculation of the magnetic ﬁeld. After the proper modelling of the motor a calculation of the magnetic ﬁeld for no load and current load is performed, for the three models. The results of the magnetic ﬁeld distribution, air gap ﬂux density distribution and the values of the magnetic and electric parameters for the three models are also presented.
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Finite element analysis of a novel single phase permanent magnet brushless DC motor
(IEEE, 2010-09)
Lefley, Paul
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Petkovska, Lidija
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Ahmed, Saeed
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Cvetkovski, Goga
This paper is an extension and continuation of the previous authors’ work, where a practical solution for a novel single phase PM BLDC motor model has been developed, utilising an asymmetrical stator pole design. An accurate 2D finite element simulation was employed to numerically analyse the magnetic field distribution inside the motor. The results are used to prove the selected stator/rotor arc length ratio combination that produces a flat back EMF shape, at a reduced cogging torque.
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Comparative analysis of two optimal design approaches of PM disc motor for EV
(IEEE, 2010-09)
Cvetkovski, Goga
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Petkovska, Lidija
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Gair, Sinclair
The application of the permanent magnet disc motor (PMDM) is in electric vehicle and therefore there are several objectives that could be tackled in the design procedure, such as an increased efficiency, reduced total weight of the motor or increased power/weight ratio (specific power). In this paper an optimal design of a PMDM using efficiency and specific power as objective function is performed. In the design procedure performed on the PM disc motor, genetic algorithm, as an optimisation tool is used. Comparative analysis of the optimal motor solutions and its parameters in relation to the initial model is presented.
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Specific power based optimal design of novel single phase PM BLDC motor using GA
(IEEE, 2014-09)
Cvetkovski, Goga
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Petkovska, Lidija
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Lefley, Paul
In this paper a genetic algorithm based optimal design of a single-phase permanent magnet brushless DC motor (SPMBLDCM) is proposed. This approach employs a genetic algorithm (GA) technique as a search tool for the optimization process of the SPMBLDCM. The specific power of the motor is selected as an objective function. At the end of the optimisation a best solution is proposed based on the values of the optimisation parameters, as well as other important motor parameters. An overall comparison of the best optimal solution and the basic model of the motor is presented.
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Multi-objective optimal design of permanent magnet synchronous motor
(IEEE, 2016-09)
Cvetkovski, Goga
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Petkovska, Lidija
In this paper a genetic algorithm based optimal design of a permanent magnet synchronous motor (PMSM) is proposed. This approach employs a genetic algorithm (GA) technique as a search tool for optimal design solution of a PMSM based on the value of the objective function. The sum of the efficiency of the motor and the inverse value of the permanent magnet total weight is selected as a multi-objective function. An overall comparative analysis of the optimisation parameters and the values of certain important motor parameter of the prototype model and the optimal solution motor is presented.
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Nature Inspired Optimal Design of Axial Flux Permanent Magnet Motor for Electric Vehicle
(IEEE, 2018-08)
Cvetkovski, Goga
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Petkovska, Lidija
Optimal design of electrical machines generally is usually a complicated process with a lot of optimization parameters, constrains and complex objective functions. Standard deterministic methods can sometimes have difficulties to solve such problems, where on the other hand lately the stochastic methods have proved that they are quite powerful in solving such problems. There is large group of stochastic methods that are nature inspired and based on behavior of certain species in nature. The purpose of this research work is to implement several nature-based optimization methods in the optimal design of an electric motor and investigate the effectiveness of the implemented methods. The object of investigation is an axial flux permanent magnet motor. The objective function in the optimization process is defined to be the efficiency of the motor. The optimization methods that are implemented in the optimal design of the permanent magnet motor are Genetic Algorithm, Particle Swarm Optimization and Cuckoo Search. A comparative analysis of all the optimal solutions gained from each optimization method is performed, based on the values of the objective function, optimization parameters as well as several other specific motor parameters. For each optimized model a Finite Element Analysis is also performed in order to check and validate the quality of the results.

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