A method for evaluating electrolyte recovery of power lithium batteries

Abstract

The present invention discloses a method for evaluating the recovery of electrolytes from power lithium batteries, which relates to the field of lithium battery electrolyte recovery. The method comprises: constructing a distributed edge node network based on the regional distribution characteristics of power lithium battery electrolyte recovery; establishing an electrolyte stability and recoverability evaluation model to pre-treat and evaluate the electrolytes of used lithium batteries to be recycled; obtaining the transportation distance of the electrolyte recovery, and judging the transportation risk of the electrolyte recovery based on the transportation distance of the electrolyte recovery; constructing a comprehensive evaluation model for the recovery of electrolytes from power lithium batteries based on a neural network, based on the stability, recoverability, transportation distance, and risk of the electrolyte recovery, to comprehensively evaluate the recovery of electrolytes from power lithium batteries. The advantages of the present invention are: comprehensively evaluating the stability, recoverability, transportation distance, and risk of electrolyte recovery, accurately optimizing the transportation process, reducing transportation and risk costs, and achieving a dual improvement in economic benefits and safety.

Description

Technical Field

[0001] The present invention relates to the field of lithium battery electrolyte recovery, and in particular to a method for evaluating the recovery of electrolyte of a power lithium battery. Background Art

[0002] Power lithium battery electrolyte recycling refers to the process of extracting, purifying and reusing electrolytes and their effective ingredients (such as organic solvents, lithium salts, additives, etc.) from waste power lithium batteries through physical, chemical or biological methods. With the rapid development of the new energy vehicle and electric vehicle markets, the demand for power lithium batteries has increased sharply, and the number of waste batteries has also increased accordingly. As an important component of power lithium batteries, the recycling and reuse of electrolytes is of great significance to environmental protection and resource recycling. By recycling lithium battery electrolytes, it can effectively reduce the over-mining of rare metals such as lithium and cobalt, and reduce dependence on non-renewable resources. At the same time, it can avoid the leakage of harmful substances in the electrolyte and the pollution of soil and water sources, such as fluoride produced by the decomposition of lithium hexafluorophosphate. Through electrolyte recovery evaluation, it can effectively optimize the recycling process, reduce costs, improve resource utilization, and create economic value.

[0003] Currently, the recycling of power lithium battery electrolytes faces multiple challenges. Economically, the recycling cost is high, while the added value of recycled products is limited, resulting in poor economic benefits. Technically, the recycling technology of power lithium battery electrolytes has an unbalanced distribution of process emphasis. The use of a unified recycling strategy makes it difficult to achieve efficient separation and precise purification, affecting the quality of electrolyte recovery. In terms of logistics, electrolytes are hazardous chemicals, and the transportation cost increases with increasing distance, and the transportation risk increases, increasing the economic cost of electrolyte recycling. In addition, the industry lacks a comprehensive evaluation system for electrolyte recycling in terms of stability, recyclability, transportation distance, transportation risk, and recycling process, making it difficult to scientifically guide recycling practices, which restricts the scale and sustainable development of this field. Summary of the Invention

[0004] In order to solve the above technical problems, a method for evaluating the electrolyte recovery of power lithium batteries is provided. This technical solution solves the problem raised in the above background technology that the recycling cost is high and the added value of the recycled products is limited, resulting in poor economic benefits. The power lithium battery electrolyte recovery technology has an unbalanced distribution of process focus and adopts a unified recovery strategy, which makes it difficult to achieve efficient separation and precise purification, affecting the quality of electrolyte recovery. The transportation cost increases with the distance, and the transportation risk increases. In addition, the industry lacks a comprehensive evaluation system for electrolyte recovery in terms of stability, recyclability, transportation distance, transportation risk and recycling process, making it difficult to scientifically guide recycling practices, which restricts the scale and sustainable development of this field.

[0005] In order to achieve the above objects, the technical solution adopted by the present invention is:

[0006] A method for evaluating electrolyte recovery of a power lithium battery, comprising:

[0007] Based on the regional distribution characteristics of power lithium battery electrolyte recovery, a distributed edge node network is constructed to complete the pre-processing of electrolyte before recovery;

[0008] Obtain status data of waste lithium battery electrolytes, establish electrolyte stability and recyclability evaluation models, and pre-treat and evaluate the recycled waste lithium battery electrolytes;

[0009] According to the recycling process of power lithium battery electrolyte, the transportation distance of electrolyte recycling is obtained, and based on the transportation distance of electrolyte recycling, the transportation risk of electrolyte recycling is determined;

[0010] According to the stability, recycling rate, transportation distance and transportation risk of electrolyte recovery, a comprehensive evaluation model for power lithium battery electrolyte recovery is constructed based on neural network to conduct a comprehensive evaluation of power lithium battery electrolyte recovery.

[0011] Preferably, the construction of a distributed edge node network based on the regional distribution characteristics of power lithium battery electrolyte recovery to complete the pre-processing of the electrolyte before recovery specifically includes:

[0012] The area for recycling power lithium battery electrolytes is divided into several sub-areas based on population density and the density of lithium battery-containing industries;

[0013] Obtain the number of distributed edge nodes in each sub-region based on population density and lithium battery-related industry density;

[0014] Obtain the number of distributed edge nodes in each sub-region and build a distributed edge node network based on the SDN network architecture;

[0015] Through the distributed edge nodes in each sub-region, the electrolyte is pre-processed before recycling. Based on the distributed edge node network, the pre-processing data information of the power lithium battery electrolyte before recycling in each sub-region is obtained;

[0016] The number of distributed edge nodes in each sub-area is expressed as:

[0017] ;

[0018] Where, for The number of distributed edge nodes in each sub-region, It is a balance coefficient used to prevent the obtained value from being too large or too small, and at the same time, eliminate the unit dimension effect of density. 、 are the weighted values ​​of population density and industrial density containing lithium batteries, respectively. The least square method is used to obtain the accurate value. for The population density value of each sub-region, For the The industrial density value of lithium batteries in each sub-region is is the rounding symbol.

[0019] Preferably, the acquisition of status data of waste lithium battery electrolyte, establishment of electrolyte stability and recyclability evaluation model, and pre-processing and evaluation of waste lithium battery electrolyte to be recycled specifically include:

[0020] Obtaining status data of the spent lithium battery electrolyte through the distributed edge nodes in each sub-region, where the electrolyte status data includes: electrolyte concentration, composition, component quality, and temperature;

[0021] Normalize the electrolyte state data to eliminate the influence of data peak and data dimension;

[0022] Evaluate the electrolyte stability based on the normalized electrolyte state data;

[0023] The electrolyte recovery rate is evaluated based on the normalized electrolyte status data;

[0024] The evaluation expression for the electrolyte stability is:

[0025] ;

[0026] Where, is the electrolyte stability evaluation value, 、 、 are the weights of the toxic parameter components, corrosive parameter components, and flammable and explosive parameter components in the electrolyte, 、 、 The electrolyte The mass values ​​of the toxic parameter components, corrosive parameter components and flammable and explosive parameter components, 、 、 are the number of component types of toxic parameter components, corrosive parameter components, and flammable and explosive parameter components in the electrolyte, is the amplifying effect of temperature on toxicity, is the toxicity risk factor of electrolyte leakage caused by vibration, is the influence coefficient of temperature on corrosion, is the influence coefficient of temperature on flammability and explosiveness, is the influence coefficient of vibration on flammability and explosiveness;

[0027] The evaluation expression for the electrolyte recyclability is:

[0028] ;

[0029] Where, is the electrolyte recovery rate, is the number of types of recyclable components in the electrolyte, For the The test value of the mass of the recyclable components, To obtain the first The mass value of the recycled content, For the The weight of recycled content.

[0030] Preferably, obtaining the transportation distance of the electrolyte recovery according to the recycling process of the power lithium battery electrolyte, and judging the transportation risk of the electrolyte recovery according to the transportation distance of the electrolyte recovery specifically includes:

[0031] Recycling of waste lithium battery electrolytes is carried out by packaging and classification according to the status data of the waste lithium battery electrolytes and the battery types;

[0032] By analyzing the recycling process characteristics of power lithium battery electrolytes, combined with battery type and electrolyte composition, the compatibility of the recycling process with the target battery is evaluated, and a hierarchical management strategy is established accordingly;

[0033] The hierarchical management strategy refers to dividing the electrolyte recovery of different battery types and electrolyte compositions into the corresponding recycling processes according to the mapping relationship between the recycling process and the compatibility of the target battery;

[0034] Obtain the location information of the recycling center and distributed edge nodes in each sub-region through GIS and positioning technology;

[0035] According to the location information of the recycling center and the distributed edge nodes in each sub-region, based on GIS road network data, the actual transportation distance of electrolyte recycling is obtained;

[0036] Determine the transportation risk of electrolyte recovery based on the actual transportation distance of the electrolyte recovery and the electrolyte stability assessment value;

[0037] The transportation risk expression for the electrolyte recovery is:

[0038] ;

[0039] Where, Transportation risks for electrolyte recovery, is the number of road sections during the electrolyte recovery and transportation process, is the initial risk setting value based on the electrolyte stability assessment value, is the distance risk coefficient, is the actual transportation distance for electrolyte recovery, For the electrolyte recovery and transportation process The risk coefficient of each road section.

[0040] Preferably, the comprehensive evaluation model for power lithium battery electrolyte recovery is constructed based on a neural network according to the stability, recyclability, transportation distance and transportation risk of electrolyte recovery, and the comprehensive evaluation of power lithium battery electrolyte recovery specifically includes:

[0041] The stability, recyclability, transportation distance, transportation risk, and recycling process label of electrolyte recycling are used as input features, among which the transportation distance reflects the transportation cost;

[0042] Through expert evaluation or historical data annotation, set the comprehensive score of power lithium battery electrolyte recycling as the output label;

[0043] According to the normalization formula, the input feature data is normalized to eliminate the influence of data dimension;

[0044] According to historical data or test simulation experiments, set up training sets, validation sets, and test sets respectively;

[0045] According to the input characteristics, the input layer uses 5 neurons, the hidden layer uses 2 layers with 64 neurons each, and the output layer uses one neuron;

[0046] The loss function uses mean square error, , where is the number of samples, is the predicted value of the comprehensive score; is the comprehensive score target value;

[0047] The activation function is expressed in piecewise form. ;

[0048] Construct a comprehensive evaluation model for the recycling of power lithium battery electrolytes and conduct a comprehensive evaluation of the recycling of power lithium battery electrolytes.

[0049] Furthermore, the present invention provides an electronic device comprising: at least one processor; and a memory in communication with the at least one processor; wherein:

[0050] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the electrolyte recovery evaluation method for a power lithium battery as described above.

[0051] Furthermore, the present solution proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned electrolyte recovery and evaluation method for a power lithium battery.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] The present invention provides an electrolyte recovery and evaluation method for power lithium batteries. By constructing a distributed edge node network, the regional distribution characteristics of power lithium battery electrolyte recovery are fully considered. According to the characteristics of different regions, the pretreatment work before electrolyte recovery is completed more efficiently, and the adaptability and flexibility of the recovery process are improved. Secondly, by obtaining the status data of the waste lithium battery electrolyte, an electrolyte stability and recoverability evaluation model is established to achieve accurate evaluation of the electrolyte stability and recoverability, which is helpful for risk assessment of electrolyte recovery distribution and transportation, and improves recovery efficiency and quality. Furthermore, by obtaining the transportation distance and transportation risk of electrolyte recovery, a comprehensive evaluation of the transportation link is performed, which can identify potential safety issues and economic losses of transportation in advance. Finally, based on a neural network, the present invention constructs a comprehensive evaluation model for power lithium battery electrolyte recovery. Through this model, multiple factors such as electrolyte stability, recoverability, transportation distance, transportation risk and recovery process can be comprehensively and objectively evaluated for electrolyte recovery, thereby achieving the effect of accurately optimizing the transportation process, reducing transportation and risk costs, and achieving both economic benefits and safety improvements. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flow chart of a method for evaluating electrolyte recovery of a power lithium battery according to the present invention;

[0055] Figure 2 Based on the regional distribution characteristics of power lithium battery electrolyte recovery, a distributed edge node network is constructed to complete the pre-processing flow chart before electrolyte recovery;

[0056] Figure 3 The flow chart of the present invention for obtaining status data of waste lithium battery electrolyte, establishing an electrolyte stability and recyclability evaluation model, and pre-processing and evaluating the recycled waste lithium battery electrolyte;

[0057] Figure 4 A flow chart of obtaining the transportation distance for electrolyte recovery according to the recycling process for power lithium battery electrolyte of the present invention, and determining the transportation risk of electrolyte recovery based on the transportation distance for electrolyte recovery;

[0058] Figure 5This is a flowchart of the comprehensive evaluation model for power lithium battery electrolyte recovery based on a neural network, which is constructed according to the stability, recyclability, transportation distance and transportation risk of electrolyte recovery;

[0059] Figure 6 This is a structural diagram of the electronic device proposed by the present invention;

[0060] Figure 7 This is a schematic diagram of the structure of the computer-readable storage medium proposed in the present invention. DETAILED DESCRIPTION

[0061] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may conceive of other obvious variations.

[0062] Reference Figure 1 As shown, a method for evaluating the recovery of electrolyte of a power lithium battery comprises:

[0063] Based on the regional distribution characteristics of power lithium battery electrolyte recovery, a distributed edge node network is constructed to complete the pre-processing of electrolyte before recovery;

[0064] Obtain status data of waste lithium battery electrolytes, establish electrolyte stability and recyclability evaluation models, and pre-treat and evaluate the recycled waste lithium battery electrolytes;

[0065] According to the recycling process of power lithium battery electrolyte, the transportation distance of electrolyte recycling is obtained, and based on the transportation distance of electrolyte recycling, the transportation risk of electrolyte recycling is determined;

[0066] According to the stability, recycling rate, transportation distance and transportation risk of electrolyte recovery, a comprehensive evaluation model for power lithium battery electrolyte recovery is constructed based on neural network to conduct a comprehensive evaluation of power lithium battery electrolyte recovery.

[0067] It can be explained that the evaluation of electrolyte recycling of power lithium batteries involves many factors such as the regional distribution characteristics of power lithium battery electrolyte recycling, electrolyte stability and recoverability, transportation distance and transportation risk, and recycling process. The evaluation of a single factor will lead to the one-sidedness and unreliability of the evaluation of electrolyte recycling of power lithium batteries. Therefore, this solution integrates and evaluates data from multiple aspects by constructing a distributed edge node network, establishing an electrolyte stability and recoverability evaluation model, obtaining the transportation distance of electrolyte recycling and judging the transportation risk of electrolyte recycling. Based on a neural network, a comprehensive evaluation model for electrolyte recycling of power lithium batteries is constructed to conduct a comprehensive and objective evaluation of electrolyte recycling, thereby achieving a comprehensive evaluation of the stability, recoverability, transportation distance and risk of electrolyte recycling, accurately optimizing the transportation process, reducing transportation and risk costs, and achieving the goal of improving both economic benefits and safety.

[0068] Reference Figure 2 As shown, the construction of a distributed edge node network based on the regional distribution characteristics of power lithium battery electrolyte recovery to complete the pre-processing of the electrolyte before recovery specifically includes:

[0069] The area for recycling power lithium battery electrolytes is divided into several sub-areas based on population density and the density of lithium battery-containing industries;

[0070] Obtain the number of distributed edge nodes in each sub-region based on population density and lithium battery-related industry density;

[0071] Obtain the number of distributed edge nodes in each sub-region and build a distributed edge node network based on the SDN network architecture;

[0072] Through the distributed edge nodes in each sub-region, the electrolyte is pre-processed before recycling. Based on the distributed edge node network, the pre-processing data information of the power lithium battery electrolyte before recycling in each sub-region is obtained;

[0073] The number of distributed edge nodes in each sub-area is expressed as:

[0074] ;

[0075] Where, for The number of distributed edge nodes in each sub-region, It is a balance coefficient used to prevent the obtained value from being too large or too small, and at the same time, eliminate the unit dimension effect of density. 、 are the weighted values ​​of population density and industrial density containing lithium batteries, respectively. The least square method is used to obtain the accurate value. for The population density value of each sub-region, For the The industrial density value of lithium batteries in each sub-region is is the rounding symbol.

[0076] It can be explained that population density and industrial density containing lithium batteries are two important factors affecting the recovery of power lithium battery electrolytes. When setting up distributed edge nodes, it is necessary to fully consider the impact of population density and industrial density containing lithium batteries to avoid the waste of resources and increased difficulty in scheduling electrolyte recovery due to unreasonable settings of distributed edge nodes. This solution provides distributed edge node support for pre-treatment of power lithium battery electrolytes before recovery by constructing a distributed edge node network, and establishes an expression for the number of distributed edge nodes in each sub-region. The number of distributed edge nodes in each sub-region is obtained scientifically and rationally through formulas, and then the distributed edge nodes of each sub-region are evenly distributed to each sub-region through a uniform distribution method. Among them, the balance coefficient It is used to adjust the value and eliminate the influence of unit dimension. It can be obtained based on historical data or test experiments. It is the weighted value of population density and industrial density. 、 , is determined by the least squares method to ensure a reasonable weight distribution. This process fully considers regional characteristics and achieves efficient and targeted pretreatment by precisely configuring edge nodes, providing reliable data support for subsequent electrolyte recovery and helping to improve overall recovery efficiency and quality.

[0077] Reference Figure 3 As shown, the acquisition of status data of waste lithium battery electrolyte, establishment of electrolyte stability and recyclability evaluation model, and pre-processing and evaluation of waste lithium battery electrolyte to be recycled specifically include:

[0078] Obtaining status data of the spent lithium battery electrolyte through the distributed edge nodes in each sub-region, where the electrolyte status data includes: electrolyte concentration, composition, component quality, and temperature;

[0079] Normalize the electrolyte state data to eliminate the influence of data peak and data dimension;

[0080] Evaluate the electrolyte stability based on the normalized electrolyte state data;

[0081] The electrolyte recovery rate is evaluated based on the normalized electrolyte status data;

[0082] The evaluation expression for the electrolyte stability is:

[0083] ;

[0084] Where, is the electrolyte stability evaluation value, 、 、 are the weights of the toxic parameter components, corrosive parameter components, and flammable and explosive parameter components in the electrolyte, 、 、 The electrolyte The mass values ​​of the toxic parameter components, corrosive parameter components and flammable and explosive parameter components, 、 、 are the number of component types of toxic parameter components, corrosive parameter components, and flammable and explosive parameter components in the electrolyte, is the amplifying effect of temperature on toxicity, is the toxicity risk factor of electrolyte leakage caused by vibration, is the influence coefficient of temperature on corrosion, is the influence coefficient of temperature on flammability and explosiveness, is the influence coefficient of vibration on flammability and explosiveness;

[0085] The evaluation expression for the electrolyte recyclability is:

[0086] ;

[0087] Where, is the electrolyte recovery rate, is the number of types of recyclable components in the electrolyte, For the The test value of the mass of the recyclable components, To obtain the first The mass value of the recycled content, For the The weight of recycled content.

[0088] It can be explained that the recycling of lithium battery electrolytes is dangerous during transportation and storage, which can easily cause safety hazards. Among them, toxic, corrosive, and flammable and explosive components require special attention. Secondly, in order to improve the quality of lithium battery electrolyte recycling and the allocation of scientific recycling processes, it is necessary to analyze the recyclability of lithium battery electrolytes. Therefore, this solution obtains the status data of waste lithium battery electrolytes through the distributed edge nodes in each sub-region, and evaluates the electrolyte stability and recyclability based on the electrolyte stability and recyclability evaluation model, thereby improving the safety and recycling efficiency of the lithium battery electrolyte recycling process. In the formula, 、 、 It can be dynamically calibrated by the Analytic Hierarchy Process (AHP). , where To actually detect the temperature, is the temperature reference value for toxic volatilization, is the temperature sensitivity decay constant, is the toxicity magnification factor, , where is the fitting value of the vibration generated during vehicle transportation, is the vibration threshold for toxic leakage, , where is the corrosion amplification factor, is the corrosive amplification temperature reference value, , where is the flash point temperature, , where In order to reach the critical threshold of flammability and explosion, in particular, to ensure the consistency of units on both sides of the formula, the state data is normalized to eliminate the impact of data peaks and dimensions, making data of different magnitudes and ranges comparable, and improving the accuracy and reliability of data analysis.

[0089] Reference Figure 4 As shown, the recycling process of power lithium battery electrolyte is used to obtain the transportation distance of electrolyte recycling, and the transportation risk of electrolyte recycling is determined based on the transportation distance of electrolyte recycling, which specifically includes:

[0090] Recycling of waste lithium battery electrolytes is carried out by packaging and classification according to the status data of the waste lithium battery electrolytes and the battery types;

[0091] By analyzing the recycling process characteristics of power lithium battery electrolytes, combined with battery type and electrolyte composition, the compatibility of the recycling process with the target battery is evaluated, and a hierarchical management strategy is established accordingly;

[0092] The hierarchical management strategy refers to dividing the electrolyte recovery of different battery types and electrolyte compositions into the corresponding recycling processes according to the mapping relationship between the recycling process and the compatibility of the target battery;

[0093] Obtain the location information of the recycling center and distributed edge nodes in each sub-region through GIS and positioning technology;

[0094] According to the location information of the recycling center and the distributed edge nodes in each sub-region, based on GIS road network data, the actual transportation distance of electrolyte recycling is obtained;

[0095] Determine the transportation risk of electrolyte recovery based on the actual transportation distance of the electrolyte recovery and the electrolyte stability assessment value;

[0096] The transportation risk expression for the electrolyte recovery is:

[0097] ;

[0098] Where, Transportation risks for electrolyte recovery, is the number of road sections during the electrolyte recovery and transportation process, is the initial risk setting value based on the electrolyte stability assessment value, is the distance risk coefficient, is the actual transportation distance for electrolyte recovery, For the electrolyte recovery and transportation process The risk coefficient of each road section.

[0099] It can be explained that due to the imbalance in the distribution of process emphasis in power lithium battery electrolyte recovery technology, it is difficult to achieve efficient separation and precise purification by adopting a unified recovery strategy, which affects the quality of electrolyte recovery. Therefore, this solution establishes a hierarchical management strategy to determine the mapping relationship between the compatibility of the recovery process and the target battery, thereby obtaining the actual transportation distance of the electrolyte recovery through the mapping relationship, and based on the actual transportation distance of the electrolyte recovery, combined with the electrolyte stability evaluation value, establishes the transportation risk expression of the electrolyte recovery, thereby judging the transportation risk of the electrolyte recovery, effectively solving the problems of poor separation and purification effect and low recovery quality caused by process imbalance and unified recovery strategy, and accurately judging the transportation risk of the electrolyte recovery, among which, and For positive closing, It is positively correlated with the road surface slope and negatively correlated with the smoothness of the road section;

[0100] Reference Figure 5 As shown, based on the stability, recyclability, transportation distance and transportation risk of electrolyte recovery, a comprehensive evaluation model for power lithium battery electrolyte recovery is constructed based on a neural network. The comprehensive evaluation of power lithium battery electrolyte recovery specifically includes:

[0101] The stability, recyclability, transportation distance, transportation risk, and recycling process label of electrolyte recycling are used as input features, among which the transportation distance reflects the transportation cost;

[0102] Through expert evaluation or historical data annotation, set the comprehensive score of power lithium battery electrolyte recycling as the output label;

[0103] According to the normalization formula, the input feature data is normalized to eliminate the influence of data dimension;

[0104] According to historical data or test simulation experiments, set up training sets, validation sets, and test sets respectively;

[0105] According to the input characteristics, the input layer uses 5 neurons, the hidden layer uses 2 layers with 64 neurons each, and the output layer uses one neuron;

[0106] The loss function uses mean square error, , where is the number of samples, is the predicted value of the comprehensive score; is the comprehensive score target value;

[0107] The activation function is expressed in piecewise form. ;

[0108] Construct a comprehensive evaluation model for the recycling of power lithium battery electrolytes and conduct a comprehensive evaluation of the recycling of power lithium battery electrolytes.

[0109] It can be explained that the evaluation of electrolyte recycling of power lithium batteries involves many factors, such as the regional distribution characteristics of power lithium battery electrolyte recycling, electrolyte stability and recycling rate, transportation distance and transportation risk, and recycling process. The evaluation of a single factor will lead to the one-sidedness and unreliability of the evaluation of electrolyte recycling of power lithium batteries. In order to ensure the comprehensiveness and reliability of the evaluation of electrolyte recycling of power lithium batteries, this solution constructs a comprehensive evaluation model for electrolyte recycling of power lithium batteries based on neural networks. The neural network model maps and fits the input features and output labels, thereby comprehensively evaluating the recycling of power lithium battery electrolytes. In particular, when the electrolyte recycling lacks a corresponding recycling process, the output label is a fixed value regardless of how other features change. Therefore, this solution sets a piecewise function as the activation function in the output layer. This function determines whether the input feature lacks a recycling process label. If so, a fixed label is output. If not, a standard activation function, such as ReLU, Sigmoid, etc., is used to process the input, thereby ensuring the rationality and stability of the evaluation model and improving the evaluation efficiency and accuracy.

[0110] Furthermore, the method according to the embodiment of the present application can also be used with the aid of Figure 6 The electronic device architecture shown in FIG. Figure 6 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, may store a method for evaluating the recovery of electrolyte of a power lithium battery provided in this application. The electronic device 500 may also include a user interface 508. Of course, Figure 6 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 6 One or more components of an electronic device are shown.

[0111] Figure 7 This is a schematic diagram of the computer-readable storage medium structure provided by an embodiment of the present application. Figure 7 As shown, a computer-readable storage medium 600 according to an embodiment of the present application is shown. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are executed by the processor, the electrolyte recovery evaluation method of a power lithium battery according to an embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache). Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0112] In summary, the advantages of the present invention are: comprehensive assessment of the stability, recoverability, transportation distance and risks of electrolyte recovery, precise optimization of the transportation process, reduction of transportation and risk costs, and realization of dual improvement of economic benefits and safety.

[0113] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for evaluating the recovery of electrolyte of a power lithium battery, characterized in that: include: Based on the regional distribution characteristics of power lithium battery electrolyte recovery, a distributed edge node network is constructed to complete the pre-processing of electrolyte before recovery; Obtain status data of waste lithium battery electrolytes, establish electrolyte stability and recyclability evaluation models, and pre-treat and evaluate the recycled waste lithium battery electrolytes; According to the recycling process of power lithium battery electrolyte, the transportation distance of electrolyte recycling is obtained, and based on the transportation distance of electrolyte recycling, the transportation risk of electrolyte recycling is determined; According to the stability, recycling rate, transportation distance and transportation risk of electrolyte recovery, a comprehensive evaluation model for power lithium battery electrolyte recovery is constructed based on neural network to conduct a comprehensive evaluation of power lithium battery electrolyte recovery.

2. The electrolyte recovery and evaluation method for a power lithium battery according to claim 1, characterized in that: The construction of a distributed edge node network based on the regional distribution characteristics of power lithium battery electrolyte recovery to complete the pre-processing of the electrolyte before recovery specifically includes: The area for recycling power lithium battery electrolytes is divided into several sub-areas based on population density and the density of lithium battery-containing industries; Obtain the number of distributed edge nodes in each sub-region based on population density and lithium battery-related industry density; Obtain the number of distributed edge nodes in each sub-region and build a distributed edge node network based on the SDN network architecture; Through the distributed edge nodes in each sub-region, the electrolyte is pre-processed before recycling. Based on the distributed edge node network, the pre-processing data information of the power lithium battery electrolyte before recycling in each sub-region is obtained; The number of distributed edge nodes in each sub-area is expressed as: ； Where, for The number of distributed edge nodes in each sub-region, It is a balance coefficient used to prevent the obtained value from being too large or too small, and at the same time, eliminate the unit dimension effect of density. 、 are the weighted values ​​of population density and industrial density containing lithium batteries, respectively. The least square method is used to obtain the accurate value. for The population density value of each sub-region, For the The industrial density value of lithium batteries in each sub-region is is the rounding symbol.

3. The electrolyte recovery and evaluation method for a power lithium battery according to claim 2, characterized in that: The acquisition of status data of waste lithium battery electrolyte, establishment of electrolyte stability and recyclability evaluation model, and pre-processing and evaluation of waste lithium battery electrolyte to be recycled specifically include: Obtaining status data of the spent lithium battery electrolyte through the distributed edge nodes in each sub-region, where the electrolyte status data includes: electrolyte concentration, composition, component quality, and temperature; Normalize the electrolyte state data to eliminate the influence of data peak and data dimension; Evaluate the electrolyte stability based on the normalized electrolyte state data; The electrolyte recovery rate is evaluated based on the normalized electrolyte status data; The evaluation expression for the electrolyte stability is: ； Where, is the electrolyte stability evaluation value, 、 、 are the weights of the toxic parameter components, corrosive parameter components, and flammable and explosive parameter components in the electrolyte, 、 、 The electrolyte The mass values ​​of the toxic parameter components, corrosive parameter components and flammable and explosive parameter components, 、 、 are the number of component types of toxic parameter components, corrosive parameter components, and flammable and explosive parameter components in the electrolyte, is the amplifying effect of temperature on toxicity, is the toxicity risk factor of electrolyte leakage caused by vibration, is the influence coefficient of temperature on corrosion, is the influence coefficient of temperature on flammability and explosiveness, is the influence coefficient of vibration on flammability and explosiveness; The evaluation expression for the electrolyte recyclability is: ； Where, is the electrolyte recovery rate, is the number of types of recyclable components in the electrolyte, For the The test value of the mass of the recyclable components, To obtain the first The mass value of the recycled content, For the The weight of recycled content.

4. The electrolyte recovery and evaluation method for a power lithium battery according to claim 3, characterized in that: The above-mentioned method of obtaining the transportation distance of electrolyte recovery according to the recycling process of power lithium battery electrolyte and judging the transportation risk of electrolyte recovery according to the transportation distance of electrolyte recovery specifically includes: Recycling of waste lithium battery electrolytes is carried out by packaging and classification according to the status data of the waste lithium battery electrolytes and the battery types; By analyzing the recycling process characteristics of power lithium battery electrolytes, combined with battery type and electrolyte composition, the compatibility of the recycling process with the target battery is evaluated, and a hierarchical management strategy is established accordingly; The hierarchical management strategy refers to dividing the electrolyte recovery of different battery types and electrolyte compositions into the corresponding recycling processes according to the mapping relationship between the recycling process and the compatibility of the target battery; Obtain the location information of the recycling center and distributed edge nodes in each sub-region through GIS and positioning technology; According to the location information of the recycling center and the distributed edge nodes in each sub-region, the actual transportation distance of the electrolyte recycling is obtained based on the GIS road network data; Determine the transportation risk of electrolyte recovery based on the actual transportation distance of the electrolyte recovery and the electrolyte stability assessment value; The transportation risk expression for electrolyte recovery is: ； Where, Transportation risks for electrolyte recovery, is the number of road sections during the electrolyte recovery and transportation process, is the initial risk setting value based on the electrolyte stability assessment value, is the distance risk coefficient, is the actual transportation distance for electrolyte recovery, For the electrolyte recovery and transportation process The risk coefficient of each road section.

5. The electrolyte recovery and evaluation method for a power lithium battery according to claim 4, characterized in that: According to the stability, recyclability, transportation distance and transportation risk of electrolyte recovery, a comprehensive evaluation model for power lithium battery electrolyte recovery is constructed based on a neural network. The comprehensive evaluation of power lithium battery electrolyte recovery specifically includes: The stability, recyclability, transportation distance, transportation risk, and recycling process label of electrolyte recycling are used as input features, among which the transportation distance reflects the transportation cost; Through expert evaluation or historical data annotation, set the comprehensive score of power lithium battery electrolyte recycling as the output label; According to the normalization formula, the input feature data is normalized to eliminate the influence of data dimension; According to historical data or test simulation experiments, set up training sets, validation sets, and test sets respectively; According to the input characteristics, the input layer uses 5 neurons, the hidden layer uses 2 layers with 64 neurons each, and the output layer uses one neuron; The loss function uses mean square error, , where is the number of samples, is the predicted value of the comprehensive score; is the comprehensive score target value; The activation function is expressed in piecewise form. ; Construct a comprehensive evaluation model for the recycling of power lithium battery electrolyte and conduct a comprehensive evaluation of the recycling of power lithium battery electrolyte.

6. An electronic device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the electrolyte recovery and evaluation method for a power lithium battery as described in any one of claims 1 to 5.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for evaluating the electrolyte recovery of a power lithium battery according to any one of claims 1 to 5 is implemented.

Images