Many-objective shape optimisation of IPM motors for electric vehicle traction

Barba, Paolo Di; Mognaschi, Maria Evelina; Rezaei, Najmeh; Lowther, D.A.; Rahman, Tanvir

doi:10.3233/jae-191113

Cited by 19 publications

(8 citation statements)

References 8 publications

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“…where s j min and s j max are the lower and upper limits of each variable s j , respectively. An optimum design is focused on the rotor structure construction and is aimed at improving the motor performance [21][22][23][24]. The functional parameters taken into account during the optimization process are: (a) motor efficiency, (b) power factor and (c) starting capability.…”

Section: Formulation Of the Design Problemmentioning

confidence: 99%

Optimization of Low-Power Line-Start PM Motor Using Gray Wolf Metaheuristic Algorithm

Knypiński

Pawełoszek

Menach³

2020

Energies

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The paper presents the optimization method and computer software for the design of a low-power line-start permanent magnet synchronous motor (LSPMSM). The in-house-developed computer software was created with two independent modules: (a) the optimization procedure and (b) the numerical model of the motor. The optimization procedure used was a metaheuristic optimization method based on the gray wolf algorithm. Four design variables linked to the rotor structure were selected. The optimization process was performed from the rotor of a low-power induction motor (IM). The prototype of the motor (LSPMSM) was then built. The experimental measurements were performed for base the IM and optimized LSPMSM. The results of the measurements were compared for both motors. The experimental results confirmed the better performance of the designed motor in comparison to the induction motor.

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Section: Formulation Of the Design Problemmentioning

confidence: 99%

Optimization of Low-Power Line-Start PM Motor Using Gray Wolf Metaheuristic Algorithm

Knypiński

Pawełoszek

Menach³

2020

Energies

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“…can be confronted and taken into consideration in a wider optimisation search. Such a variety of solutions then can be additionally analysed using the Pareto approach (Di Barba et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation

Cvetkovski

Petkovska

2021

Power Electronics and Drives

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Both permanent magnet brushless DC motors and permanent magnet synchronous motors have attracted wide attention and are increasingly used in industrial high-performance applications in recent years. Those motors are known for their good electrical, magnetic and performance characteristics, but there is one parameter known as cogging torque that has a negative influence on the performance characteristics of the motor. This pulsating torque is generated as a result of the interaction between the stator teeth and the permanent magnets. The minimisation of the ripple of this torque in those permanent magnet motors is of great importance and is generally achieved by a special motor design which in the design process involves a variety of many geometrical motor parameters. In this research work, a novel approach will be introduced where two different nature-inspired algorithms, such as genetic algorithm (GA) and cuckoo search (CS) algorithm are used as an optimisation tool, in which the defined equation for the maximum value of the cogging torque is applied as an objective function. Therefore, a proper mathematical presentation of the maximum value of the cogging torque for the analysed synchronous motor is developed and implemented in the research work. For a detailed analysis of the three different motor models, the initial motor and the two optimised motor models are modelled and analysed using a finite element method approach. The cogging torque is analytically and numerically calculated and the results for all the models are presented.

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“…Their adoption must be analyzed in light of their suitability regarding the application specifications. They are complementary to the optimization approaches used at the components level [95][96][97][98]. Along with the reviewed techniques related to the design of permanent magnet synchronous machines, important improvements in the performance of electrical machines can be sought from the development of high-performance materials [89].…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Overview of Degrees of Freedom in the Design of PM Synchronous Machines

2021

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This contribution discusses the degrees of freedom that could be advantageously exploited in the conception of permanent magnet (PM) machines in the context of very demanding applications, such as electrical vehicle traction. The aim is to inventory degrees of freedom identified in scientific and technical literatures. Identifying these additional degrees of freedom will help positively respond to highly constrained design problems, which are appearing due to the higher usage of electrical energy in many industrial and consumer products. The goal is also to stimulate new ideas in the design of PM synchronous machines.

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Many-objective shape optimisation of IPM motors for electric vehicle traction

Cited by 19 publications

References 8 publications

Optimization of Low-Power Line-Start PM Motor Using Gray Wolf Metaheuristic Algorithm

Optimization of Low-Power Line-Start PM Motor Using Gray Wolf Metaheuristic Algorithm

Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation

Overview of Degrees of Freedom in the Design of PM Synchronous Machines

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