Model-based loss minimization for DC and AC vector controlled motors including core saturation

Fernandez-Bernal, F.; García-Cerrada, Aurelio; Faure, R.

doi:10.1109/ias.1999.805957

Cited by 62 publications

(17 citation statements)

References 23 publications

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“…4(a) can easily be derived from (3) and (5) and Fig. 4(b) can easily be derived from (4) and (6) considering that the terms with differentiation will be zero in steady state [8].…”

Section: Induction Motor Modelmentioning

confidence: 99%

“…This approach is utilized in an even more simplified form by rearranging the stator resistor [5]. The same approach is utilized by Bernal et al [6] in deriving a generalized model for the different types of motor. However, in the loss models used in [4]- [6], the leakage inductance is neglected in order to simplify the induction motor equivalent circuit.…”

Section: Introductionmentioning

confidence: 99%

“…The same approach is utilized by Bernal et al [6] in deriving a generalized model for the different types of motor. However, in the loss models used in [4]- [6], the leakage inductance is neglected in order to simplify the induction motor equivalent circuit. Lim et al [7] developed a simplified loss model without sacrificing the leakage inductance, but the developed expression for an optimum flux level has a different format from the one in [4].…”

Section: Introductionmentioning

confidence: 99%

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Using of Particle Swarm Optimization for Loss Minimization of Vector-controlled Induction Motors

Rashtchi¹,

Bizhani²

2015

ujeee

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This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a tradeoff between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

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“…4(a) can easily be derived from (3) and (5) and Fig. 4(b) can easily be derived from (4) and (6) considering that the terms with differentiation will be zero in steady state [8].…”

Section: Induction Motor Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Using of Particle Swarm Optimization for Loss Minimization of Vector-controlled Induction Motors

Rashtchi¹,

Bizhani²

2015

ujeee

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“…In addition, the motor does not need brushes for excitation current, since the excitation flux is produced by the permanent magnets. Several control techniques for power loss minimization procedures with different approaches have been presented in literature [19]- [21]. Generally, these approaches can be classified into two main categories: the "loss model control" and the "search control".…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation on high efficiency real-time control algorithms for IPMSMs

Caruso

Tommaso

Genduso

et al. 2014

2014 International Conference on Renewable Energy Research and Application (ICRERA)

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This paper describes an experimental investigation on the power losses variations occurring in an Interior Permanent Magnet Synchronous Motor (IPMSM) with respect to the direct axis current component. Such investigation can be useful to determine a mathematical model accounting for copper, iron and mechanical friction losses, and for the arrangement of a speed control drive system equipped with a real-time power losses minimization algorithm. In particular, a test bench has been set up in order to carry out all measurements and the final power loss identification. The test bed is composed by a IPMSM drive with a field oriented control (FOC) strategy, a power analyzer, a dynamometric brake and a computer for data storage and processing. The experimental investigation was carried out by making several tests at different speed, magnetization and load conditions. From the obtained results, it can be stated that the power losses occurring in the IPMSM can be minimized by acting on the direct axis current component, increasing, therefore, the efficiency, without decreasing the dynamic performances of the drive

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“…MODEL DESCRIPTION A widely used model for IPMSM based on a synchronous d-q reference frame [5], including iron losses (Rc) [6] [7], is presented in Fig. 1.…”

mentioning

confidence: 99%

Determination of parameters in interior permanent magnet synchronous motors with iron losses without torque measurement

Fernandez-Bernal

García-Cerrada²,

Faure³

Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on In

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Abstruct-This paper proposes systematic procedures to estimate the circuit parameters of an inverter-fed vector controlled interior permanent magnet synchronous motor when torque measurement is not available.The methodology presented here does not neglect iron losses. New procedures have been developed and justified, because international standard recommendations (IEC standards) cannot be applied.Experimental results from a test rig will be presented in the paper to validate the most important contributions. Thanks to the procedures proposed, secondary effects on the motor parameters, like saturation or frequency dependency, have been evaluated. SYMBOLS AND DEFINITIONS Ld, Lqm P Pcu, Pfe Rs, Rc Rated rms. line current and phase voltage. Airgap current space vector in pu. Equivalent iron-loss current space vector in pu. Input current space vector in pu. Hysteresis and eddy losses in pu at rated flux and rated frequency. d-axis and q-axis inductances in pu. Electromagnetic torque in pu. Pole pairs. Copper losses and iron losses in pu. Equivalent stator copper-loss and iron-loss resistances in pu. Value of Rc at rated frequency. Rated electrical period. Airgap voltage space vector in pu. Input voltage space vector in pu. Airgap flux space vector produced by the permanent magnets in pu. Total airgap flux space vector in pu. Angular speed in pu. Angular frequency in pu. Rated angular speed. Base units Base voltage and current: VB = f i .VN Base angular speed: OB = ON Base angular frequency: qB = P.Q = P.Q Base torque: MB = PB I Q = 3'VN.IN I Q Base inductance: LB = VB I (IB .%e)

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Model-based loss minimization for DC and AC vector controlled motors including core saturation

Cited by 62 publications

References 23 publications

Using of Particle Swarm Optimization for Loss Minimization of Vector-controlled Induction Motors

Using of Particle Swarm Optimization for Loss Minimization of Vector-controlled Induction Motors

Experimental investigation on high efficiency real-time control algorithms for IPMSMs

Determination of parameters in interior permanent magnet synchronous motors with iron losses without torque measurement

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