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Research on the control laws of the electronic expansion valve for an air source heat pump water heater
Building and Environment 46 (2011) 1954e1961
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Research on the control laws of the electronic expansion valve for an air source heat pump water heater Mingliu Jiang, Jingyi Wu*, Ruzhu Wang, Yuxiong Xu Institute of Refrigeration and Cryogenic, Shanghai Jiao Tong University, Shanghai 200240, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 12 January 2011 Received in revised form 19 March 2011 Accepted 2 April 2011
Compared to the conventional air conditioner, the air source heat pump water heater (ASHPWH) possesses wider operating ranges and more dramatic changes in working conditions. Conversely, traditional throttle devices, such as the thermostatic expansion valve (TEV) and capillary tube, are restricted by narrow regulating ranges in refrigerant mass flow rate and lagging response to the superheat. This article incorporates a novel dual-fuzzy-controller to regulate the electronic expansion valve (EEV) specialized for the ASHPWH system. The study analyzes the effects of the EEV initial opening and the target superheat on the performance of the ASHPWH. Moreover, this research proposes a fuzzy control method of selecting the initial opening and the target superheat on the basis of the ambient temperature and water temperature, and employs superheat error (e) and the derivation of superheat error (ec) as the input variables of the fuzzy controller B to regulate the opening of the EEV during steady running process. To improve self-adaptability of the fuzzy controller, a rule modifier and a gain scheduler are introduced. In order to quantitatively reflect the difference in the performance between the TEV-controlled system and EEV-controlled one, experimental comparison between the EEV and the TEV is presented. Results demonstrate that both the stability and efficiency of the ASHPWH can be improved significantly by the EEV. Ó 2011 Elsevier Ltd. All rights reserved.
Keywords: Heat pump Hot water Superheat Electronic expansion valve Fuzzy control
1. Introduction Recently, the air source heat pump has found more and more applications due to its obvious advantages such as environmental protection, high efficiency and energy saving [1]. The air source heat pump water heater (ASHPWH) is a device that yields hot water by condensing heat. As the fourth generation of water heaters, the ASHPWH has shown strong market potential. The ASHPWH can be classified as the instant type and the circulate type. For the latter, the circulating water pump transfer condensing heat to the water tank. In this way, water temperature (Tw) in the tank rises gradually from the initial value to the terminal value (which is normally defined as 55e60 C) [2]. The performance of the ASHPWH depends largely on the ambient temperature (Ta). For subtropical climate, the system refrigerant circulating mass flow of the air conditioner in winter is 20e40% less than that in summer [3]. But for the ASHPWH system, the varying range in the evaporating temperature is much larger since the unit always operates in heating mode. In addition, a wide
* Corresponding author. Tel./fax: þ86 21 3420 6776. E-mail address: [email protected] (J. Wu). 0360-1323/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.buildenv.2011.04.003
varying range in the water temperature also leads to a wider varying range in the condensing temperature. If the evaporator load is assumed to be approximately proportional to the refrigerant circulating mass flow, the ASHPWH refrigerant mass flow in winter is less 25e73% than that in summer based on the experimental formulas proposed by Morrison et al. [4]. The analysis above demonstrates that the required refrigerant mass flow regulating range for the ASHPWH system is much wider than that of the air conditioning system, and working conditions of the ASHPWH system varied more intensely than that of the air conditioner. In order to improve the adaptability of system to various working conditions, variable capacity control technology has been applied in air conditioners and heat pumps. This technology is mainly used in moving components of refrigeration systems, such as compressors and throttles. Variable capacity compressor can improve system efficiency, extend the life of components and reduce the indoor temperature fluctuations, since it eliminates frequent stopestart cycles [5e7]. But for a complete heating process of the circulate type ASHPWH, water is gradually heated from the initial temperature to the target value. Thus, unlike the air conditioning system, there are no frequent start-stop cycles during the operation of ASHPWH even if a fixed-frequent compressor is used, since the water tank possesses
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energy storage capacity. For the reason above, the research on variable capacity compressor applying in the ASHPWH system and related commercial products have seldom been reported. The throttle, which is in charge of the refrigerant mass flow entering into the evaporator, plays an important role on the performance of the refrigeration system [8]. The most common throttles include the capillary tube, orifice, thermostatic expansion valve (TEV) and electronic expansion valve (EEV). In the throttles above, the EEV has wider working range, higher control precision and faster response [9e11]. Many experimental studies have been done on the flow characteristics of the EEV [12,13] and much research has been devoted to control algorithms for the EEV control. Early, the incremental PID (proportionaleintegralederivative) controller is usually adopted for the EEV control in the air conditioning system. The discrete form of the incremental PID can be expressed as:
Duk ¼ Kp eðkÞ þ Ki
k X
eðjÞ þ Kd ½eðkÞ eðk 1Þ
(1)
j¼0
where Duk represents kth pulse output number on the EEV, e represents the error of the superheat, Kp, Ki and Kd represent proportional factor, integral factor and derivative factor, respectively. Note that the selection of Kp, Ki and Kd is crucial for performance of PID controller. However, the regulation on the EEV possesses the following features: nonlinearity, lag in the response of the superheat, disturbances, coupling relationship among system parameters. These features bring about difficulties in optimization and selection of proportional factor, integral factor and derivative factor. Li et al. [14] employed PID controller to adjust the superheat in a direct expansion solar assisted heat pump hot water system. The experimental results indicated that it was hard to get satisfactory results under varying working conditions. Wang et al. [15] also pointed out that traditional PID regulator cannot achieve good performance for nonlinear refrigeration systems. Note that the special operating features of the ASHPWH system determine the complexity of the EEV control. As so far, there is little open literature on the control methods of the EEV specialized for the ASHPWH system. During the water heating process of the ASHPWH, pressure difference at the inlet and outlet of the EEV is increasing. To maintain a stable superheat, the EEV opening should be reduced continually. However, traditional PID is to achieve the final stability of control object according to integral of feedback. Therefore, PID easily lead to fluctuation of control object due to lag in the response of the superheat. Moreover, it is time-consuming even impossible to select optimal Kp, Ki and Kd under various working conditions for such a strong nonlinear system. With the development of intelligent control technology, more advanced control methods are applied in the industrial process. Fuzzy control is a popular control method due to its simple structure and excellent dynamic performance, especially for the nonlinear complex system [16e19]. Li et al. [20] proposed a fuzzy self-tuning control algorithm for the EEV control in an automobile air conditioning system. In addition, some scholars tried to apply neural networks, genetic algorithms and predictive control to the regulating of the EEV [21e24]. However, these studies still remain in the stage of design or simulation, and the related experimental results are relatively inadequate. Although much research has been devoted to the control algorithms of the EEV, little research has been published on the control of the EEV specialized for the ASHPWH [25e27]. Conversely, the special operating condition of the ASHPWH determines the differential control methods of the EEV for the ASHPWH system as compared to the conventional air conditioning system and chiller.
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In this paper, the control strategy and laws for the EEV aiming at the ASHPWH system are proposed and analyzed in detail. Moreover, the experimental comparison of the EEV and TEV in the ASHPWH under three typical working conditions is presented. 2. Experimental setup The system is composed of the rotary-type compressor with nominal power consumption 1.2 kW, condenser, evaporator, throttle devices (EEV and TEV), reversing valve, 150 l water tank with thermal insulation, circulating water pump and other accessories. The measuring points of temperature and pressure are shown in Fig. 1. Where the refrigerant is R22, temperature sensors on the water side are 4-wire PT 1000 with an accuracy of 0.2 C, temperature sensors on the refrigerant side are type T copperconstantan thermocouple with an accuracy of 0.5 C. The EEV is driven by a step motor, pulse number from close to full opening is 500, experimental data are recorded by data acquisition instrument, Watt transducer and computer. The system is tested in a thermostatic chamber which is used to simulate different outdoor ambient temperatures. 3. Operating characteristics and EEV control algorithms of the ASHPWH The ASHPHW system has the following operating features: the range of working conditions is wider than the conventional refrigeration system; the condensing temperature varies all the time as the water temperature increases; the response of the superheat to the opening of the expansion valve is nonlinear; the system characteristics are different when the unit operates in different stages; hunting and choked flow might occur under some working conditions. In this paper, a fuzzy controller A is used to control the initial opening of the EEV during start-up process, and a fuzzy B is adopted to send pulse output during steady operating process. Fig. 2 shows the control flow chart of the EEV. It is mainly divided into four parts: I(the setting of the initial EEV opening), (the setting of the target superheat), III(the control methods during steady operating process) and (other control principles for the EEV). The control schemes and algorithms will be discussed in detail as the following.
Fig. 1. Schematic diagram of the experimental system.
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Fig. 2. Control flow chart of the electronic expansion valve.
3.1. Setting of the initial opening of the EEV during start-up 3.1.1. Operating characteristics of the ASHPWH during start-up There is obvious difference in the system characteristics when the ASHPWH works in start-up process and steady operating process. Chen et al. [28] found that the superheat oscillated intensely if normal control methods are employed to regulate the EEV during start-up. During start-up process, the pressure difference at the outlet and inlet of the compressor is built gradually. Therefore, the refrigerant mass flow is relative low and varies intensely at this moment. After start-up process, the refrigerant circulating mass flow is gradually stabilized with the establishment of the system pressure difference. Therefore, regulating the EEV opening only on the basis of the superheat is likely to lead to the system instability, since the change in the superheat of start-up process is also determined by the system start-up characteristics rather than merely depending on the EEV opening. In this article, a control strategy of fixed EEV opening is employed. The superheat during start-up largely depends on the initial refrigerant quality in the evaporator which is mainly related to Ta. Hence, Ta is employed as the input variable of the fuzzy controller A to set the initial EEV opening. In addition, to improve the adaptability of the fuzzy controller A, a rule modifier is used. As shown in Fig. 3, if the initial EEV opening is proper, the superheat of start-up process will rise sharply, and then starts to decrease after reaching the peak superheat (TSH,M). Note that TSH,M should be within a certain reasonable range. In order to make the superheat more stably after start-up, TSH,M should be slightly higher than TSH,S. Too high superheat is harmful to the security of system, while too low superheat is likely to cause other problems such as hunting phenomenon and liquid slugging. In order to judge whether the initial EEV opening is proper, the lower and upper limit of the superheat (TSH,L and TSH,H) are introduced during start-up process. If the initial EEV opening is not suitable, a self- learning modifier A would regulate the fuzzy rules of controller A on the basis of the previous performance of the superheat. The specific rules to judge whether the initial EEV opening is proper can be described as follows: (1) the EEV initial opening is suitable: TSH,M is between TSH,L and TSH,H, which means the initial EEV opening is proper; (2) the EEV initial opening is small: TSH,M exceeds TSH,H, which shows the initial EEV opening is too small, simultaneously the rules of fuzzy controller A is modified; (3) the EEV initial opening is large: TSH,M is below TSH,L, which implies the initial EEV opening is too large, accompanying with similarly revision in the rules of fuzzy controller A.
It is also found in the experiment that start-up time varies considerably with different working conditions, while water temperature rise of start-up process is basically the same. Thus, a fixed judging temperature (DTs, which is defined as the temperature difference between current water temperature and the initial water temperature), is used to terminate the control strategy for start-up process and transfers the program to steady running process. 3.1.2. The structure and logic of fuzzy controller A According to the operating characteristics of the ASHPWH during start-up mentioned early, fuzzy controller A is composed of fuzzy sets, adaptive rules and defuzzifier as below. 3.1.2.1. Fuzzification process of fuzzy controller A. Fuzzification process includes the following steps: (1) choose input and output variables; (2) establish the range of each variable; (3) convert inputs and outputs into membership functions. For the fuzzy controller A, the input variable and output variable are the ambient temperature (Ta) and EEV initial opening (F), respectively. Each variable is defined with eleven membership functions based on the actual working conditions of the ASHPWH. The fuzzy sets of Ta and Fare expressed as NL, NB, NM, NS, NT, ZE, PT,
Fig. 3. Superheat performance during start-up.
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PS, PM, PB, PL based on triangular membership functions. In this way, numerical data are converted into symbolic form. 3.1.2.2. The control rules and defuzzification process of fuzzy controller A. The general form of each rule for fuzzy controller A is: If Ta ¼ PL, then F ¼ PL. Simultaneously, the modifier A is developed to adjust the fuzzy rules of A. For example, when the ambient temperature is 17.5 C, then Ta ¼ Ta ð0:5; ZEÞ þ Ta ð0:5; PTÞ based on the membership functions. According to the fuzzy rules, F ¼ Fð0:5; ZEÞ þ Fð0:5; PTÞ. Here, F(ZE) and F(PT), which correspond to the minimum and maximum fuzzy sets of the ambient temperature (17.5 C) in the fuzzy rules, are defined as F0 and F1, respectively. As mentioned early, the EEV initial opening is a fixed value during start-up. If TSH,M exceeds TSH,H, then F(ZE), which corresponds to Ta(ZE) in the previous in the fuzzy rules, should be modified to F(PT)for the next start-up process. The similar things happen in other cases. Thus, the modifier A can be described in the following form: If TSH;M > TSH;H , then F0 should increase one step. If TSH;M < TSH;L , then F1 should decrease one step. For the fuzzy controller A, the input sets can be achieved through fuzzification mentioned above, and the pulse output can be calculated by the fuzzy reasoning based on center average defuzzifier. 3.2. Setting of the target superheat The superheat is a key evaluation indicator of the performance of the ASHPWH. A reasonable superheat can utilize the area of the evaporator to the maximum extent, avoid hunting problems and protect the compressor from liquid slugging. Hunting phenomenon means that the superheat and therefore also the suction pressure continually rises and falls, which going against the stability of the refrigeration system. Huelle [29] proposed the minimum stable superheat (MSS) line theory to explain the relationship between the minimum stable superheat and evaporator load for the TEV-controlled system. Chen [30] pointed out oversized expansion valve maybe one of main causes of unstable operation. The ASHPWH runs in heating mode all the year round, so the varying range of both the evaporator load and EEV opening is very large. On the other hand, the throttling device of the ASHPWH is generally designed according to the nominal operating condition. As mentioned early, the lower the ambient temperature is, the less required refrigerant mass flow is. The EEV works within a relatively small opening range (that means the valve is oversized) when the ambient temperature is low, which also can result in the instability of the superheat. Therefore, it can be concluded that the minimum stable superheat not only depends on the evaporator load but also relates with the EEV current opening. If the ambient temperature is a constant, the evaporator load and MSS will reduce due to the increase in water temperature [18,27]. According to the analysis above, the control principle of the target superheat can be described as follow: the target superheat (TSH,S) should be set high when the ambient temperature is low, and decreases as the water temperature increases. 3.3. Pulses output of the EEV during steady running process 3.3.1. Operating characteristics of the ASHPWH during steady running process During steady running process, the condensing pressure of the ASHPWH goes up with the water temperature rising, while the
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evaporating pressure remains basically unchanged when Ta keeps constant. Therefore, the pressure difference of the inlet and outlet of the EEV will rise continually with the water temperature increasing. According to hydraulics formula [22], the flow characteristic of the EEV can be described as:
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi mr;EEV ¼ CD A 2ri ðPc Pe Þ
(2)
Assume other conditions of the ASHPWH (including the EEV opening) are the same all the time, we can believe the superheat will gradually reduce with the increase in the pressure difference between the inlet and outlet of the EEV. Therefore, in the ideal case, to maintain the superheat within a reasonable range, the pulse output should be sent to close the EEV at a certain frequency during the steady operating process. Gain scheduling is an effective method for controlling systems whose dynamics response varies with operating conditions [31]. The experimental results show that, although the e and ec are the same, if the working conditions of the ASHPWH are different, there would be distinct difference in the pulse output. For a welldesigned system, the state parameters at the inlet and outlet of the EEV can be basically determined by Ta and Tw. In this article, e and ec are used as the input variables of the fuzzy controller B to control the EEV during system steady operating process, Ta and Tw are employed as input operating conditions for the gain scheduler. To improve the adaptability of the fuzzy controller B, the maximum and minimum difference value of the actual superheat and the target superheat (ek,max and ek,min) between two neighboring pulse output (Duk and Dukþ1), are adopted to adjust the output gain factor. 3.3.2. The structure and logic of fuzzy controller B According to the operating characteristics of the ASHPWH during start-up mentioned early, fuzzy controller B is composed of fuzzy sets, adaptive rules and defuzzifier as below. 3.3.2.1. Fuzzification process of fuzzy controller B. Fuzzification process includes the following steps: (1) choose input and output variables; (2) establish the range of each variable; (3) convert inputs and outputs into membership functions. For the fuzzy controller B, the input variables are the error (e) and derivation of the error (ec), the output variable is the pulse output number (Du). Each variable is defined with 11 membership functions based on the actual working conditions of the ASHPWH. The fuzzy sets of e, ec and Duk are expressed as NL, NB, NM, NS, NT, ZE, PT, PS, PM, PB, PL based on triangular membership functions. Thus, numerical data are converted into symbolic form. 3.3.2.2. The control rules and defuzzification process of fuzzy controller B. The general form of each rule for fuzzy controller B is: If e ¼ ZE and ec ¼ ZE, then Du ¼ ZE. K(Ta,Tw) is the output gain factor of the controller B, which is fitted in the function of Ta and Tw. To improve the adaptability of the fuzzy controller B, ek,max and ek,min are introduced to adjust the output gain factor. The rules of gain scheduling are classified as Duk < 0 and Duk > 0. When Duk < 0 that means the pulse output is sent to close the expansion valve, K(Ta,Tw) will be regulated as the following rules. If ek;max > c1, then K ðkÞ ðTa ; Tw Þ ¼ u1 K ðk1Þ ðTa ; Tw Þ If ek;max < c3, then K ðkÞ ðTa ; Tw Þ ¼ u3 K ðk1Þ ðTa ; Tw Þ If c1 < ek;max < c3, then K ðkÞ ðTa ; Tw Þ ¼ K ðk1Þ ðTa ; Tw Þ
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When Duk > 0 that means the pulse output is sent to open the expansion valve, K(Ta,Tw) will be regulated as the following rules. If ek;min > c2, then K ðkÞ ðTa ; Tw Þ ¼ u2 K ðk1Þ ðTa ; Tw Þ If ek;min < c4, then K ðkÞ ðTa ; Tw Þ ¼ u4 K ðk1Þ ðTa ; Tw Þ If c2 < ek;min < c4, then K ðkÞ ðTa ; Tw Þ ¼ K ðk1Þ ðTa ; Tw Þ where Duk represents kth pulse output number on EEV during steady operating processes. K(k) represents the new output gain factor after the kth regulation. c1ec4 are the triggering values to adjust the output gain factor, u1eu4 are the correction factors to the output gain factor, ek,max and ek,min are the maximum and minimum difference value of the actual superheat and the target superheat between Duk and Dukþ1. For the fuzzy controller B, the input sets can be achieved through fuzzification mentioned above, and the pulse output can be calculated by the fuzzy reasoning based on center average defuzzifier.
4.1. The comparison of the superheat Fig. 4 shows the variation in the superheat as the function of water temperature when the EEV and the TEV are separately employed in the same ASHPWH system. In Fig. 4(a), the ambient temperature is 5 C the superheat of system controlled by TEV fluctuates around 0 C. Obviously, it not only decreases the efficiency but also degrades the reliability of the system because of possibility of wet compression. But for the system with the EEV, the superheat changes from 7.5 C to 5.5 C stably as the water temperature increases during steady running process. The EEV opening ranges from 125 to 42. Fig. 4(b) shows the superheat in the TEV-controlled system oscillates intensely and frequently at the
3.4. Other control principles for the EEV The experimental results indicates that overshoot of the superheat often occurs when excess pulse output is sent to close the EEV. So it is necessary to use pulse amplitude limit for reducing overshoot. The pulse amplitude limit to close the EEV can be regarded as the function of the current opening of the EEV (P), because different P may lead to different dynamic response in the superheat, even if both the pulse output and the working conditions are the same. There is usually delay between the change of the superheat and EEV opening, so the time interval between two neighboring pulse outputs cannot be too short. Otherwise it will lead to unstable behavior in the ASHPWH system. But, too long time interval of pulse outputs can also lead to the superheat being out of control. To avoid too frequent adjustment and ensure timely control on the EEV, an optimal time interval (Dso) between two neighboring pulse outputs is adopted. Theoretically, the opening of the EEV can be regulated from 0 to 500. However, choking flow in throttling process maybe occur if the opening of the EEV is too small. To avoid this situation, the range of the EEV opening is restricted within 50e500 through a software program. For example, the output pulse to close the EEV calculated by the controller is 80, while the current opening of the EEV is 100, the actual pulse output is revised to 30 by the position limit programmer automatically. The similar thing happens in the process to open the EEV. In defrosting process, the evaporator and condenser interchanged roles after the reversing valve switches, and the pressure difference between the inlet and outlet of the EEV is usually low at this moment, thus refrigerant flow entering evaporator is considerable small. The experiment shows that the EEV also has a considerable throttling effect even if under the full opening, so the full opening control strategy is employed during the defrosting process. 4. Experimental results The experiments are conducted under three typical working conditions for the subtropical climate (the ambient temperature is 5 C, 20 C and 35 C, respectively. Water temperature is 15e55 C in the TEV-controlled system. Water temperature is 17e55 C in the EEV-controlled system). The comparison of system performance under different throttle devices is presented below.
Fig. 4. Superheat and EEV opening with water temperature using the EEV or TEV: (a) Ta ¼ 5 C; (b) Ta ¼ 20 C; (c) Ta ¼ 35 C.
M. Jiang et al. / Building and Environment 46 (2011) 1954e1961
Fig. 5. Compressor discharge temperature with water temperature using the EEV or TEV: (a) Ta ¼ 5 C; (b) Ta ¼ 20 C; (c) Ta ¼ 35 C.
ambient temperature 20 C. While the superheat controlled by the EEV reduces from 6.4 C to 4.3 C gradually at the same ambient temperature. The opening of the EEV decreases from 500 to 104 correspondingly. Although the target superheat is relative low and the opening of the EEV opening is full all the time at high ambient temperature. As shown in Fig. 4(c), the superheat is rather high during whole operating process when the ambient temperature is 35 C, because the required refrigerant mass flow regulating range
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Fig. 6. Heating capacity with water temperature using the EEV or TEV: (a) Ta ¼ 5 C; (b) Ta ¼ 20 C; (c) Ta ¼ 35 C.
for the ASHPWH system is too wide. In addition, the system superheat controlled by the TEV is averagely over 3 C compared to that in the EEV-controlled system. The experimental data above indicate that the superheat of the TEV-controlled ASHPWH system is lower than that of the EEVcontrolled system at the ambient temperature 5 C and 20 C, but higher when the ambient temperature is 35 C. The results above imply the EEV has much wider working range than the TEV. More
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importantly, the reasonable control scheme and algorithm for the EEV can eliminate hunting problem that cannot be avoided in the TEV-controlled system.
Acknowledgments The work is supported by the State High Technologies R&D Program under the contract No. 2007AA05Z220.
4.2. The comparison of compressor discharge temperature As shown in Fig. 5(a), when the ambient temperature is 5 C, there is little difference in the compressor discharge temperature whether the TEV or the EEV is used. When the ambient temperature is 20 C, the compressor discharge temperature of the TEVcontrolled system is slight higher than that of the EEV-controlled system. When the ambient temperature is 35 C, the discharge temperature of the EEV-controlled system is 5 C lower than that of the TEV-controlled system under the same water temperature. 4.3. The comparison of heating capacity Fig. 6 indicates the variation in heating capacity as a function of the water temperature. As shown in Fig. 6, the heating capacity rise sharply at the beginning. After reaching the peak value, the heating capacity decreases nearly linearly with the water temperature. The averaging heating capacity of the TEV-controlled system is 2.77 kW, 4.08 kW and 5.46 kW when the ambient temperature is 5 C, 20 C and 35 C, respectively. While the averaging heating capacity of the EEV-controlled system is 2.96 kW, 4.30 kW and 5.74 kW when the ambient temperature is 5 C, 20 C and 35 C, respectively.
Nomenclature
e ec T TSH TSH,S TSH,H TSH,L TSH,M MSS DTS
Dso
Du F P K COP c1ec4
superheat error, C the derivation of superheat error, C/s Temperature, C actual superheat, C setting value of the superheat, C upper limit of the superheat during start-up process, C lower limit of the superheat during start-up process, C maximum superheat during start-up process, C minimum stable superheat, C judging temperature of terminating start-up process, C optimal time interval between two neighboring pulse outputs, s pulse output number EEV initial opening current opening position of the EEV gain factor heating coefficient of performance triggering value to adjust gain factor
4.4. The comparison of system COP The system COP is improved by optimized control on the EEV under whole working conditions, being enhanced about 8.2%, 5.5% and 6.1% at the ambient temperature 5 C, 20 C and 35 C, respectively. In the TEV-controlled system, the wet compression and oscillation of the superheat increase the irreversible loss of the system, which results in the decrease in the COP. 5. Conclusion The ASHPWH possesses wider operating ranges and more dramatic changes in working conditions. The EEV has wider regulating range in refrigerant mass flow, hence it is indispensable for the ASHPWH system. In this paper, a novel dual-fuzzy-controller to regulate the EEV specialized for the ASHPWH system is presented. Ta is used as the input variable of the fuzzy controller A to set the initial opening of the EEV during start-up. Furthermore, to improve the adaptability of the fuzzy controller A, a rule modifier based on TSH,M is used. While e and ec, together with Ta and Tw as the input operating conditions for the gain scheduler, are employed as the input variables of the fuzzy controller B to regulate the opening of the EEV during steady running process. In addition, to utilize the evaporator area to the maximum extent, TSH,S is determined by Ta and Tw. By such a self-adaptive dual-fuzzy-controller, the EEV can regulate the refrigerant more precisely and more widely, the EEV eliminates hunting problem and liquid slugging that cannot be avoided in the TEV-controlled system. Moreover, the compressor discharge temperature can be substantially lowered especially when the ambient temperature is high. In addition, the EEV also improves the COP of the ASHPWH system significantly, being about 8.2%, 5.5% and 6.1% more than the COP of the TEV-controlled system at the ambient temperature is 5 C, 20 C and 35 C, respectively. To further verify the of the universality of the control method proposed in this paper, this adaptive dual-fuzzy-controller will be applied in other ASHPWH systems (which have different types of evaporator, different refrigerants, etc.) The experimental results will be reported afterwards.
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M. Jiang et al. / Building and Environment 46 (2011) 1954e1961 [12] Xue ZF, Shi L, Ou HF. Refrigerant flow characteristics of electronic expansion valve based on thermodynamic analysis and experiment. Applied Thermal Engineering 2008;28(2, 3):238e43. [13] Park CS, Cho HY, Lee YT, Kim YC. Mass flow characteristics and empirical modeling of R22 and R410A flowing through electronic expansion valves. International Journal of Refrigeration 2007;30(8):1401e7. [14] Li YW, Wang RZ, Wu JY, Xu YX. Experimental performance analysis on a direct-expansion solar-assisted heat pump water heater. Applied Thermal Engineering 2007;27(17, 18):2858e68. [15] Wang FH, Fei JY, Jin LW, Di B, Bf Y. Current status and development trend of inverter air conditioning control system. Refrigeration 2000;2:1e6 [in Chinese]. [16] Chen YP, Zhang JL, Lu Z, Zhao TY, Liu H. Experimental analysis of control loops with different delay times in the supply air system of a radiator test rig. Energy and Buildings 2011;43(1):49e55. [17] Zhao TY, Zhang JL, Sun DX. Experimental study on a duty ratio fuzzy control method for fan-coil units. Building and Environment 2011;46(2):298e314. [18] Li H, Jeong SK, You SS. Feedforward control of capacity and superheat for a variable speed refrigeration system. Applied Thermal Engineering 2009; 29(5, 6):1067e74. [19] Chiou CB, Chiou CH, Chu CM, Lin SL. The application of fuzzy control on energy saving for multi-unit room air-conditioners. Applied Thermal Engineering 2009;29(2, 3):310e6. [20] Li XQ, Chen JP, Chen ZJ, Liu WH, Hu W, Liu XB. A new method for controlling refrigerant flow in automobile air conditioning. Applied Thermal Engineering 2004;24(7):1073e85. [21] Fallahsohi H, Changenet C, Placé S, Ligeret C, Lin-Shi X. Predictive functional control of an expansion valve for minimizing the superheat of an evaporator. International Journal of Refrigeration 2010;33(2):409e18.
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[22] Alessandro B, Luca C. A simulation environment for dry expansion evaporators with application to the design of autotuning control algorithms for electronic expansion valves. International Journal of Refrigeration 2009;32(7): 1765e75. [23] Miles RG, Sharpe PK, Pan W, Fogarty TC. A comparative study of artificial neural networks and rule-based techniques in the development of a computer-aided control system. Engineering Applications of Artificial Intelligence 1994;7(1):53e8. [24] Chen WY, Chen ZJ, Zhu RQ, Wu YZ. Control algorithm of electronic expansion valve in evaporator superheat regulation. Journal of Shanghai Jiaotong University 2001;35(8):1228e32 [in Chinese]. [25] Gong GC, Zeng W, Wang LP, Wu C. A new heat recovery technique for air conditioning/heat pump system. Applied Thermal Engineering 2008;28(17, 18):2360e70. [26] Ji J, Chow TT, Pei G, Dong J, He W. Domestic air-conditioner and integrated water heater for subtropical climate. Applied Thermal Engineering 2003; 23(5):581e92. [27] Kim MS, Kim MS, Chung JD. Transient thermal behavior of a water heater system driven by a heat pump. International Journal of Refrigeration 2004; 27(4):415e21. [28] Chen WY, Chen ZJ, Zhu RQ, Wu YZ. Electronic expansion valve control during the start-up of refrigeration system. Journal of Shanghai Jiaotong University 2002;36(2):210e3 [in Chinese]. [29] Huelle ZR. The MSS line-a new approach to hunting problem. ASHRAE Journal; 1972:43e6. [30] Lectures of refrigeration technology, Thermal expansion valve. Available from: [accessed 02.09.10]. [31] Tan SH, Huang CC, Chai JS. Gain scheduling: from conventional to neuro-fuzzy. Automatica 1997;33(3):411e9.
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Research on the control laws of the electronic expansion valve for an air source heat pump water heater Mingliu Jiang, Jingyi Wu*, Ruzhu Wang, Yuxiong Xu Institute of Refrigeration and Cryogenic, Shanghai Jiao Tong University, Shanghai 200240, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 12 January 2011 Received in revised form 19 March 2011 Accepted 2 April 2011
Compared to the conventional air conditioner, the air source heat pump water heater (ASHPWH) possesses wider operating ranges and more dramatic changes in working conditions. Conversely, traditional throttle devices, such as the thermostatic expansion valve (TEV) and capillary tube, are restricted by narrow regulating ranges in refrigerant mass flow rate and lagging response to the superheat. This article incorporates a novel dual-fuzzy-controller to regulate the electronic expansion valve (EEV) specialized for the ASHPWH system. The study analyzes the effects of the EEV initial opening and the target superheat on the performance of the ASHPWH. Moreover, this research proposes a fuzzy control method of selecting the initial opening and the target superheat on the basis of the ambient temperature and water temperature, and employs superheat error (e) and the derivation of superheat error (ec) as the input variables of the fuzzy controller B to regulate the opening of the EEV during steady running process. To improve self-adaptability of the fuzzy controller, a rule modifier and a gain scheduler are introduced. In order to quantitatively reflect the difference in the performance between the TEV-controlled system and EEV-controlled one, experimental comparison between the EEV and the TEV is presented. Results demonstrate that both the stability and efficiency of the ASHPWH can be improved significantly by the EEV. Ó 2011 Elsevier Ltd. All rights reserved.
Keywords: Heat pump Hot water Superheat Electronic expansion valve Fuzzy control
1. Introduction Recently, the air source heat pump has found more and more applications due to its obvious advantages such as environmental protection, high efficiency and energy saving [1]. The air source heat pump water heater (ASHPWH) is a device that yields hot water by condensing heat. As the fourth generation of water heaters, the ASHPWH has shown strong market potential. The ASHPWH can be classified as the instant type and the circulate type. For the latter, the circulating water pump transfer condensing heat to the water tank. In this way, water temperature (Tw) in the tank rises gradually from the initial value to the terminal value (which is normally defined as 55e60 C) [2]. The performance of the ASHPWH depends largely on the ambient temperature (Ta). For subtropical climate, the system refrigerant circulating mass flow of the air conditioner in winter is 20e40% less than that in summer [3]. But for the ASHPWH system, the varying range in the evaporating temperature is much larger since the unit always operates in heating mode. In addition, a wide
* Corresponding author. Tel./fax: þ86 21 3420 6776. E-mail address: [email protected] (J. Wu). 0360-1323/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.buildenv.2011.04.003
varying range in the water temperature also leads to a wider varying range in the condensing temperature. If the evaporator load is assumed to be approximately proportional to the refrigerant circulating mass flow, the ASHPWH refrigerant mass flow in winter is less 25e73% than that in summer based on the experimental formulas proposed by Morrison et al. [4]. The analysis above demonstrates that the required refrigerant mass flow regulating range for the ASHPWH system is much wider than that of the air conditioning system, and working conditions of the ASHPWH system varied more intensely than that of the air conditioner. In order to improve the adaptability of system to various working conditions, variable capacity control technology has been applied in air conditioners and heat pumps. This technology is mainly used in moving components of refrigeration systems, such as compressors and throttles. Variable capacity compressor can improve system efficiency, extend the life of components and reduce the indoor temperature fluctuations, since it eliminates frequent stopestart cycles [5e7]. But for a complete heating process of the circulate type ASHPWH, water is gradually heated from the initial temperature to the target value. Thus, unlike the air conditioning system, there are no frequent start-stop cycles during the operation of ASHPWH even if a fixed-frequent compressor is used, since the water tank possesses
M. Jiang et al. / Building and Environment 46 (2011) 1954e1961
energy storage capacity. For the reason above, the research on variable capacity compressor applying in the ASHPWH system and related commercial products have seldom been reported. The throttle, which is in charge of the refrigerant mass flow entering into the evaporator, plays an important role on the performance of the refrigeration system [8]. The most common throttles include the capillary tube, orifice, thermostatic expansion valve (TEV) and electronic expansion valve (EEV). In the throttles above, the EEV has wider working range, higher control precision and faster response [9e11]. Many experimental studies have been done on the flow characteristics of the EEV [12,13] and much research has been devoted to control algorithms for the EEV control. Early, the incremental PID (proportionaleintegralederivative) controller is usually adopted for the EEV control in the air conditioning system. The discrete form of the incremental PID can be expressed as:
Duk ¼ Kp eðkÞ þ Ki
k X
eðjÞ þ Kd ½eðkÞ eðk 1Þ
(1)
j¼0
where Duk represents kth pulse output number on the EEV, e represents the error of the superheat, Kp, Ki and Kd represent proportional factor, integral factor and derivative factor, respectively. Note that the selection of Kp, Ki and Kd is crucial for performance of PID controller. However, the regulation on the EEV possesses the following features: nonlinearity, lag in the response of the superheat, disturbances, coupling relationship among system parameters. These features bring about difficulties in optimization and selection of proportional factor, integral factor and derivative factor. Li et al. [14] employed PID controller to adjust the superheat in a direct expansion solar assisted heat pump hot water system. The experimental results indicated that it was hard to get satisfactory results under varying working conditions. Wang et al. [15] also pointed out that traditional PID regulator cannot achieve good performance for nonlinear refrigeration systems. Note that the special operating features of the ASHPWH system determine the complexity of the EEV control. As so far, there is little open literature on the control methods of the EEV specialized for the ASHPWH system. During the water heating process of the ASHPWH, pressure difference at the inlet and outlet of the EEV is increasing. To maintain a stable superheat, the EEV opening should be reduced continually. However, traditional PID is to achieve the final stability of control object according to integral of feedback. Therefore, PID easily lead to fluctuation of control object due to lag in the response of the superheat. Moreover, it is time-consuming even impossible to select optimal Kp, Ki and Kd under various working conditions for such a strong nonlinear system. With the development of intelligent control technology, more advanced control methods are applied in the industrial process. Fuzzy control is a popular control method due to its simple structure and excellent dynamic performance, especially for the nonlinear complex system [16e19]. Li et al. [20] proposed a fuzzy self-tuning control algorithm for the EEV control in an automobile air conditioning system. In addition, some scholars tried to apply neural networks, genetic algorithms and predictive control to the regulating of the EEV [21e24]. However, these studies still remain in the stage of design or simulation, and the related experimental results are relatively inadequate. Although much research has been devoted to the control algorithms of the EEV, little research has been published on the control of the EEV specialized for the ASHPWH [25e27]. Conversely, the special operating condition of the ASHPWH determines the differential control methods of the EEV for the ASHPWH system as compared to the conventional air conditioning system and chiller.
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In this paper, the control strategy and laws for the EEV aiming at the ASHPWH system are proposed and analyzed in detail. Moreover, the experimental comparison of the EEV and TEV in the ASHPWH under three typical working conditions is presented. 2. Experimental setup The system is composed of the rotary-type compressor with nominal power consumption 1.2 kW, condenser, evaporator, throttle devices (EEV and TEV), reversing valve, 150 l water tank with thermal insulation, circulating water pump and other accessories. The measuring points of temperature and pressure are shown in Fig. 1. Where the refrigerant is R22, temperature sensors on the water side are 4-wire PT 1000 with an accuracy of 0.2 C, temperature sensors on the refrigerant side are type T copperconstantan thermocouple with an accuracy of 0.5 C. The EEV is driven by a step motor, pulse number from close to full opening is 500, experimental data are recorded by data acquisition instrument, Watt transducer and computer. The system is tested in a thermostatic chamber which is used to simulate different outdoor ambient temperatures. 3. Operating characteristics and EEV control algorithms of the ASHPWH The ASHPHW system has the following operating features: the range of working conditions is wider than the conventional refrigeration system; the condensing temperature varies all the time as the water temperature increases; the response of the superheat to the opening of the expansion valve is nonlinear; the system characteristics are different when the unit operates in different stages; hunting and choked flow might occur under some working conditions. In this paper, a fuzzy controller A is used to control the initial opening of the EEV during start-up process, and a fuzzy B is adopted to send pulse output during steady operating process. Fig. 2 shows the control flow chart of the EEV. It is mainly divided into four parts: I(the setting of the initial EEV opening), (the setting of the target superheat), III(the control methods during steady operating process) and (other control principles for the EEV). The control schemes and algorithms will be discussed in detail as the following.
Fig. 1. Schematic diagram of the experimental system.
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Fig. 2. Control flow chart of the electronic expansion valve.
3.1. Setting of the initial opening of the EEV during start-up 3.1.1. Operating characteristics of the ASHPWH during start-up There is obvious difference in the system characteristics when the ASHPWH works in start-up process and steady operating process. Chen et al. [28] found that the superheat oscillated intensely if normal control methods are employed to regulate the EEV during start-up. During start-up process, the pressure difference at the outlet and inlet of the compressor is built gradually. Therefore, the refrigerant mass flow is relative low and varies intensely at this moment. After start-up process, the refrigerant circulating mass flow is gradually stabilized with the establishment of the system pressure difference. Therefore, regulating the EEV opening only on the basis of the superheat is likely to lead to the system instability, since the change in the superheat of start-up process is also determined by the system start-up characteristics rather than merely depending on the EEV opening. In this article, a control strategy of fixed EEV opening is employed. The superheat during start-up largely depends on the initial refrigerant quality in the evaporator which is mainly related to Ta. Hence, Ta is employed as the input variable of the fuzzy controller A to set the initial EEV opening. In addition, to improve the adaptability of the fuzzy controller A, a rule modifier is used. As shown in Fig. 3, if the initial EEV opening is proper, the superheat of start-up process will rise sharply, and then starts to decrease after reaching the peak superheat (TSH,M). Note that TSH,M should be within a certain reasonable range. In order to make the superheat more stably after start-up, TSH,M should be slightly higher than TSH,S. Too high superheat is harmful to the security of system, while too low superheat is likely to cause other problems such as hunting phenomenon and liquid slugging. In order to judge whether the initial EEV opening is proper, the lower and upper limit of the superheat (TSH,L and TSH,H) are introduced during start-up process. If the initial EEV opening is not suitable, a self- learning modifier A would regulate the fuzzy rules of controller A on the basis of the previous performance of the superheat. The specific rules to judge whether the initial EEV opening is proper can be described as follows: (1) the EEV initial opening is suitable: TSH,M is between TSH,L and TSH,H, which means the initial EEV opening is proper; (2) the EEV initial opening is small: TSH,M exceeds TSH,H, which shows the initial EEV opening is too small, simultaneously the rules of fuzzy controller A is modified; (3) the EEV initial opening is large: TSH,M is below TSH,L, which implies the initial EEV opening is too large, accompanying with similarly revision in the rules of fuzzy controller A.
It is also found in the experiment that start-up time varies considerably with different working conditions, while water temperature rise of start-up process is basically the same. Thus, a fixed judging temperature (DTs, which is defined as the temperature difference between current water temperature and the initial water temperature), is used to terminate the control strategy for start-up process and transfers the program to steady running process. 3.1.2. The structure and logic of fuzzy controller A According to the operating characteristics of the ASHPWH during start-up mentioned early, fuzzy controller A is composed of fuzzy sets, adaptive rules and defuzzifier as below. 3.1.2.1. Fuzzification process of fuzzy controller A. Fuzzification process includes the following steps: (1) choose input and output variables; (2) establish the range of each variable; (3) convert inputs and outputs into membership functions. For the fuzzy controller A, the input variable and output variable are the ambient temperature (Ta) and EEV initial opening (F), respectively. Each variable is defined with eleven membership functions based on the actual working conditions of the ASHPWH. The fuzzy sets of Ta and Fare expressed as NL, NB, NM, NS, NT, ZE, PT,
Fig. 3. Superheat performance during start-up.
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PS, PM, PB, PL based on triangular membership functions. In this way, numerical data are converted into symbolic form. 3.1.2.2. The control rules and defuzzification process of fuzzy controller A. The general form of each rule for fuzzy controller A is: If Ta ¼ PL, then F ¼ PL. Simultaneously, the modifier A is developed to adjust the fuzzy rules of A. For example, when the ambient temperature is 17.5 C, then Ta ¼ Ta ð0:5; ZEÞ þ Ta ð0:5; PTÞ based on the membership functions. According to the fuzzy rules, F ¼ Fð0:5; ZEÞ þ Fð0:5; PTÞ. Here, F(ZE) and F(PT), which correspond to the minimum and maximum fuzzy sets of the ambient temperature (17.5 C) in the fuzzy rules, are defined as F0 and F1, respectively. As mentioned early, the EEV initial opening is a fixed value during start-up. If TSH,M exceeds TSH,H, then F(ZE), which corresponds to Ta(ZE) in the previous in the fuzzy rules, should be modified to F(PT)for the next start-up process. The similar things happen in other cases. Thus, the modifier A can be described in the following form: If TSH;M > TSH;H , then F0 should increase one step. If TSH;M < TSH;L , then F1 should decrease one step. For the fuzzy controller A, the input sets can be achieved through fuzzification mentioned above, and the pulse output can be calculated by the fuzzy reasoning based on center average defuzzifier. 3.2. Setting of the target superheat The superheat is a key evaluation indicator of the performance of the ASHPWH. A reasonable superheat can utilize the area of the evaporator to the maximum extent, avoid hunting problems and protect the compressor from liquid slugging. Hunting phenomenon means that the superheat and therefore also the suction pressure continually rises and falls, which going against the stability of the refrigeration system. Huelle [29] proposed the minimum stable superheat (MSS) line theory to explain the relationship between the minimum stable superheat and evaporator load for the TEV-controlled system. Chen [30] pointed out oversized expansion valve maybe one of main causes of unstable operation. The ASHPWH runs in heating mode all the year round, so the varying range of both the evaporator load and EEV opening is very large. On the other hand, the throttling device of the ASHPWH is generally designed according to the nominal operating condition. As mentioned early, the lower the ambient temperature is, the less required refrigerant mass flow is. The EEV works within a relatively small opening range (that means the valve is oversized) when the ambient temperature is low, which also can result in the instability of the superheat. Therefore, it can be concluded that the minimum stable superheat not only depends on the evaporator load but also relates with the EEV current opening. If the ambient temperature is a constant, the evaporator load and MSS will reduce due to the increase in water temperature [18,27]. According to the analysis above, the control principle of the target superheat can be described as follow: the target superheat (TSH,S) should be set high when the ambient temperature is low, and decreases as the water temperature increases. 3.3. Pulses output of the EEV during steady running process 3.3.1. Operating characteristics of the ASHPWH during steady running process During steady running process, the condensing pressure of the ASHPWH goes up with the water temperature rising, while the
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evaporating pressure remains basically unchanged when Ta keeps constant. Therefore, the pressure difference of the inlet and outlet of the EEV will rise continually with the water temperature increasing. According to hydraulics formula [22], the flow characteristic of the EEV can be described as:
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi mr;EEV ¼ CD A 2ri ðPc Pe Þ
(2)
Assume other conditions of the ASHPWH (including the EEV opening) are the same all the time, we can believe the superheat will gradually reduce with the increase in the pressure difference between the inlet and outlet of the EEV. Therefore, in the ideal case, to maintain the superheat within a reasonable range, the pulse output should be sent to close the EEV at a certain frequency during the steady operating process. Gain scheduling is an effective method for controlling systems whose dynamics response varies with operating conditions [31]. The experimental results show that, although the e and ec are the same, if the working conditions of the ASHPWH are different, there would be distinct difference in the pulse output. For a welldesigned system, the state parameters at the inlet and outlet of the EEV can be basically determined by Ta and Tw. In this article, e and ec are used as the input variables of the fuzzy controller B to control the EEV during system steady operating process, Ta and Tw are employed as input operating conditions for the gain scheduler. To improve the adaptability of the fuzzy controller B, the maximum and minimum difference value of the actual superheat and the target superheat (ek,max and ek,min) between two neighboring pulse output (Duk and Dukþ1), are adopted to adjust the output gain factor. 3.3.2. The structure and logic of fuzzy controller B According to the operating characteristics of the ASHPWH during start-up mentioned early, fuzzy controller B is composed of fuzzy sets, adaptive rules and defuzzifier as below. 3.3.2.1. Fuzzification process of fuzzy controller B. Fuzzification process includes the following steps: (1) choose input and output variables; (2) establish the range of each variable; (3) convert inputs and outputs into membership functions. For the fuzzy controller B, the input variables are the error (e) and derivation of the error (ec), the output variable is the pulse output number (Du). Each variable is defined with 11 membership functions based on the actual working conditions of the ASHPWH. The fuzzy sets of e, ec and Duk are expressed as NL, NB, NM, NS, NT, ZE, PT, PS, PM, PB, PL based on triangular membership functions. Thus, numerical data are converted into symbolic form. 3.3.2.2. The control rules and defuzzification process of fuzzy controller B. The general form of each rule for fuzzy controller B is: If e ¼ ZE and ec ¼ ZE, then Du ¼ ZE. K(Ta,Tw) is the output gain factor of the controller B, which is fitted in the function of Ta and Tw. To improve the adaptability of the fuzzy controller B, ek,max and ek,min are introduced to adjust the output gain factor. The rules of gain scheduling are classified as Duk < 0 and Duk > 0. When Duk < 0 that means the pulse output is sent to close the expansion valve, K(Ta,Tw) will be regulated as the following rules. If ek;max > c1, then K ðkÞ ðTa ; Tw Þ ¼ u1 K ðk1Þ ðTa ; Tw Þ If ek;max < c3, then K ðkÞ ðTa ; Tw Þ ¼ u3 K ðk1Þ ðTa ; Tw Þ If c1 < ek;max < c3, then K ðkÞ ðTa ; Tw Þ ¼ K ðk1Þ ðTa ; Tw Þ
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When Duk > 0 that means the pulse output is sent to open the expansion valve, K(Ta,Tw) will be regulated as the following rules. If ek;min > c2, then K ðkÞ ðTa ; Tw Þ ¼ u2 K ðk1Þ ðTa ; Tw Þ If ek;min < c4, then K ðkÞ ðTa ; Tw Þ ¼ u4 K ðk1Þ ðTa ; Tw Þ If c2 < ek;min < c4, then K ðkÞ ðTa ; Tw Þ ¼ K ðk1Þ ðTa ; Tw Þ where Duk represents kth pulse output number on EEV during steady operating processes. K(k) represents the new output gain factor after the kth regulation. c1ec4 are the triggering values to adjust the output gain factor, u1eu4 are the correction factors to the output gain factor, ek,max and ek,min are the maximum and minimum difference value of the actual superheat and the target superheat between Duk and Dukþ1. For the fuzzy controller B, the input sets can be achieved through fuzzification mentioned above, and the pulse output can be calculated by the fuzzy reasoning based on center average defuzzifier.
4.1. The comparison of the superheat Fig. 4 shows the variation in the superheat as the function of water temperature when the EEV and the TEV are separately employed in the same ASHPWH system. In Fig. 4(a), the ambient temperature is 5 C the superheat of system controlled by TEV fluctuates around 0 C. Obviously, it not only decreases the efficiency but also degrades the reliability of the system because of possibility of wet compression. But for the system with the EEV, the superheat changes from 7.5 C to 5.5 C stably as the water temperature increases during steady running process. The EEV opening ranges from 125 to 42. Fig. 4(b) shows the superheat in the TEV-controlled system oscillates intensely and frequently at the
3.4. Other control principles for the EEV The experimental results indicates that overshoot of the superheat often occurs when excess pulse output is sent to close the EEV. So it is necessary to use pulse amplitude limit for reducing overshoot. The pulse amplitude limit to close the EEV can be regarded as the function of the current opening of the EEV (P), because different P may lead to different dynamic response in the superheat, even if both the pulse output and the working conditions are the same. There is usually delay between the change of the superheat and EEV opening, so the time interval between two neighboring pulse outputs cannot be too short. Otherwise it will lead to unstable behavior in the ASHPWH system. But, too long time interval of pulse outputs can also lead to the superheat being out of control. To avoid too frequent adjustment and ensure timely control on the EEV, an optimal time interval (Dso) between two neighboring pulse outputs is adopted. Theoretically, the opening of the EEV can be regulated from 0 to 500. However, choking flow in throttling process maybe occur if the opening of the EEV is too small. To avoid this situation, the range of the EEV opening is restricted within 50e500 through a software program. For example, the output pulse to close the EEV calculated by the controller is 80, while the current opening of the EEV is 100, the actual pulse output is revised to 30 by the position limit programmer automatically. The similar thing happens in the process to open the EEV. In defrosting process, the evaporator and condenser interchanged roles after the reversing valve switches, and the pressure difference between the inlet and outlet of the EEV is usually low at this moment, thus refrigerant flow entering evaporator is considerable small. The experiment shows that the EEV also has a considerable throttling effect even if under the full opening, so the full opening control strategy is employed during the defrosting process. 4. Experimental results The experiments are conducted under three typical working conditions for the subtropical climate (the ambient temperature is 5 C, 20 C and 35 C, respectively. Water temperature is 15e55 C in the TEV-controlled system. Water temperature is 17e55 C in the EEV-controlled system). The comparison of system performance under different throttle devices is presented below.
Fig. 4. Superheat and EEV opening with water temperature using the EEV or TEV: (a) Ta ¼ 5 C; (b) Ta ¼ 20 C; (c) Ta ¼ 35 C.
M. Jiang et al. / Building and Environment 46 (2011) 1954e1961
Fig. 5. Compressor discharge temperature with water temperature using the EEV or TEV: (a) Ta ¼ 5 C; (b) Ta ¼ 20 C; (c) Ta ¼ 35 C.
ambient temperature 20 C. While the superheat controlled by the EEV reduces from 6.4 C to 4.3 C gradually at the same ambient temperature. The opening of the EEV decreases from 500 to 104 correspondingly. Although the target superheat is relative low and the opening of the EEV opening is full all the time at high ambient temperature. As shown in Fig. 4(c), the superheat is rather high during whole operating process when the ambient temperature is 35 C, because the required refrigerant mass flow regulating range
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Fig. 6. Heating capacity with water temperature using the EEV or TEV: (a) Ta ¼ 5 C; (b) Ta ¼ 20 C; (c) Ta ¼ 35 C.
for the ASHPWH system is too wide. In addition, the system superheat controlled by the TEV is averagely over 3 C compared to that in the EEV-controlled system. The experimental data above indicate that the superheat of the TEV-controlled ASHPWH system is lower than that of the EEVcontrolled system at the ambient temperature 5 C and 20 C, but higher when the ambient temperature is 35 C. The results above imply the EEV has much wider working range than the TEV. More
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importantly, the reasonable control scheme and algorithm for the EEV can eliminate hunting problem that cannot be avoided in the TEV-controlled system.
Acknowledgments The work is supported by the State High Technologies R&D Program under the contract No. 2007AA05Z220.
4.2. The comparison of compressor discharge temperature As shown in Fig. 5(a), when the ambient temperature is 5 C, there is little difference in the compressor discharge temperature whether the TEV or the EEV is used. When the ambient temperature is 20 C, the compressor discharge temperature of the TEVcontrolled system is slight higher than that of the EEV-controlled system. When the ambient temperature is 35 C, the discharge temperature of the EEV-controlled system is 5 C lower than that of the TEV-controlled system under the same water temperature. 4.3. The comparison of heating capacity Fig. 6 indicates the variation in heating capacity as a function of the water temperature. As shown in Fig. 6, the heating capacity rise sharply at the beginning. After reaching the peak value, the heating capacity decreases nearly linearly with the water temperature. The averaging heating capacity of the TEV-controlled system is 2.77 kW, 4.08 kW and 5.46 kW when the ambient temperature is 5 C, 20 C and 35 C, respectively. While the averaging heating capacity of the EEV-controlled system is 2.96 kW, 4.30 kW and 5.74 kW when the ambient temperature is 5 C, 20 C and 35 C, respectively.
Nomenclature
e ec T TSH TSH,S TSH,H TSH,L TSH,M MSS DTS
Dso
Du F P K COP c1ec4
superheat error, C the derivation of superheat error, C/s Temperature, C actual superheat, C setting value of the superheat, C upper limit of the superheat during start-up process, C lower limit of the superheat during start-up process, C maximum superheat during start-up process, C minimum stable superheat, C judging temperature of terminating start-up process, C optimal time interval between two neighboring pulse outputs, s pulse output number EEV initial opening current opening position of the EEV gain factor heating coefficient of performance triggering value to adjust gain factor
4.4. The comparison of system COP The system COP is improved by optimized control on the EEV under whole working conditions, being enhanced about 8.2%, 5.5% and 6.1% at the ambient temperature 5 C, 20 C and 35 C, respectively. In the TEV-controlled system, the wet compression and oscillation of the superheat increase the irreversible loss of the system, which results in the decrease in the COP. 5. Conclusion The ASHPWH possesses wider operating ranges and more dramatic changes in working conditions. The EEV has wider regulating range in refrigerant mass flow, hence it is indispensable for the ASHPWH system. In this paper, a novel dual-fuzzy-controller to regulate the EEV specialized for the ASHPWH system is presented. Ta is used as the input variable of the fuzzy controller A to set the initial opening of the EEV during start-up. Furthermore, to improve the adaptability of the fuzzy controller A, a rule modifier based on TSH,M is used. While e and ec, together with Ta and Tw as the input operating conditions for the gain scheduler, are employed as the input variables of the fuzzy controller B to regulate the opening of the EEV during steady running process. In addition, to utilize the evaporator area to the maximum extent, TSH,S is determined by Ta and Tw. By such a self-adaptive dual-fuzzy-controller, the EEV can regulate the refrigerant more precisely and more widely, the EEV eliminates hunting problem and liquid slugging that cannot be avoided in the TEV-controlled system. Moreover, the compressor discharge temperature can be substantially lowered especially when the ambient temperature is high. In addition, the EEV also improves the COP of the ASHPWH system significantly, being about 8.2%, 5.5% and 6.1% more than the COP of the TEV-controlled system at the ambient temperature is 5 C, 20 C and 35 C, respectively. To further verify the of the universality of the control method proposed in this paper, this adaptive dual-fuzzy-controller will be applied in other ASHPWH systems (which have different types of evaporator, different refrigerants, etc.) The experimental results will be reported afterwards.
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