A hydraulic disc brake caliper body casting process parameter control method

Abstract

This invention provides a method for controlling the casting process parameters of a hydraulic disc brake caliper, relating to the field of automotive structural component casting technology. The method includes the following steps: acquiring the three-dimensional structural feature information of the target hydraulic disc brake caliper and constructing a process field based on this information; modulating the state of the aluminum alloy melt under the constraints of the process field to form a semi-solid rheological state; adjusting the thermal inertia of the insert to match the spatial flow direction based on the semi-solid rheological state, so that the insert forms differentiated thermal response states in different interface regions; applying the semi-solid rheological state and the insert's thermal response state together within the mold cavity, and controlling the filling under the mold's thermal response constraints, so that the material flow state, interface state, and mold constraint state form a coupled evolution relationship; precisely matching the temperature at the slurry flow front to eliminate the risk of microcracks and delamination at the interface caused by excessive interface temperature differences, ensuring a high-strength metallurgical bond between the insert and the substrate.

Description

Technical Field

[0001] This invention relates to the field of automotive structural component casting technology, and more specifically, to a method for controlling the casting process parameters of a hydraulic disc brake caliper body. Background Technology

[0002] As a core component of the automotive braking system, the manufacturing quality of hydraulic disc brake calipers directly affects vehicle safety and handling performance. With the automotive industry moving towards lightweighting and high integration, aluminum alloy casting has become the mainstream technology for brake caliper manufacturing. The industry commonly employs high-pressure die casting or gravity casting processes, controlling macroscopic process parameters such as mold temperature, injection speed, and specific pressure to achieve the desired shape. In recent years, with the introduction of intelligent manufacturing technologies, some advanced casting production lines have begun to utilize sensors to monitor melt temperature or mold surface heat flow, combining this with numerical simulation technology for offline optimization of the casting process.

[0003] Modern brake caliper bodies often require the embedding of steel bushings or reinforcements. Existing technologies, when dealing with such "aluminum-steel" composite structures, often overlook the differences in thermophysical behavior between the embedding and the molten metal interface, and lack targeted adjustment of the embedding's thermal inertia. This makes the interface highly susceptible to cold shuts due to the chilling effect or microcracks caused by thermal stress concentration, severely affecting the bonding strength. Existing parameter control methods are mostly open-loop static controls, lacking a real-time perception and response mechanism for the critical state of material transition from flow to solidification. They cannot dynamically compensate based on the coupled evolution of rheological behavior and mold thermal response during the actual filling process, resulting in a narrow process window and poor product consistency when mass-producing complex brake caliper bodies.

[0004] Therefore, there is an urgent need for a method to control the casting process parameters of hydraulic disc brake caliper bodies. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention is proposed. A first aspect of this invention provides a method for controlling the casting process parameters of a hydraulic disc brake caliper body, comprising the following specific steps: acquiring three-dimensional structural feature information of the target hydraulic disc brake caliper body, and constructing a process field based on the three-dimensional structural feature information;

[0006] Under the constraints of the process field, the aluminum alloy melt is subjected to state modulation to form a semi-solid rheological state;

[0007] Based on the semi-solid rheological state, the thermal inertia of the insert is adjusted to match the direction of spatial flow, so that the insert forms a differentiated thermal response state in different interface regions.

[0008] The semi-solid rheological state and the insert thermal response state are applied together in the mold cavity, and the filling control is carried out under the constraint of the mold thermal response, so that the material flow state, interface state and mold constraint state form a coupled evolution relationship.

[0009] The coupling evolution relationship is identified by state recognition. When a critical state of material transition from continuous flow to confined solidification is detected, a solidification control strategy is triggered. Based on the control result, the process field is reversed to form an adaptive process evolution mechanism.

[0010] Preferably, the construction process field includes:

[0011] The target hydraulic disc brake caliper body is solidly modeled using 3D modeling software, and the solid model is spatially discretized using mesh generation technology, dividing the overall structure into multiple volume elements with spatial coordinate attributes.

[0012] In each of the aforementioned body units, wall thickness, cross-sectional change rate, and flow channel turning angle parameters are extracted using a geometric analytical algorithm. Based on the geometric relationship between adjacent body units, wall thickness gradient and cross-sectional shrinkage rate are calculated to form structural parameter distribution data.

[0013] Using a pre-defined flow retardation calculation model, the wall thickness gradient, cross-sectional shrinkage rate, and flow channel turning angle are used as input variables to calculate and process each body element to obtain a flow retardation coefficient that reflects the local shear rate attenuation trend. The body elements are then sorted according to the magnitude of the flow retardation coefficient.

[0014] By setting a threshold for the flow retardation coefficient, volumetric units that exceed the threshold are screened out, and spatial adjacency relationships are combined to perform regional clustering to form multiple continuously distributed retardation-sensitive regions.

[0015] For the stagnant sensitive area, a temperature-flow coupling adjustment function is constructed to apply local adjustment parameters to each area. These include increasing the set temperature of the mold temperature control node in the corresponding area to enhance the local flow capability, and increasing the initial filling driving force parameter to compensate for the loss of flow kinetic energy.

[0016] The adjustment parameters of each region are mapped to the mold temperature control system and the filling control system. By configuring the arrangement of the heating units inside the mold and the parameters of the temperature control circuit, a process field with spatial difference adjustment capability is formed.

[0017] Preferably, the semi-solid rheological state includes:

[0018] By arranging multiple temperature acquisition sensors inside the smelting equipment, the temperature of the aluminum alloy melt at different spatial locations is collected in real time, and a melt temperature distribution model is constructed by combining the spatial coordinate information of the sensors.

[0019] By utilizing the spatial correspondence of the stagnation-sensitive region in the mold cavity, the high stagnation risk region is mapped to the time interval before the melt flows into the mold, and different control stages of the melt during the stirring process are divided.

[0020] Within the different control stages, by adjusting the rotation speed parameters of the high-shear stirring device, the melt is subjected to shearing forces of different intensities within the corresponding time periods. In particular, the stirring speed is increased in the control stages corresponding to the high stagnation risk region to enhance grain breakage and homogenization.

[0021] During the stirring process, a solid fraction calculation model based on temperature and shear rate is introduced to dynamically calculate the generation rate and growth trend of solid particles in the melt, and the calculation results are compared with the preset solid fraction growth rate threshold.

[0022] When the calculation results at a certain stage indicate that the solid fraction growth rate exceeds the threshold, the stage melt is regulated by reducing the local cooling rate to increase the shear strength.

[0023] Through a multi-stage shear regulation and solid fraction control process, the aluminum alloy melt forms a semi-solid rheological state with spatially corresponding regulation characteristics before entering the mold cavity, thereby reducing flow stagnation and local premature solidification in the stagnant sensitive area during the filling process.

[0024] Preferably, the thermal inertia adjustment includes:

[0025] By spatially analyzing the filling path of the semi-solid rheological state in the mold cavity and combining it with the positional relationship of the insert in the cavity, the temporal distribution of the contact between the melt flow front and the insert is determined.

[0026] Based on the time sequence distribution, by adjusting the heating power and zoning arrangement of the insert preheating device, differentiated preheating treatment is applied to different areas of the insert. At the same time, by adjusting the temperature control node parameters of the corresponding area of ​​the mold, the local thermal boundary conditions are synchronously adjusted so that the interface temperature state of the insert matches the semi-solid flow state, thereby reducing the interface temperature difference impact and maintaining the local flow continuity.

[0027] Preferably, the coupling evolution relationship includes:

[0028] By setting up multiple independent cooling circuits inside the mold and equipping each cooling circuit with an adjustable flow control unit, the cooling intensity of different areas of the mold cavity can be dynamically adjusted during the filling process.

[0029] By using temperature acquisition units deployed on the surface of the mold cavity, the heat distribution state inside the cavity is monitored in real time, and the acquired temperature data is input into the control system for processing;

[0030] Based on the temperature data, by adjusting the flow parameters and flow direction of each cooling circuit, the heat dissipation rate of the local area is coordinated with the advance speed of the melt flow front, thereby controlling the solidification interface to advance smoothly along the preset direction and reducing flow interruption.

[0031] Preferably, the filling control includes:

[0032] By deploying temperature monitoring units inside the mold and on the surface of the cavity, the thermal response state of the mold is collected in real time, forming state data that reflects the temperature gradient distribution.

[0033] Based on the aforementioned state data, by dynamically adjusting the flow distribution and flow path of each loop in the cooling system, the heat exchange capacity of different regions is matched with the local solidification demand, thereby constructing stable thermal boundary conditions.

[0034] During the regulation process, flow rate increases or decreases or flow direction switching are implemented in areas with abnormal local temperatures to suppress solidification imbalance caused by uneven heating.

[0035] Preferably, the reverse correction includes:

[0036] The status signals during the filling and solidification process are collected by an online detection device, and the status signals are processed to extract characteristic parameters reflecting changes in internal density.

[0037] Based on the aforementioned characteristic parameters, the process of the melt transitioning from a flowing state to a solidified state is identified through a state determination model, and corresponding adjustment commands are generated when a localized region is detected to exhibit flow restriction or abnormal solidification trends.

[0038] According to the adjustment instructions, the solidification rate and shrinkage compensation capacity of the local area are intervened by adjusting the holding pressure, action time and mold temperature control parameters. After the filling cycle is completed, the detection data and process parameters are compared and analyzed. The process field parameters are corrected by feedback algorithm to achieve adaptive optimization of the subsequent process.

[0039] Preferably, the adaptive optimization includes:

[0040] Based on the adjustment results of the filling and solidification stages, a correlation analysis was conducted on the effects of each process parameter in the corresponding stage to establish a mapping relationship between process parameter changes and forming quality response.

[0041] Based on the mapping relationship, the deviation generated under the current process conditions is quantitatively evaluated, and the corresponding parameter correction amount is generated through the constructed feedback correction model.

[0042] The parameter correction is applied to the process parameter settings in subsequent production cycles to coordinate the adjustment of filling speed, pressure holding strategy and mold temperature control conditions, so as to gradually approach the target forming state and achieve adaptive optimization of the process.

[0043] Preferably, by comprehensively analyzing historical process data and current process setting parameters, a predictive model is constructed to characterize the semi-solid flow behavior and solidification evolution trend, and the filling path, flow velocity distribution and solidification initiation region are predicted based on the predictive model.

[0044] Based on the predicted results, the preheating state of the insert, the local temperature control parameters of the mold, and the initial distribution scheme of the cooling circuit are preset and adjusted before the filling process begins.

[0045] During the filling and solidification process, the real-time collected status data is compared with the predicted results. When the deviation exceeds the set threshold, the injection speed curve, cooling intensity distribution and pressure holding parameters are dynamically corrected so that the actual process converges to the predicted optimization path.

[0046] A second aspect of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that: when the processor executes the computer program, it implements the steps of the above-described method for controlling the casting process parameters of a hydraulic disc brake caliper.

[0047] Compared with existing technologies, the hydraulic disc brake caliper casting process parameter control method provided by this invention modulates the state of the aluminum alloy melt under process field constraints to form a semi-solid rheological state. It utilizes the thixotropic properties of the slurry's "shear thinning" to achieve stable laminar flow filling, significantly reducing air entrapment and oxide inclusions from the source. Furthermore, it significantly reduces internal shrinkage defects by utilizing its low solidification shrinkage rate, thereby improving the density of the casting. By adjusting the thermal inertia of the insert based on the semi-solid rheological state to match the spatial flow direction, it achieves differentiated thermal response in the interface region of the insert, accurately matches the temperature of the slurry flow front, eliminates the risk of microcracks and delamination at the interface caused by excessive interface temperature difference, and ensures a high-strength metallurgical bond between the insert and the matrix. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the drawings without creative effort. In the drawings:

[0049] Figure 1This is a flowchart of a method for controlling the casting process parameters of a hydraulic disc brake caliper body according to an embodiment of the present invention. Detailed Implementation

[0050] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0051] As mentioned in the background section, ignoring the differences in thermophysical behavior at the interface between the insert and the melt, and lacking targeted adjustment of the insert's thermal inertia, makes the interface prone to cold shuts due to the chilling effect or microcracks caused by thermal stress concentration, which seriously affects the bonding strength. Existing parameter control methods are mostly open-loop static control, lacking a real-time perception and response mechanism for the critical state of material transition from flow to solidification. They cannot dynamically compensate based on the coupled evolution of rheological behavior and mold thermal response during the actual filling process, resulting in a narrow process window and poor product consistency when mass-producing complex clamp structures.

[0052] Therefore, there is an urgent need for a method to control the casting process parameters of hydraulic disc brake caliper bodies.

[0053] Figure 1 A flowchart of a method for controlling the casting process parameters of a hydraulic disc brake caliper body according to an embodiment of the present invention is provided, including the following specific steps:

[0054] S1: Obtain the three-dimensional structural feature information of the target hydraulic disc brake caliper and construct the process field based on the three-dimensional structural feature information.

[0055] In step S1, the target hydraulic disc brake caliper is modeled using 3D modeling software, and the solid model is spatially discretized using mesh generation technology, dividing the overall structure into multiple solid elements with spatial coordinate attributes.

[0056] In each body element, the wall thickness, cross-sectional change rate, and flow channel turning angle parameters are extracted using a geometric analytical algorithm. Based on the geometric relationship between adjacent body elements, the wall thickness gradient and cross-sectional shrinkage rate are calculated to form structural parameter distribution data.

[0057] Using a pre-defined flow retardation calculation model, wall thickness gradient, cross-sectional shrinkage rate, and flow channel turning angle are used as input variables to calculate and process each body element to obtain the flow retardation coefficient that reflects the local shear rate attenuation trend, and the body elements are sorted according to the magnitude of the flow retardation coefficient.

[0058] By setting a threshold for the flow retardation coefficient, volumetric units that exceed the threshold are screened out, and spatial adjacency relationships are combined to perform regional clustering to form multiple continuously distributed retardation-sensitive regions.

[0059] For the stagnant flow sensitive area, a temperature-flow coupling regulation function is constructed to apply local regulation parameters to each area. These include increasing the set temperature of the mold temperature control node in the corresponding area to enhance the local flow capability, and increasing the initial filling driving force parameter to compensate for the loss of flow kinetic energy.

[0060] The adjustment parameters of each region are mapped to the mold temperature control system and the filling control system. By configuring the arrangement of the heating units inside the mold and the parameters of the temperature control circuit, a process field with spatial difference adjustment capability is formed.

[0061] Furthermore, in the process of constructing the process field, the traditional experience-based analysis of filling difficulty is transformed into a calculable and quantifiable analysis based on structural parameters. This enables the prediction and active control of flow behavior in complex structural regions. Hydraulic disc brake calipers typically have structural features such as multi-branch flow channels, uneven wall thickness, and frequent cross-sectional changes. During the filling process, they are prone to local flow deceleration, shear rate attenuation, or even flow stagnation, which can lead to defects such as cold shuts, porosity, or incomplete filling. Therefore, we need to consider how to reflect the flow resistance distribution through geometric information.

[0062] Furthermore, considering that abrupt changes in the local wall thickness of the hydraulic disc brake caliper can lead to changes in melt flow velocity and a decrease in local shear rate, the wall thickness difference between adjacent body elements is used as a fundamental term reflecting the degree of structural abruptness. Simultaneously, the spatial distance between two body elements is used as a normalization scale term to avoid judgment bias caused by absolute wall thickness difference alone. The ratio of the wall thickness difference to the spatial distance is used as a wall thickness gradient evaluation term to characterize the impact of local wall thickness changes on melt flow resistance. For the first... Individual unit, wall thickness gradient The expression is:

[0063] ;

[0064] in, Indicates the first The wall thickness of the individual unit, Indicates the relationship with the first The wall thickness value of the j-th adjacent individual unit. Indicates the first Individual unit and the first The spatial distance between the center points of individual units characterizes the influence of wall thickness variations in adjacent regions on melt flow resistance.

[0065] Furthermore, considering that the melt undergoes flow area compression when moving from a large cross-section region to a small cross-section region, resulting in increased flow resistance and local pressure loss, the equivalent flow cross-sectional area before the melt enters the volume element is used as a baseline term. The difference between the entry cross-sectional area and the exit cross-sectional area is used as a cross-sectional shrinkage variation term, and the ratio of these two terms characterizes the intensity of the cross-sectional shrinkage variation. This cross-sectional shrinkage variation is transformed into a dimensionless cross-sectional shrinkage rate evaluation term to reflect the impact of local cross-sectional changes on the continuity of mold filling. Section shrinkage rate of individual unit The expression is:

[0066] ;

[0067] in, Indicates that the melt enters the first The equivalent flow cross-sectional area in front of the individual unit. Indicates that the melt leaves the first The equivalent flow cross-sectional area after the individual unit, when A larger value indicates a more pronounced contraction of the cross-section, resulting in greater velocity and pressure losses during melt flow.

[0068] Wall thickness gradient is selected to characterize the effect of flow cross-section change on flow velocity, cross-sectional contraction rate is selected to characterize flow compression effect, and flow channel turning angle is selected to reflect energy loss caused by abrupt change in flow direction. These parameters together constitute the core factors affecting melt flowability. By meshing the three-dimensional model, each solid element has independent spatial coordinates and geometric properties. Then, gradient changes are calculated through the relationship between adjacent elements, thus forming a continuously distributed structural parameter field.

[0069] By mapping multidimensional structural parameters to a single evaluation index—the flow retardation coefficient—which reflects the flow attenuation trend of the melt in a local region, potential retardation-sensitive areas can be identified by sorting all volume units and setting thresholds for screening. Spatial clustering algorithms are then used to integrate discrete high-risk units into continuous regions to avoid errors caused by isolated local judgments.

[0070] Furthermore, considering that wall thickness gradient, cross-sectional area contraction rate, and flow channel inflection angle are structural parameters with different dimensions and value ranges, directly involving them in the coupled calculation could easily lead to one parameter excessively dominating the calculation results due to its large numerical scale. Therefore, before calculating the flow hindrance coefficient, all structural parameters are first processed to be dimensionless, transforming different parameters into a unified evaluation range. The current, minimum, and maximum values ​​of each parameter are standardized and used as the basic input for subsequent multi-factor coupled calculations. The wall thickness gradient, cross-sectional area contraction rate, and flow channel inflection angle are normalized to obtain normalized wall thickness gradient, normalized cross-sectional area contraction rate, and normalized flow channel inflection angle. The normalized expressions are:

[0071] ;

[0072] in, Indicates the parameter to be normalized. This represents the minimum value of the parameter across all volume elements. This represents the maximum value of the parameter across all volume elements.

[0073] Furthermore, considering that local flow hindrance is not determined by a single structural factor, but rather by the combined effects of abrupt changes in wall thickness, cross-sectional contraction, and abrupt changes in flow direction, the normalized wall thickness gradient is used as the influence term for wall thickness variation, the normalized cross-sectional contraction rate as the influence term for cross-sectional compression, and the normalized flow channel turning angle as the influence term for abrupt changes in flow direction. Each is assigned a weighting coefficient, and by performing a weighted coupling calculation on these three influence terms, the characteristic of the first... The flow resistance coefficient, representing the overall flow difficulty of an individual unit, is the first... Flow resistance coefficient of individual unit The expression is:

[0074] ;

[0075] Wherein, α, β, and γ represent the weighting coefficients corresponding to the wall thickness gradient, cross-sectional shrinkage rate, and flow channel turning angle, respectively, and satisfy α+β+γ=1, which can unify multiple structural influencing factors into flow hindrance evaluation indicators.

[0076] Furthermore, considering that insufficient flow in stagnant-sensitive areas typically manifests as a high flow resistance coefficient and an actual flow velocity lower than the target flow velocity, the difference between the region's average flow resistance coefficient and the threshold is used as a structural risk deviation term, and the difference between the target flow velocity and the predicted flow velocity is used as a flow capacity deviation term. These two types of deviations are coupled to determine the required mold temperature compensation for the region, ensuring that the temperature compensation reflects both the inherent structural resistance and the degree of insufficient actual flow velocity. For the first... In a flow-sensitive area, the local mold temperature compensation amount The expression is:

[0077] ;

[0078] in, Indicates the first The average value of the flow retardation coefficient of each volume element in the flow-sensitive region. This represents the threshold value for the flow retardation coefficient. Indicates the preset target flow velocity. Indicates the first Predicted flow velocity in stagnant-sensitive areas , This is the temperature compensation coefficient.

[0079] Furthermore, considering that simply increasing the mold temperature cannot fully compensate for the kinetic energy loss in complex structural areas, especially in areas with sudden cross-sectional contraction or significant flow channel turning points, it is also necessary to compensate for the filling pressure or injection speed. The average flow resistance coefficient of the area is used as the comprehensive resistance term, the average cross-sectional shrinkage rate as the compression loss term, and the average flow channel turning angle as the directional loss term. The filling driving force compensation is then calculated through weighted linkage, enabling the filling system to output differentiated driving force adjustment commands for different flow-sensitive areas. Compensation amount of filling driving force in each stagnant sensitive area The expression is:

[0080] ;

[0081] in, Indicates the first Average cross-sectional shrinkage rate of each flow-sensitive region Indicates the first The average channel turning angle of each flow-sensitive region , , The driving force compensation coefficient is determined based on the degree of flow difficulty in the region, and the corresponding filling pressure or injection speed compensation amount is determined accordingly.

[0082] Furthermore, considering that the temperature compensation and driving force compensation parameters calculated above first exist in the three-dimensional digital model or process field model and cannot be directly executed by the mold temperature control system and filling control system, it is necessary to establish a mapping relationship between virtual process field parameters and actual control nodes. The adjustment parameters of each flow-sensitive area are combined into a process field parameter vector, and the spatial correspondence between the mold temperature control node, heating unit, and filling control unit is constructed into a spatial mapping matrix. Through matrix mapping, the virtual parameters are converted into control commands executable by the actual equipment. The expression for the mapping relationship between virtual process field parameters and actual temperature control nodes is as follows:

[0083] ;

[0084] in, This represents a vector of process field parameters composed of the adjustment parameters of each flow-sensitive region. Represents the spatial mapping matrix, This represents the control command vector output to the mold temperature control system and filling control system. Through mapping, the regional adjustment parameters in the three-dimensional model are converted into temperature, pressure and speed control commands that can be executed by the actual equipment.

[0085] Considering increasing the local temperature of the mold to reduce the viscosity of the melt, and at the same time compensating for the loss of kinetic energy by increasing the initial driving force of filling, the stagnant area can gain additional flow capacity. Spatially differentiated control can be achieved by adjusting the power of the heating unit, the distribution of the temperature control circuit, and the injection speed curve. Ultimately, a process field with regional response capability can be formed to realize the control mechanism of "defect pre-identification - local reinforcement compensation", thereby reducing the risk of uneven filling and flow interruption from the source.

[0086] S2: Under the constraints of the process field, the aluminum alloy melt is modulated to form a semi-solid rheological state.

[0087] In step S2, multiple temperature acquisition sensors are arranged inside the melting equipment to collect the temperature of the aluminum alloy melt at different spatial locations in real time, and a melt temperature distribution model is constructed by combining the spatial coordinate information of the sensors.

[0088] By utilizing the spatial correspondence between the stagnation-sensitive areas and the mold cavity, high stagnation risk areas are mapped to the time interval before the melt flows into the mold, and different control stages of the melt during the stirring process are divided.

[0089] In different control stages, by adjusting the rotation speed parameters of the high-shear stirring device, the melt is subjected to shearing forces of different intensities within the corresponding time period. In particular, in the control stage corresponding to the high stagnation risk region, the stirring speed is increased to enhance the degree of grain breakage and homogenization.

[0090] During the stirring process, a solid fraction calculation model based on temperature and shear rate is introduced to dynamically calculate the generation rate and growth trend of solid particles in the melt, and the calculation results are compared with the preset solid fraction growth rate threshold.

[0091] When the calculation results of a certain stage show that the solid fraction growth rate exceeds the threshold, the stage melt is regulated by reducing the local cooling rate to increase the shear strength.

[0092] Through a multi-stage shear regulation and solid fraction control process, the aluminum alloy melt forms a semi-solid rheological state with spatially corresponding regulation characteristics before entering the mold cavity, thereby reducing flow stagnation and local premature solidification in the stagnant sensitive area during the filling process.

[0093] Furthermore, when modulating the semi-solid rheological state of aluminum alloy melt, the flow problem in the mold space is transformed into a time control problem in the melt preparation stage, realizing the pre-directional optimization of flow properties. Considering that the rheological properties of semi-solid metals are highly dependent on the solid fraction and grain morphology, when the solid particles are spherical and uniformly distributed, the melt has low apparent viscosity and good flowability. However, an unreasonable solidification process will lead to the formation of dendrite structure and increase flow resistance.

[0094] Furthermore, considering that the temperature of the molten aluminum alloy within the smelting equipment is not completely uniform, and that a single-point temperature cannot accurately reflect the overall thermal state of the melt, the detection values ​​from multiple temperature acquisition sensors are used as discrete temperature inputs. Simultaneously, considering that different sensors have different distances from the spatial location to be calculated, and thus contribute differently to the location temperature estimation, a spatial weighting coefficient is introduced to weight and fuse the temperature values ​​from each sensor, thereby obtaining the spatial location temperature. In Continuous temperature estimates at any given time, and the spatial location of the melt. Temperature at the location The expression is:

[0095] ;

[0096] in, Indicates the first A temperature acquisition sensor in Temperature values ​​collected at all times Indicates the first Each sensor relative to spatial position The weighting coefficients.

[0097] Considering that the closer the sensor is to the location to be calculated, the more accurately it reflects the true thermal state of that location, therefore, the sensor is placed in relation to the spatial location. The distance between them is used as a weight attenuation term, and the weight coefficient is determined using the reciprocal of the distance. To avoid the denominator being zero when the sensor coordinates coincide with the location to be calculated, a correction constant is added to the distance term. This ensures the stability of the weight calculation process. The expression is:

[0098] ;

[0099] in, Indicates the first The spatial coordinates of each sensor To prevent the correction constant from being zero in the denominator, a continuous melt temperature distribution model can be constructed based on multi-point temperature data.

[0100] Furthermore, considering that the flow-sensitive areas are located at different spatial positions within the mold cavity, the arrival time of the melt in each area varies. Since semi-solid rheological modulation needs to be completed before the melt enters the corresponding area, it is necessary to convert the spatial positional relationship into a time-controlled relationship, adjusting the melt inlet time to the designated area. The equivalent flow path length of each stagnant sensitive region is used as the path term, and the equivalent average flow velocity during the filling process is used as the velocity term. The time for the melt to reach the region is determined by the ratio of the path length to the velocity. Melt arrival time corresponding to each stagnation-sensitive region The expression is:

[0101] ;

[0102] in, Indicates the melt inlet to the first The equivalent flow path length at the center of each flow-sensitive region It represents the equivalent average flow velocity during the filling process.

[0103] Furthermore, considering that the injection velocity during actual die casting filling is usually not a constant value but varies in stages with time, calculating the arrival time using only the average velocity may have errors. To improve the accuracy of time mapping, the integral of the instantaneous flow velocity over time is used as the cumulative flow distance. When the cumulative flow distance reaches the equivalent path length from the melt inlet to the stagnation-sensitive area, the time node for the melt to reach the region is determined. When considering the variation of filling velocity with time, the melt arrival time... The expression is:

[0104] ;

[0105] in, express The instantaneous flow velocity at any given moment transforms the spatial stagnant region within the mold cavity into a time-controlled interval for the melt preparation stage.

[0106] Furthermore, considering the different levels and durations of stagnation risk corresponding to different control stages, it is difficult to achieve a rheological state of the melt that matches the target region if a fixed stirring speed is used. Therefore, the base stirring speed is used as a benchmark, the average flow resistance coefficient of the region corresponding to the current stage is used as a risk enhancement term, and the duration of the current stage is used as a settling time term. The target stirring speed is calculated by linking these three factors, ensuring that the stage corresponding to the high-resistance region receives stronger shearing action, while the stage corresponding to the low-resistance region maintains lower shear strength. The target stirring speed for each control stage The expression is:

[0107] ;

[0108] in, Indicates the basic stirring speed. Indicates the first The average flow resistance coefficient of the flow-sensitive region corresponding to each control stage. Indicates the duration of the control phase. , This is the speed adjustment coefficient.

[0109] Furthermore, considering that the rotational speed of a high-shear stirring device cannot be directly equated with the actual shear strength borne by the melt, the influence of the stirring impeller size, stirring gap, and stirring structure form also needs to be considered. The target stirring speed is taken as the power input term, the equivalent diameter of the stirring impeller as the shear effect amplification term, and the equivalent gap between the stirring impeller and the inner wall of the container as the shear effect constraint term. A stirring structure correction coefficient is also introduced to calculate the... Equivalent shear rate in each control stage, equivalent shear rate in high-shear mixing process. The expression is:

[0110] ;

[0111] in, This represents the correction factor for the stirring structure. Indicates the first Stirring speed during each control stage This indicates the equivalent diameter of the agitator. This represents the equivalent gap between the stirring paddle and the inner wall of the melt container, converting the stirring speed into the actual shear strength that the melt can withstand.

[0112] Furthermore, considering that the formation of the semi-solid rheological state depends on the melt temperature's position between the liquidus and solidus temperatures, the solid content is lower when the melt temperature is close to the liquidus and increases when the melt temperature is close to the solidus. The difference between the liquidus temperature and the current melt temperature is used as the solidification driving force term, and the difference between the liquidus temperature and the solidus temperature is used as the solidification temperature range scale term. An alloy solidification characteristic correction index is also introduced to calculate the solid fraction of the melt at the current temperature. The expression is:

[0113] ;

[0114] in, This indicates the liquidus temperature of the aluminum alloy melt. This indicates the solidus temperature of the aluminum alloy melt. express At all times, the melt temperature This indicates the correction index for the solidification properties of the alloy.

[0115] Furthermore, considering that high shear can break dendrites, inhibit solid particle agglomeration, and improve the spheroidization of solid particles, thus maintaining better fluidity of the melt at the same solid fraction, it is necessary to perform shear correction on the solid fraction obtained solely from temperature calculations. The solid fraction obtained under temperature control is used as the basic solid fraction term, and the equivalent shear rate is used as the microstructure refinement term. A shear correction coefficient is introduced to reduce the negative impact of dendrite growth and agglomeration on fluidity through denominator correction, resulting in the corrected effective solid fraction. Considering the influence of shear on the morphology and growth of solid particles, the solid fraction is further corrected. The corrected solid fraction... The expression is:

[0116] ;

[0117] in, express The equivalent shear rate at time t. This represents the shear correction factor, used to characterize the inhibitory effect of shearing on dendrite growth and agglomeration.

[0118] Furthermore, considering that observing the solid fraction at a single moment is insufficient to determine whether the melt has a tendency to solidify prematurely, it is also necessary to pay attention to the rate of increase of the solid fraction over time. When the solid fraction increases too rapidly, even if the current solid fraction has not exceeded the target range, a rapid decrease in fluidity may occur before entering the mold cavity. The derivative of the corrected solid fraction with respect to time is used as the evaluation term for the solid fraction growth rate, which is used to characterize the rate of change of the melt's solidification trend. The expression is:

[0119] ;

[0120] Furthermore, considering the different allowable solid phase growth rates for different aluminum alloy materials and different target semi-solid regions, a pre-set solid phase fraction growth rate threshold is used as an anomaly judgment benchmark. When the real-time calculated solid phase fraction growth rate reaches or exceeds the threshold, it indicates that the current stage of melt solid phase formation is too fast, posing a risk of premature solidification or rapid decrease in fluidity. Therefore, subsequent shear enhancement and cooling slowdown adjustments are triggered. If the following formula is satisfied, it is determined that there is a tendency for premature solidification in the current stage:

[0121] ;

[0122] in, This indicates the preset solid fraction growth rate threshold. It can be set according to the aluminum alloy material grade and the target solid fraction.

[0123] Furthermore, considering that the stirring speed correction should simultaneously respond to the melt's own solidification trend and the degree of flow resistance in the target region, the portion of the solid fraction growth rate exceeding the threshold is taken as a solidification anomaly deviation term, and the portion of the flow resistance coefficient in the corresponding region at the current stage exceeding the threshold is taken as a structural risk deviation term. These two are then weighted and coupled for calculation. The resulting stirring speed correction can improve shear strength when the melt solidifies too quickly and the corresponding region has high flow resistance, thereby enhancing grain breakage and flow retention capabilities. At that time, the correction amount of the stirring speed in the current control stage The expression is:

[0124] ;

[0125] in, This represents the correction factor for the solid-phase growth rate. This represents the flow retardation correction factor. This represents the average flow resistance coefficient of the region corresponding to the current control phase. This represents the threshold value for the flow retardation coefficient.

[0126] Furthermore, considering that excessively rapid solid fraction growth is usually related to excessive cooling intensity or excessive heat dissipation, when the solid fraction growth rate is detected to exceed a threshold, a reverse correction of the cooling rate is required. The difference between the solid fraction growth rate and the threshold is used as a cooling anomaly deviation term, and the cooling rate correction amount is calculated using a negative coefficient. The larger the deviation, the more significant the reduction in cooling rate, thereby slowing down the solid fraction formation rate. The expression is:

[0127] ;

[0128] in, This represents the cooling rate correction factor. The negative sign indicates that when the solid fraction increases too quickly, the cooling rate is reduced to ensure that the melt maintains a suitable solid fraction and low flow resistance before entering the mold cavity.

[0129] Furthermore, considering that whether the semi-solid rheological state meets the requirements for entering the mold cavity cannot be judged solely by the solid fraction, it is also necessary to comprehensively consider the degree of flow resistance in the corresponding melt region, the degree of spheroidization of solid particles, and the deviation between the actual solid fraction and the target solid fraction. The inverse vector of the region-average flow resistance coefficient is used as the flow capacity term, the degree of spheroidization of solid particles is used as the microstructure term, and the inverse vector of the deviation between the corrected solid fraction and the target solid fraction is used as the solid-liquidity term. These are then weighted and coupled to form a semi-solid rheological state evaluation index. The expression is:

[0130] ;

[0131] in, This represents the average flow resistance coefficient for the corresponding region. This represents the evaluation value for the spheroidization degree of solid particles. This indicates the corrected solid fraction. Indicates the target solid fraction. , , To evaluate the weighting coefficients, and .

[0132] Furthermore, considering that the semi-solid rheological state evaluation index reflects the comprehensive result of melt fluidity, microstructure, and solid fraction matching, it is necessary to set a state threshold as the criterion for judging whether the melt meets the conditions for entering the mold cavity. When the threshold is reached or exceeded, it indicates that the melt simultaneously meets the requirements of low flow resistance, good particle spheroidization, and suitable solid fraction at the current stage, and can be judged to have the semi-solid rheological state to enter the mold cavity and complete stable filling. When it is greater than the preset state threshold, it is judged that the aluminum alloy melt meets the semi-solid rheological state requirements for entering the mold cavity, which is used to comprehensively evaluate the melt fluidity, microstructure, and solid fraction deviation.

[0133] Furthermore, by establishing a mapping relationship between the stagnation-sensitive region and the filling time series, spatial risk regions are mapped to the time interval before the melt enters the mold. In specific implementation, the time nodes when the melt arrives at each region can be determined through filling simulation or path prediction methods, and the stirring control stage can be divided accordingly. By adjusting the stirring speed to change the shear rate, the melt in the corresponding high-risk region undergoes stronger shearing before entering the mold, thereby promoting grain breakage and spheroidization and improving flowability. At the same time, a solid fraction dynamic calculation model is introduced, with input variables including the temperature change rate and shear rate. The solid phase formation trend is evaluated in real time through the solid fraction dynamic calculation model.

[0134] Furthermore, when the solid fraction growth rate is detected to exceed the preset threshold, it indicates that there is a risk of premature solidification in a local area. At this time, intervention is carried out by reducing the cooling intensity or increasing the shear rate to make the structure tend to stabilize again. This is achieved through multi-stage cycles, so that the melt forms a semi-solid state that matches the flow requirements of the mold before entering the cavity, reducing flow resistance in key areas and improving the integrity of filling.

[0135] S3: Based on the semi-solid rheological state, the thermal inertia of the insert is adjusted to match the direction of spatial flow, so that the insert forms a differentiated thermal response state in different interface regions.

[0136] In step S3, the spatial analysis of the filling path of the semi-solid rheological state in the mold cavity is performed, and the temporal distribution of the contact between the melt flow front and the insert is determined by combining the positional relationship of the insert in the cavity.

[0137] Based on the time-series distribution, by adjusting the heating power and zoning arrangement of the insert preheating device, differentiated preheating treatment is applied to different areas of the insert. At the same time, by adjusting the temperature control node parameters of the corresponding area of ​​the mold, the local thermal boundary conditions are synchronously adjusted so that the interface temperature state of the insert matches the semi-solid flow state, thereby reducing the interface temperature difference impact and maintaining the local flow continuity.

[0138] Furthermore, in step S3, when adjusting the thermal inertia of the insert, in order to solve the problem of rapid cooling of the interface between the insert and the semi-solid melt due to the difference in heat capacity, the insert is usually made of a material with high thermal conductivity or high heat capacity. When the temperature is low, it will quickly absorb the heat of the melt, causing the local melt to solidify prematurely, thereby destroying the flow continuity.

[0139] Furthermore, the flow path and time distribution of the melt in the cavity are analyzed. The sequence and time difference of the contact between the melt front and the insert are determined by simulation or path analysis. The surface of the insert is divided into multiple regions, and different preheating temperatures are set for each region according to the arrival time of the melt, so as to form a temperature gradient that matches the flow sequence.

[0140] Furthermore, the insert is preheated using zoned electric heating, induction heating, or hot air circulation. At the same time, the mold temperature control system is used to assist in the adjustment of the area near the interface, so that the interface temperature is kept within a range that is conducive to flow. Through "time-sequence matching + zone temperature control", the thermal shock of the interface is reduced, and local solidification is prevented from occurring prematurely, thereby improving the interface bonding quality and overall forming stability.

[0141] S4: The semi-solid rheological state and the insert thermal response state are applied together in the mold cavity, and the filling control is carried out under the constraint of the mold thermal response, so that the material flow state, interface state and mold constraint state form a coupled evolution relationship.

[0142] In step S4, by setting multiple independent cooling circuits inside the mold and configuring an adjustable flow control unit for each cooling circuit, the cooling intensity of different areas of the mold cavity is dynamically adjusted during the filling process.

[0143] By using temperature acquisition units deployed on the surface of the mold cavity, the heat distribution state inside the cavity is monitored in real time, and the acquired temperature data is input into the control system for processing;

[0144] Based on temperature data, by adjusting the flow parameters and flow direction of each cooling circuit, the heat dissipation rate of the local area is coordinated with the advance speed of the melt flow front, thereby controlling the solidification interface to advance smoothly along the preset direction and reducing flow interruption.

[0145] By deploying temperature monitoring units inside the mold and on the surface of the cavity, the thermal response state of the mold is collected in real time, forming state data that reflects the temperature gradient distribution.

[0146] Based on state data, by dynamically adjusting the flow distribution and flow path of each loop in the cooling system, the heat exchange capacity of different areas is matched with the local solidification demand, thus constructing stable thermal boundary conditions.

[0147] During the regulation process, flow rate increases or decreases or flow direction switching are implemented in areas with abnormal local temperatures to suppress solidification imbalance caused by uneven heating.

[0148] Furthermore, when performing coordinated control of filling and solidification, a dynamic matching relationship is established between melt flow behavior and mold heat dissipation behavior, so that the solidification interface advancement process is controllable and stable. Since the cooling conditions of different areas of the mold are different, if the heat dissipation is too fast, the flow will terminate prematurely, and if the heat dissipation is too slow, heat accumulation and coarsening of the structure may occur. Therefore, the cooling process needs to be finely adjusted.

[0149] Furthermore, by setting up multiple independent cooling circuits, different areas can be independently adjusted, and the cooling intensity can be continuously adjusted through flow control valves. At the same time, temperature sensors are deployed to collect the surface temperature data of the cavity in real time, and the data is input into the control system for analysis.

[0150] Furthermore, taking the melt flow front position as a reference, the cooling intensity is appropriately reduced in areas that have not yet been reached to maintain a higher temperature to ensure flow; the cooling intensity is increased in filled areas to accelerate solidification and form a stable support structure. At the same time, abnormal areas, such as localized overcooled or overheated areas, are identified through temperature gradient analysis and quickly corrected by adjusting the cooling flow rate or changing the flow direction.

[0151] Furthermore, by dynamically estimating the position of the solidification interface, cooling regulation is always carried out around the interface, thereby achieving directional solidification control, avoiding solidification imbalance, improving microstructure uniformity, and reducing the generation of shrinkage cavities and cracks.

[0152] S5: State identification of the coupling evolution relationship, triggering solidification control strategy when the critical state of material transitioning from continuous flow to confined solidification is detected, and reverse correction of the process field based on the control result to form an adaptive process evolution mechanism.

[0153] In step S5, the state signals during the filling and solidification process are collected by an online detection device, and the state signals are processed to extract characteristic parameters reflecting changes in internal density.

[0154] Based on characteristic parameters, the process of melt transitioning from a flowing state to a solidified state is identified through a state determination model, and corresponding adjustment commands are generated when flow restriction or abnormal solidification trends are detected in local areas.

[0155] According to the adjustment instructions, the solidification rate and shrinkage compensation capacity of the local area are intervened by adjusting the holding pressure, action time and mold temperature control parameters. After the filling cycle is completed, the detection data and process parameters are compared and analyzed. The process field parameters are corrected through feedback algorithm to achieve adaptive optimization of the subsequent process.

[0156] Based on the adjustment results of the filling and solidification stages, a correlation analysis was conducted on the effects of each process parameter in the corresponding stage to establish a mapping relationship between process parameter changes and forming quality response.

[0157] Based on the mapping relationship, the deviation generated under the current process conditions is quantitatively evaluated, and the corresponding parameter correction amount is generated through the constructed feedback correction model.

[0158] The parameter correction is applied to the process parameter settings in subsequent production cycles, and the filling speed, pressure holding strategy and mold temperature control conditions are adjusted in a coordinated manner to gradually approach the target forming state and achieve adaptive optimization of the process.

[0159] Furthermore, during state identification and adaptive correction, a closed-loop control system is constructed to enable dynamic optimization of process parameters based on the actual forming state. Since the die casting process is affected by the coupling of multiple factors, it is difficult to maintain long-term stability by relying solely on preset parameters, and process perception needs to be achieved through online monitoring.

[0160] Furthermore, process data is acquired using pressure sensors, temperature sensors, or non-destructive testing methods, and characteristic parameters reflecting the tightness and flow state, such as pressure fluctuations and temperature change rates, are extracted through signal processing. Key nodes in the transition from flow to solidification are identified through a state determination model, and adjustment commands are generated when abnormal trends are detected.

[0161] Furthermore, by changing the holding pressure and time, adjusting the cooling strategy, or modifying the filling speed, intervention can be made in the local solidification behavior. After a production cycle, the test data and process parameters are compared and analyzed to establish a mapping relationship between parameter changes and molding quality.

[0162] Furthermore, the parameter correction amount is calculated through a feedback algorithm and applied to the next production cycle to achieve gradual optimization. After multiple iterations, the process parameters will tend to a stable optimal state, thereby improving product consistency and yield.

[0163] Example 2

[0164] Figure 1 The flowchart of a hydraulic disc brake caliper body casting process parameter control method according to an embodiment of the present invention includes: constructing a prediction model to characterize semi-solid flow behavior and solidification evolution trend by comprehensively analyzing historical process data and current process setting parameters, and making predictions on filling path, flow velocity distribution and solidification initiation area based on the prediction model.

[0165] Based on the prediction results, the preheating state of the insert, the local temperature control parameters of the mold, and the initial distribution scheme of the cooling circuit are preset and adjusted before the filling process begins;

[0166] During the filling and solidification process, the real-time collected status data is compared with the prediction results. When the deviation exceeds the set threshold, the injection speed curve, cooling intensity distribution and pressure holding parameters are dynamically corrected so that the actual process converges to the predicted optimization path.

[0167] Furthermore, considering the influence of rheological properties, temperature field distribution, and shearing on microstructure evolution of aluminum alloy melt in the semi-solid region, key characteristic parameters related to flow hindrance, temperature gradient, and solidification rate are extracted by correlation analysis of incomplete filling areas, cold shut defect locations, and local premature solidification areas in historical process data. A coupling relationship model between these parameters is established so that the prediction results can simultaneously reflect the trend of flow capacity changes and the evolution characteristics of solidification behavior.

[0168] Furthermore, based on the predicted melt arrival time and local temperature requirements, the initial temperature of the insert is set in zones to ensure that the insert is in a temperature range that is conducive to interface bonding and does not cause local rapid solidification before the melt arrives, thereby reducing the risk of filling blockage and interface defects caused by excessive temperature difference.

[0169] Furthermore, based on the predicted distribution of stagnant sensitive areas, the heating units and cooling circuits in different areas of the mold cavity are set with differentiated parameters to keep the areas with high flow resistance at a high temperature level, while the areas prone to overheating or shrinkage defects are kept at a moderate cooling intensity, thereby forming a temperature field distribution that is conducive to uniform melt filling.

[0170] Furthermore, by continuously comparing the real-time collected pressure, temperature, and flow front position information with the output results of the prediction model, the actual flow path deviation, local flow velocity anomalies, and solidification advance trends are identified. Based on the deviation change trend, the injection velocity curve is modified in stages so that the melt can obtain sufficient kinetic energy in the critical path section to overcome structural resistance.

[0171] Furthermore, based on the deviation between the real-time temperature field and the predicted solidification initiation area, the flow rate and opening sequence of the cooling circuit are dynamically adjusted to ensure that the solidification process proceeds along the expected path, avoiding the formation of closed areas or shrinkage defects in local areas due to excessively rapid cooling.

[0172] Furthermore, by combining the real-time pressure decay trend with the predicted feeding demand, the magnitude and duration of the holding pressure are adjusted in a coordinated manner, so that the melt can receive sufficient feeding during the solidification and shrinkage stage, thereby improving the density of the casting and reducing the probability of internal defects.

[0173] Furthermore, by coordinating the adjustment of various parameters, the actual filling and solidification process gradually converges to the predicted optimized path, thereby ensuring the integrity of the filling process while simultaneously improving the uniformity of the microstructure and mechanical properties.

[0174] Comparative Example 1

[0175] In this comparative example, the conventional hydraulic disc brake caliper casting process parameter control method was used for production. The process was basically the same as in the example, but no predictive model based on semi-solid flow behavior and solidification evolution trend was introduced, nor were the process parameters dynamically adjusted, as follows:

[0176] Before casting, the mold temperature is uniformly set to 280℃, the insert preheating temperature is set to 200℃, the cooling circuit adopts a fixed flow distribution method, and the cooling intensity of each area is kept consistent; during the filling process, the injection speed curve adopts a fixed two-stage injection mode and is not adjusted according to the differences in cavity structure; during the solidification stage, the holding pressure is set to 70MPa and the holding time is 8s, and no real-time parameter correction is performed throughout the process.

[0177] A total of 30 brake caliper body samples were prepared. The filling quality, internal defects, and mechanical properties were tested, and the results are as follows:

[0178] Regarding the integrity of the filling, X-ray inspection revealed that 8 samples had significant underfilling in the bridging channel transition area, with an incomplete filling rate of 26.7%. Meanwhile, 6 samples had cold shut defects in the wall thickness abrupt change area, accounting for 20.0%.

[0179] Regarding internal density, CT scan analysis of the sample revealed that the average porosity of the thick cross-section area was 2.8%, with the local maximum porosity reaching 4.5%, which is significantly higher than the control level in the example. Shrinkage cavities and porosity defects are mainly concentrated in the end area far from the ingate.

[0180] In terms of mechanical properties, tensile tests were conducted on the samples, and the average tensile strength was 245 MPa, the yield strength was 165 MPa, and the elongation was 3.2%. The performance of different samples fluctuated greatly, and the standard deviation of tensile strength reached ±18 MPa.

[0181] In contrast, the brake caliper prepared using the methods of Examples 1 and 2, under the same testing conditions, showed a reduction in incomplete filling rate to below 5%, an average porosity controlled to below 1.2%, an increase in tensile strength to above 280 MPa, and reduced performance fluctuations.

[0182] It is evident that, due to the lack of prediction and dynamic control over the filling path, flow state, and solidification process, the comparative example results in insufficient melt flow capacity in complex structural regions and localized solidification out of control. Consequently, it is significantly inferior to the method of the embodiments of the present invention in terms of filling integrity, internal density, and mechanical properties.

[0183] Those skilled in the art will readily conceive of embodiments of the invention upon consideration of the specification and practice of the methods disclosed herein. The invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein.

Claims

1. A method for controlling the casting process parameters of a hydraulic disc brake caliper body, characterized in that, The specific steps include the following: Obtain the three-dimensional structural feature information of the target hydraulic disc brake caliper, and construct the process field based on the three-dimensional structural feature information; Under the constraints of the process field, the aluminum alloy melt is subjected to state modulation to form a semi-solid rheological state; Based on the semi-solid rheological state, the thermal inertia of the insert is adjusted to match the direction of spatial flow, so that the insert forms a differentiated thermal response state in different interface regions. The semi-solid rheological state and the insert thermal response state are applied together in the mold cavity, and the filling control is carried out under the constraint of the mold thermal response, so that the material flow state, interface state and mold constraint state form a coupled evolution relationship. The coupling evolution relationship is identified by state recognition. When a critical state of material transition from continuous flow to confined solidification is detected, a solidification control strategy is triggered. Based on the control result, the process field is reversed to form an adaptive process evolution mechanism.

2. The method for controlling the casting process parameters of the hydraulic disc brake caliper body according to claim 1, characterized in that, The construction process field includes: The target hydraulic disc brake caliper body is solidly modeled using 3D modeling software, and the solid model is spatially discretized using mesh generation technology, dividing the overall structure into multiple volume elements with spatial coordinate attributes. In each of the aforementioned body units, wall thickness, cross-sectional change rate, and flow channel turning angle parameters are extracted using a geometric analytical algorithm. Based on the geometric relationship between adjacent body units, wall thickness gradient and cross-sectional shrinkage rate are calculated to form structural parameter distribution data. Using a pre-defined flow retardation calculation model, the wall thickness gradient, cross-sectional shrinkage rate, and flow channel turning angle are used as input variables to calculate and process each body element to obtain a flow retardation coefficient that reflects the local shear rate attenuation trend. The body elements are then sorted according to the magnitude of the flow retardation coefficient. By setting a threshold for the flow retardation coefficient, volumetric units that exceed the threshold are screened out, and spatial adjacency relationships are combined to perform regional clustering to form multiple continuously distributed retardation-sensitive regions. For the stagnant sensitive area, a temperature-flow coupling adjustment function is constructed to apply local adjustment parameters to each area. These include increasing the set temperature of the mold temperature control node in the corresponding area to enhance the local flow capability, and increasing the initial filling driving force parameter to compensate for the loss of flow kinetic energy. The adjustment parameters of each region are mapped to the mold temperature control system and the filling control system. By configuring the arrangement of the heating units inside the mold and the parameters of the temperature control circuit, a process field with spatial difference adjustment capability is formed.

3. The method for controlling the casting process parameters of the hydraulic disc brake caliper body according to claim 1, characterized in that, The semi-solid rheological state includes: By arranging multiple temperature acquisition sensors inside the smelting equipment, the temperature of the aluminum alloy melt at different spatial locations is collected in real time, and a melt temperature distribution model is constructed by combining the spatial coordinate information of the sensors. By utilizing the spatial correspondence of the stagnation-sensitive region in the mold cavity, the high stagnation risk region is mapped to the time interval before the melt flows into the mold, and different control stages of the melt during the stirring process are divided. Within the different control stages, by adjusting the rotation speed parameters of the high-shear stirring device, the melt is subjected to shearing forces of different intensities within the corresponding time periods. In particular, the stirring speed is increased in the control stages corresponding to the high stagnation risk region to enhance grain breakage and homogenization. During the stirring process, a solid fraction calculation model based on temperature and shear rate is introduced to dynamically calculate the generation rate and growth trend of solid particles in the melt, and the calculation results are compared with the preset solid fraction growth rate threshold. When the calculation results at a certain stage indicate that the solid fraction growth rate exceeds the threshold, the stage melt is regulated by reducing the local cooling rate to increase the shear strength. Through a multi-stage shear regulation and solid fraction control process, the aluminum alloy melt forms a semi-solid rheological state with spatially corresponding regulation characteristics before entering the mold cavity, thereby reducing flow stagnation and local premature solidification in the stagnant sensitive area during the filling process.

4. The method for controlling the casting process parameters of the hydraulic disc brake caliper body according to claim 1, characterized in that, The thermal inertia adjustment includes: By spatially analyzing the filling path of the semi-solid rheological state in the mold cavity and combining it with the positional relationship of the insert in the cavity, the temporal distribution of the contact between the melt flow front and the insert is determined. Based on the time sequence distribution, by adjusting the heating power and zoning arrangement of the insert preheating device, differentiated preheating treatment is applied to different areas of the insert. At the same time, by adjusting the temperature control node parameters of the corresponding area of ​​the mold, the local thermal boundary conditions are synchronously adjusted so that the interface temperature state of the insert matches the semi-solid flow state, thereby reducing the interface temperature difference impact and maintaining the local flow continuity.

5. The method for controlling the casting process parameters of the hydraulic disc brake caliper body according to claim 1, characterized in that, The coupling evolution relationship includes: By setting up multiple independent cooling circuits inside the mold and equipping each cooling circuit with an adjustable flow control unit, the cooling intensity of different areas of the mold cavity can be dynamically adjusted during the filling process. By using temperature acquisition units deployed on the surface of the mold cavity, the heat distribution state inside the cavity is monitored in real time, and the acquired temperature data is input into the control system for processing; Based on the temperature data, by adjusting the flow parameters and flow direction of each cooling circuit, the heat dissipation rate of the local area is coordinated with the advance speed of the melt flow front, thereby controlling the solidification interface to advance smoothly along the preset direction and reducing flow interruption.

6. The method for controlling the casting process parameters of the hydraulic disc brake caliper body according to claim 1, characterized in that, The filling control includes: By deploying temperature monitoring units inside the mold and on the surface of the cavity, the thermal response state of the mold is collected in real time, forming state data that reflects the temperature gradient distribution. Based on the aforementioned state data, by dynamically adjusting the flow distribution and flow path of each loop in the cooling system, the heat exchange capacity of different regions is matched with the local solidification demand, thereby constructing stable thermal boundary conditions. During the regulation process, flow rate increases or decreases or flow direction switching are implemented in areas with abnormal local temperatures to suppress solidification imbalance caused by uneven heating.

7. The method for controlling the casting process parameters of the hydraulic disc brake caliper body according to claim 1, characterized in that, The reverse correction includes: The status signals during the filling and solidification process are collected by an online detection device, and the status signals are processed to extract characteristic parameters reflecting changes in internal density. Based on the aforementioned characteristic parameters, the process of the melt transitioning from a flowing state to a solidified state is identified through a state determination model, and corresponding adjustment commands are generated when a localized region is detected to exhibit flow restriction or abnormal solidification trends. According to the adjustment instructions, the solidification rate and shrinkage compensation capacity of the local area are intervened by adjusting the holding pressure, action time and mold temperature control parameters. After the filling cycle is completed, the detection data and process parameters are compared and analyzed. The process field parameters are corrected by feedback algorithm to achieve adaptive optimization of the subsequent process.

8. The method for controlling the casting process parameters of the hydraulic disc brake caliper body according to claim 1, characterized in that, The adaptive optimization includes: Based on the adjustment results of the filling and solidification stages, a correlation analysis was conducted on the effects of each process parameter in the corresponding stage to establish a mapping relationship between process parameter changes and forming quality response. Based on the mapping relationship, the deviation generated under the current process conditions is quantitatively evaluated, and the corresponding parameter correction amount is generated through the constructed feedback correction model. The parameter correction is applied to the process parameter settings in subsequent production cycles to coordinate the adjustment of filling speed, pressure holding strategy and mold temperature control conditions, so as to gradually approach the target forming state and achieve adaptive optimization of the process.

9. The method for controlling the casting process parameters of the hydraulic disc brake caliper body according to claim 1, characterized in that, By comprehensively analyzing historical process data and current process setting parameters, a predictive model is constructed to characterize semi-solid flow behavior and solidification evolution trend. Based on the predictive model, the filling path, flow velocity distribution and solidification initiation region are predicted. Based on the predicted results, the preheating state of the insert, the local temperature control parameters of the mold, and the initial distribution scheme of the cooling circuit are preset and adjusted before the filling process begins. During the filling and solidification process, the real-time collected status data is compared with the predicted results. When the deviation exceeds the set threshold, the injection speed curve, cooling intensity distribution and pressure holding parameters are dynamically corrected so that the actual process converges to the predicted optimization path.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the hydraulic disc brake caliper casting process parameter control method according to any one of claims 1-8.

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