With the development of power density in motor, the cooling becomes more and more important. Heat pipe is a method to solve this issue. However, the performance of heat pipe is largely affected by the structure, the operating angle, and the cooling at condensation section. Therefore, this paper experimentally discusses its impact on heat pipe performance. Based on the experimental data, (artificial neural network) ANN model is established to predict the performance. Results showed that, when the operating angle of heat pipe was large than 45°, it can be well adopted for motor cooling; while for other operating angles, the performance would be largely changed. ANN model is suitable method for the prediction the performance of heat pipe. The average relative errors of evaporator temperature, heat load, and effective thermal conductivity 1.0%, 1.7% and 2.9%, respectively.
Keywords Motor cooling, heat pipe, effective thermal conductivity, artificial neural network