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A Practical Thermal Model for the Estimation of Permanent Magnet and Stator Winding Temperatures
(2014)
A thermal model for the determination of the temperatures of interior permanent magnets and stator windings is presented in this paper. The innovation of the model relies on one temperature sensor being located in the stator core of the machine. Such sensor is simple to implement in many applications such as traction or EV, where reliability is critical. The estimated stator winding and permanent magnet temperatures are determined by a simplified thermal lumped element network model with only two time constants. It is shown that the proposed thermal model is very robust due to the structure of the model and the measured stator core temperature. The distortion of the temperature estimates caused by the cooling circuit is inherently accounted for such that the model can be used for robust online prediction of temperatures. Experimental results based on a forced water-cooled interior permanent magnet synchronous machine setup are presented to validate the effectiveness of the presented model.
Condition monitoring of rotor problems such as demagnetization and eccentricity in permanent magnet synchronous motors (PMSM) is essential for guaranteeing high motor performance, efficiency, and reliability. However, there are many limitations to the off-line and on-line methods currently used for PMSM rotor quality assessment. In this paper, an inverter-embedded technique for automated detection and classification of PMSM rotor faults is proposed as an alternative. The main concept is to use the inverter to perform a test whenever the motor is stopped, to detect rotor faults independent of operating conditions or load torque oscillations, which is not possible with motor current signature analysis (MCSA). The d-axis is excited with a dc+ac signal, and the variation in the inductance pattern due to the change in the degree of magnetic saturation caused by demagnetization or eccentricity is observed for fault detection. An experimental study on a 7.5kW PMSM verifies that demagnetization and eccentricity can be detected and classified independent of the load with high sensitivity.
The majority of the work performed for detecting eccentricity faults for permanent magnet synchronous motors (PMSM) focus on motor current signature analysis (MCSA), as it provides continuous on-line monitoring with existing current sensors. However, MCSA cannot be applied under nonstationary conditions and cannot distinguish faults with load torque oscillations, which are limitations for many PMSM drive applications. In this paper, it is shown that the d-axis inductance, L d , decreases with increase in the severity of eccentricity due to the change in the degree of magnetic saturation, and it is proposed as a new fault indicator. The inverter can be used to perform a standstill test automatically whenever the motor is stopped, to measure L d for eccentricity testing independent of load variations or oscillations, which is not possible with MCSA. An FE and experimental study on a 10hp PMSM verifies that eccentricity can be detected independent of the load with high sensitivity and reliability.
In this paper a new model for the estimation of the stator winding and rotor cage temperatures of induction machines is presented. This model can be used in series applications of machines operated under dynamic load conditions where stator and rotor temperature shall be monitored. The proposed model relies on a simplified lumped element thermal equivalent circuit model where the stator core temperature serves as input quantity. The great advantage of this model is that it covers ambient and cooling conditions inherently. This leads to great simplicity and robustness. The parametrization and validation of the model through experimental data is presented. Advantages, drawbacks and possible implementations are discussed.
Innovative thermal model for the estimation of permanent magnet and stator winding temperatures
(2012)
In this paper an innovative thermal model for the determination of the temperatures of the permanent magnets and stator windings is presented. This model relies on one temperature sensor located in the stator core of the machine. The estimated stator winding and permanent magnet temperatures are determined by a simplified thermal lumped element network model with only two time constants. Due to the structure of the model and the measured stator core temperature the proposed thermal model is very robust. Distortion of the cooling circuit are inherently sensed such that the model can be used for the online prediction of temperatures. Experimental results based on an interior permanent magnet synchronous machine are presented to validate the presented model.