Performance optimization matching design method for fan and radiator of lubricating oil cooling device

Abstract

The invention belongs to the technical field of lubricating oil cooling of an aero-engine lubricating oil system, and discloses a lubricating oil cooling device fan and radiator performance optimization matching design method, which is used for carrying out optimization design on a fan and a radiator of a lubricating oil cooling device, and testing a flow-flow resistance characteristic curve of the fan by adopting a surface mount method. The method comprises the following steps: establishing a lubricating oil radiator heat exchange model, calculating a relation between cold side flow and flow resistance, modeling heat exchange performance, obtaining a radiator heat exchange power model, completing characteristic curve matching of a fan and a radiator, correcting the radiator heat exchange power model according to a matching result, performing simulation analysis on a radiator flow field and a temperature field, and verifying the corrected model. And the corrected model is further corrected according to a simulation analysis result. Efficient heat dissipation and low-power-consumption operation of the lubricating oil cooling device are achieved, and the heat exchange efficiency is remarkably improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of lubricating oil cooling of an aero-engine lubricating oil system, and relates to a fan and radiator performance optimization matching design method of a lubricating oil cooling device, in particular to a fan and radiator performance optimization matching design method of a lubricating oil cooling device based on test, characteristic matching of the fan and the radiator, and combined with aerodynamic-thermal coupling simulation analysis. BACKGROUND

[0002] In an aero-engine and a mechanical transmission system, a lubricating oil cooling device is a core component for ensuring normal operation of a lubricating system. The lubricating oil cooling device realizes lubricating oil heat exchange through the cooperation of a fan and a radiator, ensures that the lubricating oil temperature is within a specified range, and thus avoids oil deterioration, component wear and even system failure caused by high temperature. However, the design and optimization of the existing lubricating oil cooling device face the following key problems: Performance matching is insufficient: in the traditional design method, the fan and the radiator are often designed and selected independently, and there is a lack of systematic coupling analysis. Because the flow-pressure characteristics of the fan and the flow resistance characteristics of the radiator are not effectively matched, insufficient air volume or excessive power consumption may occur under actual working conditions, resulting in low heat dissipation efficiency or energy waste.

[0003] Parameter iterative optimization is missing: the correlation between the structural parameters (such as fin spacing, heat exchange area and material thermal conductivity) of the radiator and the lubricating oil flow is complex. The radiator heat dissipation performance calculation is often a single design or evaluation, and the fan power consumption is not associated, and the heat exchange performance is not iteratively optimized to balance the heat exchange power and the fan power consumption.

[0004] Verification means is limited: the verification of the design scheme usually relies on physical tests, which are costly, time-consuming and difficult to cover all working conditions, resulting in frequent design deviations or substandard performance. SUMMARY

[0005] To solve the above problems, the application provides a fan and radiator performance optimization matching design method of a lubricating oil cooling device, which optimizes the design of the fan and the radiator systematically to maximize the heat exchange performance and accurately control the energy consumption. Through the closed-loop design process of fan and radiator characteristic curve matching-iterative optimization-multi-dimensional verification, the accuracy of the optimization and improvement of the lubricating oil cooling device is improved.

[0006] A fan and radiator performance optimization matching design method of a lubricating oil cooling device optimizes the design of the fan and the radiator of the lubricating oil cooling device, including the following steps: S1, test the flow-resistance characteristic curve of the fan by using the patch method; S2, establish a lubricating oil radiator heat exchange model to calculate the flow rate and flow resistance relationship; S3, perform heat transfer performance modeling to obtain the radiator heat transfer power model: S4. Based on the flow rate-flow resistance characteristic curve of S1 and the cold side flow rate-flow resistance relationship of S2, the characteristic curves of the fan and the heat sink are matched, and the heat sink heat transfer power model is corrected based on the matching results. S5 simulates and analyzes the flow field and temperature field of the radiator to verify the corrected model, and further modifies the corrected model based on the simulation analysis results.

[0007] Furthermore, S1 specifically includes the following steps: S11, Set up the testing device, including setting up a fan test bench, installing the fan to be tested on the test bench, and setting a mesh throttle on the inlet side of the fan's air duct. Evenly adsorb circular blocking plates onto the mesh throttle. S12, using the patch method for testing, involves adjusting the number of uniformly adsorbed circular blocking plates on the adjustable mesh throttle to adjust the fan flow rate Q flow resistance characteristic curve, and recording the control and measurement parameters. The control parameters include the fan flow rate Q and the static pressure P at the fan inlet at the beginning of the duct. 1st The measured parameters include the static pressure P at the fan inlet at the beginning of the duct. 1st Static pressure P at the inlet of the fan at the end of the air duct 2st The parameters included fan inlet temperature, fan outlet temperature, and ambient atmospheric pressure; finally, curve fitting was performed. S13, Key Parameter Verification: Including Repeatability Testing.

[0008] Furthermore, in S11, during the test, the center of the air inlet must maintain a distance of at least 1.5 times the diameter D of the duct from the ground and walls, the length of the duct at the front end of the fan must be greater than or equal to 6D, and the static pressure P must be measured using a pressure gauge at a distance D / 2 from the beginning of the duct. st1 Measure the static pressure P at the fan inlet at a distance of 2D from the end of the air duct. st2 .

[0009] Furthermore, in S12, by adjusting the number of uniformly adsorbed circular blocking plates on the grid throttle, the fan flow rate Q flow resistance characteristic curve is obtained, and multiple flow points are set to record control parameters and measurement parameters, while simultaneously recording the actual flow rate value measured by the anemometer. Based on traffic

[0010] Calculate the required P st1 The measured values ​​were recorded during the experiment. In the formula, A1 is the cross-sectional area of ​​the duct, ρ is the air density, and φ is determined based on the shape and opening of the collector. Curve fitting uses polynomial or piecewise linear interpolation to fit discrete data points into a continuous fan characteristic curve, characterizing the flow rate-flow resistance relationship.

[0011] Furthermore, in S13, the measurement and recording of S12 are repeated 3 times under the same working conditions as S11, ensuring that the error of the result each time is less than ±2%.

[0012] Furthermore, in S2, the flow resistance calculation equation is: Radiator cold edge flow resistance ΔP and airflow Q air Relationship:

[0013] Where f is the coefficient of friction, L is the length of the cold-side flow channel of the radiator, and D... h ρ is the hydraulic diameter. air For air density, A flow This refers to the cross-sectional area of ​​the cold side of the radiator. Based on the radiator core design parameters, including fin pitch s, fin height h, and fin thickness δ, calculate the equivalent flow channel dimensions, including the hydraulic diameter D. h 1. Radiator cold side cold edge flow cross-sectional area A flow and the coefficient of friction f.

[0014] Furthermore, in S3, the ε-NTU (efficiency-number of heat transfer units) model is used to establish the radiator heat transfer power Φ model: Φ=ε×C min ×(T oil,in −(T oil,out ) Where ε is the heat transfer efficiency, C min T represents the smaller specific heat capacity of lubricating oil compared to air. oil,in With T oil,out These are the inlet and outlet temperatures of the lubricating oil, respectively. Then perform parameter coupling calculations.

[0015] Furthermore, in S3, the parameter coupling calculation method is as follows: the cold edge flow rate Q... air With lubricating oil flow rate Q oil Input the calculation model, and combine the thermal conductivity λ of the heat sink material and the fin efficiency η fin and surface area A surface Calculate the heat exchange efficiency ε, heat exchange power Φ, and outlet temperature.

[0016] Furthermore, in S4, the matching design method is as follows: Modeling and definition of objective function: Φ max滑油散热器 =ε×C min ×(T oil,in −(T oil,out ) P min风扇 =Q³·k1 +Q²·k2+Q·k3+k4 Where k1, k2, k3, and k4 are fan power characteristic coefficients obtained through polynomial fitting, Φ max滑油散热器 P represents the maximum heat dissipation power of the oil cooler. min风扇 Where Q is the minimum power extracted by the fan, ε is the fan flow rate, and C is the heat exchange efficiency. min T represents the smaller specific heat capacity of lubricating oil compared to air. oil,in With T oil,out These are the inlet and outlet temperatures of the lubricating oil, respectively. Define the comprehensive evaluation index J; after discretizing the fan characteristic curve ΔP_f(Q) and the heat sink flow resistance curve ΔP_h(Q) using the exact intersection solution algorithm, solve the problem using the Newton iteration method to obtain the optimal solution of the improved model.

[0017] After optimization by this invention, the increase in fan power consumption is guaranteed to be ≤2% of the extracted power, and the heat exchange power Φ of the lubricating oil radiator is increased by 10% or other required indicators.

[0018] Furthermore, in S4, J = w1 × (Φ 滑油散热器 / Φ 滑油散热器base )−w2×(P 风扇 / P 风扇base ) The weighting factors are set to w1=0.7 and w2=0.3. The maximum value of J corresponds to the optimal operating point, Φ 滑油散热器base This represents the heat dissipation power of the prototype lubricating oil radiator.

[0019] Furthermore, the solution process using Newton's iterative method is as follows: initially, the flow rate at the point closest to the two curves is taken; Iteration termination condition: |ΔP f (Q i )−ΔP h (Q i )|<0.5%ΔP f (Q i The convergence accuracy is ≤ ±0.8%; i is a point on the curve; Output the air volume Q* under optimal operating conditions, and record the pressure rise difference error threshold ≤ ±3%; Output the air volume Q* under optimal operating conditions, and iterate Q* into the heat exchange performance model in step 3 to calculate the heat exchange efficiency ε, heat exchange power Φ, and lubricating oil outlet temperature.

[0020] Furthermore, in S5, ANSYS Fluent or STAR-CCM+ is used to simulate and analyze the flow field and temperature field of the radiator. The flow resistance, heat transfer power, and lubricating oil outlet temperature calculated by the model are compared. If the error exceeds 5%, the friction coefficient or heat transfer correlation is corrected, and the simulation is repeated. Through the simulation calculation of flow resistance and heat transfer model, the radiator performance can be accurately predicted and the reliability of the optimization and improvement scheme can be determined. Based on the simulation analysis results, it is determined whether the percentage increase in heat transfer power meets the specified requirements. If not, steps 2 to 4 are repeated for structural and calculation iterations until the percentage increase in heat transfer power meets the specified requirements.

[0021] The specific content of the model verification and correction includes: 1) Determine the performance operating point input 2) Determination of boundary conditions and material parameters Given the inlet temperature, flow rate, and pressure of the hot and cold sides of the lubricating oil cooling device, input the material's thermodynamic properties (physical properties) and thermal conductivity.

[0022] 3) Simplified modeling of the core structure of the lubricating oil radiator Due to the limitation of the number of model meshes, the solid-fluid mixed porous media method is used in the calculation to consider the flow and heat transfer in the fin region.

[0023] 4) Simulation analysis and calculation of heat transfer, flow resistance, etc. Simulation analysis yielded the heat exchange power, cold and hot edge outlet temperatures, and cold and hot edge flow resistance of the radiator.

[0024] Technical effects of the present invention: 1. This invention achieves efficient heat dissipation and low power consumption operation of the lubricating oil cooling device through precise matching and iterative optimization of the characteristic curves of the fan and the radiator, significantly improving heat exchange efficiency and reducing energy waste; combined with parametric modeling and multi-dimensional simulation verification, it ensures the reliability and accuracy of the design scheme, while shortening the development cycle and reducing trial and error costs, and can meet the stringent requirements of high performance and high reliability of lubricating oil cooling devices in aero-engines and other fields.

[0025] 2. This method significantly improves the heat dissipation efficiency of lubricating oil cooling devices through integrated design and optimization, while shortening the development cycle and reducing trial and error costs. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram of the design process for optimizing the performance matching of the fan and radiator in the lubricating oil cooling device of the present invention.

[0028] Figure 2 Principle of the patch-mount fan characteristic curve test device Figure One .

[0029] Figure 3 Principle of the patch-mount fan characteristic curve test device Figure Two .

[0030] Figure 4 Design diagram for matching the fan's flow rate and flow resistance characteristic curve with the heatsink's cold edge flow rate and flow resistance curve. Figure One .

[0031] Figure 5 Design diagram for matching the fan's flow rate and flow resistance characteristic curve with the heatsink's cold edge flow rate and flow resistance curve. Figure Two .

[0032] Figure 6 This is a schematic diagram of the structure of the lubricating oil cooling device of the present invention. Figure One .

[0033] Figure 7 This is a schematic diagram of the structure of the lubricating oil cooling device of the present invention. Figure Two .

[0034] Among them, 1-fan, 2-heat sink. Detailed Implementation

[0035] This section describes embodiments of the present invention, used to explain and illustrate the technical solutions of the present invention. Unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0036] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating directions or positional relationships, are given in the accompanying drawings and are used only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or device referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include more than one of those features. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0037] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integrated connections; they can refer to mechanical connections or point connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0038] Example 1: A method for optimizing the performance matching of a fan and radiator in an oil cooling device includes the following steps: S1, The flow rate-flow resistance characteristic curve of the fan is tested using the patch method; S2, Establish a heat transfer model for the lubricating oil radiator and calculate the relationship between cold side flow rate and flow resistance; S3, perform heat transfer performance modeling to obtain the radiator heat transfer power model: S4. Based on the flow rate-flow resistance characteristic curve of S1 and the cold side flow rate-flow resistance relationship of S2, the characteristic curves of the fan and the heat sink are matched, and the heat sink heat transfer power model is corrected based on the matching results. S5 simulates and analyzes the flow field and temperature field of the radiator to verify the corrected model, and further modifies the corrected model based on the simulation analysis results.

[0039] S1 specifically includes the following steps: S11, Set up the testing device, including setting up a fan test bench, installing the fan to be tested on the test bench, and setting a mesh throttle on the inlet side of the fan's air duct. Evenly adsorb circular blocking plates onto the mesh throttle. S12, using the patch method for testing, involves adjusting the number of uniformly adsorbed circular blocking plates on the adjustable mesh throttle to adjust the fan flow rate Q flow resistance characteristic curve, and recording the control and measurement parameters. The control parameters include the fan flow rate Q and the static pressure P at the fan inlet at the beginning of the duct. 1st The measured parameters include the static pressure P at the fan inlet at the beginning of the duct. 1st Static pressure P at the inlet of the fan at the end of the air duct 2st The parameters included fan inlet temperature, fan outlet temperature, and ambient atmospheric pressure; finally, curve fitting was performed. S13, Key Parameter Verification: Including Repeatability Testing.

[0040] In S11, during the test, the center of the air inlet must maintain a distance of at least 1.5 times the diameter D of the duct from the ground and walls, the length of the duct at the front end of the fan must be greater than or equal to 6D, and the static pressure P must be measured with a pressure gauge at a distance D / 2 from the beginning of the duct. st1Measure the static pressure P at the fan inlet at a distance of 2D from the end of the air duct. st2 .

[0041] In S12, by adjusting the number of uniformly adsorbed circular blocking plates on the grid throttle, the fan flow rate Q flow resistance characteristic curve is obtained. Multiple flow points are set to record control parameters and measurement parameters, and the actual flow rate value measured by the anemometer is recorded simultaneously. Based on traffic

[0042] Calculate the required P st1 The measured values ​​were recorded during the experiment. In the formula, A1 is the cross-sectional area of ​​the duct, ρ is the air density, and φ is determined based on the shape and opening of the collector. Curve fitting uses polynomial or piecewise linear interpolation to fit discrete data points into a continuous fan characteristic curve, characterizing the flow rate-flow resistance relationship.

[0043] In S13, the measurement and recording of S12 are repeated 3 times under the same working conditions as S11, ensuring that the error of the result is less than ±2% each time.

[0044] In S2, the equation for calculating flow resistance is: Radiator cold edge flow resistance ΔP and airflow Q air Relationship:

[0045] Where f is the coefficient of friction, L is the length of the cold-side flow channel of the radiator, and D... h ρ is the hydraulic diameter. air For air density, A flow This refers to the cross-sectional area of ​​the cold side of the radiator. Based on the radiator core design parameters, including fin pitch s, fin height h, and fin thickness δ, calculate the equivalent flow channel dimensions, including the hydraulic diameter D. h 1. Radiator cold side cold edge flow cross-sectional area A flow and the coefficient of friction f.

[0046] In S3, the ε-NTU (efficiency-number of heat transfer units) model is used to establish the heat transfer power Φ model of the radiator: Φ=ε×C min ×(T oil,in −(T oil,out ) Where ε is the heat transfer efficiency, C min T represents the smaller specific heat capacity of lubricating oil compared to air. oil,in With T oil,out These are the inlet and outlet temperatures of the lubricating oil, respectively. Then perform parameter coupling calculations.

[0047] In S3, the parameter coupling calculation method is as follows: the cold edge flow rate Q is... air With lubricating oil flow rate Q oil Input the calculation model, and combine the thermal conductivity λ of the heat sink material and the fin efficiency η fin and surface area A surface Calculate the heat exchange efficiency ε, heat exchange power Φ, and outlet temperature.

[0048] In S4, the matching design method is as follows: Modeling and definition of objective function: Φ max滑油散热器 =ε×C min ×(T oil,in −(T oil,out ) P min风扇 =Q³·k1 +Q²·k2+Q·k3+k4 Where k1, k2, k3, and k4 are fan power characteristic coefficients obtained through polynomial fitting, Φ max滑油散热器 P represents the maximum heat dissipation power of the oil cooler. min风扇 Where Q is the minimum power extracted by the fan, ε is the fan flow rate, and C is the heat exchange efficiency. min T represents the smaller specific heat capacity of lubricating oil compared to air. oil,in With T oil,out These are the inlet and outlet temperatures of the lubricating oil, respectively. Define the comprehensive evaluation index J; after discretizing the fan characteristic curve ΔP_f(Q) and the heat sink flow resistance curve ΔP_h(Q) using the exact intersection solution algorithm, solve the problem using the Newton iteration method to obtain the optimal solution of the improved model.

[0049] After optimization by this invention, the increase in fan power consumption is guaranteed to be ≤2% of the extracted power, and the heat exchange power Φ of the lubricating oil radiator is increased by 10% or other required indicators.

[0050] In S4, J = w1 × (Φ 滑油散热器 / Φ 滑油散热器base )−w2×(P 风扇 / P 风扇base ) The weighting factors are set to w1=0.7 and w2=0.3. The maximum value of J corresponds to the optimal operating point, Φ 滑油散热器base This represents the heat dissipation power of the prototype lubricating oil radiator.

[0051] The solution process using Newton's iteration method is as follows: initially, take the flow rate at the point where the two curves are closest; Iteration termination condition: |ΔP f (Q i )−ΔP h (Q i )|<0.5%ΔP f (Qi The convergence accuracy is ≤ ±0.8%; i is a point on the curve; Output the air volume Q* under optimal operating conditions, and record the pressure rise difference error threshold ≤ ±3%; Output the air volume Q* under optimal operating conditions, and iterate Q* into the heat exchange performance model in step 3 to calculate the heat exchange efficiency ε, heat exchange power Φ, and lubricating oil outlet temperature.

[0052] In S5, ANSYS Fluent or STAR-CCM+ is used to simulate and analyze the flow field and temperature field of the radiator. The flow resistance, heat transfer power, and lubricating oil outlet temperature calculated by the model are compared. If the error exceeds 5%, the friction coefficient or heat transfer correlation is corrected, and the simulation is repeated. Through the simulation calculation of flow resistance and heat transfer model, the radiator performance can be accurately predicted and the reliability of the optimization and improvement scheme can be improved. Based on the simulation analysis results, it is determined whether the percentage increase in heat transfer power meets the specified requirements. If not, steps 2 to 4 are repeated for structural and calculation iterations until the percentage increase in heat transfer power meets the specified requirements.

[0053] The specific content of the model verification and correction includes: 2) Determine the performance operating point input 2) Determination of boundary conditions and material parameters Given the inlet temperature, flow rate, and pressure of the hot and cold sides of the lubricating oil cooling device, input the material's thermodynamic properties (physical properties) and thermal conductivity.

[0054] 3) Simplified modeling of the core structure of the lubricating oil radiator Due to the limitation of the number of model meshes, the solid-fluid mixed porous media method is used in the calculation to consider the flow and heat transfer in the fin region.

[0055] 4) Simulation analysis and calculation of heat transfer, flow resistance, etc. Simulation analysis yielded the heat exchange power, cold and hot edge outlet temperatures, and cold and hot edge flow resistance of the radiator.

[0056] Example 2: To address the aforementioned issues, an integrated design method for matching the performance of the fan and radiator is needed to achieve efficient heat dissipation and low power consumption operation of the lubricating oil cooling device. While existing technologies have made preliminary attempts based on flow resistance-flow rate curve matching, they lack deep integration of heat transfer performance simulation verification with structural optimization design and experimental verification, making it difficult to ensure the reliability and accuracy of the design results. This invention proposes a performance optimization matching design method for the fan and radiator of a lubricating oil cooling device. Its core innovations lie in: fan and radiator characteristic curve matching and iterative optimization: The flow rate-pressure characteristic curve of the fan is accurately tested using a patch method, and the cold-side flow resistance characteristics of the radiator are calculated using a theoretical model. The curves of the two are matched to determine the performance intersection point, and the radiator power and outlet temperature are iteratively optimized based on the airflow at this point, achieving maximum heat transfer power and precise control of fan power consumption; parametric modeling and dynamic adjustment: A heat transfer performance calculation model of the radiator is established, linking parameters such as heat transfer area, fin spacing, material thermal conductivity, and oil flow rate. The flow resistance curve is dynamically corrected by adjusting the core structure parameters, forming a closed-loop optimization process of "design-simulation-redesign". Multi-dimensional verification: The optimized scheme is verified by CFD-thermal coupling simulation analysis to verify the performance of the design point, and combined with the measured heat transfer power of the lubricating oil comprehensive test bench to ensure the consistency between theoretical design and actual working conditions, significantly reducing trial and error costs and development cycle.

[0057] This method is not only applicable to improving the performance of aero-engine lubricating oil cooling systems, but can also be extended to the design of integrated heat dissipation devices in other fields such as vehicles and ships, providing a general solution for optimizing the function and reliability of complex thermal management systems.

[0058] Figure 1 The diagram shows a flow chart of the performance optimization design method for the fan and radiator of the lubricating oil cooling device of the present invention. The specific execution steps are as follows: Step 1: Test the fan's flow rate-flow resistance characteristic curve using the patch method. This step aims to accurately obtain the fan's flow-pressure (Q-ΔP) characteristic curve, providing a data foundation for subsequent flow resistance matching with the heatsink. The specific implementation method is as follows: 1.1 Test setup: Set up a fan test bench, including an air source, flow control valve, high-precision differential pressure sensor (range coverage (0-5) kPa (determined according to actual requirements), accuracy ±0.1%), an anemometer (hot-wire or ultrasonic), fan power extraction tester, and data acquisition system. See installation photos below. Figure 2 .

[0059] Install the fan under test (fan 1) on the test bench. During the test, use an AC variable frequency speed control motor to drive it. When installing the fan, ensure that the runout between the spline shaft on the fan and the motor axis of the test bench does not exceed 0.05mm, and ensure that the spline axis is aligned with the motor axis to avoid shaft breakage.

[0060] A grid throttling device (for flow equalization) is installed at the inlet side of the air duct (test fixture) at the front end of the fan to eliminate the influence of gas turbulence and ensure uniform flow and stable airflow inside the air duct.

[0061] During the test, the center of the air inlet should be at least 1.5 times the diameter of the duct (D) from the ground and walls to ensure natural airflow at the inlet.

[0062] The length of the fan duct at the front end should be at least 6 times the duct diameter (D). The static pressure P should be measured with a pressure gauge at a distance D / 2 from the beginning of the duct. st1 This is used to calculate the import flow rate.

[0063] Measure the static pressure P at the fan inlet at a distance of 2D from the end of the air duct. st2 .

[0064] The patch method for flow regulation involves uniformly adsorbing circular plugs (circular plug diameter 14mm or the diameter specified as needed, material is barley paper or other similar hard paper) onto the grid throttling device.

[0065] 1.2 Patch Method Testing Procedure: By adjusting the number of uniformly adsorbed circular blocking plates on the grid throttle, the flow rate Q flow resistance characteristic curve of the fan is obtained. Multiple flow points (usually 10 to 15 points) are set, and data is recorded and collected according to the table below. The actual flow rate value measured by the anemometer is recorded simultaneously.

[0066] Based on traffic Calculate the required P st1 The measured values ​​were recorded during the experiment. The experimental parameters are shown in Table 1. In the formula, A1 is the cross-sectional area of ​​the ventilation duct (m²). 2 ρ is the air density (kg / m³) 3 When selecting a conical collector (opening degree of 60°), φ is taken as 0.98. Refer to "Ventilators" and select the φ value according to the shape and opening of the collector.

[0067] Table 1 Test Record Parameters

[0068] 1.3 Curve Fitting: By using polynomial or piecewise linear interpolation, discrete (Q, ΔP) data points are fitted into a continuous fan characteristic curve to characterize its flow rate-flow resistance relationship.

[0069] 1.3 Verification of key parameters: Repeatability test: Repeat the measurement and recording 3 times under the same working conditions to ensure that the error is less than ±2%.

[0070] Step 2: Establish a heat transfer model for the lubricating oil radiator and calculate the relationship between cold side flow rate and flow resistance. This step establishes a flow resistance-heat transfer coupling model for the radiator, quantitatively analyzes the relationship between flow rate and flow resistance on the cold side (air side), and correlates the radiator's structural parameters with its heat transfer performance.

[0071] Flow resistance calculation equation: Radiator cold-side flow resistance (ΔP) versus airflow rate (Q) air The relationship between )

[0072] Where f is the coefficient of friction (related to fin structure and Reynolds number), L is the length of the cold side flow channel of the radiator, and D... h The hydraulic diameter (related to fin pitch, height, and thickness), ρ air For air density, A flow This refers to the cross-sectional area of ​​the cold side of the radiator.

[0073] Structural parameter correlation: Based on the radiator core design parameters (such as fin pitch s, fin height h, fin thickness δ, etc.), calculate the equivalent flow channel dimensions (D). h A flow ) and the coefficient of friction f.

[0074] Step 3: Heat transfer performance modeling: Heat transfer equation: The heat transfer power (Φ) model of the radiator is established using the ε-NTU (efficiency-number of heat transfer units) method: Φ=ε×C min ×(T oil,in −(T oil,out ) Where ε is the heat transfer efficiency, C min T represents the smaller specific heat capacity of lubricating oil compared to air. oil,in With T oil,out These are the inlet and outlet temperatures of the lubricating oil, respectively.

[0075] Parameter coupling calculation: cold edge flow rate Q air With lubricating oil flow rate Q oil Input the calculation model, and combine the thermal conductivity (λ) of the radiator material and the fin efficiency (η) fin ) and surface area (A surface ), calculate the heat exchange efficiency ε, heat exchange power Φ, and outlet temperature.

[0076] Step 4: Matching the characteristic curves of the fan and the heatsink The fan's flow rate-resistance characteristic curve obtained from the patch method in step 1 and the flow rate-resistance curve of the cold edge of the oil cooler in step 2 are used for matching design. Modeling and objective function definition: Φ max 滑油散热器 =ε×C min ×(T oil,in −(Toil,out ) P min风扇 = Q³·k1 + Q²·k2 + Q·k3 + k4 Where k1, k2, k3, and k4 are the fan power characteristic coefficients obtained through polynomial fitting.

[0077] Define the comprehensive evaluation index J: J = w1×(Φ 滑油散热器 / Φ 滑油散热器base ) − w2×(P 风扇 / P 风扇base ) The weighting factors are set to w1=0.7 and w2=0.3, and the maximum value of J corresponds to the optimal operating point.

[0078] Exact intersection point solution algorithm: After discretizing the fan characteristic curve ΔP_f(Q) and the heatsink resistance curve ΔP_h(Q), the Newton-Raphson iteration method is used to solve the problem. The initial guess is taken as the nearest neighbor point between the two curves; Iteration termination condition: |ΔP f (Q i )−ΔP h (Q i )|<0.5%ΔP f (Q i The convergence accuracy is ≤ ±0.8%; Output the air volume Q* under optimal operating conditions and record the pressure rise difference error threshold ≤ ±3%.

[0079] Output the optimal air volume Q*, and iterate Q* into the heat exchange performance model in step 3 to calculate the heat exchange efficiency ε, heat exchange power Φ, and lubricating oil outlet temperature. This is the best solution for improving the model.

[0080] Step 5: Model Validation and Revision The flow and temperature fields of the radiator are simulated and analyzed using ANSYS Fluent or STAR-CCM+. The calculated flow resistance, heat transfer power, and lubricating oil outlet temperature are compared with those calculated by the model. If the error exceeds 5%, the friction coefficient or heat transfer correlation is corrected, and the simulation is repeated. Through the simulation calculation of flow resistance and heat transfer model, the radiator performance can be accurately predicted, and the reliability of the optimization and improvement scheme can be verified. Based on the simulation analysis results, the percentage increase in heat transfer power is determined to meet the specified requirements. If not, steps 2-4 are repeated for structural and calculation iterations until the percentage increase in heat transfer power meets the specified requirements.

[0081] The specific content of the model verification and correction includes: 3) Determine the performance operating point input 2) Determination of boundary conditions and material parameters Given the inlet temperature, flow rate, and pressure of the hot and cold sides of the lubricating oil cooling device, input the material's thermodynamic properties (physical properties) and thermal conductivity.

[0082] 3) Simplified modeling of the core structure of the lubricating oil radiator Due to the limitation of the number of model meshes, the solid-fluid mixed porous media method is used in the calculation to consider the flow and heat transfer in the fin region.

[0083] 4) Simulation analysis and calculation of heat transfer, flow resistance, etc. Simulation analysis yielded the heat exchange power, cold and hot edge outlet temperatures, and cold and hot edge flow resistance of the radiator.

[0084] Figure 4 The diagram shows the structure of the lubricating oil cooling device of the present invention. The power output shaft of the engine upper casing is connected to the fan shaft via a spline, driving the fan impeller to rotate at high speed. The fan draws in ambient air, which passes through the radiator to cool the hot lubricating oil from the lubricating oil system, thereby ensuring the normal operating temperature of the lubricating oil system.

[0085] Precise testing technology for surface mount fan characteristic curves A patch method (circular plug adsorption adjustment) combined with a high-precision sensor network is used to dynamically acquire the flow-resistance characteristic curves (Q-ΔP) of the fan under all operating conditions. Data reliability is ensured through standardized test bench construction (e.g., 6D fan duct length, 1.5D environmental spacing) and repeatability verification (error <±2%). This solves the problem of inaccurate fan characteristic testing in traditional methods, providing a high-fidelity data foundation for subsequent matching.

[0086] Radiator flow resistance-heat transfer coupling modeling method A joint calculation framework based on the flow resistance equation (ΔP=f(Qair)) and the ε-NTU heat transfer model, using fin structural parameters (pitch s, height h, thickness δ), is established. This framework integrates multiple parameters such as cold edge flow rate, lubricating oil flow rate, and material thermal conductivity (λ) to achieve quantitative prediction of heat dissipation power (Φ) and outlet temperature (Toil,out). This overcomes the limitations of traditional independent design, enabling dynamic coupling analysis of radiator performance and structural parameters.

[0087] Invention Point 3: Fan-Heater Characteristic Curve Matching and Iterative Optimization Mechanism By superimposing and matching the fan's Q-ΔP curve with the radiator's flow resistance curve to determine the performance intersection point, the heat exchange power and power consumption balance are optimized through closed-loop iteration (adjusting fin parameters, airflow, etc.) until the required percentage improvement (e.g., >5%) is met. This systematically solves the problem of fan and radiator synergy optimization, achieving maximum efficiency and precise energy consumption control.

[0088] CFD-thermal coupling simulation verification and simplified modeling of porous media ANSYS / STAR-CCM+ was used to perform multiphysics simulations on the optimized scheme. The fin region model was simplified using a solid-fluid hybrid porous medium method. Key indicators such as flow resistance and heat transfer power were compared (error <5%), and the friction coefficient or heat transfer correlation was dynamically corrected. This significantly reduced experimental costs, shortened the development cycle, and improved the first-pass yield of the design scheme.

[0089] Design-Simulation-Experiment Closed-Loop Verification System It integrates patch testing, parametric modeling, CFD simulation, and actual testing on a lubricating oil comprehensive test bench, forming a complete process of "characteristic matching → iterative optimization → simulation verification → test closed loop". This ensures consistency between theory and actual working conditions, provides a general solution, and can be extended to fields such as vehicles and ships, combining engineering applicability with theoretical rigor.

[0090] The above description is merely a specific embodiment of the present invention, providing a detailed description of the invention. Parts not covered herein are conventional techniques. However, the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for optimizing the performance matching of a fan and radiator in an oil cooling device, characterized in that: Includes the following steps: S1, The flow rate-flow resistance characteristic curve of the fan is tested using the patch method; S2, Establish a heat transfer model for the lubricating oil radiator and calculate the relationship between cold side flow rate and flow resistance; S3, perform heat transfer performance modeling to obtain the radiator heat transfer power model: S4. Based on the flow rate-flow resistance characteristic curve of S1 and the cold side flow rate-flow resistance relationship of S2, the characteristic curves of the fan and the heat sink are matched, and the heat sink heat transfer power model is corrected based on the matching results. S5 simulates and analyzes the flow field and temperature field of the radiator to verify the corrected model, and further modifies the corrected model based on the simulation analysis results.

2. The method for optimizing the matching of fan and radiator performance in a lubricating oil cooling device according to claim 1, characterized in that, S1 specifically includes the following steps: S11, Set up the testing device, including setting up a fan test bench, installing the fan to be tested on the test bench, and setting a mesh throttle on the inlet side of the fan's air duct. Evenly adsorb circular blocking plates onto the mesh throttle. S12, using the patch method for testing, involves adjusting the number of uniformly adsorbed circular blocking plates on the adjustable mesh throttle to adjust the fan flow rate Q flow resistance characteristic curve, and recording the control and measurement parameters. The control parameters include the fan flow rate Q and the static pressure P at the fan inlet at the beginning of the duct. 1st The measured parameters include the static pressure P at the fan inlet at the beginning of the duct. 1st Static pressure P at the inlet of the fan at the end of the air duct 2st The parameters included fan inlet temperature, fan outlet temperature, and ambient atmospheric pressure; finally, curve fitting was performed. S13, Key Parameter Verification: Including Repeatability Testing.

3. The method for optimizing the matching of fan and radiator performance in a lubricating oil cooling device according to claim 2, characterized in that, In S11, during the test, the center of the air inlet must maintain a distance of at least 1.5 times the diameter D of the duct from the ground and walls, the length of the duct at the front end of the fan must be greater than or equal to 6D, and the static pressure P must be measured with a pressure gauge at a distance D / 2 from the beginning of the duct. st1 Measure the static pressure P at the fan inlet at a distance of 2D from the end of the air duct. st2 .

4. The method for optimizing the matching design of the fan and radiator performance of a lubricating oil cooling device according to claim 2, characterized in that, In S12, by adjusting the number of uniformly adsorbed circular blocking plates on the grid throttle, the fan flow rate Q flow resistance characteristic curve is obtained. Multiple flow points are set to record control parameters and measurement parameters, and the actual flow rate value measured by the anemometer is recorded simultaneously. Based on traffic Calculate the required P st1 The measured values ​​were recorded during the experiment. In the formula, A1 is the cross-sectional area of ​​the duct, ρ is the air density, and φ is determined based on the shape and opening of the collector. Curve fitting uses polynomial or piecewise linear interpolation to fit discrete data points into a continuous fan characteristic curve, characterizing the flow rate-flow resistance relationship.

5. The method for optimizing the matching design of the fan and radiator performance of a lubricating oil cooling device according to claim 2, characterized in that, In S13, the measurement and recording of S12 are repeated 3 times under the same working conditions as S11, ensuring that the error of the result is less than ±2% each time.

6. The method for optimizing the matching of fan and radiator performance in a lubricating oil cooling device according to claim 1, characterized in that, In S2, the equation for calculating flow resistance is: Radiator cold edge flow resistance ΔP and airflow Q air Relationship : Where f is the coefficient of friction, L is the length of the cold-side flow channel of the radiator, and D... h ρ is the hydraulic diameter. air For air density, A flow This refers to the cross-sectional area of ​​the cold side of the radiator. Based on the radiator core design parameters, including fin pitch s, fin height h, and fin thickness δ, calculate the equivalent flow channel dimensions, including the hydraulic diameter D. h 1. Radiator cold side cold edge flow cross-sectional area A flow and the coefficient of friction f.

7. The method for optimizing the matching design of the fan and radiator performance of a lubricating oil cooling device according to claim 1, characterized in that, In S3, the ε-NTU (efficiency-number of heat transfer units) model is used to establish the heat transfer power Φ model of the radiator: Φ=ε×C min ×(T oil,in −(T oil,out ) Where ε is the heat transfer efficiency, C min T represents the smaller specific heat capacity of lubricating oil compared to air. oil,in With T oil,out These are the inlet and outlet temperatures of the lubricating oil, respectively. Then perform parameter coupling calculations.

8. The method for optimizing the matching of fan and radiator performance in a lubricating oil cooling device according to claim 7, characterized in that, In S3, the parameter coupling calculation method is as follows: the cold edge flow rate Q is... air With lubricating oil flow rate Q oil Input the calculation model, and combine the thermal conductivity λ of the heat sink material and the fin efficiency η fin and surface area A surface Calculate the heat exchange efficiency ε, heat exchange power Φ, and outlet temperature.

9. The method for optimizing the matching of fan and radiator performance in a lubricating oil cooling device according to claim 1, characterized in that, In S4, the matching design method is as follows: Modeling and definition of objective function: Φ max滑油散热器 =ε×C min ×(T oil,in −(T oil,out ) P min风扇 =Q³·k1 +Q²·k2+Q·k3+k4 Where k1, k2, k3, and k4 are fan power characteristic coefficients obtained through polynomial fitting, Φ max滑油散热器 P represents the maximum heat dissipation power of the oil cooler. min风扇 Where Q is the minimum power extracted by the fan, ε is the fan flow rate, and C is the heat exchange efficiency. min T represents the smaller specific heat capacity of lubricating oil compared to air. oil,in With T oil,out These are the inlet and outlet temperatures of the lubricating oil, respectively. Define the comprehensive evaluation index J; after discretizing the fan characteristic curve ΔP_f(Q) and the heat sink flow resistance curve ΔP_h(Q) using the exact intersection solution algorithm, solve the problem using the Newton iteration method to obtain the optimal solution of the improved model.

10. The method for optimizing the matching design of the fan and radiator performance of an oil cooling device according to claim 9, characterized in that, In S4, J = w1×(Φ 滑油散热器 / Φ 滑油散热器base ) - w2×(P 风扇 / P 风扇base ) The weighting factors are set to w1=0.7 and w2=0.

3. The maximum value of J corresponds to the optimal operating point, Φ 滑油散热器base This represents the heat dissipation power of the prototype lubricating oil radiator.

Images