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Simulating Winding Parameter Variations in Cooling of an Electric Motor using FloEFD

posted Aug 30, 2017, 5:27 PM by Songyi Han
An electric motor is an electrical machine that converts electrical energy into mechanical energy. Most electric motors operate through the interaction between an electric motor‘s magnetic field and its copper winding currents to generate
force within the motor. In certain applications, such as in electric vehicles which have traction motors, electric motors
can operate in both motoring and generating, or in braking to produce electrical energy from mechanical energy.

Motors tend to operate at high efficiencies. However, electrical losses can reach such high levels that the associated thermal losses produced must be removed through an appropriate method. Life expectancy of a motor’s windings strongly depends on temperature; an increase of the temperature levels by 5 to 8°C results in a halving of the winding’s life expectancy. As the winding resistance is temperature dependant, an improvement of the motor’s cooling system will bring about a decrease in the copper losses. Due to high material costs it is desirable to
use cooling to its limit in a motor. A more efficient cooling process can increase the motor’s current density and as a
result the same motor can reach a higher power than it would otherwise be able to.

Fluid flow and thermal processes in a motor are highly complicated and they cannot be well described with older simulation and testing methods. Measurements inside a fast rotating rotor (figure 1) are very difficult to do due to high circumferential speeds such that it is not easy to ‘see’ thermally what is going on. 3D Computational Fluid Dynamics (CFD) is therefore the best alternative for the conceptual design and detailed analysis of motors as it allows users to precisely predict the flow structure around the stator coil ends, the distribution of the cooling medium, any pressure losses, the heat transfer coefficients (HTCs) and the overall temperature distribution. CFD simulations of complex motors and windings can be very slow and tedious to set up, though, using traditional approaches and numerically intensive because of the many small channels and gaps in a motor’s design. This is where Mentor’s FloEFD 3D CFD rapid Cartesian meshing approach is so valuable to us.


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