Abstract
Monitoring critical temperatures in permanent magnet synchronous motors is crucial for improving working reliability. Aiming at resolving the difficulty in online temperature estimation, an accurate and simple five-node lumped parameter thermal network (LPTN) is proposed and the mathematical model of the LPTN is built. Both radial and axial heat transfer paths inside the motor are considered to model the complete thermal circuit. In addition, an innovative parameter identification method based on multiple linear regression is applied to identify the parameters of the LPTN model. The parameters in the state equation are identified instead of the data of the motor, which are strongly dependent on the material and geometrical parameters. Finally, an open-loop estimation scheme based on the state equation and Kalman filter algorithm is adopted to predict the motor temperature online. The model performances are validated by extensive experiments under varying speed and torque conditions in terms of the accuracy and robustness. The results indicate that the temperature estimation error is within the range of ±5 °C in most cases and the proposed model can quickly follow the load variation. Besides, the online temperature estimation scheme and parameter identification method are easy and convenient to implement in an embedded system, which is feasible in automobile applications.
Highlights
Permanent magnet synchronous motors (PMSMs) have been widely used in automotive traction drives due to their high performance, efficiency, and power density [1,2,3]
There are mainly four methods for the thermal analysis of motors, i.e., finite element method (FEM), estimation method based on the rotor flux, estimation method based on the rotor high frequency impedance, and lumped parameter thermal networks (LPTNs)
4, the parameters of the statestate equation were identified at each fixed speed based on the multiple linear regression algorithm
Summary
Permanent magnet synchronous motors (PMSMs) have been widely used in automotive traction drives due to their high performance, efficiency, and power density [1,2,3]. Based on the above analysis, a simplification model has been proposed in this paper to predict the temperatures in PMSMs. According to the structure of the motor, PMSM can mainly be divided into several parts: The cooling jackets, casing, stator core, wingdings, permanent magnet, rotor core, and shaft. The end cap and the casing are considered as two important nodes in connecting the axial and radial heat paths, making the thermal flow in a complete circuit. Both radial and axial heat transfer paths inside the motor are taken into consideration, and minimum thermal nodes are allowed to model the real thermal flow. The axial heat path mainly considers the thermal flow from the rotor node to the end cap node, which is conducted through the motor shaft. Stator the of rotor the motor, heat capacity, motor rotor heat capacity, and motor end cap heat capacity, respectively; are the loss of the stator and the rotor of the motor, respectively
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