The hot forging mold device for low-pressure casting includes an upper and lower mold forming a cavity, a riser cavity that supplies molten metal, and a press device positioned above the riser cavity to apply pressure. A sensor and controller can adjust pressure based on the molten metal's temperature or fill level. Cooling fluid circulates through a cylinder base plate, and an insulating plate reduces heat transfer. An ejection device, moved by an actuator, removes the solidified cast product. Guide blocks help align components, and a leakage preventing plate with a seal helps avoid fluid intrusion. The overall design ensures efficient feeding of molten metal, controlled forging pressure, and reliable ejection, improving casting quality and reducing defects.

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.

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.

Provided is a method for evaluating the stability of the cooling effect of a cooling system for low-pressure casting of an aluminum alloy wheel hub, relating to the technical field of low-pressure casting of automobile wheel hubs. The method includes: selecting a mold object; arranging a thermocouple, and acquiring temperature data; changing an initial temperature at a temperature measuring point of the thermocouple, and further acquiring real-time temperature data; extracting characteristic temperature data, and performing linear regression between an initial temperature value and a characteristic temperature value; and performing temperature data fluctuation analysis, and quantitatively measuring the stability of the cooling effect of the cooling system by using a maximum value and a minimum value of deviation of discrete points from a fitting curve as indexes.

Provided is a method for evaluating the stability of the cooling effect of a cooling system for low-pressure casting of an aluminum alloy wheel hub, relating to the technical field of low-pressure casting of automobile wheel hubs. The method includes: selecting a mold object; arranging a thermocouple, and acquiring temperature data; changing an initial temperature at a temperature measuring point of the thermocouple, and further acquiring real-time temperature data; extracting characteristic temperature data, and performing linear regression between an initial temperature value and a characteristic temperature value; and performing temperature data fluctuation analysis, and quantitatively measuring the stability of the cooling effect of the cooling system by using a maximum value and a minimum value of deviation of discrete points from a fitting curve as indexes.