Extrusion forming method of battery pack aluminum alloy profile and aluminum alloy profile

Abstract

The invention belongs to the field of aluminum profile extrusion control, and discloses a battery pack aluminum alloy profile extrusion forming method and a correspondingly produced aluminum alloy profile. The method comprises the following steps: acquiring corresponding temperature values of a plurality of cavity positions of a plurality of parallel cooling channels for extruding a profile on an extrusion die in real time, determining a maximum value and a minimum value from the corresponding temperature values, and calculating a difference value between the maximum value and the minimum value as a maximum cavity temperature difference; when the difference value exceeds a preset threshold value, a preset temperature adjusting power value is obtained firstly, then whether the real-time heating power of the cavity corresponding to the minimum temperature is lower than the maximum heating power or not is checked, if yes, the heating power of the cavity corresponding to the maximum temperature is synchronously reduced, and the heating power of the cavity corresponding to the minimum temperature is synchronously increased; the adjusting amplitude is a preset adjusting power value, so that the temperature of each cavity is balanced, and the extrusion forming quality of the battery pack aluminum alloy profile with the multiple parallel cooling channels is improved.

Description

Technical Field

[0001] This application relates to the field of aluminum profile extrusion control technology, and more specifically, to an extrusion molding method for aluminum alloy profiles for battery packs and the aluminum alloy profiles themselves. Background Technology

[0002] Extrusion molding is a common forming process in the processing of aluminum alloy profiles for battery packs. Current extrusion molding equipment can extrude aluminum alloy profiles for battery packs with multiple parallel cooling channels. In practical production applications, extrusion molding equipment can be adapted to aluminum alloy billets of different specifications. By controlling process parameters such as extrusion speed and billet heating temperature during the extrusion process, battery pack aluminum alloy profiles with preset cooling channel numbers, channel arrangement, and external dimensions can be obtained. This provides basic components for the subsequent assembly of the battery pack heat dissipation system and is suitable for the processing and preparation of aluminum alloy profiles in scenarios such as power battery packs for new energy vehicles.

[0003] Existing extrusion molding equipment cannot achieve online real-time detection of the wall thickness uniformity parameters of each cooling channel during the processing of aluminum alloy profiles for battery packs containing multiple parallel cooling channels. It is difficult to promptly control channel offset and collapse defects that occur during extrusion. Subsequent verification of profile quality can only be done through offline sampling inspection, which cannot guarantee the consistency of cooling channels in mass-produced profiles. Problems such as insufficient flow capacity and substandard structural strength in some profile cooling channels are prone to occur. It is difficult to achieve effective full-process quality control for this type of aluminum alloy profile for battery packs containing multiple parallel cooling channels, resulting in low product yield and inability to meet the profile supply requirements of high-reliability battery packs. Summary of the Invention

[0004] The purpose of this application is to provide an extrusion molding method for aluminum alloy profiles of battery packs and the aluminum alloy profiles themselves, which solves the technical problem of not being able to effectively control the quality of aluminum alloy profiles of battery packs with multiple parallel cooling channels, and achieves the technical effect of effectively controlling the quality of aluminum alloy profiles of battery packs with multiple parallel cooling channels.

[0005] In a first aspect, embodiments of this application provide an extrusion molding method for aluminum alloy profiles of battery packs. The method includes: acquiring in real time multiple chamber temperature values ​​corresponding to multiple chamber positions of an extrusion die, wherein the multiple chamber positions are used for multiple parallel cooling channels of the aluminum alloy profiles of the battery pack; determining the maximum and minimum chamber temperature values ​​among the multiple chamber temperature values; determining the difference between the maximum and minimum chamber temperature values ​​as the maximum chamber temperature difference; when the maximum chamber temperature difference is greater than a preset maximum chamber temperature difference, acquiring a preset temperature adjustment power value; acquiring the real-time second heating power and the maximum second heating power of the second chamber position corresponding to the minimum chamber temperature value; when the real-time second heating power is less than the maximum second heating power, decreasing the real-time first heating power of the first chamber position corresponding to the maximum chamber temperature value by a preset temperature adjustment power value, and increasing the real-time second heating power of the second chamber position corresponding to the minimum chamber temperature value by a preset temperature adjustment power value.

[0006] In one possible implementation, the method further includes: when the real-time second heating power is greater than or equal to the maximum second heating power, after removing the minimum chamber temperature value from multiple chamber temperature values, a new minimum chamber temperature value is determined; the difference between the maximum chamber temperature value and the minimum chamber temperature value is determined as the maximum chamber temperature difference; when the maximum chamber temperature difference is greater than a preset maximum chamber temperature difference, a preset temperature adjustment power value is determined based on the maximum chamber temperature difference; the real-time second heating power and the maximum second heating power at the second chamber position corresponding to the minimum chamber temperature value are re-acquired; when the real-time second heating power is less than the maximum second heating power, the preset temperature adjustment power value is reduced for the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value, and the preset temperature adjustment power value is increased for the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value.

[0007] In another possible implementation, the method further includes: reducing the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value by a preset temperature adjustment power value, and increasing the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value by a preset temperature adjustment power value; when the maximum chamber temperature difference is greater than a preset maximum chamber temperature difference value, determining the change value of the maximum chamber temperature difference as the chamber temperature adjustment value; when the chamber temperature adjustment value is less than the preset chamber temperature adjustment value, reducing the local extrusion speed at the first chamber position corresponding to the maximum chamber temperature value by 0.5%-2%, and increasing the local extrusion speed at the second chamber position corresponding to the minimum chamber temperature value by 0.5%-2%.

[0008] In another possible implementation, the method further includes: reducing the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value by a preset temperature adjustment power value, increasing the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value by a preset temperature adjustment power value, and then obtaining the maximum chamber temperature difference value again; when the maximum chamber temperature difference value is less than the preset maximum chamber temperature difference value, obtaining the real-time forming deviation index of the battery pack aluminum alloy profile; when the real-time forming deviation index is less than the preset real-time forming deviation index, reducing the preset maximum chamber temperature difference value to adjust the preset maximum chamber temperature difference value.

[0009] In another possible implementation, the method further includes: acquiring multiple molding record data corresponding to multiple production batches; clustering the multiple molding record data to obtain multiple molding record groups; wherein the multiple molding record data includes multiple chamber temperature values, maximum chamber temperature difference values, chamber heating power values, temperature regulation power values, local extrusion speeds, and molding deviation indicators of multiple parallel cooling channels; determining the target molding record group to which the current extrusion molding process belongs, and determining the average temperature regulation power corresponding to the target molding record group as the preset temperature regulation power value corresponding to the current extrusion molding process.

[0010] In another possible implementation, determining the target forming record group to which the current extrusion forming process belongs includes: acquiring multiple current chamber temperature values ​​and the current maximum chamber temperature difference corresponding to the current extrusion forming process; determining the current chamber temperature characteristics corresponding to the multiple chamber temperature values ​​corresponding to the current extrusion forming process, and determining the average values ​​of multiple chamber temperatures corresponding to multiple forming record groups, and determining the average characteristics of multiple chamber temperatures corresponding to the average values ​​of multiple chamber temperatures; determining the average value of the maximum chamber temperature difference corresponding to multiple forming record groups as the average maximum chamber temperature difference; determining the similarity between the current chamber temperature characteristics and the average characteristics of multiple chamber temperature, as the chamber temperature difference degree corresponding to multiple forming record groups; determining the difference between the current maximum chamber temperature difference and the average maximum chamber temperature difference, as the chamber temperature extreme value difference degree; determining the sum of the chamber temperature difference degree and the chamber temperature extreme value difference degree of multiple forming record groups as the multiple extrusion parameter difference degree corresponding to multiple forming record groups; and determining the forming record group corresponding to the minimum extrusion parameter difference degree as the target forming record group to which the current extrusion forming process belongs.

[0011] In another possible implementation, the method further includes: obtaining the chamber temperature difference weight and the chamber temperature extreme value difference weight corresponding to the current extrusion molding process; determining the sum of the product of the chamber temperature difference degree and the chamber temperature difference weight of multiple molding record groups, and the product of the chamber temperature extreme value difference degree and the chamber temperature extreme value difference weight, as the multiple extrusion parameter difference degrees corresponding to the multiple molding record groups.

[0012] In another possible implementation, the method further includes: obtaining the average molding deviation index corresponding to the target molding record group to which the current extrusion molding process belongs; and using the average molding deviation index as a preset real-time molding deviation index corresponding to the real-time molding deviation index of the current extrusion molding process.

[0013] In another possible implementation, the method further includes: determining the maximum and minimum molding deviation indices of parallel cooling channels for multiple chamber locations corresponding to multiple molding record data; determining the difference between the maximum and minimum molding deviation indices corresponding to multiple chamber locations as the extreme values ​​of the molding deviation indices corresponding to multiple molding record data; and determining the mean of the extreme values ​​of the molding deviation indices corresponding to multiple molding record data as the mean of the molding deviation indices corresponding to multiple molding record data of the target molding record group.

[0014] Secondly, this application provides an aluminum alloy profile manufactured by extrusion molding using the above-mentioned extrusion molding method for battery pack aluminum alloy profiles.

[0015] The beneficial effects of the embodiments in this application compared with the prior art are:

[0016] This application provides an extrusion molding method for aluminum alloy profiles of battery packs. The method includes: acquiring multiple chamber temperature values ​​corresponding to multiple chamber positions of an extrusion die in real time, wherein the multiple chamber positions are used for multiple parallel cooling channels of the extruded aluminum alloy profile of the battery pack; determining the maximum and minimum chamber temperature values ​​among the multiple chamber temperature values; determining the difference between the maximum and minimum chamber temperature values ​​as the maximum chamber temperature difference; when the maximum chamber temperature difference is greater than a preset maximum chamber temperature difference, acquiring a preset temperature adjustment power value; acquiring the real-time second heating power and the maximum second heating power of the second chamber position corresponding to the minimum chamber temperature value; when the real-time second heating power is less than the maximum second heating power, decreasing the real-time first heating power of the first chamber position corresponding to the maximum chamber temperature value by the preset temperature adjustment power value, and increasing the real-time second heating power of the second chamber position corresponding to the minimum chamber temperature value by the preset temperature adjustment power value. In this application embodiment, effective full-process quality control can be achieved for the aluminum alloy profile of the battery pack with multiple parallel cooling channels. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A schematic flowchart illustrating the extrusion molding method for a first type of aluminum alloy profile for a battery pack provided in this application embodiment;

[0019] Figure 2 A schematic diagram illustrating the workflow of the first extrusion molding method for aluminum alloy profiles of a battery pack provided in this application embodiment;

[0020] Figure 3 A schematic flowchart illustrating the extrusion molding method for a second type of aluminum alloy profile for a battery pack provided in this application embodiment;

[0021] Figure 4 A schematic diagram illustrating the workflow of the extrusion molding method for the second type of aluminum alloy profile for battery packs provided in this application embodiment;

[0022] Figure 5 A schematic flowchart illustrating the extrusion molding method for a third type of aluminum alloy profile for a battery pack provided in this application embodiment;

[0023] Figure 6 A schematic diagram illustrating the workflow of the third extrusion molding method for aluminum alloy profiles of battery packs provided in this application embodiment;

[0024] Figure 7 A schematic flowchart illustrating the extrusion molding method for a fourth type of aluminum alloy profile for a battery pack provided in this application embodiment;

[0025] Figure 8 A schematic diagram of the workflow for the extrusion molding method of the fourth type of aluminum alloy profile for battery pack provided in the embodiments of this application;

[0026] Figure 9 A schematic flowchart illustrating the fifth method for extruding aluminum alloy profiles for battery packs provided in this application embodiment;

[0027] Figure 10 A schematic diagram of the workflow for the fifth type of extrusion molding method for aluminum alloy profiles of battery packs provided in this application embodiment;

[0028] Figure 11 A schematic flowchart illustrating the extrusion molding method for the sixth type of aluminum alloy profile for battery packs provided in this application embodiment;

[0029] Figure 12 A schematic flowchart illustrating the extrusion molding method for the seventh type of aluminum alloy profile for battery packs provided in this application embodiment;

[0030] Figure 13 This is a schematic flowchart of the extrusion molding method for the eighth type of aluminum alloy profile for battery packs provided in this application embodiment. Detailed Implementation

[0031] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.

[0032] It should be noted that when a component or structure is referred to as being "fixed to" or "set on" another component or structure, it can be directly on or indirectly on the other component or structure. When a component or structure is referred to as being "connected to" another component or structure, it can be directly connected to or indirectly connected to the other component or structure.

[0033] It should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device, component, or structure referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0034] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0035] Existing extrusion molding equipment struggles to achieve effective end-to-end quality control for aluminum alloy profiles used in battery packs that contain multiple parallel cooling channels.

[0036] Based on the above reasons, this application provides an extrusion molding method for aluminum alloy profiles of battery packs. The method includes: acquiring multiple chamber temperature values ​​corresponding to multiple chamber positions of an extrusion die in real time, wherein the multiple chamber positions are used for multiple parallel cooling channels of the extruded aluminum alloy profile of the battery pack; determining the maximum and minimum chamber temperature values ​​among the multiple chamber temperature values; determining the difference between the maximum and minimum chamber temperature values ​​as the maximum chamber temperature difference; when the maximum chamber temperature difference is greater than a preset maximum chamber temperature difference, acquiring a preset temperature adjustment power value; acquiring the real-time second heating power and the maximum second heating power of the second chamber position corresponding to the minimum chamber temperature value; when the real-time second heating power is less than the maximum second heating power, decreasing the real-time first heating power of the first chamber position corresponding to the maximum chamber temperature value by a preset temperature adjustment power value, and increasing the real-time second heating power of the second chamber position corresponding to the minimum chamber temperature value by a preset temperature adjustment power value. In this application embodiment, effective full-process quality control can be achieved for the aluminum alloy profile of the battery pack with multiple parallel cooling channels.

[0037] In some scenarios, the extrusion molding method for aluminum alloy profiles of battery packs according to the embodiments of this application can be applied to the extrusion molding of aluminum alloy profiles for battery packs of new energy passenger vehicles, and can quickly produce battery pack frame profiles with high consistency.

[0038] In other scenarios, the extrusion molding method for aluminum alloy profiles of battery packs according to the embodiments of this application can also be applied to the production of customized battery packs for energy storage power stations, enabling high-quality production of energy storage modules of different specifications.

[0039] The following describes in detail, with specific examples, a method for extruding aluminum alloy profiles for battery packs provided in this application.

[0040] Figure 1 A schematic flowchart of the extrusion molding method for the first type of aluminum alloy profile for a battery pack provided in this application embodiment is shown below. Figure 1 As shown in the embodiment of this application, an extrusion molding method for aluminum alloy profiles of battery packs is provided. The method further includes steps S110 to S120, which will be described in detail below.

[0041] S110. Real-time acquisition of multiple chamber temperature values ​​corresponding to multiple chamber positions of the extrusion die. These multiple chamber positions are used for multiple parallel cooling channels in the extrusion of aluminum alloy profiles for the battery pack. Determine the maximum and minimum chamber temperature values ​​among the multiple chamber temperature values. Determine the difference between the maximum and minimum chamber temperature values ​​as the maximum chamber temperature difference. When the maximum chamber temperature difference is greater than the preset maximum chamber temperature difference, acquire the preset temperature regulation power value.

[0042] Figure 2 A schematic diagram of the workflow for the extrusion molding method of the first type of aluminum alloy profile for battery pack provided in this application embodiment is shown below. Figure 2 As shown, in this implementation, suitable temperature acquisition devices can be deployed at multiple chamber locations of the extrusion die. The temperature of each chamber is acquired through a preset acquisition cycle to obtain the corresponding multiple chamber temperature values. The acquired multiple chamber temperature values ​​can be transmitted to the corresponding control module to provide a data basis for subsequent temperature difference calculation and temperature adjustment.

[0043] It should be noted that the various chambers are separated by a flow divider bridge. The temperature difference between the flow channels of the flow divider bridge has a significant impact on the quality of the finished product, and is even one of the core determining factors of the forming quality of the hollow profile. The aluminum alloy material in the extrusion die re-converges in the welding chamber after passing through the flow divider bridge, thereby realizing the extrusion forming of the aluminum alloy profile of the battery pack.

[0044] It should be noted that the cavity positions of the extrusion die correspond to the structural requirements of the aluminum alloy profile of the battery pack. Each cavity position is distributed in multiple parallel cooling channels of the extrusion die used to extrude the aluminum alloy profile of the battery pack. The cavities of the multiple parallel cooling channels are distributed in the width direction of the profile.

[0045] For example, the extrusion die has four chambers evenly arranged along its width. The four chambers are separated by a flow divider bridge. Each of the four chambers corresponds to a parallel cooling channel, which is used to circulate coolant within the aluminum alloy profile of the battery pack.

[0046] In this implementation, all collected chamber temperature values ​​can be imported into a preset numerical comparison logic. All values ​​are compared one by one, and the maximum and minimum values ​​are selected as the maximum and minimum chamber temperature values, respectively. The two values ​​can be used for subsequent temperature difference calculations, providing a basis for judging temperature uniformity.

[0047] For example, the collected chamber temperature values ​​are 430 degrees Celsius, 470 degrees Celsius, 510 degrees Celsius, 490 degrees Celsius, 400 degrees Celsius, and 440 degrees Celsius. The first value of 430 degrees Celsius is taken as the initial maximum and minimum value. The subsequent values ​​are compared in turn to obtain the maximum chamber temperature value of 510 degrees Celsius and the minimum chamber temperature value of 400 degrees Celsius.

[0048] In this implementation, the difference between the maximum and minimum chamber temperature values ​​can be calculated, and the resulting value is the maximum chamber temperature difference. The maximum chamber temperature difference can directly reflect the temperature uniformity between different chambers of the extrusion die. The smaller the difference, the higher the temperature consistency of each chamber, which is more conducive to the forming quality control of aluminum alloy profiles.

[0049] In this implementation, the calculated maximum chamber temperature difference can be compared with the preset maximum chamber temperature difference. When the maximum chamber temperature difference is greater than the preset maximum chamber temperature difference, it is determined that the current chamber temperature uniformity does not meet the process requirements, triggering the temperature adjustment process and obtaining the corresponding preset temperature adjustment power value. The obtained preset temperature adjustment power value can be directly applied to the adjustment device of the cooling channel to adjust the chamber temperature.

[0050] It should be noted that the preset maximum chamber temperature difference range is set according to the forming accuracy requirements of the aluminum alloy profile of the battery pack. The higher the requirement, the smaller the corresponding preset maximum chamber temperature difference, to ensure that the chamber temperature deviation will not have a negative impact on the dimensional accuracy and mechanical properties of the profile.

[0051] For example, when the dimensional accuracy requirement of the aluminum alloy profile of the battery pack is ±0.1 mm, the preset maximum chamber temperature difference range is 15 degrees Celsius to 25 degrees Celsius; when the dimensional accuracy requirement is ±0.2 mm, the preset maximum chamber temperature difference range is 25 degrees Celsius to 40 degrees Celsius.

[0052] It should be noted that the preset temperature regulation power value range is determined based on the volume of the chamber and the heat exchange efficiency of the cooling channel. The determination is based on the ability to adjust the chamber temperature to the target range within the set time, while avoiding thermal stress damage to the chamber structure caused by excessively fast temperature regulation rate.

[0053] S120. Obtain the real-time second heating power and the maximum second heating power at the second chamber position corresponding to the minimum chamber temperature value. When the real-time second heating power is less than the maximum second heating power, decrease the preset temperature adjustment power value of the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value, and increase the preset temperature adjustment power value of the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value.

[0054] In this implementation, the second chamber position corresponding to the minimum chamber temperature value can be located according to the mapping relationship between the chamber position and the heating power acquisition module. The real-time second heating power currently running at the second chamber position is collected. Heating the second chamber position can improve the fluidity of the aluminum material and improve the extrusion molding effect. The maximum second heating power supported by the heating device at this position is also collected. The two types of power parameters collected can provide a basis for judgment for the subsequent heating power adjustment logic.

[0055] It should be noted that the range of the real-time second heating power is related to the process temperature requirements of the molding section corresponding to the second chamber position, the difference between the current actual temperature and the target temperature. During actual operation, the power value will be dynamically adjusted according to temperature changes, and will always be within the range of zero to the maximum second heating power.

[0056] For example, the second chamber corresponds to the shaping section of the extrusion die, and its real-time second heating power ranges from 0 kW to 3 kW. When the temperature of the second chamber is close to the target temperature, the real-time second heating power is in the range of 0.5 kW to 1 kW. When the temperature is much lower than the target temperature, the real-time second heating power is in the range of 1.5 kW to 2.5 kW.

[0057] It should be noted that the maximum range of the second heating power is determined by the rated parameters of the heating device configured in the second chamber, the volume of the chamber, and the heat exchange efficiency. It is the maximum power limit that the heating device in this position can operate stably for a long time and will not be adjusted with changes in real-time operating conditions.

[0058] In this implementation, the collected real-time second heating power and the maximum second heating power can be compared. When the comparison result shows that the real-time second heating power is less than the maximum second heating power, it is determined that there is redundant heating power that can be increased at the second chamber location, and the corresponding temperature adjustment operation can be performed. When adjusting the power, the real-time first heating power at the first chamber location corresponding to the maximum chamber temperature value can be reduced by a preset temperature adjustment power value, while the real-time second heating power at the second chamber location can be increased by a preset temperature adjustment power value.

[0059] For example, if the current real-time second heating power of the second chamber is 2.2 kW and the pre-stored maximum second heating power is 3 kW, the difference between the two values ​​is 0.8 kW. Since the difference is positive, it is determined that the real-time second heating power is less than the maximum second heating power, thus meeting the condition for power adjustment.

[0060] It should be noted that the process of reducing the preset temperature adjustment power value of the real-time first heating power at the first chamber location is implemented by the heating power control module. First, the heating control loop corresponding to the first chamber location is located, and a power reduction command is sent to the power adjustment device of the loop. The reduction amount is the preset temperature adjustment power value. After the command is sent, the new power value is collected in real time to confirm that the adjustment has taken effect.

[0061] For example, if the current real-time first heating power in the first chamber is 4 kW and the preset temperature adjustment power value is 0.5 kW, the power control module sends a downward adjustment command to the heating controller in the first chamber to adjust the real-time first heating power to 3.5 kW. After the adjustment is completed, the real-time power is collected to confirm that the value matches.

[0062] It should be noted that the process of increasing the real-time second heating power of the second chamber to the preset temperature adjustment power value is also achieved by the heating power control module. The heating control loop corresponding to the second chamber is located, and a power increase command is sent to the power adjustment device of the loop. The increase is the preset temperature adjustment power value. After the command is sent, the new power value is collected in real time to confirm that the adjustment is effective.

[0063] For example, if the current real-time second heating power in the second chamber is 2.2 kW and the preset temperature adjustment power is 0.5 kW, the power control module sends an upward adjustment command to the heating controller in the second chamber to adjust the real-time second heating power to 2.7 kW. After the adjustment is completed, the real-time power is collected to confirm that the value matches.

[0064] This method collects multiple chamber temperature values ​​in real time for multiple chamber locations of the extrusion die, filters out the maximum and minimum chamber temperature values, and calculates the maximum chamber temperature difference. This can accurately identify the temperature deviation between each chamber, avoid the problem of insufficient forming accuracy of parallel cooling channels due to excessive chamber temperature difference, and ensure the structural consistency of the battery pack aluminum alloy profile.

[0065] This implementation method, when the maximum chamber temperature difference is determined to be greater than the preset maximum chamber temperature difference, calls the preset temperature regulation power value as the regulation benchmark, and at the same time obtains the real-time second heating power and the maximum second heating power of the second chamber position corresponding to the minimum chamber temperature value, so as to realize the standardized control of the triggering conditions and regulation range of the regulation action, reduce unnecessary power regulation actions, reduce energy consumption and improve the accuracy of temperature regulation.

[0066] By means of this implementation, when it is determined that the real-time second heating power is less than the maximum second heating power, the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value is reduced by a preset temperature adjustment power value, while the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value is increased by a preset temperature adjustment power value. This can quickly reduce the temperature difference between chambers without exceeding the heating power threshold, ensure uniform forming quality of each parallel cooling channel, and reduce the defect rate of the battery pack aluminum alloy profile.

[0067] Figure 3 This is a schematic flowchart of the extrusion molding method for a second type of aluminum alloy profile for a battery pack provided in an embodiment of this application, as shown below. Figure 3 As shown, in some implementations, the above method also includes S130 to S140, which will be described in detail below.

[0068] S130. When the real-time second heating power is greater than or equal to the maximum second heating power, the minimum chamber temperature value is discarded from multiple chamber temperature values, and a new minimum chamber temperature value is determined. The difference between the maximum chamber temperature value and the minimum chamber temperature value is determined as the maximum chamber temperature difference value. When the maximum chamber temperature difference value is greater than the preset maximum chamber temperature difference value, the preset temperature adjustment power value is determined based on the maximum chamber temperature difference value.

[0069] Figure 4 This is a schematic diagram of the workflow of the extrusion molding method for the second type of aluminum alloy profile for battery packs provided in the embodiments of this application, as shown below. Figure 4 As shown, in this implementation, the collected real-time second heating power can be compared with the pre-stored maximum second heating power. When the comparison result shows that the real-time second heating power is greater than or equal to the maximum second heating power, it is determined that there is no room for increasing the heating power at the second chamber location, and the power increase operation for that chamber is no longer performed. At this time, the multiple chamber temperature values ​​that have been collected can be filtered, and the minimum chamber temperature value can be removed. Based on the remaining chamber temperature values, the minimum value identification logic is re-executed to obtain a new minimum chamber temperature value.

[0070] It should be noted that the process of determining whether the real-time second heating power is greater than or equal to the maximum second heating power is based on numerical comparison logic. First, the current real-time second heating power and the pre-stored maximum second heating power at the position of the second chamber are obtained. The difference between the two is calculated, and the determination is completed based on whether the difference is positive, negative or zero. The determination result directly determines the subsequent processing logic.

[0071] For example, the original multiple chamber temperature values ​​are 430 degrees Celsius, 470 degrees Celsius, 510 degrees Celsius, 490 degrees Celsius, 400 degrees Celsius, and 440 degrees Celsius. The identified minimum chamber temperature value is 400 degrees Celsius. After removing this value from the set, the remaining values ​​are 430 degrees Celsius, 470 degrees Celsius, 510 degrees Celsius, 490 degrees Celsius, and 440 degrees Celsius. By comparing the remaining values, a new minimum chamber temperature value of 430 degrees Celsius is obtained.

[0072] In this implementation, the difference between the current maximum chamber temperature and the newly determined minimum chamber temperature can be calculated, and the result is used as the updated maximum chamber temperature difference. This difference reflects the overall temperature uniformity after removing unheated redundant chambers, providing a basis for subsequent temperature adjustment logic.

[0073] In this implementation, the updated maximum chamber temperature difference is compared with the preset maximum chamber temperature difference. When the maximum chamber temperature difference is greater than the preset maximum chamber temperature difference, it is determined that the current chamber temperature uniformity still does not meet the process requirements, and temperature regulation needs to be initiated. At this time, the corresponding preset temperature regulation power value can be matched according to the specific value of the maximum chamber temperature difference, providing parameter support for subsequent heating power adjustments.

[0074] It should be noted that the process of determining the preset temperature regulation power value based on the maximum chamber temperature difference can be achieved through a pre-stored empirical value table. The empirical value table stores the preset temperature regulation power values ​​corresponding to the maximum chamber temperature difference in different ranges. By matching the actual maximum chamber temperature difference with the range in the empirical value table, the corresponding power value can be obtained.

[0075] For example, the empirical value table stores a preset temperature regulation power value of 0.3 kW for a maximum chamber temperature difference between 10 and 15 degrees Celsius; 0.5 kW for a maximum chamber temperature difference between 15 and 25 degrees Celsius; and 0.8 kW for a maximum chamber temperature difference above 25 degrees Celsius. When the actual maximum chamber temperature difference is 18 degrees Celsius, the corresponding preset temperature regulation power value is 0.5 kW.

[0076] S140. Reacquire the real-time second heating power and the maximum second heating power at the second chamber position corresponding to the minimum chamber temperature value. When the real-time second heating power is less than the maximum second heating power, decrease the preset temperature adjustment power value for the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value, and increase the preset temperature adjustment power value for the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value.

[0077] In this implementation, the updated minimum chamber temperature value can be used to match the corresponding second chamber position and trigger the power parameter re-acquisition process. The real-time second heating power currently running at the second chamber position can be acquired through the heating power acquisition module, and the maximum second heating power corresponding to the position can be pre-stored in the storage module. These two types of parameters can provide the latest basis for subsequent power adjustment judgment.

[0078] It should be noted that the trigger condition for re-acquiring the real-time second heating power and maximum second heating power of the second chamber position corresponding to the minimum chamber temperature value is that the real-time second heating power of the second chamber position corresponding to the original minimum chamber temperature value is greater than or equal to the maximum second heating power, and there is no room for further heating adjustment. During execution, the second chamber position corresponding to the new minimum chamber temperature value can be located first, and then real-time parameters and pre-stored parameters can be collected respectively to ensure that the parameters match the current minimum chamber position.

[0079] For example, if the real-time second heating power at the second chamber location corresponding to the original minimum chamber temperature value is 3.1 kW, which is greater than the maximum second heating power of 3 kW at that location, a re-acquisition process is triggered. The new minimum chamber temperature value corresponds to the second chamber location in the shaping section. The real-time second heating power at that location is obtained through the power acquisition module as 1.8 kW, and the stored maximum second heating power of 3 kW at that location is retrieved, thus completing the parameter re-acquisition.

[0080] In this implementation, the newly acquired real-time second heating power and the maximum second heating power can be compared. When the comparison result shows that the real-time second heating power is less than the maximum second heating power, it is determined that there is redundant heating power that can be increased at the second chamber location, and the corresponding temperature adjustment operation can be performed. A power reduction command can be sent to the heating control circuit at the first chamber location to decrease the real-time first heating power to a preset temperature adjustment power value, while a power increase command can be sent to the heating control circuit at the second chamber location to increase the real-time second heating power to a preset temperature adjustment power value, thereby achieving synchronous adjustment of the temperatures of the two chambers and reducing the temperature difference between the chambers.

[0081] By using this implementation method, when it is determined that the real-time second heating power is greater than or equal to the maximum second heating power, the minimum chamber temperature value is removed from multiple chamber temperature values ​​and then the minimum chamber temperature value is re-determined. This can avoid chambers where the power has reached the upper limit, avoid ineffective adjustment actions, and ensure that the temperature adjustment process can proceed smoothly.

[0082] By using this method, the difference between the maximum chamber temperature value and the new minimum chamber temperature value is recalculated as the maximum chamber temperature difference value. Based on this value, the preset temperature regulation power value is determined, which can adapt to the current actual chamber temperature difference, making the adjustment range more in line with actual needs and improving the adaptability of temperature regulation.

[0083] By using this method, the real-time second heating power and the maximum second heating power of the second chamber position corresponding to the new minimum chamber temperature value are re-verified. After meeting the adjustment conditions, the heating power of the corresponding chamber is adjusted bidirectionally. This can quickly reduce the temperature difference of the chamber within the power threshold and ensure the uniformity of the parallel cooling channel forming quality of the battery pack aluminum alloy profile.

[0084] Figure 5 This is a schematic flowchart of the third method for extruding aluminum alloy profiles for battery packs provided in this application embodiment, as shown below. Figure 5 As shown, in some implementations, the above method also includes S150 to S160, which are described in detail below.

[0085] S150. After reducing the preset temperature adjustment power value of the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value, and increasing the preset temperature adjustment power value of the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value, when the maximum chamber temperature difference is greater than the preset maximum chamber temperature difference value, the change value of the maximum chamber temperature difference is determined as the chamber temperature adjustment value.

[0086] Figure 6 A schematic diagram of the workflow for the extrusion molding method of the third type of aluminum alloy profile for battery pack provided in this application embodiment is shown below. Figure 6 As shown, in this implementation, after adjusting the heating power of the first and second chamber positions, the chamber temperature values ​​of all chamber positions are re-acquired at preset temperature acquisition intervals. Based on the newly acquired temperature values, the updated maximum chamber temperature difference is calculated. The updated maximum chamber temperature difference can be compared with the preset maximum chamber temperature difference. When the comparison result shows that the updated maximum chamber temperature difference is still greater than the preset maximum chamber temperature difference, the calculation process for the difference change is initiated.

[0087] It should be noted that the process of determining whether the maximum chamber temperature difference after adjusting the heating power is greater than the preset maximum chamber temperature difference needs to be executed after the power adjustment is completed and the temperature is stable. First, the temperature values ​​of each chamber after the power adjustment are obtained, the new maximum chamber temperature difference is calculated, and then compared with the pre-stored preset maximum chamber temperature difference. The subsequent logic is determined based on the comparison result.

[0088] For example, after completing the power adjustment, wait 5 minutes for the chamber temperature to stabilize, re-collect the temperature values ​​of each chamber, calculate the new maximum chamber temperature difference to be 22 degrees Celsius, and the preset maximum chamber temperature difference to be 20 degrees Celsius. After comparing the two values, it is determined that the adjusted maximum chamber temperature difference is greater than the preset maximum chamber temperature difference.

[0089] In this implementation, the original maximum chamber temperature difference before power adjustment can be recorded. This difference is then calculated by subtracting the original maximum chamber temperature difference from the adjusted value. This difference is the change in the maximum chamber temperature difference and is determined as the chamber temperature adjustment value. The resulting chamber temperature adjustment value reflects the improvement in temperature uniformity achieved by this power adjustment, providing data support for subsequent optimization of power adjustment parameters.

[0090] It should be noted that the change in the maximum chamber temperature difference is calculated by subtracting the maximum chamber temperature difference after power adjustment from the maximum chamber temperature difference before power adjustment. The resulting value is the change value. The sign of the value reflects whether the adjustment effect meets expectations, and the magnitude of the value reflects the adjustment range.

[0091] S160. When the chamber temperature adjustment value is less than the preset chamber temperature adjustment value, the local extrusion speed at the first chamber position corresponding to the maximum chamber temperature value is reduced by 0.5%-2%, and the local extrusion speed at the second chamber position corresponding to the minimum chamber temperature value is increased by 0.5%-2%.

[0092] In this implementation, the calculated chamber temperature adjustment value can be compared with a pre-stored preset chamber temperature adjustment value. When the comparison result shows that the chamber temperature adjustment value is less than the preset chamber temperature adjustment value, it is determined that adjusting the heating power alone cannot meet the temperature uniformity adjustment requirements, and the local extrusion speed adjustment process needs to be initiated. During adjustment, the local extrusion speed can be adjusted downward and upward for the first chamber position corresponding to the maximum chamber temperature value and the second chamber position corresponding to the minimum chamber temperature value, respectively, with the adjustment range controlled within the range of 0.5%-2%.

[0093] It should be noted that the range of preset chamber temperature adjustment values ​​is set according to the temperature regulation efficiency requirements of the extrusion process. The value is positively correlated with the forming accuracy requirements of the profile. The higher the accuracy requirement, the smaller the preset chamber temperature adjustment value, ensuring that temperature deviations can be quickly corrected.

[0094] For example, the chamber temperature adjustment value obtained after this power adjustment is 2 degrees Celsius, and the preset chamber temperature adjustment value is 4 degrees Celsius. The difference between the two values ​​is -2 degrees Celsius. Since the difference is negative, it is determined that the chamber temperature adjustment value is less than the preset chamber temperature adjustment value, and the local extrusion speed adjustment needs to be activated.

[0095] It should be noted that the process of reducing the local extrusion speed by 0.5%-2% at the first chamber position corresponding to the maximum chamber temperature value can be achieved by moving the position of the diversion module at the diversion bridge corresponding to the first chamber position. By adjusting the metal flow rate at the diversion bridge, the metal flow rate can be adjusted. The target speed after reduction is calculated based on the current extrusion speed, and a speed adjustment command is sent to the diversion module. After the adjustment is completed, the real-time speed is collected to confirm that the adjustment range meets the requirement of 0.5%-2%.

[0096] For example, if the current local extrusion speed in the first chamber is 10 mm / s, and the adjustment range is determined to be 1%, the calculated target speed after the adjustment is 9.9 mm / s. An adjustment command is then sent to the extrusion drive module at that location. Once the speed stabilizes, the actual operating speed is confirmed to be 9.9 mm / s, and the adjustment is completed.

[0097] It should be noted that the process of increasing the local extrusion speed by 0.5%-2% at the second chamber position corresponding to the minimum chamber temperature value can be achieved by moving the position of the diversion module at the diversion bridge corresponding to the second chamber position. By adjusting the metal flow rate at the diversion bridge, the metal flow rate can be adjusted. The target speed after the increase is calculated based on the current extrusion speed, and a speed adjustment command is sent to the drive module. After the adjustment is completed, the real-time speed is collected to confirm that the adjustment range meets the requirement of 0.5%-2%.

[0098] For example, if the current local extrusion speed in the second chamber is 10 mm / s, and the adjustment range is determined to be 1%, the calculated target speed after adjustment is 10.1 mm / s. An adjustment command is then sent to the extrusion drive module at that location. Once the speed stabilizes, the actual operating speed is confirmed to be 10.1 mm / s, and the adjustment is completed.

[0099] This implementation method, after adjusting the heating power, if the maximum chamber temperature difference is still greater than the preset maximum chamber temperature difference, calculates the change in the maximum chamber temperature difference as the chamber temperature adjustment value. This can accurately identify the effect of power adjustment, clarify the degree of improvement in temperature deviation, and provide a reliable basis for subsequent adjustments.

[0100] With this implementation, when the chamber temperature adjustment value is less than the preset chamber temperature adjustment value, it means that power adjustment alone cannot effectively reduce the temperature difference. At this time, the extrusion speed adjustment process is started, which can enrich the means of adjusting the temperature deviation and avoid the problem of excessive temperature difference caused by the failure of a single adjustment method.

[0101] By implementing this method, the local extrusion speed at the first chamber position corresponding to the maximum chamber temperature value is reduced by 0.5%-2%, and the local extrusion speed at the second chamber position corresponding to the minimum chamber temperature value is increased by 0.5%-2%. This can quickly reduce the temperature difference between chambers without affecting the overall forming efficiency, and further ensure the uniformity of the parallel cooling channel forming of the battery pack aluminum alloy profile.

[0102] Figure 7 This is a schematic flowchart of the extrusion molding method for the fourth type of aluminum alloy profile for battery packs provided in this application embodiment, as shown below. Figure 7 As shown, in some implementations, the above method also includes S170 to S180, which will be described in detail below.

[0103] S170. Reduce the preset temperature adjustment power value of the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value, and increase the preset temperature adjustment power value of the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value, and then obtain the maximum chamber temperature difference value again.

[0104] Figure 8A schematic diagram illustrating the workflow of the fourth extrusion molding method for aluminum alloy profiles for battery packs provided in this application embodiment is shown below. Figure 8 As shown, in this implementation, after completing the real-time adjustment of the first heating power at the first chamber position and the real-time adjustment of the second heating power at the second chamber position, the system waits for the chamber temperature to complete heat exchange and enter a stable state before starting a new round of temperature acquisition.

[0105] It should be noted that the execution process of obtaining the maximum chamber temperature difference again is the same as the logic of obtaining the maximum chamber temperature difference for the first time. First, the temperature values ​​of all chamber locations are read according to the preset acquisition cycle. All temperature values ​​are compared and filtered to find the maximum and minimum values. Then, the difference between the two is calculated, and finally the updated maximum chamber temperature difference is obtained.

[0106] For example, after completing the power adjustment and waiting for 5 minutes, the temperature acquisition process is started. The temperature values ​​of each chamber are read as 425 degrees Celsius, 465 degrees Celsius, 500 degrees Celsius, 485 degrees Celsius, 435 degrees Celsius, and 440 degrees Celsius. All values ​​are compared, and the maximum chamber temperature value is found to be 500 degrees Celsius, and the minimum chamber temperature value is 425 degrees Celsius. The difference between the two is calculated to find that the maximum chamber temperature difference is 75 degrees Celsius, and the acquisition process is completed again.

[0107] S180. When the maximum chamber temperature difference is less than the preset maximum chamber temperature difference, obtain the real-time forming deviation index of the battery pack aluminum alloy profile. When the real-time forming deviation index is less than the preset real-time forming deviation index, reduce the preset maximum chamber temperature difference to adjust the preset maximum chamber temperature difference.

[0108] In this implementation, the newly acquired maximum chamber temperature difference can be compared with a pre-stored maximum chamber temperature difference. When the comparison result shows that the maximum chamber temperature difference is less than the pre-stored maximum chamber temperature difference, it is determined that the temperature uniformity of each chamber meets the basic process requirements, and the molding quality verification process can be initiated. Parameters of the freshly extruded battery pack aluminum alloy profile can be collected using online detection devices deployed at the extrusion die exit, obtaining corresponding real-time molding deviation indicators, providing a basis for subsequent process parameter optimization.

[0109] It should be noted that the real-time forming deviation index of the aluminum alloy profile for the battery pack includes dimensional deviation indexes, which reflect the degree of deviation between the profile's external dimensions and the design values.

[0110] For example, the real-time forming deviation indicators of aluminum alloy profiles for battery packs specifically include cross-sectional width deviation, cross-sectional height deviation, wall thickness deviation, flatness deviation, and Vickers hardness deviation. Among them, the dimensional deviation is the absolute value of the difference between the actual measured value and the design value, and the hardness deviation is the absolute value of the difference between the actual measured hardness value and the standard required hardness value.

[0111] In this implementation, the collected real-time forming deviation indicators are compared one by one with the pre-stored preset real-time forming deviation indicators. When all real-time forming deviation indicators are less than the corresponding preset real-time forming deviation indicators, it is determined that the current forming quality exceeds the basic requirements, and there is room for optimization of process parameters. At this time, the preset maximum chamber temperature difference can be dynamically adjusted to reduce the preset chamber temperature difference, improve the control standard of subsequent temperature uniformity, and further improve the forming quality of the battery pack aluminum alloy profile.

[0112] It should be noted that the types of preset real-time forming deviation indicators correspond one-to-one with the types of real-time forming deviation indicators. The value range is set according to the quality requirements corresponding to the application scenario of the battery pack aluminum alloy profile. The higher the quality requirements, the smaller the corresponding value of the preset real-time forming deviation indicator.

[0113] For example, for aluminum alloy profiles used in power battery packs for passenger vehicles, the preset range for cross-sectional width deviation is 0.05 mm to 0.1 mm, the preset range for cross-sectional height deviation is 0.05 mm to 0.1 mm, the preset range for wall thickness deviation is 0.03 mm to 0.08 mm, the preset range for flatness deviation is 0.1 mm / m to 0.2 mm / m, and the preset range for Vickers hardness deviation is 3 HV to 5 HV.

[0114] It should be noted that the process of determining whether the real-time forming deviation index is less than the preset real-time forming deviation index requires comparing each type of real-time forming deviation index with the corresponding preset real-time forming deviation index one by one. Only when all types of deviation indices meet the condition of being less than the corresponding preset value can it be determined that the triggering requirements for subsequent adjustments are met.

[0115] For example, the collected real-time forming deviation indicators are 0.06 mm for cross-section width, 0.05 mm for cross-section height, 0.04 mm for wall thickness, 0.12 mm / m for flatness, and 2 HV for Vickers hardness. The corresponding preset real-time forming deviation indicators are 0.1 mm, 0.1 mm, 0.08 mm, 0.2 mm / m, and 5 HV, respectively. All real-time deviations are less than the corresponding preset values, so the triggering conditions are met.

[0116] It should be noted that the range of the preset chamber temperature difference is determined based on the current maximum preset chamber temperature difference and the redundancy of the profile forming deviation. The adjustment range will not be too large to avoid negatively affecting the stability of the extrusion process.

[0117] For example, the current preset maximum chamber temperature difference is 20 degrees Celsius, the profile forming deviation redundancy is sufficient, the preset chamber temperature difference value ranges from 2 degrees Celsius to 5 degrees Celsius, and after adjustment, the preset maximum chamber temperature difference value is still within the reasonable range allowed by the process.

[0118] By using this method, after adjusting the heating power, the maximum chamber temperature difference is obtained again, which can promptly verify the effect of the chamber temperature difference control after power adjustment. When the maximum chamber temperature difference is less than the preset maximum chamber temperature difference, the subsequent optimization process is initiated, avoiding blindly adjusting parameters when the temperature difference does not meet the standard, and ensuring the rationality of the process.

[0119] With this implementation method, once the maximum chamber temperature difference is determined to be within the acceptable range, the real-time forming deviation index of the battery pack aluminum alloy profile is obtained. The adaptability of the current temperature difference threshold can be evaluated in conjunction with the actual forming quality, avoiding the use of temperature difference value as the sole criterion for judgment, and making parameter adjustments more in line with actual production needs.

[0120] By implementing this method, when the real-time forming deviation index is less than the preset real-time forming deviation index, the preset maximum chamber temperature difference is reduced by the preset chamber temperature difference value. This can gradually narrow the temperature difference control standard, improve the chamber temperature control accuracy under the premise of redundancy in forming quality, and further optimize the forming quality of the battery pack aluminum alloy profile.

[0121] Figure 9 This is a schematic flowchart of the fifth method for extruding aluminum alloy profiles for battery packs provided in this application embodiment, as shown below. Figure 9 As shown, in some implementations, the above method also includes S210 to S220, which will be described in detail below.

[0122] S210. Obtain multiple molding record data corresponding to multiple production batches. Cluster the multiple molding record data to obtain multiple molding record groups. Among them, the multiple molding record data includes multiple chamber temperature values, maximum chamber temperature difference, chamber heating power value, temperature regulation power value, local extrusion speed, and molding deviation index of multiple parallel cooling channels.

[0123] Figure 10 A schematic diagram of the workflow for the fifth type of extrusion molding method for aluminum alloy profiles of battery packs provided in this application embodiment is shown below. Figure 10As shown, in this implementation, the production data acquisition system of the extrusion production line can retrieve complete production process data and quality inspection data corresponding to each production batch according to the production batch division, and summarize multiple molding record data corresponding to multiple production batches. During the acquisition process, the process parameters, process control parameters and final quality indicators of each batch can be associated and stored to ensure the integrity and traceability of each molding record data, providing a basic dataset for subsequent data analysis.

[0124] It should be noted that the multiple molding record data include four types of parameters: chamber temperature, power, speed, and quality. The numerical range of each type of parameter matches the normal operating range of the extrusion process. The parameters of different batches may fluctuate reasonably depending on the characteristics of the raw materials and the condition of the equipment.

[0125] For example, the specific items and corresponding value ranges of multiple molding record data are as follows: the temperature values ​​of multiple chambers in multiple parallel cooling channels range from 380 degrees Celsius to 520 degrees Celsius; the maximum chamber temperature difference ranges from 5 degrees Celsius to 40 degrees Celsius; the chamber heating power ranges from 0 kW to 4 kW; the temperature regulation power ranges from 0.2 kW to 1 kW; the local extrusion speed ranges from 8 mm / s to 15 mm / s; and the cross-sectional width deviation in the molding deviation index ranges from 0.03 mm to 0.2 mm.

[0126] In this implementation, all collected molding record data can be imported into a preset clustering analysis component. Using the similarity of molding quality as the core clustering dimension, and combined with the distribution characteristics of process parameters, all molding record data are grouped into multiple molding record groups. The molding record data within each group have similar process parameter characteristics and molding quality performance, which can provide a basis for classification analysis for subsequent process parameter optimization and process threshold iteration.

[0127] It should be noted that the process of clustering multiple formed record data to obtain multiple formed record groups relies on an unsupervised clustering algorithm. First, the parameters of all formed record data are normalized to eliminate the differences in the dimensions of different parameters. Then, the K-means clustering algorithm is used to group the normalized data, and finally, the corresponding number of formed record groups are obtained.

[0128] For example, a total of 200 molding record data were collected. First, the parameters such as chamber temperature, heating power, local extrusion speed, and molding deviation index in all data were normalized to 0-1. The number of cluster groups was set to 4. The K-means algorithm was run to calculate and finally 4 molding record groups were obtained. The molding record data in each group had similar molding deviation levels and process parameter combinations.

[0129] S220. Determine the target molding record group to which the current extrusion molding process belongs, and determine the average temperature regulation power corresponding to the target molding record group as the preset temperature regulation power value corresponding to the current extrusion molding process.

[0130] In this implementation, the initial process parameters of the current extrusion molding process can be extracted, including the chamber temperature setpoint, target local extrusion speed, and profile type parameters. These parameters are then matched with the characteristics of each molding record group to locate the target molding record group with the highest matching degree to the current process. The temperature regulation power values ​​contained in all molding record data within the target molding record group can be statistically calculated to obtain the corresponding average temperature regulation power. This average value is then determined as the preset temperature regulation power value corresponding to the current extrusion molding process, providing a suitable parameter basis for subsequent temperature regulation.

[0131] It should be noted that the calculation process of the average temperature regulation power corresponding to the target molding record group is based on the average statistical logic. First, the temperature regulation power value is extracted from all valid molding record data in the target molding record group. After removing the outliers, all valid values ​​are summed and then divided by the number of valid values. The result is the average temperature regulation power.

[0132] For example, the target molding record group contains 50 valid molding record data. The temperature regulation power value corresponding to each data is extracted. After removing two outliers that are outside the normal range, the sum of the remaining 48 valid values ​​is 24 kilowatts. Dividing 24 kilowatts by 48 gives the average temperature regulation power of 0.5 kilowatts. This value is the preset temperature regulation power value corresponding to the current extrusion molding process.

[0133] This implementation method collects multiple molding record data corresponding to multiple production batches, covering multiple chamber temperature values ​​and maximum chamber temperature difference values ​​of multiple parallel cooling channels, etc., which are full-chain parameters. It can accumulate complete production process data, provide sufficient data support for subsequent parameter optimization, and avoid relying on experience judgment for parameter setting.

[0134] This implementation method clusters multiple molding record data to obtain multiple molding record groups, which can group production data with similar working conditions into one category, eliminate interference from differences in parameter characteristics under different working conditions, improve the accuracy of subsequent parameter matching, and avoid reference deviation caused by the mixing of data from different working conditions.

[0135] By using this method, the target molding record group to which the current extrusion molding process belongs is determined, and the average temperature regulation power corresponding to the target molding record group is taken as the preset temperature regulation power value corresponding to the current extrusion molding process. This allows the initial setting of the regulation power to conform to the optimal experience of similar working conditions, improve the efficiency and adaptability of temperature regulation, and reduce trial and error costs.

[0136] Figure 9 This is a schematic flowchart of the fifth method for extruding aluminum alloy profiles for battery packs provided in this application embodiment, as shown below. Figure 9 As shown, in some implementations, in the above-mentioned S220, determining the target molding record group to which the current extrusion molding process belongs also includes S221 to S223, which will be explained in detail below.

[0137] S221. Obtain multiple current chamber temperature values ​​and the current maximum chamber temperature difference corresponding to the current extrusion molding process. Determine the current chamber temperature characteristics corresponding to the multiple chamber temperature values ​​corresponding to the current extrusion molding process. Determine the average value of multiple chamber temperatures corresponding to multiple molding record groups, and determine the average value of multiple chamber temperatures corresponding to the average value of multiple chamber temperatures. Determine the average value of the maximum chamber temperature difference corresponding to multiple molding record groups as the average value of the maximum chamber temperature difference.

[0138] In this implementation, temperature acquisition devices deployed at various chamber locations of the extrusion die can read the temperature values ​​of all chambers during the current extrusion molding process according to a preset acquisition cycle, obtaining multiple current chamber temperature values. The maximum and minimum values ​​of these multiple current chamber temperature values ​​can be identified, and the difference between them can be calculated to obtain the current maximum chamber temperature difference, providing a real-time data foundation for subsequent feature matching and parameter calculation.

[0139] It should be noted that the current chamber temperature features can be represented by vector embedding. Each chamber location is used as a dimension of the vector, and the value of the corresponding dimension is the current temperature value of that chamber. The resulting multidimensional vector is the current chamber temperature feature, which can intuitively reflect the temperature distribution of each chamber.

[0140] For example, the extrusion die contains 14 chambers. The collected current chamber temperature values ​​are 420 degrees Celsius, 430 degrees Celsius, 470 degrees Celsius, 475 degrees Celsius, 510 degrees Celsius, 505 degrees Celsius, 490 degrees Celsius, 485 degrees Celsius, 440 degrees Celsius, 435 degrees Celsius, 400 degrees Celsius, 405 degrees Celsius, 450 degrees Celsius, and 445 degrees Celsius. A 14-dimensional vector [420, 430, 470, 475, 510, 505, 490, 485, 440, 435, 400, 405, 450, 445] is constructed according to the chamber position order. This vector is the current chamber temperature feature.

[0141] In this implementation, the chamber temperature values ​​of all molding record data within each molding record group can be statistically analyzed by location, and the average temperature of each chamber location within the group can be calculated to obtain the average temperature of multiple chambers corresponding to each molding record group. The average temperature of multiple chambers in each molding record group can then be converted into corresponding feature representations to obtain multiple chamber temperature average feature values.

[0142] In this implementation, the maximum chamber temperature difference of all molding record data in each molding record group can be statistically calculated simultaneously to obtain the corresponding average value, which is used as the average maximum chamber temperature difference.

[0143] It should be noted that the calculation process of multiple chamber temperature averages is carried out separately according to the chamber location. For each molding record group, the temperature value of the same chamber location in all molding record data within the group is extracted, summed and divided by the number of valid molding records in the group to obtain the chamber temperature average at that location. After traversing all chamber locations, multiple chamber temperature averages for the group are obtained.

[0144] For example, a molding record group contains 50 valid molding record data. For the No. 1 chamber in the feeding section, the temperature value of that position is extracted from the 50 records and summed to get 22,500 degrees Celsius. Dividing 22,500 degrees Celsius by 50 gives the average temperature of the chamber at that position as 450 degrees Celsius. The average temperature of all 14 chamber positions is calculated in turn to obtain the average temperature of the 14 chambers corresponding to the molding record group.

[0145] It should be noted that the average temperature features of multiple chambers can be represented by vector embedding. Each chamber location is taken as a dimension of the vector, and the value of the corresponding dimension is the average temperature of that chamber location. The resulting multidimensional vector is the average temperature feature of the chambers of the molding record group, which can reflect the chamber temperature distribution characteristics corresponding to the process.

[0146] For example, the average temperature values ​​of the 14 chamber locations in a certain molding recording group are 425 degrees Celsius, 425 degrees Celsius, 472 degrees Celsius, 472 degrees Celsius, 508 degrees Celsius, 508 degrees Celsius, 488 degrees Celsius, 488 degrees Celsius, 438 degrees Celsius, 438 degrees Celsius, 402 degrees Celsius, 402 degrees Celsius, 448 degrees Celsius, and 448 degrees Celsius, respectively. A 14-dimensional vector [425, 425, 472, 472, 508, 508, 488, 488, 438, 438, 402, 402, 448, 448] is constructed according to the chamber location order. This vector is the characteristic of the average chamber temperature of this group.

[0147] It should be noted that the calculation process for the average of the maximum chamber temperature difference corresponding to multiple molding record groups is performed separately for each molding record group. The maximum chamber temperature difference is extracted from all valid molding record data within the group, summed, and then divided by the number of valid molding records in that group. The result is the average of the maximum chamber temperature difference corresponding to that molding record group.

[0148] For example, a molding record group contains 50 valid molding record data. The maximum chamber temperature difference value extracted from all records is summed to get 1000 degrees Celsius. Dividing 1000 degrees Celsius by 50 gives 20 degrees Celsius. This value is the average maximum chamber temperature difference value corresponding to the molding record group.

[0149] S222. Determine the similarity between the current chamber temperature characteristics and the average characteristics of multiple chamber temperatures, as the chamber temperature difference degree corresponding to multiple molding record groups. Determine the difference between the current maximum chamber temperature difference and the average maximum chamber temperature difference, as the chamber temperature extreme value difference degree.

[0150] In this implementation, the current chamber temperature feature can be matched with the mean chamber temperature feature of each molding record group to obtain the similarity value between the two, and this value can be used as the chamber temperature difference of the corresponding molding record group.

[0151] In this implementation, the difference between the current maximum chamber temperature difference and the mean maximum chamber temperature difference for each molding record group can be calculated. The difference is used as the extreme difference degree of the chamber temperature for the corresponding molding record group. The two types of difference degrees can provide a quantitative basis for matching the target molding record group in the future.

[0152] It should be noted that the similarity between the current chamber temperature feature and the average temperature feature of multiple chambers can be calculated using the cosine similarity calculation logic. By substituting the two feature vectors into the cosine similarity formula, the calculated value is the similarity between the two. The closer the value is to 1, the higher the similarity between the two features.

[0153] For example, if the current chamber temperature feature is a 14-dimensional vector A, and the mean chamber temperature feature of a certain molding record group is a 14-dimensional vector B, substituting the two vectors into the cosine similarity formula yields a similarity value of 0.92. This value represents the similarity between the current chamber temperature feature and the mean chamber temperature feature of the group.

[0154] It should be noted that the numerical range of the temperature difference between the chambers corresponding to multiple molding record groups is 0 to 1. The closer the value is to 0, the greater the difference between the current chamber temperature distribution and the temperature distribution of the molding record group. The closer the value is to 1, the smaller the temperature distribution difference between the two and the higher the matching degree.

[0155] For example, the chamber temperature differences calculated for the current extrusion molding process and the four molding record groups are 0.72, 0.92, 0.85, and 0.68, respectively. All values ​​are in the range of 0 to 1, with 0.92 being the highest chamber temperature difference, indicating that the temperature distribution of the corresponding molding record group matches the current process the best.

[0156] For example, if the current maximum chamber temperature difference is 22 degrees Celsius and the average maximum chamber temperature difference of a certain molding recording group is 20 degrees Celsius, the difference between the two values ​​is 2 degrees Celsius. The absolute value is also 2 degrees Celsius. This value is the extreme difference of the chamber temperature of the corresponding molding recording group.

[0157] It should be noted that the numerical range of the extreme difference in chamber temperature is from 0 degrees Celsius to 20 degrees Celsius. The smaller the value, the higher the degree of matching between the current maximum chamber temperature difference and the average extreme difference of the molding record group. The larger the value, the greater the difference between the two.

[0158] For example, the extreme temperature differences of the chambers calculated by the current extrusion molding process and the four molding record groups are 8 degrees Celsius, 2 degrees Celsius, 5 degrees Celsius, and 10 degrees Celsius, respectively. All values ​​are within the range of 0 degrees Celsius to 20 degrees Celsius. Among them, 2 degrees Celsius is the smallest extreme temperature difference of the chambers, which means that the extreme difference characteristics of the corresponding molding record group have the highest matching degree with the current process.

[0159] S223. Determine the sum of the chamber temperature difference and the extreme temperature difference of multiple molding record groups, and use this sum as the multiple extrusion parameter differences corresponding to the multiple molding record groups. Determine the molding record group corresponding to the minimum extrusion parameter difference, and use this group as the target molding record group to which the current extrusion molding process belongs.

[0160] In this implementation, for each molding record group, the corresponding chamber temperature difference and chamber temperature extreme value difference are normalized and then summed. The resulting value is the extrusion parameter difference for that molding record group. The extrusion parameter difference for all molding record groups can be compared, and the group with the smallest value can be selected as the target molding record group for the current extrusion molding process, thus completing the process group matching.

[0161] It should be noted that the calculation process of the sum of the chamber temperature difference degree and the chamber temperature extreme value difference degree requires first normalizing the two types of difference degree to eliminate the difference in dimensions, and then adding the two normalized values ​​together. The result is the extrusion parameter difference degree of the corresponding molding record group.

[0162] For example, the chamber temperature difference of a certain molding record group is 0.92, and the value after normalization is 0.92. The extreme temperature difference of the chamber is 2 degrees Celsius, and the value after normalization is 0.1. Adding the two values ​​together gives 1.02, which is the extrusion parameter difference corresponding to the molding record group.

[0163] For example, the extrusion parameter differences for the four molding record groups are 1.38, 1.02, 1.15, and 1.42, respectively. All values ​​are in the range of 0 to 2. Among them, 1.02 is the smallest extrusion parameter difference, which means that the corresponding molding record group and the current extrusion process have the highest matching degree.

[0164] It should be noted that the matching rule for determining the molding record group corresponding to the minimum extrusion parameter difference as the target molding record group is that the smaller the extrusion parameter difference, the higher the overlap between the temperature distribution characteristics, extreme value difference characteristics of the current extrusion process and the historical data characteristics of the molding record group, and the stronger the adaptability of the corresponding historical process parameters. Therefore, the group corresponding to the minimum difference is selected as the target molding record group.

[0165] This implementation method extracts the current chamber temperature characteristics and the current maximum chamber temperature difference of the current extrusion molding process. At the same time, it extracts the average chamber temperature characteristics and the average maximum chamber temperature difference of each molding record group. It constructs matching features from two dimensions: overall temperature distribution and extreme value deviation, avoiding the one-sidedness of single feature matching and improving the accuracy of group matching.

[0166] This implementation method calculates the temperature difference between the current chamber temperature characteristics and the average temperature characteristics of each chamber, as well as the extreme temperature difference between the current maximum chamber temperature difference and the average temperature difference of each maximum chamber. This quantifies the degree of parameter deviation between the current operating conditions and each historical group, providing a clear quantitative basis for group matching.

[0167] This implementation method takes the sum of the chamber temperature difference and the extreme temperature difference of the chamber as the extrusion parameter difference, and defines the molding record group corresponding to the minimum extrusion parameter difference as the target molding record group. This can accurately match the historical data group that best fits the current working conditions, ensure the adaptability of the preset temperature adjustment power value, and improve the temperature adjustment efficiency.

[0168] Figure 12 This is a schematic flowchart of the extrusion molding method for the seventh type of aluminum alloy profile for battery packs provided in this application embodiment, as shown below. Figure 12 As shown, in some implementations, the above method also includes S224 to S225, which will be explained in detail below.

[0169] S224. Obtain the chamber temperature difference weight and chamber temperature extreme value difference weight corresponding to the current extrusion molding process.

[0170] In this implementation, based on the profile type and molding accuracy requirements of the current extrusion molding process, corresponding parameters are matched from a pre-stored weight configuration table to obtain the chamber temperature difference weight and chamber temperature extreme value difference weight for the current process. These two types of weights can be used for weighted calculation of subsequent extrusion parameter differences, ensuring that the difference calculation is adapted to the current process focus and improving the matching accuracy of the target molding record group.

[0171] It should be noted that the weight of the temperature difference in the chamber can be determined by empirical values, ranging from 0.4 to 0.7. The specific value is set according to the process requirements for the uniformity of the overall temperature distribution. The higher the requirements, the greater the corresponding weight value, highlighting the matching priority of the overall temperature distribution.

[0172] For example, the aluminum alloy profiles for extruded battery packs currently have a thin-walled, multi-cavity structure, which requires high uniformity of overall temperature distribution. Based on empirical values, the chamber temperature difference weight is set at 0.65, which is within the range of 0.4 to 0.7.

[0173] It should be noted that the weight of extreme temperature difference in the chamber can be determined by empirical values, ranging from 0.3 to 0.6. The specific value is set according to the process requirements for controlling the maximum temperature difference in the chamber. The higher the requirements, the greater the corresponding weight value, highlighting the matching priority of extreme temperature deviation.

[0174] For example, the aluminum alloy profiles for extruded battery packs currently have extremely high requirements for dimensional accuracy. The fluctuation of the maximum chamber temperature difference has a significant impact on dimensional accuracy. Based on empirical values, the weight of the extreme difference in chamber temperature is set to 0.35, which is within the range of 0.3 to 0.6.

[0175] S225. Determine the sum of the products of the chamber temperature difference degree and the chamber temperature difference weight of multiple molding record groups, and the products of the chamber temperature extreme value difference degree and the chamber temperature extreme value difference weight, as the difference degree of multiple extrusion parameters corresponding to multiple molding record groups.

[0176] In this implementation, for each molding record group, the product of the chamber temperature difference degree and the chamber temperature difference weight, and the product of the chamber temperature extreme value difference degree and the chamber temperature extreme value difference weight are calculated separately. The two products are then added together, and the resulting value is the extrusion parameter difference degree corresponding to that molding record group. By using a weighted summation method, the influence ratio of the two types of difference degrees can be adjusted according to the current process focus, improving the rationality of the extrusion parameter difference degree calculation and ensuring the matching accuracy of the target molding record group.

[0177] For example, the chamber temperature difference weight in the current extrusion process is 0.65, the extreme chamber temperature difference weight is 0.35, the chamber temperature difference of a certain forming record group is 0.92, and the normalized extreme chamber temperature difference is 0.1. First, calculate 0.92 multiplied by 0.65 to get 0.598, then calculate 0.1 multiplied by 0.35 to get 0.035. Add the two products together to get 0.633, which is the extrusion parameter difference corresponding to this forming record group.

[0178] This implementation method obtains the chamber temperature difference weight and chamber temperature extreme value difference weight corresponding to the current extrusion molding process. The proportion of the two types of features can be flexibly adjusted according to actual production needs to adapt to the control focus of different batches and different structures of battery pack aluminum alloy profiles, thereby improving the scenario adaptability of group matching.

[0179] By multiplying the chamber temperature difference degree and the chamber temperature difference weight, and multiplying the chamber temperature extreme value difference degree and the chamber temperature extreme value difference weight, and then summing them, the extrusion parameter difference degree can be obtained. This makes the difference degree calculation more in line with the current production control priorities, avoids matching deviations caused by fixed proportions, and improves the matching accuracy of the target molding record group.

[0180] By using this method, the target forming record group is selected based on the weighted calculation of the difference in extrusion parameters. This allows the final determined preset temperature regulation power value to better match the actual needs of the current working conditions, further improving the efficiency and accuracy of temperature regulation and ensuring the forming quality of the battery pack aluminum alloy profile.

[0181] In some implementations, the method further includes: obtaining the average molding deviation index corresponding to the target molding record group to which the current extrusion molding process belongs; and using the average molding deviation index as a preset real-time molding deviation index corresponding to the real-time molding deviation index of the current extrusion molding process.

[0182] In this implementation, after matching the target molding record group, the molding deviation index corresponding to each record can be extracted from all valid molding record data in the group. The average molding deviation index corresponding to the group of molding records is then obtained through statistical calculation. The calculated average molding deviation index can be configured as the judgment benchmark for the real-time molding deviation index of the current extrusion molding process, i.e., a preset real-time molding deviation index, providing a suitable reference standard for subsequent molding quality verification and process parameter optimization.

[0183] It should be noted that the calculation process for the average molding deviation index corresponding to the target molding record group is performed separately for each type of molding deviation index. The values ​​of the same type of deviation index are extracted from all valid records in the group, outliers are removed, the sum is calculated, and then divided by the number of valid records to obtain the average value of that type of deviation index. The average values ​​of all categories together constitute the average molding deviation index.

[0184] For example, the target molding record group contains 50 valid molding records. For the cross-sectional width deviation index, after extracting the values ​​of all records and removing 2 outliers, the sum of the remaining 48 values ​​is 2.4 mm. Dividing 2.4 mm by 48 gives 0.05 mm, which is the average value of the cross-sectional width deviation. The average value of the deviation index of all categories is calculated in turn to obtain the average molding deviation index of the group.

[0185] It should be noted that the numerical range of the average molding deviation index is positively correlated with the molding quality level of the target molding record group. The higher the molding quality of the group, the smaller the average molding deviation index value. All values ​​are within the allowable deviation range of the corresponding profile quality requirements.

[0186] For example, the target molding record group corresponds to a batch with high molding quality, and the average molding deviation indexes range as follows: the average deviation of cross-section width is 0.03 mm to 0.08 mm, the average deviation of cross-section height is 0.03 mm to 0.08 mm, the average deviation of wall thickness is 0.02 mm to 0.06 mm, the average deviation of flatness is 0.08 mm / m to 0.15 mm / m, and the average deviation of Vickers hardness is 2 HV to 4 HV.

[0187] It should be noted that the mapping rule for using the average forming deviation index as the preset real-time forming deviation index is that the average value of each type of deviation in the average forming deviation index directly corresponds to the preset real-time forming deviation index of that type of real-time forming deviation index in the current extrusion process, thereby achieving the adaptation of the preset index and the matched historical process quality level.

[0188] This implementation method obtains the average molding deviation index corresponding to the target molding record group to which the current extrusion molding process belongs. The deviation threshold can be set based on historical molding quality data under the same working conditions, avoiding the problem of overly strict or lenient threshold setting due to reliance on manual experience, and improving the rationality of the deviation judgment standard.

[0189] By using this implementation method, the average molding deviation index is used as the preset real-time molding deviation index corresponding to the real-time molding deviation index of the current extrusion molding process. This allows the deviation verification standard to fit the actual quality level of the current working conditions, avoids the problem of general thresholds not being suitable for special production scenarios, and improves the adaptability of molding quality verification.

[0190] This implementation method sets a preset real-time molding deviation index based on the matched target molding record group, which can provide an accurate judgment basis in the subsequent chamber temperature threshold optimization stage, ensuring that the threshold narrowing process does not exceed the quality tolerance range of the current working conditions, and taking into account both molding quality optimization and production stability.

[0191] Figure 13 This is a schematic flowchart of the extrusion molding method for the eighth type of aluminum alloy profile for battery packs provided in this application embodiment, as shown below. Figure 13 As shown, in some implementations, the above method also includes S226 to S227, which will be explained in detail below.

[0192] S226. Determine the maximum and minimum molding deviation indices for the parallel cooling channels at multiple chamber locations corresponding to multiple molding record data. Determine the difference between the maximum and minimum molding deviation indices corresponding to multiple chamber locations as the extreme values ​​of the molding deviation indices corresponding to the multiple molding record data.

[0193] In this implementation, the molding deviation index of the parallel cooling channel corresponding to each cavity position can be extracted from all molding record data. For each cavity position, the deviation index of that position in all records is compared, and the maximum and minimum values ​​are selected as the maximum and minimum molding deviation indices corresponding to that cavity position, respectively. The difference between the maximum and minimum molding deviation indices for each cavity position is then calculated; the difference is the extreme value of the molding deviation index corresponding to that cavity position. These values ​​for all cavity positions collectively form a set of extreme values ​​of the molding deviation index corresponding to multiple molding record data.

[0194] It should be noted that the calculation process for the difference between the maximum and minimum molding deviation indices is performed separately for each type of molding deviation index and each chamber position. First, the maximum and minimum values ​​of the same type of deviation index for the same chamber position are located in all molding records. The difference between the two is taken as the absolute value, and the result is the difference corresponding to that type of deviation index at that position.

[0195] For example, regarding the cross-sectional width deviation index corresponding to the position of the No. 3 chamber in the molding section, the values ​​of this type of index at this position in all molding records are statistically analyzed. The maximum molding deviation index is 0.12 mm and the minimum molding deviation index is 0.03 mm. The difference between the two is 0.09 mm. This value is the difference between the maximum and minimum molding deviation index of this type of deviation index at the position of the chamber.

[0196] It should be noted that the extreme value range of the molding deviation index is related to the degree of quality fluctuation of the molding record data. The greater the degree of fluctuation, the larger the corresponding value range. Usually, different categories of deviation indices correspond to different value ranges, all of which are within a reasonable range of process fluctuations.

[0197] For example, the extreme values ​​of the forming deviation index corresponding to the cross-sectional width deviation range from 0.05 mm to 0.15 mm, the extreme values ​​of the forming deviation index corresponding to the Vickers hardness deviation range from 2 HV to 6 HV, and the extreme values ​​of the forming deviation index corresponding to the flatness deviation range from 0.05 mm / m to 0.2 mm / m.

[0198] S227. Determine the mean of the extreme values ​​of the molding deviation index corresponding to multiple molding record data, and use it as the mean of the molding deviation index corresponding to multiple molding record data of the target molding record group.

[0199] In this implementation, the extreme values ​​of molding deviation indices corresponding to all chamber locations can be extracted. For each type of molding deviation index, the average of the extreme values ​​of that type of deviation across all chamber locations is calculated. The result is the average of the extreme values ​​of molding deviation indices corresponding to multiple molding record data. This average can be configured as the average of the molding deviation indices corresponding to multiple molding record data of the target molding record group, providing a reference for subsequent process parameter optimization and quality fluctuation assessment.

[0200] It should be noted that the calculation process of the mean of the extreme values ​​of the molding deviation index corresponding to multiple molding record data is performed separately for each type of molding deviation index. First, the extreme values ​​of the molding deviation index of all cavity positions under this type of deviation index are extracted, summed and then divided by the total number of cavity positions. The result is the mean value corresponding to this type of deviation index.

[0201] For example, under the cross-sectional width deviation index, there are 14 extreme values ​​of the molding deviation index corresponding to the cavity positions. The sum of all extreme values ​​is 1.12 mm. Dividing 1.12 mm by 14 gives 0.08 mm, which is the mean value of the extreme values ​​of the molding deviation index corresponding to the cross-sectional width deviation. The mean values ​​of all categories of deviation indices are calculated in turn to obtain the overall set of mean values.

[0202] It should be noted that the average value range of the molding deviation index is related to the overall quality stability of the molding record. The higher the quality stability, the smaller the corresponding value range. Different categories of deviation indexes correspond to different value ranges, all of which are within the allowable fluctuation range of the process.

[0203] For example, the average value of the forming deviation index corresponding to the cross-sectional width deviation ranges from 0.06 mm to 0.1 mm, the average value of the forming deviation index corresponding to the wall thickness deviation ranges from 0.04 mm to 0.08 mm, the average value of the forming deviation index corresponding to the Vickers hardness deviation ranges from 3 HV to 5 HV, and the average value of the forming deviation index corresponding to the flatness deviation ranges from 0.1 mm / m to 0.18 mm / m.

[0204] This implementation method calculates the difference between the maximum and minimum molding deviation indices of the parallel cooling channels at multiple chamber locations corresponding to multiple molding record data, and obtains the extreme value of the molding deviation index. This can accurately quantify the dispersion of molding quality in each chamber during a single batch of production, avoiding the problem that the average value alone cannot reflect the deviation within the batch.

[0205] By using this method, the average of the extreme values ​​of the molding deviation index corresponding to multiple molding record data is taken as the average value of the molding deviation index corresponding to multiple molding record data of the target molding record group. This can comprehensively consider the quality dispersion of multiple batches under the same working conditions, making the reference index more consistent with the quality fluctuation characteristics of actual production.

[0206] By using this implementation method, the average value of the molding deviation index obtained by the above method can be used as a reference for the preset real-time molding deviation index, which can make the quality judgment standard more reasonable. It can avoid substandard quality caused by being too loose, and also avoid unnecessary adjustment costs caused by being too strict, thus ensuring a balance between production stability and product quality.

[0207] This application also provides an aluminum alloy profile, which is manufactured by extrusion molding using the above-described extrusion molding method for battery pack aluminum alloy profiles.

[0208] The aluminum alloy profile in this embodiment is manufactured using the aforementioned extrusion molding method for battery pack aluminum alloy profiles. During the molding process, the temperature difference between each chamber can be precisely controlled by dynamically adjusting the chamber heating power and local extrusion speed, ensuring consistent molding accuracy of multiple parallel cooling channels of the aluminum alloy profile and reducing structural deviations.

[0209] In this embodiment, the production process is based on historical molding record data to match the adjustment parameters of the corresponding working conditions, so that the production process of aluminum alloy profiles is adapted to mature production experience under the same working conditions, reducing the cost of parameter trial and error in the production process, and improving the production efficiency and batch quality stability of aluminum alloy profiles. The deviation judgment threshold in the production process is dynamically optimized according to the real-time molding quality, and the control precision can be gradually improved when there is quality redundancy, so that the dimensional accuracy and structural uniformity of the molded aluminum alloy profiles are continuously optimized, better meeting the assembly and use requirements of battery packs.

[0210] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for extruding aluminum alloy profiles for battery packs, characterized in that, The method includes: The system acquires multiple chamber temperature values ​​corresponding to multiple chamber positions of the extrusion die in real time. These multiple chamber positions are used for multiple parallel cooling channels of the extruded aluminum alloy profile of the battery pack. The system determines the maximum and minimum chamber temperature values ​​among the multiple chamber temperature values. The system determines the difference between the maximum and minimum chamber temperature values ​​as the maximum chamber temperature difference. When the maximum chamber temperature difference is greater than the preset maximum chamber temperature difference, the system acquires the preset temperature regulation power value. Obtain the real-time second heating power and the maximum second heating power at the second chamber position corresponding to the minimum chamber temperature value; when the real-time second heating power is less than the maximum second heating power, decrease the preset temperature adjustment power value of the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value, and increase the preset temperature adjustment power value of the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value.

2. The method according to claim 1, characterized in that, The method further includes: When the real-time second heating power is greater than or equal to the maximum second heating power, the minimum chamber temperature value is discarded from multiple chamber temperature values, and then the minimum chamber temperature value is re-determined; the difference between the maximum chamber temperature value and the minimum chamber temperature value is determined as the maximum chamber temperature difference value; when the maximum chamber temperature difference value is greater than the preset maximum chamber temperature difference value, the preset temperature adjustment power value is determined based on the maximum chamber temperature difference value. Reacquire the real-time second heating power and maximum second heating power at the second chamber position corresponding to the minimum chamber temperature value; when the real-time second heating power is less than the maximum second heating power, decrease the preset temperature adjustment power value for the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value, and increase the preset temperature adjustment power value for the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value.

3. The method according to claim 2, characterized in that, The method further includes: After reducing the preset temperature adjustment power value of the real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value, and increasing the preset temperature adjustment power value of the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value, when the maximum chamber temperature difference is greater than the preset maximum chamber temperature difference value, the change value of the maximum chamber temperature difference is determined as the chamber temperature adjustment value. When the chamber temperature adjustment value is less than the preset chamber temperature adjustment value, the local extrusion speed at the first chamber position corresponding to the maximum chamber temperature value is reduced by 0.5%-2%, and the local extrusion speed at the second chamber position corresponding to the minimum chamber temperature value is increased by 0.5%-2%.

4. The method according to claim 3, characterized in that, The method further includes: The real-time first heating power at the first chamber position corresponding to the maximum chamber temperature value is reduced by a preset temperature adjustment power value, and the real-time second heating power at the second chamber position corresponding to the minimum chamber temperature value is increased by a preset temperature adjustment power value, and then the maximum chamber temperature difference value is obtained again. When the maximum chamber temperature difference is less than the preset maximum chamber temperature difference, the real-time forming deviation index of the aluminum alloy profile of the battery pack is obtained; when the real-time forming deviation index is less than the preset real-time forming deviation index, the preset maximum chamber temperature difference is reduced to adjust the preset maximum chamber temperature difference.

5. The method according to claim 4, characterized in that, The method further includes: Acquire multiple molding record data corresponding to multiple production batches; cluster the multiple molding record data to obtain multiple molding record groups; among them, the multiple molding record data includes multiple chamber temperature values, maximum chamber temperature difference values, chamber heating power values, temperature regulation power values, local extrusion speeds, and molding deviation indicators of multiple parallel cooling channels; Determine the target molding record group to which the current extrusion molding process belongs, and determine the average temperature regulation power corresponding to the target molding record group, which is used as the preset temperature regulation power value for the current extrusion molding process.

6. The method according to claim 5, characterized in that, Determine the target forming record group to which the current extrusion forming process belongs, including: Obtain multiple current chamber temperature values ​​and the current maximum chamber temperature difference corresponding to the current extrusion molding process; determine the current chamber temperature characteristics corresponding to the multiple chamber temperature values ​​corresponding to the current extrusion molding process, and determine the average temperature of multiple chambers corresponding to multiple molding record groups, and determine the average temperature characteristics of multiple chambers corresponding to the average temperature of multiple chambers; determine the average of the maximum chamber temperature difference corresponding to multiple molding record groups, as the average maximum chamber temperature difference; The similarity between the current chamber temperature characteristics and the average characteristics of multiple chamber temperatures is determined as the chamber temperature difference between multiple molding record groups; the difference between the current maximum chamber temperature difference and the average maximum chamber temperature difference is determined as the chamber temperature extreme value difference. The sum of the chamber temperature difference and the extreme temperature difference of multiple molding record groups is determined as the multiple extrusion parameter differences corresponding to the multiple molding record groups; the molding record group corresponding to the minimum extrusion parameter difference is determined as the target molding record group to which the current extrusion molding process belongs.

7. The method according to claim 6, characterized in that, The method further includes: Obtain the chamber temperature difference weight and chamber temperature extreme value difference weight corresponding to the current extrusion molding process; The sum of the products of the chamber temperature difference degree and the chamber temperature difference weight, and the product of the chamber temperature extreme value difference degree and the chamber temperature extreme value difference weight, is determined as the difference degree of multiple extrusion parameters corresponding to multiple molding record groups.

8. The method according to claim 7, characterized in that, The method further includes: Obtain the average molding deviation index corresponding to the target molding record group to which the current extrusion molding process belongs; use the average molding deviation index as the preset real-time molding deviation index corresponding to the real-time molding deviation index of the current extrusion molding process.

9. The method according to claim 8, characterized in that, The method further includes: Determine the maximum and minimum molding deviation indices of the parallel cooling channels at multiple chamber locations corresponding to multiple molding record data; determine the difference between the maximum and minimum molding deviation indices corresponding to multiple chamber locations as the extreme values ​​of the molding deviation indices corresponding to multiple molding record data. The mean of the extreme values ​​of the molding deviation index corresponding to multiple molding record data is determined as the mean of the molding deviation index corresponding to multiple molding record data of the target molding record group.

10. An aluminum alloy profile, characterized in that, The battery pack aluminum alloy profile is manufactured by extrusion molding using the extrusion molding method described in any one of claims 1 to 9.

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