Condition monitoring of a surface mounted permanent magnet-type brushless direct current motor using remodelling of rotor magnetic field and stator winding inductance

IF 1.9 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Adil Usman, Bharat Singh Rajpurohit
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引用次数: 2

Abstract

The high-performance characteristics of brushless direct current (BLDC) motor has made them indispensable for electric vehicle (EV) applications. The physical replacement of rotor windings with the permanent magnets on the rotor, makes the BLDC motor more compact, generating high torque-power density. However, the continuous operation of BLDC motors in EVs make them vulnerable to faults. Develops the surface mounted permanent magnet-type BLDC motor under healthy and fault conditions using remodelling of stator winding inductances and rotor magnetic fields of a machine. The stator winding inductance (LS) is modelled using winding function theory depending on the physical distribution of a winding, while the rotor magnetic field (Bg) is modelled through magnetic equivalent circuit based approach, respectively. Both the machine quantities under healthy operating conditions are estimated based on the motor geometry and validated numerically using finite element based methods. The experimental investigation validates the results obtained through given modelling techniques. The experimental and numerically obtained data of LS and Bg are then remodelled in a BLDC motor, to investigate the hybrid performance of a machine, useful in diagnosis of faults. The results obtained are further used to classify the faults and estimate its severity.

Abstract Image

基于转子磁场和定子绕组电感重构的表面安装永磁体型无刷直流电机的状态监测
无刷直流电机的高性能特性使其在电动汽车应用中不可或缺。用转子上的永磁体物理替换转子绕组,使无刷直流电机更加紧凑,产生高转矩功率密度。然而,电动汽车中无刷直流电机的连续运行使其容易发生故障。利用机器定子绕组电感和转子磁场的重塑,开发了在健康和故障条件下的表面安装永磁体型无刷直流电机。定子绕组电感(LS)根据绕组的物理分布使用绕组函数理论建模,而转子磁场(BG)分别通过基于磁等效电路的方法建模。健康运行条件下的两个机器数量都是基于电机几何形状进行估计的,并使用基于有限元的方法进行数值验证。实验研究验证了通过给定的建模技术获得的结果。然后在无刷直流电机中对实验和数值获得的LS和BG数据进行重构,以研究机器的混合性能,对故障诊断有用。所获得的结果被进一步用于对故障进行分类并估计其严重程度。
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来源期刊
CiteScore
5.80
自引率
4.30%
发文量
18
审稿时长
29 weeks
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