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the motor temperature is too high will cause insulation aging, electrical safety performance degradation.Motor control system is a typical nonlinear system, temperature and so has the characteristics of time lag and coupling, it is difficult to establish accurate mathematical model.The traditional methods for motor temperature control accuracy is poorer, resulting in motor temperature abuse.Therefore, based on BP neural network adaptive control algorithm of motor delay coupling relationship under temperature control method.Combining the BP neural network and PID control method to establish the motor temperature network adaptive controller model, using the gradient descent method modified the weight coefficient of motor temperature controller model, so as to realize the BP neural network adaptive controller parameters real-time adjustment.The experimental results show that the use of BP neural network adaptive algorithm motor delay under the coupling temperature adjustment, can effectively improve the control accuracy, shorten the time delay in the control process.