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Multi-physics field decoupling control method and system for air source heat pump drying system

An air source heat pump, decoupling control technology, applied in drying solid materials, heat pump, drying and other directions, can solve the problems of low dehumidification efficiency, low energy efficiency, rough control, etc., and achieve the effect of improving dehumidification efficiency and improving dehumidification efficiency.

Active Publication Date: 2022-04-29
ELECTRIC POWER RES INST OF GUANGXI POWER GRID CO LTD +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Heat pump control usually adopts manual adjustment method, simply setting temperature, humidity and time, and its control is relatively rough. Since drying is a complex nonlinear process, its dehumidification efficiency will continue to change with changes in physical quantities such as temperature, humidity, and pressure of the drying box. Changes, and these physical quantities are coupled and influenced each other, and present strong nonlinear characteristics, which makes the traditional control method have low dehumidification efficiency and low energy efficiency.

Method used

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  • Multi-physics field decoupling control method and system for air source heat pump drying system
  • Multi-physics field decoupling control method and system for air source heat pump drying system
  • Multi-physics field decoupling control method and system for air source heat pump drying system

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Embodiment 1

[0064] A specific embodiment of the present invention provides a multi-physics field decoupling control method for an air source heat pump drying system, as shown in Figure 1, including the following steps:

[0065] S1: Collect the air pressure, temperature and humidity in the oven, as well as the dehumidification efficiency in the oven;

[0066] S2: Detect the power supply of the compressor, and perform decoupling control through the trained neural network to obtain the reference power of the compressor, and control the compressor according to the reference power.

[0067] The dehumidification efficiency ρ in the oven is calculated as follows:

[0068]

[0069] ΔW=W t -W t-1 ;

[0070] ΔE=E t -E t-1 ;

[0071] In the formula, ΔW is the weight of the material lost in drying, and ΔE is the electric energy consumed by drying the material with a weight of ΔW; the dehumidification efficiency of the heat pump drying system is obtained by the difference in material weight a...

Embodiment 2

[0114] Such as Figure 5 As shown, in this embodiment, an adaptive neural network is used for decoupling automatic control. In this example, the nonlinear auto-regressive neural network NARX (Nonlinear Auto-regressive with External Inputs) with external input is used. Its output is not only related to the current input, but also related to the past output. In terms of topological connection, it can be equal to The effect is a BP neural network with input delay plus a delay feedback from output to input, which belongs to a dynamic recursive neural network with feedback. Because the NARX neural network contains multi-step input and output delays, it can reflect the historical state information of the system, so the network has a memory function, which can better describe the characteristics of the time-varying system. The model of the NARX neural network can be defined as:

[0115] y(t)=f[y(t-1),y(t-2),...,y(t-n y ),

[0116] u(t-1),u(t-2),···,u(t-n u )];

[0117] In the f...

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Abstract

The invention belongs to the technical field of air source heat pump drying, and particularly relates to a multi-physical field decoupling control method and system for an air source heat pump drying system.The method comprises the steps that the air pressure, temperature and humidity in a drying oven and the dehumidification efficiency in the drying oven are collected; the power supply power of the compressor is detected, decoupling control is carried out through the trained neural network, the reference power of the compressor is obtained, the compressor is controlled according to the reference power, multiple physical quantities such as oven pressure, oven temperature and humidity are comprehensively considered, the compressor is automatically controlled, and the dehumidification efficiency can be effectively improved. In consideration of mutual coupling and nonlinear characteristics among the temperature, the humidity and the pressure of the drying oven, an intelligent control algorithm of a neural network is adopted, the method is simple and practical, and is realized by programming of a controller, and the dehumidification efficiency can be further improved. The reciprocal of the dehumidification efficiency is used as an error of neural network control, and the dehumidification efficiency is continuously improved through closed-loop adjustment.

Description

technical field [0001] The invention belongs to the technical field of air source heat pump drying, and in particular relates to a multi-physics field decoupling control method and system for an air source heat pump drying system. Background technique [0002] Food drying processing is an important field in industrial and agricultural production. Drying is a high-energy-consuming process. The energy consumption of different drying processes varies greatly. The energy consumed for drying at home and abroad accounts for 7% to 15% of the total energy consumption in the country, while the thermal efficiency is only 25% to 10%. 50%, and the drying process will affect the color, flavor, nutrition and texture of heat-sensitive materials (such as food and biological materials). Low-carbon energy saving is the theme of current economic and social development, and the energy-saving renovation of the drying system is of great significance to energy conservation and environmental prote...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): F26B23/00F26B25/22F25B30/06F25B49/00G06F30/27
CPCF26B23/00F26B25/225F25B30/06F25B49/00G06F30/27G06F2119/02Y02P60/85
Inventor 郭小璇韩帅刘雨兵舒杰孙乐平卢健斌王显龙陈浩波陈卫东肖静崔琼田甜吴晓锐龚文兰郭敏姚知洋阮诗雅赵立夏
Owner ELECTRIC POWER RES INST OF GUANGXI POWER GRID CO LTD
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