Integrated design method and device for flow restraining ribs of automobile oil pan

Abstract

The invention is suitable for the technical field of automobile oil pan design, and particularly relates to an automobile oil pan flow restraining rib integrated design method and device.The automobile oil pan flow restraining rib integrated design method comprises the steps that working condition parameters and performance requirements of an automobile oil pan are obtained; generating a plurality of flow suppression rib design schemes based on the working condition parameters and the performance requirements; wherein the flow suppression rib design scheme comprises scheme characteristic parameters and performance evaluation data; determining an effective design scheme from the plurality of flow suppression rib design schemes according to a matching relationship between the scheme characteristic parameters corresponding to each flow suppression rib design scheme and the performance evaluation data; and based on the effective design scheme, determining an optimal integrated design scheme of the flow suppression ribs of the automobile oil pan. According to the method, invalid schemes with substandard flow suppression effect, insufficient structural strength or light weight not meeting requirements can be quickly eliminated, the scheme screening period is greatly shortened, the screening accuracy is improved, and the optimal design scheme is further selected from the screened effective design schemes.

Description

Technical Field

[0001] This application belongs to the field of automotive oil pan design technology, and particularly relates to an integrated design method and device for automotive oil pan flow control ribs. Background Technology

[0002] As a crucial component of the engine lubrication system, the oil pan's core function is to store engine oil and provide a stable oil suction environment for the oil pump. During engine operation, changes in vehicle driving conditions such as acceleration, deceleration, and cornering, as well as fluctuations in engine speed, cause the engine oil in the oil pan to slosh violently, a phenomenon known as oil sloshing. Oil sloshing can not only interrupt oil pump suction, affecting engine lubrication, but also increase the impact friction between the oil and the oil pan walls, exacerbating power loss and component wear. Therefore, the design of the internal flow-damping ribs of the oil pan is essential.

[0003] With the development of simulation technology, some design processes have adopted single simulation tools for performance verification. For example, fluid simulation is used to evaluate the flow suppression effect, or structural simulation is used to verify strength performance. However, this single performance-oriented design mode can easily lead to a "one-sided" problem in the design scheme—a scheme that meets the flow suppression effect may fail to meet the lightweight target due to structural redundancy, while a lightweight optimized scheme may have structural strength risks. To solve this problem, existing technologies have begun to try to generate multiple design schemes through multiple simulation algorithms, but it is difficult to accurately identify the optimal scheme that meets the operating parameters and multiple performance requirements, which seriously restricts the design efficiency and quality of oil pan flow suppression ribs.

[0004] Therefore, how to construct an integrated design method that can efficiently generate and accurately select flow-damping rib design schemes based on operating parameters and performance requirements has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] This application provides a method and apparatus for the integrated design of flow-damping ribs for automotive oil pans, which can solve the problems of low design efficiency and quality of flow-damping ribs for oil pans in the prior art.

[0006] In a first aspect, embodiments of this application provide a method for integrating flow-damping ribs into an automotive oil pan, including: Obtain the operating parameters and performance requirements of the automotive oil pan; wherein, the operating parameters include engine speed, oil temperature, and oil flow rate, and the performance requirements include flow suppression effect, structural strength, and lightweight indicators; Based on the operating parameters and performance requirements, multiple flow-damping rib design schemes are generated; wherein, each flow-damping rib design scheme includes scheme characteristic parameters and performance evaluation data; Based on the matching relationship between the characteristic parameters of each flow-suppressing rib design scheme and the performance evaluation data, an effective design scheme is determined from multiple flow-suppressing rib design schemes; Based on the aforementioned effective design scheme, the optimal integrated design scheme for the flow-damping ribs of the automotive oil pan was determined.

[0007] The technical solutions described in this application embodiment have at least the following technical effects: The integrated design method for automotive oil pan flow damping ribs provided in this application obtains the operating parameters of the automotive oil pan, including engine speed, oil temperature, and oil flow rate, as well as performance requirements including flow damping effect, structural strength, and lightweighting indicators. Then, based on the operating parameters and performance requirements, multiple flow damping rib design schemes are generated, each including scheme characteristic parameters and performance evaluation data. Next, based on the matching relationship between the scheme characteristic parameters and performance evaluation data for each flow damping rib design scheme, an effective design scheme is determined from the multiple flow damping rib design schemes. Finally, based on the effective design schemes, the optimal integrated design scheme for the automotive oil pan flow damping ribs is determined. This method, by establishing a correlation logic between scheme characteristic parameters and performance evaluation data, can quickly eliminate invalid schemes that fail to meet the flow damping effect, structural strength, or lightweighting requirements, significantly shortening the scheme selection cycle and improving selection accuracy. It further selects the best among the selected effective design schemes, achieving a synergistic balance between flow damping effect, structural strength, and lightweighting indicators, and significantly improving the design quality and engineering applicability of the oil pan flow damping ribs.

[0008] Secondly, embodiments of this application provide an integrated design system for an automotive oil pan flow control rib, comprising: The acquisition module is used to acquire the operating parameters and performance requirements of the automotive oil pan; wherein, the operating parameters include engine speed, oil temperature, and oil flow rate, and the performance requirements include flow suppression effect, structural strength, and lightweight indicators; The generation module is used to generate multiple flow-suppressing rib design schemes based on the operating parameters and the performance requirements; wherein, the flow-suppressing rib design scheme includes scheme characteristic parameters and performance evaluation data; The first determining module is used to determine an effective design scheme from multiple flow-suppressing rib design schemes based on the matching relationship between the scheme characteristic parameters corresponding to each flow-suppressing rib design scheme and the performance evaluation data. The second determining module is used to determine the optimal integrated design scheme for the automotive oil pan flow suppression ribs based on the effective design scheme.

[0009] Thirdly, embodiments of this application provide an integrated design device for an automotive oil pan flow damper, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method described in any one of the first aspects above.

[0010] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in any one of the first aspects above.

[0011] Fifthly, embodiments of this application provide a computer program product that, when running on an integrated design device for automotive oil pan flow damping ribs, causes the integrated design device for automotive oil pan flow damping ribs to execute the integrated design method for automotive oil pan flow damping ribs described in any of the first aspects.

[0012] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart illustrating the integrated design method for the automotive oil pan flow control ribs provided in this application embodiment; Figure 2 This is a schematic diagram of the integrated design system for the automotive oil pan flow control ribs provided in this application embodiment; Figure 3 This is a schematic diagram of the integrated design device for the automotive oil pan flow control ribs provided in the embodiments of this application. Detailed Implementation

[0015] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0016] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0017] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0018] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determination" or "if the described condition or event is detected" may be interpreted, depending on the context, as "once determination," "in response to determination," "once the described condition or event is detected," or "in response to the detection of the described condition or event."

[0019] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0020] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0021] With the development of simulation technology, some design processes have adopted single simulation tools for performance verification, such as evaluating flow suppression effects through fluid simulation or verifying strength performance through structural simulation. However, this single performance-oriented design mode can easily lead to a "one-sided" problem in the design scheme—a scheme that meets the flow suppression requirements may fail to meet lightweighting requirements due to structural redundancy, while a lightweight optimized scheme may have structural strength vulnerabilities. To solve this problem, existing technologies have begun to try to generate multiple design schemes through multiple simulation algorithms, but this has brought about a new problem of low scheme selection efficiency. Due to the lack of systematic analysis methods, designers need to manually compare a large number of schemes one by one, which is not only time-consuming and labor-intensive, but also makes it difficult to accurately identify the optimal scheme that meets the operating parameters and multiple performance requirements, seriously restricting the design efficiency and quality of oil pan flow suppression ribs.

[0022] To address the aforementioned issues, this application provides a method and apparatus for integrated design of flow-damping ribs for automotive oil pans. The method involves acquiring operating parameters of the automotive oil pan, including engine speed, oil temperature, and oil flow rate, as well as performance requirements including flow suppression effect, structural strength, and lightweighting. Based on these parameters and requirements, multiple flow-damping rib design schemes, including scheme characteristic parameters and performance evaluation data, are generated. Then, based on the matching relationship between the scheme characteristic parameters and performance evaluation data for each design scheme, an effective design scheme is determined from the multiple schemes. Finally, based on the effective design schemes, the optimal integrated design scheme for the automotive oil pan flow-damping ribs is determined. This method, by establishing a logical association between scheme characteristic parameters and performance evaluation data, can quickly eliminate invalid schemes that fail to meet flow suppression effects, structural strength, or lightweighting requirements, significantly shortening the scheme selection cycle and improving selection accuracy. It further selects the best among the selected effective design schemes, achieving a synergistic balance between flow suppression effect, structural strength, and lightweighting, and significantly improving the design quality and engineering applicability of the oil pan flow-damping ribs.

[0023] The integrated design method for the automotive oil pan flow suppressor provided in this application embodiment can be applied to the integrated design device for the automotive oil pan flow suppressor. In this case, the integrated design device for the automotive oil pan flow suppressor is the executing subject of the integrated design method for the automotive oil pan flow suppressor provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of the integrated design device for the automotive oil pan flow suppressor.

[0024] For example, the integrated design device for the flow control rib of an automotive oil pan can be a mobile phone, tablet, wearable device, augmented reality (AR) / virtual reality (VR) device, laptop, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), desktop computer, smart screen, smart TV and other terminal devices, handheld devices with wireless communication capabilities, computing devices or other processing devices connected to a wireless modem, Internet of Things terminals, computers, laptops, handheld communication devices, handheld computing devices, satellite wireless devices, wireless modem cards, customer premises equipment (CPE) and / or other devices used for communication over wireless systems, as well as next-generation communication systems, such as mobile terminals in 5G networks or mobile terminals in future evolved Public Land Mobile Networks (PLMNs).

[0025] To better understand the integrated design method for automotive oil pan flow control ribs provided in this application, the specific implementation process of the integrated design method for automotive oil pan flow control ribs provided in this application will be described below by way of example.

[0026] Figure 1 This illustration shows a schematic flowchart of the integrated design method for automotive oil pan flow damping ribs provided in an embodiment of this application. The integrated design method for automotive oil pan flow damping ribs includes: S100 obtains the operating parameters and performance requirements of the automotive oil pan; among which, the operating parameters include engine speed, oil temperature, and oil flow rate, and the performance requirements include flow suppression effect, structural strength, and lightweight indicators.

[0027] It's understandable that engine speed isn't a single fixed value, but rather covers the entire operating range of the engine, including idle speed (typically 600-800 rpm), normal driving speed (2000-4000 rpm), and high-load peak speed (such as 6000-7000 rpm for turbocharged engines). It's necessary to collect the percentage of continuous operation time at different speeds to form a speed distribution matrix, because the oil sloshing intensity varies significantly at different speeds: at high speeds, the oil centrifugal force is large, making it prone to surface tilting, thus requiring higher resistance from the flow suppressor. Oil temperature is further differentiated into cold start (ambient temperature to 80℃), normal operation (80-110℃), and high-load overheating (110-130℃). Oil viscosity changes significantly at different temperatures (e.g., oil viscosity at 40℃ may be 3-5 times that at 100℃). This viscosity difference directly affects oil flow resistance and sloshing characteristics. Therefore, collecting kinematic viscosity data for each temperature range can serve as the fluid property basis for the flow suppressor design. The oil flow rate is related to the engine oil pump displacement, oil circuit resistance, and the lubrication requirements of each lubrication point, including the minimum maintaining flow rate at idle speed (to ensure stable oil pump suction) and the maximum circulating flow rate at high speed (to prevent the oil from flowing rapidly in the oil pan and causing severe impact). At the same time, the flow pulsation frequency needs to be recorded, because pulsation will cause the oil to intermittently impact the flow suppressor, and the structural fatigue resistance needs to be considered in the design.

[0028] The flow suppression effect can be quantified into specific indicators, such as oil sloshing control (at the maximum tilt angle of 30° and the highest speed, the maximum sloshing height of the oil in the oil pan does not exceed 1 / 3 of the total height of the oil pan), oil surface stability (oil surface fluctuation amplitude ≤ 5mm), and anti-vacuum capability (the lowest oil level at the oil pump suction port is not less than twice the diameter of the suction port). These indicators can be determined through actual vehicle road tests or bench simulation tests to meet the reliability requirements of the engine lubrication system. Structural strength needs to consider oil impact load, engine vibration transmission, and installation and fixing requirements, specifically including the bending strength of the flow suppression ribs (bending deformation ≤ 0.5mm under the maximum oil impact load) and the shear strength of welded or connected parts (shear stress ≤ 80% of the allowable shear stress of the material). If the oil pan is made of aluminum alloy, the material fatigue characteristics also need to be considered to ensure that the flow suppression ribs have no risk of cracking during the entire life cycle of the engine (usually 200,000 kilometers or 10 years). Lightweighting targets need to balance structural strength and quality control. Typically, it is required that, while meeting the requirements of flow suppression effect and structural strength, the added mass of the flow suppression ribs should not exceed 5% of the mass of the oil pan base (e.g., if the mass of the oil pan base is 3 kg, the mass of the flow suppression ribs should be controlled within 0.15 kg). At the same time, material utilization rate should be considered to avoid mass redundancy caused by over-design.

[0029] Regarding data acquisition methods, operating parameters can be collected in real time through the vehicle engine management system (EMS). Combined with the vehicle driving condition database (such as typical operating conditions like urban congestion, highway cruising, and mountain road climbing), key operating points covering more than 95% of actual usage scenarios are selected. Performance requirements can be obtained from the engine database, which contains the performance requirements of the oil pan for all engines. This data can be obtained through laboratory experiments, on-site measurements and monitoring, and past experience. After acquisition, the collected data is organized, classified, and archived, useful information and patterns are extracted, and the relevant data is saved to the database to form the engine database.

[0030] Based on operating parameters and performance requirements, S200 generates multiple flow-damping rib design schemes; among them, the flow-damping rib design schemes include scheme characteristic parameters and performance evaluation data.

[0031] It is understandable that the characteristic parameters of the solution comprehensively cover the key dimensions affecting the flow suppression effect and structural performance. In addition to the basic flow suppression rib height (usually 5-30mm, which needs to be determined in combination with the internal space of the oil pan and the oil level), thickness (2-5mm, which needs to meet the balance between structural strength and lightweighting), and arrangement density (the spacing between adjacent flow suppression ribs is 50-150mm, which needs to be optimized according to the oil flow path), it also includes the cross-sectional shape of the flow suppression ribs (such as rectangular, trapezoidal, and triangular, with different shapes having significantly different effects on blocking and guiding oil flow - trapezoidal cross-sections can reduce oil impact noise, while triangular cross-sections are more advantageous in terms of lightweighting), arrangement position (such as the front, middle, and rear of the oil pan, which needs to be determined in combination with the engine vibration characteristics and the concentrated area of ​​oil sloshing. Usually, oil tends to accumulate in the front of the oil pan during rapid acceleration, so the flow suppression ribs need to be denser), and connection method (such as integral molding with the oil pan, welding, or bolt connection). The performance evaluation data corresponds one-to-one with the characteristic parameters of the solution, forming quantitative performance feedback. For example, for the flow suppression effect, data such as oil sloshing, oil surface fluctuation amplitude, and anti-air suction capability are obtained; for structural strength, data such as stress distribution, deformation, and fatigue life of the flow suppression ribs under oil impact and engine vibration are obtained; for lightweighting, data such as the mass of the flow suppression ribs, material utilization rate, and proportion of the overall mass of the oil pan are calculated.

[0032] For example, operating parameters and performance requirements can be input into the modeling model, which outputs multiple flow-damping rib design schemes. Then, simulation analysis is performed based on simulation and optimization algorithms to determine the characteristic parameters and performance evaluation data of each flow-damping rib design scheme.

[0033] Alternatively, a solution can be generated using a combination of parameterized variables and multi-objective constraint iteration: First, with operating parameters as the core constraint, establish a matrix of the value ranges of the solution's characteristic parameters. For example, combining the maximum oil sloshing height (e.g., 25mm) at the engine's highest speed (e.g., 6000r / min), limit the value range of the flow suppressor height to 18-28mm (leaving a 3-5mm safety margin to prevent the oil from exceeding the flow suppressor); based on the oil viscosity change corresponding to the oil temperature range (80-110℃) (e.g., the viscosity at 40℃ is 3 times that at 100℃), lock the selectable range of the flow suppressor cross-sectional shape to trapezoidal or arc shape (to reduce the resistance difference when oil of different viscosities flows); based on the oil flow rate (e.g., 5L / min at idle and 15L / min at high speed), set the adjustment range of the arrangement density to 60-120mm (densify when the flow rate is high to avoid oil impact overload, and widen when the flow rate is low to reduce flow resistance). Next, based on performance requirements, a multi-objective optimization function was set, with the objectives of "maximizing the flow suppression effect (oil sloshing ≤ 10mm), ensuring structural strength safety (maximum stress ≤ 90% of the material's allowable stress), and optimizing lightweighting (mass ≤ 0.18kg)". The objective function was constructed as follows: F(x) = α × (10 - Δh) / 10 + β × (σ max -σ) / σ max+γ×(m0-m) / m0, where Δh is the oil sloshing amount, σ is the actual stress, m is the actual mass, α, β, and γ are the weights of the flow suppression effect, structural strength, and lightweighting (e.g., α=0.4, β=0.35, γ=0.25), and x is the combination of characteristic parameters of the scheme (height, thickness, cross-sectional shape, etc.). The parameter combinations are iteratively optimized using a genetic algorithm, generating 20-30 sets of parameter combinations in each iteration. These combinations are then substituted into fluid simulation software (e.g., FLUENT) to calculate the flow suppression effect data, into structural simulation software (e.g., ANSYS) to calculate stress and deformation, and into a lightweighting calculation model (e.g., topology optimization module) to calculate mass and material utilization, forming initial performance evaluation data. Then, the initial schemes were screened for feasibility, eliminating combinations that clearly violated the constraints—for example, schemes with a 28mm high flow deflector but only 25mm of internal space in the oil pan (geometric interference), 2mm thick flow deflectors but stress calculations exceeding allowable stress (structural insecurity), and a weight of 0.2kg that could not be further reduced through topology optimization (lightweighting not up to standard). 30-50 schemes that met the basic constraints were retained. Finally, the retained schemes underwent a second optimization iteration, fine-tuning the bottleneck parameters in the performance evaluation data: for example, a scheme with 12mm oil sloshing (slightly exceeding the 10mm threshold) reduced sloshing to 9mm after resimulation by increasing the flow deflector density from 100mm to 80mm; a scheme with stress values ​​close to the allowable stress limit reduced stress to a safe range by increasing the root thickness of the flow deflector from 3mm to 3.5mm; and a scheme with a weight of 0.19kg (slightly exceeding 0.18kg) reduced weight to 0.17kg by changing the cross-sectional shape from rectangular to trapezoidal (reducing material usage by 10%). After 2-3 rounds of iteration, multiple schemes with complete characteristic parameters and qualified performance evaluation data were finally formed, etc., but not limited to these.

[0034] In one possible implementation, in step S200, multiple flow-damping rib design schemes are generated based on operating parameters and performance requirements, including: Based on a parametric modeling model, a parametric design of flow-damping ribs for an automotive oil pan is performed according to operating parameters and performance requirements, generating an initial design scheme library. Based on fluid simulation algorithms, structural strength simulation algorithms, and lightweight optimization algorithms, simulation analysis is conducted on each flow-damping rib design scheme in the initial design scheme library to determine the characteristic parameters and performance evaluation data corresponding to each scheme. The parametric modeling model, fluid simulation algorithm, structural strength simulation algorithm, and lightweight optimization algorithm are obtained through training and optimization based on training sample data. The process of generating the training sample data includes: Obtain design case data and corresponding measured performance data for oil pan flow control ribs in various vehicle models; The design case data for each vehicle model is divided into structural parameter data and working condition matching data. The structural parameter data of the Mth model is associated with the measured performance data of the (M-1)th model, and the working condition matching data of the Mth model is associated with the measured performance data of the Mth model to obtain training sample data, where M is a positive integer greater than 0.

[0035] It is understandable that the parametric design of flow-damping ribs for automotive oil pans based on operating parameters and performance requirements involves using these parameters and requirements as input constraints to construct a parametric template for the flow-damping rib design. First, the model determines the basic value range of the characteristic parameters of the design scheme based on the input operating parameters (such as engine speed 6000 r / min, oil temperature 80-110℃, and oil flow rate 5-15 L / min). For example, considering the characteristic of severe oil sloshing at high speeds, the lower limit of the flow-damping rib height is set to 20 mm (higher than 15 mm for low-speed models); based on the viscosity change corresponding to oil temperature, the selectable type of the flow-damping rib cross-section shape is limited to trapezoidal (to reduce the impact of viscosity fluctuations on oil flow); and referring to the oil flow range, the adjustment range of the arrangement density is set to 70-110 mm (to avoid impact overload during peak flow). At the same time, the model will incorporate performance requirement constraints, such as converting the lightweight index into a parameter limit of "the mass of the flow suppressor ≤ 5% of the mass of the oil pan base", and converting the structural strength requirement into a rigid standard of "the thickness of the flow suppressor ≥ 3mm (aluminum alloy material)".

[0036] When generating the initial design scheme library, the parametric modeling model adopts a "full parameter combination traversal + constraint pruning" strategy: for example, the height of the flow suppressor is set to three levels: 20mm, 23mm, and 26mm; the thickness is set to three levels: 3mm, 3.5mm, and 4mm; the cross-sectional shape is set to two types: trapezoidal and arc; and the arrangement density is set to three levels: 70mm, 90mm, and 110mm. Theoretically, 3×3×2×3=54 sets of parameter combinations can be generated. Then, through the constraint checking module built into the model, combinations with geometric interference (such as a height of 26mm exceeding the internal space of the oil pan by 25mm) and obviously substandard performance (such as a thickness of 3mm but the estimated structural strength is lower than the safety threshold) are eliminated. Finally, 30-40 sets of schemes are retained to form the initial design scheme library, which not only ensures the diversity of schemes, but also reduces the use of invalid schemes for subsequent simulation resources.

[0037] Multi-algorithm simulation analysis is a crucial step in verifying the performance of the scheme and supplementing performance evaluation data. Fluid simulation algorithms (such as FLUENT and STAR-CCM+) construct a three-dimensional fluid domain model of the oil pan and the flow suppressor, import the characteristic parameters of the initial scheme (such as a height of 23 mm and a layout density of 90 mm), and set boundary conditions consistent with actual operating conditions (such as the centrifugal force of the oil at an engine speed of 6000 r / min and the kinematic viscosity of the oil at an oil temperature of 100℃). Through computational fluid dynamics (CFD), the flow state of the oil under different operating conditions is simulated, and performance evaluation data related to the flow suppressor effect, such as oil sloshing (such as 8 mm), oil surface fluctuation amplitude (such as 4 mm), and anti-cavitation capability (such as "no risk of cavitation"), are output. Structural strength simulation algorithms (such as ANSYS and ABAQUS) convert the flow suppressor model into a finite element mesh, apply oil impact loads (such as an impact force of 15N at high speeds) and engine vibration loads (such as a vibration frequency of 200Hz), and calculate structural performance data such as stress distribution (such as a maximum stress of 140MPa at the root), deformation (such as 0.3mm), and fatigue life (such as 250,000 kilometers). Lightweight optimization algorithms (such as topology optimization and size optimization modules) will, based on the above simulation results, calculate lightweight indicators such as material utilization rate (such as 88%), flow suppressor mass (such as 0.16kg), and proportion of the overall oil pan mass (such as 4.5%), while satisfying the flow suppression effect and structural strength requirements, forming a complete performance evaluation data loop.

[0038] The generation and application of training sample data are crucial for improving the accuracy of model algorithms. During the data acquisition phase, it is necessary to cover vehicle models with different displacements (1.5L-3.0L), power types (naturally aspirated, turbocharged, hybrid), and usage scenarios (passenger cars, commercial vehicles, construction machinery) to ensure sample diversity. For example, this involves collecting design drawings of over 100 vehicle models for their anti-slip ribs (including structural parameters such as height, thickness, and cross-sectional shape), operating parameters (such as engine speed range and oil temperature range), and corresponding real-vehicle test data (such as measured oil sloshing and measured anti-slip rib fatigue life). When separating structural parameter data (such as anti-slip rib height 22mm and thickness 3.5mm) from operating condition matching data (such as suitable engine speeds of 2000-6000r / min and oil temperatures of 80-110℃), the correlation between the two types of data must be ensured. For example, the structural parameter data of a certain vehicle model must clearly correspond to its operating condition matching data to prevent mismatch between parameters and operating conditions.

[0039] The correlation mapping process adopts the logic of "cross-model reference + same-model verification": the structural parameter data of the Mth model is correlated with the measured performance data of the M-1th model. This is to optimize the structural design of the subsequent model by using the actual performance feedback of the previous model. For example, the measured performance of the M-1th model (a turbocharged sedan) shows that when the height of the flow suppressor is 20mm, the oil sloshing is 10mm (slightly exceeding the target value of 8mm). Therefore, the lower limit of the height in the structural parameter data of the Mth model (an upgraded version on the same platform) can be adjusted to 22mm. By referencing previous experience, the cost of trial and error is reduced. The operating condition matching data of the Mth model is correlated with its own measured performance data, so that the operating condition and performance are directly correlated. For example, the operating condition matching data of the Mth model is "speed 2000-6000r / min". Its corresponding measured performance data can directly verify the adaptability of the structural parameters under this operating condition.

[0040] This setup generates an initial design scheme library by combining parametric modeling with operating condition parameters and performance requirements. Then, fluid simulation, structural strength simulation, and lightweight optimization algorithms are used to simulate and analyze each scheme to determine its characteristic parameters and performance evaluation data. Both the model and algorithms are optimized based on specific training sample data. This training sample data is constructed through cross-vehicle model association mapping (the structural parameter data of the Mth vehicle model is associated with the measured performance data of the M-1th vehicle model, and its own operating condition matching data is associated with its own measured performance data). The technical effects are significant: on the one hand, the model and algorithms optimized based on the training sample data can accurately capture the inherent relationship between "operating condition-parameter-performance," reducing transmission... The blindness of traditional experience-based design allows the initial design scheme library to be adapted to the target operating conditions from the source. The performance evaluation data output by simulation analysis is also more in line with the actual use scenario, which greatly improves the accuracy of the adaptation of the scheme to the operating conditions and performance requirements and reduces the rectification rate in the later real vehicle testing. On the other hand, parametric modeling can quickly generate a variety of initial schemes, and multi-algorithm collaborative simulation can simultaneously verify the flow suppression effect, structural strength and lightweight performance, effectively solving the problem of single performance optimization but overall imbalance. At the same time, cross-model sample association mapping reduces the trial and error cost of new model design and significantly shortens the scheme generation cycle. Ultimately, it achieves synergistic optimization of the flow suppression rib design scheme in terms of accuracy, comprehensive performance, R&D efficiency and cost control.

[0041] S300 determines the effective design scheme from multiple flow-suppressing rib design schemes based on the matching relationship between the characteristic parameters of each design scheme and the performance evaluation data.

[0042] It is understandable that the matching of the characteristic parameters of the solution and the performance evaluation data is not a simple one-to-one correspondence, but a multi-dimensional and non-linear relationship. For example, increasing the height of the flow suppressor not only improves the flow suppression effect (reduces the amount of oil sloshing), but may also increase the mass (affecting the lightweight index), and may also change the oil flow path, leading to an increase in local structural stress (affecting structural strength). Increasing the density of the flow suppressor arrangement can enhance the flow suppression effect, but it will increase the oil flow resistance and may lead to an increase in oil temperature. It is necessary to make a comprehensive judgment in conjunction with the oil flow parameters.

[0043] In one possible implementation, in step S300, based on the matching relationship between the characteristic parameters of each flow-suppressing rib design scheme and the performance evaluation data, an effective design scheme is determined from multiple flow-suppressing rib design schemes, including: S310A determines the comprehensive performance score of each flow-suppressing rib design scheme based on the matching relationship between the characteristic parameters of each scheme and the performance evaluation data.

[0044] Understandably, the core of this step is to transform the multi-dimensional matching relationship between the scheme's characteristic parameters and performance evaluation data into a single, quantifiable comprehensive performance score, providing an intuitive and unified basis for subsequent screening and reducing screening confusion caused by too many parameters and performance dimensions.

[0045] By clarifying the correlation weights between "parameters and performance," performance scores are calculated across dimensions, and finally, a comprehensive score is obtained through weighted fusion. First, the weights can be determined by combining the priority of performance requirements with the significance of parameter impact—for example, for a certain vehicle model, the flow suppression effect is the core (weight 40%), followed by structural strength (35%), and lightweighting is the least important (25%). Among the characteristic parameters of the design, the height and density of the flow suppression ribs have the greatest impact on the flow suppression effect (totaling 70% of the weight of the flow suppression effect dimension), thickness has the most significant impact on structural strength (accounting for 50% of the weight of the structural strength dimension), and cross-sectional shape contributes the most to lightweighting (accounting for 40% of the weight of the lightweighting dimension). These influencing relationships can be transformed into specific weight values ​​using the Analytic Hierarchy Process (AHP) or expert scoring method. For example, the final weight of the height of the flow-suppressing rib in the comprehensive score is 40% (total weight of flow suppression effect) × 40% (weight of height in flow suppression effect) = 16%, the final weight of the arrangement density is 40% × 30% = 12%, and the final weight of the thickness is 35% × 50% = 17.5%, making the weight allocation objective and in line with actual needs.

[0046] In calculating the multidimensional performance score, the actual values ​​of the characteristic parameters of each solution can be linked with the performance evaluation data to be converted into a quantitative score of 0-100. Taking the flow suppression effect dimension as an example, if the height of the flow suppression rib of a certain scheme is 22mm (optimal design height 20mm, deviation value 10%), and the corresponding performance evaluation data is an oil sloshing amount of 8mm (flow suppression effect compliance threshold 10mm), then first determine the parameter contribution score based on the height deviation value: deviation value ≤5% gets 100 points, 5%-10% gets 90 points, 10%-15% gets 80 points, and the scheme with a height deviation of 10% gets 90 points; then combine the oil sloshing amount to determine the performance result score: sloshing amount ≤8mm gets 100 points, 8-10mm gets 90 points, >10mm gets 70 points, and the scheme with a sloshing amount of 8mm gets 100 points; finally, calculate the flow suppression effect dimension score according to "parameter contribution score × 30% + performance result score × 70%" = 90 × 30% + 100 × 70% = 97 points.

[0047] The calculation logic for structural strength is similar. If the thickness of the design is 3.5mm (the critical thickness corresponding to the allowable stress of the material is 3mm), and the performance evaluation data shows a maximum stress of 130MPa (allowable stress 150MPa), then the parameter contribution score (100 points for thickness compliance) × 40% + performance result score (100 points for stress ≤ 130MPa) × 60% = 100 × 40% + 100 × 60% = 100 points. In the lightweight dimension, if the cross-sectional shape of the design is trapezoidal (12% weight reduction compared to a rectangular cross-section), and the performance evaluation data shows a mass of 0.16kg (compliance threshold 0.18kg), then the parameter contribution score (90 points for trapezoidal cross-section) × 30% + performance result score (100 points for mass ≤ 0.16kg) × 70% = 90 × 30% + 100 × 70% = 97 points.

[0048] The final comprehensive performance score = (flow suppression effect score × 40%) + (structural strength score × 35%) + (lightweighting score × 25%) = 97 × 40% + 100 × 35% + 97 × 25% = 98.05 points. It should be noted that the entire calculation process must ensure the traceability of the correspondence between each parameter and performance data. For example, the correlation between height deviation and oil sloshing must be verified based on historical simulation and measured data to prevent subjective assignment from causing score distortion. At the same time, an outlier correction mechanism must be set up. If a solution's score in a single dimension is abnormal due to data error (e.g., a structural strength score of 30 points), the parameters and performance data must be re-verified, corrected, and then included in the scoring to ensure the accuracy and reliability of the comprehensive score.

[0049] S320A: When the overall performance score of a flow-suppressing rib design scheme is greater than a preset threshold, the flow-suppressing rib design scheme is determined as a valid design scheme; when the overall performance score of a flow-suppressing rib design scheme is less than or equal to the preset threshold, the flow-suppressing rib design scheme is determined as an invalid design scheme.

[0050] It's understandable that preset thresholds are pre-defined scoring values. They can be manually input, retrieved from a database, etc., but are not limited to these methods. The determination of preset thresholds combines performance baseline requirements, industry standards, and historical data statistics to form a quantitative indicator that is both "necessary" and "feasible." First, the minimum compliance requirements for each performance dimension can be broken down and converted into baseline thresholds for the comprehensive score—for example, the minimum score for flow suppression effect must be ≥70 points (corresponding to oil sloshing ≤12mm), the minimum score for structural strength must be ≥70 points (corresponding to maximum stress ≤150MPa), and the minimum score for lightweighting must be ≥70 points (corresponding to mass ≤0.22kg). If the weights for each dimension are 40%, 35%, and 25% respectively, then the minimum threshold for the comprehensive score = 70 × 40% + 70 × 35% + 70 × 25% = 70 points.

[0051] This setup first determines the comprehensive performance score based on the matching relationship between the characteristic parameters of each flow-damping rib design scheme and the performance evaluation data. Then, it uses a preset threshold as the criterion to screen valid design schemes. The multi-dimensional and complex matching relationship between the characteristic parameters of the scheme (such as the height, thickness, and density of the flow-damping ribs) and the performance evaluation data (such as the flow-damping effect, structural strength, and lightweight index) is transformed into a single quantitative comprehensive performance score. This makes the comparison of the merits of the schemes more intuitive and the judgment criteria more consistent. It can quickly eliminate invalid schemes that do not meet the comprehensive performance standards, reduce unnecessary subsequent analysis and verification costs, and significantly improve the efficiency of scheme screening.

[0052] In another possible implementation, in step S300, based on the matching relationship between the characteristic parameters of each flow-suppressing rib design scheme and the performance evaluation data, an effective design scheme is determined from multiple flow-suppressing rib design schemes, including: S310, based on the matching relationship between the characteristic parameters of each design scheme and the performance evaluation data corresponding to each flow-suppressing rib design scheme, determine the performance range corresponding to each flow-suppressing rib design scheme; wherein, the performance range includes at least the first range, the second range and the third range, the comprehensive score of the performance evaluation data in the first range is the highest, the comprehensive score in the second range is less than the comprehensive score in the first range, and greater than the comprehensive score in the third range.

[0053] It is understandable that this step differs from step S310A in obtaining the comprehensive performance score. This step involves matching the "scheme characteristic parameters" of each flow-damping rib design with the "performance evaluation data" to locate it within a multi-dimensional "performance range," thereby achieving a visual and structured description of the scheme performance. For example, key indicators of the scheme characteristic parameters of each flow-damping rib design can be extracted. Then, the correlation between these key indicators and the corresponding flow-damping effect contribution value, structural strength influence coefficient, and lightweighting achievement rate in the performance evaluation data can be calculated to obtain the performance correlation degree corresponding to each scheme characteristic parameter. Finally, the performance range corresponding to each flow-damping rib design scheme is determined based on the performance correlation degree. Alternatively, the priority of each performance dimension can be determined based on vehicle type requirements. For example, for commercial vehicles, the priority is set as follows: structural strength (weight 50%) > flow-damping effect (weight 30%) > lightweighting (weight 20%); for passenger vehicles, the priority is set as follows: lightweighting (weight 40%) > flow-damping effect (weight 35%) > structural strength (weight 25%). For each performance dimension, a "limit threshold" (an insurmountable bottom line) and a "target threshold" (ideal performance standard) are set. Taking structural strength as an example, when using aluminum alloy materials (allowable stress 150MPa), the limit threshold is set to maximum stress ≤ 150MPa (to ensure no failure), and the target threshold is set to maximum stress ≤ 120MPa (to ensure long-term reliability); the limit threshold for flow suppression effect is set to oil sloshing ≤ 12mm (to prevent air suction), and the target threshold is set to ≤ 8mm (for stable lubrication); the limit threshold for lightweighting is set to mass ≤ 0.2kg (for overall vehicle weight reduction requirements), and the target threshold is set to ≤ 0.15kg (for optimal lightweighting level). Finally, the performance evaluation data of each design scheme is checked against the relationship with the two thresholds, and its performance range is determined according to the judgment rules, etc., but not limited to this method.

[0054] In one possible implementation, in step S310, the performance range corresponding to each flow control rib design scheme is determined based on the matching relationship between the characteristic parameters of each scheme and the performance evaluation data, including: S311 Extract the key indicators of the characteristic parameters of each flow-suppressing rib design scheme. The key indicators include the flow-suppressing rib height deviation value, thickness uniformity, and arrangement density fluctuation coefficient.

[0055] It is understandable that the height deviation of the flow suppressor is a core indicator affecting the flow suppressing effect—the height directly determines the blocking height for oil sloshing. The optimal design height needs to be determined by combining the internal space of the oil pan (e.g., height 250mm) and the maximum oil sloshing height (e.g., 25mm), and is usually set to 22mm (with a 3mm safety margin). The height deviation value = |actual height - 22mm| / 22mm × 100%. For example, when the actual height is 20mm, the deviation value ≈ 9.1%. The larger the deviation, the worse the flow suppressing effect. Thickness uniformity is a key indicator affecting structural strength—uneven thickness of the flow suppressor can easily lead to stress concentration, especially the thickness difference between the root and the middle, which will significantly affect the impact resistance. The calculation method is to measure the thickness values ​​of the root (3.5mm), middle (3.2mm), and top (3.0mm) of the flow suppressor, and take the ratio of the minimum thickness to the maximum thickness, that is, uniformity = 3.0 / 3.5 × 100% ≈ 85.7%. The lower the uniformity, the higher the structural strength risk. The density fluctuation coefficient is a key indicator for balancing lightweighting and flow suppression. The density needs to be optimized according to the oil flow path (e.g., 80mm for the front, 100mm for the middle, and 120mm for the rear). The fluctuation coefficient = standard deviation of the spacing in each area / average spacing × 100%. For example, with 75mm for the front, 105mm for the middle, and 115mm for the rear, the average spacing is 98.3mm, the standard deviation is 17.2mm, and the fluctuation coefficient is ≈17.5%. Excessive fluctuation can easily lead to insufficient local flow suppression or mass redundancy.

[0056] S312, the key indicators are correlated with the corresponding contribution value of the flow suppression effect, the influence coefficient of structural strength, and the lightweighting achievement rate in the performance evaluation data to obtain the performance correlation degree corresponding to the characteristic parameters of each scheme.

[0057] It is understandable that the correlation between each key indicator and the performance evaluation data adopts a "one-to-one" correspondence logic: the deviation value of the flow suppression rib height corresponds to the contribution value of the flow suppression effect. The contribution value of the flow suppression effect is obtained through fluid simulation. For example, when the deviation value is 5%, the contribution value is 90% (oil sloshing amount of 8mm), and when the deviation value is 10%, the contribution value is 75% (oil sloshing amount of 12mm). The correlation degree is calculated by grey relational analysis, and the formula is ξ(i)=(minΔ+ρmaxΔ) / (Δi+ρmaxΔ) (ρ=0.5). For example, for a certain scheme, the height deviation value of 9.1% corresponds to Δi=0.15, minΔ=0.05, maxΔ=0.3, and the calculated ξ(i)≈0.67. The correlation degree is the average value of ξ(i) under each working condition, reflecting the degree of influence of the height deviation on the flow suppression effect. The structural strength influence coefficient corresponding to thickness uniformity is obtained through structural simulation. The coefficient is 0.85 (maximum stress 130 MPa) when uniformity is 85% and 0.65 (maximum stress 155 MPa) when uniformity is 75%. The correlation coefficient is calculated using the Pearson correlation coefficient. If the correlation coefficient r = 0.82 (P < 0.05) for 10 sets of data, it indicates a strong positive correlation between uniformity and strength coefficient, with a high correlation. The lightweighting achievement rate corresponding to density fluctuation coefficient is calculated as follows: Lightweighting achievement rate = (theoretical minimum mass - actual mass) / theoretical minimum mass × 100%. The achievement rate is 88% (mass 0.16 kg) when the fluctuation coefficient is 15% and 75% (mass 0.19 kg) when the fluctuation coefficient is 20%. The correlation is calculated using nonlinear regression, yielding the correlation function y = -0.02x + 1.18 (x is the fluctuation coefficient). For a certain scheme, the correlation coefficient y ≈ 0.83 when the fluctuation coefficient is 17.5%.

[0058] S313, determine the performance range corresponding to each flow-damping rib design scheme based on performance correlation.

[0059] It is understandable that determining the performance range based on performance correlation is key to transforming the quantified correlation into a hierarchical range. For example, a mapping matrix of performance correlation and operating condition adaptability can be constructed. Then, the performance correlation of each flow suppressor design scheme can be substituted into the mapping matrix to obtain the dynamic adaptability score of the flow suppressor design scheme under different operating condition combinations, and a probability distribution curve can be generated. The kurtosis and skewness values ​​of the probability distribution curve can be calculated, and the performance range corresponding to each flow suppressor design scheme can be obtained by comparing the kurtosis and skewness values ​​with a threshold group. Alternatively, the performance correlation of all scheme characteristic parameters can be weighted and summed one-to-one to obtain a comprehensive performance correlation score. Then, the comprehensive correlation score can be divided according to a preset grading standard, and finally, the performance range corresponding to each flow suppressor design scheme can be determined.

[0060] This approach focuses on key indicators that significantly impact flow suppression, structural strength, and lightweighting, avoiding redundancy and interference from full-parameter analysis. It makes performance correlation calculations more targeted—for example, height deviation directly correlates with flow suppression, and thickness uniformity precisely corresponds to structural strength. Through this "one-to-one" correlation logic, the accuracy of parameter-performance matching analysis is greatly improved, reducing correlation distortion caused by traditional multi-parameter aliasing. Furthermore, by quantifying the impact of key indicators on performance through performance correlation, and then dividing performance intervals based on correlation, this approach achieves a tiered characterization of scheme performance (e.g., high correlation corresponds to the excellent interval, medium correlation corresponds to the acceptable interval) and directly exposes scheme weaknesses (e.g., low correlation of thickness uniformity in a scheme indicates structural strength risk), providing a clear basis for subsequent effective scheme selection.

[0061] In one possible implementation, step S313 involves determining the performance range corresponding to each flow-damping rib design scheme based on performance correlation, including: S3131, construct a mapping matrix of performance correlation degree and operating condition adaptability degree; wherein, the operating condition adaptability degree is obtained by coupling calculation of engine speed fluctuation coefficient, oil temperature gradient change rate and oil flow pulsation frequency.

[0062] The core of this step is to establish a bridge connecting the "inherent performance of the solution" with "actual operating conditions," that is, to construct a mapping matrix of performance correlation and operating condition adaptability. The rows of this matrix represent the performance potential (performance correlation) determined during the design phase, the columns represent the various dynamic operating conditions the vehicle encounters in the real world (operating condition adaptability), and the values ​​in the matrix are the comprehensive performance score generated by combining the two. Crucially, operating condition adaptability is not simply the sum of parameters such as engine speed, oil temperature, and oil flow rate, but is calculated through coupling. It considers the mutual influence between these parameters: the engine speed fluctuation coefficient reflects the drasticness of speed changes, affecting oil agitation; the oil temperature gradient change rate reflects the speed of temperature changes, directly altering oil viscosity; and the oil flow pulsation frequency represents the stability of the oil pump output. By coupling these three factors with a weighted nonlinear function, such as squaring the rate of change of temperature gradient to amplify its nonlinear effect and taking the logarithm of the flow pulsation frequency to compress its numerical range, a comprehensive index that can fully reflect the degree of challenge to the oil pan under complex working conditions is finally obtained, so that the mapping matrix can realistically simulate the performance of the scheme under various working conditions.

[0063] S3132, substitute the performance correlation of each flow suppressor design scheme into the mapping matrix to obtain the dynamic adaptation score of the flow suppressor design scheme under different working conditions, and use the kernel density estimation method to generate the probability distribution curve of the dynamic adaptation score.

[0064] Understandably, by substituting the defined performance correlation (i.e., its performance potential) into the mapping matrix, the matrix automatically calculates and outputs the "dynamic adaptation score" for each operating condition (such as cold start, idling, high-speed cruising, rapid acceleration, and rapid deceleration). This score reflects the actual level of the solution's potential under specific operating conditions. Subsequently, to evaluate the overall performance and stability of the solution across all operating conditions, rather than focusing solely on the score of a single condition, this step employs kernel density estimation (KDE), a statistical method, to analyze all dynamic adaptation scores and generate a continuous probability distribution curve. The X-axis of this curve represents the score, and the Y-axis represents the probability density of obtaining that score. Its peak position, width, and overall offset direction visually reveal the most likely performance level, performance stability, and overall merits of the solution.

[0065] S3133 calculates the kurtosis and skewness values ​​of the probability distribution curve, and compares the kurtosis and skewness values ​​with the threshold group to obtain the performance range corresponding to each flow control rib design scheme.

[0066] It is understandable that by deeply analyzing the "shape characteristics" of the dynamic adaptation score probability distribution curve, precise stratification of solution performance can be achieved. First, the kurtosis and skewness of the curve are calculated: Kurtosis measures the concentration and stability of the score distribution—moderate kurtosis (close to normal distribution kurtosis) means that the solution's scores are concentrated under most operating conditions, indicating stable performance; excessively high kurtosis may hide performance risks under extreme operating conditions, while excessively low kurtosis indicates excessive performance fluctuations. Skewness is used to judge the overall tendency of the score distribution—negative skewness (the curve's "tail" drags to the left) represents high scores under most operating conditions, with only a few conditions showing slightly lower scores, representing an ideal performance distribution; positive skewness (the curve's "tail" drags to the right) means that scores are low under most operating conditions, with only a few conditions showing excellent performance, indicating performance weaknesses. Subsequently, the calculated kurtosis and skewness values ​​are compared with preset threshold groups (determined based on historical excellent scheme data, such as the ideal kurtosis range [2.5, 3.5] and the ideal skewness range [-1, 0]): if the skewness is negative and the kurtosis is in the ideal range, it indicates that the scheme has excellent and stable performance and is classified into the first range; if the skewness is close to 0 or the kurtosis deviates slightly from the ideal range, it indicates that the scheme has acceptable performance but with small fluctuations and is classified into the second range; if the skewness is positive or the kurtosis is far above / far below the ideal range, it indicates that the scheme has unstable performance or poor overall performance and is classified into the third range.

[0067] This setup, by constructing a performance correlation-operating condition fit mapping matrix, generating a dynamic fit score probability distribution curve, and determining the performance range by combining kurtosis and skewness with threshold groups, overcomes the limitations of traditional static performance evaluation. It obtains operating condition fit by coupling the calculation of engine speed fluctuation coefficient, oil temperature gradient change rate, and oil flow pulsation frequency, and then constructs a mapping matrix. This allows the performance evaluation to closely match the complex dynamic operating conditions of real vehicle operation (such as cold start acceleration and high-speed cruising speed fluctuations), reducing the problem of "testing performance in the laboratory but failing in actual operating conditions," and significantly improving the authenticity and relevance of the performance evaluation. On the other hand… The algorithm generates probability distribution curves through kernel density estimation, and combines kurtosis (reflecting performance stability) and skewness (reflecting overall performance tendency) to quantitatively analyze the full-condition performance of the proposed solution. Kurtosis can identify performance fluctuation risks, and skewness can judge the performance quality under most conditions. By comparing with threshold groups and stratifying, the algorithm can not only judge whether the solution is "qualified", but also accurately distinguish different levels such as "excellent and stable performance", "qualified but fluctuating", and "unqualified and high risk". This provides a more refined basis for selecting effective solutions, while reducing decision-making bias caused by misjudgment due to scores of a single condition. Ultimately, it helps to select a flow-suppressing rib design solution that is suitable for all conditions and has stable and reliable performance.

[0068] S320 determines the flow-suppressing rib design scheme with a performance range of the first or second range as a valid design scheme, and determines the flow-suppressing rib design scheme with a performance range of the third range as an invalid design scheme.

[0069] It is understandable that the first range of representative solutions exhibits excellent and stable performance under all operating conditions (e.g., high dynamic adaptation scores in most operating conditions and kurtosis and skewness meeting ideal thresholds), meeting the usage requirements of high-end models or demanding operating conditions (e.g., heavy-duty commercial vehicles and range requirements of new energy vehicles). Although the second range of representative solutions is not optimal, its core performance (flow suppression effect, structural strength, and lightweighting) meets basic design standards, with only slight fluctuations under extreme operating conditions. It is suitable for models with moderate performance requirements (e.g., daily commuting in economy passenger cars). Together, they constitute the effective solution range.

[0070] This setup, by first dividing the performance range into three intervals (ranked from high to low based on the matching relationship between the scheme's characteristic parameters and performance evaluation data), and then designating the schemes in the first two intervals as valid and the schemes in the third interval as invalid, highlights the technical effect of balancing performance reliability and design flexibility: On the one hand, by dividing the range into multiple intervals, the first interval is used to lock in the high-performance scheme with the "highest comprehensive score," meeting the extreme requirements of high-end models and harsh operating conditions (such as heavy-duty commercial vehicles and long-range new energy vehicles) for flow suppression effect, structural strength, and lightweighting. On the other hand, the second interval retains practical schemes that "meet the score but are not optimal," adapting to scenarios with moderate performance requirements, such as economy passenger cars and daily commuting, avoiding performance overkill and cost waste caused by only pursuing the first interval. On the other hand, the schemes in the third interval (lowest score) are clearly determined to be invalid, completely eliminating risky schemes with substandard core performance (such as poor flow suppression effect that easily leads to oil cavitation, and insufficient structural strength that easily leads to cracking), ensuring the reliability of the oil pan's basic functions. Meanwhile, this "high-medium-low" tiered screening logic can form an effective pool of solutions covering different vehicle requirements and cost gradients. This not only provides diverse candidates for subsequent optimal solution selection, but also reduces the design limitations caused by single-range screening, helping to balance performance, cost and mass production feasibility.

[0071] Based on effective design schemes, the optimal integrated design scheme for the flow-damping ribs of the automotive oil pan was determined for the S400.

[0072] For example, the optimal integrated design scheme for the automotive oil pan flow suppressor can be determined in different ways based on the distribution of the performance range of the effective design schemes. For instance, when the effective design schemes correspond to the second range, the performance weight of each effective design scheme is determined based on the performance evaluation data. Then, the product of the performance score of each effective design scheme and the corresponding performance weight is used to determine the weighted comprehensive score for each effective design scheme. Finally, the optimal integrated design scheme for the automotive oil pan flow suppressor is determined based on the maximum value of each weighted comprehensive score. When all effective design schemes correspond to the first range, the average score is calculated, and the optimal integrated design scheme for the automotive oil pan flow suppressor is determined based on the final score. Alternatively, the optimal scheme selection method can be based on multi-objective optimization and the primary objective (such as cost-effectiveness ratio, user scenario matching, etc.), etc., but is not limited to these methods.

[0073] Taking cost-effectiveness as an example, the core indicators are selected as follows: flow suppression effect (oil sloshing), structural strength (maximum stress), lightweighting (mass), and manufacturing cost (yuan / piece). The indicator data of each effective design scheme are normalized to the [0,1] interval. Among them, flow suppression effect, structural strength, and lightweighting are "positive indicators" (the smaller the value, the better the performance), and the normalization formula is x'=(x max -x) / (x max -x minManufacturing cost is a "negative indicator" (the smaller the value, the better), and the normalization formula is x'=(x max -x) / (x max -x min Ensure all indicators are aligned. For example, in a certain scheme, the oil sloshing amount is 8mm (x_min = 7mm, x...). max =12mm), after normalization x'=(12-8) / (12-7)=0.8; manufacturing cost 80 yuan (x min =70 yuan, x max =120 yuan), after normalization, x'=(120-80) / (120-70)=0.8. Then define the cost-benefit ratio = (normalized value of flow suppression effect × 0.3 + normalized value of structural strength × 0.3 + normalized value of lightweighting × 0.2) / (normalized value of manufacturing cost × 0.2), and adjust the weight according to the vehicle model requirements (for example, the cost weight can be increased to 0.3 for economy passenger cars). For example, the normalized sum of performance of a certain first interval scheme is 0.85, the normalized value of cost is 0.7, and the cost-benefit ratio = 0.85 / 0.7≈1.21; the normalized sum of performance of a certain second interval scheme is 0.7, the normalized value of cost is 0.4, and the cost-benefit ratio = 0.7 / 0.4=1.75, the latter has a higher cost-effectiveness. For the top three cost-effectiveness options, their compliance with mass production constraints is verified, including mold development cycle (≤3 months), material procurement difficulty (common aluminum alloys are easy to procure), and assembly compatibility (matching with engine oil pan mounting holes ≥98%). If an option has the highest cost-effectiveness but requires custom-made molds (cycle 6 months), that option is eliminated, and the second-best option that meets the constraints is selected. Considering both cost-effectiveness and engineering constraints, the option with the highest cost-effectiveness and that meets all constraints is selected as the optimal option. For example, in the economy passenger vehicle project, although the performance of the second-tier options is slightly lower than that of the first-tier options, their cost-effectiveness is higher and they are compatible with existing molds, thus ultimately being determined as the optimal option.

[0074] In one possible implementation, in step S400, based on effective design schemes, the optimal integrated design scheme for the automotive oil pan flow control ribs is determined, including: S410a, when all effective design schemes correspond to the second interval, the performance weight of each effective design scheme is determined based on the performance evaluation data; wherein, the performance weight is determined according to the priority of the flow suppression effect, structural strength, and lightweight index.

[0075] It's understandable that when all effective design solutions fall within the second tier (performance meets standards but isn't optimal, and each has its own emphasis), performance weights are set to differentiate considerations across different performance dimensions. Performance weights must be strictly prioritized based on the core needs of the vehicle model: for example, economy passenger cars prioritize basic performance under cost control, so a weight of 0.4 for flow suppression (ensuring stable oil supply), 0.3 for structural strength (meeting daily commuting needs), and 0.3 for lightweighting (while also considering fuel consumption) can be set. For urban SUVs prioritizing off-road capability, the weights can be increased to 0.4 for structural strength, 0.35 for flow suppression, and 0.25 for lightweighting. Weight determination can combine market research (user tolerance for malfunctions) and engineering standards (such as the risk level of oil pump cavitation), quantified using expert scoring or the Analytic Hierarchy Process (AHP) to ensure the weight allocation is highly aligned with the vehicle's positioning.

[0076] S420b determines the weighted comprehensive score for each valid design scheme by multiplying the performance score of each valid design scheme by the corresponding performance weight.

[0077] It is understandable that the performance scores of each effective design scheme are weighted and calculated with their corresponding weights to obtain a weighted comprehensive score, thereby achieving a quantitative ranking of the overall performance of the schemes. For example, in a certain second interval, scheme A has a flow suppression effect score of 85 points, a structural strength score of 80 points, and a lightweighting score of 82 points. Calculated using the weights for economy passenger vehicles (0.4, 0.3, 0.3), the weighted comprehensive score = 85 × 0.4 + 80 × 0.3 + 82 × 0.3 = 82.6 points; scheme B has a flow suppression effect score of 82 points, a structural strength score of 83 points, and a lightweighting score of 80 points, and the weighted comprehensive score = 82 × 0.4 + 83 × 0.3 + 80 × 0.3 = 81.7 points. During the calculation process, it is necessary to ensure the correspondence between the performance scores and weights. For example, the flow suppression effect score must correspond to the flow suppression effect weight, and two decimal places should be retained to ensure ranking accuracy.

[0078] Based on the maximum value of each weighted comprehensive score, the optimal integrated design scheme for the flow suppression ribs of the automotive oil pan is determined for S430c.

[0079] It is understandable that by comparing the weighted comprehensive scores of each effective design scheme, the scheme with the highest score is determined as the optimal integrated design scheme, ensuring that the selection results directly reflect the priority of vehicle performance requirements. For example, if scheme A has a weighted comprehensive score of 82.6, scheme B 81.7, and scheme C 83.2, then scheme C is the optimal scheme. If multiple schemes have the same weighted comprehensive score (e.g., all 82.5), secondary evaluation indicators (such as manufacturing cost and assembly complexity) can be introduced for secondary ranking, selecting the scheme with better secondary indicators.

[0080] This setup, when all valid design schemes correspond to the second interval, determines performance weights based on the priority of flow suppression effect, structural strength, and lightweight indicators. Then, it calculates a weighted comprehensive score of each scheme's performance score and weights, ultimately determining the optimal scheme based on the maximum weighted comprehensive score. This reduces blind selection when schemes in the second interval have similar performance, and reflects the differentiated needs of different vehicle models through weights (e.g., economy cars prioritize cost and basic performance, while SUVs prioritize structural strength), ensuring the optimal scheme accurately matches actual usage priorities. Simultaneously, the weighted calculation quantifies the differences in overall scheme performance, ensuring the selection results are objective and controllable. While guaranteeing core performance standards are met, it achieves efficient and accurate selection of the best scheme within the second interval.

[0081] In another possible implementation, in step S400, based on effective design schemes, the optimal integrated design scheme for the automotive oil pan flow control ribs is determined, including: S410A, when the effective design schemes include effective design schemes corresponding to the first interval and effective design schemes corresponding to the second interval, for the effective design schemes corresponding to the second interval, the product of the performance score of each effective design scheme and the performance weight of the effective design scheme is determined as the weighted comprehensive score corresponding to each effective design scheme; wherein, the performance weight of the effective design scheme is determined based on the performance evaluation data and the priority of the operating parameters.

[0082] It's understandable that calculating the weighted comprehensive score using "performance score × performance weight" hinges on the fact that performance weights must be determined using a two-dimensional approach: "performance evaluation data + operating condition parameter priority." Performance evaluation data determines the basic importance of each indicator (e.g., substandard flow suppression can lead to oil cavitation, so the basic weight is no less than 0.3). Operating condition parameter priority is dynamically adjusted based on the vehicle's high-frequency operating conditions (e.g., for taxis operating at high frequencies of idling / low speed, the structural strength weight can be increased to 0.35; for long-haul trucks operating at high frequencies of high speed, the lightweighting weight can be increased to 0.3). For example, if a second-tier solution has a performance score of 83 for flow suppression, 85 for structural strength, and 80 for lightweighting, and the weights for taxi operating conditions are 0.35 for flow suppression, 0.35 for structural strength, and 0.3 for lightweighting, the weighted comprehensive score would be 83 × 0.35 + 85 × 0.35 + 80 × 0.3 = 82.7. This approach reflects both the inherent performance differences and aligns with the actual usage scenario's emphasis on parameters, preventing the second-tier solution from being underestimated or overestimated due to a single evaluation dimension.

[0083] Based on the weighted comprehensive score of the effective design schemes in the corresponding second interval and the average comprehensive score of the effective design schemes in the corresponding first interval, the optimal integrated design scheme for the automotive oil pan flow suppression ribs is determined.

[0084] It is understandable that by comparing the weighted comprehensive score of the second interval scheme with the average comprehensive score of the first interval scheme, horizontal comparability and selection of the best between the two types of interval schemes can be achieved. First, the average comprehensive score of all schemes in the first interval is calculated (since the performance of the schemes in the first interval is excellent and the differences are small, the average can represent the overall performance level of the interval). For example, if the comprehensive scores of the three schemes in the first interval are 92, 90 and 91 respectively, the average comprehensive score = (92+90+91) / 3 = 91. Then, the weighted comprehensive score of the second interval scheme (e.g., the highest 85) is compared with this average: if the average comprehensive score of the first interval is higher than the highest weighted comprehensive score of the second interval (91>85), then the best is further selected from the schemes in the first interval (e.g., the scheme with the highest score of 92). If there is a scheme in the second interval whose weighted comprehensive score is close to or exceeds the average comprehensive score of the first interval (e.g., 89), then a second evaluation is required in combination with cost factors. If the cost of the second interval scheme is only 80% of that of the first interval scheme and meets the core requirements of the vehicle model, it can be included in the final comparison with the first interval scheme to determine the optimal integrated design scheme of the automotive oil pan flow control rib.

[0085] This setup, when an effective design scheme includes both the first and second zones, determines the weight of the second zone schemes by combining performance evaluation data and priority of operating parameters, and calculates a weighted comprehensive score. The first zone schemes are then compared and selected based on their average comprehensive score. This weighting ensures that the evaluation of the second zone schemes aligns with operating conditions, preventing them from being overlooked due to indistinguishable performance. Furthermore, the average comprehensive score of the first zone establishes a baseline for high-performance schemes, enabling a scientific horizontal comparison between the two zones. Ultimately, this prioritizes high-performance first-zone schemes while also considering cost-effective second-zone schemes suitable for specific operating conditions. This approach ensures performance reliability while enhancing the flexibility and economy of scheme selection, adapting to the differentiated performance and cost requirements of different vehicle models.

[0086] In one possible implementation, in step S300, when the performance requirements include flow suppression effect and structural strength, the scheme characteristic parameters include the height, thickness, and arrangement density of the flow suppression ribs, and the performance evaluation data includes first evaluation data corresponding to the flow suppression effect and second evaluation data corresponding to the structural strength. Based on the matching relationship between the scheme characteristic parameters and performance evaluation data corresponding to each flow suppression rib design scheme, an effective design scheme is determined from multiple flow suppression rib design schemes, including: Based on the height, thickness, and arrangement density of the flow-suppressing ribs corresponding to each design scheme, and the first evaluation data, candidate schemes that meet the flow-suppressing effect are determined from multiple design schemes. Based on the height, thickness, and arrangement density of the flow-suppressing ribs corresponding to each candidate scheme, and the second evaluation data, effective design schemes that meet the structural strength requirements are determined from multiple candidate schemes.

[0087] It is understandable that, in order to meet the dual performance requirements of flow suppression effect and structural strength, a "progressive screening" approach is adopted to determine the effective design scheme, ensuring that the scheme simultaneously meets the two core performance indicators. First, the height, thickness, and arrangement density of the flow-suppressing ribs are used as inputs. A first round of screening is conducted using primary evaluation data corresponding to the flow-suppressing effect (such as oil sloshing suppression rate and turbulence intensity reduction value). A threshold for achieving the flow-suppressing effect is set (e.g., oil sloshing suppression rate ≥ 85%), eliminating schemes with insufficient height (e.g., less than 20mm resulting in a small blocking range) or unreasonable arrangement density (e.g., excessive spacing leading to flow-suppressing blind zones), resulting in candidate schemes. Then, for the candidate schemes, a second round of screening is conducted based on the secondary evaluation data corresponding to the flow-suppressing rib height, thickness, and arrangement density and structural strength (e.g., bending stiffness and torsional stiffness values). A threshold for achieving the structural strength is set (e.g., bending stiffness ≥ 500N / mm), eliminating schemes with insufficient thickness (e.g., less than 3mm resulting in insufficient stiffness) or unbalanced height and density (e.g., excessive height and density leading to stress concentration), resulting in structural strength deficiencies. Finally, the effective design scheme is determined.

[0088] In step S400, based on effective design schemes, the optimal integrated design scheme for the automotive oil pan flow suppression ribs is determined, including: The comprehensive score is obtained by weighted summing of the flow suppression effect score and the structural strength score of the effective design scheme.

[0089] It's understandable that "the comprehensive score is obtained by weighted summation of the flow suppression effect score and the structural strength score" is based on the difference in importance between the two performance indicators to achieve quantitative optimization. The weights need to be set according to the vehicle model's priority requirements for the two performance indicators. For example, heavy-duty trucks, due to their large oil volume and harsh operating conditions, have a structural strength weight of 0.55 and a flow suppression effect weight of 0.45; passenger cars, which prioritize flow suppression effect to ensure lubrication stability, have a flow suppression effect weight of 0.55 and a structural strength weight of 0.45. For instance, if an effective solution has a flow suppression effect score of 90 and a structural strength score of 85, the comprehensive score calculated using the passenger car weights would be 90 × 0.55 + 85 × 0.45 = 87.75; another solution would have a flow suppression effect score of 88 and a structural strength score of 88, resulting in a comprehensive score of 88 × 0.55 + 88 × 0.45 = 88.

[0090] The effective design scheme with the highest comprehensive score was determined as the optimal integrated design scheme for the automotive oil pan flow control rib.

[0091] This setup, through a combination of "progressive screening + weighted summation and selection," yields significant technical results: the progressive screening first uses the height, thickness, and density of the flow-suppressing ribs, combined with the first evaluation data, to screen candidate solutions that meet the flow-suppressing effect standards; then, based on the second evaluation data, it screens effective solutions that meet the structural strength standards, ensuring that effective solutions simultaneously meet the core flow-suppressing function of the oil pan and structural reliability, avoiding performance shortcomings caused by single-index screening; during the weighted summation, the weights of the two indicators are set according to the priority of vehicle model requirements, quantifying the differences in the comprehensive performance of the solutions, which not only adapts to the different performance focuses of different vehicle models such as heavy trucks and passenger cars, but also accurately selects the solution with the best overall performance, achieving a balance between the scientific nature and engineering practicality of the solution selection while ensuring that the core performance standards are met.

[0092] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0093] Corresponding to the integrated design method of the automotive oil pan flow suppressor ribs described in the above embodiments, this application also provides an integrated design system for the automotive oil pan flow suppressor ribs. Each module of this device can realize each step of the integrated design method for the automotive oil pan flow suppressor ribs. Figure 2 The diagram shows a structural block diagram of the integrated design system for the automotive oil pan flow control ribs provided in the embodiments of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0094] Reference Figure 2 The integrated design system for the flow-damping ribs in the automotive oil pan includes: The acquisition module is used to acquire the operating parameters and performance requirements of the automotive oil pan; the operating parameters include engine speed, oil temperature, and oil flow rate, and the performance requirements include flow suppression effect, structural strength, and lightweight indicators.

[0095] The generation module is used to generate multiple flow-damping rib design schemes based on operating parameters and performance requirements; among them, the flow-damping rib design schemes include scheme characteristic parameters and performance evaluation data.

[0096] The first determination module is used to determine the effective design scheme from multiple flow suppression rib design schemes based on the matching relationship between the characteristic parameters of each flow suppression rib design scheme and the performance evaluation data.

[0097] The second determining module is used to determine the optimal integrated design scheme for the flow-suppressing ribs of the automotive oil pan based on effective design schemes.

[0098] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0099] Those skilled in the art will understand that, for the sake of convenience and brevity, the above-described module division is merely an example. In practical applications, the above functions can be assigned to different modules as needed, that is, the internal structure of the system can be divided into different modules to complete all or part of the functions described above. The modules in the embodiments can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0100] This application also provides an integrated design device for a flow-damping rib on an automotive oil pan. Figure 3 This is a schematic diagram of the structure of an integrated design device 6 for an automotive oil pan flow control rib, provided in one embodiment of this application. Figure 3 As shown, the automotive oil pan anti-flow rib integrated design device 6 of this embodiment includes: at least one processor 60 ( Figure 3 Only one is shown in the image), at least one memory 61 ( Figure 3 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the automotive oil pan anti-flow rib integrated design device 6 to implement the steps in any of the above-described automotive oil pan anti-flow rib integrated design method embodiments, or causes the automotive oil pan anti-flow rib integrated design device 6 to implement the functions of each module in the above-described system embodiments.

[0101] For example, the computer program 62 can be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 62 in the automotive oil pan anti-flow rib integrated design device 6.

[0102] The integrated design device 6 for the automotive oil pan flow damper can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. This integrated design device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 3 This is merely an example of the integrated design device 6 for the automotive oil pan flow damper, and does not constitute a limitation on the integrated design device 6 for the automotive oil pan flow damper. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0103] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0104] In some embodiments, the memory 61 can be an internal storage unit of the automotive oil pan deflector integrated design device 6, such as a hard drive or memory of the automotive oil pan deflector integrated design device 6. In other embodiments, the memory 61 can be an external storage device of the automotive oil pan deflector integrated design device 6, such as a plug-in hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the automotive oil pan deflector integrated design device 6. Further, the memory 61 can include both internal storage units and external storage devices of the automotive oil pan deflector integrated design device 6. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of the computer program. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0105] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0106] This application provides a computer program product that, when run on an integrated design device for automotive oil pan flow damping ribs, enables the integrated design device for automotive oil pan flow damping ribs to implement the steps in any of the above-described method embodiments.

[0107] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to the integrated design device for the automotive oil pan slick, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, such as a USB flash drive, a portable hard drive, a magnetic disk, or an optical disk.

[0108] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0109] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0110] In the embodiments provided in this application, it should be understood that the disclosed integrated design device and system for automotive oil pan flow damping ribs can be implemented in other ways. For example, the embodiments of the automotive oil pan flow damping rib integrated design system described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0111] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0112] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for integrating flow-damping ribs into an automotive oil pan, characterized in that, include: Obtain the operating parameters and performance requirements of the automotive oil pan; wherein, the operating parameters include engine speed, oil temperature, and oil flow rate, and the performance requirements include flow suppression effect, structural strength, and lightweight indicators; Based on the operating parameters and performance requirements, multiple flow-damping rib design schemes are generated; wherein, each flow-damping rib design scheme includes scheme characteristic parameters and performance evaluation data; Based on the matching relationship between the characteristic parameters of each flow-suppressing rib design scheme and the performance evaluation data, an effective design scheme is determined from multiple flow-suppressing rib design schemes; Based on the aforementioned effective design scheme, the optimal integrated design scheme for the flow-damping ribs of the automotive oil pan was determined.

2. The integrated design method for the flow-damping ribs of an automotive oil pan as described in claim 1, characterized in that, The step of determining an effective design scheme from multiple flow-suppressing rib design schemes based on the matching relationship between the characteristic parameters of each design scheme and the performance evaluation data includes: Based on the matching relationship between the characteristic parameters of each of the flow-suppressing rib design schemes and the performance evaluation data, the performance range corresponding to each flow-suppressing rib design scheme is determined; wherein, the performance range includes at least a first range, a second range and a third range, and the performance evaluation data has the highest comprehensive score in the first range, the comprehensive score in the second range is lower than the comprehensive score in the first range, and higher than the comprehensive score in the third range; The flow-suppressing rib design scheme with the performance range being the first range or the second range is determined as a valid design scheme, and the flow-suppressing rib design scheme with the performance range being the third range is determined as an invalid design scheme.

3. The integrated design method for the flow-damping ribs of an automotive oil pan as described in claim 2, characterized in that, The step of determining the performance range corresponding to each flow-suppressing rib design scheme based on the matching relationship between the characteristic parameters of each scheme and the performance evaluation data includes: The key indicators of the characteristic parameters of each flow-suppressing rib design scheme are extracted, including the flow-suppressing rib height deviation value, thickness uniformity, and arrangement density fluctuation coefficient. The key indicators are correlated with the corresponding contribution value of the flow suppression effect, the structural strength influence coefficient, and the lightweight achievement rate in the performance evaluation data to obtain the performance correlation degree corresponding to each characteristic parameter of the scheme. The performance range corresponding to each of the flow-suppressing rib design schemes is determined based on the performance correlation.

4. The integrated design method for the flow-damping ribs of an automotive oil pan as described in claim 3, characterized in that, The process of determining the performance range corresponding to each of the flow-suppressing rib design schemes based on the performance correlation includes: Construct a mapping matrix of performance correlation degree and operating condition adaptability degree; wherein, the operating condition adaptability degree is obtained by coupling calculation of engine speed fluctuation coefficient, oil temperature gradient change rate and oil flow pulsation frequency; Substitute the performance correlation of each of the flow-suppressing rib design schemes into the mapping matrix to obtain the dynamic adaptation score of the flow-suppressing rib design schemes under different working conditions, and use the kernel density estimation method to generate the probability distribution curve of the dynamic adaptation score. The kurtosis and skewness values ​​of the probability distribution curve are calculated, and the performance range corresponding to each of the flow-suppressing rib design schemes is obtained by comparing the kurtosis and skewness values ​​with a threshold group.

5. The integrated design method for the flow-damping ribs of an automotive oil pan as described in claim 2, characterized in that, The determination of the optimal integrated design scheme for the automotive oil pan flow suppression ribs based on the effective design scheme includes: When all the effective design schemes correspond to the second interval, the performance weight of each effective design scheme is determined based on the performance evaluation data; wherein, the performance weight is determined according to the priority of flow suppression effect, structural strength, and lightweight index; The weighted comprehensive score for each effective design scheme is determined by multiplying the performance score of each effective design scheme by the corresponding performance weight. Based on the maximum value of each weighted comprehensive score, the optimal integrated design scheme of the automotive oil pan flow suppression rib is determined.

6. The integrated design method for the flow-damping ribs of an automotive oil pan as described in claim 2, characterized in that, The determination of the optimal integrated design scheme for the automotive oil pan flow suppression ribs based on the effective design scheme includes: When the effective design schemes include the effective design schemes corresponding to the first interval and the effective design schemes corresponding to the second interval, for the effective design schemes corresponding to the second interval, the product of the performance score of each effective design scheme and the performance weight of the effective design scheme is determined as the weighted comprehensive score corresponding to each effective design scheme; wherein, the performance weight of the effective design scheme is determined based on the performance evaluation data and the priority of the operating parameters; Based on the weighted comprehensive score of the effective design schemes corresponding to the second interval and the average comprehensive score of the effective design schemes corresponding to the first interval, the optimal integrated design scheme of the automotive oil pan flow suppression rib is determined.

7. The integrated design method for the flow-damping ribs of an automotive oil pan as described in claim 1, characterized in that, The step of determining an effective design scheme from multiple flow-suppressing rib design schemes based on the matching relationship between the characteristic parameters of each design scheme and the performance evaluation data includes: Based on the matching relationship between the characteristic parameters of each of the flow-suppressing rib design schemes and the performance evaluation data, the comprehensive performance score of the flow-suppressing rib design scheme is determined; When the overall performance score of a flow-suppressing rib design scheme is greater than a preset threshold, the flow-suppressing rib design scheme is determined as a valid design scheme; when the overall performance score of a flow-suppressing rib design scheme is less than or equal to the preset threshold, the flow-suppressing rib design scheme is determined as an invalid design scheme.

8. The integrated design method for the flow-damping ribs of an automotive oil pan as described in claim 1, characterized in that, Based on the operating parameters and performance requirements, multiple flow-damping rib design schemes are generated, including: Based on the parametric modeling model, a parametric design of flow-damping ribs for the automotive oil pan is performed according to the operating parameters and performance requirements, generating an initial design scheme library. Based on fluid simulation algorithms, structural strength simulation algorithms, and lightweight optimization algorithms, simulation analysis is conducted on each flow-damping rib design scheme in the initial design scheme library to determine the characteristic parameters and performance evaluation data corresponding to each design scheme. The parametric modeling model, fluid simulation algorithm, structural strength simulation algorithm, and lightweight optimization algorithm are obtained through training and optimization based on training sample data. The process of generating the training sample data includes: Obtain design case data and corresponding measured performance data for oil pan flow control ribs in various vehicle models; The design case data for each vehicle model is divided into structural parameter data and working condition matching data; The structural parameter data of the Mth model is associated with the measured performance data of the (M-1)th model, and the working condition matching data of the Mth model is associated with the measured performance data of the Mth model to obtain training sample data, where M is a positive integer greater than 0.

9. The integrated design method for the flow-damping ribs of an automotive oil pan as described in any one of claims 1-7, characterized in that, When the performance requirements include the flow suppression effect and the structural strength, the scheme characteristic parameters include the height, thickness, and arrangement density of the flow suppression ribs. The performance evaluation data includes first evaluation data corresponding to the flow suppression effect and second evaluation data corresponding to the structural strength. The step of determining an effective design scheme from multiple flow suppression rib design schemes based on the matching relationship between the scheme characteristic parameters and the performance evaluation data for each flow suppression rib design scheme includes: Based on the height, thickness, and arrangement density of the flow-suppressing ribs corresponding to each of the flow-suppressing rib design schemes and the first evaluation data, candidate schemes that meet the flow-suppressing effect are determined from multiple flow-suppressing rib design schemes. Based on the height, thickness, and arrangement density of the flow-suppressing ribs corresponding to each of the candidate schemes and the second evaluation data, effective design schemes that meet the structural strength standard are determined from multiple candidate schemes. The determination of the optimal integrated design scheme for the automotive oil pan flow suppression ribs based on the effective design scheme includes: The effective design scheme's flow suppression effect score and structural strength score are weighted and summed to obtain a comprehensive score; The effective design scheme with the highest comprehensive score is determined as the optimal integrated design scheme for the automotive oil pan flow control rib.

10. An integrated design device for flow-damping ribs in an automotive oil pan, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as claimed in any one of claims 1 to 9.

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