Limitations/capabilities of electric machine technologies and modeling approaches for electric motor design and analysis in plug-in electric vehicle applications

Yılmaz, Murat

doi:10.1016/j.rser.2015.07.033

Cited by 68 publications

(75 citation statements)

References 237 publications

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“…The common goal of the design processes is to determine a geometry of stator and rotor, which meet certain requirements and boundary conditions. A general overview of different procedures regarding the design optimization problem can be found in [12][13][14]. In the upcoming sections a deeper insight into deterministic and stochastic methods will be given.…”

Section: Recent Design Optimization Methodsmentioning

confidence: 99%

Recent Design Optimization Methods for Energy-Efficient Electric Motors and Derived Requirements for a New Improved Method—Part 1

Schmelcher

Büning

Kreisköther

et al. 2018

The Economy, Sustainable Development, and Energy International Conference

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Energy-efficient electric motors are gathering an increased attention since they are used in electric cars or to reduce operational costs, for instance. Due to their high efficiency, permanent-magnet synchronous motors are used progressively more. However, the need to use rare-earth magnets for such high-efficiency motors is problematic not only in regard to the cost but also in socio-political and environmental aspects. Therefore, an increasing effort has to be put in finding the best design possible. The goals to achieve are, among others, to reduce the amount of rare-earth magnet material but also to increase the efficiency. In the first part of this multipart paper, characteristics of optimization problems in engineering and general methods to solve them are presented. In part two, different approaches to the design optimization problem of electric motors are highlighted. The last part will evaluate the different categories of optimization methods with respect to the criteria: degrees of freedom, computing time and the required user experience. As will be seen, there is a conflict of objectives regarding the criteria mentioned above. Requirements, which a new optimization method has to fulfil in order to solve the conflict of objectives will be presented in this last paper.

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Section: Recent Design Optimization Methodsmentioning

confidence: 99%

Recent Design Optimization Methods for Energy-Efficient Electric Motors and Derived Requirements for a New Improved Method—Part 1

Schmelcher

Büning

Kreisköther

et al. 2018

The Economy, Sustainable Development, and Energy International Conference

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show abstract

“…In [14], the author states the objective of the specifications is to translate the function of the driven-load into the terms of electric drives, providing a classification of characteristics of the system with examples. An application example demanding special requirements on electric motors is presented in [15].…”

Section: Tailor-made Solutions Approachmentioning

confidence: 99%

A Requirement Engineering Framework for Electric Motors Development

et al. 2018

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The applications using electric motors have increased in the last decade. Some of these applications encounter the need for tailor-made motors that must meet demanding requirements. Therefore, the specification stage of an electric motor is a critical part of its development. If this stage is properly addressed, then future failures in the development process can be avoided. This paper presents a requirement engineering framework to support small-medium electric motors designers/manufacturers with the development of their product. The framework identifies the stakeholders and the tasks that they should undertake to finish a successful requirements specification stage. The framework is made from the designer/manufacturer’s perspective and it emphasizes the derivation of specialized requirements (lower-level). The result of the framework is well-defined requirements that form the design requirements specification of the motor that leads to the beginning of the design stage.

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“…PMBLAC has fractional slot due to its slot/pole ratio. In general, PMBLAC can be modeled using three modeling techniques, namely analytical model, magnetic equivalent circuit (MEC), and finite element analysis (FEA) [6,9]. The analytical model has the shortest computational time compared to MEC and FEA models, whereas MEC is computationally shorter than FEA [7,9].…”

Section: Introductionmentioning

confidence: 99%

“…In general, PMBLAC can be modeled using three modeling techniques, namely analytical model, magnetic equivalent circuit (MEC), and finite element analysis (FEA) [6,9]. The analytical model has the shortest computational time compared to MEC and FEA models, whereas MEC is computationally shorter than FEA [7,9]. FEA has the longest computational time, but highest torque accuracy and magnetic loss estimation, as well as better design flexibility [8,9].…”

Section: Introductionmentioning

confidence: 99%

“…The analytical model has the shortest computational time compared to MEC and FEA models, whereas MEC is computationally shorter than FEA [7,9]. FEA has the longest computational time, but highest torque accuracy and magnetic loss estimation, as well as better design flexibility [8,9]. Despite the advantage of computational effort, the analytical model has few disadvantages such as less accuracy, less flexible compared to FEA, and incapable of 3-D effect.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimization of surface-mounted permanent magnet brushless AC motor using analytical model and differential evolution algorithm

Mohamed

Ishak

2019

Journal of Electrical Engineering

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This paper discusses the optimization of surface-mounted permanent magnet brushless AC (PMBLAC) motor using Analytical Sub-domain model with Differential Evolution Algorithm (ASDEA). Only two regions were considered in this analytical sub-domain model, ie magnet and airgap regions, with assistance of Complex Relative Permeance Function (CRPF) to account for the stator slotting effect. Five machine parameters were chosen to be optimized, namely the magnet arc-pole-pitch ratio, slot opening width, magnet thickness, airgap length and stator inner radius. The optimization process has four objectives, ie minimum torque ripple, low cogging torque, high efficiency, and high output torque. The results from the optimized ASDEA were compared with the Analytical Sub-domain Genetic Algorithm (ASGA) and further validated against 2-D finite element model (FEM). Results show a good agreement between analytically optimized models and finite element model. The ASDEA has faster computational time compared to ASGA, and this provides benefit in terms of reducing the machine design parameterization time and less redundancy work required to achieve motor design specifications.

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Limitations/capabilities of electric machine technologies and modeling approaches for electric motor design and analysis in plug-in electric vehicle applications

Cited by 68 publications

References 237 publications

Recent Design Optimization Methods for Energy-Efficient Electric Motors and Derived Requirements for a New Improved Method—Part 1

Recent Design Optimization Methods for Energy-Efficient Electric Motors and Derived Requirements for a New Improved Method—Part 1

A Requirement Engineering Framework for Electric Motors Development

Optimization of surface-mounted permanent magnet brushless AC motor using analytical model and differential evolution algorithm

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