Classified recovery method and equipment for waste lithium batteries of electric heavy truck, medium and product

Abstract

The invention discloses a classified recycling method, equipment, medium and product for waste lithium batteries of an electric heavy truck, and relates to the technical field of lithium battery recycling, the method comprises the following steps: evaluating the health state of a target waste lithium battery by adopting a multi-head attention mechanism based on state parameters to obtain the health state value of the target waste lithium battery; when the health state value is greater than or equal to a threshold value, taking the target waste lithium battery as a discarded recycled lithium battery, and performing discarded recycling treatment on the discarded recycled lithium battery; and when the health state value is smaller than a threshold value, taking the target waste lithium battery as a reassembled and utilized lithium battery, and performing reassembled and utilized treatment on the reassembled and utilized lithium battery through appearance damage state classification. According to the method, the classification efficiency of the waste lithium batteries of the electric heavy trucks is improved, the recycling rate of the waste lithium batteries of the electric heavy trucks is further improved, and environmental pollution in the recycling process of the waste lithium batteries of the electric heavy trucks is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium battery recycling, and particularly to a method, device, medium and product for classified recycling of waste lithium batteries of electric heavy trucks. Background Art

[0002] With the vigorous development of the new energy vehicle industry, the consumption of power lithium batteries is also increasing rapidly, and the consumption of power lithium batteries in electric heavy trucks is also quite considerable. Due to the limited service life of lithium batteries, the problem of treating a large number of waste lithium batteries has become increasingly prominent. The steady increase in the number of retired power batteries has brought no small pressure to the environment. These power batteries contain rich valuable metal resources such as lithium, nickel, cobalt, iron, and copper. Therefore, developing short-range and efficient power battery recycling and reuse technologies can not only effectively reduce the demand for key material resources but also solve major problems such as environmental pollution and ecological impact.

[0003] At present, there is a situation of polarization in the waste lithium batteries of electric heavy trucks. Some lithium batteries of electric heavy trucks are retired due to the significant reduction in health due to overloaded work, while some lithium batteries are prematurely retired due to electric heavy truck accidents when their own health is very good. Therefore, if the waste lithium batteries of electric heavy trucks are simply recycled by taking the scrapping method, it will cause great waste of the lithium batteries of electric heavy trucks, reduce the recycling efficiency of the lithium batteries of electric heavy trucks, and indirectly cause environmental pollution during the recycling process. Summary of the Invention

[0004] In view of this, the present invention provides a method, device, medium and product for classified recycling of waste lithium batteries of electric heavy trucks. The present invention can improve the classification efficiency of waste lithium batteries of electric heavy trucks, thereby improving the recycling rate of waste lithium batteries of electric heavy trucks and reducing environmental pollution during the recycling process of waste lithium batteries of electric heavy trucks.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] In a first aspect, the present invention provides a method for classifying and recycling waste lithium batteries of electric heavy trucks. The recycling method of the waste lithium batteries of electric heavy trucks includes: obtaining the state parameters of a target waste lithium battery, where the target waste lithium battery is a waste lithium battery of an electric heavy truck, and the state parameters at least include capacity, internal resistance value, cycle life electricity, and self-discharge rate; evaluating the health state of the target waste lithium battery by using a multi-head attention mechanism based on the state parameters to obtain the health state value of the target waste lithium battery; when the health state value is greater than or equal to a threshold, regarding the target waste lithium battery as a waste lithium battery for recycling and performing waste recycling treatment on the waste lithium battery for recycling; when the health state value is less than the threshold, regarding the target waste lithium battery as a lithium battery for reuse after reinstallation, and performing reuse treatment on the lithium battery for reuse after reinstallation by classifying the appearance damage state.

[0007] In a second aspect, the present invention provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. The processor executes the computer program to implement the above-mentioned method for classifying and recycling waste lithium batteries of electric heavy trucks.

[0008] In a third aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the above-mentioned method for classifying and recycling waste lithium batteries of electric heavy trucks.

[0009] In a fourth aspect, the present invention provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the above-mentioned method for classifying and recycling waste lithium batteries of electric heavy trucks.

[0010] According to the specific embodiments provided by the present invention, the following technical effects are disclosed:

[0011] As can be seen from the above technical solutions, the present invention evaluates the health state of the target waste lithium battery by using a multi-head attention mechanism based on the state parameters to obtain the health state value of the target waste lithium battery; then uses the health state value of the target waste lithium battery to distinguish between waste lithium batteries for recycling and lithium batteries for reuse after reinstallation; improves the classification efficiency and classification accuracy of waste lithium batteries; and performs reuse treatment on the lithium batteries for reuse after reinstallation by classifying the appearance damage state, improves the recycling rate of waste lithium batteries of electric heavy trucks, and reduces environmental pollution in the process of recycling waste lithium batteries of electric heavy trucks. Description of the Drawings

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0013] Figure 1 It is a schematic flow chart of a method for classifying and recycling waste lithium batteries of electric heavy trucks provided by an embodiment of the present invention;

[0014] Figure 2 It is a schematic structural diagram of a computer device provided by an embodiment of the present invention. Detailed implementation manners

[0015] In order to enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0016] Embodiment 1, as Figure 1 shown, this embodiment provides a method for classifying and recycling waste lithium batteries of electric heavy trucks, including:

[0017] S1. Obtain the state parameters of the target waste lithium battery; the target waste lithium battery is a waste lithium battery of an electric heavy truck; the state parameters at least include: capacity, internal resistance value, cycle life electricity, and self-discharge rate.

[0018] Optionally, the state parameters further include: depth of discharge, charge cut-off voltage, discharge cut-off voltage, and internal resistance consistency.

[0019] S2. Based on the state parameters, use the multi-head attention mechanism to evaluate the health state of the target waste lithium battery, and obtain the health state value of the target waste lithium battery.

[0020] Step S2 specifically includes:

[0021] S21. Perform normalization processing on the capacity, internal resistance value, cycle life electricity, and self-discharge rate to obtain the normalized capacity, internal resistance value, cycle life electricity, and self-discharge rate.

[0022] S22. Use the attention mechanism to assign weights to the normalized capacity, internal resistance value, cycle life electricity, and self-discharge rate respectively.

[0023] S23. Sum up the weights of the normalized capacity, internal resistance value, cycle life, and self-discharge rate to obtain the health state value of the target used lithium battery.

[0024] S3. When the health state value is greater than or equal to the threshold value, regard the target used lithium battery as a scrapped and recycled lithium battery, and perform scrapped and recycled processing on the scrapped and recycled lithium battery; the threshold value is 0.7.

[0025] S4. When the health state value is less than the threshold value, regard the target used lithium battery as a reused lithium battery, and perform reuse processing on the reused lithium battery through classification according to the appearance damage state.

[0026] In some embodiments, performing reuse processing on the reused lithium battery through classification according to the appearance damage state specifically includes:

[0027] Obtain the appearance image of the reused lithium battery in a 3D scanning manner.

[0028] Optionally, the 3D scanning manner includes at least any one of laser scanning, structured light scanning, photogrammetry, infrared scanning, handheld 3D scanning, and holographic scanning.

[0029] Optionally, the appearance image of the reused lithium battery is a panoramic image.

[0030] Perform multi-scale feature recognition and feature fusion on the appearance image of the reused lithium battery to obtain the appearance fusion feature, specifically including: performing multi-scale feature extraction on the appearance image of the reused lithium battery to obtain multiple features of different scales of the appearance image of the lithium battery; performing feature fusion on the multiple features of different scales of the appearance image of the lithium battery from the spatial dimension and the channel dimension to obtain the multi-scale fusion feature; enhancing the relationship of the multi-scale fusion feature through a multi-head attention mechanism to obtain the relationship-enhanced feature; performing feature fusion on the relationship-enhanced feature and the multi-scale fusion feature to obtain the appearance fusion feature.

[0031] Classify the appearance damage state of the reused lithium battery based on the appearance fusion feature; the appearance damage states are packaging damage and encapsulation damage.

[0032] After repackaging the reused lithium battery with packaging damage, perform reuse.

[0033] After sequentially repackaging and resealing the reused lithium battery with encapsulation damage, perform reuse.

[0034] In the specific implementation process, through multi-scale feature recognition and feature fusion, the appearance of lithium batteries can be detected and recognized. If only the outer packaging is damaged, it only needs to be repackaged and then can enter the next reassembly link. If the encapsulation layer is damaged, the encapsulation layer needs to be repaired first and then repackaged before entering the next reassembly link. This process improves the accuracy of the appearance recognition of lithium batteries, thereby ensuring the safe recycling of reassembled and reused lithium batteries.

[0035] In some embodiments, the waste recycling treatment specifically includes: discharging the waste recycled lithium batteries; disassembling the discharged waste recycled lithium batteries to obtain waste recycled materials; the waste recycled materials include: outer shells, electrode materials, and electrolytes; using physical, chemical, and metallurgical methods to classify and refine the waste recycled materials to obtain recycled metals, plastic materials, and waste; the waste is materials that cannot be recycled; and performing harmless treatment on the waste.

[0036] In some embodiments, the reassembly specifically includes: after surface cleaning the reassembled and reused lithium batteries, reinstalling the protection circuit and the outer shell to obtain a reused battery module.

[0037] From the above technical solutions, the technical effects of the present invention are as follows:

[0038] The present invention evaluates the health state of the target waste lithium battery by using the multi-head attention mechanism based on the state parameters to obtain the health state value of the target waste lithium battery; then uses the health state value of the target waste lithium battery to distinguish between waste recycled lithium batteries and reassembled and reused lithium batteries; improves the classification efficiency and classification accuracy of waste lithium batteries; and performs reassembly and reuse treatment on the reassembled and reused lithium batteries through appearance damage state classification, improves the recycling rate of waste lithium batteries of electric heavy trucks, and reduces environmental pollution in the recycling process of waste lithium batteries of electric heavy trucks.

[0039] Example 2, as Figure 2As shown, the present invention also provides a computer device, which can be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store processed data. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above method is implemented.

[0040] Those skilled in the art can understand that Figure 2 the structure shown in is only a block diagram of some structures related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0041] In Embodiment 3, the present invention also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above-mentioned various methods are implemented.

[0042] In Embodiment 4, the present invention also provides a computer program product including a computer program, and when the computer program is executed by a processor, the above-mentioned various methods are implemented.

[0043] In several embodiments provided by the present invention, it can be understood that each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and a module, a program segment, or a part of code includes one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved.

[0044] In several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of devices or units can be in electrical, mechanical or other forms.

[0045] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for sorting and recycling waste lithium batteries of electric heavy trucks, characterized in that: The method for recycling waste lithium batteries of electric heavy trucks comprises: Obtaining state parameters of a target waste lithium battery; the target waste lithium battery is a waste lithium battery of an electric heavy truck; the state parameters at least include: capacity, internal resistance, cycle life and self-discharge rate; Based on the state parameters, a multi-head attention mechanism is used to evaluate the health state of the target waste lithium battery to obtain the health state value of the target waste lithium battery; When the health status value is greater than or equal to the threshold, the target waste lithium battery is regarded as a scrapped and recycled lithium battery, and the scrapped and recycled lithium battery is scrapped and recycled; When the health status value is less than a threshold value, the target waste lithium battery is used as a reusable lithium battery, and the reusable lithium battery is processed for reusability based on the classification of the appearance damage status.

2. The method for classifying and recycling waste lithium batteries of electric heavy trucks according to claim 1 is characterized in that: Based on the state parameters, a multi-head attention mechanism is used to evaluate the health state of the target waste lithium battery, and the health state value of the target waste lithium battery is obtained, including: The capacity, internal resistance, cycle life and self-discharge rate are normalized to obtain the normalized capacity, internal resistance, cycle life and self-discharge rate; The attention mechanism is used to assign weights to the normalized capacity, internal resistance, cycle life and self-discharge rate respectively; The normalized capacity, internal resistance, cycle life and self-discharge rate are added together to obtain the health status value of the target waste lithium battery.

3. The method for classifying and recycling waste lithium batteries of electric heavy trucks according to claim 1 is characterized in that: The threshold is 0.

7.

4. The method for classifying and recycling waste lithium batteries of electric heavy trucks according to claim 1 is characterized in that: The re-usable lithium batteries are classified according to their appearance damage status and then re-used, including: Obtain appearance images of reinstalled lithium batteries by 3D scanning; Perform multi-scale feature recognition and feature fusion on the appearance images of reinstalled lithium batteries to obtain appearance fusion features; Classifying the appearance damage states of the reinstalled lithium batteries based on the appearance fusion features; the appearance damage states include packaging damage and encapsulation damage; Repack the damaged packaging by repackaging the lithium battery; The damaged package is repacked by resealing and repackaging the lithium battery in sequence and then repackaging.

5. The method for classifying and recycling waste lithium batteries of electric heavy trucks according to claim 4 is characterized in that: Multi-scale feature recognition and feature fusion are performed on the appearance images of reinstalled lithium batteries to obtain appearance fusion features, including: Perform multi-scale feature extraction on the appearance image of the reassembled lithium battery to obtain features of multiple different scales of the appearance image of the lithium battery; The features of multiple scales of the appearance image of the lithium battery are fused from the spatial dimension and the channel dimension to obtain multi-scale fusion features; The multi-scale fusion features are enhanced through the multi-head attention mechanism to obtain the enhanced features. The relationship enhancement feature and the multi-scale fusion feature are fused to obtain an appearance fusion feature.

6. The method for classifying and recycling waste lithium batteries of electric heavy trucks according to claim 1 is characterized in that: The scrap recycling process specifically includes: Discharge the scrapped and recycled lithium batteries; Disassembling the waste recycled lithium battery after the discharge point treatment to obtain waste recycled materials; the waste recycled materials include: shell, electrode material and electrolyte; The scrapped and recycled materials are classified and refined by physical, chemical and metallurgical methods to obtain recycled metals, plastic materials and waste; the waste is non-recyclable materials; Treat waste harmlessly.

7. The method for classifying and recycling waste lithium batteries of electric heavy trucks according to claim 1 is characterized in that: The repackaging specifically includes: After cleaning the surface of the reinstalled lithium battery, reinstall the protection circuit and casing to obtain a reused battery module.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for sorting and recycling waste lithium batteries of electric heavy-duty trucks as claimed in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for classifying and recycling waste lithium batteries of electric heavy-duty trucks described in any one of claims 1 to 7 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for classifying and recycling waste lithium batteries of electric heavy-duty trucks described in any one of claims 1 to 7 is implemented.

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