• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.52 no.7
• /
• pp.320-326
• /
• 2003

Slotless Permanent Magnet Linear Synchronous Motor (PMLSM) has good control ability but thrust density is low. So, this paper proposes inserted core type of slotless PMLSM to improve its thrust density. Inserting the core between windings of each phase, detent force is generated by the difference of magnetic resistance in an air gap. To minimize detent force, this paper applies the neural network to inserted core type of slotless PMLSM. The, Magnetic pole ratio, the width of the inserted core and the width of the coil are selected as a design parameter to minimize detent force. In comparison with inserted core type one, thrust ripple greatly decreases by minimizing detent force and also thrust increases in this optimal model.

• Proceedings of the KIEE Conference
• /
• 2003.07b
• /
• pp.855-857
• /
• 2003

A slotless Permanent Magnet Linear Synchronous Motor (PMLSM) has good control ability but thrust density is low. So, this paper proposes inserted core type of slotless PMLSM to improve its low thrust density. Inserting the core between windings of each phase, detent force is generated by the difference of magnetic resistance in an air gap. To minimize detent force and maxize thrust, this paper applies the neural network to inserted core type of slotless PMLSM.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.53 no.9
• /
• pp.525-531
• /
• 2004

This paper proposes inserted core type of slotless Permanent Magnet Linear Synchronous Motor(PMLSM) to improve its low thrust density. However, by inserting the core between windings of each phase, detent force is generated and it acts as thrust ripple. Furthermore, linear motors generate end effect making thrust ripple. So, this paper applies the neural network to minimize detent force and to maximize thrust. Also, sub-poles is placed at the end parts of the mover to compensate end effect. To confirm of calculation method's validity, the calculated results are compared with experimental results.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.53 no.8
• /
• pp.463-468
• /
• 2004

This paper was applied space harmonic method as a characteristic analysis technique for slotless PMLSM. There is advantages of active response to the change of design parameters as well as reduction of the calculation time. The method can be overcome disadvantages of finite element analysis that needs long times calculation, repetitions of pre and post-process. In this paper, 3D-space harmonic method was applied to consider the precise description of end turn coil shape and the changes of characteristic according to changes of length of z-axis direction. The thrust of optimal design was performed using genetic algorithm to enhance the thrust which is the disadvantage of slotless type PMLSM. For design parameters, width of permanent magnet, width of coil, width of coil inner and lengths of z-axis direction were selected. For objective functions. thrust per weight. thrust per volume. multi-objective function was selected.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.51 no.7
• /
• pp.379-386
• /
• 2002

This paper deals with dynamic analysis method of a slotless type permanent magnet linear synchronous motor(PMLSM) using 3-dimensional space harmonic method. The results are good agreement with FEA results because that slotless type PMLSM has simple structure and no saturation of core. And then, Under open-loop control, starting characteristic is analyzed by voltage equation combining with dynamic equation. In order to obtain more accuracy results, this paper use instantaneous back-EMF and thrust instead of back-EMF constant and thrust constant.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
• /
• v.5B no.3
• /
• pp.262-266
• /
• 2005

In this paper, in order to enhance thrust of slotless type Permanent Magnet Linear Synchronous Motor, an optimal design is achieved by combining a genetic algorithm with 3D space harmonic method. In the case of multi-objective functions, the ratio of thrust/weight and thrust/volume are increased by $\7.56[%]l\;and\;7.98\[%]$, respectively. Thus, miniaturization and lightweight were realized at the same time.

• Proceedings of the KIEE Conference
• /
• 2003.07b
• /
• pp.849-851
• /
• 2003

This paper is deal with the method of design for optimum thrust model using genetic algorithms in slotless Permanent Magnet Linear Synchrous Motor (PMLSM). Characteristic analysis method is used 3D space harmonic analysis method. Design parameters are PM width and coil width.

• Proceedings of the KIEE Conference
• /
• 2003.10b
• /
• pp.39-41
• /
• 2003

This paper deals with the characteristics of the permanent magnet type linear synchronous motors(PMLSMs). Firstly, the structures and the characteristics of a slotted type and a slotless type PMLSM are compared. Secondly, the analyses and the design methods of each motor are presented. Finally, slotted type PMLSM and slotless type PMLSM are designed using the presented design method.

• Proceedings of the KIEE Conference
• /
• 2003.10b
• /
• pp.33-35
• /
• 2003

This paper proposes inserted core type of slotless Permanent Magnet Linear Synchronous Motor(PMLSM) to improve its low thrust density. However, by inserting the core between windings of each phase, detent force is generated. Furthermore, linear motors have the feature of structurally limited length. So, it causes the end-effect in actual operation. So, this paper applies the neural network to this model to minimize detent force and maximize thrust. Also, sub-poles used the to the end parts of the mover for compensating the end-effect.

• Proceedings of the KIEE Conference
• /
• 2002.11d
• /
• pp.94-96
• /
• 2002

This paper is deal with the method of redesign for optimum thrust model using Neural-Networks in Permanent Magnet Linear Synchrous Motor(PMLSM). This method is saved time compared with design method using only Finite Element Method(FEM). In this paper data sets for training Neural-Networks obtained using 2D FEM. To confirm the validity of the data sets for training Neural-Networks optimum values of that Is compared with results of FEM. And then. this method is verified that it could be applied to the design for Slotless type PMLSM.