A core analysis of the synchronous reluctance motor for automotive applications

Taghavi, Seyedmorteza; Pillay, Pragasen

doi:10.1109/icelmach.2014.6960297

Cited by 21 publications

(8 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As ξ is directly dependent on the rotor topology, then it needs to be properly defined. The typical saliency ratio value is ξ ≤ 10 for TLA and ξ >10 for ALA [12]. From all the above, it can be concluded that the main parameters that define the saliency ratio are the magnetizing coefficients given by (6).…”

Section: B Linear Sizingmentioning

confidence: 90%

“…Few assumptions can be made as discussed in Sec. II, referring to equation for saliency ratio estimation (12), which later on can be adjusted according to (32) -(33).…”

Section: Sizing Methodsmentioning

confidence: 99%

“…2) The main sizing step is the rotor diameter Dro estimation (13). 3) Using equations ( 6) - (11) and the predefined saliency ratio (12), the main d-q parameters can be estimated. At this point the number of turns for ( 7) -( 10) and ( 12) -( 13) is not considered.…”

Section: Sizing Methodsmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Sizing Approach for Synchronous Reluctance Machines

Murataliyev

Galea

2021

IEEE Trans. Ind. Electron.

View full text Add to dashboard Cite

This paper presents a simple analytical model for the sizing of Synchronous Reluctance (SynRel) machines. The accuracy of the method is achieved by modelling a simple rotor geometry that presents all the characteristics of a real machine. The analytical equations proposed are able to guarantee accurate and fast results during the preliminary design of the machine.A generalized sizing approach, based on the saliency ratio, is presented in detail. The method is flexible and can be adapted for any SynRel machine. The accuracy of the proposed model is validated, for a range of operating conditions, comparing the results with both finite element simulations and experimental measurement carried out from an existing four poles SynRel 15kW prototype.

show abstract

Section: B Linear Sizingmentioning

confidence: 90%

“…Few assumptions can be made as discussed in Sec. II, referring to equation for saliency ratio estimation (12), which later on can be adjusted according to (32) -(33).…”

Section: Sizing Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Sizing Approach for Synchronous Reluctance Machines

Murataliyev

Galea

2021

IEEE Trans. Ind. Electron.

View full text Add to dashboard Cite

show abstract

“…6)). It is suggested in [21], [23], and [30], that if the difference of the number of stator slots per pair of poles (ns) and the number of rotor slots per pair of poles (nr) equals to ±4, then a more reasonable result will be achieved [29], [30]. The distances between the flux barriers, (Sk), is calculated by equation ( 20): Where fdh is the magneto-motive force along the d axis and h=2… K [ 29].…”

Section: Fig 7 Herementioning

confidence: 99%

Analytical Method to Optimum design of Synchronous Reluctance Motor for Electric Scooter Application

Salehinia

Afjei²,

Hekmati

2021

Scientia Iranica

View full text Add to dashboard Cite

In recent years, synchronous reluctance motor (SynRM) has attracted the attention of researchers and well-known companies have been involved in designing and manufacturing electric motors due to its simplicity. The current study aimed to provide a comprehensive approach to design a series of SynRMs using both combined methods and finite element analysis to achieve an algorithm which is based on the similarity between flux lines and the shape of flux barriers to achieve both maximum torque and minimum torque ripple. In this paper, a SynRM is designed for a specific electric vehicle. Consequently, study cases with a different number of both flux barriers and poles, are analyzed and optimized in each case. Finally, the optimal specifications of the motors are compared in different cases and the best one is selected. Accordingly, the design parameters are identified and optimized through the Taguchi method and then, the obtained results are evaluated through finite element analysis. To achieve both maximum torque and minimum torque ripple in a range of power between 150 to 750 watts, three different number of poles with a constant number of slots (per pole per phase) at the same size for all the described motors are considered. The validity of the proposed method is confirmed through the experimental test results.

show abstract

“…Synchronous reluctance (SynRel) motor is attracting an increasing interest due to its wide speed range, low cost, and robust structure [1]. However, this type of machine presents some drawbacks, such as low power factor [2] and high torque ripple [3], which limits the application of SynRel motor to some areas.…”

Section: Introductionmentioning

confidence: 99%

Artificial Monitoring of Eccentric Synchronous Reluctance Motors Using Neural Networks

Shu-guang¹,

Li²,

Zhao³

et al. 2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

This paper proposes an artificial neural network for monitoring and detecting the eccentric error of synchronous reluctance motors. Firstly, a 15 kW synchronous reluctance motor is introduced and took as a case study to investigate the effects of eccentric rotor. Then, the equivalent magnetic circuits of the studied motor are analyzed and developed, in cases of dynamic eccentric rotor and static eccentric rotor condition, respectively. After that, the analytical equations of the studied motor are derived, in terms of its air-gap flux density, electromagnetic torque, and electromagnetic force, followed by the electromagnetic finite element analyses. Then, the modal analyses of the stator and the whole motor are performed, respectively, to explore the natural frequency and the modal shape of the motor, by which the further vibrational analysis is possible to be conducted. The vibration level of the housing is furtherly studied to investigate its relationship with the rotor eccentricity, which is validated by the prototype test. Furthermore, an artificial neural network, which has 3 layers, is proposed. By taking the air-gap flux density, the electromagnetic force, and the vibrational level as inputs, and taking the eccentric distance as output, the proposed neural network is trained till the error smaller than 5%. Therefore, this neural network is obtaining the input parameters of the tested motor, based on which it is automatically monitoring and reporting the eccentric error to the upper-level control center.

show abstract

A core analysis of the synchronous reluctance motor for automotive applications

Cited by 21 publications

References 20 publications

A Novel Sizing Approach for Synchronous Reluctance Machines

A Novel Sizing Approach for Synchronous Reluctance Machines

Analytical Method to Optimum design of Synchronous Reluctance Motor for Electric Scooter Application

Artificial Monitoring of Eccentric Synchronous Reluctance Motors Using Neural Networks

Contact Info

Product

Resources

About