Design method of aviation electric fuel pump based on structure optimization and intelligent control

Abstract

The invention discloses an aviation electric fuel pump design method based on structure optimization and intelligent control, belongs to the field of intelligent optimization design and control, and aims to optimize the structure of a gear pump, simplify the bearing design and neglect a diffusion area and an unloading groove, so that the gear pump better meets the quality requirement in practical application, and the gear pump design method is suitable for large-scale popularization and application. And a sparrow search algorithm is used for optimizing structural parameters, so that the quality and efficiency of the gear pump are improved. The spline is additionally arranged between the motor end and the gear pump end of the gear shaft, rotation isolation of the two ends is achieved, and the problem that the electric fuel pump is stuck in the to-be-loaded starting stage is effectively solved. By redesigning the shell and comprehensively considering the problems of weight, leakage, torque and the like, the overall design of the electric fuel pump is optimized. By adopting a super-spiral direct torque control method, rapid torque response and accurate flow control of the electric fuel pump are realized. According to the method, the gain parameters of the controller are optimized through the sparrow search algorithm, and the control precision and the steady-state performance of the system are improved.

Description

Technical Field

[0001] The invention relates to the field of intelligent optimization design and control technology, and in particular to a design method for an aviation electric fuel pump based on structural optimization and intelligent control. Background Art

[0002] At present, the fuel systems of modern large passenger aircraft mostly use electric fuel pumps with a variable displacement pump structure driven by a high-speed induction motor. Electric pumps with this structure have some significant disadvantages, especially low energy efficiency at partial load, wear and noise caused by high speed.

[0003] As an emerging intelligent optimization algorithm, the Sparrow Search Algorithm (SSA) can be applied in the design and optimization of electric fuel pumps. By simulating the behavior of sparrows foraging and escaping from predators, SSA has a strong global search capability and can avoid falling into local optimal solutions when solving complex design optimization problems. Especially in the multi-dimensional and multi-objective optimization of electric fuel pumps, SSA can show faster convergence speed and higher stability. In addition, SSA can take into account multiple performance indicators during the design process, such as the optimization of parameters such as flow control accuracy, noise and vibration, thereby improving the comprehensive performance of the pump body. Compared with traditional optimization methods, SSA effectively improves the design efficiency and optimization quality, and provides new ideas for the efficient design and performance improvement of aviation electric fuel pumps.

[0004] As the core subsystem of aircraft engines, the fuel pump control system can supply fuel of corresponding flow rate and pressure to the combustion chamber under different operating conditions of the engine, thereby ensuring the smooth and safe operation of the aircraft under different flight conditions. Therefore, the quality of its control performance directly determines the safety and reliability of the entire flight system. It is very necessary to study high-performance control algorithms to achieve fast and precise control.

[0005] The superiority of electric fuel pumps has long been widely recognized at home and abroad. However, electric fuel pumps for aviation still need to have technical characteristics such as fast response speed, high steady-state accuracy, wide adjustment range, strong reliability and high power density. These requirements have become difficult problems that need to be solved urgently by current technology. Summary of the invention

[0006] The present invention provides an aviation electric fuel pump design method based on structural optimization and intelligent control, deeply analyzes the flow characteristics of the electric fuel pump, designs a high-performance flow intelligent control system, further optimizes its structure, and combines intelligent optimization algorithms such as sparrow search algorithm for innovative design, which will help promote the application and performance improvement of electric fuel pumps.

[0007] The embodiment of the present invention provides an aviation electric fuel pump design method based on structural optimization and intelligent control, comprising the following steps:

[0008] Step 1: Aiming at the quality optimization problem of the aviation electric fuel pump, the principle of the gear pump is analyzed, the strength of the gear and shaft, the minimum oil film thickness, and the design flow rate are determined to establish constraint conditions, and the overall quality of the gear pump is used as the optimization objective function to optimize the design parameters. The sparrow search algorithm is used to obtain the optimal gear pump parameter configuration and its corresponding overall quality, thereby realizing the structural optimization of the gear pump;

[0009] Step 2: To solve the problem of the aviation electric fuel pump getting stuck, the connection, positioning, strength requirements, weight, leakage, and torque issues are comprehensively considered, and the gear shaft, bearings, left and right housings, and splines are analyzed to optimize the overall design of the aviation electric fuel pump;

[0010] Step 3, in order to solve the problem of fast and accurate control of the speed of the electric fuel pump, a super-helical direct torque electric fuel pump control method is used to control the electric fuel pump based on the sparrow search algorithm to meet the response requirements of flow and torque. The speed is controlled by the PI controller of the outer loop, and the super-helical flux / torque controller of the inner loop controls the flux and torque respectively.

[0011] Step 4: Conduct characteristic analysis based on the optimized electric fuel pump prototype, perform no-load displacement test and load characteristic analysis, adjust the speed and outlet pressure, obtain the characteristic curve, and verify the electric fuel pump structure optimization and control method.

[0012] Optionally, in one embodiment of the present invention, step 1 specifically includes:

[0013] Assuming that the gear parameters are consistent and that the volume between gear teeth is equal to the volume of the gear teeth, the gear pump bearing is simplified, and the diffusion zone and the unloading groove are ignored:

[0014]

[0015] S 轴 =2πr z 2

[0016]

[0017] The overall mass of the gear pump is obtained as:

[0018] M=ρ1(2bS 轴 +BS 齿轮 )+2bρ2S 轴承

[0019] Taking the overall mass of the fuel pump as the optimization objective function, we can find the following:

[0020] minM(m,z,B,b)

[0021]

[0022] The sparrow search algorithm is used to obtain the optimal gear pump parameter configuration and its corresponding overall mass, thereby achieving structural optimization of the gear pump.

[0023] Optionally, in one embodiment of the present invention, step 2 specifically includes:

[0024] Add splines between the gear shaft motor end and the gear pump end to isolate the rotation of the two ends. Redesign the housing and comprehensively consider weight, leakage, and torque issues. Finally, the optimized overall design of the electric fuel pump is obtained:

[0025] Keep the rotor, stator size and impeller size unchanged, lengthen the driving gear shaft at the left end of the impeller to install the bearing, the right half shell and the original end cover are matched with stud screws; the left side of the bearing is positioned axially with a washer and the right side is positioned axially with the shell part; the driving gear shaft is connected with splines on the left and right sides; the gear pump is connected to the left half shell by stud screws; the oil circuit is connected to the rotor cavity and the gear pump on the left and right sides respectively, the fuel is sucked into the oil circuit through the rotation of the rotor, enters the gear pump, and then flows out from the upper channel of the left shell.

[0026] Optionally, in one embodiment of the present invention, step 2 further includes:

[0027] Choose deep groove ball bearings and add 1mm washers between bearings;

[0028] Add 7mm undercut groove after spline;

[0029] The O-ring is the external sealing ring of the long screw.

[0030] Optionally, in one embodiment of the present invention, step 3 further includes:

[0031] According to the direct torque control principle, one loop controls the flux, one loop controls the torque, and the outer loop controls the speed. The outer loop uses a PI controller and the inner loop uses a super-helical flux / torque controller.

[0032] The super-helical flux controller is designed as:

[0033]

[0034] Among them, the sliding mode variable is the error of the flux amplitude, and the gain K pd and K id Satisfy stability conditions;

[0035] The superhelical torque controller is designed to:

[0036]

[0037] Among them, the sliding mode variable is the torque error, and the gain K pq and K iq Satisfy stability conditions;

[0038] In the sparrow search algorithm, the position of the sparrow population is represented by the matrix X:

[0039]

[0040] Among them, n is the number of sparrows, d is the dimension of the variable to be optimized, and the fitness value of each sparrow is expressed as:

[0041]

[0042] F X Each row in represents the fitness value of each sparrow;

[0043] The sparrows with the highest fitness values ​​are regarded as producers. During the iteration process, the producer's position is updated as follows:

[0044]

[0045] Where t is the current iteration number, j = 1, 2, ..., d, is the value of the j-th dimension variable of the i-th sparrow at the t-th iteration, iter max is the maximum number of iterations, α∈(0,1] is a random number, R2(R2∈[0,1]) and ST(ST∈[0.5,1.0]) are the alarm value and safety threshold respectively, Q is a random number that follows a normal distribution, and L is a 1×d matrix in which all elements are 1;

[0046] The follower's position is updated as follows:

[0047]

[0048] Among them, X P is the optimal position among producers, X worst is the current global worst position, A is a 1×d matrix, in which all elements are randomly 1 or -1, A + =A T (AA T ) -1 ;

[0049] Randomly select alerters from the entire sparrow population, and the position update formula of the alerter is:

[0050]

[0051] Among them, X best is the global optimal position, β~N(0,1) is the parameter controlling the step size, K∈[-1,1] is a random number, and f i is the current sparrow fitness value, f g and f w are the fitness values ​​of the global optimal position and the worst position respectively, and ε is a constant;

[0052] The flow rate and torque errors are used as the control targets of the sparrow search algorithm to select the parameter gain of the controller in the loop, thereby ultimately determining the parameters in the controller.

[0053] Optionally, in one embodiment of the present invention, step 4 further includes:

[0054] Carry out characteristic analysis based on the optimized electric fuel pump prototype: verify whether the improved and optimized electric fuel pump can operate stably without failure, and whether its stability and dynamic performance meet the design requirements; verify whether the performance indicators of the fuel supply of the electric fuel pump and the pulsation of the fuel supply meet the design requirements; and test the reliability and stability of the electric fuel pump operation.

[0055] Optionally, in one embodiment of the present invention, in step 4, the characteristic analysis platform uses a turbine flowmeter to measure the fuel flow rate. The principle of the turbine flowmeter to measure the flow rate is: the fluid flows through the turbine to drive the turbine to rotate. When the turbine rotates, the sensor outputs a pulse signal that is proportional to the flow rate. The frequency of the pulse signal is measured and then a numerical transformation is performed to obtain the flow value.

[0056] Optionally, in one embodiment of the present invention, in step 4, the characteristic analysis process is as follows:

[0057] The starting pump group is equipped with a motor. After the gear pump inlet draws oil from the oil tank, it generates working oil flow through the oil outlet. The pressure sensor displays the working pressure of the pump outlet, and the flow sensor displays the working oil flow rate of the pump outlet. The back pressure valve is adjusted to control the pump workload. The pump speed is controlled by adjusting the power supply current of the built-in motor. Finally, a complete control system is obtained. The following no-load displacement test and load test are subjected to characteristic analysis.

[0058] The design method of an aviation electric fuel pump based on structural optimization and intelligent control according to an embodiment of the present invention has the following beneficial effects:

[0059] (1) The present invention simplifies the bearing design and ignores the pressure diffusion area and the unloading groove by optimizing the structure of the gear pump, so that it is more in line with the quality requirements in practical applications. The sparrow search algorithm is used to optimize the structural parameters, thereby improving the quality and efficiency of the gear pump.

[0060] (2) The present invention achieves rotation isolation between the motor end and the gear pump end of the gear shaft by adding a spline, which effectively solves the problem of the electric fuel pump getting stuck during the start-up phase. The overall design of the electric fuel pump is optimized by redesigning the housing and comprehensively considering weight, leakage, torque and other issues.

[0061] (3) The present invention adopts a super-helical direct torque control method to achieve rapid torque response and precise flow control of the electric fuel pump. The method optimizes the gain parameters of the controller through a sparrow search algorithm, thereby improving the control accuracy and steady-state performance of the system.

[0062] (4) The present invention designs a test system based on a turbine flowmeter and a variety of sensors, which can monitor the flow rate, pressure and other performance parameters of the electric fuel pump in real time, effectively verify the stability, fuel supply and dynamic performance of the pump, and ensure that it meets the design requirements.

[0063] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0065] Figure 1 This is the general diagram of the electric fuel pump structure before improvement;

[0066] Figure 2 Schematic diagram of washers added for bearing diameter;

[0067] Figure 3 This is a schematic diagram of the tool recess behind the spline;

[0068] Figure 4 The figure is a schematic diagram of the replaced sealing ring;

[0069] Figure 5 This is the overall design diagram of the optimized electric fuel pump;

[0070] Figure 6 This is the overall control framework diagram of the electric fuel pump;

[0071] Figure 7 Flowchart for the sparrow search algorithm;

[0072] Figure 8 Schematic diagram of the aviation electric fuel pump test system;

[0073] Fig. 9 This is the relationship diagram of flow rate versus speed in the electric fuel pump test experiment;

[0074] Fig.10This is the speed change diagram after adding back pressure in the electric fuel pump test experiment;

[0075] Fig.11 This is a graph showing the relationship between power and back pressure during the electric fuel pump test. DETAILED DESCRIPTION

[0076] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0077] The design method of aviation electric fuel pump based on structural optimization and intelligent control includes the following steps:

[0078] Step 1, aiming at the quality optimization problem of aviation electric fuel pump, analyze the principle of gear pump, determine the strength of gear and shaft, minimum oil film thickness, and design flow rate to establish constraint conditions, take the overall quality of gear pump as the optimization objective function to optimize the design parameters, and use sparrow search algorithm to obtain the optimal gear pump parameter configuration and its corresponding overall quality, so as to achieve structural optimization of gear pump.

[0079] In order to reduce the weight of the aviation electric fuel pump as much as possible, the principle of the gear pump is first analyzed, and the strength of the gear and shaft, the minimum oil film thickness, the design flow rate and other constraints are determined. The overall quality of the gear pump is used as the objective function to optimize the design parameters. The optimization algorithm is used to output the optimal gear pump parameter configuration and its corresponding overall quality. According to the optimization results, the parameter characteristics of the gear are obtained, and the instantaneous flow rate, theoretical oil supply, oil supply pulsation of the gear pump and the influence of each parameter on the oil supply are analyzed. The overall quality of the gear pump is optimized through the sparrow search algorithm.

[0080] Step 2, in response to the stuck problem of the aviation electric fuel pump, the connection, positioning, strength requirements, as well as weight, leakage, and torque issues are comprehensively considered, and the gear shaft, bearings, left and right housings, and splines are analyzed to achieve overall design optimization of the aviation electric fuel pump.

[0081] In order to avoid the jam of the aviation electric fuel pump, the overall design optimization of the aviation electric fuel pump is implemented based on an in-depth analysis of the principle of the electric fuel pump, involving the optimization of the housing, gear shaft, spline, bearing, sealing ring, etc., and the optimized aviation electric fuel pump CAD overall design drawings and parts drawings are obtained.

[0082] Step 3, in order to solve the problem of fast and accurate control of the electric fuel pump speed, a super-helical direct torque electric fuel pump control method is used to control the electric fuel pump based on the sparrow search algorithm to meet the response requirements of flow and torque. The speed is controlled by the PI controller of the outer loop, and the super-helical flux / torque controller of the inner loop controls the flux and torque respectively.

[0083] The present invention uses super-helical direct torque control to control the electric fuel pump to meet the response requirements of flow and torque. The speed is controlled by the PI controller of the outer loop, and the super-helical flux / torque controller of the inner loop controls the flux and torque respectively. The controller gain parameters are optimized by the sparrow search algorithm to reduce the flow and torque errors, thereby improving the control accuracy.

[0084] Step 4: Conduct characteristic analysis based on the optimized electric fuel pump prototype, perform no-load displacement test and load characteristic analysis, adjust the speed and outlet pressure, obtain the characteristic curve, and verify the electric fuel pump structure optimization and control method.

[0085] The characteristics of the electric fuel pump were analyzed to verify the pump's stability, fuel supply performance, and operational reliability. The experiment used aviation kerosene as fuel, and the pump's inlet and outlet pressures were adjusted by controlling the overflow valve and throttle valve. Key data were measured using turbine flowmeters, pressure sensors, and temperature sensors, and the pump's speed was adjusted by the main controller. The test was divided into no-load displacement test and load test, analyzing the outlet pressure, flow rate, and volumetric efficiency, and evaluating the pump's performance at different speeds and loads.

[0086] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description is given below with reference to the accompanying drawings and specific embodiments.

[0087] (1) Optimization design of gear pump structure for quality issues

[0088] For the convenience of research, it is assumed that the gear parameters are the same, and the volume between gear teeth is equal to the volume of the gear teeth. Now simplify the gear pump bearing, ignore the expansion area and unloading groove, etc. The simplified gear pump is as follows Figure 1 shown.

[0089]

[0090] S 轴 =2πr z 2

[0091]

[0092]

[0093] In the formula, is the pressure angle, r is the pitch circle radius, r a S is the tooth top radius, 轴 is the cross-sectional area of ​​the shaft, S 轴承 is the cross-sectional area of ​​the bearing, S 齿轮 is the cross-sectional area of ​​the gear, r f is the tooth root circle radius;

[0094] The total mass of the main components of the gear pump can be obtained as:

[0095] M=ρ1(2bS 轴 +BS 齿轮 )+2bρ2S 轴承

[0096] Where M is the overall mass of the gear pump, ρ1 is the density of the gear and shaft, b is the bearing width, B is the tooth width, and ρ2 is the bearing density;

[0097] Taking the overall mass of the fuel pump as the objective function for optimization, the following mathematical description can be obtained:

[0098] minM(m,z,B,b)

[0099]

[0100] In the formula, m is the module, z is the number of teeth, N* is a positive integer, Q 需求 is the required fuel flow, Q is the actual fuel flow, F is the bearing load, d z is the bearing diameter, [p] is the bearing pressure constraint, n is the gear speed, [pv] is the bearing load capacity constraint, ρ is the fuel density, μ is the Poisson's ratio, E is the elastic modulus, [σ] H is the gear contact fatigue constraint, [σ] F is the gear bending strength constraint, K is the load factor, T is the torque of the driven wheel due to the hydraulic pressure, and Y F is the tooth form coefficient, z1 is the number of teeth of the driving gear, α g1 is the engagement angle, m 标准 is the standard modulus, d f is the journal diameter, D is the minimum diameter;

[0101] The sparrow search algorithm is adopted and Matlab is used for optimization calculation to obtain the optimized parameters.

[0102] (2) Overall design optimization of aviation electric fuel pumps to address the problem of jamming

[0103] In actual applications, the rotation of the motor may cause vibration or swaying. Since the motor and the gear pump are connected by a shaft, namely the driving gear shaft, it will affect the operation of the gear pump. At the same time, the motor and the gear pump have different speed requirements. If the speed is too high, a local high-pressure area will be formed at the inlet of the gear pump, which will increase the end face leakage and cause insufficient filling losses.

[0104] In order to solve this problem, the present invention adds a spline between the motor end of the gear shaft and the gear pump end to relatively isolate the rotation of the two ends, in the hope of solving the problem of the electric pump being blocked during the waiting and starting stage, that is, the problem of the pump being stuck. At the same time, the housing is redesigned, and the weight problem, leakage problem, and torque problem are comprehensively considered, and finally the overall design of the electric fuel pump after optimization is obtained.

[0105] 1) Keep the rotor, stator and impeller dimensions unchanged, lengthen the driving gear shaft at the left end of the impeller to facilitate the installation of the bearing, and use stud screws to match the right half shell with the original end cover. The left side of the bearing is positioned with a washer, and the right side is positioned axially with the shell part. The driving gear shaft is connected to the left and right with splines. The gear pump is connected to the left half shell by stud screws. The left and right oil circuits are connected to the cavity where the rotor is located and the gear pump respectively. The fuel is sucked into the oil circuit through the rotation of the rotor, enters the gear pump, and then flows out from the upper channel of the left shell.

[0106] 2) Improve and optimize. The key points of optimization are as follows:

[0107] 1. Wrap the gear pump in the left housing with a larger gap to achieve adequate cooling. The left and right housings are connected by four long hexagonal screws, and a sealing ring is set outside the circumference of the screws to prevent fuel from leaking from the housing gap.

[0108] 2. The oil circuit is punched out from the side and enters the cavity where the gear pump is located.

[0109] 3. The left side of the bearing is still axially positioned by the step, and the shaft length on the right side is shortened. Considering the assembly problem, a retaining ring is selected for the axial positioning on the right side and is tightly pressed against the impeller.

[0110] 3) The improvements on details are as follows:

[0111] 1. Choose deep groove ball bearings and add 1mm washers between the bearings. Figure 2 shown.

[0112] 2. Add a 7mm back cutter groove after the spline, such as Figure 3 shown.

[0113] 3. The O-ring is the external sealing ring of the long screw. It has a simple design and a self-sealing function. It has a stable sealing effect and is relatively easy to install. Figure 4 shown.

[0114] The final improved overall design is as follows Figure 5 shown.

[0115] (3) Research on optimization control method of aviation electric fuel pump

[0116] The present invention regards the pump as the load of the motor, so the control of the electric fuel pump is actually the control of the motor. At present, direct torque control has become a mature motor control scheme like vector control. Moreover, direct torque control does not require complex coordinate transformation, can achieve fast torque response, and its structure is simple and easy to apply. Therefore, super helical direct torque control is used to control the electric fuel pump to ensure that it meets the flow and torque response requirements. The basic control framework is as follows Figure 6 As shown in the figure. Based on the direct torque control principle, one loop controls the flux, one loop controls the torque, and the outer loop controls the speed. The outer loop uses a PI controller, and the inner loop uses a super-helical flux / torque controller.

[0117] The super-helical flux controller is designed as:

[0118]

[0119] Among them, the sliding mode variable is the error of the flux amplitude, and the gain K pd and K id Satisfy the stability condition, u sd is the control input, s d is the sliding mode variable, u sd1 is the intermediate variable, K pd , K id , r is the parameter that needs to be adjusted, both are greater than 0.

[0120] The superhelical torque controller is designed to:

[0121]

[0122] Among them, the sliding mode variable is the torque error, and the gain K pq and K iq Satisfy the stability condition, u sq is the control input, s q is the sliding mode variable, u sq1 is the intermediate variable, K pq , K iq , r is the parameter that needs to be adjusted, both are greater than 0.

[0123] The sparrow search algorithm is often used in various optimization problems. In the sparrow search algorithm, the position of the sparrow population is represented by the matrix X.

[0124]

[0125] Where n is the number of sparrows and d is the dimension of the variable to be optimized. The fitness value of each sparrow can be expressed as:

[0126]

[0127] F X Each row in represents the fitness value of each sparrow.

[0128] Sparrows are divided into producers and followers. Producers are responsible for finding food and providing information about foraging areas to the population; followers use finders to obtain food. For simplicity, the behavior of sparrows can be idealized and corresponding rules can be formulated. Sparrows with higher fitness values ​​are regarded as producers, and they have better food resources. During the iteration process, the position of producers is updated as follows:

[0129]

[0130] Where t represents the current iteration number, j = 1, 2, ..., d, Iter represents the value of the j-th dimension variable of the i-th sparrow at the t-th iteration. max Represents the maximum number of iterations, α∈(0,1] is a random number. R2(R2∈[0,1]) and ST(ST∈[0.5,1.0]) represent the alarm value and safety threshold respectively. Q is a random number that follows a normal distribution, and L is a 1×d matrix in which all elements are 1.

[0131] The follower's position update method is defined as:

[0132]

[0133] Among them, X P represents the optimal position among producers, X worst represents the current global worst position, A represents a 1×d matrix, in which all elements are randomly 1 or -1, A + =A T (AA T ) -1 .

[0134] Assume that in the simulation experiment, some sparrows can be aware of the coming of danger (such as natural enemies), and these sparrows are called alerters. They are randomly selected from the entire sparrow population. The position update formula of the alerter is:

[0135]

[0136] Among them, X best is the global optimal position. β~Ν(0,1) is the parameter controlling the step size. K∈[-1,1] is a random number. fi is the current sparrow fitness value, f g and f w are the fitness values ​​of the global optimal position and the worst position respectively. ε is a small constant to avoid the denominator being 0. The process of the sparrow search algorithm is as follows Figure 7 shown.

[0137] Since the gains in both loops of the controller need to be further determined, the flow and torque errors are used as the control targets of the sparrow search algorithm to select the parameter gains of the controller in the loop, thereby ultimately determining the parameters in the controller and achieving better control effects.

[0138] (4) Research on test methods for aviation electric fuel pumps

[0139] The electric fuel pump characteristic analysis performed by the present invention includes the following main purposes:

[0140] 1. Verify whether the improved and optimized electric fuel pump can operate stably without failure, and whether its stability and dynamic performance meet the design requirements.

[0141] 2. Verify whether the performance indicators of the fuel supply of the electric fuel pump and the fuel supply pulsation meet the design requirements.

[0142] 3. Check the reliability and stability of the electric fuel pump operation.

[0143] In the experiment, aviation kerosene was used as fuel, which was extracted from the booster pump to the fuel tank, then transmitted to the electric fuel pump through the oil filter, and finally returned to the fuel tank with the help of the throttle valve and the turbine flowmeter. The inlet pressure of the electric fuel pump is changed by controlling the opening degree of the overflow valve, and the discharge pressure of the electric fuel pump is changed by controlling the opening degree of the throttle valve. The measuring range of the pressure test equipment at the import is 0-1MPa, and the data it generates is 4-20mA. At the export, the measuring range of the pressure test equipment is 0-6MPa, and the data it generates is also 4-20mA. As for the turbine flowmeter, its measuring range is 0.09733-11.51494L / min, and the data it generates is a pulse signal of 0-5V. The temperature of the fuel is measured by a thermal resistance temperature sensor, and its measuring range is between -20℃ and 350℃. After signal adjustment, the output signal of the sensor is input into the main controller. The main controller issues instructions to control the speed of the electric fuel pump according to the sensor data and the flow control program. The schematic diagram of the test system is as follows: Figure 8 As shown, among them, 1. oil tank, 2. oil filter, 3. tested pump group, 4. pressure sensor, 5. turbine flowmeter, 6. back pressure valve.

[0144] The characteristic analysis platform uses a turbine flowmeter to measure the fuel flow. The principle of the turbine flowmeter to measure the flow is to use the fluid to flow through the turbine to drive the turbine to rotate. When the turbine rotates, the sensor will output a pulse signal that is proportional to the flow rate. The frequency of the pulse signal is measured and then converted into a numerical value to obtain the flow value.

[0145] The characteristic analysis process is as follows:

[0146] After the gear pump inlet draws oil from the oil tank, it generates working oil flow through the oil outlet. The pressure sensor displays the working pressure at the pump outlet, and the flow sensor displays the working oil flow at the pump outlet. The back pressure valve is adjusted to control the pump working load. The speed of the pump is controlled by adjusting the power supply current of the built-in motor. Finally, a complete control system is obtained, and the characteristics of the following no-load displacement test and load test are analyzed.

[0147] 1) No-load displacement test

[0148] When the electric fuel pump is unloaded, first ensure its stable and reliable operation, then input the speed from 1000 to 10000r / min respectively to measure the pump flow. The theoretical flow of the pump is equal to the product of the displacement and the speed, and the error between the theoretical flow and the measured flow is obtained.

[0149] Theoretically, as the speed increases, the pump outlet flow rate increases in steps, corresponding to the speed. Fig. 9 The relationship between flow rate and speed under no-load condition is shown. It can be seen that the flow rate increases with the increase of speed, but after about 4000 rpm, the flow rate increases more slowly.

[0150] 2) Load characteristics analysis

[0151] When the electric fuel pump is under load, the pump performance test is carried out to obtain the pump outlet pressure, motor power, theoretical flow rate, measured flow rate and volumetric efficiency. The volumetric efficiency is the ratio of the measured flow rate to the theoretical flow rate. Fig.10 , Fig.11 shown. Fig.10 The figure shows the change of speed after adding back pressure. As the outlet pressure increases, the speed shows a downward trend.

[0152] Theoretically, when the pump speed increases, the pump outlet pressure remains unchanged, the motor power increases with the speed, the flow rate increases with the speed and the measured flow rate is less than the theoretical flow rate, and the volumetric efficiency decreases with the speed. Fig.11 The variation of motor power with back pressure is shown. When the outlet pressure increases, the motor power increases with the increase of outlet pressure.

[0153] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0154] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "N" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0155] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

Claims

1. A design method for an aviation electric fuel pump based on structural optimization and intelligent control, characterized in that: The following steps are involved: Step 1: Aiming at the quality optimization problem of the aviation electric fuel pump, the principle of the gear pump is analyzed, the strength of the gear and shaft, the minimum oil film thickness, and the design flow rate are determined to establish constraint conditions, and the overall quality of the gear pump is used as the optimization objective function to optimize the design parameters. The sparrow search algorithm is used to obtain the optimal gear pump parameter configuration and its corresponding overall quality, thereby realizing the structural optimization of the gear pump; Step 2: To solve the problem of the aviation electric fuel pump getting stuck, the connection, positioning, strength requirements, weight, leakage, and torque issues are comprehensively considered, and the gear shaft, bearings, left and right housings, and splines are analyzed to optimize the overall design of the aviation electric fuel pump; Step 3, in order to solve the problem of fast and accurate control of the speed of the electric fuel pump, a super-helical direct torque electric fuel pump control method is used to control the electric fuel pump based on the sparrow search algorithm to meet the response requirements of flow and torque. The speed is controlled by the PI controller of the outer loop, and the super-helical flux / torque controller of the inner loop controls the flux and torque respectively. Step 4: Conduct characteristic analysis based on the optimized electric fuel pump prototype, perform no-load displacement test and load characteristic analysis, adjust the speed and outlet pressure, obtain the characteristic curve, and verify the electric fuel pump structure optimization and control method.

2. The method according to claim 1, characterized in that Step 1 specifically includes: Assuming that the gear parameters are consistent and that the volume between gear teeth is equal to the volume of the gear teeth, the gear pump bearing is simplified, and the diffusion zone and the unloading groove are ignored: S 轴 ＝2πr z 2 In the formula, is the pressure angle, r is the pitch circle radius, r a S is the tooth top radius, 轴 is the cross-sectional area of ​​the shaft, S 轴承 is the cross-sectional area of ​​the bearing, S 齿轮 is the cross-sectional area of ​​the gear, r f is the tooth root circle radius; The overall mass of the gear pump is obtained as: M=ρ1(2bS 轴 +BS 齿轮 )+2bρ2S 轴承 Where M is the overall mass of the gear pump, ρ1 is the density of the gear and shaft, b is the bearing width, B is the tooth width, and ρ2 is the bearing density; Taking the overall quality of the fuel pump as the optimization objective function, we can find the following: minM(m,z,B,b) In the formula, m is the module, z is the number of teeth, N* is a positive integer, Q 需求 is the required fuel flow, Q is the actual fuel flow, F is the bearing load, d z is the bearing diameter, [p] is the bearing pressure constraint, n is the gear speed, [pv] is the bearing load capacity constraint, ρ is the fuel density, μ is the Poisson's ratio, E is the elastic modulus, [σ] H is the gear contact fatigue constraint, [σ] F is the gear bending strength constraint, K is the load factor, T is the torque of the driven wheel due to the hydraulic pressure, and Y F is the tooth form coefficient, z1 is the number of teeth of the driving gear, α g1 is the engagement angle, m 标准 is the standard modulus, d f is the journal diameter, D is the minimum diameter; The sparrow search algorithm is used to obtain the optimal gear pump parameter configuration and its corresponding overall mass, thereby achieving structural optimization of the gear pump.

3. The method according to claim 1, characterized in that Step 2 specifically includes: Add splines between the gear shaft motor end and the gear pump end to isolate the rotation of the two ends. Redesign the housing and comprehensively consider weight, leakage, and torque issues. Finally, the optimized overall design of the electric fuel pump is obtained: Keep the rotor, stator size and impeller size unchanged, lengthen the driving gear shaft at the left end of the impeller to install the bearing, the right half shell and the original end cover are matched with stud screws; the left side of the bearing is positioned axially with a washer and the right side is positioned axially with the shell part; the driving gear shaft is connected with splines on the left and right sides; the gear pump is connected to the left half shell by stud screws; the oil circuit is connected to the rotor cavity and the gear pump on the left and right sides respectively, the fuel is sucked into the oil circuit through the rotation of the rotor, enters the gear pump, and then flows out from the upper channel of the left shell.

4. The method according to claim 3, characterized in that The step 2 also includes: Choose deep groove ball bearings and add 1mm washers between bearings; Add 7mm undercut groove after spline; The O-ring is the outer sealing ring of the long screw.

5. The method according to claim 1, characterized in that The step 3 also includes: According to the direct torque control principle, one loop controls the flux, one loop controls the torque, and the outer loop controls the speed. The outer loop uses a PI controller and the inner loop uses a super-helical flux / torque controller. The super-helical flux controller is designed as: Among them, the sliding mode variable is the error of the flux amplitude, and the gain K pd and K id Satisfy the stability condition, u sd is the control input, s d is the sliding mode variable, u sd1 is the intermediate variable, K pd , K id , r is the parameter that needs to be adjusted, both are greater than 0; The superhelical torque controller is designed to: Among them, the sliding mode variable is the torque error, and the gain K pq and K iq Satisfy the stability condition, u sq is the control input, s q is the sliding mode variable, u sq1 is the intermediate variable, K pq , K iq , r is the parameter that needs to be adjusted, both are greater than 0; In the sparrow search algorithm, the position of the sparrow population is represented by the matrix X: Among them, n is the number of sparrows, d is the dimension of the variable to be optimized, and the fitness value of each sparrow is expressed as: F X Each row in represents the fitness value of each sparrow; The sparrows with the highest fitness values ​​are regarded as producers. During the iteration process, the producer's position is updated as follows: Where t is the current iteration number, j = 1, 2, ..., d, is the value of the j-th dimension variable of the i-th sparrow at the t-th iteration, iter max is the maximum number of iterations, α∈(0,1] is a random number, R2(R2∈[0,1]) and ST(ST∈[0.5,1.0]) are the alarm value and safety threshold respectively, Q is a random number that follows a normal distribution, and L is a 1×d matrix in which all elements are 1; The follower's position is updated as follows: Among them, X P is the optimal position among producers, X worst is the current global worst position, A is a 1×d matrix, in which all elements are randomly 1 or -1, A + =A T (AA T ) -1 ; Randomly select alerters from the entire sparrow population, and the position update formula of the alerter is: Among them, X best is the global optimal position, β~N(0,1) is the parameter controlling the step size, K∈[-1,1] is a random number, and f i is the current sparrow fitness value, f g and f w are the fitness values ​​of the global optimal position and the worst position respectively, and ε is a constant; The flow rate and torque errors are used as the control targets of the sparrow search algorithm to select the parameter gain of the controller in the loop, thereby ultimately determining the parameters in the controller.

6. The method according to claim 1, characterized in that The step 4 also includes: Carry out characteristic analysis based on the optimized electric fuel pump prototype: verify whether the improved and optimized electric fuel pump can operate stably without failure, and whether its stability and dynamic performance meet the design requirements; verify whether the performance indicators of the fuel supply of the electric fuel pump and the pulsation of the fuel supply meet the design requirements; and test the reliability and stability of the electric fuel pump operation.

7. The method according to claim 6, characterized in that In step 4, the characteristic analysis platform uses a turbine flowmeter to measure the fuel flow. The principle of the turbine flowmeter for measuring flow is: the fluid flows through the turbine to drive the turbine to rotate. When the turbine rotates, the sensor outputs a pulse signal that is proportional to the flow rate. The frequency of the pulse signal is measured and then numerically transformed to obtain the flow value.

8. The method according to claim 7, characterized in that In step 4, the characteristic analysis process is as follows: The starting pump group is equipped with a motor. After the gear pump inlet draws oil from the oil tank, it generates working oil flow through the oil outlet. The pressure sensor displays the working pressure of the pump outlet, and the flow sensor displays the working oil flow rate of the pump outlet. The back pressure valve is adjusted to control the pump workload. The pump speed is controlled by adjusting the power supply current of the built-in motor. Finally, a complete control system is obtained. The following no-load displacement test and load test are subjected to characteristic analysis.

Images