Electronic expansion valve flow characteristic prediction method based on particle swarm optimization BP neural network

Abstract

The invention discloses an electronic expansion valve flow characteristic prediction method based on a particle swarm optimization BP neural network. The method comprises the following steps that an experimental data sample is obtained and preprocessed; constructing a BP neural network topological structure; optimizing an initial weight and a threshold value of the BP neural network by adopting a particle swarm algorithm; inputting the optimized initial weight and threshold into a BP neural network for sample training and testing; and performing flow characteristic prediction on the trained neural network under different working conditions. The method has the advantages that the flow characteristics of the electronic expansion valve are predicted by adopting a BP neural network method, the initial weight and the threshold value of the BP neural network are optimized by adopting the particle swarm optimization algorithm, the defect that the BP neural network is slow in convergence speed and even does not converge or falls into a local minimum value is overcome, the method is convenient and efficient, and flow prediction is accurate.

Description

technical field [0001] The invention relates to the field of thermal management systems of new energy vehicles, in particular to the prediction of flow characteristics of electronic expansion valves based on particle swarm optimization BP neural network. Background technique [0002] As a throttling device in the heat pump system, the electronic expansion valve mainly plays the role of reducing pressure and regulating flow in the system. The flow characteristic is one of the key parameters of the electronic expansion valve. For a normal working heat pump system, different refrigerant flow rates are required to achieve the purpose of cooling and heating under different working conditions. For a designed electronic expansion valve , it is of great significance to study its flow characteristics. [0003] Regarding the research on the flow characteristics of the electronic expansion valve, some existing technologies study the flow characteristics of the expansion valve from the...

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Problems solved by technology

[0003] Regarding the research on the flow characteristics of the electronic expansion valve, some existing technologies study the flow characteristics of the expansion valve from the theoretical level based on the flow characteristic formula of the fluid flowing through the orifice, but because the flow coefficient in the flow characteristic formula is unknown, only An empirical formula is used instead. As a result, there is a large error between the expansion valve flow characteristics obtained by this orifice flow characteristic formula and the actual working conditions.

In the prior art, polynomial fitting or Parkingham's law is used to study the relationship between mass flow and influencing factors. Due to the consideration of many influencing factors, the fitting relationship is particularly complicated.

In the prior art, there is also an experimental method to study the flow characteristics (Mass flow rate prediction of R1233zd through electronic expansion valves based on ANN and power-law correlation models), but considering the experimental equipment, cost and time, it can only be used under special working conditions Therefore, a new practical research method is needed to study the flow characteristics of electronic expansion valves.

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