Relationship of Parallel Model and Series Model for Permanent Magnet Synchronous Motors Taking Iron Loss Into Account

Urasaki, Naomitsu; Senjyu, Tomonobu; Uezato, K.

doi:10.1109/tec.2004.827291

Cited by 55 publications

(15 citation statements)

References 12 publications

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“…From that, L d (I dc ) is easily derived. The method takes also into account the iron losses [22], through the estimation of the parallel equivalent resistance R i , in the inverse-Γ model of Fig. 4.…”

Section: Direct Inductance Estimationmentioning

confidence: 99%

Torque Estimation in High-Efficency IPM Synchronous Motor Drives

Tinazzi

Zigliotto

2015

IEEE Trans. Energy Convers.

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In modern electrical drives, the energy saving starts with the careful generation of the electromagnetic torque, which involves the electrical motor and its current control. A modern choice is represented by an anisotropic synchronous permanent magnet (IPM) motor combined with the maximum torque per ampere (MTPA) control technique. The MTPA locus brings along additional information that is worth deepening. In particular, this paper shows that a proper rearrangement of the torque expression in MTPA condition, merged with a simple leastsquare\ud algorithm, returns an accurate on-line estimation of the electromagnetic torque. The effectiveness of the proposed method is proved by a worked out example, based on a IPM drive model fitted with finite-element analysis and experimental measurements, including motor saturation effects. The torque estimator extends its usability in the whole working region of the drive, even during transients outside the MTPA curve, and it comes almost for free. In this, the proposed method should be technically sound in many industrial applications

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Section: Direct Inductance Estimationmentioning

confidence: 99%

Torque Estimation in High-Efficency IPM Synchronous Motor Drives

Tinazzi

Zigliotto

2015

IEEE Trans. Energy Convers.

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“…In those studies, iron losses are modeled as the thermal power dissipated on an "iron-loss" resistance placed in series, or in parallel, to the conventional PMSM equivalent circuits. From a modeling point of view, it has been found that there is substantial equivalence between series and parallel types [17]. Hereafter, the latter will be chosen for its better adherence to the physical meaning [17].…”

Section: Motor Modelmentioning

confidence: 99%

“…From a modeling point of view, it has been found that there is substantial equivalence between series and parallel types [17]. Hereafter, the latter will be chosen for its better adherence to the physical meaning [17]. The PMSM voltage balance equations in a stationary α-β reference frame are the following:…”

Section: Motor Modelmentioning

confidence: 99%

Commissioning of Electromechanical Conversion Models for High Dynamic PMSM Drives

Bolognani

Peretti

Zigliotto

et al. 2010

IEEE Trans. Ind. Electron.

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Several emerging applications require fast and precise torque control. Torque measurements are still expensive, bulky, and delicate. On the other hand, estimation techniques are all valid in principle, but their accuracy is largely affected by model identification and commissioning. This paper presents an accurate model for an effective torque estimation based on voltage and current measurements. The model includes all motor losses to get an enhanced overall accuracy, along with a fast response. The key feature is the commissioning procedure, based on a set of offline measurements. Procedure details and experimental results on a laboratory prototype are included

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“…The power source is realized using a voltage source inverter (VSI) with the triangular wave carrier. The effects of magnetic saturation, as well as iron loss, are incorporated with the mathematical model of the IPMSM, i.e., the q-axis inductance, which is the function of the q-axis current [2], and the iron loss resistance, which is the function of the electrical angular velocity [8], are applied to the model. The parameters L d and L q are identified by the RLS method, while the parameters R, K e , and R i are identified by the CGAI method.…”

Section: Identification Of R K E and R Imentioning

confidence: 99%

Wide-speed Range Operation of Interior Permanent Magnet Synchronous Motor with Parameter Identification

Urasaki

Noguchi

Howlader

et al. 2009

Electric Power Components and Systems

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To realize the maximum efficiency control and/or flux-weakening control for interior permanent magnet synchronous motors, exact motor parameters are typically required. It is well known that motor parameters vary with driving conditions such as temperature and magnetic saturation. In this article, the effect of parameter variations on the performance of maximum efficiency control and fluxweakening control are quantitatively investigated. Then, an on-line parameter identification method is proposed to prevent parameter variation from degrading the control performance. This method simultaneously identifies motor parameters involved in the control strategies by using both the recursive least-squares method and constant gain adaptive identification method. The effectiveness of the maximum efficiency control and flux-weakening control incorporated with on-line parameter identification strategy is confirmed by computer simulations.

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Relationship of Parallel Model and Series Model for Permanent Magnet Synchronous Motors Taking Iron Loss Into Account

Cited by 55 publications

References 12 publications

Torque Estimation in High-Efficency IPM Synchronous Motor Drives

Torque Estimation in High-Efficency IPM Synchronous Motor Drives

Commissioning of Electromechanical Conversion Models for High Dynamic PMSM Drives

Wide-speed Range Operation of Interior Permanent Magnet Synchronous Motor with Parameter Identification

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