Abstract
Permanent magnet retarder wins high favor of large cars with easy installation, low power consumption and small size. But this retarder is easily affected by outside conditions or road conditions, so that the temperature field, the magnetic field, the relationship between design parameters will be changed, and the brake torque will further be affected. Through research we found that the parameter design of permanent magnet retarder is the most important point. An optimized parameter enables the brake torque to come into full play and to adjust its external environment. The paper presents the parameter optimization design model of permanent magnet type retarder based on neural network algorithm. In the model, the design parameters of permanent magnet retarder is taken as input values, all influencing factors as the hidden layer of neural network, and the weight coefficient and threshold values of various scene parameters are constantly adjusted to conform to meet practical needs. In addition, according to the results of the output layer, the values of the design parameters are constantly adjusted to reach the ultimate goal of optimizing the design parameters. The comparison of experimental analysis shows that with practicability and reliability, the model can provide a more intelligent, simpler method for the design of permanent magnet retarder.
