A method for preparing an aluminum alloy battery casing

Abstract

This invention belongs to the field of metal powder manufacturing and powder metallurgy technology, and proposes a method for preparing aluminum alloy battery casings. Specifically, a bypass sampling branch is first set up at the tail gas end of the delubrication furnace, and a carbon dioxide analyzer is installed in the branch. When low-temperature desorption begins, the carbon dioxide emission value of the tail gas is monitored in real time by the carbon dioxide analyzer. Then, a temperature saturation model is constructed based on the emission value to obtain the temperature saturation index. Finally, the heating process is dynamically adjusted according to the temperature saturation index. This effectively shifts the risk of local high pressure and closed pore enrichment caused by the mismatch between the pyrolysis rate and the rate of gas expansion and pore connectivity during the heating process in the fixed temperature range method to a pre-identifiable and suppressed control event, improving the control accuracy and stability of the delubrication-to-sintering integrated process. This provides a more engineering-feasible solution for the high yield, low rework, and reusability of aluminum alloy battery casings for new energy vehicles.

Description

Technical Field

[0001] This invention belongs to the field of metal powder manufacturing and powder metallurgy technology, and specifically relates to a method for preparing an aluminum alloy battery casing. Background Technology

[0002] In the field of new energy vehicles, battery casings are extremely sensitive to airtightness, welding quality, and corrosion resistance. Stearates and other lubricants are commonly used in aluminum powder compaction. If improper decomposition or insufficient volatilization occurs in this step, it will directly cause problems such as closed pores or hydrogen and carbon residues in subsequent sintering. These residues often manifest as helium leakage failure, laser welding porosity, anodized pinholes, or decreased corrosion resistance at the end of product testing. Therefore, this delubricant removal process is very critical. Currently, the delubricant removal process commonly employs a segmented heating method with a fixed temperature range to reduce organic residues. This involves sequentially setting a low-temperature desorption section and a medium-temperature pyrolysis section in an inert atmosphere, with preset heating rates and holding times to remove the lubricant. However, this method is prone to pyrolysis and gas diffusion imbalance, i.e., a mismatch between the rates of lubricant pyrolysis and gas diffusion. This is because the process heavily relies on empirical settings and lacks real-time feedback on atmosphere composition and exhaust gas components, resulting in significant lag and inflexibility in temperature adjustment. This is especially problematic in battery casing structures with uneven density distribution or complex geometry, where narrow internal volatilization channels and increased gas exhaust resistance can easily lead to the formation of localized high-pressure and hydrogen-rich zones during the heating phase. This causes decomposition products to remain and be sealed during subsequent high-temperature sintering, resulting in closed pores or hydrocarbon inclusions. Therefore, a delubricant removal control method with dynamic adaptive capabilities is urgently needed to automatically adjust the temperature range based on real-time changes. Summary of the Invention

[0003] The purpose of this invention is to provide a method for preparing an aluminum alloy battery casing, so as to solve one or more technical problems existing in the prior art, and at least provide a beneficial option or create conditions.

[0004] To achieve the above objectives, according to one aspect of the present invention, a method for preparing an aluminum alloy battery casing is provided, the method comprising the following steps:

[0005] The pressed aluminum alloy powder battery case blank is placed into a delubrication furnace. The delubrication process in the furnace is adaptively staged to achieve delubrication treatment, resulting in a pre-sintered blank. This blank is then subjected to densification sintering and shaping to obtain the aluminum alloy battery case. The adaptive staged heating process includes the following steps for temperature adaptive configuration:

[0006] S100, a bypass sampling branch is set at the tail gas end of the delubrication furnace, and a carbon dioxide analyzer is installed in the branch;

[0007] S200: When low-temperature desorption begins, the carbon dioxide emission value of the exhaust gas is monitored in real time by a carbon dioxide analyzer.

[0008] S300 obtains the temperature saturation index by constructing a temperature saturation model based on emission values;

[0009] S400 dynamically adjusts the heating process based on the temperature range saturation index.

[0010] The delubrication furnace is equipped with atmosphere control and temperature range programming functions.

[0011] In step S100, a bypass sampling branch is set at the tail gas end of the delubrication furnace. The method for configuring a carbon dioxide analyzer in the branch is as follows: the bypass sampling branch is led out from the main exhaust pipe at the tail gas end of the delubrication furnace. The sampling port is set in the exhaust pipe that connects the main exhaust port and the furnace. It is opened 50-150mm from the exhaust port end towards the furnace along the center line of the pipe. The center axis of the sampling port intersects with the axis of the exhaust pipe. The bypass sampling branch is connected to the carbon dioxide analyzer arranged outside the furnace.

[0012] The main exhaust port end face refers to the inner edge end face flush with the flange sealing surface, located 50–150 mm upstream of the inner side of the main exhaust port flange along the pipe axis; the sampling port center axis intersects the exhaust pipe axis, and the sampling port diameter is 2–6 mm; when the structure has no flange, this end face refers to the pipe end cutting plane at the connection between the main exhaust port and the furnace.

[0013] The branch circuit includes, in sequence, a heated sampling tube with a temperature range exceeding 120°C, a 5μm filter, a constant-flow micro-vacuum pump and a needle valve to stabilize the flow rate, and a furnace maintaining a slight positive pressure of 50–150 Pa; the bypass is connected to a carbon dioxide analyzer arranged outside the furnace; the purpose of keeping the heated sampling tube at ≥120°C during operation is to suppress the hysteresis and drift of readings caused by condensation;

[0014] Preferably, micro-holes of equal length with a diameter of 1–5 mm are provided on the inner wall of each of the four corners of the workpiece's outer contour. The water flows through capillary tubes of equal length to a single collecting pipe, with the sampling port defined as the collecting pipe outlet. The collecting pipe outlet is then connected to a carbon dioxide analyzer located outside the furnace. This method is suitable for operating conditions where batch production lines exhibit significant variations.

[0015] The carbon dioxide analyzer defaults to an NDIR carbon dioxide sensor. Zero point and range calibration are performed each shift using zero gas and 0.5% vol CO2. Background baseline is acquired 2–5 minutes before heating to reduce batch-to-batch differences.

[0016] Further, in step S200, when low-temperature desorption begins, the method for real-time monitoring of the carbon dioxide emission value of the exhaust gas using a carbon dioxide analyzer is as follows: Low-temperature desorption refers to when the billet temperature reaches the preset desorption temperature, or when the control program enters the low-temperature desorption section; when low-temperature desorption begins, the carbon dioxide analyzer is activated, and the volume fraction of carbon dioxide in the exhaust gas is recorded in real time at a sampling frequency of 1–5 Hz; the volume fraction is filtered by exponential moving average according to a preset filtering time window, and the filtered volume fraction is used as the emission value.

[0017] The preset desorption temperature range is 180–240 ℃, and the preset filtering time window range is 5–10 seconds. The exponential moving average filter refers to smoothing the data by recursively applying weights to the sequence in the reverse time direction.

[0018] The carbon dioxide analyzer is zeroed and calibrated with zero gas and 0.5% vol CO2 each shift. A background baseline is acquired 2–5 minutes before heating to reduce batch-to-batch differences.

[0019] The principle behind selecting carbon dioxide monitoring lies in the fact that during the removal of organic lubricants such as stearates in aluminum powder compacts, the process involves pyrolysis, oxidation, and diffusion. The carbon elements in the lubricant are ultimately oxidized into stable products, mainly carbon dioxide, through one or more steps of reaction in the oxygen-containing microenvironment of the furnace. Compared to intermediate products such as carbon monoxide or hydrocarbons, carbon dioxide has the advantages of thermodynamic stability under process temperature and atmosphere, low probability of secondary reaction and adsorption recombination, and insensitivity to carrier gas dew point. Furthermore, since the measured emission amount approximates the carbon release flux per unit time, it serves as an effective criterion for determining whether the pyrolysis rate matches the emission capacity.

[0020] Furthermore, in step S300, the method for obtaining the temperature saturation index by constructing a temperature saturation model using emission values ​​is as follows:

[0021] Monitoring points are constructed at equal intervals, with the interval value between 5 and 10 seconds. By default, a monitoring point t is constructed every 5 seconds.

[0022] A dual sliding observation window is constructed using monitoring points: any monitoring point and its preceding Num monitoring points constitute a local dynamic observation sequence, and any monitoring point and its preceding 2Num monitoring points constitute a global trend observation sequence.

[0023] Near-field dynamic factors EMAs are extracted by applying an exponential moving average to the local dynamic observation sequence, while far-field background factors EMAl are extracted by applying an exponential moving average to the global trend observation sequence.

[0024] The ratio of the near-field dynamic factor EMAs to the far-field background factor EMAl is calculated, and the first-order differential operation is performed on this ratio along the time-series dimension of the monitoring point to obtain the near-field coupling ratio R, which characterizes the deviation strength between the local dynamic trend and the global background trend. t ;

[0025] If Rt > 0, the system is determined to have entered the activation and propagation stage. Based on the exponential decay accumulation function, the calculation model of the temperature saturation index St is mapped to the closed interval [0,1] for continuous characterization. Its specific functional form is defined as S. t =exp(-R t )S t-1 +[1-exp(-R t )]|EMAl t -EMAs t | / max(1,|EMAl t -EMAs t |);

[0026] Where S t and R t These are the temperature saturation index and the near-field coupling ratio obtained at the current monitoring point, respectively. exp() is an exponential function with the natural constant e as the base. t and t-1 represent the current monitoring point and the first monitoring point in the reverse time direction, respectively. EMAl t and EMAs t These are the near-field dynamic factor and far-field background factor of the current monitoring point, respectively; max() is the maximum value function symbol.

[0027] If Rt < 0, the system is determined to have entered the decay phase. In this state, the temperature saturation index St value will directly inherit the calculation result of the previous monitoring point, thus reflecting the continuity of the state.

[0028] If the monitored Rt value continuously falls within the critical narrow range of [0, 0.05], and this state is stably maintained across kn consecutive monitoring points, the temperature saturation index S... t All are forcibly assigned the maximum value of 1, indicating that the system has reached a saturated steady state, kn∈[3,15], and ensuring that the span of kn does not exceed 2 minutes.

[0029] Because the method of obtaining analysis results through the near-field coupling ratio uses a single ratio and its first-order rate of change to characterize the deviation intensity between the near and far fields, it is sensitive to baseline drift, short-term noise, and non-stationary disturbances in the clamping, which can lead to premature release or excessive suppression. Especially in weak carbon emission systems, thick-walled and deep-cavity structures, or cases with fluctuating carrier gas dew points, the single-point ratio and fixed critical narrow range are prone to hysteresis and fluctuation. Existing technologies cannot stably distinguish the true stages dominated by pyrolysis and migration emissions without relying on absolute magnitude. To make stage identification faster and more stable, solve the above problems, and eliminate false signals caused by local abrupt changes and baseline drift, this invention proposes a better solution as follows.

[0030] Furthermore, in step S300, the method for obtaining the temperature saturation index by constructing a temperature saturation model through emission values ​​is as follows: monitoring points are constructed at equal intervals, with the interval value being between 5 and 10 seconds, and by default, a monitoring point is constructed every 5 seconds.

[0031] If the emission value of a monitoring point is less than that of the previous and next monitoring points, it is marked as the thermal phase change critical point.

[0032] If the emission value of a thermal phase transition critical point is greater than that of the previous thermal phase transition critical point, then the set of all monitoring points between the two points constitutes a positive gradient pyrolysis activation interval; if the emission value of a thermal phase transition critical point is less than that of the previous thermal phase transition critical point, then the set of all monitoring points between the two points constitutes a negative gradient pyrolysis relaxation interval.

[0033] The previous thermal phase transition critical point refers to the previous thermal phase transition critical point in the reverse time direction.

[0034] The thermal phase transition modulus / flux transition intensity Etip between adjacent thermal phase transition critical points is defined as the absolute difference between their corresponding emission values, and its value is taken from the two thermal phase transition critical points; the absolute difference between the emission value corresponding to a thermal phase transition critical point and its previous thermal phase transition critical point is defined as the phase transition modulus.

[0035] An integer variable is preset as the integration interval zrv, zrv∈[5,10]; if zrv consecutive intervals are all positive gradient pyrolysis activation intervals, and the thermal phase transition modulus corresponding to each interval shows a strict monotonically increasing trend, then the zrv intervals are marked as activation decomposition phases, and the corresponding temperature range saturation index St is forcibly assigned to zero.

[0036] In aluminum alloy powder compacts, the lubricant undergoes thermal decomposition and volatilization as the temperature rises. The resulting carbon-containing small molecules need to expand outward along open channels and be carried away by the carrier gas. If the carbon release rate instantaneously exceeds the pore connectivity and convection emission capacity, local pressure rise and reduction enrichment will occur, inducing closed pores and subsequent welding porosity. This contradiction arises because thermal decomposition is an exponentially increasing process with temperature, while gas expansion is constrained by pore connectivity and flow field boundaries, and the two are often not synchronized. Therefore, emission values ​​sampled at equal intervals are used as the sole sample. The physical meaning of the valley point in the time series is defined as a stage transition. The intervals between valley points are divided into two categories: activation and relaxation. The former corresponds to the stage dominated by thermal decomposition, while the latter corresponds to the stage dominated by migration and emission. The difference in emission values ​​between two adjacent transition points is defined as the transition intensity to reflect the net change in the released flux during this period and to eliminate short-term noise, retaining only the stage-specific energy and material transfer characteristics.

[0037] The interval can refer to either the negative gradient pyrolysis relaxation interval or the positive gradient pyrolysis activation interval;

[0038] If all zrv consecutive intervals are negative gradient pyrolysis relaxation intervals and the thermal phase transition modulus Etip∈[0,0.5], then it is determined that it has entered the temperature range saturation phase, and the corresponding temperature range saturation index St is forcibly assigned a value of one; the instantaneous decomposition rate observation value Vt is obtained by calculating the difference between the emission value of the current monitoring point and the emission value of the previous monitoring point, and the ratio of the difference to the monitoring point interval; the maximum value of the instantaneous decomposition rate observation value of the final positive gradient pyrolysis activation interval of the activated decomposition phase is extracted as the peak dissociation rate benchmark value Vc;

[0039] The final positive gradient pyrolysis activation interval refers to the interval that is closest to the current time among the intervals marked as the activation decomposition phase;

[0040] When the observed instantaneous decomposition rate is greater than zero, the absolute deviation between the current instantaneous decomposition rate and the benchmark value of the peak dissociation rate is calculated, and a temperature-range saturation model is constructed using the sigmoid function. Its mathematical expression is St=1 / (1+exp(-|Vt-Vc| 2 / 2Vc 2 When the instantaneous decomposition rate observation value is less than or equal to zero, the temperature range saturation index value of the previous monitoring point is inherited to maintain the continuity of the index.

[0041] The temperature saturation model works by jointly judging the unidirectionality and monotonicity of transition intensity in several continuous intervals. Statistically, it confirms that the system has truly entered the relaxation stage where connectivity and emissions dominate, forcing the temperature saturation index to one. Otherwise, if continuous activation and increasing transition intensity occur, it indicates that the reaction is strengthening but the channel is not fully open, so the index is forced to zero, thus preventing the imbalance where pyrolysis exceeds emissions. The instantaneous decomposition rate is constructed using the emission change rate of adjacent monitoring points, and the maximum change rate of the most recent activation peak is used as the peak benchmark. A smooth nonlinear function maps the deviation between the two to a continuous temperature saturation. A small deviation indicates that the decomposition has matched the emission capacity, and the control system can safely advance the heating or segmentation. A large deviation indicates that there is still a risk of weak connectivity. This method avoids the dependence of traditional rigid thresholds on absolute magnitude, transforming the rate matching relationship in natural laws into a continuously adjustable control quantity.

[0042] The innovations of this process include the following dimensions: First, hierarchical modeling identifies the different dominant stages of pyrolysis and external emission, avoiding misjudging short-term fluctuations as stage transitions. Second, continuous unidirectionality and monotonic transitions are used to simultaneously filter out occasional noise, ensuring the statistical robustness of stage discrimination. Third, relative rates and nonlinear mapping are used to directly couple micro-rate matching to heating decisions, preferentially suppressing the formation of closed pores, hydrogen-rich regions, keyhole effects, and hydrocarbon inclusions. Fourth, without significantly lengthening the cycle time, delayed re-judgment provides sufficient buffer time for gas expansion and pore connectivity, which is beneficial for batch-to-batch consistent output, thus enabling engineering replication.

[0043] Since the temperature saturation index is calculated based on the terminal carbon emission flux directly observed from the exhaust carbon dioxide emission value, the pyrolysis in the delubrication stage is mapped as a real-time feedback signal. This effectively shifts the risk of local high pressure and enrichment of closed pores caused by the mismatch between the pyrolysis rate and the rate of gas expansion and pore connectivity during the heating process in the fixed temperature range method to a control event that can be predicted, identified and suppressed in advance, providing a monitoring mathematical basis for subsequent adaptive control.

[0044] Further, in step S400, the method for dynamically adjusting the heating process based on the temperature saturation index is as follows: the overflow filter window is 5-10 monitoring points, the temperature saturation index is processed by the exponential moving average of the overflow filter window to obtain the overflow filter value, and twice the overflow filter window is defined as the buffer filter window. The temperature saturation index is processed by the exponential moving average of the buffer filter window to obtain the overflow filter value. If the overflow filter value at the current moment is greater than the buffer filter value, a temperature oversaturation event is defined as occurring. When heating the advance zone, it is determined whether a temperature oversaturation event has occurred at the current measuring point. If it has, the heating action is delayed by 1-3 minutes, and the temperature oversaturation event is re-determined until it no longer occurs, at which point the heating action is executed.

[0045] In the comparison process where the overflow filter value is greater than the buffer filter value, a dimensionless margin δ is added to the criterion and hysteresis is set. The value of δ is between 0.005 and 0.02. The event is released if the overflow filter value is less than (buffer filter value - δ / 2) and lasts for more than 5 seconds.

[0046] If no valid sample is collected for more than 30 consecutive seconds, the controller will enter fail-safe control mode and will not intervene in the heating process.

[0047] When different lubrication systems or different types of lubricants cause changes in absolute magnitude, it is only necessary to adjust the dimensionless margin δ, the overflow filter window, and the delay time through trial production.

[0048] This step uses EMA to dynamically smooth the temperature saturation index, providing both the recent trend and the background baseline trend of temperature saturation. This allows for a positive deviation, i.e., a temperature oversaturation event, to occur when the lubricant pyrolysis intensifies instantaneously but emissions have not yet fully caught up. This indicates that the pyrolysis rate is higher than the emission capacity, suggesting that further accelerating the temperature rise could easily lead to the formation of closed pores and hydrogen-rich zones. Furthermore, a buffered heating program is used to provide a buffer time for gas emission and pore connectivity without significantly lengthening the cycle time, effectively reducing the risk of defects caused by temperature control lag or mismatch with exhaust.

[0049] Preferably, all undefined variables in this invention, if not explicitly defined, can be manually set thresholds.

[0050] This invention also provides a system for manufacturing an aluminum alloy battery casing. The system includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the method for manufacturing the aluminum alloy battery casing. This system can run on computing devices such as desktop computers, laptops, handheld computers, and cloud data centers. The runnable system may include, but is not limited to, processors, memory, and server clusters. The processor executes the computer program within the following system units:

[0051] The monitoring unit is used to set up a bypass sampling branch at the tail gas end of the delubrication furnace, and a carbon dioxide analyzer is installed in the branch.

[0052] The real-time monitoring unit is used to monitor the carbon dioxide emission value of the exhaust gas in real time through a carbon dioxide analyzer when low-temperature desorption begins.

[0053] The temperature saturation model calculation unit is used to construct a temperature saturation model from emission values ​​to obtain temperature saturation indices.

[0054] An adaptive control unit is used to dynamically adjust the heating process based on the temperature range saturation index.

[0055] The beneficial effects of this invention are as follows: This invention provides a method for preparing aluminum alloy battery casings, mapping the pyrolysis during the delubrication stage into a real-time feedback signal. This effectively shifts the risk of localized high pressure and pore enrichment caused by the mismatch between the pyrolysis rate and the rate of gas expansion and pore connectivity during the heating process using the fixed temperature range method to a pre-emptive, predictive, and suppressable control event. Especially under conditions of large density gradients in the pressed billet and complex rib geometry, this invention addresses the significant lag and inflexibility of traditional experience-based temperature range configuration in setting stage switching points, thus enabling microscopic-level temperature control decisions. It effectively suppresses the keyhole effect and hydrocarbon inclusions caused by premature growth of the sintering neck, significantly reducing the probability of defects such as helium leakage failure and pinholes in anodizing. At the same time, threshold-based adaptive release and rate limiting can stabilize batch-to-batch fluctuations without significantly lengthening the cycle time, improve the consistency of airtightness and weld density, and provide easily calibrated and traceable release criteria for mass production lines. It also improves the control accuracy and stability of the delubrication to sintering integrated process, providing a more engineering-feasible solution for high yield, low rework and reusability of aluminum alloy battery casings for new energy vehicles. Attached Figure Description

[0056] The above and other features of the present invention will become more apparent from the detailed description of the embodiments shown in conjunction with the accompanying drawings. In the accompanying drawings, the same reference numerals denote the same or similar elements. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort. In the drawings:

[0057] Figure 1 The diagram shows a flowchart of a method for preparing an aluminum alloy battery casing.

[0058] Figure 2 The diagram shows a structural diagram of a manufacturing system for an aluminum alloy battery casing. Detailed Implementation

[0059] The following will provide a clear and complete description of the concept, specific structure, and technical effects of the present invention in conjunction with the embodiments and accompanying drawings, so as to fully understand the purpose, solution, and effects of the present invention. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0060] like Figure 1 The diagram shows a flowchart of a method for preparing an aluminum alloy battery casing. The following section will discuss this method in conjunction with... Figure 1 This invention describes a method for preparing an aluminum alloy battery casing according to an embodiment of the present invention, the method comprising the following steps:

[0061] Example 1

[0062] The pressed aluminum alloy powder battery case blank is placed into a delubrication furnace. The delubrication process in the furnace is adaptively staged to achieve delubrication treatment, resulting in a pre-sintered blank. This blank is then subjected to densification sintering and shaping to obtain the aluminum alloy battery case. The adaptive staged heating process includes the following steps for temperature adaptive configuration:

[0063] S100, a bypass sampling branch is set at the tail gas end of the delubrication furnace, and a carbon dioxide analyzer is installed in the branch;

[0064] S200: When low-temperature desorption begins, the carbon dioxide emission value of the exhaust gas is monitored in real time by a carbon dioxide analyzer.

[0065] S300 obtains the temperature saturation index by constructing a temperature saturation model based on emission values;

[0066] S400 dynamically adjusts the heating process based on the temperature range saturation index.

[0067] In step S100, a bypass sampling branch is set at the tail gas end of the delubrication furnace. The method for configuring a carbon dioxide analyzer in the branch is as follows: the bypass sampling branch is led out from the main exhaust pipe at the tail gas end of the delubrication furnace. The sampling port is set in the exhaust pipe that connects the main exhaust port and the furnace. It is opened 100mm from the exhaust port end towards the furnace along the center line of the pipe. The center axis of the sampling port intersects with the axis of the exhaust pipe. The bypass sampling branch is connected to the carbon dioxide analyzer arranged outside the furnace.

[0068] The main exhaust port end face refers to the inner edge end face flush with the flange sealing surface, located 100mm upstream of the inner side of the main exhaust port flange along the pipe axis; the sampling port center axis intersects the exhaust pipe axis, and the sampling port diameter is 3mm; when the structure has no flange, this end face refers to the pipe end cutting plane at the connection between the main exhaust port and the furnace.

[0069] The branch circuit includes, in sequence, a heated sampling tube with a temperature range exceeding 120°C, a 5μm filter, a constant-flow micro-vacuum pump and a needle valve to stabilize the flow rate, and a furnace maintaining a slight positive pressure of 50–150 Pa; the bypass is connected to a carbon dioxide analyzer arranged outside the furnace; the purpose of keeping the heated sampling tube at ≥120°C during operation is to suppress the lag and drift of readings caused by condensation.

[0070] Preferably, micro-holes of equal length with a diameter of 3 mm are provided at the inner walls of the four corners of the workpiece's outer contour. The water flows through capillary tubes of equal length to a single collecting pipe, with the sampling port defined as the collecting pipe outlet. The collecting pipe outlet is then connected to a carbon dioxide analyzer located outside the furnace. This method is suitable for scenarios where batch production lines exhibit significant variations.

[0071] The carbon dioxide analyzer defaults to an NDIR carbon dioxide sensor. Zero point and range calibration are performed each shift using zero gas and 0.5% vol CO2. Background baseline is acquired 2–5 minutes before heating to reduce batch-to-batch differences.

[0072] Further, in step S200, when low-temperature desorption begins, the method for real-time monitoring of the carbon dioxide emission value of the exhaust gas using a carbon dioxide analyzer is as follows: Low-temperature desorption refers to when the billet temperature reaches the preset desorption temperature, or when the control program enters the low-temperature desorption section; when low-temperature desorption begins, the carbon dioxide analyzer is activated, and the volume fraction of carbon dioxide in the exhaust gas is recorded in real time at a sampling frequency of 1–5 Hz; the volume fraction is filtered by exponential moving average according to a preset filtering time window, and the filtered volume fraction is used as the emission value.

[0073] The preset desorption temperature range is 200 ℃, and the preset filtering time window range is 5 seconds. The exponential moving average filter refers to smoothing the data by recursively applying weights in the reverse time direction to the sequence.

[0074] The carbon dioxide analyzer is calibrated for zero point and range with zero gas and 0.5% vol CO2 each shift. A background baseline is acquired 2 minutes before heating to reduce batch-to-batch differences.

[0075] Furthermore, in step S300, the method for obtaining the temperature saturation index by constructing a temperature saturation model through emission values ​​is as follows: monitoring points are constructed at equal intervals, with an interval of 5 seconds.

[0076] A dual sliding observation window is constructed using monitoring points: any monitoring point and its preceding Num monitoring points constitute a local dynamic observation sequence, and any monitoring point and its preceding 2Num monitoring points constitute a global trend observation sequence.

[0077] Near-field dynamic factors EMAs are extracted by applying an exponential moving average to the local dynamic observation sequence, while far-field background factors EMAl are extracted by applying an exponential moving average to the global trend observation sequence.

[0078] The ratio of the near-field dynamic factor EMAs to the far-field background factor EMAl is calculated, and the first-order differential operation is performed on this ratio along the time-series dimension of the monitoring point to obtain the near-field coupling ratio R, which characterizes the deviation strength between the local dynamic trend and the global background trend. t ;

[0079] If Rt > 0, the system is determined to have entered the activation and propagation stage. Based on the exponential decay accumulation function, the calculation model of the temperature saturation index St is mapped to the closed interval [0,1] for continuous characterization. Its specific functional form is defined as S. t =exp(-R t )St-1 +[1-exp(-R t )]|EMAl t -EMAs t | / max(1,|EMAl t -EMAs t |);

[0080] Where S t and R t These are the temperature saturation index and the near-field coupling ratio obtained at the current monitoring point, respectively. exp() is an exponential function with the natural constant e as the base. t and t-1 represent the current monitoring point and the first monitoring point in the reverse time direction, respectively. EMAl t and EMAs t These are the near-field dynamic factor and the far-field background factor of the current monitoring point, respectively.

[0081] If Rt < 0, the system is determined to have entered the decay phase. In this state, the temperature saturation index St value will directly inherit the calculation result of the previous monitoring point, thus reflecting the continuity of the state.

[0082] If R is detected t The value consistently falls within the critical narrow range of [0, 0.05], and this state is stably maintained across kn consecutive monitoring points, indicating that the temperature saturation index S... t All values ​​are forcibly assigned the maximum value of 1, indicating that the system has reached a saturated steady state.

[0083] Further, in step S400, the method for dynamically adjusting the heating process based on the temperature saturation index is as follows: the overflow filter window consists of 10 monitoring points. The temperature saturation index is processed by the exponential moving average of the overflow filter window to obtain the overflow filter value. Twice the overflow filter window is defined as the buffer filter window. The temperature saturation index is processed by the exponential moving average of the buffer filter window to obtain the overflow filter value. If the overflow filter value at the current moment is greater than the buffer filter value, a temperature oversaturation event is defined as occurring. When heating the advance zone, it is determined whether a temperature oversaturation event has occurred at the current measuring point. If it has, the heating action is delayed by 1-3 minutes, and the temperature oversaturation event is re-determined until it no longer occurs, at which point the heating action is executed.

[0084] In the comparison process where the overflow filter value is greater than the buffer filter value, a dimensionless margin δ is added to the criterion and hysteresis is set. The value of δ is 0.005. The event is released if the overflow filter value is less than (buffer filter value - δ / 2) and lasts for more than 5 seconds.

[0085] If no valid sample is collected for more than 30 consecutive seconds, the controller will enter fail-safe control mode and will not intervene in the heating process.

[0086] When different lubrication systems or different types of lubricants cause changes in absolute magnitude, it is only necessary to adjust the dimensionless margin δ, the overflow filter window, and the delay time through trial production.

[0087] Example 2

[0088] Example 2 uses the same aluminum alloy battery casing preparation method as Example 1. The difference is that in step S300, the method for obtaining the temperature saturation index by constructing a temperature saturation model through emission values ​​is as follows: monitoring points are constructed at equal intervals, with a value taken at 5-second intervals.

[0089] If the emission value of a monitoring point is less than that of the previous and next monitoring points, it is marked as a thermal phase transition critical point. If the emission value of a thermal phase transition critical point is greater than that of the previous thermal phase transition critical point, the set of all monitoring points between the two points constitutes a positive gradient pyrolysis activation interval. If the emission value of a thermal phase transition critical point is less than that of the previous thermal phase transition critical point, the set of all monitoring points between the two points constitutes a negative gradient pyrolysis relaxation interval.

[0090] The previous thermal phase transition critical point refers to the previous thermal phase transition critical point in the reverse time direction.

[0091] The thermal phase transition modulus / flux transition intensity Etip between adjacent thermal phase transition critical points is defined as the absolute difference between their corresponding emission values, and its value is taken from the two thermal phase transition critical points; the absolute difference between the emission value corresponding to a thermal phase transition critical point and its previous thermal phase transition critical point is defined as the phase transition modulus.

[0092] An integer variable is preset as the integration interval zrv, with a value of 5. If zrv consecutive intervals are positive gradient pyrolysis activation intervals and the thermal phase transition modulus of each interval shows a strict monotonically increasing trend, then zrv intervals are marked as activation decomposition phases, and the corresponding temperature range saturation index St is forcibly assigned to zero.

[0093] The net change in flux is released and short-term noise is removed, retaining only the phased energy and matter transfer characteristics.

[0094] The interval can refer to either the negative gradient pyrolysis relaxation interval or the positive gradient pyrolysis activation interval;

[0095] If all zrv consecutive intervals are negative gradient pyrolysis relaxation intervals and the thermal phase transition modulus Etip∈[0,0.5], then it is determined that it has entered the temperature range saturation phase, and the corresponding temperature range saturation index St is forcibly assigned a value of one; the instantaneous decomposition rate observation value Vt is obtained by calculating the difference between the emission value of the current monitoring point and the emission value of the previous monitoring point, and the ratio of the difference to the monitoring point interval; the maximum value of the instantaneous decomposition rate observation value of the final positive gradient pyrolysis activation interval of the activated decomposition phase is extracted as the peak dissociation rate benchmark value Vc;

[0096] When the observed instantaneous decomposition rate is greater than zero, the absolute deviation between the current instantaneous decomposition rate and the benchmark value of the peak dissociation rate is calculated, and a temperature-range saturation model is constructed using the sigmoid function, whose mathematical expression is S. t =1 / (1+exp(-|Vt-Vc| 2 / 2Vc 2 When the instantaneous decomposition rate observation value is less than or equal to zero, the temperature range saturation index value of the previous monitoring point is inherited to maintain the continuity of the index.

[0097] Comparative Example

[0098] The comparative example uses a fixed temperature range method to achieve delubrication treatment of the battery casing blank, with the following specifications:

[0099] Alloy powder: gas-atomized Al-Mg-Si, oxygen content ≤0.20 wt%, d10≈12μm, d50≈30μm, d90≈72μm, sphericity ≥0.92.

[0100] Lubrication system: 0.6 wt% ZnSt2 zinc stearate (total powder mass percentage).

[0101] Mixing powder: V-cone mixing for 20 min, rotation speed 18 rpm, nitrogen protection.

[0102] Forming: Unidirectional cold pressing at 600 MPa, demolding angle 1.5°; key ribs are fitted with cores, and the relative density of the pressed blank is 0.88–0.91.

[0103] Component geometry: Shell outer diameter 180×125 mm, wall thickness 2.0±0.2 mm, 8 longitudinal ribs, 5 deep cavity areas.

[0104] Clamping / Loading: The open end of the blank faces upward, supported by ceramic honeycomb on a tray; 12 pieces are loaded per boat, with a layer spacing of 35 mm.

[0105] Atmosphere and pressure: N2 (purity ≥99.999%), total flow rate 25–30 L / min, furnace slightly positive pressure 80–120 Pa, dew point ≤-40 ℃.

[0106] Furnace type: Horizontal intermittent pre-firing / sintering furnace, 3 independent temperature control zones, 6 K-type thermocouples.

[0107] Batch execution: 5 boats × 12 pieces constitute one batch, and 30 batches are executed for Example 1, Example 2 and the comparative example respectively.

[0108] The difference from Examples 1 and 2 is that exhaust CO2 sampling and NDIR analysis are not performed, hysteresis, rate limiting, and propulsion zone delay re-judgment are not executed, and delubrication is completed using a fixed heating rate and a fixed holding time. The specific fixed temperature range procedure includes:

[0109] Stage 1, pre-drying, desorption of free water / light evaporation, heating rate 0.8℃ / min, target 120℃, holding for 20min, atmosphere N2 (dew point ≤ -50℃, slightly positive pressure 80–120Pa);

[0110] Stage 2, Low-temperature desorption-I, melting / initial desorption to open the connection, heating rate 0.6℃ / min, target 180℃, hold for 20min, atmosphere N2;

[0111] Stage 3, Low-temperature desorption-II, continue desorption and stabilization, increase temperature by 0.5℃ / min, target 220℃, hold for 30min, atmosphere N2;

[0112] Stage 4, gradual temperature increase to suppress the sudden transition from desorption to pyrolysis, temperature increase 0.4℃ / min, target 260℃, hold for 20 min, atmosphere N2;

[0113] Stage 5, Intermediate-temperature pyrolysis-I, metal soap pyrolysis / CO2 front rise, temperature increase 0.4℃ / min, target 300℃, hold for 30min, atmosphere N2;

[0114] Stage 6, Intertemperature pyrolysis-II, pyrolysis main peak / easiest rate mismatch, heating rate 0.3℃ / min, target 340℃, hold for 40 min, atmosphere N2;

[0115] Stage 7, Intermediate-temperature pyrolysis-III, tail-end purification / mild re-oxidation of residual carbon, heating rate 0.3℃ / min, target 380℃, hold for 45min, atmosphere N2→N2+H2 (0.5–3%, dew point ≤–40℃);

[0116] Transfer to sintering, densification, heating and holding, heating 2.0℃ / min, peak temperature 600℃, holding for 30min, furnace cold tapping in N2+H2 (3%) atmosphere.

[0117] In Examples 1, 2, and the Comparative Example, the release criteria for the aluminum alloy battery casing included: airtightness (helium testing, component level): leakage rate ≤ 5 × 10⁻⁶. -7 mbar·L / s; Batch release conditions: ≥95% of pieces meet the standards.

[0118] Welding zone holes (part level): X-CT after laser butt welding test; hole area ratio ≤ 0.40%, and maximum single hole equivalent diameter ≤ 80 μm; batch release conditions: ≥ 90% of parts meet the standards.

[0119] Anodized pinholes (batch grade): MAO inspection at 10×, ≤1 pinhole / 100 cm² per piece; Batch release condition: pinhole batch rate ≤3%.

[0120] Corrosion resistance (sampling inspection level): 72 h neutral salt spray, appearance rating ≥ B; Batch release conditions: ≥95% of sampled parts meet the B standard. Grade B implies that very slight discoloration or pinpoint loss of gloss is permissible, but blistering, peeling, pitting corrosion exposing the substrate are prohibited. The cumulative defect area on functional surfaces is ≤0.5%, and the diameter of a single defect point is ≤0.3 mm; the cumulative defect area on non-functional surfaces is ≤1.0%.

[0121] Table 1

[0122]

[0123] Table 1 shows a comparison of the effects of this method before and after its application in the preparation of aluminum alloy battery casings. The batch release rate represents the proportion of production batches that meet all conformity criteria and are approved for shipment under the established NQS release standards, out of all inspected batches. The helium leak rate compliance rate refers to the proportion of products within the batch that meet the helium leak rate threshold at the component level out of all inspected pieces. The weld hole compliance rate refers to the proportion of qualified pieces in the batch where, after laser butt welding and X-CT evaluation, the hole area ratio does not exceed the limit and the maximum single hole size does not exceed the specified upper limit. The pinhole batch rate refers to the proportion of production batches where pinhole defects exceeding the limit are observed after anodizing, out of all batches. The 72h salt spray rating ≥B percentage refers to the proportion of sampled pieces in the batch that achieve an appearance rating of B or higher after a 72-hour neutral salt spray test. The key performance indicator (Ppk) is a process capability index for part-level critical quality characteristics (specifically, leakage rate and void area ratio). It comprehensively reflects the deviation and variation level of the process mean relative to the specification center. A higher value indicates a more stable process and less prone to exceeding tolerances. Oversaturation trigger and suppression count refers to the average number of times that oversaturation is detected during the delubrication control process, triggering suppression actions such as speed reduction or temperature control. This is counted on a batch basis.

[0124] The comparative example, lacking online emission criteria and suppression delay mechanisms, continued to advance the temperature range in sections where pyrolysis was instantaneously enhanced and connectivity was not fully opened, significantly increasing the probability of forming closed pores and hydrogen-rich zones. This resulted in deterioration of airtightness and welding performance, with a batch release rate of only 63%, Ppk less than 1.33, and low process stability.

[0125] Example 1 constructs a continuous St using near-field and far-field dual EMA, which is insensitive to short-term noise and baseline drift. It only triggers deceleration and isothermal control when the deviation from the trend becomes persistent, resulting in the lowest defect rate and minimal cycle time cost. It suppresses noise and drift, significantly improving part-level compliance and Ppk, achieving an 87% batch release rate with a milder cycle time cost of only 0.3 minutes. Example 2 robustly identifies activation and relaxation intervals using structured evidence of critical points and transition strengths, and incorporates delayed re-judgment, making it more sensitive and reliable under unfavorable geometries such as deep cavities and rib locations.

[0126] As can be seen from the examples, incorporating the principle of matching reaction rate with external emission capacity into delubrication control is key to improving the airtightness, welding, and anodizing quality of aluminum alloy battery casings.

[0127] An embodiment of the present invention provides a manufacturing system for an aluminum alloy battery casing, such as... Figure 2 The diagram shows a structural diagram of an aluminum alloy battery casing fabrication system according to the present invention. The aluminum alloy battery casing fabrication system of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the above-described embodiment of the aluminum alloy battery casing fabrication method.

[0128] The system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program in units of the following system:

[0129] The monitoring unit is used to set up a bypass sampling branch at the tail gas end of the delubrication furnace, and a carbon dioxide analyzer is installed in the branch.

[0130] The real-time monitoring unit is used to monitor the carbon dioxide emission value of the exhaust gas in real time through a carbon dioxide analyzer when low-temperature desorption begins.

[0131] The temperature saturation model calculation unit is used to construct a temperature saturation model from emission values ​​to obtain temperature saturation indices.

[0132] An adaptive control unit is used to dynamically adjust the heating process based on the temperature range saturation index.

[0133] The aluminum alloy battery casing fabrication system described above can run on computing devices such as desktop computers, laptops, handheld computers, and cloud servers. The system that can run on the aluminum alloy battery casing fabrication system may include, but is not limited to, processors and memory. Those skilled in the art will understand that the example described is merely an illustration of an aluminum alloy battery casing fabrication system and does not constitute a limitation on such a system. It may include more or fewer components, or a combination of certain components, or different components. For example, the aluminum alloy battery casing fabrication system may also include input / output devices, network access devices, buses, etc.

[0134] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the aluminum alloy battery casing fabrication system, connecting various parts of the system via various interfaces and lines.

[0135] The memory can be used to store the computer programs and / or modules. The processor, by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory, realizes various functions of the aluminum alloy battery casing manufacturing system. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0136] Although the invention has been described in considerable detail and particularly with regard to several of the described embodiments, it is not intended to limit itself to any of these details or embodiments or any particular embodiment, thereby effectively covering the intended scope of the invention. Furthermore, the invention has been described above with respect to embodiments foreseeable by the inventors in order to provide a useful description, and non-substantial modifications to the invention that have not yet been foreseen may still represent equivalent modifications.

Claims

1. A method of producing an aluminum alloy battery case, characterized by, The method comprises the following steps: placing the pressed aluminum alloy powder battery shell blank into a de-lubricating furnace, realizing de-lubricating treatment of the battery shell blank through an adaptive staged temperature rising process of the de-lubricating furnace, obtaining a pre-fired blank, and obtaining the aluminum alloy battery shell through densification sintering and shaping treatment; wherein the step of adaptively configuring the temperature in the adaptive staged temperature rising process comprises: S100, a bypass sampling branch is arranged at the tail gas end of the de-lubricating furnace, and a carbon dioxide analyzer is arranged in the bypass sampling branch; S200, when low-temperature desorption starts, the discharge value of the tail gas carbon dioxide is monitored in real time through the carbon dioxide analyzer; S300, a temperature-saturation model is constructed through the discharge value to obtain a temperature-saturation index; S400, the temperature rising process is dynamically adjusted according to the temperature-saturation index; In step S300, the method of obtaining the temperature-saturation index by constructing the temperature-saturation model through the discharge value is: equally interval monitoring points are constructed, a double sliding observation window is constructed through the monitoring points: a local dynamic observation sequence is formed by intercepting any monitoring point and the previous Num monitoring points, and a global trend observation sequence is formed by any monitoring point and the previous 2Num monitoring points; By applying exponential moving average operation to the local dynamic observation sequence to extract near-field dynamic factor EMAs, and applying exponential moving average operation to the global trend observation sequence to extract far-field background factor EMAl; the ratio of the near-field dynamic factor EMAs and the far-field background factor EMAl is calculated, and a first-order differential operation is performed on the ratio along the time sequence dimension of the monitoring point to obtain the near-far field coupling ratio R representing the deviation intensity of the local dynamic trend and the global background trend t ; If Rt>0, it is determined that the system enters the activation promotion phase, and the calculation model of the temperature saturation index St is mapped into the closed interval [0, 1] for continuous characterization based on an exponential decay accumulation function, and the specific function form is defined as S t =exp(-R t )S t-1 +[1-exp(-R t )]|EMAl t -EMAs t | / max(1,|EMAl t -EMAs t |); if Rt<0, it is determined that the system enters the decay subsidence phase, and the temperature saturation index St value in this state directly inherits the calculation result of the previous monitoring point, thereby embodying the persistence of the state; In step S400, the method of dynamically adjusting the temperature rising process according to the temperature-saturation index is: the overflow filter window is 5-10 monitoring points, the temperature-saturation index is subjected to exponential moving average filter processing of the overflow filter window to obtain an overflow filter value, the buffer filter window is defined as twice the overflow filter window, the temperature-saturation index is subjected to exponential moving average filter processing of the buffer filter window to obtain a buffer filter value, and if the current time overflow filter value is greater than the buffer filter value, it is defined that a temperature-saturation oversaturation event occurs; when the temperature rising in the advancing zone is judged whether the current monitoring point occurs the temperature-saturation oversaturation event, if it occurs, the temperature rising action is delayed for 1-3 minutes, and then it is re-judged whether the temperature-saturation oversaturation event occurs, until the temperature-saturation oversaturation event does not occur, and then the temperature rising action is performed.

2. The method of making an aluminum alloy battery case of claim 1, wherein, In step S100, the method of arranging the bypass sampling branch at the tail gas end of the de-lubricating furnace and arranging the carbon dioxide analyzer in the bypass sampling branch is: a bypass sampling branch is introduced from the total exhaust pipe at the tail gas end of the de-lubricating furnace, the sampling port is arranged in the exhaust pipeline connected with the main exhaust port and the furnace chamber, and is opened at a position of 50-150 mm from the main exhaust port end surface to the furnace chamber along the pipeline center line; the center axis of the sampling port intersects with the axis of the exhaust pipe; and the bypass sampling branch is communicated with the carbon dioxide analyzer arranged outside the furnace.

3. The method of making an aluminum alloy battery case of claim 1, wherein, In step S200, when low-temperature desorption starts, the method of monitoring the discharge value of the tail gas carbon dioxide in real time through the carbon dioxide analyzer is: low-temperature desorption refers to when the blank temperature reaches a preset desorption temperature, or the control program enters the low-temperature desorption section; when the low-temperature desorption starts, the carbon dioxide analyzer is started, the volume fraction of the tail gas carbon dioxide is recorded in real time at a sampling frequency of 1-5 Hz; the volume fraction is subjected to exponential moving average filter processing according to a preset filter time window, and the filtered volume fraction is taken as the discharge value.

4. The method of making an aluminum alloy battery case of claim 1, wherein, In step S300, the method of obtaining the temperature and concentration saturation index by constructing the temperature and concentration saturation model through the emission value can be replaced by: constructing monitoring points at equal intervals, and marking a monitoring point as a thermal phase change critical point when the emission value of the monitoring point is less than that of the previous and next monitoring points; If the emission value of a thermal phase change critical point is greater than that of the previous thermal phase change critical point, then the set of all monitoring points between the two points constitutes a positive gradient thermal decomposition activation interval; if the emission value of a thermal phase change critical point is less than that of the previous thermal phase change critical point, then the set of all monitoring points between the two points constitutes a negative gradient thermal decomposition relaxation interval; The thermal phase change transition modulus / flux transition strength Etip between adjacent thermal phase change critical points is defined as the absolute difference between the corresponding emission values of the two thermal phase change critical points, and the value is taken as the two thermal phase change critical points; the absolute difference between the corresponding emission values of a thermal phase change critical point and the previous thermal phase change critical point is defined as the phase change transition modulus; A preset integer variable is denoted as integration interval zrv, if the continuous zrv intervals are all positive gradient thermal decomposition activation intervals, and the thermal phase change transition modulus corresponding to each interval presents a strictly monotonic increasing, then the zrv intervals are marked as activation decomposition phase, and the corresponding temperature and concentration saturation index St is forced to be assigned a value of zero; If the continuous zrv intervals are all negative gradient thermal decomposition relaxation intervals, and the thermal phase change transition modulus Etip is in the range of [0, 0.5], then it is determined that the temperature and concentration saturation phase is entered, and the corresponding temperature and concentration saturation index St is forced to be assigned a value of one; the instantaneous decomposition rate observation value Vt is obtained by calculating the difference between the emission values of the current monitoring point and the previous monitoring point, and the ratio of the interval length between the monitoring points; the maximum value of the instantaneous decomposition rate observation value of the final positive gradient thermal decomposition activation interval of the activation decomposition phase is extracted as the peak dissociation rate reference value Vc; When the instantaneous decomposition rate observation value is greater than zero, the absolute deviation of the current instantaneous decomposition rate and the peak dissociation rate reference value is calculated, and a temperature saturation model is constructed by a sigmoid function, which is mathematically expressed as St=1 / (1+exp(-|Vt-Vc 2 / 2Vc 2 ));When the instantaneous decomposition rate observation value is less than or equal to zero, the temperature saturation index value of the previous monitoring point is inherited.

5. A system for producing an aluminum alloy battery case, characterized by comprising: The preparation system of the aluminum alloy battery shell includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the preparation method of the aluminum alloy battery shell according to any one of claims 1-4 are implemented. The preparation system of the aluminum alloy battery shell is run in a desktop computer, a notebook computer, a palm computer, and a cloud data center computing device.

Images