Abstract
This paper presents a rigorous design and optimization of an axial flux microelectromechanical systems (MEMS) brushless dc (BLDC) micromotor with dual rotor improving both efficiency and power density with an external diameter of only around 10 mm. The stator is made of two layers of windings by MEMS technology. The rotor is developed by film permanent magnets assembled over the rotor yoke. The characteristics of the MEMS micromotor are analyzed and modeled through a 3-D magnetic equivalent circuit (MEC) taking the leakage flux and fringing effect into account. Such a model yields a relatively accurate prediction of the flux in the air gap, back electromotive force (EMF) and electromagnetic torque, whilst being computationally efficient. Based on 3-D MEC model the multi-objective firefly algorithm (MOFA) is developed for the optimal design of this special machine. Both 3-D finite element (FE) simulation and experiments are employed to validate the MEC model and MOFA optimization design.
Highlights
Micromotors are indispensable for driving microelectromechanical systems (MEMS)
40.2 μN ∙ m when the speed of the motor is 20,000 rpm, which is consistent with the simulation result and validates the analytical calculations used during the multi-objective firefly algorithm (MOFA) optimization
An MEMS brushless dc (BLDC) micromotor has been developed with improvement of both power density and efficiency
Summary
Micromotors are indispensable for driving microelectromechanical systems (MEMS). There are many types of micromotors, such as electrostatic, piezoelectric and electromagnetic ones. The first electromagnetic systems assembled with permanent magnets were reported in 2006 [2] Rare earth magnets such as neodymium-iron-boron (NdFeB) are often used in these micromotors to provide for high energy density. 3.78 nNm due to its micro dimensions (external diameter is 2.6 mm) For real applications, such as microrobotics and microaircraft to be competitive, micromotors need to simultaneously have a high output torque density and high efficiency. Multiobjective FA (MOFA) was further developed by Xin-She Yang later in 2012 [11] Such a multiobjective algorithm is powerful in dealing with design problems in electrical machines with a large number of design variables and multiple objectives under complex nonlinear constraints.
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