Permanent Magnet Temperature Estimation Research Articles

Permanent magnet temperature estimation of high power density permanent magnet synchronous machines by considering magnetic saturation

Permanent magnet temperature estimation of high power density permanent magnet synchronous machines by considering magnetic saturation

Current Injection-Based Simultaneous Stator Winding and PM Temperature Estimation for Dual Three-Phase PMSMs

This article proposes a current injection-based simultaneous stator winding and permanent magnet (PM) temperature tracking technique for dual three-phase permanent magnet synchronous machines (PMSMs). The estimation models involving winding and PM temperatures are derived for different control strategies with the cancelation of inductances. To improve the tracking performance, a Kalman filter is used for simultaneous winding and PM temperature estimation. Compared with the existing methods, the proposed simultaneous winding and PM temperature estimation technique is independent of the voltage-source nonlinearity effect and is applicable to various machine operating conditions. The main features of the proposed method are underscored by the cancelation of inductance and the elimination of the need for a lookup table. The test results on a laboratory dual three-phase PMSM are used to validate the proposed method under different speed and torque conditions.

Efficient Permanent Magnet Temperature Modeling and Estimation for Dual Three-Phase PMSM Considering Inverter Nonlinearity

Accurate temperature information is crucial to dual three-phase permanent magnet synchronous machine (DT-PMSM) drives. Therefore, this article proposes two efficient models for permanent magnet temperature estimation of DT-PMSMs. The proposed models are derived through current injection in the reference frame that does not contribute to torque production. Through current injection, the proposed models can fully explore the two sets of machine equations to cancel winding resistance and machine inductances. To improve the estimation performance, inverter nonlinearity is compensated in the first model and cancelled in the second model. In comparison to existing methods, the proposed approach is computationally efficient and robust to parameter variation, magnetic saturation, and inverter nonlinearity. Moreover, the current injection will not affect the machine torque production and control performance. The proposed estimation approach is evaluated on a laboratory DT-PMSM under various operating conditions.

Speed Harmonic Based Modeling and Estimation of Permanent Magnet Temperature for PMSM Drive Using Kalman Filter

This paper investigates permanent magnet temperature (PMT) modeling and estimation for permanent magnet synchronous machines (PMSMs) by using the measured speed harmonic. First, a linear temperature model is derived to demonstrate that the magnitude of the speed harmonic decreases linearly with the increase of PMT. To achieve this linear model, the speed harmonic is induced by the injected harmonic currents satisfying certain conditions developed in this paper. To improve the estimation performance, PMT estimation is represented in a state–space model based on the derived temperature model, and the Kalman filter is applied to estimate the PMT from the measured speed harmonic. Compared with existing methods, the proposed approach has advantages in terms of simplicity in estimation and robustness to the variation of machine resistance and inductances. The proposed Kalman filter based modeling and estimation approach is evaluated with extensive experiments on a laboratory PMSM drive system under different speed and load conditions.

Noninvasive Kalman Filter Based Permanent Magnet Temperature Estimation for Permanent Magnet Synchronous Machines

Permanent magnet temperature (PMT) is crucial to high-performance control and condition monitoring of permanent magnet synchronous machines (PMSMs). This paper proposes a noninvasive PMT estimation approach based on the PMSM steady-state equation. First, a linear temperature model, dependent solely on the PMT, is derived from the steady-state equation and the PM thermal model. Thus, the PMT can be directly estimated from the measurements using the derived linear model. In order to improve the estimation performance, a linear state-space model is developed based on the derived model, and the Kalman filter is employed for PMT estimation. The inverter nonlinearity is considered and compensated in the proposed model to improve the estimation performance. Compared with the existing methods, the proposed approach is noninvasive and computationally efficient. More importantly, the derived model does not involve machine parameters such as winding resistance and self and mutual inductances, and thus, the proposed approach is independent of winding temperature rise, magnetic saturation, and cross-coupling effect. The proposed approach is evaluated with extensive experiments under various speed and load conditions.

Improved High-Frequency Voltage Injection Based Permanent Magnet Temperature Estimation for PMSM Condition Monitoring for EV Applications

Permanent magnet (PM) temperature is critical to ensure high-performance and reliable control of permanent magnet synchronous machines (PMSMs) for electric vehicle (EV) applications. High-frequency (HF) voltage injection based approach has been shown to be capable of PM temperature estimation under all-speed range with simple implementation. This paper improves existing HF voltage injection based PM temperature estimation approach by considering the cross-coupling effect. The key to PM temperature estimation is the temperature-dependent HF resistance estimated from the injected HF voltage and the current response. It is found that the cross-coupling effect has a great influence on the HF resistance estimation. This paper firstly improves the HF voltage injection model by considering the cross-coupling effect. Then, a comparative numerical investigation is conducted to analyze the estimation errors induced by the cross-coupling effect. A novel HF resistance estimation approach is derived from the proposed improved model and the PM temperature is calculated from the HF resistance with a linear thermal model. The influence of inverter nonlinearity is also analyzed. Experimental investigations demonstrate that the proposed approach is able to improve the performance of PM temperature estimation.

Permanent Magnet Temperature Estimation in PM Synchronous Motors Using Low-Cost Hall Effect Sensors

Knowledge of the permanent magnet (PM) temperature in PM synchronous machines (PMSMs) is of great importance both for control and monitoring purposes. Increase in PM temperature during motor operation can degrade the magnetic flux strength and consequently the machine's torque production capability, and can also cause irreversible demagnetization of the PM. Direct measurement of the PM temperature is not viable in practice due to both cost and reliability issues. Indirect PM temperature estimation methods recently studied require knowledge of thermal or electrical model parameters or can have undesired effects on motor operation. In this paper, the feasibility of using low-cost Hall-effect sensors for PM temperature estimation is investigated. Hall sensors are present for detecting the initial position of the rotor in majority of PMSM applications for which incremental encoders are used for control. The proposed method can, therefore, be implemented with low or no additional cost. Experimental results on two interior PMSMs show that the method is capable of providing noninvasive estimation of the PM temperature without a priori motor parameter information for monitoring and protection against excessive increase in temperature.

Expectation-Maximization Particle-Filter- and Kalman-Filter-Based Permanent Magnet Temperature Estimation for PMSM Condition Monitoring Using High-Frequency Signal Injection

In permanent magnet synchronous machine, high-frequency (HF) signal injection has been extensively investigated for permanent magnet temperature (PMT) estimation, in which PMT is estimated from the temperature-dependent HF resistance. Existing studies require prior knowledge on the HF resistance and neglect the fact that PMT is temporally correlated. This paper proposes a state-space model for PMT estimation, in which PMT is modeled with a piecewise linear equation to explore the temporal correlation. The state-space model is nonlinear due to unknown model parameters, which is required to be known in existing studies. This paper proposes to use expectation maximization particle filter (EM-PF) for simultaneous PMT and model parameter estimation. After EM-PF estimation, the state-space model becomes linear, so Kalman filter is employed for online PMT estimation. The proposed EM-PF along with a Kalman-filter-based approach can explore the temporal correlation among PMTs to improve the estimation performance, which can be hardly achieved in existing studies regarding PMT as a time-independent parameter. It should be noted that EM-PF is for initial PMT and model parameter estimation, while Kalman filter is for online PMT estimation ensuring computation efficiency and real-time capability. Our approach is validated with both numerical and experimental investigations.

Permanent-Magnet Temperature Distribution Estimation in Permanent-Magnet Synchronous Machines Using Back Electromotive Force Harmonics

Permanent magnet (PM) temperature measurement/estimation in permanent-magnet synchronous machines (PMSMs) is convenient for both torque control and monitoring purposes. Most of the existing methods provide an averaged/punctual temperature. However, PM temperature distribution is not uniform, which can have unexpected adverse effects such as reduced accuracy estimating the torque produced by the machine or local demagnetization e.g., due to hot spots. PM temperature distribution can be measured or estimated. Inner and outer PM surfaces are not visible once the machine is assembled. Therefore, measurement of the PM temperature distribution cannot be realized by visual means. An array of temperature sensors attached to the PM can be used in this case. While this is technically feasible, it is unaffordable in commercial products due to cost and robustness issues. Alternatively, the PM temperature distribution can be estimated. This paper analyzes the use of back electromotive force (BEMF) harmonics to estimate the differential temperature in the PM of a PMSM, i.e., the temperature difference between the hottest and coldest parts of the magnets. Combined with average PM temperature estimation methods, this information can be used to estimate the PM temperature spatial distribution. The proposed method has been developed on an empirical basis.