Enhanced Field Reconstruction Method for the Efficient Analysis of Permanent Magnet Synchronous Machines

Deken, B.; Pekarek, Steven

doi:10.1109/tec.2012.2204755

Cited by 8 publications

(8 citation statements)

References 17 publications

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“…The fault inductance is given as (),

L_{A B f} (θ_{m}) = \frac{μ_{0} . r . l}{g_{a}} \int_{0}^{2 π} N_{A f} (ϕ) . N_{B f} (ϕ) d ϕ

where

N_{A f} (ϕ)

and

N_{B f} (ϕ)

is the WF of the windings under fault conditions. For the current study where the machine winding of phase a is shorted at 33.3% winding (Figure 15a), and the fault inductance measured practically is found to be L sf = 0.049 mH which validates [19]. The fault L sf as shown in Figure 15b is remodelled in the hybrid BLDC motor to investigate the machine performance under subjected conditions.…”

Section: Remodelling Of Winding Inductances and Magnetic Fields In A Hybrid Bldc Motorsupporting

confidence: 70%

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

Usman

Rajpurohit

2020

IET Electrical Syst in Trans

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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.

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“…The fault inductance is given as (),

L_{A B f} (θ_{m}) = \frac{μ_{0} . r . l}{g_{a}} \int_{0}^{2 π} N_{A f} (ϕ) . N_{B f} (ϕ) d ϕ

where

N_{A f} (ϕ)

and

N_{B f} (ϕ)

Section: Remodelling Of Winding Inductances and Magnetic Fields In A Hybrid Bldc Motorsupporting

confidence: 70%

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

Usman

Rajpurohit

2020

IET Electrical Syst in Trans

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“…After the sweep, since the air-gap of the LTPMM is finite, it is necessary to shift the position of the air-gap flux distribution corresponding to the mover movement. The sweeping and shifting are performed simultaneously in (12)- (13).…”

Section: B Basis Function : Movermentioning

confidence: 99%

“…The previous research work on the FRM has focused on the applications, such as axial flux PM motors [6]- [8], switched reluctance machines [9], PM synchronous machines [10]- [13], and induction machines [14]- [15]. Park et al [6] and Ajily et al [7] presented the performance of axial flux PM motors using the 3-D FRM.…”

Section: Introductionmentioning

confidence: 99%

Field Reconstruction Method for Linear Tubular Permanent Magnet Motor

Kim

Woo

2020

IEEE Access

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This paper considers a linear tubular permanent magnet motor (LTPMM) for an active suspension system. The LTPMM has an end effect due to its structure. This can be an important factor for analysis and design of the LTPMM because it distorts the air-gap magnetic flux distribution. The field reconstruction method (FRM) was developed for an effective evaluation of the magnetic field in the electric machine. It can reduce the computation time using the basis-function which reconstructs the air-gap magnetic flux distribution with a static finite element analysis. In this paper, we adopted the FRM to evaluate the LTPMM. However, the FRM has been applied only to the rotating machines and does not take into account the distortion of the magnetic flux distribution in the LTPMM. To deal with this problem, we proposed an enhanced FRM with new basis-function. The proposed method is verified by comparing between experiment result, conventional and enhanced FRM. INDEX TERMS Active suspension system, linear active suspension, linear permanent magnet motor, field reconstruction method.

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“…• No deformation in stator or rotor core structures due to internal forces • No saturation condition • Zero flux density in the axial direction • No end-coil effect • Hysteresis and eddy currents are neglected To improve the existing FRMs, three versions of the FRMs VOLUME 1, 2021 have been proposed in [5]- [7] during the last decade. These FRMs included the interaction between the magnets and stator teeth, and slotting effect.…”

Section: Introductionmentioning

confidence: 99%

Field Reconstruction for Modeling Multiple Faults in Permanent Magnet Synchronous Motors in Transient States

2021

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Conventional field reconstruction model (FRM) for electrical machines has proved its main strength in efficient computations of magnetic fields and forces in healthy permanent magnet synchronous machines (PMSM) or faulty machines in steady states. This study aims to develop a magnet library of different magnet defects and include inter-turn short-circuit (ITSC) in the FRM for PMSM. The developed FRM can model a combination fault between ITSC, and magnet defect in a PMSM in transient states. Within the framework, an 8-turn ITSC was modelled in both finite element analysis (FEA) and FRM, and then identified by the extended Park's vector approach. The air-gap magnetic field reproduced by the FRM shows a good agreement with the result from time-stepping FEA. The computation speed is over 1000 times faster than an equivalent time-stepping FEA. The suggested FRM allows for quickly understanding effect of faults in the rotor and stator on the air-gap magnetic flux density and identifying unique signatures for such defects.

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Enhanced Field Reconstruction Method for the Efficient Analysis of Permanent Magnet Synchronous Machines

Cited by 8 publications

References 17 publications

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

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

Field Reconstruction Method for Linear Tubular Permanent Magnet Motor

Field Reconstruction for Modeling Multiple Faults in Permanent Magnet Synchronous Motors in Transient States

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