FE parameters sensitivity analysis of an industrial LS Interior PM Synchronous Motor

Abbas, Abdelaziz Y. M.; Yousef, Hassan; Sebakhy, O.A.

doi:10.1109/pes.2008.4595989

Cited by 12 publications

(2 citation statements)

References 2 publications

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“…In general, the design parameters of line start permanent magnet (LSPM) motors have a conflicting impact on the transient and the steady‐state operating performance of the motor [1, 2]. In particular, stronger rotor PMs can boost the overall efficiency and the power factor but it disrupts the start‐up process.…”

Section: Introductionmentioning

confidence: 99%

Analytical modelling and optimisation of line start LSPM synchronous motors

Ghahfarokhi

Aliabad

Boroujeni

et al. 2020

IET Electric Power Applications

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This study presents a comprehensive analytical analysis of line start permanent magnet (LSPM) synchronous motors in both steady-state and transient domains. The PM flux, the back-EMF and the winding inductances are first calculated in the steady-state based on the hybrid solution of magnetic circuit and the magnetic islands. Next, the motor voltage relations are mapped into an arbitrary d-q reference frame to dynamically assess the transient speed response as well as the individual motor torque components. Based on the presented analytical modelling, the parameters of the motor are optimised via genetic algorithm to maximise the back-EMF voltage and the overall steady-state performance. Given the parabolic relation between the back-EMF and the braking torque, the starting capability of the motor is defined as the optimisation constraint. Finally, the analytical results are verified by using a finite element analysis software package.

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Section: Introductionmentioning

confidence: 99%

Analytical modelling and optimisation of line start LSPM synchronous motors

Ghahfarokhi

Aliabad

Boroujeni

et al. 2020

IET Electric Power Applications

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show abstract

“…Although there are enormous investigations on studying the effect of model accuracy on PMSM performance calculations, inadequate research is dedicated to parameter sensitivity analysis of the PMSM performance. The parameters sensitivity to temperature, saturation and irreversible demagnetisation is studied in [9] for an interior PMSM. However, it does not provide numerical demonstrations and comparative analysis of various parameters' sensitivity.…”

Section: Introductionmentioning

confidence: 99%

Analytical modelling and parametric sensitivity analysis for the PMSM steady‐state performance prediction

Kazerooni

Hamidifar²,

Kar³

2013

IET Electric Power Applications

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Inaccuracy in the permanent magnet synchronous motor (PMSM) steady-state performance calculation corresponds to the parameter error and model imprecision. Accurate determination of the PMSM parameters may encounter various complications because of its rotor structure and drive design. Therefore PMSM performance calculation is generally vulnerable to inaccuracy because of the parameter error. This article studies the effect of parameter error on the inaccuracy of the performance calculations. Several methods for determining the PMSM armature resistance, flux linkage constant and d-and q-axis inductances with varying level of accuracy are proposed. The presented methods are applied to a laboratory PMSM and the sensitivity of the PMSM output power to the equivalent circuit parameters is analysed based on the experimental results. In addition, this study contributes to accurate performance estimations of the PMSM by developing a precise model that incorporates the saturation saliency and core losses. The accuracy of the proposed model is compared with the conventional dq-axis model and its higher accuracy is validated through experimental results. NomenclatureR a , L l armature resistance and leakage inductance N, p number of turns per phase and number of pole pairs L s armature stack effective length h M height of the permanent magnets g, g q air-gap length in d-and q-axis τ pole pitch a number of parallel paths σ electric conductivity s a conductor cross-sectional area λ f , E f flux linkage constant and excitation voltage k w stator winding coefficient B r remnant magnet flux density μ rrec relative recoil permeability μ 0 magnetic permeability of free space L d , L q d-and q-axis synchronous inductances λ ls per-slot leakage permeance s number of stator slots V DC-150% DC voltage corresponding to 150% of the rated current V DC-100% DC voltage corresponding to rated current I DC-150% DC current corresponding to 150% of the rated current I DC-100% DC current corresponding to rated current i(t), v(t) armature instantaneous current and voltage t time I DC PMSM steady-state DC current R CKT circuit resistance in the DC standstill test τ d , τ q time constants for d-and q-axis inductance measurements I a , V aphase 'a' current and voltage L aa phase 'a' self-inductance M ac mutual inductance between 'a' and 'c' phases ω s , ω r angular frequency of rotor and stator V t , I t stator terminal voltage and current a 0 , a 1 coefficients of L aa fitted curve b 0 , b 1 coefficients of M ac fitted curve θ, δ phase and torque angle S g r sensitivity of γ to ρ γ ex , γ cal experimental and calculated performance factor ρ act , ρ det actual value and determined value of the parameter E id , E iq d-and q-axis internal voltage R c , R ce , R ch core, eddy-current and hysteresis loss resistances L md , L mq d-and q-axis magnetising inductances I d , I q d-and q-axis currents V d , V q d-and q-axis voltages L md , L mq d-and q-axis inductances including the core loss

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Investigation of performance of fuzzy logic controllers optimized with the hybrid genetic-gravitational search algorithm for PMSM speed control

Ünsal

Aliskan

2022

Automatika

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FE parameters sensitivity analysis of an industrial LS Interior PM Synchronous Motor

Cited by 12 publications

References 2 publications

Analytical modelling and optimisation of line start LSPM synchronous motors

Analytical modelling and optimisation of line start LSPM synchronous motors

Analytical modelling and parametric sensitivity analysis for the PMSM steady‐state performance prediction

Investigation of performance of fuzzy logic controllers optimized with the hybrid genetic-gravitational search algorithm for PMSM speed control

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