Heat-treatment-free aluminum alloy die-casting forming process optimization method

Abstract

The invention discloses a heat-treatment-free aluminum alloy die-casting forming process optimization method. The method comprises the following steps that firstly, thermophysical parameters of a heat-treatment-free aluminum alloy material used by a to-be-optimized die-casting part are obtained; 2, determining optimizable variables of the die-casting part to be optimized; 3, grouping the optimizable variables according to the influence principle similarity of the optimizable variables to the to-be-optimized die-casting part, and constructing one or more optimizable variable groups; 4, determining a corresponding reference sample group according to the optimizable variable group; and 5, screening out the optimizable variable group with the maximum influence degree as the optimal variable group according to the reference sample group, and determining the optimal process of the to-be-optimized part according to the optimal variable group and the corresponding reference sample group. The method has the advantages that the design period is shortened, and flexibility and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of aluminum alloy die-casting forming, and more specifically, the present invention relates to a method for optimizing the die-casting forming process of heat-treatable aluminum alloy. Background Art

[0002] The integrated die-casting process has become one of the disruptive technologies in the automotive industry. Compared with the traditional process, one-step forming has natural advantages in saving manufacturing costs. In 2020, Tesla first applied the integrated die-cast rear floor on the Model Y model, and in 2023, the largest integrated die-cast vehicle body in the world was applied on Huawei's Wenjie M9 model. The common problems faced by integrated die-cast parts in production applications are part deformation and surface blistering caused by heat treatment, as well as the high transportation costs of ultra-large die-cast parts.

[0003] Heat-treatable die-casting aluminum alloy is a new die-casting material developed on the basis of traditional die-casting aluminum alloy. It can directly obtain good comprehensive properties without heat treatment, effectively avoiding the adverse effects of heat treatment on part performance.

[0004] In recent years, due to the increasing requirements for the stability and aesthetics of aluminum alloy die-cast parts, there has been less research on die-cast parts with complex shapes and uneven wall thicknesses, and the forming difficulty is large. Defects such as cold shuts, misruns, and shrinkage porosity are likely to occur.

[0005] The optimized design of the die-casting forming process can greatly reduce the impact of casting defects on part quality, which is directly related to part quality, production efficiency, and cost control.

[0006] However, the optimized design of traditional aluminum alloy die-casting processes lacks the support of a unified automated tool, making it difficult to ensure the consistency and flexibility of process design, resulting in low design efficiency.

[0007] In addition, the trial-and-error method is a widely used optimization method at present, causing great waste of resources in terms of labor costs and equipment costs. Summary of the Invention

[0008] The purpose of the present invention is to design and develop a method for optimizing the die-casting forming process of heat-treatable aluminum alloy, determine the optimization direction of shrinkage porosity defects, and combine orthogonal experiments to save costs and ensure flexibility and accuracy.

[0009] The technical solution provided by the present invention is as follows: A method for optimizing the die-casting forming process of heat-treatable aluminum alloy, comprising the following steps: Step 1: Obtain the thermophysical parameters of the heat-treatable aluminum alloy material used for the die-casting part to be optimized; Step 2: Determine the optimizable variables according to the problem of reducing shrinkage porosity defects of the die-casting part to be optimized; Among them, the optimizable variables are the pouring temperature, the initial mold temperature, and the injection speed; Step 3: Group the optimizable variables according to the similarity of the influence principles of the optimizable variables on the die-casting parts to be optimized, and construct one or more optimizable variable groups; Step 4: Determine the corresponding reference sample group according to the optimizable variable group through an orthogonal experiment; Step 5: Screen out the optimizable variable group with the greatest influence degree from the reference sample group as the optimal variable group, and determine the best process of the parts to be optimized according to the optimal variable group and the corresponding reference sample group; Among them, the best process of the parts to be optimized is: The pouring temperature is 680 °C, the initial mold temperature is 200 °C, and the injection speed is 5 m / s.

[0010] Preferably, the thermophysical parameters include: density, viscosity, latent heat, liquidus, solidus, thermal conductivity, and specific heat capacity.

[0011] Preferably, the optimizable variables further include: cooling method and / or wall thickness of the casting.

[0012] Preferably, the influence principles of the initial mold temperature, pouring temperature, and injection speed are all to improve the filling ability of the molten metal and reduce the problems of shrinkage porosity and shrinkage cavity defects.

[0013] Preferably, the reference sample group is a set composed of multiple reference samples corresponding to multiple optimizable variables included in the optimizable variable group.

[0014] Preferably, the multiple reference samples corresponding to the pouring temperature include: 640 °C, 660 °C, and 680 °C.

[0015] Preferably, the multiple reference samples corresponding to the initial mold temperature include: 120 °C, 160 °C, and 200 °C.

[0016] Preferably, the multiple reference samples corresponding to the injection speed include: 1 m / s, 3 m / s, and 5 m / s.

[0017] Preferably, the influence degree of the reference sample group is determined by principal component analysis or range analysis.

[0018] Preferably, the best process of the parts to be optimized needs to meet the thermophysical parameters of the heat-treatable aluminum alloy material used.

[0019] The beneficial effects of the present invention: An optimization method for the heat - treatment - free aluminum alloy die - casting forming process designed and developed by the present invention, based on the objective analysis of the forming defect problems of the parts to be optimized, can determine the optimization direction of the die - casting forming design scheme in advance by obtaining the optimizable variables, avoiding the manpower and cost burdens caused by multiple trial - and - error and mold opening, and greatly saving the design cycle of the heat - treatment - free die - casting forming. Group the optimizable variables according to the actual defect problems, and combine with orthogonal experiments to obtain multiple groups of optimizable variables and reference sample groups. By determining the influence strength of each group of optimizable variables on the casting quality, the most optimal variable group can be determined, ensuring high flexibility and accuracy in dealing with design occasions with many influencing factors and complex processes, and having good general applicability of the process. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic flow chart of the optimization method for the heat - treatment - free aluminum alloy die - casting forming process described in the present invention.

[0021] Figure 2 It is a schematic diagram of the crankcase cover product before the optimization of the die - casting forming process in the embodiment described in the present invention.

[0022] Figure 3 It is a schematic diagram of the crankcase cover product after the optimization of the die - casting forming process in the embodiment described in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The following further describes the present invention in detail with reference to the accompanying drawings of the specification, so that those skilled in the art can implement it according to the text of the specification.

[0024] As Figure 1 shown, an optimization method for the heat - treatment - free aluminum alloy die - casting forming process provided by the present invention includes the following steps: Step 1 S1: Obtain the thermal physical properties parameters of the heat - treatment - free aluminum alloy material used for the die - casting parts to be optimized; Among them, the thermal physical properties parameters include: density, viscosity, latent heat, liquidus, solidus, thermal conductivity, and specific heat capacity; The thermal physical properties parameters can be obtained through thermodynamic calculations or relevant experimental operations; Step 2 S2: Determine the optimizable variables of the die - casting parts to be optimized; Among them, the optimizable variables refer to the key variables that directly affect the quality of the casting during the design process and die - casting forming process of the heat - treatment - free die - casting parts (such as cooling method, casting wall thickness, initial mold temperature, pouring temperature, injection speed, etc.), and can be adjusted during the die - casting forming design process of the heat - treatment - free die - casting parts. Obtaining the optimizable variables helps to determine the optimization direction of the process, reduce the number of trial - and - error and mold repair, and improve the optimization efficiency.

[0025] Step S3. Based on the similarity of the principles by which the optimizable variables affect the quality of the casting, group the optimizable variables to construct one or more groups of optimizable variables; The group of optimizable variables refers to a set of multiple optimizable variables that have a direct impact on a certain defect during the die-casting process of heat-treatable die-cast aluminum alloy. That is, each group of optimizable variables consists of multiple optimizable variables with similar principles. Among them, the defect can be all forming defects that occur during the forming process, including but not limited to shrinkage porosity, misrun, cold shut, etc.

[0026] Step S4. Obtain the reference sample group corresponding to the group of optimizable variables according to the orthogonal experiment; Among them, the reference sample group is a set composed of multiple reference samples corresponding to the multiple optimizable variables included in the group of optimizable variables. Based on the defects that occur during the forming process and the selected optimizable variables, confirm how the optimizable variables affect the forming defects and determine their influence range.

[0027] Step S5. Conduct a mathematical statistics analysis for each group of optimizable variables; Among them, the mathematical statistics analysis is used to judge the strength of the influence of the group of optimizable variables on the casting quality of the part to be optimized; Step S6. Screen out the group of optimizable variables with the strongest influence degree as the optimal variable group, and determine the best optimization design of the part to be optimized according to the optimal variable group; Among them, based on multiple optimizable variables and the corresponding reference samples, the interaction between the optimizable variables and the casting quality can be obtained. Through methods such as principal component analysis and range analysis, it can be confirmed whether there is a strong correlation between the optimizable variables and the casting quality. Similarly, the group of optimizable variables with a strong correlation with the casting quality is screened out.

[0028] The best optimization design obtained in Step S6 must meet the objective reality of the thermal physical properties parameters described in the first step. Embodiment

[0029] Optimize the die-casting process of a heat-treatable die-cast aluminum alloy crankcase cover of a certain company. The purpose of this optimization is to reduce the shrinkage porosity and shrinkage cavity defects generated during the forming process.

[0030] S1. The thermal physical properties parameters of the heat-treatable aluminum alloy material used for the part to be optimized are shown in Table 1:

[0031] S2. The optimizable variables of the part to be optimized die-cast are: Pouring temperature (T): Affects the fluidity of the alloy, the cooling rate, and the possible formation of thermal cracks; Initial mold temperature (T0 ): It affects the surface quality of the casting, the fluidity of the molten metal, and the solidification uniformity; Injection speed (V): It affects the gas evacuation inside the cavity, the fluidity of the molten metal, and the density of the casting; S3. Confirm the influencing principle: For the purpose of optimization to reduce shrinkage porosity and shrinkage cavity defects, the residual melt modulus is used as an index to measure the quality of the casting.

[0032] The pouring temperature (T) refers to the temperature when the molten metal enters the cavity from the pressure chamber for filling, and it is negatively correlated with the residual melt modulus. The principle is that a lower pouring temperature results in a lower overall temperature of the aluminum liquid, and the flow is not smooth; the initial mold temperature (T 0 ): It refers to the temperature of the mold surface in contact with the melt, and it is negatively correlated with the residual melt modulus. The principle is that a lower mold temperature causes the filling molten metal to cool rapidly, and the fluidity weakens; the injection speed (V) refers to the moving speed of the injection punch in the pressure chamber to push the molten metal, and it is negatively correlated with the residual melt modulus. The principle is that a large injection speed gives the aluminum liquid greater kinetic energy and improves the filling quality.

[0033] Construct an optimizable variable group: Based on the analysis of the influencing principle, the optimizable variables pouring temperature (T), initial mold temperature (T 0 ), and injection speed (V) all reduce the occurrence of shrinkage cavity and shrinkage porosity defects by improving the filling ability of the molten metal, and they are similar in the influencing principle. Therefore, they form an optimizable variable group.

[0034] S4. Combine with the orthogonal experiment, and the reference sample group corresponding to the optimizable variable group is shown in Table 2:

[0035] S5. Mathematical statistics analysis: Based on historical data, analyze the relationship between the parameter samples and the residual melt modulus, and use the range analysis to determine the influence of the optimizable variables on the residual melt modulus, so as to determine the size of the correlation between the optimizable variables and the casting quality. The range analysis is shown in Table 3:

[0036] Use the range analysis method to analyze the results of the simulation experiment, and compare the influence degrees of the pouring temperature, initial mold temperature, and injection speed on the residual melt modulus of the crankcase cover die-casting. As shown in Table 3, where K i1 、K i2 、K i3 (i = A, B, C) respectively represent the total of the residual melt modulus under different levels of the same factor; k i1 、k i2 、k i3(i = A, B, C) represent the average values of the residual melt modulus under different levels of the same factor, and the range represents the difference between the maximum average value and the minimum average value.

[0037] S6. According to the calculation results, the ranges of the three factors are 0.5508, 0.3301, and 0.1447 respectively. It can be inferred that the influence degrees on the residual melt modulus of the casting are: A > B > C. The above analysis shows that the order of the influence degrees on the residual melt modulus of the casting, from large to small, is pouring temperature, initial die temperature, and injection speed. Take the minimum level corresponding to the average value of the residual melt modulus in each factor as the optimal process parameter combination: A3, B3, C3 - The optimized variable combination can be pouring temperature 680°C, initial die temperature 200°C, and injection speed 5 m / s.

[0038] As Figure 2 , Figure 3 shown, it is a comparison of the crankcase cover products before and after the optimization of the die-casting forming process, and it can be seen that the defects are greatly reduced.

[0039] An optimization method for the die-casting forming process of heat-treatable aluminum alloy designed and developed by the present invention, based on the objective analysis of the forming defect problems of the parts to be optimized, can determine the optimization direction of the die-casting forming design scheme in advance by obtaining the optimizable variables, avoiding the manpower and cost burdens caused by multiple trial-and-error and mold opening, and greatly saving the design cycle of the heat-treatable die-casting forming. Group the optimizable variables according to the actual defect problems to obtain multiple optimizable variable groups and a reference sample group. By determining the influence strength of each optimizable variable group on the casting quality, the most preferred variable group can be determined, which can ensure high flexibility and accuracy in dealing with design occasions with many influencing factors and complex processes, and has good general applicability of the process.

[0040] Although the embodiments of the present invention have been disclosed as above, it is not limited to the applications listed in the specification and embodiments. It can be fully applied to various fields suitable for the present invention. For those familiar with the field, additional modifications can be easily made. Therefore, without departing from the general concept defined by the claims and the equivalent scope, the present invention is not limited to the specific details and the embodiments shown and described here.

Claims

1. A method for optimizing heat treatment-free aluminum alloy die-casting process, characterized in that: The steps include: Step 1: Obtain the thermal physical property parameters of the heat-treatment-free aluminum alloy material used for the die-casting parts to be optimized; Step 2: determining the optimizable variables according to reducing the shrinkage and shrinkage defects of the die-casting part to be optimized; Wherein, the optimizable variables are casting temperature, initial mold temperature and injection speed; Step 3: grouping the optimizable variables according to the similarity of their influence on the die-casting parts to be optimized, and constructing one or more optimizable variable groups; Step 4: Determine the corresponding reference sample group according to the optimizable variable group through orthogonal experiments; Step 5: Screen out the optimizable variable group with the greatest influence as the optimal variable group according to the reference sample group, and determine the optimal process of the part to be optimized according to the optimal variable group and the corresponding reference sample group; Among them, the optimal process of the part to be optimized is: The pouring temperature was 680°C, the initial mold temperature was 200°C, and the injection speed was 5 m / s.

2. The heat treatment-free aluminum alloy die-casting molding process optimization method according to claim 1, characterized in that: The thermophysical property parameters include: density, viscosity, latent heat, liquidus, solidus, thermal conductivity and specific heat capacity.

3. The method for optimizing the heat treatment-free aluminum alloy die-casting process as claimed in claim 2, characterized in that: The optimizable variables also include: cooling method and / or casting wall thickness.

4. The method for optimizing the die-casting process of aluminum alloy without heat treatment as claimed in claim 3, characterized in that: The influencing principles of the initial mold temperature, pouring temperature and injection speed are all to improve the metal liquid filling capacity and reduce the shrinkage and shrinkage cavity defect problems.

5. The method for optimizing the heat treatment-free aluminum alloy die-casting process as claimed in claim 4, characterized in that: The reference sample group is a set consisting of a plurality of reference samples corresponding to a plurality of optimizable variables included in the optimizable variable group.

6. The method for optimizing the heat treatment-free aluminum alloy die-casting process as claimed in claim 5, characterized in that: The plurality of reference samples corresponding to the casting temperature include: 640°C, 660°C and 680°C.

7. The method for optimizing the heat treatment-free aluminum alloy die-casting process according to claim 6, characterized in that: The multiple reference samples corresponding to the initial mold temperature include: 120°C, 160°C and 200°C.

8. The method for optimizing the heat treatment-free aluminum alloy die-casting process as claimed in claim 7, characterized in that: The multiple reference samples corresponding to the injection speed include: 1 m / s, 3 m / s and 5 m / s.

9. The method for optimizing the heat treatment-free aluminum alloy die-casting process as claimed in claim 8, characterized in that: The influence of the reference sample group is determined by principal component analysis or range analysis.

10. The heat treatment-free aluminum alloy die-casting process optimization method according to claim 9, characterized in that: The optimal process for the part to be optimized must meet the thermal physical property parameters of the heat-treatment-free aluminum alloy material used.

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