Research on intelligent control method ofair-cooled heat pump defrosting based on improved BP neural network
The current intelligent defrosting process does not consider the impact of the unit itself on defrosting,resulting in high energy consumption and low efficiency of the control method mainly based on BP neural network.This article proposes an improved BP neural network control method for defrosting of air-cooled heat pumps.Based on the principle of conservation of mass,clarify the heat transfer relation-ship between moist air and the finned tube heat exchanger in the air-cooled heat pump.Calculate the frost formation of the air-cooled heat pump by calculating the difference in moisture content between the inlet and outlet of the control unit.Using the Northern Eagle Optimization Algorithm to improve the BP neural network,the frosting related parameters of the air side heat exchanger and the influence parameters of the unit system on frosting are taken as network inputs.Based on the amount of frosting,the defrosting start time and heating end time of the heat exchanger are output,achieving intelligent control of defrosting for air-cooled heat pumps.The experimental results show that the proposed control method can remove frost within 170 seconds and maintain the operating pressure fluctuation during the frosting process at 0.3 MPa,reducing energy consumption while accelerating defrosting efficiency,ensuring high-performance and stable operation of air conditioning equipment.
万方数据
维普
