A third-party heat transfer fluid cooling system and control method for fuel freezing

Abstract

The present invention discloses a third-party heat transfer fluid cooling system and control method for fuel freezing, which realizes fuel cooling control by adjusting the flow of the third-party heat transfer fluid, obtains fuel temperature change data based on system simulation and systematically identifies the fuel cooling mathematical model, constructs an extended observer with a predictor to estimate interference, fuzzifies variables and establishes domains and membership, improves the fuzzy rule base, performs fuzzy reasoning and defuzzification, and verifies the effectiveness of the temperature control method through simulation. Compared with traditional PID control, the present invention has strong anti-interference ability, can shorten the adjustment time, and achieves the purpose of precise temperature control.

Description

Technical Field

[0001] The present invention relates to the technical field of aviation fuel icing system control, and in particular to a fuel icing third-party heat transfer fluid cooling system and a control method. Background Art

[0002] The existing airworthiness regulations have strict requirements on the water content and temperature of the test fuel. The fuel temperature and the method of configuring the fuel containing water directly affect the water content of the fuel and the distribution form of free water in the fuel, which in turn directly affects whether the expected amount of ice can be produced in the test oil circuit, which has an important impact on the test results. Different fuel icing test items require different fuel configuration methods and test processes. The present invention intends to study the configuration method of the test fuel through relevant standards and specifications for fuel icing tests at home and abroad, and analyze its influence relationship. In view of the fact that the water in the fuel may freeze on the wall of the heat exchanger, it is necessary to strictly control the temperature difference between the fuel and the refrigerant in the heat exchanger not to exceed 13°C, and precise temperature control cannot be achieved. It is necessary to increase the fuel heating and cooling rate through a new heating and cooling method. The heating and cooling control system should make the temperature difference as close to 24℉ (13℃) as possible without exceeding 24℉ (13℃) to ensure that the temperature difference is not over-adjusted to achieve the effect of precise temperature control.

[0003] According to the traditional method, refrigerant is used for gas-liquid two-phase heat exchange. Due to the different specific heat capacity and heat absorption capacity of each state, during the fuel cooling process, the temperature difference between the fuel and the refrigerant in the heat exchanger exceeds 13°C, causing the free water in the fuel to freeze on the wall of the heat exchanger, resulting in a decrease in the water content of the fuel and even blocking the flow channel of the heat exchanger. At the same time, if the electric heater is damaged, leaks electricity or generates sparks, it is very easy to cause serious accidents such as fire or even explosion, and the equipment has a great safety hazard.

[0004] In terms of control methods, the traditional PID has insufficient anti-interference ability and poor robustness. It is not only unable to perform self-anti-interference control for uncertain interference outside the system, but also causes overshoot and increases the control cycle. Based on this purpose, the present invention discloses a fuel freezing third-party heat transfer fluid cooling system and control method. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a composite control method for fuel freezing and cooling by a third-party heat transfer fluid in view of the defects involved in the background technology.

[0006] To achieve the above object, the technical solution adopted by the present invention is:

[0007] A fuel freezing third-party heat transfer fluid cooling system comprises a fuel tank, a plate heat exchanger, a hydraulic module and a control module.

[0008] A temperature sensor and a stirring motor are provided in the oil tank; the temperature sensor is used to sense the temperature of the oil in the oil tank, and the stirring motor is used to stir the oil in the oil tank so that the temperature distribution in the oil tank is uniform;

[0009] The hydraulic module comprises a ball valve, first to second electric pumps, a one-way valve, first to second filters, first to sixth solenoid valves, an electric regulating valve, and a safety valve;

[0010] The outlet of the oil tank, the ball valve, the first electric pump, and one end of the one-way valve are connected in sequence by pipelines;

[0011] The other end of the one-way valve is connected to one end of the first filter and one end of the sixth solenoid valve through pipelines respectively;

[0012] One end of the second filter is connected to one end of the first filter through a pipeline, and the other end is respectively connected to the other end of the sixth solenoid valve, one end of the first solenoid valve, one end of the second solenoid valve, and one end of the safety valve;

[0013] The other end of the first solenoid valve is connected to the external engine oil supply port;

[0014] One end of the cold side channel of the plate heat exchanger is connected to the inlet pipe of the oil tank, and the other end of the cold side channel is respectively connected to one end of the electric regulating valve, the other end of the second solenoid valve, and the other end of the safety valve;

[0015] One end of the hot side channel of the plate heat exchanger is connected to the output end pipeline of the external third party heat transfer fluid through the fourth solenoid valve, and the other end of the hot side channel is connected to the one end pipeline of the fifth solenoid valve through the second electric pump; the other end of the fifth solenoid valve is connected to the input end pipeline of the external third party heat transfer fluid;

[0016] One end of the third solenoid valve is connected to the other end of the electric regulating valve through a pipeline, and the other end is connected to the external engine oil return port;

[0017] The electric pump is used to control the flow of fuel and thermal fluid; the first and second filters are used to purify the oil during the internal circulation and fuel output process, and filter the undissolved water; the electric regulating valve is used to control the return oil volume; the safety valve is used to adjust the required pressure of the system;

[0018] The control module is electrically connected to the temperature sensor, the first electric pump, and the second electric pump, respectively, and is used to control the operation of the second electric pump according to the sensing data of the temperature sensor and the received target temperature.

[0019] The present invention also discloses a control method for the fuel freezing third-party heat transfer fluid cooling system, comprising the following steps:

[0020] Step 1), according to the fuel freezing third-party heat transfer fluid cooling system, a digital simulation model is built, and a mathematical model of the fuel freezing third-party heat transfer fluid cooling system is obtained by system identification based on the second electric pump speed input and the fuel temperature output;

[0021] Step 2), based on the mathematical model of fuel freezing and cooling by third-party heat transfer fluid, a composite control model of fuel freezing and cooling by third-party heat transfer fluid is established;

[0022] Step 2.1), establish a linear expansion observer, and use the Fal function to improve the linear filter link, and then improve the linear expansion state observer based on the fuel freezing third-party heat transfer fluid cooling composite control mathematical model;

[0023] Step 2.2), establish a fuzzy rule base combined with PI control to achieve optimal control with parameter self-adjustment, and establish a fuzzy adaptive controller;

[0024] Step 2.3), establish a time lag predictor, adjust parameters, and predict the lag of the actual change of temperature in the third-party thermal fluid cooling system for fuel freezing compared to the estimated change;

[0025] Step 2.4), a composite control model of fuel freezing third-party heat transfer fluid cooling is established based on the fuzzy adaptive controller, the improved extended observer, and the time-delay predictor:

[0026] First, the expected temperature is set, and the error between the expected value and the actual value and the first-order derivative of the error are used as input for fuzzification, and the domain and membership are established. Then, the improved fuzzy rule base is imported, and fuzzy reasoning is performed to achieve clarity, and three proportional integral differential control parameters are output. Then, the time-delay predictor and the improved extended observer are used to perform prediction and interference estimation, eliminate the large inertia inside the model, record the temperature, and return the new error and error change rate to iterate again.

[0027] Step 3), the control module receives the sensing data of the temperature sensor, obtains the current temperature of the oil in the oil tank, and compares the current temperature with the preset target temperature;

[0028] Step 4), controlling the temperature in the fuel tank by a third-party heat transfer fluid cooling control method based on fuel freezing;

[0029] Step 4.1), open the fifth solenoid valve to allow the third-party heat transfer fluid and fuel to exchange heat, start the stirring motor to balance the oil temperature in the oil tank; open the ball valve and the second solenoid valve, set the safety valve pressure parameter and the first electric pump speed, so that the oil flows through the oil tank, ball valve, first electric pump, check valve, primary filter, secondary filter, second solenoid valve, plate heat exchanger in sequence and then returns to the oil tank for continuous circulation;

[0030] Step 4.2), taking the difference between the current temperature and the preset target temperature as the input signal, and based on the expanded observer and fuzzy adaptive control, adjusting the speed of the second electric pump in real time to control the flow of the thermal fluid, and controlling the temperature of the fuel freezing system;

[0031] Step 4.3), after the fuel temperature reaches the desired temperature, open the first solenoid valve and close the second solenoid valve, so that the oil flows from the fuel tank, the ball valve, the first electric pump, the one-way valve, the primary filter, the secondary filter, and the first solenoid valve in sequence to supply oil to the engine components; during the oil supply process, the required pressure is adjusted through the safety valve.

[0032] As a further optimization scheme of the control method of the third-party heat transfer fluid cooling system for fuel freezing of the present invention, the mathematical model of the third-party heat transfer fluid cooling system for fuel freezing in step 2) is:

[0033]

[0034] Where y is the output temperature of the fuel tank after Laplace transform, and s is a complex variable.

[0035] As a further optimization scheme of the control method of the third-party heat transfer fluid cooling system for fuel freezing of the present invention, the detailed steps of step 2.1) are as follows:

[0036] Step 2.1.1), establish the linear expansion observer as follows:

[0037]

[0038] Among them, β1, β2, and β3 are the thresholds of the high-frequency, medium-frequency, and low-frequency coefficients preset by LESO, respectively; u is the input signal of the fuzzy adaptive controller; w is the output signal recognized by the temperature sensor; b0 is the amplification parameter of the controller; z1 is the tracking signal of the output signal; z2 is the tracking signal after the differential transformation of the output signal; and z3 is the tracking signal of the total disturbance of the system. is the first-order partial derivative of the corresponding LESO output;

[0039] Step 2.1.2), use the following Fal function to improve the linear filtering link:

[0040]

[0041] Where, e is the system error, α is a constant between 0 and 1, and δ is a constant for improving the filtering effect. The LESO improved by the Fal function can not only make the tracking error approach 0, but also has a faster tracking speed than conventional optimization control.

[0042] Step 2.1.3), based on the fuel freezing third-party heat transfer fluid plus cooling composite control mathematical model, the improved linear expansion state observer is as follows:

[0043]

[0044] Wherein, α1 and α2 are two parameter thresholds preset by the nonlinear function and 0<α1, α2<1.

[0045] As a further optimization scheme of the control method of the third-party heat transfer fluid cooling system for fuel freezing of the present invention, the specific steps of step 2.2) are as follows:

[0046] Step 2.2.1), perform fuzzification operation:

[0047] The input and output in the rule base are divided into the following seven levels {positive large, positive medium, positive small, zero, negative small, negative medium, negative large}, and the fuzzy subsets of e and ec are defined as {NB, NM, NS, ZO, PS, PM, PB}; and the domain corresponding to the fuzzy sets of e and ec is introduced, which is defined as {-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6};

[0048] Introduce the quantization function to quantize e and ec:

[0049]

[0050]

[0051] Where V max 、V min They are the maximum and minimum values ​​of the range of the set value during proportional-integral regulation, and the fuzzy operation is completed by adding a membership degree between 0 and 1 through a linear formula;

[0052] Step 2.2.2), establish the fuzzy rule base as follows:

[0053]

[0054] In the rule base, the basic domains of the two input quantities e and ec and the three output quantities are set up in one-to-one correspondence, and a set of 49 fuzzy rules is established; the fuzzy rules are reasoned to obtain a set of output language variable values ​​derived from each rule, and these output language variable values ​​are synthesized to obtain a comprehensive output fuzzy set:

[0055]

[0056] Where c0 is the exact value of the proportional integral derivative parameter after defuzzification output by the fuzzy controller, c iis the value in the domain of fuzzy control quantity, u c (c i ) is c i The membership value of the fuzzy controller is the temperature signal deviation. When the fuel is cooled, the heat exchange between the third-party heat transfer fluid and the fuel needs to be adjusted according to the real-time temperature measured by the current sensor. The comprehensive output fuzzy set obtained by fuzzy synthesis is transformed, and the language variable value is transformed into a real value in the basic domain of the input variable to control the cooling process of the mathematical model.

[0057] Step 2.2.3), establish the fuzzy adaptive controller:

[0058] According to the mathematical model of cooling fuel by third-party thermal fluid during fuel freezing, and based on the requirement in the airworthiness standard that "fuel without anti-icing additives is injected into the storage tank, and the fuel is heated so that the fuel is circulated from the tank through the heat exchanger and then returned to the tank until the fuel is heated to the expected value of 27°C", the corresponding processes of fuzzification, fuzzy reasoning and defuzzification are integrated to establish a fuzzy adaptive controller.

[0059] As a further optimization scheme of the control method of the third-party heat transfer fluid cooling system for fuel freezing of the present invention, the mathematical model G(s) of the fuel tank output after passing through the time delay predictor in step 2.3) is:

[0060] G(s)=K z *exp(-Ls) / (Ts+1)

[0061] In the formula, K z is the open-loop gain of the mathematical model, T is the preset time constant, and L is the preset lag time threshold.

[0062] As a further optimization scheme of the control method of the third-party heat transfer fluid cooling system for fuel freezing of the present invention, the fuel flow range of the first electric pump in step 4.1) is 0.75-19L / min.

[0063] Beneficial results of the present invention:

[0064] 1. According to the principle diagram of the fuel heating and cooling control system, the present invention builds a digital simulation model based on relevant components and fuel pipelines, which can more accurately simulate the fuel heating and cooling changes based on the third-party heat transfer fluid.

[0065] 2. Based on the identified mathematical model of fuel freezing and cooling control, the present invention establishes a fuel freezing third-party heat transfer fluid and cooling composite control model; compared with traditional PID control and anti-disturbance control methods, a system containing an expanded observer and fuzzy adaptive control is adopted to meet the requirement that the steady-state fuel temperature accuracy control error does not exceed 3%, shorten the adjustment time, and achieve the purpose of precise temperature control.

[0066] 3. The temperature-adding and cooling composite control method adopted by the present invention has a small temperature overshoot amplitude when interfered by external interference and temperature drift, has good robustness and performance index output quality, and can better meet the system's anti-interference requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 It is a schematic diagram of the process of the present invention;

[0068] Figure 2 It is a diagram of the cooling system of the present invention;

[0069] Figure 3 It is a schematic diagram of the principle of the temperature-adding and cooling composite control model in the present invention;

[0070] Figure 4 A schematic diagram showing the comparison of membership functions of three output items of the fuzzy rule base in the present invention;

[0071] FIG5( a ) is a comparison diagram of controller outputs of two control strategies in the presence of external interference during the heating process of the present invention;

[0072] FIG5( b ) is a comparison diagram of controller outputs of two control strategies in the present invention when there is external interference during the cooling process;

[0073] FIG6( a ) is a comparison diagram of controller outputs of two control strategies under the condition of a 1 s time delay during the heating process of the present invention;

[0074] FIG6( b ) is a comparison diagram of controller outputs of two control strategies under the condition of a 1 s time delay during the cooling process of the present invention.

[0075] In the figure, 1- stirring motor, 2- ball valve, 3- plate heat exchanger, 4.1- first electric pump, 4.2- second electric pump, 5- temperature sensor, 6- electric regulating valve, 7- one-way valve, 8.1- second filter, 8.2- first filter, 9.1- solenoid valve, 9.1- first solenoid valve, 9.2- second solenoid valve, 9.3- third solenoid valve, 9.4- fourth solenoid valve, 9.5- fifth solenoid valve, 10- safety valve. DETAILED DESCRIPTION

[0076] In order to facilitate the understanding of those skilled in the art, the present invention is further described below in conjunction with embodiments and drawings. The contents mentioned in the implementation modes are not intended to limit the present invention.

[0077] Reference Figure 1 The present invention provides a third-party heat transfer fluid cooling system and control method based on fuel freezing, including the following steps:

[0078] Design a fuel freezing and cooling system, select a suitable third-party thermal fluid and build pipelines for the system; Figure 2 As shown, a fuel freezing third-party thermal fluid cooling system is characterized by comprising a fuel tank, a plate heat exchanger, a hydraulic module and a control module.

[0079] A temperature sensor and a stirring motor are provided in the oil tank; the temperature sensor is used to sense the temperature of the oil in the oil tank, and the stirring motor is used to stir the oil in the oil tank so that the temperature distribution in the oil tank is uniform;

[0080] The hydraulic module comprises a ball valve, first to second electric pumps, a one-way valve, first to second filters, first to sixth solenoid valves, an electric regulating valve, and a safety valve;

[0081] The outlet of the oil tank, the ball valve, the first electric pump, and one end of the one-way valve are connected in sequence by pipelines;

[0082] The other end of the one-way valve is connected to one end of the first filter and one end of the sixth solenoid valve through pipelines respectively;

[0083] One end of the second filter is connected to one end of the first filter through a pipeline, and the other end is respectively connected to the other end of the sixth solenoid valve, one end of the first solenoid valve, one end of the second solenoid valve, and one end of the safety valve;

[0084] The other end of the first solenoid valve is connected to the external engine oil supply port;

[0085] One end of the cold side channel of the plate heat exchanger is connected to the inlet pipe of the oil tank, and the other end of the cold side channel is respectively connected to one end of the electric regulating valve, the other end of the second solenoid valve, and the other end of the safety valve;

[0086] One end of the hot side channel of the plate heat exchanger is connected to the output end pipeline of the external third party heat transfer fluid through the fourth solenoid valve, and the other end of the hot side channel is connected to the one end pipeline of the fifth solenoid valve through the second electric pump; the other end of the fifth solenoid valve is connected to the input end pipeline of the external third party heat transfer fluid;

[0087] One end of the third solenoid valve is connected to the other end of the electric regulating valve through a pipeline, and the other end is connected to the external engine oil return port;

[0088] The electric pump is used to control the flow of fuel and thermal fluid; the first and second filters are used to purify the oil during the internal circulation and fuel output process, and filter the undissolved water; the electric regulating valve is used to control the return oil volume; the safety valve is used to adjust the required pressure of the system;

[0089] The control module is electrically connected to the temperature sensor, the first electric pump, and the second electric pump, respectively, and is used to control the operation of the second electric pump according to the sensing data of the temperature sensor and the received target temperature.

[0090] Depend on Figure 2 As can be seen from the system diagram, one of the innovations of this invention is that the fuel oil exchanges heat with a third-party heat transfer fluid through a plate heat exchanger. According to the traditional method, refrigerant is used for gas-liquid two-phase heat exchange. Due to the different specific heat capacities and heat absorption capacities of each state, during the fuel oil cooling process, the temperature difference between the fuel oil and the refrigerant in the heat exchanger will exceed 13°C, causing the water in the fuel oil to freeze on the heat exchanger wall, resulting in a decrease in the water content of the fuel oil and even blocking the heat exchanger flow channel. The general form of the heat transfer equation for a plate heat exchanger used for heat exchange is:

[0091]

[0092] In the formula, Δt is the temperature difference between the two heat transfer media at the micro-element heat transfer surface, Q is the heat load, and k is the heat transfer coefficient of the plate heat exchanger at a certain position on the micro-element heat transfer surface. dA is the micro-element heat transfer area. In the formula, Δt and k are functions of A, which vary with position and time. In engineering, they can be simplified to the following form:

[0093] Q=kAΔt m

[0094] Where A is the heat transfer area where the aviation fuel contacts the third-party heat transfer fluid in the heat exchanger, k is the average heat transfer coefficient on the entire plate heat exchanger heat transfer surface, Δt m is the logarithmic mean temperature difference between the fuel and the refrigerant. h1 -t c2 ≠t h2 -t c1 When , the logarithmic mean error is calculated as follows:

[0095]

[0096] When t h1 -t c2 =t h2 -t c1 When Δt m =t h1 -t c2 .

[0097] In the formula, t h1 is the temperature of fuel entering the heat exchanger, t h2 is the fuel outlet temperature, t c1 is the temperature of the third-party thermal fluid entering the heat exchanger, t c2 is the third party heat conduction outlet temperature.

[0098] When using conventional electric heaters, if the electric heater is damaged, leaks electricity or generates sparks, it is very easy to cause serious safety accidents such as fire or even explosion. The fuel freezing third-party heat transfer fluid cooling system of the present invention intends to use R404a as the refrigerant for the test. R404a is an industrial medium-low temperature refrigerant and belongs to the HFC type non-azeotropic environmentally friendly refrigerant (completely free of CFC and HCFC that destroy the ozone layer). It can be used for the initial installation of new refrigeration equipment and re-addition during maintenance. Its ASHRAE safety level is the highest A1 level, that is, non-toxic and non-flammable, safe and reliable, and suitable for this cooling system.

[0099] Step 1), build a digital simulation model based on relevant components and fuel pipelines, and obtain the speed-time and temperature-time related data through simulation, and then obtain the mathematical model of fuel freezing and cooling by the third-party thermal fluid based on the second electric pump speed input and fuel temperature output by system identification:

[0100]

[0101] Where y is the output temperature of the fuel tank after Laplace transform, and s is a complex variable.

[0102] Step 2), based on the mathematical model of the fuel freezing and cooling system identified, a fuel freezing third-party heat transfer fluid cooling and cooling composite control model is established;

[0103] Step 2.1.1), establish a linear expansion observer, and use the Fal function to improve the linear filter link to observe the total disturbance of the system, improve the linear filter link, increase the tracking speed, and reduce the tracking error;

[0104] Based on the mathematical model of fuel freezing third-party thermal fluid plus cooling composite control, a linear expansion observer is established:

[0105]

[0106] Where β1, β2, and β3 are the thresholds of the high-frequency, intermediate-frequency, and low-frequency coefficients preset by LESO, u is the input signal of the fuzzy adaptive controller, w is the output signal recognized by the temperature sensor, b0 is the amplification parameter of the controller, z1 is the tracking signal of the output signal, z2 is the tracking signal after the differential transformation of the output signal, and z3 is the tracking signal of the total disturbance of the system. is the first-order partial derivative of the corresponding LESO output.

[0107] Step 2.1.2), use the following Fal function to improve the linear filtering link:

[0108]

[0109] Where, e is the system error, α is a constant between 0 and 1, and δ is a constant for improving the filtering effect. The LESO improved by the Fal function can not only make the tracking error approach 0, but also has a faster tracking speed than conventional optimization control.

[0110] Step 2.1.3), based on the fuel freezing third-party heat transfer fluid plus cooling composite control mathematical model, the improved linear expansion state observer is as follows:

[0111]

[0112] Where, α1 and α2 are two parameter thresholds preset by the nonlinear function and 0<α1, α2<1;

[0113] Step 2.2), establish a new type of fuzzy rule base combined with PI control to achieve optimal control with self-adjustment of parameters;

[0114] Step 2.2.1), fuzzification operation:

[0115] First, in order to determine the fuzzy subsets of e and ec, the rule base divides the input and output into the following seven levels {positive large, positive medium, positive small, zero, negative small, negative medium, negative large}, and defines the fuzzy subsets of e and ec as {NB, NM, NS, ZO, PS, PM, PB}. After determining the fuzzy subsets, the domain corresponding to the fuzzy sets of e and ec is introduced and defined as {-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6}.

[0116] Introduce the quantization function to quantize e and ec:

[0117]

[0118]

[0119] Where V max 、V min They are the maximum and minimum values ​​of the range of the set value during PID adjustment. The fuzzy operation is completed by adding a membership degree between 0 and 1 through a linear formula, such as Figure 4 As shown in the figure, it is the membership function diagram of the three output items of the fuzzy controller. The interval values ​​of the three items are 1000-5000, 100-300 and 1-10 respectively. It can quickly self-tune the input values ​​to make the temperature of the cooling system accurately controlled.

[0120] Step 2.2.2), establish the fuzzy rule base:

[0121] Then a fuzzy rule base was established. According to the mathematical model of the model and the parameter values ​​obtained by PID parameter adjustment, a set of 49 fuzzy rules was established. After fuzzy reasoning, the fuzzy rules obtain a set of output language variable values ​​inferred by each rule, and these output language variable values ​​are subjected to some kind of synthesis operation to obtain a comprehensive output fuzzy set.

[0122]

[0123] Where c0 is the exact value of the proportional integral derivative parameter after defuzzification output by the fuzzy controller, z i is the value in the domain of fuzzy control quantity, u c (c i ) is c i The membership value of the fuzzy controller is the temperature signal deviation. When controlling the temperature of fuel oil, the heat exchange between the third-party heat transfer fluid and the fuel oil needs to be adjusted according to the real-time temperature measured by the current sensor. For example, if the difference between the input temperature and the oil temperature measured by the sensor is negative, the system must make a positive judgment to offset the negative error. The comprehensive output fuzzy set obtained by fuzzy synthesis is transformed, and the language variable value is transformed into a real value in the basic domain of the input variable to control the temperature-adding and cooling process of the mathematical model.

[0124] Step 2.2.3), establish the fuzzy adaptive controller:

[0125] According to the mathematical model of the heat exchange temperature change between the third-party thermal fluid and the fuel, based on the requirement mentioned in the airworthiness standard that "the fuel without anti-icing additives is injected into the storage tank, and the fuel is heated so that the fuel is circulated from the tank through the heat exchanger and then returned to the tank until the fuel is heated to the expected value of 27°C", the corresponding processes of fuzzification, fuzzy reasoning, and defuzzification are integrated to establish a fuzzy adaptive controller.

[0126] Step 2.3), establish a time-delay predictor, adjust the parameters, and predict the lag between the actual change of temperature and the estimated change in the third-party thermal fluid cooling system for fuel freezing; during the heat transfer process, the temperature transfer between the thermal fluid and the fuel is delayed due to the limited heat transfer efficiency, causing the observed value of the temperature sensor to lag behind the estimated value of the mathematical model, so the improved time-delay observer model is introduced:

[0127] G(s)=K z *exp(-Ls) / (Ts+1)

[0128] In the formula, K z is the open-loop gain of the mathematical model, T is the preset time constant, L is the preset lag time threshold, and G(s) is the mathematical model of the tank output after passing through the predictor.

[0129] Adding the improved estimator to the model improves the control instability problem in the temperature lag system and reduces the error caused by temperature delay.

[0130] Step 2.4), a composite control model of fuel freezing third-party heat transfer fluid cooling is established based on the fuzzy adaptive controller, the improved extended observer, and the time-delay predictor:

[0131] like Figure 3 As shown, firstly, the expected temperature is set, the error between the expected value and the actual value and the first-order derivative of the error are used as input for fuzzification, and the domain and membership are established. Then, the improved fuzzy rule base is imported, and fuzzy reasoning is performed to achieve clarity, and three proportional integral differential control parameters are output. Then, the time-delay predictor and the improved extended observer are used to perform prediction and interference estimation, eliminate the large inertia inside the model, record the temperature, and return the new error and error change rate to iterate again.

[0132] Step 3) The control module receives the sensing data from the temperature sensor, obtains the current temperature of the oil in the oil tank, and compares the current temperature with the preset target temperature;

[0133] Step 4), based on the extended observer and fuzzy adaptive control, the temperature of the fuel freezing system is controlled.

[0134] The temperature sensor in the fuel tank will record the real-time feedback of the fuel temperature. The oil cooling and heating are achieved through the internal circulation plate heat exchanger. The temperature control is achieved by controlling the second electric pump to balance the fuel tank temperature, and start the stirring motor to make the oil in the fuel tank cool more evenly to ensure constant temperature operation. When cooling, operate the temperature setting button on the controller to set the temperature required for the system to work. Turn on the third-party thermal fluid system, press the temperature control start / stop button, and the fifth solenoid valve opens. The controller controls the flow of thermal fluid to make it enter the plate heat exchanger, and the cooling system starts to work.

[0135] Step 4.1), open the fifth solenoid valve to allow the third-party heat transfer fluid and fuel to exchange heat, start the stirring motor to balance the oil temperature in the oil tank; open the ball valve and the second solenoid valve, set the safety valve pressure parameter and the first electric pump speed, so that the oil flows through the oil tank, ball valve, first electric pump, check valve, primary filter, secondary filter, second solenoid valve, plate heat exchanger in sequence and then returns to the oil tank for continuous circulation;

[0136] Step 4.2), taking the difference between the current temperature and the preset target temperature as the input signal, and based on the expanded observer and fuzzy adaptive control, adjusting the speed of the second electric pump in real time to control the flow of the thermal fluid, and controlling the temperature of the fuel freezing system;

[0137] When the fuel inlet temperature is 20°C and 40°C, the fuel is heated and cooled respectively, and the desired temperature is set to 27°C in the controller. The error from the temperature sensor in the fuel tank and the preset temperature is received in real time, and the error is fuzzified to establish the membership, fuzzy reasoning and defuzzification to obtain the adjustment parameters of the controller. The controller converts the adjustment parameters into the speed signal output of the second electric pump, controls the flow of the heat transfer fluid to control the heat exchange effect. If the temperature does not meet the requirements, it will return a new error based on the interference estimation and error compensation of the temperature signal deviation, and re-perform fuzzy reasoning until the fuel temperature in the fuel tank is the same as the desired temperature. In order to verify the control performance of the composite controller designed by the present invention, a traditional PID controller is used for comparison under different working conditions. The superiority of the present invention is illustrated below in combination with simulation results.

[0138] As shown in Figure 5(a), when the fuel inlet temperature is 20°C, the composite control method and traditional PID are used to heat the fuel at the same time. The composite control method can reach the expected temperature of 27°C at 1 second, while the traditional PID control is still in a state of approaching the expected temperature at 10 seconds. The overshoot of the composite control method is about 3%, which is slightly lower than the traditional PID, with smaller oscillation and good robustness, and can achieve precise temperature control. Then, a first-order step signal is input at 10 seconds to simulate the uncertainty interference brought by the outside world. It can be seen from the enlarged part of the figure that when the composite control method responds to external noise interference, the temperature overshoot is less than 0.1%, which is 1 / 10 of the overshoot of the traditional PID. It can perform real-time prediction and interference estimation, and has strong anti-interference ability.

[0139] As shown in Figure 5(b), when the fuel inlet temperature is 40°C, the composite control method and traditional PID are used to cool the fuel at the same time. The composite control method also achieves the expected rapid temperature response, and the overshoot is significantly smaller than the traditional PID control, the oscillation is smaller, the robustness is good, and accurate temperature control can be achieved. Similarly, at 10s, a first-order step signal is input to simulate the uncertainty interference brought by the outside world. It can be seen from the enlarged figure that when cooling, the composite control method has stronger anti-interference ability than the traditional PID control, and the temperature overshoot is smaller, which can effectively predict and correct the external disturbance.

[0140] The composite control system can also significantly improve the steady-state performance and dynamic performance of the system and enhance the robustness of the system when there is a time delay in temperature control. In Figure 6(a), under the condition of a time delay of 1000ms, the overshoot of the temperature increase controlled by the composite control method is 3.9%. In Figure 6(b), under the same time delay condition, the overshoot of the temperature is reduced to the expected value by the composite control method, and the overshoot is 3.3%, which is significantly better than the traditional PID overshoot of 37.2%.

[0141] Step 4.3), after the fuel temperature reaches the desired temperature, open the first solenoid valve and close the second solenoid valve, so that the oil flows from the fuel tank, the ball valve, the first electric pump, the one-way valve, the primary filter, the secondary filter, and the first solenoid valve in sequence to supply oil to the engine components; during the oil supply process, the required pressure is adjusted through the safety valve.

[0142] In summary, the use of expanded observer and fuzzy adaptive control to perform composite control on the temperature of the fuel freezing system has the advantages of good tracking and strong anti-interference ability compared to ordinary PID control. It can effectively deal with the influence of external interference and large inertia on temperature control, and greatly improve the reliability and sensitivity of the fuel freezing and cooling control system. For the same expected temperature, the use of the composite control method can shorten the adjustment time and achieve the purpose of accurate temperature control, so as to ensure the stability and efficiency of the fuel freezing and cooling control system, and provide a new control idea for the water-containing fuel configured with fuel freezing in actual engineering.

Claims

1. A third-party heat transfer fluid cooling system for fuel freezing, characterized in that: Contains oil tank, plate heat exchanger, hydraulic module and control module; A temperature sensor and a stirring motor are provided in the oil tank; the temperature sensor is used to sense the temperature of the oil in the oil tank, and the stirring motor is used to stir the oil in the oil tank so that the temperature distribution in the oil tank is uniform; The hydraulic module comprises a ball valve, first to second electric pumps, a one-way valve, first to second filters, first to sixth solenoid valves, an electric regulating valve, and a safety valve; The outlet of the oil tank, the ball valve, the first electric pump, and one end of the one-way valve are connected in sequence by pipelines; The other end of the one-way valve is connected to one end of the first filter and one end of the sixth solenoid valve through pipelines respectively; One end of the second filter is connected to one end of the first filter through a pipeline, and the other end is respectively connected to the other end of the sixth solenoid valve, one end of the first solenoid valve, one end of the second solenoid valve, and one end of the safety valve; The other end of the first solenoid valve is connected to the external engine oil supply port; One end of the cold side channel of the plate heat exchanger is connected to the inlet pipe of the oil tank, and the other end of the cold side channel is respectively connected to one end of the electric regulating valve, the other end of the second solenoid valve, and the other end of the safety valve; One end of the hot side channel of the plate heat exchanger is connected to the output end pipeline of the external third party heat transfer fluid through the fourth solenoid valve, and the other end of the hot side channel is connected to the one end pipeline of the fifth solenoid valve through the second electric pump; the other end of the fifth solenoid valve is connected to the input end pipeline of the external third party heat transfer fluid; One end of the third solenoid valve is connected to the other end of the electric regulating valve through a pipeline, and the other end is connected to the external engine oil return port; The electric pump is used to control the flow of fuel and thermal fluid; the first and second filters are used to purify the oil during the internal circulation and fuel output process, and filter the undissolved water; the electric regulating valve is used to control the return oil volume; the safety valve is used to adjust the required pressure of the system; The control module is electrically connected to the temperature sensor, the first electric pump, and the second electric pump, respectively, and is used to control the operation of the second electric pump according to the sensing data of the temperature sensor and the received target temperature.

2. The control method of the third-party thermal fluid cooling system for fuel freezing according to claim 1 is characterized in that: The following steps are involved: Step 1), according to the fuel freezing third-party heat transfer fluid cooling system, a digital simulation model is built, and a mathematical model of the fuel freezing third-party heat transfer fluid cooling system is obtained by system identification based on the second electric pump speed input and the fuel temperature output; Step 2), based on the mathematical model of fuel freezing and cooling by third-party heat transfer fluid, a composite control model of fuel freezing and cooling by third-party heat transfer fluid is established; Step 2.1), establish a linear expansion observer, and use the Fal function to improve the linear filter link, and then improve the linear expansion state observer based on the fuel freezing third-party heat transfer fluid cooling composite control mathematical model; Step 2.2), establish a fuzzy rule base combined with PI control to achieve optimal control with parameter self-adjustment, and establish a fuzzy adaptive controller; Step 2.3), establish a time lag predictor, adjust parameters, and predict the lag of the actual change of temperature in the third-party thermal fluid cooling system for fuel freezing compared to the estimated change; Step 2.4), a composite control model of fuel freezing third-party heat transfer fluid cooling is established based on the fuzzy adaptive controller, the improved extended observer, and the time-delay predictor: First, the expected temperature is set, and the error between the expected value and the actual value and the first-order derivative of the error are used as input for fuzzification, and the domain and membership are established. Then, the improved fuzzy rule base is imported, and fuzzy reasoning is performed to achieve clarity, and three proportional integral differential control parameters are output. Then, the time-delay predictor and the improved extended observer are used to perform prediction and interference estimation, eliminate the large inertia inside the model, record the temperature, and return the new error and error change rate to iterate again. Step 3), the control module receives the sensing data of the temperature sensor, obtains the current temperature of the oil in the oil tank, and compares the current temperature with the preset target temperature; Step 4), controlling the temperature in the fuel tank by a third-party heat transfer fluid cooling control method based on fuel freezing; Step 4.1), open the fifth solenoid valve to allow the third-party heat transfer fluid and fuel to exchange heat, start the stirring motor to balance the oil temperature in the oil tank; open the ball valve and the second solenoid valve, set the safety valve pressure parameter and the first electric pump speed, so that the oil flows through the oil tank, ball valve, first electric pump, check valve, primary filter, secondary filter, second solenoid valve, plate heat exchanger in sequence and then returns to the oil tank for continuous circulation; Step 4.2), taking the difference between the current temperature and the preset target temperature as the input signal, and based on the expanded observer and fuzzy adaptive control, adjusting the speed of the second electric pump in real time to control the flow of the thermal fluid, and controlling the temperature of the fuel freezing system; Step 4.3), after the fuel temperature reaches the desired temperature, open the first solenoid valve and close the second solenoid valve, so that the oil flows from the fuel tank, the ball valve, the first electric pump, the one-way valve, the primary filter, the secondary filter, and the first solenoid valve in sequence to supply oil to the engine components; during the oil supply process, the required pressure is adjusted through the safety valve.

3. The control method of the third party heat transfer fluid cooling system for fuel freezing according to claim 2 is characterized in that: The mathematical model of the third-party heat transfer fluid cooling when the fuel freezes in step 2) is: Where y is the output temperature of the fuel tank after Laplace transform, and s is a complex variable.

4. The control method of the third party heat transfer fluid cooling system for fuel freezing according to claim 3 is characterized in that: The detailed steps of step 2.1) are as follows: Step 2.1.1), establish the linear expansion observer as follows: Among them, β1, β2, and β3 are the thresholds of the high-frequency, medium-frequency, and low-frequency coefficients preset by LESO, respectively; u is the input signal of the fuzzy adaptive controller; w is the output signal recognized by the temperature sensor; b0 is the amplification parameter of the controller; z1 is the tracking signal of the output signal; z2 is the tracking signal after the differential transformation of the output signal; and z3 is the tracking signal of the total disturbance of the system. is the first-order partial derivative of the corresponding LESO output; Step 2.1.2), use the following Fal function to improve the linear filtering link: In the formula, e is the system error, α is a constant between 0 and 1, and δ is a constant for improving the filtering effect. The LESO improved by using the Fal function can not only make the tracking error approach 0, but also has a faster tracking speed than conventional optimization control. Step 2.1.3), based on the fuel freezing third-party heat transfer fluid plus cooling composite control mathematical model, the improved linear expansion state observer is as follows: Wherein, α1 and α2 are two parameter thresholds preset by the nonlinear function and 0<α1, α2<1.

5. The control method of the third party heat transfer fluid cooling system for fuel freezing according to claim 4 is characterized in that: The specific steps of step 2.2) are as follows: Step 2.2.1), perform fuzzification operation: The input and output in the rule base are divided into the following seven levels {positive large, positive medium, positive small, zero, negative small, negative medium, negative large}, and the fuzzy subsets of e and ec are defined as {NB, NM, NS, ZO, PS, PM, PB}; and the domain corresponding to the fuzzy sets of e and ec is introduced, which is defined as {-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6}; Introduce the quantization function to quantize e and ec: Where V max 、V min They are the maximum and minimum values ​​of the range of the set value during proportional-integral regulation, and the fuzzy operation is completed by adding a membership degree between 0 and 1 through a linear formula; Step 2.2.2), establish the fuzzy rule base as follows: In the rule base, the basic domains of the two input quantities e and ec and the three output quantities are set up in one-to-one correspondence, and a set of 49 fuzzy rules is established; the fuzzy rules are reasoned to obtain a set of output language variable values ​​derived from each rule, and these output language variable values ​​are synthesized to obtain a comprehensive output fuzzy set: Where c0 is the exact value of the proportional integral derivative parameter after defuzzification output by the fuzzy controller, c i is the value in the domain of fuzzy control quantity, u c (c i ) is c i The membership value of the fuzzy controller is the temperature signal deviation. When the fuel is cooled, the heat exchange between the third-party heat transfer fluid and the fuel needs to be adjusted according to the real-time temperature measured by the current sensor. The comprehensive output fuzzy set obtained by fuzzy synthesis is transformed, and the language variable value is transformed into a real value in the basic domain of the input variable to control the cooling process of the mathematical model. Step 2.2.3), establish the fuzzy adaptive controller: According to the mathematical model of cooling fuel by third-party thermal fluid during fuel freezing, and based on the requirement in the airworthiness standard that "fuel without anti-icing additives is injected into the storage tank, and the fuel is heated so that the fuel circulates from the tank through the heat exchanger and then returns to the tank until the fuel is heated to the expected value of 27°C", the corresponding processes of fuzzification, fuzzy reasoning and defuzzification are integrated to establish a fuzzy adaptive controller.

6. The control method of the third party heat transfer fluid cooling system for fuel freezing according to claim 5 is characterized in that: The mathematical model G(s) of the fuel tank output after passing through the time-delay predictor in step 2.3) is: G(s)=K z *exp(-Ls) / (Ts+1) In the formula, K z is the open-loop gain of the mathematical model, T is the preset time constant, and L is the preset lag time threshold.

7. The control method of the third party heat transfer fluid cooling system for fuel freezing according to claim 2 is characterized in that: The fuel flow rate of the first electric pump in step 4.1) is in the range of 0.75-19 L / min.

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