Electric drive bridge oil duct flow distribution optimization method and system based on simulation technology

Abstract

The invention discloses an electric drive bridge oil duct flow distribution optimization method and system based on a simulation technology, and belongs to the technical field of electric drive bridge lubricating oil duct design. The method comprises the steps that a mathematical model of an electric drive bridge lubricating oil duct and the target flow of each oil injection opening are obtained; performing gridding processing on the mathematical model, constructing a CFD simulation model, and calculating the simulation flow of each oil injection port; establishing a one-dimensional pipeline analysis model, and comparing a calculation result with a fluid dynamics simulation result to confirm the effectiveness of the one-dimensional model; setting a variable range by taking the pipe diameter of the oil injection port as an optimization variable, and performing multi-round optimization on the one-dimensional model by adopting a genetic algorithm to obtain optimization parameters meeting design requirements; reconstructing an oil duct model according to an optimization result, and performing designability verification through simulation; according to the method, lubricating oil flow distribution can be efficiently evaluated and optimized in the design stage, the optimization precision is improved, the development period is shortened, and the test cost is reduced.

Description

Technical Field

[0001] The present invention relates to a method and system for optimizing oil channel flow distribution in an electric drive axle based on simulation technology, and belongs to the technical field of electric drive axle lubricating oil channel design. Background Art

[0002] As a core component in the powertrain of new energy vehicles, the lubrication system of the electric drive axle has a significant impact on the vehicle's performance and reliability. Due to the highly integrated structure of the electric drive axle and its complex lubrication requirements, multiple oil injectors are typically used to lubricate and cool different parts. In actual design, significant flow coupling exists between the various oil injectors, making it difficult to accurately predict and control the flow distribution of the lubrication oil channels. If the flow rates of the various oil injectors are not properly matched, insufficient or excessive lubrication may occur in some parts, leading to problems such as abnormal temperature rise, mechanical wear, and increased energy consumption.

[0003] Existing technologies often rely on experimental or empirical methods to evaluate and optimize lubrication channels. This approach suffers from long evaluation cycles, high costs, low design efficiency, and difficulty achieving precise control. This approach struggles to meet the rapid iteration and high-performance design demands of modern electric drive axle products. Therefore, a technology is urgently needed that can efficiently and accurately evaluate and assist in optimizing oil channel flow distribution during the design phase, thereby improving design quality, shortening development cycles, and reducing reliance on testing. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art. In the existing electric drive axle lubricating oil channel design stage, traditional testing methods have the problems of long cycle, high cost and low precision.

[0005] In order to solve the above technical problems, the present invention is implemented by adopting the following technical solutions: In a first aspect, a method for optimizing oil channel flow distribution in an electric drive axle based on simulation technology is provided, comprising the following steps: Obtaining the mathematical model of the electric drive axle lubrication oil channel and the first theoretical flow rate of each oil injection port; Meshing the mathematical model of the electric drive axle lubricating oil channel and constructing a CFD simulation model; calculating a second theoretical flow rate of each oil injection port based on the CFD simulation model, and comparing the calculated second theoretical flow rate with the first theoretical flow rate; The lubrication oil channel is segmented according to its structural characteristics, and a one-dimensional pipeline analysis model is established. The flow rate of each oil injection port in the one-dimensional pipeline analysis model is compared with the flow rate of each oil injection port in the CFD simulation model. If the error is within the preset threshold, the one-dimensional model is confirmed to be valid. The diameter of each fuel injection port is used as the optimization variable, the variable range is set, and the effective one-dimensional model is optimized through multiple rounds using a genetic algorithm to obtain the optimized diameter of each fuel injection port. Based on the optimization results, the mathematical model of the electric drive axle lubrication oil channel was reconstructed, and the flow rate of each injection port was verified and released based on the CFD simulation model.

[0006] Furthermore, the first theoretical flow rate is a target flow rate value calculated by the lubrication and heat dissipation requirements of the electric drive axle lubrication oil channel itself.

[0007] Furthermore, the gridding of the mathematical model of the electric drive axle lubricating oil channel and the construction of a CFD simulation model include: selecting a k-epsilon turbulence model as a fluid dynamics simulation model.

[0008] Furthermore, the calculating of the second theoretical flow rate of each fuel injection port according to the CFD simulation model includes: performing calculation using grid independence verification; The grid independence verification includes: reducing the mesh size of the mathematical model of the electric drive axle lubrication oil channel, and calculating the calculation results of each fuel injection port under different mesh sizes respectively. When the impact of the reduction in mesh size on the calculation result of the fuel injection port flow rate does not exceed a preset error threshold, it is determined that the current mesh division result meets the simulation accuracy requirements.

[0009] Furthermore, segmenting the lubricating oil channel according to its structural characteristics includes: The lubricating oil channel of the electric drive axle is segmented according to the straight pipe, curved pipe and adjustable part of the oil injection port; The preset threshold is set to 5%.

[0010] Furthermore, the optimization parameters of the genetic algorithm include: population size, maximum number of iterations, reproduction ratio, mutation probability, mutation amplitude and number of random seeds.

[0011] Furthermore, the use of a genetic algorithm to perform multiple rounds of optimization on an effective one-dimensional model includes: using a one-dimensional analysis method to use the results of one round of optimization as the initial value of a second round of optimization, comparing with the first theoretical flow, and optimizing by narrowing the variable range until the optimization result meets the design requirements.

[0012] Furthermore, in the design verification, when the flow rate of a certain fuel injection port does not meet the design requirements, the fuel injection port and the oil channel connected thereto are further optimized.

[0013] In a second aspect, a simulation-based oil channel flow distribution system for an electric drive axle is provided, comprising: A modeling module, used to obtain a mathematical model of the electric drive axle lubrication oil channel and a first theoretical flow rate of each oil injection port; a simulation module, configured to perform gridding processing on the mathematical model and construct a CFD simulation model, calculate a second theoretical flow rate of each fuel injection port based on the simulation model, and compare the second theoretical flow rate with the first theoretical flow rate; A one-dimensional modeling module is used to segment the lubrication oil channel according to its structural characteristics, construct a one-dimensional pipeline analysis model, and compare the flow rate of each oil injection port in the one-dimensional analysis model with the fluid dynamics simulation results to determine the validity of the one-dimensional model; The optimization module is used to use the diameter of the fuel injection port as the optimization variable, set the variable range, and use the genetic algorithm to perform multiple rounds of optimization on the fuel injection port, while confirming the validity of the one-dimensional model, and output the optimized diameter value; The verification module is used to rebuild the mathematical model of the electric drive axle lubrication oil channel based on the optimization results, and to perform design verification through the CFD simulation model to determine whether the flow rate of each oil injection port meets the design requirements and implement release.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention ensures the stability and reliability of the simulation results by constructing a CFD simulation model and introducing grid independence verification, and can accurately predict the actual flow of each fuel injection port in the design stage, avoiding reliance on physical prototypes for flow evaluation, and significantly improving evaluation efficiency and accuracy; at the same time, a one-dimensional pipeline analysis model is introduced and compared with the three-dimensional simulation results for verification. Under the premise of ensuring calculation accuracy, the computing resource consumption in the optimization process is reduced, so that the multi-nozzle flow evaluation of the oil channel can be completed in a shorter time, effectively improving design efficiency; finally, a genetic algorithm is used to perform multiple rounds of optimization with the fuel injection port diameter as a variable, so that the optimization process has adaptability and global optimization capabilities, and can quickly converge to the design parameters that meet the flow target of each fuel injection port. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The figure shows a flow chart of the electric drive axle oil channel flow distribution optimization method based on simulation technology provided by the present invention; Figure 2 The figure shows the original digital model of the lubricating oil channel of the electric drive axle provided in the first embodiment of the present invention; Figure 3 The figure shows the comparison between the CFD analysis results of the original scheme of the electric drive axle lubrication oil channel provided by the first embodiment of the present invention and the required flow rate and the expected flow rate; Figure 4 The figure shows a comparison between the CFD analysis results and the one-dimensional simulation results of the flow rate of each injection port of the original solution of the electric drive axle lubrication oil channel provided by the first embodiment of the present invention; Figure 5 Shown are the four-wheel optimization results of the one-dimensional model of the electric drive axle lubricating oil channel provided by the first embodiment of the present invention, as well as a comparison diagram of the required flow rate and the expected flow rate; Figure 6 Shown is a comparison chart of the calculation results and test data of the electric drive axle lubrication oil channel simulation optimization solution provided in Example 1 of the present invention, as well as the required flow rate and expected flow rate. DETAILED DESCRIPTION

[0016] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. Unless there is a conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0017] The term "and / or" in this document simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone. Additionally, the character " / " in this document generally indicates an "or" relationship between the related objects. Example 1:

[0018] like Figure 1 As shown, this embodiment provides an electric drive axle oil passage flow distribution optimization method based on simulation technology. In order to verify the feasibility and effectiveness of the electric drive axle oil passage flow distribution optimization method based on simulation technology of the present invention, as shown in FIG. Figure 2 The figure shows the initial digital model of the lubricating oil channel. The flow rate of each oil nozzle should be greater than the required flow rate to achieve the desired flow rate. This example uses the flow distribution evaluation and optimization of 16 oil nozzles in the lubricating oil channel of an electric drive axle as an example, including the following specific steps: First, the original mathematical model of the electric drive axle's lubrication oil channel and the initial theoretical flow rate (i.e., target required flow rate) for each oil injection port were obtained from the design department. After extracting and discretizing the model's internal surface, a CFD simulation model was constructed. The k-epsilon turbulence model was used for calculations. The inlet boundary conditions were set to flow inlet, and the outlet to pressure outlet.

[0019] To ensure simulation accuracy, the meshing scheme was verified for mesh independence. Specifically, the mesh size was gradually reduced and simulations of the injector flow rate were compared at various mesh densities. Ultimately, the simulation results at the current medium mesh density exhibited an error of less than 2%, meeting the accuracy requirements. This meshing scheme was then adopted as the standard for subsequent simulations.

[0020] like Figure 3 As shown in the figure, the simulation results show that there is a large deviation between the actual ejection flow of multiple fuel injection ports and the first theoretical flow, some are lower and some are significantly higher. The original structure has a serious flow unevenness problem and needs to be optimized.

[0021] The oil channel is segmented into straight pipe, curved pipe and injection port characteristic sections, a one-dimensional pipeline simulation model is built, and the flow rate of each injection port is calculated under the same working conditions. Figure 4 As shown in the figure, the comparison results show that except for the relative errors of 3 fuel injectors exceeding 5%, the errors of the remaining fuel injectors are well controlled. The overall average flow error of the 16 fuel injectors is –3.37%, which meets the prerequisite for using a one-dimensional model instead of CFD simulation.

[0022] The diameters of the 16 fuel injectors were selected as optimization variables, initially within a range of 1–10 mm. The optimization goal was to achieve a flow rate close to the theoretical flow rate for all injectors. A genetic algorithm was used for global optimization. After the first round of optimization, some injectors (such as injectors 1, 2, 8, 9, 14, and 15) exhibited high flow rates, so their ranges were narrowed to 1–5 mm. Injectors 3 and 4, which were sensitive to flow and exhibited large errors, were further restricted to 1–2 mm. The remaining injectors remained unchanged for the second round of optimization.

[0023] like Figure 5 As shown in the figure, after four rounds of optimization iterations, the flow rates of all fuel injection ports are finally greater than the required flow rates, and most of them are close to the expected values.

[0024] The optimized injector diameter parameters were used for digital-analog reconstruction and re-run with CFD simulation. A comparison revealed that the flow rates of injectors 3, 4, 13, and 15 deviated from design requirements, while the other injectors met the requirements. Three rounds of local fine-tuning and simulation iterations were conducted to address the deviations. Ultimately, the flow rates of all injectors met the design requirements, allowing for release.

[0025] like Figure 6 As shown in the figure, physical prototypes were fabricated based on the final optimized parameters and injection flow rate tests were conducted. The experimental data were highly consistent with the simulation results. The flow rates of all injection ports were higher than the first theoretical flow rate, and the error between the actual flow rate and the simulation value for most injection ports was less than 5%. Example 2:

[0026] This embodiment provides an electric drive axle oil channel flow distribution system based on simulation technology, including: A modeling module, used to obtain a mathematical model of the electric drive axle lubrication oil channel and a first theoretical flow rate of each oil injection port; a simulation module, configured to perform gridding processing on the mathematical model and construct a CFD simulation model, calculate a second theoretical flow rate of each fuel injection port based on the simulation model, and compare the second theoretical flow rate with the first theoretical flow rate; A one-dimensional modeling module is used to segment the lubrication oil channel according to its structural characteristics, construct a one-dimensional pipeline analysis model, and compare the flow rate of each oil injection port in the one-dimensional analysis model with the fluid dynamics simulation results to determine the validity of the one-dimensional model; The optimization module is used to use the diameter of the fuel injection port as the optimization variable, set the variable range, and use the genetic algorithm to perform multiple rounds of optimization on the fuel injection port, while confirming the validity of the one-dimensional model, and output the optimized diameter value; The verification module is used to reconstruct the mathematical model of the electric drive axle lubrication oil channel according to the optimization results, and perform design verification through the CFD simulation model to determine whether the flow rate of each oil injection port meets the design requirements and realize release.

[0027] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for optimizing oil channel flow distribution in an electric drive axle based on simulation technology, characterized by: The following steps are involved: Obtaining the mathematical model of the electric drive axle lubrication oil channel and the first theoretical flow rate of each oil injection port; Gridding the mathematical model of the electric drive axle lubricating oil channel and performing CFD simulation on the model; calculating a second theoretical flow rate of each oil injection port based on the CFD simulation model, and comparing the calculated second theoretical flow rate with the first theoretical flow rate; The lubrication oil channel is segmented according to its structural characteristics, and a one-dimensional pipeline analysis model is established. The flow rate of each oil injection port in the one-dimensional pipeline analysis model is compared with the flow rate of each oil injection port in the CFD simulation model. If the error is within the preset threshold, the one-dimensional model is confirmed to be valid. The diameter of each fuel injection port is used as the optimization variable, the variable range is set, and the effective one-dimensional model is optimized through multiple rounds using a genetic algorithm to obtain the optimized diameter of each fuel injection port. Based on the optimization results, the mathematical model of the electric drive axle lubrication oil channel was reconstructed, and the flow rate of each injection port was verified and released based on the CFD simulation model.

2. The electric drive axle oil channel flow distribution optimization method based on simulation technology according to claim 1 is characterized in that: The first theoretical flow rate is a target flow rate value calculated based on the lubrication and heat dissipation requirements of the electric drive axle lubricating oil channel itself.

3. The electric drive axle oil channel flow distribution optimization method based on simulation technology according to claim 1 is characterized in that: The gridding of the mathematical model of the electric drive axle lubricating oil channel and the construction of a CFD simulation model include: selecting a k-epsilon turbulence model as a fluid dynamics simulation model.

4. The electric drive axle oil channel flow distribution optimization method based on simulation technology according to claim 1 is characterized in that: Calculating the second theoretical flow rate of each fuel injection port according to the CFD simulation model includes: performing calculations using grid independence verification; The grid independence verification includes: reducing the mesh size of the mathematical model of the electric drive axle lubrication oil channel, and calculating the calculation results of each fuel injection port under different mesh sizes respectively. When the impact of the reduction in mesh size on the calculation result of the fuel injection port flow rate does not exceed a preset error threshold, it is determined that the current mesh division result meets the simulation accuracy requirements.

5. The electric drive axle oil channel flow distribution optimization method based on simulation technology according to claim 1 is characterized in that: The segmenting of the lubricating oil channel according to the structural characteristics of the lubricating oil channel includes: The lubricating oil channel of the electric drive axle is segmented according to the straight pipe, curved pipe and adjustable part of the oil injection port; The preset threshold is set to 5%.

6. The method for optimizing oil channel flow distribution of an electric drive axle based on simulation technology according to claim 1 is characterized in that: The optimization parameters of the genetic algorithm include: population size, maximum number of iterations, reproduction ratio, mutation probability, mutation amplitude and number of random seeds.

7. The method for optimizing oil channel flow distribution of an electric drive axle based on simulation technology according to claim 1 is characterized in that: The multi-round optimization of the effective one-dimensional model using the genetic algorithm includes: using the one-dimensional analysis method to take the results of one round of optimization as the initial value of the second round of optimization, comparing with the first theoretical flow, optimizing by narrowing the variable range until the optimization result meets the design requirements.

8. The method for optimizing oil channel flow distribution of an electric drive axle based on simulation technology according to claim 1 is characterized in that: During the design verification, when the flow rate of a certain fuel injection port does not meet the design requirements, the fuel injection port and the oil channel connected thereto are further optimized.

9. An electric drive axle oil channel flow distribution system based on simulation technology, characterized in that: include: A modeling module, used to obtain a mathematical model of the electric drive axle lubrication oil channel and a first theoretical flow rate of each oil injection port; a simulation module, configured to perform gridding processing on the mathematical model and construct a CFD simulation model, calculate a second theoretical flow rate of each fuel injection port based on the simulation model, and compare the second theoretical flow rate with the first theoretical flow rate; A one-dimensional modeling module is used to segment the lubrication oil channel according to its structural characteristics, construct a one-dimensional pipeline analysis model, and compare the flow rate of each oil injection port in the one-dimensional analysis model with the fluid dynamics simulation results to determine the validity of the one-dimensional model; The optimization module is used to use the diameter of the fuel injection port as the optimization variable, set the variable range, and use the genetic algorithm to perform multiple rounds of optimization on the fuel injection port, while confirming the validity of the one-dimensional model, and output the optimized diameter value; The verification module is used to reconstruct the mathematical model of the electric drive axle lubrication oil channel according to the optimization results, and perform design verification through the CFD simulation model to determine whether the flow rate of each oil injection port meets the design requirements and realize release.

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