Solar Energy - Phase Change Thermal Storage New Air Control System

In this dissertation, all the research work is mainly about a new type of fresh air system with the help of the solar energy and LHTS (phase change thermal storage) which can achieve organized ventilation.Only few of studies is on this type of fresh air system in China, so are the thermodynamic modeling, control algorithm and system identification. However, the modeling and control of this fresh air system is of great importance to the thermal efficiency of the system and related to energy consumption. So, the study in this dissertation will certainly become a hot topic in this area.To facilitate the theoretical analysis and experimental research of this new type of fresh air system, an experimental platform and a simulating platform were developed in turn. In this dissertation, the advanced monitoring systems were firstly realized with the help of Labwindows/CVI and CAN bus by using these two platforms. Then, taking the simulating fresh air system as the object, a series of studies were done thoroughly on the thermodynamic modeling, control strategies and parameter identification:the fan coil and room air temperature model were established; fuzzy control algorithm was proposed to this fresh air system, and also the simulation was done on the fan coil model; basing on the acquisition of fresh air temperature and heat water flow, the simulation of nonlinear system identification was realized using the adaptive neuro-fuzzy inference method; finally, lots of fuzzy control experiments on the simulating fresh air system were designed and accomplished. The main contents and results of this dissertation are as follows:The novel structure of a fresh air system was firstly introduced. And then the characteristics and the operation modes of the system were analyzed in detail. Measurement and control of the fresh air system with solar collectors and LHTS was finally realized basing on CAN bus.Secondly, an observing and controlling system of the simulating fresh air system was designed and finally established. The operation modes of the system and the way it transfers between modes were presented for the first time. In full consideration of the nonlinerity and hysteresis of the fresh air system, the overall control goal was determined. This work lays theoretical foundation for the establishment and performance evaluation of the whole controlling system.Afterwards, the manual experiments were designed based on the simulating fresh air system. Through experiments, the validity of the system is verified, the operation features of the system components are mastered, and a mass of valid test data are achieved, which provide sufficient data support for the fuzzy control realization of the fresh air system, adaptive neuro-fuzzy modeling and parameter identification.Fourthly, the fan coil and the room temperature model were focused on and established. In the room temperature model, the external environment such as out air temperature and heat load disturbances are all taken into consideration, which makes the control model simulate the actual system characteristics more accurately. This work is the solid basis to verify the reasonability and effectiveness of the design of the fuzzy controller.Fifthly, the Mamdani fuzzy algorithm was proposed for the first time to control the temperature of the simulating fresh air system according to the nonlinearity and hysteresis of the system. The fuzzy controllers of three operation modes of the system are also designed in workspace and simulated numerically with MATLAB.Sixthly, adaptive'neural fuzzy inference controller was designed according to the characteristics of the mathematical model, which combines the neural network theory with the T-S fuzzy model. Regarding the deviation and the rate of the deviation as the input and the controlling variable as output, the proposed controller was realized by continuous BP neural network using the approximation ability of the network.The adaptive neuro-fuzzy controller of the simulation results show a reasonable identification of the parameters, and the simulated output can approach the original output very closely and the error is almost zero, which verifies the proposed adaptive neural modeling.Finally, a number of fuzzy experiments were designed and carried out to verify the correctess and feasibility of the fuzzy arithmetic. The result shows that the fuzzy controller is of good performance of robustness and adaptability, and it meets the control requirement of the fresh air temperature.This study provides theoretical basis and technical support for future application of the fresh air system with solar collectors and LHTS.