Dynamic Characteristics Identification of Electronic Expansion Valve

Abstract: According to the model of the relationship between the degree of superheat of the evaporator of the refrigeration system and the opening of EDM electronic expansion valve, the electric expansion of the electronic expansion valve is driven by electric impulse to obtain the operation rule of superheat of evaporator as the dynamic response. Eight kinds of system identification methods are used to identify the refrigeration system.After comparing the identification results of various identification methods, the identification accuracy of various identification methods in dealing with this kind of problems is given, as well as the characteristics in the specific process, The identification method suitable for this kind of model is also given, which also shows that the link described by a third-order link is closer to the actual situation, which lays a good foundation for the simulation and simulation of the refrigeration system in the future. Keywords: electronic expansion valve; system identification; evaporator superheat At present, a variety of refrigeration electrical equipment, because of its internal system complexity and strong mutual coupling, it is difficult to establish an accurate system model using the usual mechanistic method, using the conventional ratio Integral derivative (PID) regulator is difficult to achieve good control effect, such as the initial operation and conditions change, you need to re-adjust the PID parameters, and sometimes can not even meet the basic requirements. Theoretical analysis and application experience shows that, like refrigeration systems This type of structure is known and the control object with unknown parameters but slow changes is particularly suitable for adaptive control.1 The primary problem facing process control is process modeling [2], and modeling methods are usually based on organic methods and system identification The method of system identification is based on the input and output data to establish the mathematical model, which is the basis of self-tuning control system. There are many system identification methods, the most commonly used method is least square method, in addition to the auxiliary variable method, gradient correction method and Maximum likelihood, etc. However, not every method of identification is applicable to all problems [3,4] gives a random search method, the practice shows that this method is very suitable for the refrigeration system of this type of identification [5]. In this paper, using several identification methods to identify the test data, the results were Compared with the online real-time requirements of these methods, in order to get suitable for this type of identification methods.Many literature of these methods give a more detailed derivation, some methods of identifying some of the parameters of the method of selection also have some instructions [ 6,7] .But according to the parameters in the literature, the identification results of this paper are often biased estimates, therefore, in the specific model, this paper gives the setting of these parameters.1, This type of refrigeration system, through the regulation of the expansion valve to regulate the flow of working fluid in the system, is a simple and effective way to control the cooling capacity and power consumption of the showcase.In order to achieve the control of the evaporator outlet superheat Target, the expansion valve opening to be self-correcting real-time control, the evaporator outlet overheating with the expansion valve opening changes in real-time identification to Set the structure of this section.In this paper, the test object of the literature [5] ?? DNS-106-type 1.1 kW supermarket freezer freezer, the use of stepper motor driven EDM electronic expansion valve, driven by a four-phase stepper motor with two Only Pt1000 platinum resistance were attached to the evaporator inlet and outlet pipe wall to experience the evaporator inlet and outlet temperatures.The evaporator is three rows of fork row pipe, tube length 1 410 mm, the test ambient temperature is 28 ° C. Test equipment such as Figure 1 shows. Figure 1 Schematic diagram of the pilot device After power on for a period of time, the system is stable operation, step change electronic expansion valve opening to the expansion valve plus 200 electronic pulses, the valve closed small, 10s for the sampling period dynamic acquisition of the evaporator Outlet temperature, so as to obtain the evaporator superheat signal to get better results for the test, the test process must pay attention to the expansion valve opening change should not be too large, nor too small [5] 2, the identification method The least squares (LS) (Recursive Least Squares (RLS)), random search (LJ), generalized least squares (GLS), recursive augmented least squares (RELS) (RIV) (two methods), Recursive Maximum Likelihood (RML) and random Newton's (SNA) method to identify the experimental data collected by the test device shown in Figure 1, the specific process is as follows. 1) The LS method. In this paper, the system model is identified by the step function method, which encounters the singular matrix inversion problem when performing matrix operation. Here we add some random noise with small variance when u is read in. The RLS method can also be used Online identification, the initial value is: P = 106I θ = 0. Because the two identification results are very close, so only the LS identification results are given in the paper.The results of comparison with the experimental data shown in Figure 2. Can be seen from Figure 2, the identification results have some error, overshoot ratio test This means that LS and RLS can not give higher recognition accuracy in the presence of noise. Figure 2 Comparison of various identification methods (2) LJ method. It is assumed here that the system is second order. It can be seen from Figure 2 that its identification accuracy is high, but this method is not suitable for on-line identification. (3) GLS method. Try to select the noise model for the first order, the error bound of the number of iterations take 0.1. The error bound of the number of iterations should not be too small, too small will eventually lead to iterative divergence, the reason may be due to the increase of the number of iterations, The results show that the accuracy of the identification method is better than that of LS, but it does not improve much. (4) RELS method. This algorithm is based on the third-order model and the first-order noise model. The initial value is the same as that of RLS and noise model. It can be seen from the results in Fig. 2 that the identification accuracy is better (as the result of RELS, RIV-1, RIV-2, RML, SNA and other identification methods are very close, (5) RIV method. The noise-independent auxiliary variables selected in this paper are: hπ (k) = [-x (k-1), ..., -x For x (k), the following algorithms are given in [7]: (1) α = 0.01 ~ 0.1; d = 0 ~ 10 this The results are respectively denoted by RIV-1 and RIV-2. During the experiment, it is found that the initial value of the intermediate variable P in the calculation process strongly affects the identification accuracy, the value is not good and may even cause Divergence, P = 106I for the first method and P = 400I for the second method.At the same time, according to the recommended value α = 0.01 ~ 0.1, the identification result is biased. d = 1. It can be seen from Figure 2 that the identification result is better. (6) RML method. It is found in the calculation that P is initialized as a unit matrix according to [7], and the identification result is biased. It can be seen from Fig. 2 that the recognition result is better. (7) SNA method In this paper, the initial value of R is taken as the unit matrix, the convergence factor ρ (k) = 0.9 / (k + 0.3) The result is better.3.The superheat of the evaporator with the electronic expansion valve opening change model to determine For the stepper motor drive EDM electronic expansion valve, evaporator superheat with the electronic expansion valve stepping motor pulse number of dynamic relationship, In addition to LJ identification method, the rest are to increase the order without increasing the accuracy to determine the model order. The method of [5] removed the delay, LJ, LS, RLS identified the link as second order, the rest of the method identified as the third order.To determine the order of the link, the LJ identification results are derived pulse transfer function, It can be seen from this that the link has a small gain, so the process of dynamic change depends more on the initial state of the system, which is also obtained from the simulation results in Figure 3. As a comparison, the following is given by RIV- 1 Results of the method of identification derived pulse transfer function: From here it is clear that the third order is better than the second order, so that the link is third order. Figure 3 Comparison of simulation results 4 Conclusion By adjusting the expansion valve to It is a simple and effective method to regulate the flow of working fluid in the refrigeration system to control the cooling capacity and power consumption.This paper uses eight kinds of system identification methods to identify the link and through comparison, A link, RELS, RIV-1, RIV-2, RML and SNA are relatively good identification methods, and also suitable for online identification.LJ identification method of data processing ability is strong, distinguish Recognition accuracy is also very high, but due to the need to determine the model structure in advance by this method, this not only increases the complexity but also limits its application because of a predetermined model inaccuracies. In addition, the LJ method is slow and not suitable On-line identification.For the refrigeration system, the evaporator inlet and outlet superheat with the electronic expansion valve opening of the pulse transfer function changes, this article through the simulation that the link should be the third-order link, which for the future of refrigeration system simulation has laid a certain (School of Power and Energy Engineering, Shanghai Jiaotong University, Shanghai 200030, China) References: [1] Zhong Hua (1971 ~), male, Ph.D. J] .Journal of Control Theory and Applications, 1997,14 (2): 66-63. [1] Chen Zhijiu, Zhu Ruiqi, Wu Jingyi. Automation of refrigeration equipment [M] .Beijing: Mechanical Industry Press, 1997. [2] Jin Yihui.Process Control Development and Prospect [J] : 145 to 151. [3] Stark PA, Ralston D. L. Comparative study of two recent on-line process identification techni ques [A]. American Control Conference [C]. Arlington, VA, June 1982. [4] Luus R, Taakola TH I. Optimization by direct search and systematic reduction of the search region [J] , 19 (4): 760 ~ 766. [5] SUN Wen, ZHONG Hua, CHEN Zhi-jiu. Off-line identification of refrigeration system adjustment process [A] .98 'National General Mechanical Mechatronics Symposium Proceedings [C] Huangshan, 1998. [6] Ren Jintang. System Identification [M]. Shanghai: Shanghai Jiaotong University Press, 1989. [7] Fang Chongzhi. Process Identification [M]. Beijing: Tsinghua University Press, 1988.

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