Rotor Temperature Estimation Research Articles

Thermal analysis and temperature evaluation on a magnetic‐geared dual‐rotor machine

AbstractThe thermal performance of the magnetic‐geared dual‐rotor machine (MGDRM) is investigated. Because the effective component in the outer airgap magnetic field harmonics is low, the torque production of MGDRM cannot match the regular permanent magnetic synchronous machine (PMSM). Although the analysis shows that the torque generation of the MGDRM is weak, this conclusion is limited in the electromagnetic field. The MGDRM outer rotor should also be considered from the thermal aspect, and the effect on the torque generation should be valued in particular. The outer rotor thermal buffer effect blocks the heating flow from the winding to the inner rotor magnets. Thus, the MGDRM can withstand a heavy electrical load in a short period, producing higher torque. With this understanding, the torque production ability of the MGDRM can extend to a higher level, even close to the regular PMSM. To validate the analysis, a MGDRM machine is prototyped, and the dual‐rotor temperature information acquisition is realised by a wireless data collection. The rotor temperature estimation technology on the dual‐rotor is then investigated as an auxiliary function. The estimation error can be limited around 5°C, which is good for warning the thermal risk. And thus the MGDRM overheating can be safely adopted to extend the torque generation.

Robust Rotor Temperature Estimation of Permanent Magnet Motors for Electric Vehicles

As the mainstream powertrain of electric vehicles, permanent magnet motors are facing the challenge of durability and thermal failure. Therefore, the real-time rotor temperature monitoring plays a critical role, however, it is hard to online measure with sensors. To this end, a rotor temperature estimation method based on the lumped-parameter thermal networks and dual H infinity filters is proposed. Firstly, the lumped-parameter thermal network of three nodes, such as the stator, rotor and bearing, is numerically formulated to determine the power loss. Accordingly, the discretized state-space expressions are specified for the time-step iterative solution. Then, to address the uncertainty of model parameters, the dual H infinity filters are used in the rotor temperature estimation process. Finally, the simulation and experimental tests are performed to validate the effectiveness and the real-time executability of the proposed method. The test results show that the proposed method can well track the actual temperature tendency with estimation errors of less than 7.5 °C. Compared with the existing methods, the worst-case estimation accuracy has been improved by at least 25 %; besides, the proposed method presents good robustness against the parameter uncertainty; meanwhile, the higher estimation convergence is made in the face of huge model deviations.

Static sensor assisted rotor temperature estimation of permanent magnet machine for the low‐speed servo applications

AbstractA permanent magnet synchronous machine (PMSM) temperature estimation method fusing the classic lumped‐parameter thermal network (LPTN) and the stator sensor temperature information is investigated. With respect to the industrial servo applications, it is important to monitor the rotor magnet temperature to extend the machine thermal utilisation. A simple LPTN is developed and the quadratic programming is applied to identify the model parameters. The research work shows that the rotor temperature is sensitive to the rotor speed even at low speeds, and this simple estimation network can provide an accurate estimation. The winding sensor information can further improve the performance. A compound mechanism is built, by which the winding temperature estimation error is used as feedback to suppress the model‐based temperature estimation error accumulation. The estimation performance is compared with a regular constant LPTN‐based method. Experimental results based on a PMSM are presented to validate the proposed method.

Rotor Temperature Estimation for Magnetically Suspended Turbo Molecular Pump Based on Flux Linkage Identification

Monitoring rotor temperature is a significant issue for safe operations in magnetically suspended turbo molecular pump (MSTMP). The increase in rotor temperature may cause the irreversible demagnetization of the permanent magnet (PM) and destroy the vacuum environment, eventually affecting the efficiency and security of the MSTMP system. Unfortunately, the direct measurement of the rotor temperature is complicated in practice due to the difficulty of accessing temperature sensors on a rotating shaft. This article proposes a novel rotor temperature estimation method based on the identification of the PM flux linkage. In order to address rank-deficiency in the identification of multiparameters, the resistance is calculated from the measured stator temperature, and two recursive least square (RLS) algorithm segments are combined to identify the inductance and flux linkage. Furthermore, the dynamic factor is introduced into the RLS algorithm to enhance the identification accuracy and convergence rate of the algorithm. The experiment results on the MSTMP test rig, equipped with the infrared temperature measuring module, demonstrate that the identified flux linkage has a good performance for the estimating rotor temperature under different working conditions.

Parameter Identification Based Online Noninvasive Estimation of Rotor Temperature in Induction Motors

This article proposes a rotor temperature estimation method for in-service induction machine (IM) based on parameter identification, which combines the advantage of recursive least squares (RLS) and model reference adaptive system (MRAS). The RLS with forgetting factor is firstly adopted to identify the parameters of motor inductances. Then, the online identification of rotor resistance can be realized via the MRAS based on the instantaneous reactive power (IRP) and the proportional integral (PI) regulation adaptive law designed by the Popov hyper-stable theory. Thereby, the rotor temperature is computed by the resistance-temperature relationship of metals. To achieve a fast convergence of the parameter identification, rotor slot harmonics are extracted from the stator current and used to determine the rotor speed in real time. Furthermore, to obtain a more accurate initial value of the stator and rotor leakage inductances and resistances, the first 5–15 cycles of the IM starting process are used to mimic the locked-rotor test condition. A merit of the proposed method is that it requires significantly less time to estimate the rotor resistance than the traditional methods. With a novel test bench, experimental validation is performed on a 22-kW IM. In the test, the rotor temperature is measured in three different ways: 1) wireless sensors inserted in the rotating rotor core and rotor end rings, 2) infrared sensor for rotor end ring temperature, and 3) PT100 installed in stator end winding. With this test bench, the real rotor temperature was revealed, and the effectiveness of the presented method is also verified.

Rotor Temperature Safety Prediction Method of PMSM for Electric Vehicle on Real-Time Energy Equivalence

The load capacity of the permanent magnet synchronous motor is limited by the rotor temperature, and the excessive temperature of the rotor will bring potential thermal safety problems of the system. Therefore, the accurate prediction of the rotor temperature of the permanent magnet synchronous motor for the electric vehicle is crucial to improve the motor performance and system operation safety. This paper studied the heating mechanism and the energy flow path of the motor and built the heat energy conversion model of the stator and rotor. The real-time algorithm to predict the rotor temperature was constructed based on the dissipative energy conservation of the stator of the motor rotor temperature. And the prediction method of the initial rotor temperature is fitted using the experimental results when the system is powered on. Finally, the test platform was set up to validate the rotor temperature accuracy. The results show that the motor rotor temperature estimation error under the dynamic operating condition is within ±5. The research provides a solution to improve the performance and thermal safety of the permanent magnet synchronous motor for electric vehicles.

Advanced rotor temperature estimation of permanent magnet synchronous machines for electric vehicles

The actual power capacity of permanent magnet synchronous machine for electric vehicles is usually limited by rotor temperature, and rotor overheating is one of the major reasons for permanent magnet synchronous machine failure. Therefore, an approach of rotor temperature estimation is proposed to improve motor peak power utilization and protect permanent magnet synchronous machine from serious demagnetization due to thermal damage. A real-time iterative algorithm is provided based on the equivalent thermal model for rotor temperature. First, the heat generating principle of each part as well as the power flow transferring of the motor system is analyzed. Second, rotor temperature model is built based on the conservation of energy loss from the stator and real-time superposition of temperature variation rate for the rotor. Finally, the motor performance test bench is built to validate the proposed algorithm and numerical models are also constructed to simplify estimation parameters for rotor temperature model. The algorithm accuracy is improved and verified by optimizing control parameters with given environment temperature and power load. The experimental result shows that the maximum error between actual test value and estimation value is within ±10°C, and it meets the requirement of algorithm accuracy and also benefits on system performance and manufacture cost efficiently.

Rotor Temperature Estimation in Doubly-Fed Induction Machines Using Rotating High-Frequency Signal Injection

Thermal monitoring is a common feature in most electric machine drives since thermal overloading is one of the most common causes of motor failures. Contact-type sensors are normally used to measure the stator temperature in electric machines. However, use of this type of sensor is not advisable in the rotor as it requires cabling to a rotating part or the use of a wireless transmission system. Consequently, measurement of the rotor temperature is not easy in practice and is not normally implemented in standard machines. An alternative to rotor temperature measurement is rotor temperature estimation. To date, only thermal models have been used for rotor temperature estimation in doubly-fed induction machines (DFIMs). This paper proposes rotor temperature estimation in DFIMs using high-frequency signal injection. The proposed method estimates the rotor temperature from the rotor high frequency resistance, which is a function of the rotor windings temperature. The method does not interfere with the normal operation of the drive and can be implemented in existing DFIM drives without requiring additional hardware.

Supply Frequency Tracking in Resistance-Based Induction Motor's Rotor Temperature Estimation

In resistance-based rotor temperature estimation schemes, a grid-connected induction motor's rotor temperature is derived from a resistance quantity based on an equivalent circuit model. This temperature is susceptible to fluctuations in the motor's supply frequency. In this paper, the relationship between supply frequency fluctuations and accuracy in resistance-based rotor temperature estimates is analyzed, and a complex adaptive phase discriminator is proposed to track the supply frequency fluctuations for grid-connected induction motors. A complex voltage vector is constructed from polyphase voltage measurements and passed through a frequency-selective digital filter to attenuate harmonics and interference. The complex adaptive phase discriminator then operates on the filtered voltage signal, iteratively adapting a complex reference signal's phase to align it with the filtered voltage signal. The power grid's supply frequency is directly estimated from the adapted phase on a sample-by-sample basis. Experimental results demonstrate that the proposed complex adaptive phase discriminator helps produce rotor temperature estimates with increased accuracy.

Induction-Motor Rotor Temperature Estimation Using Superheterodyne Receivers

A rotor temperature estimator is proposed in this paper for grid-connected squirrel-cage induction motors during dynamic or steady-state operations. The method utilizes a pipelined architecture with two superheterodyne receivers that operate on a common complex current vector input. The first superheterodyne receiver detects motor speed by extracting an instantaneous rotor-slot-harmonic frequency from the complex current vector. The second superheterodyne receiver extracts a complex fundamental current vector from the same complex current vector. Given a few known motor parameters and a complex voltage vector, a model-reference adaptive system then produces an estimate of the rotor time constant from the superheterodyne receivers' outputs. Finally, the rotor temperature is derived from the estimated rotor time constant via a correlation between the rotor temperature and its resistance. Experimental results demonstrate that the proposed method is capable of estimating induction-motor rotor temperature on a sample-by-sample basis without using temperature or speed sensors.

Induction Motor Rotor Temperature Estimation Based on a High-Frequency Model of a Rotor Bar

This paper analyzes a high-frequency (HF) voltage-injection-based rotor winding temperature estimation method for current-regulated squirrel-cage induction motors (IMs). We develop a theoretical HF model of the rotor bar and then first provide an analysis of relevant HF model-based estimation aspects, such as the dependence of the rotor leakage inductance on the temperature and the relationship between the rotor resistance and rotor leakage inductance. We also include an analysis of magnetic saturation to improve the estimation accuracy, as well as an analysis of the phase delay effect resulting from the drive that significantly affects the HF signal precision. Then, a specialized offline commissioning scheme is proposed to compensate for the effect of the phase delay and magnetic saturation. The estimation technique and sensitivity analysis are verified by means of experiments performed on an inverter-fed 1.5-kW IM.

A Model Reduction Perspective on Thermal Models for Induction Machine Overload Relays

Full-order thermal models are often used by machine designers to analyze the induction machine thermal behavior. The real-time implementation of such models for the purpose of motor thermal protection is difficult because an extensive knowledge on motors and sufficient computational resource are required. This paper demonstrates that full-order thermal models can be systematically reduced via pole-zero cancellation or Hankel singular-values-based model reduction techniques without additional physical assumptions. As a result, a system of a substantially lower dimension, which has nearly the same response characteristics in the frequency band of interest, is obtained. Both the estimated rotor cage temperature, which is extracted from the voltage and current measurements by a sensorless rotor temperature estimator, and the measured stator winding temperature are used to evaluate the performance of low-order thermal models. Given a certain tolerance for the modeling error, a reduced low-order thermal model can be used to characterize the thermal dynamics of a small- to medium-sized line-connected induction machine and to provide proper protection against motor overheating.

A Sensorless Rotor Temperature Estimator for Induction Machines Based on a Current Harmonic Spectral Estimation Scheme

This paper proposes a sensorless rotor temperature estimator for small- to medium-sized mains-fed induction machines. With measurements obtained only from voltage and current sensors, the proposed estimator can capture the rotor temperature online. The rotor speed is first extracted from the stator current harmonic spectrum based on the estimated rotor slot and eccentricity harmonic frequencies. Then the inductances are estimated according to the induction machine equivalent circuit developed from the rotor flux field orientation. The stator winding resistance at ambient temperature is the only motor parameter needed as input in this stage. Once the inductances are obtained, they are fed into the rotor resistance estimation algorithm to yield an estimate of the rotor resistance. Finally, the rotor temperature is calculated from the linear relationship between the temperature and rotor resistance. The experimental results from different motors are shown to validate the proposed algorithms. The whole scheme is efficient and reliable and is therefore suitable for implementation in a motor overload protection relay to provide thermal protection against rotor overheating.

Rotor Temperature Estimation of Squirrel-Cage Induction Motors by Means of a Combined Scheme of Parameter Estimation and a Thermal Equivalent Model

This paper deals with a rotor temperature estimation scheme for fan-cooled mains-fed squirrel-cage induction motors. The proposed technique combines a rotor resistance estimation method with a thermal equivalent circuit. Usually, rotor resistance estimation works quite well under rated load conditions. By contrast, if the motor is slightly loaded, rotor resistance estimation becomes inaccurate due to the small slip. Therefore, rotor temperature estimation under low-load conditions may be estimated by a thermal equivalent model. In order to determine the rotor resistance and, thus, rotor temperature accurately, several machine parameters have to be obtained in advance. Load tests provide the leakage reactance and the iron losses of the induct machine. The stator resistance has to be measured separately. The parameters of the thermal equivalent model are a thermal resistance and a thermal capacitance. These parameters are derived from a heating test, where the reference temperature is provided from the parameter model in the time domain. This lumped thermal parameter model is based on the assumption that the total rotor temperature increase is caused by the total sum of the losses in the induction machine. Measuring results of a 1.5-kW and an 18.5-kW four-pole low-voltage motor and a 210-kW four-pole high-voltage motor are presented and compared.