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Lumped Parameter Transient Thermal Model of Motor Considering Temperature and Flow Rate of Cooling Water
Technical Paper
2019-01-0890
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The influence of heat flow and cooling water characteristics on motor temperature cannot be accurately reflected by the traditional motor temperature analysis method. In order to study the motor and its key components’ temperature characteristics under different temperatures and flow rates of cooling water, this paper establishes the lumped parameter transient thermal model which includes cooling water module, based on a 50kW permanent magnet synchronous motor. The transient and steady temperature is calculated through this model together with the motor loss calculation module in the electric drive system model. The influence of different temperature and flow rate of cooling water on motor and its key components’ temperature characteristics is compared. During the modeling process, the motor body is divided into 14 parts, based on the internal heat flow path of the motor. The thermal resistance of each key component and cooling water is calculated. The thermal behavior of the motor can be accurately described by the solution of eight linear differential equations. The simulation and experiments prove that the transient thermal model of the motor can accurately calculate the steady state and transient temperature of the motor. The analysis results show that, when the flow rate of cooling water rises from 0 to 2.0 m/s, the average temperature’s decreasing speed of motor stator winding and rotor magnetic steel slows down gradually, after reaching 2.0 m/s, the average temperature is no longer affected by the increasement of flow rate. The average temperature of motor stator winding and rotor magnetic steel increases linearly with the increase of cooling water temperature.
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Li, J., Ni, J., and Xu, X., "Lumped Parameter Transient Thermal Model of Motor Considering Temperature and Flow Rate of Cooling Water," SAE Technical Paper 2019-01-0890, 2019, https://doi.org/10.4271/2019-01-0890.Data Sets - Support Documents
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