Accurate control method for forging forming of automobile spline shaft yoke

Abstract

The invention discloses a precise control method for forging forming of an automobile spline shaft yoke, which comprises the following steps of: (1) designing a most reasonable forge piece blank and a forming die thereof according to the size characteristics of a specific spline shaft yoke product; (2) the forming die is installed on horizontal forging oil press equipment; (3) the blank is placed in a forming die, and a closed forming process is adopted for forging operation; and (4) the computer analyzes the forging forming process through whole-process numerical simulation, and optimal process parameters are determined through hot forging forming process design optimization. According to the spline shaft yoke precise forming control method, spline shaft yoke forging forming is simulated in the whole process, analysis and optimization are conducted on a computer, an optimal forming scheme is finally formulated, and the optimal combination of the forming force, the filling effect and the mold service life is achieved. The method is applied to research and development of a near-net forming manufacturing core technology of high-end heavy truck transmission shaft complex forgings, and has great significance in improving the manufacturing level and the independent innovation capacity of automobile parts in China.

Description

Technical Field

[0001] The invention belongs to the technical field of heavy truck manufacturing, and in particular relates to a method for accurately controlling the forging forming of a spline shaft fork of an automobile. Background Art

[0002] The conventional processing method of automobile spline shaft forks adopts hot die forging process, which has high energy consumption, large amount of waste and large pollution, and the process technology innovation is imminent. As a new way of manufacturing complex precision forgings, near-net-shape manufacturing technology has the characteristics of precision, high quality, high efficiency, low consumption, low cost and large-scale production. The near-net-shape technology is used for forging production, which only needs a small amount of processing or no processing before it can be used as a finished product, which can effectively improve the utilization rate of the billet and the processing accuracy of the forging. Summary of the invention

[0004] In order to solve the above technical problems existing in the prior art, the present invention provides a method for accurately controlling the forging forming of an automobile spline shaft fork by means of computer-assisted numerical simulation combined with physical experimental verification and optimization.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solution: a method for accurately controlling the forging of an automobile spline shaft fork, comprising the following steps:

[0006] (1) Design the most reasonable forging blank and its forming die according to the specific dimensional characteristics of the spline shaft fork product;

[0007] (2) Install the forming die on the flat forging hydraulic press equipment;

[0008] (3) Placing the blank into a forming die and performing forging operation using a closed forming process;

[0009] (4) The forging process is analyzed by computer numerical simulation, and the optimal process parameters are determined through hot forging process design optimization.

[0010] The specific contents of step (1) are as follows: a bar with a diameter of 70 mm and a length of 300 mm, with a single piece weight of about 9 kg, is used. A medium frequency induction heating furnace is used at a temperature of 1100°C. Only a 200 mm length range is locally heated, and the remaining 100 mm portion is not heated. After heating, a descaling machine is used to remove the oxide scale on the heated surface of the blank.

[0011] The specific contents of step (3) are as follows: the flat forging hydraulic press equipment provides forming forces in three directions: the vertical cylinder clamps the forming die, the horizontal cylinder performs forging and forming, then the vertical cylinder returns to open the die, and the lower ejector cylinder ejects the forged workpiece; the vertical cylinder provides a maximum upper and lower clamping force of 400 tons, the horizontal cylinder provides a maximum forming force of 400 tons in the horizontal direction, and the lower ejector cylinder provides a maximum ejection force of 30 tons in the bottom-up direction; the hydraulic system of the flat forging hydraulic press equipment adopts servo control, and the screen displays Display main parameters, and can set pressure and stroke displacement.

[0012] The specific steps of the occlusion forming process are as follows:

[0013] Step 1: After the blank is placed in the lower die of the forming die, the vertical cylinder drives the upper die of the forming die to move downward so that the upper die and the lower die are closed to form a closed die cavity, preparing for the forming of the part;

[0014] Step 2: The horizontal cylinder is started to perform flat forging on the blank in the closed die cavity until the forging is completed;

[0015] Step 3: The vertical cylinder returns upward to open the die, and the lower ejector cylinder is started to eject the forged workpiece from the lower die.

[0016] There are three important factors in the optimization of hot forging process design in step (4): objective function, design variables and constraints;

[0017] The hot forging process design optimization includes the following steps:

[0018] The first step is to transform the optimization target from a qualitative form into a specific quantitative expression. In order to optimize the material utilization rate in the hot forging process, the volume difference is used to characterize the objective function, which is specifically defined as the percentage of the volume difference between the ideal forging and the actual forging in the volume of the ideal forging, which is defined as:

[0019] φ=(V i -V s ) / V i

[0020] Where: V i is the volume of the ideal forging, V s is the volume of the actual forging; when the φ value is zero, it means that the metal completely fills the cavity; when the φ value is greater than zero, it means that the metal does not fill the cavity; when the φ value is less than zero, it means that there is too much metal and it will overflow the cavity to form flash;

[0021] Step 2: Select design variables according to the characteristics of die forging process, and select parameters that have an important influence on the objective function as design variables. Other less important parameters will not be considered in the design optimization process;

[0022] Step 3: Set a constraint condition that must be satisfied; the hot forging process design optimization problem is a constrained optimization problem. Although this will make the problem more difficult to solve, it is an unavoidable problem for a practical production application. In order to ensure the quality of forgings, during the optimization process, while the objective function reaches an ideal state, it must ensure that the metal completely fills the cavity without defects.

[0023] In step (4), in order to accurately simulate and analyze the forging process, an accurate constitutive equation of the material is a necessary basis, and the constitutive equation parameters need to be accurately identified;

[0024] The constitutive equation of 40Cr obtained by the traditional averaging method is:

[0025]

[0026] Then, the error between the predicted stress calculated by the constitutive equation and the test stress is used as the objective function:

[0027]

[0028] in: is the flow stress obtained from the experiment, is the predicted flow stress;

[0029] Using the Levenberg-Marquardt algorithm, the identification strategy of minimizing the objective function, and a specially designed optimization process, the constitutive equation of 40Cr is obtained as follows:

[0030]

[0031] After optimization, the correlation coefficient R between the rheological stress test value and the predicted value of the optimized model increased from 0.928 to 0.985;

[0032] Then, based on finite element analysis and optimization algorithm, the process parameters and structural design of the forging are optimized. According to the above volume difference formula, the process flow before optimization has huge flash, and the φ value is much less than zero; therefore, this application chooses to use φ value equal to zero as the optimization objective function, and the shape parameters of the flash, the fillet radius of the mold cavity and the shape of the pre-forging are design variables. The changes in these design variables directly change the geometric models of the mold and pre-forging. This process is achieved by calling the API function of the SolidWorks software; the changed geometric model is read into the finite element model description file (KEY file) in IGES or STL format, and the finite element preprocessor converts the KEY file into a DB file for the simulation program to call; after the simulation program is run, the calculation results are stored in the DB file; since the DB file is in binary format, it needs to be converted into the KEY file format through the preprocessor, and the specific value of the objective function is obtained through parameter extraction and calculation of the program, and a complete iterative calculation is completed.

[0033] The above technical solution can reduce the raw material utilization rate of the traditional forging process of spline shaft forks, resulting in poor consistency of forging quality and high production costs. The forming process is analyzed by computer numerical simulation, and the optimal process parameters are determined after optimization and improvement.

[0034] The entire process of numerical simulation needs to be completed on a computer using software: the core link is to establish an analysis model that is closest to the actual process, and the goal is to restore the actual dynamic process to the greatest extent on the computer, so as to rely on these analysis data to guide and optimize the actual production process. The most critical process step is the closed horizontal billet making process. The entire process of numerical simulation analysis and the analysis and optimization of the algorithm are also centered on the key step of closed billet making.

[0035] The present invention adopts a closed forming forging process. The blank is in a three-dimensional compressive stress state during the closed forging process, which can greatly improve the deformation degree of the metal. For fork shaft parts, the forming force can be provided from the rod direction. In this way, only the fork-shaped part of the original bar needs to be locally heated, which saves energy consumption and greatly reduces the forging forming force. The "clever force" is used from the process to realize the forging forming of the fork shaft.

[0036] The present invention adopts DEFORM simulation analysis software to simulate the whole process of spline shaft forging, analyzes and optimizes on the computer, and finally formulates the optimal forming plan to achieve the best combination of forming force, filling effect and die life. A spline shaft fork precise forming control method is summarized and proposed, which is applied to the research and development of core technology of near-net forming manufacturing of complex forgings of high-end heavy-duty truck drive shafts, which is of great significance to improving my country's automobile parts manufacturing level and independent innovation capability as well as the problem of key parts of high-end heavy-duty trucks. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the optimization process specially designed using the Levenberg-Marquardt algorithm;

[0038] Figure 2 It is a schematic diagram of the comparison between the experimental value and the model prediction value using the traditional averaging method;

[0039] Figure 3 It is a schematic diagram of the comparison between the experimental value and the model prediction value using the inverse optimization method;

[0040] Figure 4 It is a flow chart of the simulation optimization algorithm from design variables to objective function. DETAILED DESCRIPTION

[0041] The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and examples.

[0042] A method for accurately controlling forging of a spline shaft fork of an automobile according to the present invention comprises the following steps:

[0043] (1) Design the most reasonable forging blank and its forming die according to the specific dimensional characteristics of the spline shaft fork product;

[0044] (2) Install the forming die on the flat forging hydraulic press equipment;

[0045] (3) Placing the blank into a forming die and performing forging operation using a closed forming process;

[0046] (4) The forging process is analyzed by computer numerical simulation, and the optimal process parameters are determined through hot forging process design optimization.

[0047] The specific contents of step (1) are as follows: a bar with a diameter of 70 mm and a length of 300 mm, with a single piece weight of about 9 kg, is used. A medium frequency induction heating furnace is used at a temperature of 1100°C. Only a 200 mm length range is locally heated, and the remaining 100 mm portion is not heated. After heating, a descaling machine is used to remove the oxide scale on the heated surface of the blank.

[0048] The specific content of step (3) is as follows: the flat forging hydraulic press equipment provides forming forces in three directions: the vertical cylinder clamps the forming die, the horizontal cylinder performs forging and forming, then the vertical cylinder returns to open the die, and the lower ejector cylinder ejects the forged workpiece; the vertical cylinder provides a maximum upper and lower clamping force of 400 tons, the horizontal cylinder provides a maximum forming force of 400 tons in the horizontal direction, and the lower ejector cylinder provides a maximum ejection force of 30 tons in the bottom-up direction; the hydraulic system of the flat forging hydraulic press equipment adopts servo control, the screen displays the main parameters, and the pressure and stroke displacement can be set.

[0049] The specific steps of the occlusion forming process are as follows:

[0050] Step 1: After the blank is placed in the lower die of the forming die, the vertical cylinder drives the upper die of the forming die to move downward so that the upper die and the lower die are closed to form a closed die cavity, preparing for the forming of the part;

[0051] Step 2: The horizontal cylinder is started to perform flat forging on the blank in the closed die cavity until the forging is completed;

[0052] Step 3: The vertical cylinder returns upward to open the die, and the lower ejector cylinder is started to eject the forged workpiece from the lower die.

[0053] There are three important factors in the optimization of hot forging process design in step (4): objective function, design variables and constraints;

[0054] The hot forging process design optimization includes the following steps:

[0055] The first step is to transform the optimization target from a qualitative form into a specific quantitative expression. In order to optimize the material utilization rate in the hot forging process, the volume difference is used to characterize the objective function, which is specifically defined as the percentage of the volume difference between the ideal forging and the actual forging in the volume of the ideal forging, which is defined as:

[0056] φ=(V i -V s ) / V i

[0057] Where: V i is the volume of the ideal forging, V s is the volume of the actual forging; when the φ value is zero, it means that the metal completely fills the cavity; when the φ value is greater than zero, it means that the metal does not fill the cavity; when the φ value is less than zero, it means that there is too much metal and it will overflow the cavity to form flash;

[0058] Step 2: Select design variables according to the characteristics of die forging process, and select parameters that have an important influence on the objective function as design variables. Other less important parameters will not be considered in the design optimization process;

[0059] Step 3: Set a constraint condition that must be satisfied; the hot forging process design optimization problem is a constrained optimization problem. Although this will make the problem more difficult to solve, it is an unavoidable problem for a practical production application. In order to ensure the quality of forgings, during the optimization process, while the objective function reaches an ideal state, it must ensure that the metal completely fills the cavity without defects.

[0060] In step (4), in order to accurately simulate and analyze the forging process, an accurate constitutive equation of the material is a necessary basis, and the constitutive equation parameters need to be accurately identified;

[0061] The constitutive equation of 40Cr obtained by the traditional averaging method is:

[0062]

[0063] Then, the error between the predicted stress calculated by the constitutive equation and the test stress is used as the objective function:

[0064]

[0065] in: is the flow stress obtained from the experiment, is the predicted flow stress;

[0066] The Levenberg-Marquardt algorithm is used to identify the objective function minimization strategy, and a specially designed optimization process (such as Figure 1 As shown), the constitutive equation of 40Cr is as follows:

[0067]

[0068] like Figure 2 and 3 As shown and compared, after optimization, the correlation coefficient R between the flow stress test value and the predicted value of the optimized model increased from 0.928 to 0.985;

[0069] Then, based on finite element analysis and optimization algorithm, the process parameters and structural design of the forging are optimized. According to the above volume difference formula, the process flow before optimization has a huge flash, and the φ value is much less than zero; therefore, this application chooses the φ value equal to zero as the optimization objective function, and the shape parameters of the flash, the fillet radius of the mold cavity and the shape of the pre-forging are the design variables. The changes in these design variables directly change the geometric models of the mold and the pre-forging, such as Figure 4 As shown in the figure, this process is implemented by calling the API function of SolidWorks software; the changed geometric model is read into the finite element model description file (KEY file) in IGES or STL format, and the finite element pre-processor converts the KEY file into a DB file for the simulation program to call; after the simulation program is finished running, the calculation results are stored in the DB file; since the DB file is in binary format, it needs to be converted into the KEY file format through the pre-processor, and the specific value of the objective function is obtained through the program parameter extraction and calculation, and a complete iterative calculation is completed.

[0070] Analysis of actual process application of simulation optimization algorithm:

[0071] The traditional forging process of spline shaft fork is: blanking - heating - pre-forging (material drawing, material distribution) - final forging - trimming. With the goal of improving the quality and performance of forgings, the process parameters of forgings are optimized to obtain a new process flow: blanking - local heating - oxide scale removal - horizontal closed diversion extrusion billet (key process) - final forging - trimming. According to the volume difference formula, it can be seen that the φ value of the optimized process flow is close to zero, achieving the optimization goal, and then verified by actual process physical simulation.

[0072] The above embodiments illustrate the basic principles and features of the present invention, but the above only illustrates the preferred embodiments of the present invention and is not limited to the embodiments. Under the inspiration of this patent, a person skilled in the art can make many forms of deformation and improvement without departing from the scope of protection of the present invention and the claims, which are all within the protection scope of the present invention. Therefore, the patent and protection scope of the present invention shall be subject to the attached claims.

Claims

1. A precise control method for forging a spline shaft fork of an automobile, characterized in that: The following steps are involved: (1) Design the most reasonable forging blank and its forming die according to the specific dimensional characteristics of the spline shaft fork product; (2) Install the forming die on the flat forging hydraulic press equipment; (3) Placing the blank into a forming die and performing forging operation using a closed forming process; (4) The forging process is analyzed by computer numerical simulation, and the optimal process parameters are determined through hot forging process design optimization.

2. The method for accurately controlling the forging of a spline shaft fork of an automobile according to claim 1, characterized in that: The specific contents of step (1) are as follows: a bar with a diameter of 70 mm and a length of 300 mm, with a single piece weight of about 9 kg, is used. A medium frequency induction heating furnace is used at a temperature of 1100°C. Only a 200 mm length range is locally heated, and the remaining 100 mm portion is not heated. After heating, a descaling machine is used to remove the oxide scale on the heated surface of the blank.

3. The method for accurately controlling the forging of a spline shaft fork of an automobile according to claim 2, characterized in that: The specific content of step (3) is as follows: the flat forging hydraulic press equipment provides forming forces in three directions: the vertical cylinder clamps the forming die, the horizontal cylinder performs forging and forming, then the vertical cylinder returns to open the die, and the lower ejector cylinder ejects the forged workpiece; The vertical cylinder provides a maximum upper and lower clamping force of 400 tons, the horizontal cylinder provides a maximum forming force of 400 tons in the horizontal direction, and the lower ejector cylinder provides a maximum ejection force of 30 tons in the bottom-up direction; The hydraulic system of the flat forging hydraulic press equipment adopts servo control. The screen displays the main parameters and can set the pressure and stroke displacement.

4. The method for accurately controlling the forging of a spline shaft fork of an automobile according to claim 3, characterized in that: The specific steps of the occlusion forming process are as follows: Step 1: After the blank is placed in the lower die of the forming die, the vertical cylinder drives the upper die of the forming die to move downward so that the upper die and the lower die are closed to form a closed die cavity, preparing for the forming of the part; Step 2: The horizontal cylinder is started to perform flat forging on the blank in the closed die cavity until the forging is completed; Step 3: The vertical cylinder returns upward to open the die, and the lower ejector cylinder is started to eject the forged workpiece from the lower die.

5. A method for accurately controlling forging of a spline shaft fork for an automobile according to any one of claims 1 to 4, characterized in that: There are three important factors in the optimization of hot forging process design in step (4): objective function, design variables and constraints; The hot forging process design optimization includes the following steps: The first step is to transform the optimization target from a qualitative form into a specific quantitative expression. In order to optimize the material utilization rate in the hot forging process, the volume difference is used to characterize the objective function, which is specifically defined as the percentage of the volume difference between the ideal forging and the actual forging in the volume of the ideal forging, which is defined as: φ=(V i -V s ) / V i Where: V i is the volume of the ideal forging, V s is the volume of the actual forging; when the φ value is zero, it means that the metal completely fills the cavity; when the φ value is greater than zero, it means that the metal does not fill the cavity; when the φ value is less than zero, it means that there is too much metal and it will overflow the cavity to form flash; Step 2: Select design variables according to the characteristics of die forging process, and select parameters that have an important influence on the objective function as design variables. Other less important parameters will not be considered in the design optimization process; Step 3: Set a constraint condition that must be satisfied; the hot forging process design optimization problem is a constrained optimization problem. Although this will make the problem more difficult to solve, it is an unavoidable problem for a practical production application. In order to ensure the quality of forgings, during the optimization process, while the objective function reaches an ideal state, it must ensure that the metal completely fills the cavity without defects.

6. The method for accurately controlling the forging of a spline shaft fork of an automobile according to claim 5, characterized in that: In step (4), in order to accurately simulate and analyze the forging process, an accurate constitutive equation of the material is a necessary basis, and the constitutive equation parameters need to be accurately identified; The constitutive equation of 40Cr obtained by the traditional averaging method is: Then, the error between the predicted stress calculated by the constitutive equation and the test stress is used as the objective function: in: is the flow stress obtained from the experiment, is the predicted flow stress; Using the Levenberg-Marquardt algorithm, the identification strategy of minimizing the objective function, and a specially designed optimization process, the constitutive equation of 40Cr is obtained as follows: After optimization, the correlation coefficient R between the rheological stress test value and the predicted value of the optimized model increased from 0.928 to 0.985; Then, based on finite element analysis and optimization algorithm, the process parameters and structural design of the forging are optimized. According to the above volume difference formula, the process flow before optimization has huge flash, and the φ value is much less than zero; therefore, this application chooses to use φ value equal to zero as the optimization objective function, and the shape parameters of the flash, the fillet radius of the mold cavity and the shape of the pre-forging are design variables. The changes in these design variables directly change the geometric models of the mold and pre-forging. This process is achieved by calling the API function of the SolidWorks software; the changed geometric model is read into the finite element model description file (KEY file) in IGES or STL format, and the finite element preprocessor converts the KEY file into a DB file for the simulation program to call; after the simulation program is run, the calculation results are stored in the DB file; since the DB file is in binary format, it needs to be converted into the KEY file format through the preprocessor, and the specific value of the objective function is obtained through parameter extraction and calculation of the program, and a complete iterative calculation is completed. Using the Levenberg-Marquardt algorithm and the identification strategy of minimizing the objective function, the constitutive equation of 40Cr obtained after optimization is as follows: After optimization, the correlation coefficient R between the rheological stress test value and the predicted value of the optimized model increased from 0.928 to 0.985; Then, based on finite element analysis and optimization algorithms, the process parameters and structural design of the forgings are optimized. According to the above volume difference formula, the process flow before optimization has huge flash, and the φ value is much less than zero; therefore, this application chooses to use the φ value equal to zero as the optimization objective function, and the shape parameters of the flash, the fillet radius of the mold cavity, and the shape of the pre-forging as design variables. The changes in these design variables directly change the geometric model of the mold and the pre-forging. This process is achieved by calling the API function of the SolidWorks software. The changed geometric model is read into the finite element model description file (KEY file) in IGES or STL format, and the finite element preprocessor converts the KEY file into a DB file for the simulation program to call; after the simulation program is run, the calculation results are stored in the DB file. Since the DB file is in binary format, it needs to be converted into the KEY file format through the preprocessor. After the program parameters are extracted and calculated, the specific value of the objective function is obtained, and a complete iterative calculation is completed.

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