A method and system for calculating the carbon footprint of lithium batteries based on their entire life cycle.

Abstract

This invention provides a method and system for calculating the carbon footprint of lithium batteries based on their entire lifecycle. The method includes: dividing the entire lifecycle of a lithium battery into multiple calculation stages; obtaining the activity types required for each calculation stage and retrieving corresponding collection information from a first preset association table based on the activity types to collect activity data; assigning weights to multiple initial carbon emission factors under the same activity type to calculate the carbon emission factor for each calculation stage based on the weights and the initial carbon emission factors; calculating a carbon contribution coordination factor based on the annual carbon emissions and calculating a fusion weight for each calculation stage based on the carbon contribution coordination factor; and calculating the total carbon footprint based on the activity data, fusion weights, and carbon emission factors within the same calculation stage. This invention can improve the accuracy and reliability of carbon footprint calculation throughout the lithium battery's lifecycle.

Description

Technical Field

[0001] This invention relates to the field of lithium battery carbon footprint accounting technology, and in particular to a method and system for lithium battery carbon footprint accounting based on the entire life cycle. Background Technology

[0002] With increasing global concern over climate change, the need for accurate carbon footprint calculations for products is becoming increasingly urgent across industries. As a core component of the new energy industry, lithium batteries are experiencing continuous expansion in production and application, and their carbon emissions throughout their entire lifecycle have a significant impact on the environment.

[0003] Currently, lithium battery carbon footprint accounting faces numerous challenges: Complex lifecycle stages: The lithium battery lifecycle includes multiple stages such as raw material acquisition, precursor / material manufacturing, battery assembly, packaging and transportation, use, and final waste recycling, each involving diverse processes and emission sources. Difficult data acquisition: Data sources are diverse across stages, including internal company measurements, supply chain data, industry averages, and literature data, with varying data quality and availability, making it difficult to establish a unified and standardized data collection system. Dynamic emission factors: The continuous development and changes in energy structure, production processes, and recycling technologies mean that carbon emission factors at each stage are not static. Traditional accounting methods often use static emission factors, which fail to reflect actual conditions. Therefore, there is an urgent need for an intelligent lithium battery lifecycle carbon footprint accounting method that can integrate multi-source data, dynamically adjust emission factors, adapt to different technological routes, and scientifically allocate weights. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for calculating the carbon footprint of lithium batteries based on the entire life cycle, which aims to solve the problem that the calculation results obtained by traditional technologies using static emission factors are difficult to reflect the actual situation, resulting in low accuracy and reliability.

[0005] In a first aspect, the present invention provides a method for calculating the carbon footprint of lithium batteries based on their entire life cycle, the method comprising:

[0006] The entire life cycle of lithium batteries is divided into multiple accounting stages, including the raw material acquisition stage, the precursor and positive and negative electrode material manufacturing stage, the cell manufacturing and battery packaging stage, the packaging and transportation stage, and the waste recycling and disposal stage.

[0007] Obtain the activity types required for each accounting stage, and retrieve the corresponding collection information from the first preset association table according to the activity types. The collection information includes the collection data content, collection data source, and collection method, so as to collect activity data according to the collection information.

[0008] An initial carbon emission factor is set for each data source, and weights are assigned to multiple initial carbon emission factors under the same activity type, so as to calculate the carbon emission factor for each accounting stage based on the weights and the initial carbon emission factors.

[0009] The annual carbon emissions for each accounting stage are obtained, and the carbon contribution coordination factor is calculated based on the annual carbon emissions. The fusion weight for each accounting stage is then calculated based on the carbon contribution coordination factor.

[0010] The carbon emissions for each accounting stage are calculated based on the activity data, fusion weights, and carbon emission factors under the same accounting stage, and the total carbon footprint is calculated based on the carbon emissions.

[0011] In some embodiments, the activity type includes energy consumption, material consumption, transportation activities, and waste generation, and the step of collecting activity data based on the collected information includes:

[0012] The raw signal is obtained based on the collected information, and the raw signal is preprocessed:

[0013] ;

[0014] in, , These are the signals at time t and time t-1, respectively, after wavelet transform denoising. Let be the original signal at time t. Let k be the detail coefficients of the k-th layer. This refers to the number of detail levels obtained when performing multi-scale decomposition on the signal. This is the signal after differential processing.

[0015] In some embodiments, the step of setting initial carbon emission factors for each data source and assigning weights to multiple initial carbon emission factors under the same activity type to calculate the carbon emission factor for each accounting stage based on the weights and the initial carbon emission factors includes:

[0016] The carbon emission factor is calculated using the following formula:

[0017] ;

[0018] in, This is the carbon emission factor for the j-th activity type in the i-th accounting stage after final correction. This represents the carbon emission factor for the j-th activity type in the i-th accounting stage after fuzzy-probabilistic multidimensional fusion. Let be the feedback coefficient for the j-th activity type in the i-th accounting stage, used to measure the difference between measured emission data and simulated emission data based on the fusion factor. The measured emissions from the continuous emission monitoring system. For digital twin models, The total number of data sources collected for the j-th activity type in the i-th accounting stage. Let be the expert membership degree of the k-th data source. , These are the weights of the m-th and k-th data sources, respectively. For the initial carbon emission factor of the k-th data source corresponding to the initial carbon emission factor of the j-th activity type in the i-th accounting stage, Let be the expected value of the initial carbon emission factor of the k-th data source corresponding to the initial carbon emission factor of the j-th activity type in the i-th accounting stage.

[0019] In some embodiments, the step of obtaining the annual carbon emissions for each accounting stage and calculating the carbon contribution coordination factor based on the annual carbon emissions includes:

[0020] The carbon contribution coordination factor is calculated using the following formula:

[0021] ;

[0022] in, The carbon contribution coordination factor for the i-th accounting stage. , These represent the annual carbon emissions for the i-th and n-th accounting stages, respectively.

[0023] In some embodiments, the step of calculating the fusion weights for each accounting stage based on the carbon contribution coordination factor includes:

[0024] Define the subjective weight for each accounting stage, and then weight and fuse the subjective weight with the carbon contribution coordination factor:

[0025] ;

[0026] in, Let the initial fusion weights be those for the i-th calculation stage. The carbon contribution enhancement factor, Let be the subjective weight of the i-th accounting stage;

[0027] The initial fusion weights are normalized:

[0028] ;

[0029] in, is the final fusion weight for the i-th accounting stage.

[0030] In some embodiments, the step of calculating the carbon emissions of each accounting stage based on activity data, fusion weights, and carbon emission factors under the same accounting stage, and calculating the total carbon footprint based on the carbon emissions, includes:

[0031] The carbon emissions for each accounting stage are calculated using the following formula:

[0032] ;

[0033] in, Let i be the total carbon emissions in the i-th accounting stage. The total number of activity types contained in the i-th accounting stage. This refers to the activity data under the j-th activity type in the i-th accounting stage;

[0034] The total carbon footprint is calculated using the following formula:

[0035] ;

[0036] in, The total carbon footprint of lithium battery products throughout their entire lifecycle.

[0037] Secondly, the present invention provides a lithium battery carbon footprint accounting system based on the entire life cycle, the system comprising:

[0038] The cycle division module is used to divide the entire life cycle of a lithium battery into multiple accounting stages, which include the raw material acquisition stage, the precursor and positive and negative electrode material manufacturing stage, the cell manufacturing and battery packaging stage, the packaging and transportation stage, and the waste recycling and disposal stage.

[0039] The data acquisition module is used to obtain the activity types required for each accounting stage, and retrieve the corresponding acquisition information from the first preset association table according to the activity type. The acquisition information includes the acquisition data content, acquisition data source, and acquisition method, so as to acquire activity data according to the acquisition information.

[0040] The carbon emission factor acquisition module is used to set the initial carbon emission factor for each data source and assign weights to multiple initial carbon emission factors under the same activity type, so as to calculate the carbon emission factor for each accounting stage based on the weights and the initial carbon emission factors.

[0041] The weight calculation module is used to obtain the annual carbon emissions of each accounting stage, calculate the carbon contribution coordination factor based on the annual carbon emissions, and calculate the fusion weight of each accounting stage based on the carbon contribution coordination factor.

[0042] The carbon footprint calculation module is used to calculate the carbon emissions of each accounting stage based on the activity data, fusion weights, and carbon emission factors under the same accounting stage, and to calculate the total carbon footprint based on the carbon emissions.

[0043] Thirdly, the present invention provides a storage medium that stores one or more programs, which, when executed by a processor, implement the above-described method for calculating the carbon footprint of lithium batteries based on their entire life cycle.

[0044] Fourthly, the present invention provides an electronic device, the electronic device comprising a memory and a processor, wherein:

[0045] The memory is used to store computer programs;

[0046] When the processor executes the computer program stored in the memory, it implements the above-mentioned method for calculating the carbon footprint of lithium batteries based on their entire life cycle.

[0047] Compared with the prior art, the present invention has the following advantages:

[0048] This invention comprehensively and meticulously divides the entire life cycle accounting stages of lithium batteries, standardizes the collection of activity data by the system, and uses scientific methods such as fuzzy-probabilistic multidimensional fusion to accurately determine carbon emission factors. It comprehensively considers the actual carbon emission contribution and subjective evaluation to objectively allocate the fusion weight of the accounting stages, and finally accurately calculates the carbon emission amount of each stage and the total carbon footprint of the entire life cycle. Specifically, firstly, by constructing a phased system covering the entire lifecycle of lithium batteries from raw material acquisition to waste recycling, the completeness of carbon footprint accounting is ensured. Secondly, by integrating multi-source data such as enterprise measured data, industry databases, and literature, and through data cleaning and standardization, the reliability of the data foundation is improved. By fully considering the differences and uncertainties of data from different sources, the actual situation can be reflected more scientifically and accurately, improving the accuracy and reliability of carbon emission factor calculation, thereby enhancing the precision of carbon footprint accounting. By comprehensively considering the actual carbon emission contribution and subjective evaluation factors of each accounting stage, the one-sidedness of a single subjective weight allocation is avoided, making the weight allocation more objective and accurate, and more reasonably reflecting the importance of each accounting stage in the carbon footprint of the entire lifecycle of lithium batteries. Finally, the carbon emissions of each accounting stage are accurately calculated using specific calculation formulas, and the total carbon footprint of lithium battery products throughout their entire lifecycle is obtained by summarizing them. This accurately reflects the carbon emissions of lithium batteries throughout their entire lifecycle, providing strong data support for enterprises to formulate carbon reduction strategies and evaluate the effectiveness of carbon reduction. Attached Figure Description

[0049] Figure 1This is a flowchart of a lithium battery carbon footprint accounting method based on the entire life cycle proposed in an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of the structure of a lithium battery carbon footprint accounting system based on the entire life cycle, as proposed in an embodiment of the present invention.

[0051] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Unless otherwise defined, the technical or scientific terms used herein should have the ordinary meaning understood by those skilled in the art. The terms "comprising" and similar expressions used herein mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, but does not exclude other elements or objects.

[0053] like Figure 1 The figure shows a method for calculating the carbon footprint of lithium batteries based on their entire life cycle according to an embodiment of the present invention. The method includes steps S101 to S105, wherein:

[0054] Step S101: Divide the entire life cycle of lithium batteries into multiple accounting stages, including the raw material acquisition stage, the precursor and positive and negative electrode material manufacturing stage, the cell manufacturing and battery packaging stage, the packaging and transportation stage, and the waste recycling and disposal stage.

[0055] It should be noted that in this step, the entire life cycle of a lithium battery is divided into several independent and quantifiable accounting stages, specifically including the following stages:

[0056] S1: Raw material acquisition stage (e.g., mining, refining, and initial processing of raw materials such as lithium, nickel, cobalt, manganese, graphite, electrolyte solutes / solvents, separators, and current collectors). S2: Precursor and cathode / anode material manufacturing stage (e.g., precursor preparation, cathode material synthesis, anode material graphitization and modification). S3: Cell manufacturing and battery packaging stage (e.g., cell winding / stacking, electrolyte injection, formation, capacity testing, battery module / pack assembly, and final product packaging). S4: Packaging and transportation stage (including transportation of semi-finished products between stages and transportation of the final product from the factory to the user). S5: Waste recycling and disposal stage (including collection, dismantling, valuable metal recovery, and residue disposal after battery disposal).

[0057] Step S102: Obtain the activity type required for each accounting stage, and retrieve the corresponding collection information from the first preset association table according to the activity type. The collection information includes the collection data content, collection data source, and collection method, so as to collect activity data according to the collection information.

[0058] It should be noted that the first preset association table is shown in Table 1 below:

[0059] Table 1

[0060]

[0061] It should be noted that, as shown in Table 1, each activity type corresponds to multiple data contents, multiple data sources, and multiple collection methods. Specifically, the corresponding data contents are collected according to the data source and the corresponding collection method. For example, by connecting to the API interface of the enterprise's MES / SCADA system, real-time consumption data of energy such as electricity and natural gas can be automatically obtained, thereby obtaining multiple activity data corresponding to each activity type.

[0062] Furthermore, in some embodiments, when collecting activity data, raw signals are first acquired using a sensor array, and then the raw signals are preprocessed:

[0063] ;

[0064] in, , These are the signals at time t and time t-1, respectively, after wavelet transform denoising. Let be the original signal at time t. Let k be the detail coefficients of the k-th layer. This refers to the number of detail levels obtained when performing multi-scale decomposition on the signal. The signal is the result of differential processing, and this differentially processed signal is the active data.

[0065] In summary, by using a sensor array to collect raw signals and employing wavelet transform denoising technology to effectively eliminate noise interference, followed by differential processing to highlight signal change characteristics, the purity and accuracy of the signal are significantly improved. This enhances the sensitivity and usability of the data to actual changes, enabling the system to operate reliably in complex environments and providing a more solid foundation for subsequent data analysis and decision-making.

[0066] Step S103: Set the initial carbon emission factor for each data source, and assign weights to multiple initial carbon emission factors under the same activity type, so as to calculate the carbon emission factor for each accounting stage based on the weights and the initial carbon emission factors.

[0067] It should be noted that after obtaining activity data for each activity type, the carbon emission factor is calculated using the following formula:

[0068] ;

[0069] in, This is the carbon emission factor for the j-th activity type in the i-th accounting stage after final correction. This represents the carbon emission factor for the j-th activity type in the i-th accounting stage after fuzzy-probabilistic multidimensional fusion. Let be the feedback coefficient for the j-th activity type in the i-th accounting stage, used to measure the difference between measured emission data and simulated emission data based on the fusion factor. The measured emissions from the continuous emission monitoring system. For digital twin models, The total number of data sources collected for the j-th activity type in the i-th accounting stage. Let be the expert membership degree of the k-th data source. , These are the weights of the m-th and k-th data sources, respectively. For the initial carbon emission factor of the k-th data source corresponding to the initial carbon emission factor of the j-th activity type in the i-th accounting stage, Let be the expected value of the initial carbon emission factor of the k-th data source corresponding to the initial carbon emission factor of the j-th activity type in the i-th accounting stage.

[0070] In summary, weighting can balance the advantages of different sources, making the final carbon emission factor more consistent with reality and avoiding the bias that may be caused by a single data source, thereby improving the scientificity and rationality of the carbon emission factor setting. At the same time, based on the set weights and the initial carbon emission factor, the carbon emission factor for each accounting stage is calculated using specific formulas. This process fully considers the complexity of different activity types and data sources. Finally, adjusting the fused carbon emission factor can more accurately reflect the actual carbon emission situation, reduce errors caused by incomplete or inaccurate data, and enhance the accuracy and reliability of carbon emission accounting.

[0071] Step S104: Obtain the annual carbon emissions for each accounting stage, calculate the carbon contribution coordination factor based on the annual carbon emissions, and calculate the fusion weight for each accounting stage based on the carbon contribution coordination factor.

[0072] In this step, the annual carbon emissions for each of the five life cycle stages are first calculated or statistically analyzed, denoted as C1, C2, C3, C4, and C5. Then, the carbon contribution coordination factor is calculated using the following formula:

[0073] ;

[0074] in, The carbon contribution coordination factor for the i-th accounting stage. , These represent the annual carbon emissions for the i-th and n-th accounting stages, respectively.

[0075] Furthermore, in some embodiments, it is also necessary to define the subjective weight for each accounting stage and to weight and fuse the subjective weight and the carbon contribution coordination factor:

[0076] ;

[0077] in, Let the initial fusion weights be those for the i-th calculation stage. The carbon contribution enhancement factor, Let be the subjective weight of the i-th accounting stage;

[0078] The initial fusion weights are normalized:

[0079] ;

[0080] in, is the final fusion weight for the i-th accounting stage.

[0081] In addition, it should be noted that, This value is used to balance the relative importance of expert subjective judgment and actual carbon contribution, and takes a value between [0,1]. If more emphasis is placed on the actual effect of emission reduction, it can be increased. (e.g., 0.3–0.5); if more emphasis is placed on expert judgment, the value can be reduced. (e.g., 0.1–0.2).

[0082] Furthermore, in some embodiments, all fusion weights All values ​​are greater than 0. If the weights are too large after fusion at a certain stage (e.g., exceeding 0.6), backtracking adjustment is required. This is to avoid excessive concentration of fusion weights.

[0083] In summary, calculating the carbon contribution coordination factor clearly measures the relative contribution of each accounting stage to total carbon emissions. For example, if the annual carbon emissions of a certain accounting stage are large, its carbon contribution coordination factor will also be relatively large, which helps to intuitively identify the key stages that have a significant impact on total carbon emissions. Defining the subjective weight of each accounting stage and weighting it with the carbon contribution coordination factor takes into account both subjective factors such as expert experience and policy guidance (reflected by subjective weights) and actual carbon emission data (reflected by the carbon contribution coordination factor), so that the final weight can comprehensively reflect various influencing factors and avoid bias caused by a single factor. In addition, the introduction of the carbon contribution enhancement coefficient increases the flexibility of weight calculation.

[0084] Step S105: Calculate the carbon emissions for each accounting stage based on the activity data, fusion weight, and carbon emission factor under the same accounting stage, and calculate the total carbon footprint based on the carbon emissions.

[0085] It should be noted that after calculating the weights and carbon emissions for each stage, the carbon footprint is quantified.

[0086] The carbon emissions for each accounting stage are calculated using the following formula:

[0087] ;

[0088] in, Let i be the total carbon emissions in the i-th accounting stage. The total number of activity types contained in the i-th accounting stage. This refers to the activity data under the j-th activity type in the i-th accounting stage;

[0089] The total carbon footprint is calculated using the following formula:

[0090] ;

[0091] in, The total carbon footprint of lithium battery products throughout their entire lifecycle.

[0092] In summary, the carbon emissions calculated using the above formula for each accounting stage can take into account the impact of different types of activities at each stage in great detail. Then, the carbon emissions of lithium battery products throughout their entire life cycle, from raw material acquisition, production and manufacturing, transportation, use to waste disposal, are integrated to obtain the total carbon footprint.

[0093] In summary, this invention comprehensively and meticulously divides the entire life cycle accounting stages of lithium batteries, standardizes the collection of activity data by the system, and uses scientific methods such as fuzzy-probabilistic multidimensional fusion to accurately determine carbon emission factors. It also comprehensively considers the actual carbon emission contribution and subjective evaluation to objectively allocate the fusion weight of the accounting stages, and finally accurately calculates the carbon emissions of each stage and the total carbon footprint of the entire life cycle. Specifically, firstly, by constructing a phased system covering the entire lifecycle of lithium batteries from raw material acquisition to waste recycling, the completeness of carbon footprint accounting is ensured. Secondly, by integrating multi-source data such as enterprise measured data, industry databases, and literature, and through data cleaning and standardization, the reliability of the data foundation is improved. By fully considering the differences and uncertainties of data from different sources, the actual situation can be reflected more scientifically and accurately, improving the accuracy and reliability of carbon emission factor calculation, thereby enhancing the precision of carbon footprint accounting. By comprehensively considering the actual carbon emission contribution and subjective evaluation factors of each accounting stage, the one-sidedness of a single subjective weight allocation is avoided, making the weight allocation more objective and accurate, and more reasonably reflecting the importance of each accounting stage in the carbon footprint of the entire lifecycle of lithium batteries. Finally, the carbon emissions of each accounting stage are accurately calculated using specific calculation formulas, and the total carbon footprint of lithium battery products throughout their entire lifecycle is obtained by summarizing them. This accurately reflects the carbon emissions of lithium batteries throughout their entire lifecycle, providing strong data support for enterprises to formulate carbon reduction strategies and evaluate the effectiveness of carbon reduction.

[0094] like Figure 2 As shown, one embodiment of the present invention proposes a lithium battery carbon footprint accounting system based on the entire life cycle, the system comprising:

[0095] The cycle division module 10 is used to divide the entire life cycle of a lithium battery into multiple accounting stages, including the raw material acquisition stage, the precursor and positive and negative electrode material manufacturing stage, the cell manufacturing and battery packaging stage, the packaging and transportation stage, and the waste recycling and disposal stage.

[0096] The data acquisition module 20 is used to obtain the activity types required for each accounting stage, and retrieve the corresponding acquisition information from the first preset association table according to the activity type. The acquisition information includes the acquisition data content, acquisition data source, and acquisition method, so as to acquire activity data according to the acquisition information.

[0097] The carbon emission factor acquisition module 30 is used to set the initial carbon emission factor for each data source and assign weights to multiple initial carbon emission factors under the same activity type, so as to calculate the carbon emission factor for each accounting stage based on the weights and the initial carbon emission factors.

[0098] The weight calculation module 40 is used to obtain the annual carbon emissions of each accounting stage, calculate the carbon contribution coordination factor based on the annual carbon emissions, and calculate the fusion weight of each accounting stage based on the carbon contribution coordination factor.

[0099] The carbon footprint calculation module 50 is used to calculate the carbon emissions of each accounting stage based on the activity data, fusion weights, and carbon emission factors under the same accounting stage, and to calculate the total carbon footprint based on the carbon emissions.

[0100] In another aspect, the present invention also proposes a storage medium on which one or more programs are stored, which, when executed by a processor, implement the above-described method for calculating the carbon footprint of lithium batteries based on their entire life cycle.

[0101] In another aspect, the present invention also proposes an electronic device, including a memory and a processor, wherein the memory is used to store a computer program and the processor is used to execute the computer program stored in the memory to realize the above-mentioned method for calculating the carbon footprint of lithium batteries based on the entire life cycle.

[0102] Those skilled in the art will understand that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can mean any means that can contain stored, communicated, propagated, or transmitted programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0103] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0104] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0105] While embodiments of the present invention have been described in detail above, it will be apparent to those skilled in the art that various modifications and variations can be made to these embodiments. However, it should be understood that such modifications and variations fall within the scope and spirit of the invention as set forth in the claims. Furthermore, the invention described herein may have other embodiments and can be implemented or carried out in various ways.

Claims

1. A full-life-cycle-based lithium battery carbon footprint accounting method, characterized in that, The method comprises: dividing the whole life cycle of a lithium battery into multiple accounting stages, the accounting stages comprising a raw material acquisition stage, a precursor and positive and negative electrode material manufacturing stage, a cell manufacturing and battery packaging stage, a packaging and transportation stage, a waste recovery and disposal stage; acquiring an activity type required to be collected in each accounting stage, and calling corresponding collection information from a first preset correlation table according to the activity type, the collection information comprising collection data content, collection data source, and collection method, so as to collect activity data according to the collection information; setting an initial carbon emission factor of each data source, and allocating weights to multiple initial carbon emission factors under the same activity type, so as to calculate a carbon emission factor of each accounting stage according to the weights and the initial carbon emission factors; acquiring annual carbon emission amounts of the accounting stages, and calculating a carbon contribution coordination factor according to the annual carbon emission amounts, and calculating a fusion weight of each accounting stage according to the carbon contribution coordination factor; the carbon contribution coordination factor is calculated according to the following formula: wherein, α i is a carbon contribution coordination factor of the i-th accounting stage, C i, C n are annual carbon emissions of the i-th, n-th accounting stage, respectively. defining a subjective weight of each accounting stage, and weighting and fusing the subjective weight and the carbon contribution coordination factor: w i raw = (1 - δ)ω i s +δα i , i = 1,..., 5; wherein w i raw is the initial fusion weight of the i-th accounting stage, δ is the carbon contribution enhancement coefficient, ω i s is the subjective weight of the i-th accounting stage; normalizing the initial fusion weight: wherein w i is the final fusion weight of the i-th accounting phase; calculating carbon emission amounts of the accounting stages according to activity data, fusion weights, and carbon emission factors under the same accounting stage, and calculating a total carbon footprint according to the carbon emission amounts.

2. The full life cycle based lithium battery carbon footprint accounting method according to claim 1, characterized in that, The activity type comprises energy consumption, material consumption, transportation activity, and waste generation, and the step of collecting activity data according to the collection information comprises: acquiring an original signal according to the collection information, and preprocessing the original signal: wherein, k k k k k k k k k k k k k k k k k k k k k k k k k k k k k k k k k k k k k 3.The full life cycle based lithium battery carbon footprint accounting method according to claim 2, characterized in that, The step of setting an initial carbon emission factor of each data source, and allocating weights to multiple initial carbon emission factors under the same activity type, so as to calculate a carbon emission factor of each accounting stage according to the weights and the initial carbon emission factors comprises: the carbon emission factor is calculated according to the following formula: wherein, is the carbon emission factor of the jth activity type in the ith accounting period after final revision, is the carbon emission factor of the jth activity type in the ith accounting period after fuzzy-probabilistic multi-dimensional fusion, γ ij is the feedback coefficient of the jth activity type in the ith accounting period, used to measure the difference between the measured emission data and the simulated emission data based on the fused factor, E meas is the measured emission amount of the continuous emission monitoring system, f DT is the digital twin model, K2 is the total number of data sources collected for the jth activity type in the ith accounting period, μ k is the expert membership degree of the kth data source, μ m , ω k are the weights of the mth and kth data sources, respectively, is the initial carbon emission factor of the kth data source corresponding to the initial carbon emission factor of the jth activity type in the ith accounting period, is the expected value of the initial carbon emission factor of the kth data source corresponding to the initial carbon emission factor of the jth activity type in the ith accounting period.

4. The full life cycle based lithium battery carbon footprint accounting method according to claim 3, characterized in that, The step of calculating carbon emission amounts of the accounting stages according to activity data, fusion weights, and carbon emission factors under the same accounting stage, and calculating a total carbon footprint according to the carbon emission amounts comprises: the carbon emission amount of each accounting stage is calculated according to the following formula: wherein CE i is the total carbon emissions in the i-th accounting period, K3 is the total number of activity types contained in the i-th accounting period, A ij is the activity data of the j-th activity type in the i-th accounting period; the total carbon footprint is calculated according to the following formula: where CF total is the total carbon footprint of the lithium battery product over its full life cycle.

5. A full life cycle based lithium battery carbon footprint accounting system, characterized in that, The system comprises: a period division module, configured to divide the whole life cycle of a lithium battery into multiple accounting stages, the accounting stages comprising a raw material acquisition stage, a precursor and positive and negative electrode material manufacturing stage, a cell manufacturing and battery packaging stage, a packaging and transportation stage, a waste recovery and disposal stage; a data collection module, configured to acquire an activity type required to be collected in each accounting stage, and call corresponding collection information from a first preset correlation table according to the activity type, the collection information comprising collection data content, collection data source, and collection method, so as to collect activity data according to the collection information; a fusion weight calculation module, configured to set an initial carbon emission factor of each data source, and allocate weights to multiple initial carbon emission factors under the same activity type, so as to calculate a carbon emission factor of each accounting stage according to the weights and the initial carbon emission factors; The carbon emission factor acquisition module is configured to set initial carbon emission factors of each data source, and assign weights to a plurality of the initial carbon emission factors under the same activity type, so as to calculate carbon emission factors of each accounting stage according to the weights and the initial carbon emission factors; The weight calculation module is configured to obtain annual carbon emission amounts of each accounting stage, calculate a carbon contribution coordination factor according to the annual carbon emission amounts, and calculate fusion weights of each accounting stage according to the carbon contribution coordination factor; The carbon contribution coordination factor is calculated according to the following formula: wherein, α i is the carbon contribution coordination factor of the i-th accounting stage, C i , C n is the annual carbon emission of the i-th, n-th accounting stage, respectively; The subjective weight of each accounting stage is defined, and the subjective weight and the carbon contribution coordination factor are fused by weighting: w i raw = (1 - δ)ω i s +δα i , i = 1,..., 5; wherein w i raw is the initial fusion weight of the i-th accounting phase, δ is the carbon contribution enhancement coefficient, ω i s is the subjective weight of the i-th accounting phase; The initial fusion weight is normalized: wherein w i is the final fusion weight of the i-th accounting phase; The carbon footprint calculation module is configured to calculate carbon emission amounts of each accounting stage according to activity data, fusion weights and carbon emission factors under the same accounting stage, and calculate a total carbon footprint according to the carbon emission amounts.

6. A storage medium, characterized by The storage medium stores one or more programs, which are executed by the processor to implement the full-life-cycle-based lithium battery carbon footprint accounting method according to any one of claims 1-4.

7. An electronic device, comprising: The electronic device includes a memory and a processor, wherein: The memory is configured to store a computer program; The processor is configured to execute the computer program stored on the memory to implement the full-life-cycle-based lithium battery carbon footprint accounting method according to any one of claims 1-4. The electronic device includes a memory and a processor, wherein: The memory is configured to store a computer program; The processor is configured to execute the computer program stored on the memory to implement the full-life-cycle-based lithium battery carbon footprint accounting method according to any one of claims 1-4.

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