US-20260124677-A1 - MULTI-PROCESS PARAMETER OPTIMIZATION METHOD FOR LOW-PRESSURE CASTING OF ALUMINUM ALLOY WHEEL HUBS

Abstract

A multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs is disclosed, relating to the technical field of low-pressure casting of automobile wheel hubs. The method includes: building a three-dimensional model of an aluminum alloy wheel hub; setting initial production process parameters; numerically simulating a low-pressure casting process; analyzing temperature distribution in key points of a mold; adjusting the production process parameters based on temperature distribution; repeating the above steps to further optimize the production process parameters and obtain an optimal combination of process parameters; collecting and analyzing actual production data and building a model; and optimizing the process parameters by using a dynamic multi-objective particle swarm.

Inventors

• Tianxiao Yuan
• Yixin Huang
• Ji Wang
• Yiming Li
• Dan YAO
• Jiaze Xu
• Xuewen Qian
• Yajun YIN
• Shiwei Guo
• Xu Shen
• Xiaoyuan JI
• Jianxin Zhou
• Hongbiao Li
• Zexin Wu

Assignees

• CITIC DICASTAL CO., LTD.

Dates

Publication Date

20260507

Application Date

20250827

Priority Date

20241106

Claims (9)

1. 1 . A multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs, comprising: step S 1 : building a three-dimensional model of an aluminum alloy wheel hub, wherein information contained in the three-dimensional model comprises a geometric shape and a size of the aluminum alloy wheel hub; step S 2 : setting initial production process parameters, wherein the initial production process parameters comprise a quantity of cooling channels, a type of a cooling medium, and a flow rate in the cooling channels; step S 3 : numerically simulating a low-pressure casting process, wherein the low-pressure casting process is numerically simulated by using computer-aided software and inputting attributes of an aluminum alloy material, a casting temperature, and a pre-heating temperature of a mold; step S 4 : analyzing temperature distribution in key points of the mold, observing an isolated liquid phase region and temperature distribution in the aluminum alloy wheel hub based on simulated porosity defects and temperature distribution results, adjusting the initial production process parameters such as the casting temperature of the aluminum alloy wheel hub and the pre-heating temperature of the mold, and designating the process parameters for simulated aluminum alloy wheel hub castings with minimum defects for actual production; step S 5 : adjusting the production process parameters based on the temperature distribution; step S 6 : repeating steps S 3 to S 5 to further optimize the production process parameters and obtain an optimal combination of process parameters; step S 7 : collecting and analyzing actual production data and building a model; and step S 8 : optimizing the process parameters by using a dynamic multi-objective particle swarm.
2. 2 . The multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs according to claim 1 , wherein in step S 1 , the three-dimensional model is built by means of SolidWorks or UG modeling software.
3. 3 . The multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs according to claim 1 , wherein in step S 2 , structural features of the aluminum alloy wheel hub are determined by on-site production, and 17 cooling channels are set.
4. 4 . The multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs according to claim 1 , wherein in step S 2 , the type of the cooling medium is at least one of water cooling or air cooling.
5. 5 . The multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs according to claim 1 , wherein in step S 2 , the flow rate in the cooling channels is 8 to 10 L/min when a water cooling medium is used and 60 to 80 m 3 /h when an air cooling medium is used.
6. 6 . The multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs according to claim 1 , wherein in step S 5 , if the regional temperature is too high, the quantity of cooling channels is increased or the flow rate in the cooling channels is increased; if the cooling effect is poor, the cooling medium is changed, such as from air cooling to water cooling; if the temperature distribution is non-uniform, the positions of the cooling channels are adjusted or the flow allocation in the cooling channels is adjusted.
7. 7 . The multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs according to claim 1 , wherein in step S 6 , the optimal combination of process parameters has the characteristics of uniform temperature distribution in each key point of the mold, moderate temperature gradient, and high cooling efficiency.
8. 8 . The multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs according to claim 1 , wherein in step S 7 , low-pressure casting is carried out by using initially set production process parameters, wherein thermocouples are arranged at the key points of the mold to collect process parameters of equipment and temperatures of the key points of the mold during the production process; a relationship among the opening and closing time of the mold cooling channels, the flow rate in the cooling channels, and the temperatures of the key points of the mold is built by using the collected process parameters; and an LSTM time series prediction model is built based on time series characteristics of the collected parameters.
9. 9 . The multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs according to claim 1 , wherein in step S 8 , after the LSTM time series prediction model is built, the temperature of each key point of the mold for the qualified casting as a standard temperature of the key point of the mold, and the process parameters such as the initial cooling channels as initial particles, are input into the built LSTM model to obtain a predicted temperature of each key point of the mold, an absolute value of the difference between the predicted temperature of each key point and the standard temperature is designated as an objective function of the dynamic multi-objective particle swarm to seek each process parameter of the cooling channels, so as to obtain a plurality of optimized process parameters of the low-pressure casting of the aluminum alloy wheel hub.

Description

TECHNICAL FIELD The present invention relates to the technical field of low-pressure casting of automobile wheel hubs, in particular to a multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs. BACKGROUND In the low-pressure casting process of an aluminum alloy wheel hub, temperature control on a mold is one of the key factors affecting the quality of a casting. Factors, such as a quantity of cooling channels, a type of a cooling medium (water cooling or air cooling), and a flow rate in the cooling channels, have a significant impact on the temperature at key points of the mold, which further affects the internal structure and surface quality of the casting significantly. However, relevant parameters affecting mold temperature have not been effectively controlled. Therefore, the optimization of each process parameter in the low-pressure casting process is of great significance for improving the overall performance of the wheel hub casting. Therefore, in view of the problems in existing technologies, the designer of this patent, leveraging years of industry experience, conducted active research and improvement to develop a multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs in the present invention. SUMMARY The present invention aims to provide a multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs in view of the defects in existing technologies that, during low-pressure casting of an aluminum alloy wheel hub, temperature control on a mold directly affects the quality of a casting, while relevant parameters affecting mold temperature have not been effectively controlled. To achieve the objective of the present invention, the present invention provides a multi-process parameter optimization method for low-pressure casting of aluminum alloy wheel hubs, including: step S1: building a three-dimensional model of an aluminum alloy wheel hub, where information contained in the three-dimensional model includes a geometric shape and a size of the aluminum alloy wheel hub;step S2: setting initial production process parameters, where the initial production process parameters include a quantity of cooling channels, a type of a cooling medium, and a flow rate in the cooling channels;step S3: numerically simulating a low-pressure casting process, where the low-pressure casting process is numerically simulated by using computer-aided software and inputting attributes of an aluminum alloy material, a casting temperature, and a pre-heating temperature of a mold;step S4: analyzing temperature distribution in key points of the mold, observing an isolated liquid phase region and temperature distribution in the aluminum alloy wheel hub based on simulated porosity defects and temperature distribution results, adjusting the initial production process parameters such as the casting temperature of the aluminum alloy wheel hub and the pre-heating temperature of the mold, and designating the process parameters for simulated aluminum alloy wheel hub castings with minimum defects for actual production;step S5: adjusting the production process parameters based on the temperature distribution;step S6: repeating steps S3 to S5 to further optimize the production process parameters and obtain an optimal combination of process parameters;step S7: collecting and analyzing actual production data and building a model; andstep S8: optimizing the process parameters by using a dynamic multi-objective particle swarm. Optionally, in step S1, the three-dimensional model is built by means of SolidWorks or Unigraphics (UG) modeling software. Optionally, in step S2, structural features of the aluminum alloy wheel hub are determined by on-site production, and 17 cooling channels are set. Optionally, in step S2, the type of the cooling medium is at least one of water cooling or air cooling. Optionally, in step S2, the flow rate in the cooling channels is 8 to 10 L/min when a water cooling medium is used and 60 to 80 m3/h when an air cooling medium is used. Optionally, in step S5, if the regional temperature is too high, the quantity of cooling channels is increased or the flow rate in the cooling channels is increased; if the cooling effect is poor, the cooling medium is changed, such as from air cooling to water cooling; if the temperature distribution is non-uniform, the positions of the cooling channels are adjusted or the flow allocation in the cooling channels is adjusted. Optionally, in step S6, the optimal combination of process parameters has the characteristics of uniform temperature distribution in each key point of the mold, moderate temperature gradient, and high cooling efficiency. Optionally, in step S7, low-pressure casting is carried out by using initially set production process parameters, where thermocouples are arranged at the key points of the mold to collect process parameters of equipment and temperatur