Low-vibration low-noise lightweight air conditioner compressor shell precision stamping process

Abstract

The application discloses a low-vibration low-noise lightweight air conditioner compressor shell precision stamping process and relates to the technical field of air conditioner compressor shell manufacturing. The application collects dynamic contact stress signals of a contact area between a plate and a die in a drawing process, constructs dynamic stress characteristic parameters, and calculates an acoustic risk index by using the dynamic stress characteristic parameters and a drawing stroke position parameter, so that a blank holder force control process can be adjusted according to target frequency band vibration risks. Further, blank holder force modulation parameters are generated according to the acoustic risk index, and the blank holder force modulation parameters are used to control multiple blank holder subareas to form dynamic blank holder forces with phase differences, so that the plate produces circumferential differential material flow, thereby forming a gradient wall thickness structure. Then, a residual risk index is constructed by using a wall thickness gradient index and the acoustic risk index, and a microstructure array is formed according to the residual risk index, so that the vibration radiation capacity of the target frequency band is effectively reduced without increasing the weight of the shell.

Description

Technical Field

[0001] This invention relates to the field of air conditioner compressor housing manufacturing technology, and in particular to a precision stamping process for a low-vibration, low-noise, lightweight air conditioner compressor housing. Background Technology

[0002] Air conditioner compressor housings are typically manufactured from thin sheet metal through deep drawing. With the development of inverter and high-efficiency air conditioners, compressor housings are increasingly trending towards lighter weight and thinner walls. However, during the deep drawing process for thin-walled housings, the contact state between the sheet metal and the die continuously changes. Fluctuations in blank holder force, uneven material flow, and changes in the die contact state all lead to differentiated plastic deformation in different areas of the sheet metal, thus affecting the final wall thickness distribution of the housing.

[0003] Existing research primarily focuses on forming quality control during the deep drawing process, such as preventing cracking, wrinkling, and wall thickness reduction. However, there is limited research on the correlation between dynamic contact stress changes during deep drawing and the vibration radiation performance of the formed shell. In actual production, it has been found that even shells meeting dimensional accuracy requirements may exhibit high vibration radiation capabilities in the target frequency band during compressor operation, leading to increased overall machine noise. Current processes typically address this by increasing shell thickness, adding damping materials, or incorporating post-processing steps. However, this not only increases material consumption but also hinders lightweight design. Therefore, how to reduce the target frequency band vibration radiation capability of the shell through stamping process control and subsequent surface microstructure modulation without increasing shell weight has become a pressing technical problem in this field. Summary of the Invention

[0004] The purpose of this invention is to provide a precision stamping process for a low-vibration, low-noise, lightweight air conditioning compressor housing. By establishing the correlation between dynamic contact stress characteristics and acoustic risks, the blank holder force during the deep drawing process is actively controlled. Furthermore, by combining gradient wall thickness structure and microstructure array to synergistically optimize the housing vibration characteristics, the vibration radiation capability of the target frequency band is reduced.

[0005] This invention proposes a precision stamping process for a low-vibration, low-noise, lightweight air conditioner compressor housing, comprising the following steps:

[0006] S1. Collect dynamic contact stress signals in the contact area between the sheet metal and the die during the deep drawing process, and obtain dynamic stress characteristic parameters F based on the dynamic contact stress signals;

[0007] S2. Calculate the acoustic risk index R corresponding to the target frequency band based on the dynamic stress characteristic parameter F and the current drawing stroke position parameter T, and generate the blank holder force modulation parameter P based on the acoustic risk index R.

[0008] S3. According to the blank holder force modulation parameter P, control multiple blank holder zones to output dynamic blank holder forces with phase differences, so that the sheet material forms a circumferentially differentiated flow and constructs a gradient wall thickness structure.

[0009] S4. Obtain the wall thickness distribution data corresponding to the gradient wall thickness structure, calculate the wall thickness gradient index G based on the wall thickness distribution data, and obtain the residual risk index M by combining the acoustic risk index R.

[0010] S5. Generate surface microstructure processing parameters based on the residual risk index M, and form a microstructure array on the shell surface, so that the gradient wall thickness structure and the microstructure array work together to reduce the vibration radiation capability of the target frequency band.

[0011] Preferably, step S1 includes:

[0012] S101, The contact area between the sheet metal and the mold includes the die opening area and the pressing edge area;

[0013] Pressure sensors are installed in the contact area between the sheet metal and the mold to collect dynamic contact stress signals.

[0014] S102. Perform frequency domain analysis on the dynamic contact stress signal to extract the dominant frequency f, stress fluctuation amplitude A and phase angle φ corresponding to the dynamic contact stress signal.

[0015] S103. Construct dynamic stress characteristic parameters F based on the dominant frequency f, amplitude A, and phase φ.

[0016] Preferably, the dynamic stress characteristic parameters in step S103 satisfy:

[0017] F = A × f × cosφ;

[0018] Where: F represents the dynamic stress characteristic parameter, A represents the stress fluctuation amplitude, f represents the dominant frequency, and φ represents the phase angle.

[0019] Preferably, step S2 includes:

[0020] S201. Obtain the current drawing stroke position parameter T;

[0021] S202. Calculate the acoustic risk index R based on the dynamic stress characteristic parameter F and the drawing stroke position parameter T.

[0022] S203. Generate the edge clamping force modulation parameter P based on the acoustic risk index R;

[0023] In step S202, the acoustic risk index satisfies the following:

[0024] R = αF + βT;

[0025] in:

[0026] The values ​​of α and β are obtained using the entropy weight method.

[0027] Preferably, in step S203, the blank holder force modulation parameter P is generated based on the acoustic risk index R, as follows:

[0028] The blank holder force compensation amplitude ΔA and blank holder force compensation phase Δφ are calculated based on the acoustic risk index R. The blank holder force compensation amplitude ΔA satisfies ΔA=k1×R, and the blank holder force compensation phase Δφ satisfies Δφ=k2×R. The values ​​of k1 and k2 are obtained by grid search method. The blank holder force compensation amplitude ΔA and blank holder force compensation phase Δφ are combined to form the blank holder force modulation parameter P, i.e., P=(ΔA,Δφ).

[0029] As an explanation, the values ​​of k1 and k2 are obtained through a grid search method. For example, k1 and k2 are discretely selected within a preset range; the noise reduction of the target frequency band corresponding to different combinations is calculated; and the parameter combination with the largest noise reduction of the target frequency band is selected as the final k1 and k2.

[0030] Preferably, step S3 includes:

[0031] S301. Divide the pressing area into multiple independent control areas along the circumferential direction, and use the independent control areas as pressing partitions; distribute the pressing force modulation parameter P to the multiple pressing partitions.

[0032] S302. Control each pressing zone to output a dynamic pressing force with a phase difference. The dynamic pressing force acts on the sheet to drive the sheet to generate circumferentially differentiated material flow along the circumferential direction, so that the material inflow amount at different circumferential positions of the sheet is different.

[0033] S303. Based on the difference in material inflow at different circumferential positions, different wall thickness values ​​are formed at different circumferential positions of the shell, and the different wall thickness values ​​are continuously varied along the circumference to form a gradient wall thickness structure.

[0034] In step S302, target output phases corresponding to multiple pressing partitions are generated based on the pressing force compensation phase Δφ, and multiple pressing partitions are controlled to output dynamic pressing force according to their respective target output phases, so that a phase difference is formed between adjacent pressing partitions.

[0035] Preferably, the phase difference formed between adjacent pressing sections in step S302 is 30° to 180°;

[0036] Preferably, the phase difference of the pressure waveform between adjacent pressure zones is 90°.

[0037] Preferably, step S4 includes:

[0038] S401. Determine the maximum wall thickness tmax, minimum wall thickness tmin, and average wall thickness tavg based on the wall thickness distribution data.

[0039] S402. Calculate the wall thickness gradient exponent G based on the maximum wall thickness tmax, the minimum wall thickness tmin, and the average wall thickness tavg.

[0040] S403. Calculate the residual risk index M based on the acoustic risk index R and the wall thickness gradient index G.

[0041] Preferably, the wall thickness gradient exponent in step S402 satisfies:

[0042] G = (tmax − tmin) / tavg;

[0043] The residual risk index in step S403 satisfies:

[0044] M = R × (1 − G).

[0045] Preferably, step S5 includes:

[0046] S501, Surface microstructure processing parameters include microstructure array processing area and microstructure array processing density;

[0047] S502. Determine the microstructure array processing area and microstructure array processing density based on the residual risk index M.

[0048] S503, the microstructure array processing area and the microstructure array processing density form a microstructure array;

[0049] Gradient wall thickness structures are used to reduce vibration propagation uniformity; microstructure arrays are used to increase vibration scattering; and the synergistic effect of gradient wall thickness structures and microstructure arrays is used to reduce vibration radiation capability in the target frequency band.

[0050] In S502, the fabrication area and fabrication density of the microstructure array are determined based on the residual risk index M, as follows:

[0051] The shell surface is divided into multiple surface unit regions of equal area, and the corresponding residual risk index M is calculated for each surface unit region.

[0052] Arrange the residual risk indices M corresponding to all surface unit regions in descending order of their numerical values, and calculate the contribution ratio of the residual risk index M corresponding to each surface unit region to the total residual risk index of all surface unit regions.

[0053] The contribution ratios are accumulated sequentially according to the descending order of the results until the cumulative contribution ratio reaches a preset cumulative ratio. The surface unit regions that participate in the cumulative contribution ratio reaching the preset cumulative ratio are determined as microstructure array processing regions.

[0054] For a given microstructure array processing area, the microstructure array processing density ρ of the corresponding area is determined based on the ratio between the residual risk index M of the corresponding surface unit area and the maximum residual risk index M_max of all processing areas.

[0055] The fabrication density ρ of the microstructure array satisfies:

[0056] ;

[0057] Where ρ0 represents the basic processing density and ρmax represents the maximum processing density;

[0058] The larger the residual risk index M corresponding to a certain processing area, the larger the microstructure array processing density ρ corresponding to that processing area; the smaller the residual risk index M corresponding to a certain processing area, the smaller the microstructure array processing density ρ corresponding to that processing area.

[0059] The microstructure array processing parameters are generated based on the microstructure array processing density ρ corresponding to each processing area.

[0060] The precision stamping process for low-vibration, low-noise, and lightweight air conditioner compressor housing proposed in this invention has the following beneficial technical effects:

[0061] This invention collects dynamic contact stress signals from the contact area between the sheet metal and the die during deep drawing, constructs dynamic stress characteristic parameters F, and calculates the acoustic risk index R using the dynamic stress characteristic parameters F and the deep drawing stroke position parameter T. This allows the blank holder force control process to be adjusted to address vibration risks in the target frequency band. Furthermore, a blank holder force modulation parameter P is generated based on the acoustic risk index R, and this parameter P is used to control multiple blank holder zones to form dynamic blank holder forces with phase differences, causing circumferentially differentiated material flow in the sheet metal, thereby forming a gradient wall thickness structure. Subsequently, a residual risk index M is constructed using the wall thickness gradient index G and the acoustic risk index R, and a microstructure array is formed based on the residual risk index M. The placement and density of the microstructure array are matched with the vibration risk distribution of the shell, thus achieving a synergistic effect between deep drawing process control and surface structure optimization. This effectively reduces the vibration radiation capability in the target frequency band without increasing the shell weight, balancing lightweight and low noise requirements. Attached Figure Description

[0062] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0063] Embodiments of the present invention are described in detail below. Examples of these embodiments are illustrated in the accompanying drawings, wherein the same or similar symbols denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0064] like Figure 1 The precision stamping process for a low-vibration, low-noise, lightweight air conditioner compressor housing, as shown, includes the following steps:

[0065] S1. Collect dynamic contact stress signals in the contact area between the sheet metal and the die during the deep drawing process, and obtain dynamic stress characteristic parameters F based on the dynamic contact stress signals;

[0066] S2. Calculate the acoustic risk index R corresponding to the target frequency band based on the dynamic stress characteristic parameter F and the current drawing stroke position parameter T, and generate the blank holder force modulation parameter P based on the acoustic risk index R.

[0067] S3. According to the blank holder force modulation parameter P, control multiple blank holder zones to output dynamic blank holder forces with phase differences, so that the sheet material forms a circumferentially differentiated flow and constructs a gradient wall thickness structure.

[0068] S4. Obtain the wall thickness distribution data corresponding to the gradient wall thickness structure, calculate the wall thickness gradient index G based on the wall thickness distribution data, and obtain the residual risk index M by combining the acoustic risk index R.

[0069] S5. Generate surface microstructure processing parameters based on the residual risk index M, and form a microstructure array on the shell surface.

[0070] Gradient wall thickness structures are used to reduce vibration propagation uniformity; microstructure arrays are used to increase vibration scattering; and the synergistic effect of gradient wall thickness structures and microstructure arrays is used to reduce vibration radiation capability in the target frequency band.

[0071] In one optional embodiment, the manufacturing process of a variable frequency air conditioner compressor housing is described as an example. The housing material is a cold-rolled steel plate with a thickness of 0.45mm, which is deep-drawn by a servo press.

[0072] Step S1

[0073] Pressure sensors are installed in the die opening area and the blank holder area respectively.

[0074] During the deep drawing process, the pressure sensor collects the dynamic contact stress signal in the contact area between the sheet metal and the die in real time.

[0075] Fast Fourier Transform analysis was performed on the dynamic contact stress signal to extract the dominant frequency f, stress fluctuation amplitude A, and phase angle φ.

[0076] The dynamic stress characteristic parameter F is calculated according to the following formula:

[0077] F = A × f × cosφ;

[0078] Where: F represents the dynamic stress characteristic parameter, A represents the stress fluctuation amplitude, f represents the dominant frequency, and φ represents the phase angle.

[0079] For example:

[0080] A = 1.8 MPa;

[0081] f = 42Hz;

[0082] φ = 30°;

[0083] Then the corresponding dynamic stress characteristic parameter F is obtained.

[0084] Step S2

[0085] Obtain the current drawing stroke position parameter T.

[0086] The acoustic risk index R is calculated based on the dynamic stress characteristic parameter F and the drawing stroke position parameter T:

[0087] R = αF + βT;

[0088] in:

[0089] The values ​​of α and β are obtained using the entropy weight method.

[0090] Specifically:

[0091] The influence of dynamic stress characteristic parameter F and drawing stroke position parameter T on the target frequency band noise variation in historical samples was statistically analyzed.

[0092] Calculate the corresponding weights based on the information entropy of each indicator;

[0093] Obtain α and β.

[0094] Subsequently, the blank holder force compensation amplitude ΔA and blank holder force compensation phase Δφ are calculated based on the acoustic risk index R:

[0095] ΔA = k1 × R;

[0096] Δφ = k² × R;

[0097] k1 and k2 are determined using a grid search method.

[0098] Within a preset range, k1 and k2 are discretely selected;

[0099] Calculate the noise reduction in the target frequency band corresponding to different parameter combinations;

[0100] The parameter combination that maximizes the noise reduction in the target frequency band is selected as the final parameter.

[0101] Then it forms:

[0102] P=(ΔA,Δφ).

[0103] Step S3

[0104] The pressing area is divided into four independent control areas along the circumference, which are used as four pressing zones.

[0105] The blank holder force modulation parameter P is assigned to each blank holder zone.

[0106] The target output phase corresponding to each blank holder partition is generated based on the blank holder force compensation phase Δφ.

[0107] Control each blank holder zone to output dynamic blank holder force according to the target output phase.

[0108] In one embodiment:

[0109] The phase difference of the pressure waveform between adjacent pressure zones is 90°.

[0110] When dynamic blank holder force is applied to the sheet metal, different material inflow amounts occur at different circumferential positions.

[0111] Areas with a large material inflow rate form larger local wall thickness values;

[0112] Areas with smaller material inflow rates result in smaller local wall thickness values.

[0113] As the circumferential position changes, the wall thickness value changes continuously, thus forming a gradient wall thickness structure.

[0114] Step S4

[0115] Obtain the wall thickness distribution data after the shell is formed.

[0116] Sure:

[0117] Maximum wall thickness tmax;

[0118] Minimum wall thickness tmin;

[0119] Average wall thickness tavg.

[0120] The wall thickness gradient exponent G is calculated using the following formula:

[0121] G = (tmax − tmin) / tavg;

[0122] Subsequently, the residual risk index M is calculated based on the acoustic risk index R and the wall thickness gradient index G:

[0123] M=R(1-G)

[0124] The residual risk index M is used to characterize the level of vibration risk in the target frequency band that the current shell still retains.

[0125] Step S5

[0126] Surface microstructure processing parameters include the microstructure array processing area and the microstructure array processing density.

[0127] The shell surface is divided into multiple surface unit regions of equal area.

[0128] The residual risk index M is calculated for each surface unit region.

[0129] Sort by residual risk index M from largest to smallest.

[0130] The contribution ratio of the residual risk index corresponding to each surface unit region is accumulated sequentially.

[0131] When the cumulative contribution ratio reaches the preset cumulative ratio, the corresponding surface unit area will be determined as the microstructure array processing area.

[0132] Subsequently, the microstructure array processing density ρ was determined based on the residual risk index M corresponding to each processing area.

[0133] ;

[0134] in:

[0135] ρ0 is the base processing density;

[0136] ρmax is the maximum processing density;

[0137] Mmax is the maximum residual risk index in the processing area.

[0138] Finally, the microstructure array is formed based on the microstructure array processing area and the microstructure array processing density, thus completing the shell processing.

[0139] This invention collects dynamic contact stress signals from the contact area between the sheet metal and the die during deep drawing, constructs dynamic stress characteristic parameters F, and calculates the acoustic risk index R using the dynamic stress characteristic parameters F and the deep drawing stroke position parameter T. This allows the blank holder force control process to be adjusted to address vibration risks in the target frequency band. Furthermore, a blank holder force modulation parameter P is generated based on the acoustic risk index R, and this parameter P is used to control multiple blank holder zones to form dynamic blank holder forces with phase differences, causing circumferentially differentiated material flow in the sheet metal, thereby forming a gradient wall thickness structure. Subsequently, a residual risk index M is constructed using the wall thickness gradient index G and the acoustic risk index R, and a microstructure array is formed based on the residual risk index M. The placement and density of the microstructure array are matched with the vibration risk distribution of the shell, thus achieving a synergistic effect between deep drawing process control and surface structure optimization. This effectively reduces the vibration radiation capability in the target frequency band without increasing the shell weight, balancing lightweight and low noise requirements.

[0140] For clarification, "acquisition" in this application refers to obtaining the required content or data using existing technical means.

[0141] Furthermore, any content not described in detail in this specification is existing technology known to those skilled in the art.

[0142] In the embodiments provided by this invention, it should be understood that the disclosed system or method can be implemented in other ways. For example, the embodiments of the invention described above are merely illustrative; for instance, the division of modules is only a logical functional division, and there may be other division methods in actual implementation.

[0143] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0144] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or in the form of hardware plus software functional modules.

[0145] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the basic characteristics of the present invention.

[0146] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A precision stamping process for a low-vibration, low-noise, lightweight air conditioner compressor housing, characterized in that, Includes the following steps: S1. Collect dynamic contact stress signals in the contact area between the sheet metal and the die during the deep drawing process, and obtain dynamic stress characteristic parameters F based on the dynamic contact stress signals; S2. Calculate the acoustic risk index R corresponding to the target frequency band based on the dynamic stress characteristic parameter F and the current drawing stroke position parameter T, and generate the blank holder force modulation parameter P based on the acoustic risk index R. S3. According to the blank holder force modulation parameter P, control multiple blank holder zones to output dynamic blank holder forces with phase differences, so that the sheet material forms a circumferentially differentiated flow and constructs a gradient wall thickness structure. S4. Obtain the wall thickness distribution data corresponding to the gradient wall thickness structure, calculate the wall thickness gradient index G based on the wall thickness distribution data, and obtain the residual risk index M by combining the acoustic risk index R. S5. Generate surface microstructure processing parameters based on the residual risk index M, and form a microstructure array on the shell surface.

2. The precision stamping process for the low-vibration, low-noise, lightweight air conditioner compressor housing according to claim 1, characterized in that, Step S1 includes: S101, The contact area between the sheet metal and the mold includes the die opening area and the pressing edge area; Pressure sensors are installed in the contact area between the sheet metal and the mold to collect dynamic contact stress signals. S102. Perform frequency domain analysis on the dynamic contact stress signal to extract the dominant frequency f, stress fluctuation amplitude A and phase angle φ corresponding to the dynamic contact stress signal. S103. Construct dynamic stress characteristic parameters F based on the dominant frequency f, amplitude A, and phase φ.

3. The precision stamping process for the low-vibration, low-noise, lightweight air conditioner compressor housing according to claim 2, characterized in that, The dynamic stress characteristic parameters in step S103 satisfy: F = A × f × cosφ; Where: F represents the dynamic stress characteristic parameter, A represents the stress fluctuation amplitude, f represents the dominant frequency, and φ represents the phase angle.

4. The precision stamping process for the low-vibration, low-noise, lightweight air conditioner compressor housing according to claim 1, characterized in that, Step S2 includes: S201. Obtain the current drawing stroke position parameter T; S202. Calculate the acoustic risk index R based on the dynamic stress characteristic parameter F and the drawing stroke position parameter T. S203. Generate the edge clamping force modulation parameter P based on the acoustic risk index R; In step S202, the acoustic risk index satisfies the following: R = αF + βT; in: The values ​​of α and β are obtained using the entropy weight method.

5. The precision stamping process for the low-vibration, low-noise, lightweight air conditioner compressor housing according to claim 4, characterized in that, In step S203, the blank holder force modulation parameter P is generated based on the acoustic risk index R, as follows: The blank holder force compensation amplitude ΔA and blank holder force compensation phase Δφ are calculated based on the acoustic risk index R. The blank holder force compensation amplitude ΔA satisfies ΔA=k1×R, and the blank holder force compensation phase Δφ satisfies Δφ=k2×R. The values ​​of k1 and k2 are obtained by grid search method. The blank holder force compensation amplitude ΔA and blank holder force compensation phase Δφ are combined to form the blank holder force modulation parameter P, i.e., P=(ΔA,Δφ).

6. The precision stamping process for the low-vibration, low-noise, lightweight air conditioner compressor housing according to claim 1, characterized in that, Step S3 includes: S301. Divide the pressing area into multiple independent control areas along the circumferential direction, and use the independent control areas as pressing partitions; distribute the pressing force modulation parameter P to the multiple pressing partitions. S302. Control each pressing zone to output a dynamic pressing force with a phase difference. The dynamic pressing force acts on the sheet to drive the sheet to generate circumferentially differentiated material flow along the circumferential direction, so that the material inflow amount at different circumferential positions of the sheet is different. S303. Based on the difference in material inflow at different circumferential positions, different wall thickness values ​​are formed at different circumferential positions of the shell, and the different wall thickness values ​​are continuously varied along the circumference to form a gradient wall thickness structure.

7. In step S302, target output phases corresponding to multiple pressing partitions are generated according to the pressing force compensation phase Δφ, and multiple pressing partitions are controlled to output dynamic pressing force according to their respective target output phases, so that a phase difference is formed between adjacent pressing partitions.

8. The precision stamping process for the low-vibration, low-noise, lightweight air conditioner compressor housing according to claim 6, characterized in that, In step S302, the phase difference between adjacent pressing sections is 30° to 180°.

9. The precision stamping process for the low-vibration, low-noise, lightweight air conditioner compressor housing according to claim 1, characterized in that, Step S4 includes: S401. Determine the maximum wall thickness tmax, minimum wall thickness tmin, and average wall thickness tavg based on the wall thickness distribution data. S402. Calculate the wall thickness gradient exponent G based on the maximum wall thickness tmax, the minimum wall thickness tmin, and the average wall thickness tavg. S403. Calculate the residual risk index M based on the acoustic risk index R and the wall thickness gradient index G.

10. The precision stamping process for the low-vibration, low-noise, lightweight air conditioning compressor housing according to claim 8, characterized in that, In step S402, the wall thickness gradient exponent satisfies: G = (tmax − tmin) / tavg; The residual risk index in step S403 satisfies: M = R × (1 − G).

11. The precision stamping process for the low-vibration, low-noise, lightweight air conditioning compressor housing according to claim 1, characterized in that, Step S5 includes: S501, Surface microstructure processing parameters include microstructure array processing area and microstructure array processing density; S502. Determine the microstructure array processing area and microstructure array processing density based on the residual risk index M. S503, the microstructure array processing area and the microstructure array processing density form a microstructure array; In S502, the fabrication area and fabrication density of the microstructure array are determined based on the residual risk index M, as follows: The shell surface is divided into multiple surface unit regions of equal area, and the corresponding residual risk index M is calculated for each surface unit region. Arrange the residual risk indices M corresponding to all surface unit regions in descending order of their numerical values, and calculate the contribution ratio of the residual risk index M corresponding to each surface unit region to the total residual risk index of all surface unit regions. The contribution ratios are accumulated sequentially according to the descending order of the results until the cumulative contribution ratio reaches a preset cumulative ratio. The surface unit regions that participate in the cumulative contribution ratio reaching the preset cumulative ratio are determined as microstructure array processing regions. For a given microstructure array processing area, the microstructure array processing density ρ of the corresponding area is determined based on the ratio between the residual risk index M of the corresponding surface unit area and the maximum residual risk index M_max of all processing areas. The fabrication density ρ of the microstructure array satisfies: ； Where ρ0 is the basic processing density, ρmax is the maximum processing density, and Mmax is the maximum residual risk index in the processing area; The larger the residual risk index M corresponding to a certain processing area, the larger the microstructure array processing density ρ corresponding to that processing area; the smaller the residual risk index M corresponding to a certain processing area, the smaller the microstructure array processing density ρ corresponding to that processing area. The microstructure array processing parameters are generated based on the microstructure array processing density ρ corresponding to each processing area.

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