Method and device for simulating drag torque of speed reducer of automobile electric drive system

Abstract

The invention provides an automobile electric drive system reducer drag torque simulation method and device, and the method comprises the steps: obtaining a reducer geometric model, a reducer surface grid model, and a reducer gear shaft gear assembly model after receiving a system input torque; simulation calculation based on a semi-implicit particle method is conducted according to the speed reducer geometric model, and the oil stirring torque is obtained; simulation calculation based on a finite element method is conducted according to the speed reducer surface mesh model, and the wind resistance moment is obtained; performing simulation calculation based on a finite element method according to the shaft gear assembly model to obtain a system friction torque; speed reducer input rotating speed and output shaft rotational inertia are obtained; and calculating the drag torque of the assembly according to all the obtained data. The method and the device can accurately quantify the drag torque through simulation, are favorable for improving the system efficiency and shortening the development period, and provide a scientific basis for designing a more efficient and more energy-saving electric drive system.

Description

Technical Field

[0001] The present application relates to the technical field of automobile electric drive systems, and more specifically, to a method and device for simulating the drag torque of a reducer of an automobile electric drive system. Background Art

[0002] As the global energy crisis and environmental pollution become increasingly serious, new energy vehicles and electric equipment are gradually becoming the development trend of future transportation and industrial fields with their clean, efficient and energy-saving characteristics. However, the efficiency of electric drive systems has always been one of the key factors restricting their performance improvement and widespread application. Among them, the drag loss of electric drive reducers is an important factor affecting the energy efficiency of the system, and its accurate evaluation is of great significance for optimizing the design and improving the overall energy efficiency. Traditionally, the evaluation method for the drag loss of electric drive reducers mainly relies on empirical formulas or simplified theoretical models to estimate the drag loss, which leads to inaccurate evaluation and affects the energy efficiency performance of the overall system. Summary of the invention

[0003] The purpose of the embodiments of the present application is to provide a method and device for simulating the drag torque of a reducer in an automobile electric drive system, which can accurately quantify the drag torque through simulation, which is beneficial to improving system efficiency, shortening the development cycle, and providing a scientific basis for designing a more efficient and energy-saving electric drive system.

[0004] The first aspect of the present application provides a method for simulating the drag torque of a reducer of an automobile electric drive system, comprising:

[0005] After receiving the system input torque, a reducer geometric model, a reducer surface mesh model, and a shaft-tooth assembly model of the reducer gear are obtained;

[0006] According to the reducer geometric model, simulation calculation based on semi-implicit particle method is performed to obtain the oil stirring torque;

[0007] Performing simulation calculation based on the finite element method according to the reducer surface mesh model to obtain the wind resistance torque;

[0008] Performing simulation calculation based on the finite element method according to the shaft-gear assembly model to obtain the system friction torque;

[0009] Get the reducer input speed and output shaft moment of inertia;

[0010] The assembly drag torque is calculated according to the reducer input speed, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

[0011] Furthermore, the simulation calculation based on the semi-implicit particle method is performed according to the reducer geometric model to obtain the oil stirring torque, including:

[0012] Performing model pre-processing on the reducer geometric model to obtain a parts grouping model;

[0013] Importing the part grouping model into a solver, and adding the solver to a solid domain;

[0014] Creating a fluid domain, and configuring oil parameters for the fluid domain to obtain a configured fluid domain;

[0015] Performing shaft-tooth rotational motion setting on the solid domain to obtain a set solid domain;

[0016] configuring solver parameters for the solver to obtain a configured solver;

[0017] According to the configured fluid domain, the set solid domain and the configured solver, a semi-implicit particle algorithm is used to establish an oil stirring torque calculation model;

[0018] Perform simulation calculation according to the oil stirring torque calculation model to obtain a first simulation calculation result;

[0019] The oil stirring torque is obtained according to the first simulation calculation result.

[0020] Furthermore, the simulation calculation based on the finite element method is performed according to the reducer surface mesh model to obtain the wind resistance torque, including:

[0021] Defining a gear rotation envelope surface in the reducer surface mesh model to obtain a first calculation model;

[0022] According to the gear rotation envelope surface, a calculation domain of the space inside the gear box is set for the first calculation model to obtain a second calculation model;

[0023] Performing grid division on the second calculation model to obtain a third calculation model;

[0024] Performing local encryption processing near the tooth surface on the third calculation model to obtain a fourth calculation model;

[0025] Adding a physical model to the calculation domain in the fourth calculation model to obtain a fifth calculation model;

[0026] Setting a calculation boundary for the fourth calculation model according to a finite element algorithm to obtain a wind resistance moment calculation model;

[0027] Perform simulation calculation according to the wind resistance moment calculation model to obtain a second simulation calculation result;

[0028] According to the second simulation calculation result, the wind resistance torque is obtained.

[0029] Furthermore, the simulation calculation based on the finite element method is performed according to the shaft-gear assembly model to obtain the system friction torque, including:

[0030] Performing material parameter configuration on the shaft-gear assembly model to obtain a first configuration model;

[0031] Grouping the contact surfaces of large and small gears of the first configuration model to obtain a grouping result;

[0032] Performing local mesh encryption processing on the first configuration model according to the grouping result to obtain a second configuration model;

[0033] Performing link parameter configuration on the second configuration model to obtain a third configuration model;

[0034] Calculate and set the third configuration model according to a finite element algorithm to obtain a system friction torque calculation model;

[0035] Perform simulation calculation according to the system friction torque calculation model to obtain a third simulation calculation result;

[0036] According to the third simulation calculation result, the system friction torque is obtained.

[0037] Further, the calculation of the assembly drag torque according to the reducer input speed, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque includes:

[0038] Get the gear ratio of the reducer;

[0039] Calculating the output speed of the reducer according to the input speed of the reducer and the gear ratio of the reducer;

[0040] Calculating the rate of change of the output speed of the reducer with respect to time according to the output speed of the reducer;

[0041] The assembly drag torque is calculated based on the rate of change of the reducer output speed with respect to time, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

[0042] Furthermore, the calculation formula of the assembly drag torque is:

[0043]

[0044] Among them, T in is the drag torque of the assembly, T visc is the oil stirring torque, T wind is the wind resistance moment, T f is the friction torque of the system, J out is the output shaft moment of inertia, is the rate of change of the output speed of the reducer with respect to time;

[0045] Among them, T out is the output torque of the reducer, T out =0.

[0046] A second aspect of the present application provides a drag torque simulation device for a reducer of an automobile electric drive system, the drag torque simulation device for a reducer of an automobile electric drive system comprising:

[0047] A first acquisition unit is used to acquire a reducer geometric model, a reducer surface mesh model, and a shaft-tooth assembly model of the reducer gear after receiving a system input torque;

[0048] A first simulation unit is used to perform simulation calculation based on a semi-implicit particle method according to the reducer geometric model to obtain an oil stirring torque;

[0049] A second simulation unit is used to perform simulation calculation based on the finite element method according to the reducer surface mesh model to obtain a wind resistance torque;

[0050] A third simulation unit is used to perform simulation calculation based on the finite element method according to the shaft-gear assembly model to obtain a system friction torque;

[0051] The second acquisition unit is used to acquire the input speed of the reducer and the moment of inertia of the output shaft;

[0052] The calculation unit is used to calculate the assembly drag torque according to the reducer input speed, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

[0053] Furthermore, the first simulation unit includes:

[0054] A pre-processing sub-unit, used for performing model pre-processing on the reducer geometric model to obtain a parts grouping model;

[0055] Importing subunits, for importing the part grouping model into a solver, and adding the solver to a solid domain;

[0056] A first configuration subunit is used to create a fluid domain and configure oil parameters for the fluid domain to obtain a configured fluid domain;

[0057] The first configuration subunit is further used to perform shaft-tooth rotational motion setting on the solid domain to obtain a set solid domain;

[0058] A first setting subunit is used to configure solver parameters for the solver to obtain a configured solver;

[0059] Establishing a subunit for establishing an oil stirring torque calculation model by using a semi-implicit particle algorithm according to the configured fluid domain, the set solid domain and the configured solver;

[0060] A first simulation subunit, used for performing simulation calculation according to the oil stirring torque calculation model to obtain a first simulation calculation result;

[0061] The first acquisition subunit is used to acquire the oil stirring torque according to the first simulation calculation result.

[0062] Furthermore, the second simulation unit includes:

[0063] A subunit is defined, which is used to define a gear rotation envelope surface in the reducer surface mesh model to obtain a first calculation model;

[0064] A second setting subunit is used to set the calculation domain of the space inside the gear box for the first calculation model according to the gear rotation envelope surface to obtain a second calculation model;

[0065] A division subunit, used for performing grid division on the second calculation model to obtain a third calculation model;

[0066] A first encryption subunit, configured to perform local encryption processing near the tooth surface on the third calculation model to obtain a fourth calculation model;

[0067] An adding subunit, used for adding a physical model to the calculation domain in the fourth calculation model to obtain a fifth calculation model;

[0068] A third setting subunit is used to set a calculation boundary for the fourth calculation model according to a finite element algorithm to obtain a wind resistance moment calculation model;

[0069] A second simulation subunit is used to perform simulation calculation according to the wind resistance moment calculation model to obtain a second simulation calculation result;

[0070] The second acquisition subunit is used to acquire the wind resistance torque according to the second simulation calculation result.

[0071] Furthermore, the third simulation unit includes:

[0072] A second configuration subunit is used to configure material parameters of the shaft-gear assembly model to obtain a first configuration model;

[0073] A grouping subunit, used for grouping the contact surfaces of the large and small gears of the first configuration model to obtain a grouping result;

[0074] A second encryption subunit, configured to perform grid local encryption processing on the first configuration model according to the grouping result to obtain a second configuration model;

[0075] A third configuration subunit is used to configure link parameters of the second configuration model to obtain a third configuration model;

[0076] A calculation setting subunit, used for performing calculation setting on the third configuration model according to a finite element algorithm to obtain a system friction torque calculation model;

[0077] A third simulation subunit is used to perform simulation calculation according to the system friction torque calculation model to obtain a third simulation calculation result;

[0078] The third acquisition subunit is used to acquire the system friction torque according to the third simulation calculation result.

[0079] Furthermore, the calculation unit comprises:

[0080] The fourth acquisition subunit is used to obtain the speed ratio of the reducer gear;

[0081] A calculation subunit, used for calculating the output speed of the reducer according to the input speed of the reducer and the gear ratio of the reducer;

[0082] The calculation subunit is further used to calculate the rate of change of the output speed of the reducer with respect to time according to the output speed of the reducer;

[0083] The calculation subunit is further used to calculate the assembly drag torque based on the rate of change of the reducer output speed with respect to time, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

[0084] Furthermore, the calculation formula of the assembly drag torque is:

[0085]

[0086] Among them, T in is the drag torque of the assembly, T visc is the oil stirring torque, T wind is the wind resistance moment, T f is the friction torque of the system, J out is the output shaft moment of inertia, is the rate of change of the output speed of the reducer with respect to time;

[0087] Among them, T out is the output torque of the reducer, T out =0.

[0088] The third aspect of the present application provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the automotive electric drive system reducer drag torque simulation method described in any one of the first aspect of the present application.

[0089] A fourth aspect of the present application provides a computer-readable storage medium storing computer program instructions. When the computer program instructions are read and executed by a processor, the method for simulating the drag torque of a reducer of an automobile electric drive system described in any one of the first aspect of the present application is executed.

[0090] The beneficial effect of the present application is that the method and device can accurately simulate the drag loss of the electric drive reducer in the non-power transmission process under different working conditions (i.e., the internal friction and wind resistance and other losses when the drive system does not output power but still keeps rotating), thereby providing a scientific basis for designing a more efficient and energy-saving electric drive system. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0092] Figure 1 A schematic flow chart of a method for simulating drag torque of a reducer of an automobile electric drive system provided in an embodiment of the present application;

[0093] Figure 2 A schematic flow chart of another method for simulating drag torque of a reducer of an automobile electric drive system provided in an embodiment of the present application;

[0094] Figure 3 A T provided in the embodiment of the present application visc The process of calculation by semi-implicit particle method;

[0095] Figure 4 A T provided in the embodiment of the present application wind The process of calculation by finite element method;

[0096] Figure 5 An example diagram of setting a spatial calculation domain in a gearbox provided in an embodiment of the present application;

[0097] Figure 6 A schematic diagram of a slice wind field result provided in an embodiment of the present application;

[0098] Figure 7A T provided in the embodiment of the present application f Schematic diagram of the calculation process using the finite element method;

[0099] Figure 8 A schematic diagram of an example flow of a method for simulating drag torque of a reducer of an automobile electric drive system provided in an embodiment of the present application;

[0100] Fig. 9 A schematic diagram of the structure of a drag torque simulation device for a reducer of an automobile electric drive system provided in an embodiment of the present application;

[0101] Fig.10 A schematic structural diagram of another vehicle electric drive system reducer drag torque simulation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0102] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0103] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0104] Example 1

[0105] Please see Figure 1 , Figure 1 The flowchart of a method for simulating drag torque of a reducer of an automobile electric drive system provided in this embodiment includes:

[0106] S101. After receiving the system input torque, obtain a reducer geometric model, a reducer surface mesh model, and a reducer gear shaft-tooth assembly model.

[0107] S102, performing simulation calculation based on the semi-implicit particle method according to the reducer geometric model to obtain the oil stirring torque.

[0108] S103, performing simulation calculation based on the finite element method according to the reducer surface mesh model to obtain wind resistance torque.

[0109] S104. Perform simulation calculation based on the finite element method according to the shaft-gear assembly model to obtain the system friction torque.

[0110] In this embodiment, the oil stirring torque T visc , wind resistance moment T wind , system friction torque T fCalculated by different methods: T visc By using the semi-implicit particle method, T wind , T f Calculated by finite element method.

[0111] S105: Obtain the reducer input speed and output shaft moment of inertia.

[0112] S106, calculating the assembly drag torque according to the reducer input speed, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

[0113] In this embodiment, the calculation formula of the assembly drag torque is:

[0114]

[0115] Among them, T in is the assembly drag torque, T visc is the oil stirring torque, T wind is the wind resistance moment, T f is the friction torque of the system, J out is the output shaft moment of inertia, is the rate of change of the reducer output speed over time;

[0116] Among them, T out is the output torque of the reducer, T out =0.

[0117] In this embodiment, the execution subject of the method may be a computing device such as a computer or a server, and no limitation is made in this embodiment.

[0118] In this embodiment, the execution subject of the method may also be a smart device such as a smart phone, a tablet computer, etc., which is not limited in this embodiment.

[0119] It can be seen that the implementation of the automotive electric drive system reducer drag torque simulation method described in this embodiment can accurately quantify the drag torque through simulation, which is beneficial to improving system efficiency, shortening the development cycle, and providing a scientific basis for designing a more efficient and energy-saving electric drive system.

[0120] Example 2

[0121] Please see Figure 2 , Figure 2 The flowchart of a method for simulating drag torque of a reducer of an automobile electric drive system provided in this embodiment includes:

[0122] S201. After receiving the system input torque, obtain a reducer geometric model, a reducer surface mesh model, and a reducer gear shaft-tooth assembly model.

[0123] S202, performing model pre-processing on the reducer geometric model to obtain a parts grouping model.

[0124] S203, import the part grouping model into the solver, and add the solver to the solid domain.

[0125] S204. Create a fluid domain and configure oil parameters for the fluid domain to obtain a configured fluid domain.

[0126] S205 , setting the shaft-tooth rotation motion for the solid domain to obtain a set solid domain.

[0127] S206. Configure solver parameters for the solver to obtain a configured solver.

[0128] S207. According to the configured fluid domain, the set solid domain and the configured solver, a semi-implicit particle algorithm is used to establish an oil stirring torque calculation model.

[0129] S208, performing simulation calculation according to the oil stirring torque calculation model to obtain a first simulation calculation result.

[0130] S209: Obtain the oil stirring torque according to the first simulation calculation result.

[0131] For example, Figure 3 It shows that T visc The process of calculating through semi-implicit particle method, specifically using three-dimensional calculation method, using particle method CFD software to establish T visc The calculation model is as follows:

[0132] (1) Geometric model preprocessing: In the preprocessing software, the model is divided into different parts groups according to the classification methods such as shell, shaft, bearing, etc., and the different parts groups are exported into .stl format;

[0133] (2) Model import: Import the .stl file in the shonDy solver and add it to the solid domain;

[0134] (3) Create and set the fluid domain: Add a fluid domain: Select the fluid domain type: Select from liquid level for splash lubrication; When setting the fluid domain, the reference point cannot be placed in a closed space other than the shell cavity, and cannot interfere with the parts;

[0135] (4) Input oil parameters: Input oil parameters in the Physical Properties column of the Fluid Domain Settings;

[0136] (5) Shaft gear rotation setting:

[0137] ① In the solid domain, set the solid domain type of the rotating shaft gear to a moving body;

[0138] ② In the multi-body system settings, in the rotation speed column, set the motion parameters and bind the rotating body;

[0139] ③ Reference Frame is the default (for the planetary gears in the planetary gear set, the orbiting component should be selected as the Reference Frame, i.e. the planetary frame, and the rotation axis should be selected as the rotation axis). The principle for determining the direction of the rotation axis is the right-hand rule;

[0140] ④Use geometric software to determine the exact value of the rotation center. Select any point on the axis of the shaft and gear and use this coordinate as the rotation center;

[0141] ⑤ Set the rotation speed by inputting a fixed value or curve. Setting the speed curve in steps can prevent the speed surge from affecting the calculation accuracy. You can also automatically obtain the rotation center directly through the from moving body command.

[0142] (6) Solver parameter setting:

[0143] ① Solver Controls settings;

[0144] ② Set the particle radius, and keep the total number of particles between 500,000 and 1 million;

[0145] ③Set gravity properties;

[0146] ④ Turn on the turbulence model, wall viscosity model and fluid motion;

[0147] ⑤Adjust the result and sample output interval in the output setting;

[0148] (7) Run calculations and post-process results.

[0149] S210. Define a gear rotation envelope surface in the reducer surface mesh model to obtain a first calculation model.

[0150] S211. Setting a calculation domain of the space inside the gear box as the first calculation model according to the gear rotation envelope surface to obtain a second calculation model.

[0151] S212, gridding the second calculation model to obtain a third calculation model.

[0152] S213, performing local encryption processing near the tooth surface on the third calculation model to obtain a fourth calculation model.

[0153] S214. Add a physical model to the calculation domain in the fourth calculation model to obtain a fifth calculation model.

[0154] S215. Setting calculation boundaries for the fourth calculation model according to a finite element algorithm to obtain a wind resistance moment calculation model.

[0155] S216. Perform simulation calculation according to the wind resistance moment calculation model to obtain a second simulation calculation result.

[0156] S217. Obtain wind resistance torque according to the second simulation calculation result.

[0157] For example, Figure 4 It shows that T wind The calculation process is carried out by the finite element method, specifically using a three-dimensional calculation method and using the finite element software STAR CCM+ to establish T wind The calculation model is as follows:

[0158] (1) Import model: input surface mesh, format stl, etc.

[0159] (2) Define gear rotation:

[0160] ① Create a cylinder for each meshing gear envelope as a carrier for defining rotational motion:

[0161] ② Create the rotation center (local coordinate system) of each meshing gear, and create a cylinder with a radius slightly larger than the outer contour of the gear and a thickness equal to the axial length of the gear axis. First, use the model that is 1.2 times larger than the center of the large gear contour to trim the cylinder of the small gear so that the cylinder of the small gear shows the details of the meshing teeth. Then use the trimmed cylinder of the small gear to trim the cylinder of the large gear. In this way, two envelope surfaces that reflect the meshing details of the meshing gears are obtained. Finally, the two parts are summed and the overlapping meshing parts are deleted.

[0162] ③ Set the calculation domain of the entire gearbox space. The calculation domain can be found in Figure 5 ( Figure 5 The figure shows the three computational domains in a pair of meshing gears. Among them, the reducer housing and the uncut large and small gear cylinders are obtained by Boolean subtraction.

[0163] (3) Grid division: Grid division is performed on the whole, and local meshing is performed near the tooth surface;

[0164] (4) Add physical model: Add physical model to the meshed computational domain, select the air unidirectional flow - separation flow - constant density - steady-state calculation - turbulence model for the computational domain around the gear; add air density, dynamic viscosity and other physical properties; add the rotation speed and rotation reference system of each gear;

[0165] (5) Calculation settings:

[0166] ①Set the maximum static condition and calculate the time;

[0167] ② Add result axial slices along the tooth width overlap area of ​​a pair of meshing gears to be observed, and observe the flow field state of each section;

[0168] ③ Check the sum of the individual tooth surface torques in each pair of meshing gears, that is, the torque required for this gear to overcome the air T wind-i ;

[0169] Among them, each gearbox generally has two pairs of meshing gears and four gears, namely:

[0170]

[0171] Among them, the slice wind field results are as follows Figure 6 shown.

[0172] S218. Perform material parameter configuration on the shaft-gear assembly model to obtain a first configuration model.

[0173] S219, grouping the contact surfaces of the large and small gears of the first configuration model to obtain a grouping result.

[0174] S220 . Perform local mesh encryption processing on the first configuration model according to the grouping result to obtain a second configuration model.

[0175] S221. Perform link parameter configuration on the second configuration model to obtain a third configuration model.

[0176] S222. Calculate and set the third configuration model according to a finite element algorithm to obtain a system friction torque calculation model.

[0177] S223. Perform simulation calculation according to the system friction torque calculation model to obtain a third simulation calculation result.

[0178] S224. Obtain the system friction torque according to the third simulation calculation result.

[0179] For example, Figure 7 It shows that T f Through the calculation process of the finite element method, a three-dimensional calculation method is used, and the finite element software ANSYS is used to establish T f The calculation model is as follows:

[0180] (1) Model import: Import the gear shaft-tooth assembly model (bearing), and the bearing can be a simplified model;

[0181] (2) Material definition: define the material of the shaft and gear parts (including simplified bearings), and set isotropy, density, modulus, etc.

[0182] (3) Local encryption: Group the contact surfaces of large and small gears to locally encrypt the mesh;

[0183] (4) Connection definition: Select friction contact as the contact type; set the friction coefficient to the commonly used empirical value, the normal stiffness to 1, and the update stiffness to each iteration; use automatic bisection for time step control; set the revolving pair to rotate about the ground;

[0184] (5) Calculation settings: initial substep 25, minimum substep 20, maximum substep 250. A pair of gears, the connection load is set to the rotation speed and torque respectively, and the solution torque convergence;

[0185] (6) Output setting: Set to the desired torque of the output shaft driven gear, and finally read T at this speed. f .

[0186] S225. Obtain the reducer input speed and output shaft moment of inertia.

[0187] S226. Obtain the speed ratio of the reducer gear.

[0188] S227. Calculate the output speed of the reducer according to the input speed of the reducer and the gear ratio of the reducer.

[0189] In this embodiment, in the electric drive system of the new energy vehicle, the relationship between the input speed and the output speed of the reducer is:

[0190]

[0191] Among them, ω out is the output speed of the reducer, ω in is the speed reducer input speed, and i is the speed ratio of the reducer gear.

[0192] S228. Calculate the rate of change of the output speed of the reducer with respect to time according to the output speed of the reducer.

[0193] S229. Calculate the assembly drag torque according to the rate of change of the output speed of the reducer with respect to time, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

[0194] In this embodiment, the calculation formula of the assembly drag torque is:

[0195]

[0196] Among them, T in is the assembly drag torque, T visc is the oil stirring torque, T wind is the wind resistance moment, T f is the friction torque of the system, J out is the output shaft moment of inertia, is the rate of change of the reducer output speed over time;

[0197] Among them, Tout is the output torque of the reducer, T out =0.

[0198] In this embodiment, the method can obtain different input speeds ω in Lower T in The value of (this value is the drag torque of the assembly); where T out =0.

[0199] Please see Figure 8 , Figure 8 The present invention shows a schematic flow chart of an example of a method for simulating the drag torque of a reducer of an automobile electric drive system.

[0200] The implementation of this method can accurately quantify these losses, help engineers optimize designs and reduce unnecessary energy consumption; it can also test and compare multiple design options in a virtual environment through simulation technology, without the need to manufacture physical prototypes for time-consuming and costly testing, thereby greatly shortening the time from design to market for products; it can also avoid late modifications due to design defects through accurate simulation, reduce material waste and retesting costs, make the entire development process more economical and efficient, and promote cost reduction.

[0201] On the other hand, based on detailed simulation data, this method can prompt engineers to focus on optimizing components or links with large drag losses, such as improving gear design, lubrication strategy, and replacing bearings with low-friction bearings, etc., to achieve a significant improvement in overall efficiency; it can also quickly evaluate different vehicle models or application scenarios by adjusting simulation parameters and optimize the design of electric drive reducers to meet specific performance requirements and enhance the market competitiveness of products; it can also be applied to the product use stage, through comparative analysis of actual operating data and simulation results, to predict potential failures, provide users with preventive maintenance suggestions, and extend product service life.

[0202] In this embodiment, the execution subject of the method may be a computing device such as a computer or a server, and no limitation is made in this embodiment.

[0203] In this embodiment, the execution subject of the method may also be a smart device such as a smart phone, a tablet computer, etc., which is not limited in this embodiment.

[0204] It can be seen that the implementation of the drag torque simulation method of the reducer of the automobile electric drive system described in this embodiment can develop a more accurate mathematical model or physical model to describe the working characteristics of the reducer in the electric drive system, including the dynamic response and friction characteristics of key components such as the reducer and bearing, so as to more accurately predict the drag torque changes inside the reducer under different working conditions (such as acceleration, deceleration, and constant speed driving), and improve the accuracy of the simulation. The method can also combine the simulation technology of multiple physical fields such as mechanics and thermodynamics to comprehensively analyze the reducer system; through this interdisciplinary method, the interaction and energy conversion process between the components of the reducer system during operation can be more realistically simulated, including the mechanical loss of gear meshing and the resulting thermal effects, so as to more accurately evaluate the drag torque. The method can also optimize the simulation parameters using advanced algorithms such as artificial intelligence and machine learning, and automatically adjust the model parameters to achieve the best fitting effect, thereby not only improving the simulation efficiency, but also discovering nonlinear relationships based on a large amount of data, further improving the simulation accuracy, and providing strong support for design optimization. This method can also perform real-time simulation and hardware-in-the-loop testing, specifically combining the above simulation method with the actual electric drive system hardware to achieve hardware-in-the-loop (HIL) simulation testing. In this way, various extreme or complex working conditions can be simulated in a virtual environment, and the drag torque of the reducer can be deeply tested and verified to ensure the effectiveness and practicality of the simulation results, shorten the product development cycle, and reduce testing costs. This method can also incorporate the wear and aging effects of the reducer components over time in the simulation, making the simulation results closer to the actual situation, helping to predict and evaluate the performance changes of the electric drive system throughout its life cycle in advance, and provide a basis for maintenance strategies. In summary, this method can not only improve the performance and efficiency of the electric drive system of new energy vehicles, but also effectively predict and optimize its energy efficiency ratio in the design stage, reduce energy consumption, and enhance market competitiveness.

[0205] Example 3

[0206] Please see Fig. 9 , Fig. 9 This is a schematic diagram of the structure of a drag torque simulation device for a reducer of an automobile electric drive system provided in this embodiment. Fig. 9 As shown, the drag torque simulation device of the reducer of the automobile electric drive system includes:

[0207] A first acquisition unit 310 is used to acquire a reducer geometric model, a reducer surface mesh model, and a shaft-tooth assembly model of the reducer gear after receiving a system input torque;

[0208] The first simulation unit 320 is used to perform simulation calculation based on the semi-implicit particle method according to the reducer geometric model to obtain the oil stirring torque;

[0209] The second simulation unit 330 is used to perform simulation calculation based on the finite element method according to the reducer surface mesh model to obtain the wind resistance torque;

[0210] The third simulation unit 340 is used to perform simulation calculation based on the finite element method according to the shaft-gear assembly model to obtain the system friction torque;

[0211] The second acquisition unit 350 is used to acquire the input speed of the reducer and the moment of inertia of the output shaft;

[0212] The calculation unit 360 is used to calculate the assembly drag torque according to the reducer input speed, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

[0213] In this embodiment, the explanation of the drag torque simulation device for the reducer of the automobile electric drive system can refer to the description in Example 1 or Example 2, and will not be further elaborated in this embodiment.

[0214] It can be seen that the implementation of the drag torque simulation device for the reducer of the automobile electric drive system described in this embodiment can accurately quantify the drag torque through simulation, which is beneficial to improving system efficiency, shortening the development cycle, and providing a scientific basis for designing a more efficient and energy-saving electric drive system.

[0215] Example 4

[0216] Please see Fig.10 , Fig.10 This is a schematic diagram of the structure of a drag torque simulation device for a reducer of an automobile electric drive system provided in this embodiment. Fig.10 As shown, the drag torque simulation device of the reducer of the automobile electric drive system includes:

[0217] A first acquisition unit 310 is used to acquire a reducer geometric model, a reducer surface mesh model, and a shaft-tooth assembly model of the reducer gear after receiving a system input torque;

[0218] The first simulation unit 320 is used to perform simulation calculation based on the semi-implicit particle method according to the reducer geometric model to obtain the oil stirring torque;

[0219] The second simulation unit 330 is used to perform simulation calculation based on the finite element method according to the reducer surface mesh model to obtain the wind resistance torque;

[0220] The third simulation unit 340 is used to perform simulation calculation based on the finite element method according to the shaft-gear assembly model to obtain the system friction torque;

[0221] The second acquisition unit 350 is used to acquire the input speed of the reducer and the moment of inertia of the output shaft;

[0222] The calculation unit 360 is used to calculate the assembly drag torque according to the reducer input speed, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

[0223] As an optional implementation, the first simulation unit 320 includes:

[0224] The pre-processing sub-unit 321 is used to perform model pre-processing on the reducer geometric model to obtain a parts grouping model;

[0225] An import subunit 322 is used to import the part grouping model into the solver and add the solver to the solid domain;

[0226] The first configuration subunit 323 is used to create a fluid domain and configure oil parameters for the fluid domain to obtain a configured fluid domain;

[0227] The first configuration subunit 323 is further used to perform shaft-tooth rotational motion setting on the solid domain to obtain a set solid domain;

[0228] A first setting subunit 324 is used to configure solver parameters for the solver to obtain a configured solver;

[0229] Establishing a subunit 325 for establishing an oil stirring torque calculation model using a semi-implicit particle algorithm according to the configured fluid domain, the set solid domain and the configured solver;

[0230] A first simulation subunit 326 is used to perform simulation calculation according to the oil stirring torque calculation model to obtain a first simulation calculation result;

[0231] The first acquisition subunit 327 is used to acquire the oil stirring torque according to the first simulation calculation result.

[0232] As an optional implementation, the second simulation unit 330 includes:

[0233] A definition subunit 331 is used to define a gear rotation envelope surface in the reducer surface mesh model to obtain a first calculation model;

[0234] A second setting subunit 332 is used to set the calculation domain of the space inside the gear box for the first calculation model according to the gear rotation envelope surface to obtain a second calculation model;

[0235] A division subunit 333 is used to perform grid division on the second calculation model to obtain a third calculation model;

[0236] A first encryption subunit 334 is used to perform local encryption processing near the tooth surface on the third calculation model to obtain a fourth calculation model;

[0237] An adding subunit 335 is used to add a physical model to the calculation domain in the fourth calculation model to obtain a fifth calculation model;

[0238] A third setting subunit 336 is used to set a calculation boundary for the fourth calculation model according to a finite element algorithm to obtain a wind resistance moment calculation model;

[0239] The second simulation subunit 337 is used to perform simulation calculation according to the wind resistance moment calculation model to obtain a second simulation calculation result;

[0240] The second acquisition subunit 338 is used to acquire the wind resistance torque according to the second simulation calculation result.

[0241] As an optional implementation, the third simulation unit 340 includes:

[0242] The second configuration subunit 341 is used to configure material parameters of the shaft-gear assembly model to obtain a first configuration model;

[0243] The grouping subunit 342 is used to group the contact surfaces of the large and small gears of the first configuration model to obtain a grouping result;

[0244] The second encryption subunit 343 is used to perform grid local encryption processing on the first configuration model according to the grouping result to obtain a second configuration model;

[0245] The third configuration subunit 344 is used to configure the link parameters of the second configuration model to obtain a third configuration model;

[0246] A calculation setting subunit 345 is used to perform calculation setting on the third configuration model according to a finite element algorithm to obtain a system friction torque calculation model;

[0247] The third simulation subunit 346 is used to perform simulation calculation according to the system friction torque calculation model to obtain a third simulation calculation result;

[0248] The third acquisition subunit 347 is used to acquire the system friction torque according to the third simulation calculation result.

[0249] As an optional implementation, the calculation unit 360 includes:

[0250] The fourth acquisition subunit 361 is used to acquire the gear ratio of the reducer;

[0251] The calculation subunit 362 is used to calculate the output speed of the reducer according to the input speed of the reducer and the gear ratio of the reducer;

[0252] The calculation subunit 362 is further used to calculate the rate of change of the output speed of the reducer with respect to time according to the output speed of the reducer;

[0253] The calculation subunit 362 is also used to calculate the assembly drag torque according to the rate of change of the output speed of the reducer with respect to time, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

[0254] In this embodiment, the calculation formula of the assembly drag torque is:

[0255]

[0256] Among them, T in is the assembly drag torque, T visc is the oil stirring torque, T wind is the wind resistance moment, T f is the friction torque of the system, J out is the output shaft moment of inertia, is the rate of change of the reducer output speed over time;

[0257] Among them, T out is the output torque of the reducer, T out =0.

[0258] In this embodiment, the explanation of the drag torque simulation device for the reducer of the automobile electric drive system can refer to the description in Example 1 or Example 2, and will not be further elaborated in this embodiment.

[0259] It can be seen that the implementation of the drag torque simulation device for the reducer of the automobile electric drive system described in this embodiment can accurately quantify the drag torque through simulation, which is beneficial to improving system efficiency, shortening the development cycle, and providing a scientific basis for designing a more efficient and energy-saving electric drive system.

[0260] An embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the automobile electric drive system reducer drag torque simulation method in embodiment 1 or embodiment 2 of the present application.

[0261] An embodiment of the present application provides a computer-readable storage medium storing computer program instructions. When the computer program instructions are read and executed by a processor, the method for simulating the drag torque of the reducer of the automobile electric drive system in Embodiment 1 or Embodiment 2 of the present application is executed.

[0262] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0263] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0264] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0265] The above description is only an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0266] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0267] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

Claims

1. A method for simulating drag torque of a reducer of an automobile electric drive system, characterized in that: include: After receiving the system input torque, a reducer geometric model, a reducer surface mesh model, and a shaft-tooth assembly model of the reducer gear are obtained; According to the reducer geometric model, simulation calculation based on semi-implicit particle method is performed to obtain the oil stirring torque; Performing simulation calculation based on the finite element method according to the reducer surface mesh model to obtain the wind resistance torque; Performing simulation calculation based on the finite element method according to the shaft-gear assembly model to obtain the system friction torque; Get the reducer input speed and output shaft moment of inertia; The assembly drag torque is calculated according to the reducer input speed, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

2. The method for simulating drag torque of a reducer of an automobile electric drive system according to claim 1, characterized in that: The simulation calculation based on the semi-implicit particle method is performed according to the reducer geometric model to obtain the oil stirring torque, including: Performing model pre-processing on the reducer geometric model to obtain a parts grouping model; Importing the part grouping model into a solver, and adding the solver to a solid domain; Creating a fluid domain, and configuring oil parameters for the fluid domain to obtain a configured fluid domain; Performing shaft-tooth rotational motion setting on the solid domain to obtain a set solid domain; configuring solver parameters for the solver to obtain a configured solver; According to the configured fluid domain, the set solid domain and the configured solver, a semi-implicit particle algorithm is used to establish an oil stirring torque calculation model; Perform simulation calculation according to the oil stirring torque calculation model to obtain a first simulation calculation result; The oil stirring torque is obtained according to the first simulation calculation result.

3. The method for simulating drag torque of a reducer of an automobile electric drive system according to claim 1, characterized in that: The simulation calculation based on the finite element method is performed according to the reducer surface mesh model to obtain the wind resistance torque, including: Defining a gear rotation envelope surface in the reducer surface mesh model to obtain a first calculation model; According to the gear rotation envelope surface, a calculation domain of the space inside the gear box is set for the first calculation model to obtain a second calculation model; Performing grid division on the second calculation model to obtain a third calculation model; Performing local encryption processing near the tooth surface on the third calculation model to obtain a fourth calculation model; Adding a physical model to the calculation domain in the fourth calculation model to obtain a fifth calculation model; Setting a calculation boundary for the fourth calculation model according to a finite element algorithm to obtain a wind resistance moment calculation model; Perform simulation calculation according to the wind resistance moment calculation model to obtain a second simulation calculation result; According to the second simulation calculation result, the wind resistance torque is obtained.

4. The method for simulating drag torque of a reducer of an automobile electric drive system according to claim 1, characterized in that: The simulation calculation based on the finite element method is performed according to the shaft-gear assembly model to obtain the system friction torque, including: Performing material parameter configuration on the shaft-gear assembly model to obtain a first configuration model; Grouping the contact surfaces of large and small gears of the first configuration model to obtain a grouping result; Performing local mesh encryption processing on the first configuration model according to the grouping result to obtain a second configuration model; Performing link parameter configuration on the second configuration model to obtain a third configuration model; Calculate and set the third configuration model according to a finite element algorithm to obtain a system friction torque calculation model; Perform simulation calculation according to the system friction torque calculation model to obtain a third simulation calculation result; According to the third simulation calculation result, the system friction torque is obtained.

5. The method for simulating drag torque of a reducer of an automobile electric drive system according to claim 1, characterized in that: The calculating of the assembly drag torque according to the reducer input speed, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque includes: Get the gear ratio of the reducer; Calculating the output speed of the reducer according to the input speed of the reducer and the gear ratio of the reducer; Calculating the rate of change of the output speed of the reducer with respect to time according to the output speed of the reducer; The assembly drag torque is calculated based on the rate of change of the reducer output speed with respect to time, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

6. The method for simulating drag torque of a reducer of an automobile electric drive system according to claim 5, characterized in that: The calculation formula of the assembly drag torque is: Among them, T in is the drag torque of the assembly, T visc is the oil stirring torque, T wind is the wind resistance moment, T f is the friction torque of the system, J out is the output shaft moment of inertia, is the rate of change of the output speed of the reducer with respect to time; Among them, T out is the output torque of the reducer, T out =0.

7. A drag torque simulation device for a reducer of an automobile electric drive system, characterized in that: The drag torque simulation device of the reducer of the automobile electric drive system comprises: A first acquisition unit is used to acquire a reducer geometric model, a reducer surface mesh model, and a shaft-tooth assembly model of the reducer gear after receiving a system input torque; A first simulation unit is used to perform simulation calculation based on a semi-implicit particle method according to the reducer geometric model to obtain an oil stirring torque; A second simulation unit is used to perform simulation calculation based on the finite element method according to the reducer surface mesh model to obtain a wind resistance torque; A third simulation unit is used to perform simulation calculation based on the finite element method according to the shaft-gear assembly model to obtain a system friction torque; The second acquisition unit is used to acquire the input speed of the reducer and the moment of inertia of the output shaft; The calculation unit is used to calculate the assembly drag torque according to the reducer input speed, the output shaft rotational inertia, the oil stirring torque, the wind resistance torque and the system friction torque.

8. The drag torque simulation device for a reducer of an automobile electric drive system according to claim 7, characterized in that: The first simulation unit comprises: A pre-processing sub-unit, used for performing model pre-processing on the reducer geometric model to obtain a parts grouping model; Importing subunits, for importing the part grouping model into a solver, and adding the solver to a solid domain; A first configuration subunit is used to create a fluid domain and configure oil parameters for the fluid domain to obtain a configured fluid domain; The first configuration subunit is further used to perform shaft-tooth rotational motion setting on the solid domain to obtain a set solid domain; A first setting subunit is used to configure solver parameters for the solver to obtain a configured solver; Establishing a subunit for establishing an oil stirring torque calculation model by using a semi-implicit particle algorithm according to the configured fluid domain, the set solid domain and the configured solver; A first simulation subunit, used for performing simulation calculation according to the oil stirring torque calculation model to obtain a first simulation calculation result; The first acquisition subunit is used to acquire the oil stirring torque according to the first simulation calculation result.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the drag torque simulation method for the reducer of an automobile electric drive system according to any one of claims 1 to 6.

10. A readable storage medium, characterized in that: The readable storage medium stores computer program instructions, and when the computer program instructions are read and executed by a processor, the method for simulating the drag torque of a reducer of an automobile electric drive system according to any one of claims 1 to 6 is executed.

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