Lithium ion battery evaluation method and electronic equipment

Abstract

The invention discloses a lithium ion battery evaluation method and electronic equipment. Relates to the technical field of batteries, and the method comprises the steps that carbon footprint information of the lithium ion battery is obtained, the carbon footprint information comprises carbon footprints corresponding to multiple treatment stages of the lithium ion battery, and the multiple treatment stages at least comprise a raw material collection and processing stage, a manufacturing stage, a using stage and a waste treatment stage; acquiring cost information and battery performance information of the lithium ion battery; and based on the carbon footprint information, the cost information and the battery performance information corresponding to the plurality of processing stages, determining a comprehensive evaluation result of the lithium ion battery. According to the method and the device, the technical problem of inaccurate lithium ion battery evaluation caused by incomplete consideration factors during lithium ion battery evaluation in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of battery technology, and in particular to a lithium ion battery evaluation method and electronic equipment. Background Art

[0002] As the pursuit of clean energy and sustainable development continues to grow, lithium-ion batteries, as an efficient energy storage device, have been widely used in electric vehicles, consumer electronics, energy storage systems and other fields. The lithium-ion battery industry has developed rapidly, and its output and market size have continued to expand. However, the production and use of lithium-ion batteries will also have a certain impact on the environment. From the mining and processing of raw materials to the manufacture, use and disposal of batteries, each link involves energy consumption and greenhouse gas emissions. Therefore, accurately calculating and evaluating the product carbon footprint of lithium-ion batteries throughout their life cycle is of great significance for promoting the sustainable development of the lithium-ion battery industry. In the relevant technology, when evaluating lithium-ion batteries, the factors considered are not comprehensive. For example, if only the carbon footprint is focused on, these important performance advantages in actual use will be obscured, and it is impossible to fully measure the contribution of the battery to reducing the use of fuel vehicles and reducing carbon emissions from transportation, resulting in inaccurate evaluation of lithium-ion batteries.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present invention provide a lithium-ion battery evaluation method and electronic device to at least solve the technical problem in the related art that incomplete factors are considered when evaluating a lithium-ion battery, resulting in inaccurate evaluation of the lithium-ion battery.

[0005] According to one aspect of an embodiment of the present invention, a lithium-ion battery evaluation method is provided, comprising: obtaining carbon footprint information of the lithium-ion battery, wherein the carbon footprint information includes carbon footprints corresponding to the lithium-ion battery in multiple processing stages, and the multiple processing stages include at least: a raw material collection and processing stage, a manufacturing stage, a use stage, and a waste treatment stage; obtaining cost information and battery performance information of the lithium-ion battery; and determining a comprehensive evaluation result of the lithium-ion battery based on the carbon footprint information, cost information, and battery performance information corresponding to the multiple processing stages.

[0006] Optionally, based on the carbon footprint information, cost information and battery performance information corresponding to the multiple processing stages, a comprehensive evaluation result of the lithium-ion battery is determined, including: based on the carbon footprint information, cost information and battery performance information, determining multiple indicators for evaluation, and the relative importance of the multiple indicators; based on the relative importance of the multiple indicators, determining the static weights corresponding to the multiple indicators; based on the static weights corresponding to the multiple indicators and the state values ​​corresponding to the multiple indicators, determining the dynamic weights corresponding to the multiple indicators, wherein the state value is used to indicate the specific numerical value of the corresponding indicator; based on the dynamic weights corresponding to the multiple indicators, determining the comprehensive evaluation result of the lithium-ion battery.

[0007] In the above method, by introducing dynamic weights based on carbon footprint information, cost information and battery performance information, a comprehensive, flexible and accurate evaluation of the comprehensive benefits of lithium-ion batteries can be achieved.

[0008] Optionally, based on the relative importance corresponding to the multiple indicators, the static weights corresponding to the multiple indicators are determined, including: based on the relative importance corresponding to the multiple indicators, constructing a judgment matrix, wherein the elements in the judgment matrix are used to indicate the relative importance between any two indicators; performing a consistency check on the judgment matrix; if the consistency check of the judgment matrix passes, solving the maximum eigenvector of the judgment matrix; based on the maximum eigenvector, obtaining the static weights corresponding to the multiple indicators.

[0009] In the above method, by constructing and solving the judgment matrix, a scientific, quantitative and consistent indicator importance evaluation and weight determination method is provided for the comprehensive benefit evaluation system of lithium-ion batteries, thereby enhancing the reliability and acceptability of the evaluation results.

[0010] Optionally, the carbon footprint information includes the carbon footprint of the raw material collection and processing stage, the carbon footprint of the manufacturing stage, the carbon footprint of the use stage and the carbon footprint of the waste disposal stage; the cost information includes the direct cost, indirect cost and life cycle of the lithium-ion battery; the battery performance information includes the electrical performance, kinetic performance and safety performance of the lithium-ion battery.

[0011] In the above approach, the comprehensiveness and accuracy of the evaluation system can be ensured by classifying the carbon footprint, cost and performance information of lithium-ion batteries in detail.

[0012] Optionally, the method also includes: obtaining carbon footprints corresponding to multiple processing stages; determining the full life cycle carbon footprint of the lithium-ion battery based on the carbon footprints corresponding to the multiple processing stages; detecting whether the carbon footprints corresponding to the multiple processing stages exceed the preset thresholds of the corresponding stages, and whether the full life cycle carbon footprint exceeds the preset total threshold; among the carbon footprints corresponding to the multiple processing stages, if the carbon footprint of any stage exceeds the preset threshold of the corresponding stage, or the full life cycle carbon footprint exceeds the preset total threshold, issuing an alarm indication.

[0013] In the above methods, by establishing a threshold warning mechanism, not only can the carbon footprint of lithium-ion batteries throughout their life cycle be monitored in real time, but warnings can also be issued in a timely manner, prompting relevant parties to take effective measures to reduce carbon emissions, thereby ensuring the environmental sustainability of the product while promoting lithium-ion batteries to develop in a greener and more environmentally friendly direction.

[0014] Optionally, the method also includes: when the carbon footprint of any stage corresponding to multiple processing stages exceeds the preset threshold of the corresponding stage, or the carbon footprint of the entire life cycle exceeds the preset total threshold, based on the carbon footprint difference between the carbon footprint of any stage and the preset threshold of the corresponding stage, or the carbon footprint difference between the entire life cycle and the preset total threshold, determining the energy-saving and emission reduction strategy of the lithium-ion battery; based on the energy-saving and emission reduction strategy, optimizing the carbon emissions of the lithium-ion battery.

[0015] In the above methods, by formulating and implementing energy-saving and emission reduction strategies based on the difference in carbon footprint between the actual and preset thresholds, accurate emission reduction guidance can be provided, which helps to promote the environmental benefits of the lithium-ion battery industry.

[0016] Optionally, obtaining carbon footprint information of lithium-ion batteries includes: obtaining the carbon footprint of lithium-ion batteries in the raw material collection and processing stages by:

[0017]

[0018] Among them, E ycl,j is the carbon footprint of the j-th unit number of lithium-ion batteries in the raw material collection and processing stage, in kgCO 2 / unit product; j is the battery type identification of the lithium-ion battery; X S The amount of raw materials of type s required to produce unit batteries of type j; E ycl,s is the product carbon footprint of the sth unit raw material obtained in the processing stage of lithium-ion batteries, and n is the total number of raw materials used in the raw material collection and processing stages; AD i1 Data on activities of category i1 involved in processing raw materials of category s units; EF i1The carbon emission factor for the i1th activity data involved in processing the sth unit raw material; GWP i1 The global warming trend value of carbon dioxide converted from the i1th type of greenhouse gas emissions involved in processing the sth type of raw material; n1 represents the total number of activity data involved in the processing stage.

[0019] In the above method, the carbon footprint of raw material collection and processing stages can be accurately calculated, which helps to accurately evaluate and manage the environmental impact of lithium-ion battery production.

[0020] Optionally, obtaining carbon footprint information of the lithium-ion battery includes: obtaining the carbon footprint of the lithium-ion battery during the manufacturing stage by:

[0021]

[0022] Among them, E zz，j is the carbon footprint of a unit number of lithium-ion batteries during the manufacturing phase, in kgCO 2 / unit product;AD i2 Data on Category i2 activities involved in manufacturing unit quantities of lithium-ion batteries; EF i2 Carbon emission factor for the i2 activity data involved in manufacturing a unit quantity of lithium-ion batteries; GWP i2 The i2th category greenhouse gas emissions involved in manufacturing a unit number of lithium-ion batteries are converted into the global warming trend value of carbon dioxide, and n2 represents the total number of activity data involved in the manufacturing stage.

[0023] In the above manner, accurate calculation of the carbon footprint of the lithium-ion battery manufacturing stage can be achieved, which helps to accurately quantify and manage the environmental impact of the manufacturing process.

[0024] Optionally, obtaining carbon footprint information of a lithium-ion battery includes obtaining the carbon footprint of the lithium-ion battery during the use phase by:

[0025]

[0026] Among them, E ss，j is the carbon footprint of a unit number of lithium-ion batteries during the use phase, in kgCO2 / unit product; AD i3 Data on activities of category i3 involving the use of a unit quantity of lithium-ion batteries; EF i3 Carbon emission factor for Category i3 activity data related to the use of a unit quantity of lithium-ion batteries; GWP i3 The i3th category greenhouse gas emissions involved in the use of a unit number of lithium-ion batteries are converted into the global warming trend value of carbon dioxide, and n3 represents the total number of categories of activity data involved in the use phase.

[0027] In the above method, not only can the carbon footprint of lithium-ion batteries during the use phase be accurately calculated, but also the carbon emission management during the use of batteries can be strengthened.

[0028] Optionally, obtaining carbon footprint information of the lithium-ion battery includes: obtaining the carbon footprint of the lithium-ion battery at the waste treatment stage by:

[0029]

[0030] Among them, E fq，j is the carbon footprint of a unit number of lithium-ion batteries during the waste treatment phase, in kgCO 2 / unit product;AD i4 Data on Category i4 activities related to the number of lithium-ion batteries disposed of; EF i4 Carbon emission factor for category i4 activity data related to the waste treatment of a unit number of lithium-ion batteries; GWP i4 The i4th category greenhouse gas emissions involved in the disposal of a unit number of lithium-ion batteries are converted into the global warming trend value of carbon dioxide, and n4 represents the total number of activity data involved in the disposal stage.

[0031] In the above method, not only can the carbon footprint of lithium-ion batteries in the waste treatment stage be accurately calculated, but also the carbon footprint assessment system for the entire life cycle can be improved.

[0032] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement any one of the lithium-ion battery evaluation methods.

[0033] In an embodiment of the present invention, by acquiring carbon footprint information of a lithium-ion battery, wherein the carbon footprint information includes the carbon footprints of the lithium-ion battery corresponding to multiple processing stages, the multiple processing stages at least including: a raw material collection and processing stage, a manufacturing stage, a use stage, and a waste treatment stage; acquiring cost information and battery performance information of the lithium-ion battery; and determining a comprehensive evaluation result of the lithium-ion battery based on the carbon footprint information, cost information, and battery performance information corresponding to the multiple processing stages, the purpose of comprehensively evaluating the lithium-ion battery based on the carbon footprint information, cost information, and battery performance information of the lithium-ion battery at each stage is achieved, thereby achieving the technical effect of accurately calculating the carbon footprint of the lithium-ion battery throughout its life cycle and performing effective battery evaluation to promote energy conservation and emission reduction of the lithium-ion battery, thereby solving the technical problem in the related art that inaccurate evaluation of the lithium-ion battery is caused by incomplete consideration of factors when evaluating the lithium-ion battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0035] Figure 1 is a flow chart of a lithium-ion battery evaluation method according to an embodiment of the present invention;

[0036] Figure 2 is a flow chart of an optional lithium-ion battery evaluation method according to an embodiment of the present invention;

[0037] Figure 3 is a schematic diagram of an optional lithium-ion battery life cycle system boundary according to an embodiment of the present invention;

[0038] Figure 4 It is a flow chart of an optional battery comprehensive benefit evaluation module method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0040] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0041] According to an embodiment of the present invention, a method embodiment of lithium-ion battery evaluation is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0042] Figure 1 is a flow chart of a lithium-ion battery evaluation method according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0043] Step S102, obtaining carbon footprint information of the lithium-ion battery;

[0044] Optionally, the carbon footprint information includes carbon footprints corresponding to the lithium-ion battery in multiple processing stages, and the multiple processing stages include at least: raw material collection and processing stage, manufacturing stage, use stage and waste treatment stage;

[0045] In an optional embodiment, obtaining carbon footprint information of a lithium-ion battery includes: obtaining the carbon footprint of the lithium-ion battery during the raw material collection and processing stage by the following method:

[0046]

[0047] Among them, E ycl,j is the carbon footprint of the j-th unit number of lithium-ion batteries in the raw material collection and processing stage, in kgCO 2 / unit product; j is the battery type identification of the lithium-ion battery; X S The amount of raw materials of type s required to produce unit batteries of type j; E ycl,s is the product carbon footprint of the sth unit raw material obtained in the processing stage of lithium-ion batteries, and n is the total number of raw materials used in the raw material collection and processing stages; AD i1Data on activities of category i1 involved in processing raw materials of category s units; EF i1 The carbon emission factor for the i1th activity data involved in processing the sth unit raw material; GWP i1 The global warming trend value of carbon dioxide converted from the i1th type of greenhouse gas emissions involved in processing the sth type of raw material; n1 represents the total number of activity data involved in the processing stage.

[0048] Optionally, the activity data involved in the raw material collection and processing stage of lithium-ion batteries may include but are not limited to data related to raw material mining, production, molding, and refining processes, data related to raw material and energy production and transportation processes, data related to raw material transportation processes, and collection of waste treatment data and the amount of qualified products generated by the above processes. Based on the above data and in accordance with the corresponding carbon emission factors, the carbon footprint of lithium-ion batteries in the raw material collection and processing stage is calculated in the above manner.

[0049] Optionally, by quantifying the carbon emission factors and global warming trend values ​​of greenhouse gas emissions for each type of activity (such as mining, transportation, refining, etc.), the carbon footprint of this stage can be accurately calculated. This accurate calculation is crucial for carbon emission assessment throughout the life cycle and helps to accurately identify and manage the environmental impact of battery production. The activity data in the formula involves a series of key activities in the collection and processing of raw materials, such as mining, production, refining, transportation, etc., which can ensure the comprehensiveness of the carbon footprint calculation in the raw material collection and processing stage, that is, not only direct carbon emissions are taken into account, but also indirect energy consumption and greenhouse gas emissions are covered, thereby providing a more comprehensive environmental impact assessment. By calculating the carbon footprint of each type of raw material, the contribution of different raw materials to the environmental impact of the battery can be quantified, so that manufacturers can choose raw materials with less environmental impact, optimize the supply chain, and thus reduce the carbon footprint of battery production. In the above method, the accurate calculation of the carbon footprint of the raw material collection and processing stage can be achieved, which helps to accurately evaluate and manage the environmental impact of lithium-ion battery production.

[0050] In an optional embodiment, obtaining carbon footprint information of a lithium-ion battery includes: obtaining the carbon footprint of the lithium-ion battery during the manufacturing stage by:

[0051]

[0052] Among them, E zz，j is the carbon footprint of a unit number of lithium-ion batteries during the manufacturing phase, in kgCO 2 / unit product;AD i2 Data on Category i2 activities involved in manufacturing unit quantities of lithium-ion batteries; EF i2Carbon emission factor for the i2 activity data involved in manufacturing a unit quantity of lithium-ion batteries; GWP i2 The i2th category greenhouse gas emissions involved in manufacturing a unit number of lithium-ion batteries are converted into the global warming trend value of carbon dioxide, and n2 represents the total number of activity data involved in the manufacturing stage.

[0053] Optionally, the activity data involved in the manufacturing stage of lithium-ion batteries may include, but are not limited to, data related to energy consumption in the manufacturing process, data related to equipment and facilities, data related to waste and by-products in the production process, and the amount of qualified products. Based on the above data and in accordance with the corresponding carbon emission factors, the carbon footprint of lithium-ion batteries in the manufacturing stage is calculated in the above manner.

[0054] Optionally, the above calculation method of the carbon footprint of lithium-ion batteries in the manufacturing stage covers the calculation of the carbon footprint of the manufacturing stage, including the carbon emissions of all related activities, such as energy consumption, equipment use, waste disposal, etc. This allows the carbon emissions of lithium-ion batteries in the manufacturing stage to be fully quantified, which can provide enterprises with clear sources of carbon emissions, help to accurately manage carbon emissions and formulate emission reduction strategies. Each of the activity data, carbon emission factors and global warming trend values ​​corresponds to a specific link in the manufacturing process, making the calculation of the carbon footprint of the manufacturing process more refined. This refined management helps enterprises identify carbon emission high points and take targeted optimization measures, such as improving production processes, upgrading equipment, and adopting green energy, so as to effectively reduce the carbon footprint of the manufacturing stage. The formula includes battery type identification, which means that the carbon footprint of different types of batteries in the manufacturing process may be different. This differentiated consideration helps enterprises to formulate specific emission reduction plans for different battery types, optimize product portfolios, and improve the environmental benefits of the entire product line. In the above method, the accurate calculation of the carbon footprint of lithium-ion batteries in the manufacturing stage can be achieved, which helps to accurately quantify and manage the environmental impact of the manufacturing process.

[0055] In an optional embodiment, obtaining carbon footprint information of a lithium-ion battery includes: obtaining the carbon footprint of the lithium-ion battery during the use phase by:

[0056]

[0057] Among them, E ss，j is the carbon footprint of a unit number of lithium-ion batteries during the use phase, in kgCO 2 / unit product;AD i3 Data on activities of category i3 involving the use of a unit quantity of lithium-ion batteries; EF i3 Carbon emission factor for Category i3 activity data related to the use of a unit quantity of lithium-ion batteries; GWP i3The i3th category greenhouse gas emissions involved in the use of a unit number of lithium-ion batteries are converted into the global warming trend value of carbon dioxide, and n3 represents the total number of categories of activity data involved in the use phase.

[0058] Optionally, the above calculation method of the carbon footprint of lithium-ion batteries in the use phase covers all activity data, carbon emission factors and global warming trend values ​​related to the use of lithium-ion batteries, which can achieve refined management of carbon emissions during the use of batteries. This helps to accurately identify the sources of carbon emissions in the use phase, and then take targeted measures to reduce carbon emissions. Calculating the carbon footprint of lithium-ion batteries in the use phase involves data such as battery charging and discharging, energy consumption, and performance, which can not only evaluate the efficiency of the battery itself, but also reflect the impact of user behavior on carbon emissions. For example, frequent charging and discharging and high energy consumption will increase the carbon footprint, thereby prompting companies and users to optimize their use strategies, improve energy efficiency, and reduce unnecessary energy consumption. By calculating and disclosing the carbon footprint of lithium-ion batteries in the use phase, the environmental awareness of consumers and the industry can be enhanced, and all relevant parties can be urged to pay more attention to reducing carbon emissions. For users, understanding the impact of battery use on the environment can promote more environmentally friendly usage habits; for companies, this can drive them to develop products with higher energy efficiency and lower carbon emissions. In the above method, not only can the carbon footprint of lithium-ion batteries during the use phase be accurately calculated, but also the carbon emission management during the use of batteries can be strengthened.

[0059] Optionally, the activity data involved in the use phase of the lithium-ion battery may include, but is not limited to, data related to the charging and discharging of the lithium-ion battery during use, data related to energy consumption during use, data related to battery performance and the amount of qualified products. Based on the above data and in accordance with the corresponding carbon emission factors, the carbon footprint of the lithium-ion battery during the use phase is calculated in the above manner.

[0060] In an optional embodiment, obtaining carbon footprint information of a lithium-ion battery includes: obtaining the carbon footprint of the lithium-ion battery at the waste treatment stage by:

[0061]

[0062] Among them, E fq，j is the carbon footprint of a unit number of lithium-ion batteries during the waste treatment phase, in kgCO 2 / unit product;AD i4 Data on Category i4 activities related to the number of lithium-ion batteries disposed of; EF i4 Carbon emission factor for category i4 activity data related to the waste treatment of a unit number of lithium-ion batteries; GWP i4The i4th category greenhouse gas emissions involved in the disposal of a unit number of lithium-ion batteries are converted into the global warming trend value of carbon dioxide, and n4 represents the total number of activity data involved in the disposal stage.

[0063] Optionally, the activity data involved in the waste treatment stage of lithium-ion batteries may include, but are not limited to, transportation-related data during the waste treatment process, recycling-related data during the waste treatment process, disassembly and material separation-related data, reuse and disposal-related data and the amount of qualified products. Based on the above data, the carbon footprint of the products in the waste treatment stage is calculated according to the corresponding carbon emission factors.

[0064] Optionally, the above calculation method of the carbon footprint of lithium-ion batteries in the waste treatment stage quantifies the carbon footprint of the waste treatment stage, which supplements and improves the carbon footprint assessment system of the entire life cycle of lithium-ion batteries, and can ensure the comprehensiveness and accuracy of the assessment. Carbon emissions in the waste treatment stage are an important but often overlooked part of the battery life cycle. Quantifying the carbon footprint of this stage helps to fully understand the environmental impact of batteries. Calculating the carbon footprint of the waste treatment stage involves multiple activities such as waste transportation, recycling, disassembly, material separation, reuse and disposal, which prompts companies to optimize waste management processes, improve recycling efficiency, and reduce carbon emissions during the treatment process. For example, measures such as improving recycling technology, optimizing logistics arrangements, and increasing material reuse rates can effectively reduce the environmental burden of this stage. In the above method, not only can the carbon footprint of lithium-ion batteries in the waste treatment stage be accurately calculated, but also the carbon footprint assessment system of the entire life cycle can be improved.

[0065] In an optional embodiment, the method also includes: obtaining carbon footprints corresponding to multiple processing stages; determining the full life cycle carbon footprint of the lithium-ion battery based on the carbon footprints corresponding to the multiple processing stages; detecting whether the carbon footprints corresponding to the multiple processing stages exceed the preset thresholds of the corresponding stages, and whether the full life cycle carbon footprint exceeds the preset total threshold; among the carbon footprints corresponding to the multiple processing stages, if the carbon footprint of any stage exceeds the preset threshold of the corresponding stage, or the full life cycle carbon footprint exceeds the preset total threshold, issuing an alarm indication.

[0066] Optionally, by setting the carbon footprint thresholds for each processing stage and the total carbon footprint threshold for the entire life cycle, an early warning mechanism is established, which can monitor the carbon emissions of the battery at different stages in real time. When the carbon footprint exceeds the preset threshold, an alarm indication can be immediately issued to remind the relevant parties to take measures. By calculating the carbon footprint of the lithium-ion battery throughout its life cycle, rather than focusing on a single stage, the comprehensiveness and systematicness of the assessment can be ensured. The perspective of the entire life cycle helps to identify the hot spots of carbon emissions in the entire product chain and provide global guidance for the formulation of emission reduction measures. Setting thresholds and conducting real-time monitoring enables battery manufacturers, users and recyclers to respond to high carbon emissions in a timely manner and take energy-saving and carbon reduction measures, such as optimizing the raw material supply chain, improving production and manufacturing processes, improving usage efficiency and promoting battery recycling. This timely response helps to reduce the environmental impact of batteries and promote green production and consumption. By monitoring the carbon footprint at different stages and comparing it with the preset threshold, emission reduction targets and strategies can be formulated based on actual data to avoid blind decision-making. This ensures the scientificity and effectiveness of decision-making and helps achieve sustainable development. In the above methods, by establishing a threshold warning mechanism, not only can the carbon footprint of lithium-ion batteries throughout their life cycle be monitored in real time, but warnings can also be issued in a timely manner, prompting relevant parties to take effective measures to reduce carbon emissions, thereby ensuring the environmental sustainability of the product while promoting lithium-ion batteries to develop in a greener and more environmentally friendly direction.

[0067] Optionally, the carbon footprint (carbon emissions) of the raw materials of lithium-ion batteries per unit product in the collection and processing stage, manufacturing stage, use stage and waste disposal stage are collected separately, and the carbon emissions of each stage are accumulated to obtain the full life cycle carbon footprint of the lithium-ion battery per unit product.

[0068] Optionally, the full life cycle carbon footprint of lithium-ion batteries can be calculated by, but is not limited to, the following methods:

[0069] E total,j =E ycl,j +E zz,j +E ss,j +E fq,j

[0070] Among them, E total，j The carbon footprint of the whole life cycle of lithium-ion batteries per unit quantity, in kgCO 2 / unit product.

[0071] Optionally, a carbon footprint database for products at each stage and a carbon footprint database for products throughout the life cycle of various types of lithium-ion batteries may be pre-set. If the carbon footprint of products at any other stage exceeds a single-stage threshold, or the carbon footprint of products throughout the life cycle of lithium-ion batteries exceeds a total threshold, an early warning is triggered.

[0072] In an optional embodiment, the method further includes: when the carbon footprint of any stage among the carbon footprints corresponding to multiple processing stages exceeds the preset threshold of the corresponding stage, or the carbon footprint of the entire life cycle exceeds the preset total threshold, based on the carbon footprint difference between the carbon footprint of any stage and the preset threshold of the corresponding stage, or the carbon footprint difference between the carbon footprint of the entire life cycle and the preset total threshold, determining the energy-saving and emission reduction strategy of the lithium-ion battery; based on the energy-saving and emission reduction strategy, optimizing the carbon emissions of the lithium-ion battery.

[0073] Optionally, by comparing the actual carbon footprint with the preset threshold, determining the difference, and formulating energy conservation and emission reduction strategies based on this difference, more accurate emission reduction guidance can be provided. Since the stage and degree of exceeding the threshold are clearly defined, the formulated strategy can directly target these high emission points to ensure the effectiveness and pertinence of emission reduction measures. After determining the energy conservation and emission reduction strategy, the carbon emission of lithium-ion batteries is further optimized. This optimization is a dynamic process, which can be dynamically adjusted according to the changes in the carbon footprint of the battery at different stages and the difference from the threshold. For example, if the carbon footprint of the raw material collection and processing stage exceeds the threshold, the company can optimize the supply chain, select raw material suppliers with lower carbon emissions, or improve the processing technology to reduce carbon emissions. By implementing energy conservation and emission reduction strategies, the carbon footprint of lithium-ion batteries can be effectively controlled, thereby improving their environmental benefits. This is particularly important for key technologies such as lithium-ion batteries that are widely used in the fields of clean energy and sustainable development, which helps to promote the entire industry to develop in a more environmentally friendly and sustainable direction. Energy conservation and emission reduction can not only reduce environmental impact, but also bring economic benefits. Optimized production processes and more efficient energy use often reduce costs. For the use phase, improving battery efficiency and reducing energy consumption also means reducing user costs. In the above methods, by formulating and implementing energy-saving and emission reduction strategies based on the difference between the actual and preset carbon footprints, accurate emission reduction guidance can be provided, which helps promote the environmental benefits of the lithium-ion battery industry.

[0074] Optionally, the carbon footprint composition of lithium ions can be analyzed based on the carbon footprint value of the product over the entire life cycle, or the carbon footprint data of each stage, and suggestions for energy conservation and carbon reduction can be given.

[0075] Optionally, the carbon footprint of lithium-ion batteries throughout their life cycle and at each stage can be monitored in real time, timely warnings can be issued when carbon emissions exceed the standard, appropriate emission reduction measures can be taken, and continuous tracking and monitoring can be performed. The data after monitoring can then be stored to enrich the corresponding carbon database.

[0076] Step S104, obtaining cost information and battery performance information of the lithium-ion battery;

[0077] In an optional embodiment, the carbon footprint information includes the carbon footprint of the raw material collection and processing stage, the carbon footprint of the manufacturing stage, the carbon footprint of the use stage and the carbon footprint of the waste disposal stage; the cost information includes the direct cost, indirect cost and life cycle of the lithium-ion battery; the battery performance information includes the electrical performance, kinetic performance and safety performance of the lithium-ion battery.

[0078] Optionally, the carbon footprint information is set to cover the four key stages of raw material collection and processing, manufacturing, use and waste treatment, the cost information covers direct costs, indirect costs and life cycle costs, and the battery performance information includes electrical performance, kinetic performance and safety performance. This detailed classification can ensure that the evaluation system can fully capture the performance of lithium-ion batteries in different dimensions, avoid the one-sidedness of the evaluation, and make the evaluation results more comprehensive and accurate. By subdividing the carbon footprint information into the above four stages, the assessment of the environmental impact of lithium-ion batteries is more refined, and it is possible to identify which stages contribute the most to the overall carbon footprint, thereby providing a clear direction for the formulation of emission reduction strategies. For example, if the carbon footprint of the manufacturing stage is found to be particularly high, the company can focus on improving the manufacturing process and energy efficiency to achieve the goal of reducing the overall carbon footprint. The classification of cost information includes not only direct costs (material procurement, manufacturing, transportation, etc.), but also indirect costs (research and development, management, etc.) and life cycle costs (maintenance, replacement, etc.). This comprehensive consideration enables the evaluation system to comprehensively analyze the economic benefits of lithium-ion batteries, helps companies identify key points of cost control, and takes into account the cost-effectiveness of batteries throughout their life cycle, promoting cost efficiency and optimizing the battery life cycle. The classification of battery performance information covers electrical performance, kinetic performance and safety performance, which can ensure that the evaluation system can evaluate the functional performance of the battery from multiple dimensions. Electrical performance evaluation can ensure the basic power output and stability of the battery; kinetic performance evaluation focuses on the battery's charge and discharge performance, life and energy density; and safety performance evaluation can ensure the safety of the battery under different conditions. This multi-dimensional evaluation helps to comprehensively measure the applicability of the battery. In the above method, the comprehensiveness and accuracy of the evaluation system can be ensured by detailed classification of the carbon footprint, cost and performance information of lithium-ion batteries.

[0079] Step S106, determining a comprehensive evaluation result of the lithium-ion battery based on the carbon footprint information, cost information, and battery performance information corresponding to the multiple processing stages.

[0080] Optionally, based on the carbon footprint information corresponding to multiple processing stages, namely, the carbon footprint of raw material collection and processing stage, the carbon footprint of manufacturing stage, the carbon footprint of use stage and the carbon footprint of waste disposal stage, as well as cost information and battery performance information, a comprehensive assessment of lithium-ion batteries is conducted from the perspectives of carbon footprint, cost and battery performance over the entire life cycle, thereby improving the accuracy of lithium-ion battery assessment.

[0081] In an optional embodiment, based on the carbon footprint information, cost information and battery performance information corresponding to the multiple processing stages, a comprehensive evaluation result of the lithium-ion battery is determined, including: based on the carbon footprint information, cost information and battery performance information, determining multiple indicators for evaluation, and the relative importance corresponding to the multiple indicators; based on the relative importance corresponding to the multiple indicators, determining the static weights corresponding to the multiple indicators; based on the static weights corresponding to the multiple indicators, and the state values ​​corresponding to the multiple indicators, determining the dynamic weights corresponding to the multiple indicators, wherein the state value is used to indicate the specific numerical value of the corresponding indicator; based on the dynamic weights corresponding to the multiple indicators, determining the comprehensive evaluation result of the lithium-ion battery.

[0082] Optionally, by combining the carbon footprint information of lithium-ion batteries at different life cycle stages such as raw material collection and processing, manufacturing, use and waste disposal with cost information and battery performance information, the environmental, economic and functional benefits of the battery can be comprehensively evaluated, providing a comprehensive perspective to help decision makers understand the comprehensive performance of the battery in different dimensions. The introduction of dynamic weights enables the weights of different indicators to be dynamically adjusted according to the actual state of the lithium-ion battery at each stage. This means that when problems or optimizations occur at a certain stage of the battery (such as a sudden increase in carbon footprint or a significant reduction in cost), such changes can be reflected in a timely manner to ensure that the evaluation results are more accurate and real-time. Static weights can reflect the basic importance of indicators in the early stage of the evaluation system construction, while dynamic weights adjust this importance according to changes in the actual indicator status value, increasing the flexibility of the evaluation. This dynamic adjustment mechanism can take into account changes in actual operating conditions, making the evaluation results closer to the actual performance of lithium-ion batteries and improving the accuracy of the evaluation. The use of dynamic weights can not only provide immediate evaluation results, but also provide guidance for the continuous improvement of lithium-ion batteries. For example, if the assessment shows that the carbon footprint weight in the use phase increases significantly, it may indicate the need to optimize the battery's charging and discharging strategy or improve energy efficiency to reduce carbon emissions in the use phase. By comprehensively considering carbon footprint, cost and battery performance, a scientific basis can be provided for battery design, production, use and recycling decisions. Decision makers can weigh environmental, economic and functional benefits based on the comprehensive assessment results, make more reasonable decisions, and promote the sustainable development of the battery industry. In summary, by introducing dynamic weights based on carbon footprint information, cost information and battery performance information, a comprehensive, flexible and accurate assessment of the comprehensive benefits of lithium-ion batteries can be achieved.

[0083] In an optional embodiment, based on the relative importance corresponding to the multiple indicators, the static weights corresponding to the multiple indicators are determined, including: based on the relative importance corresponding to the multiple indicators, a judgment matrix is ​​constructed, wherein the elements in the judgment matrix are used to indicate the relative importance between any two indicators; a consistency check is performed on the judgment matrix; if the consistency check of the judgment matrix passes, the maximum eigenvector of the judgment matrix is ​​solved; based on the maximum eigenvector, the static weights corresponding to the multiple indicators are obtained.

[0084] Optionally, by constructing a judgment matrix, a quantitative method can be provided for the importance of indicators in the evaluation of lithium-ion batteries. The elements in the judgment matrix can reflect the relative importance between any two evaluation indicators, which helps to convert the subjective judgment of experts into objective values ​​and increase the scientificity and rigor of the evaluation system. Before solving the maximum eigenvector of the judgment matrix, it is a crucial step to perform a consistency test. The consistency test can ensure that the evaluation of the relative importance of each indicator in the judgment matrix is ​​mathematically reasonable and consistent, avoiding evaluation bias caused by inconsistency or contradiction in expert judgment, thereby improving the reliability of static weights. The maximum eigenvector method is used to solve the weight of the judgment matrix, which is a mathematical method commonly used in the analytic hierarchy process (AHP). It can find a vector so that each element of the vector (i.e., weight) matches the consistency of the judgment matrix. This method can ensure the fairness of weight distribution and avoid the weight value being affected by any indicator being too large or too small, thereby obtaining a more balanced and accurate static weight. The determination of static weights establishes a stable basic framework for the comprehensive benefit evaluation of lithium-ion batteries. In the initial construction stage and relatively stable operation period of the battery evaluation system, static weights can provide a reference for the basic importance of each indicator, and provide a stable basis for the operation of the evaluation system and the interpretation of the results. The consistency check based on the judgment matrix and the maximum eigenvector method to solve the weights can ensure the scientificity and acceptability of the lithium-ion battery evaluation system. This method not only takes into account the judgment of experts, but also verifies it through mathematical tools, making the evaluation results more accurate and reliable. In the above method, by constructing and solving the judgment matrix, a scientific, quantitative and consistent indicator importance evaluation and weight determination method is provided for the comprehensive benefit evaluation system of lithium-ion batteries, thereby enhancing the reliability and acceptability of the evaluation results.

[0085] As an optional embodiment, a comprehensive benefit evaluation index system framework for lithium-ion batteries can be constructed, specifically including levels, elements included in each level and indicators included in each element. Specifically, carbon footprint information, cost information and battery performance information are used as levels. Based on the levels, elements corresponding to each level and indicators corresponding to each element, an evaluation index system framework is constructed, wherein the elements include carbon footprint elements, cost elements and battery performance elements. The carbon footprint elements include carbon footprints corresponding to multiple processing stages, the cost elements include direct costs, indirect costs and life cycles of lithium-ion batteries, and the battery performance elements include electrical properties, kinetic properties and safety performance of lithium-ion batteries. According to the relative importance of each indicator to the comprehensive benefit of lithium-ion batteries, the basic principle of AHP can be used to divide the hierarchical structure, the importance of each indicator can be scored by the Delphi method, the judgment matrix can be constructed by pairwise comparison using the scaling method, the consistency test can be performed, and the constant weight of each indicator can be obtained by applying the maximum eigenvector method. According to the influence factors (i.e., static weights) related to the influence of each indicator on the comprehensive benefit of the battery and its proportion, a state variable weight vector that satisfies normalization is constructed to obtain a variable weight model, and the construction of the comprehensive benefit evaluation index system of the battery is completed.

[0086] Optionally, the state variable weight vector C that satisfies the normalization property may be set as: C = (c 1 ......c i ......c n ). The contingency model can be expressed in the following form:

[0087]

[0088] Among them, c i is the i-th element in the state variable weight vector C, that is, the state value of the i-th indicator, Wi is the variable weight (i.e., dynamic weight) corresponding to the i-th indicator, W i (c) is the constant weight corresponding to the i-th indicator, W k (c) is the constant weight (i.e. static weight) corresponding to the kth indicator, c k is the kth element in the state variable weight vector C.

[0089] When the state value of indicator i decreases, that is, the state of the indicator is optimized, the assigned weight increases; when the state value of indicator i increases, that is, the state of the indicator is deteriorated, the assigned weight decreases.

[0090] Optionally, the corresponding indicators of carbon footprint in the raw material collection and processing stage include the carbon emission indicators of positive electrode material production and transportation, the carbon emission indicators of negative electrode material production and transportation, the carbon emission indicators of electrolyte material production and transportation, the carbon emission indicators of diaphragm material production and transportation, and the carbon emission indicators of other auxiliary materials production and transportation; the corresponding indicators of carbon footprint in the manufacturing stage include the carbon emission indicators of the battery production process; the corresponding indicators of carbon footprint in the use stage include the carbon emission indicators in the use stage; the corresponding indicators of carbon footprint in the waste treatment stage include the carbon emission indicators in the waste treatment stage and the potential carbon emission indicators caused by non-recycling; the corresponding indicators of direct costs include material procurement cost indicators, manufacturing cost indicators and transportation cost indicators; the corresponding indicators of indirect costs include R&D cost sharing indicators and management cost sharing indicators; the corresponding indicators of life cycle include maintenance cost indicators and replacement cost prediction indicators; the corresponding indicators of electrical performance include operating voltage range indicators, voltage stability indicators and capacity characteristic indicators; the corresponding indicators of kinetic performance include charge and discharge rate indicators, expected number of cycles indicators and capacity attenuation trend indicators; the corresponding indicators of safety performance include thermal runaway protection indicators and electrical safety indicators.

[0091] Through the above steps S102 to S106, the purpose of comprehensively evaluating lithium-ion batteries based on the carbon footprint information, cost information and battery performance information of lithium-ion batteries at various stages can be achieved, thereby realizing accurate calculation of the carbon footprint of lithium-ion batteries throughout their life cycle and conducting effective battery evaluation, so as to promote the technical effect of energy conservation and emission reduction of lithium-ion batteries, thereby solving the technical problem in the related art that inaccurate lithium-ion battery evaluation is caused by incomplete consideration of factors when conducting lithium-ion battery evaluation.

[0092] Based on the above embodiments and optional embodiments, the present invention proposes an optional implementation of a lithium-ion battery evaluation system, which includes a product carbon footprint collection and calculation module, a carbon footprint threshold warning module, an energy-saving and carbon reduction module, a continuous monitoring module and a battery comprehensive benefit evaluation module. Figure 2 is a flow chart of an optional lithium-ion battery evaluation method according to an embodiment of the present invention, the system can be used to perform the following steps: Figure 2 The method shown specifically includes:

[0093] The product carbon footprint collection and calculation module collects the carbon emissions of lithium-ion batteries at each stage. Figure 3 1 is a schematic diagram of an optional lithium-ion battery life cycle system boundary according to an embodiment of the present invention. Specifically, the lithium ions of the unit product are collected in the following manner: Figure 3The carbon emissions of the battery raw material collection and processing stage, manufacturing stage, use stage and waste treatment stage are shown. The carbon emissions of each stage are accumulated to obtain the carbon footprint of the unit product lithium-ion battery throughout its life cycle. Among them, the battery raw material collection and processing stage needs to collect various carbon emission data related to raw material collection and processing at this stage. After the data collection is completed, the carbon footprint of the product in the raw material collection and processing stage is calculated based on the corresponding carbon emission factor; the manufacturing stage needs to collect the carbon emission data related to manufacturing at this stage. After the data collection is completed, the carbon footprint of the product in the manufacturing stage is calculated based on the corresponding carbon emission factor; the use stage needs to collect the carbon emission data related to use at this stage. After the data collection is completed, the carbon footprint of the product in the use stage is calculated based on the corresponding carbon emission factor; the waste treatment stage needs to collect the carbon emission data related to use at this stage. After the data collection is completed, the carbon footprint of the product in the waste treatment stage is calculated based on the corresponding carbon emission factor. The carbon footprint of the lithium-ion battery product throughout the certification cycle can be calculated by accumulating the carbon footprint of each stage. The specific calculation process is the same as above and will not be repeated here.

[0094] The carbon footprint early warning module has a built-in carbon footprint database for products at each stage and a carbon footprint database for all types of lithium-ion batteries throughout their life cycle. If the carbon footprint of products at any other stage exceeds the single-stage threshold, or the carbon footprint of lithium-ion batteries throughout their life cycle exceeds the total threshold, an early warning is triggered. The carbon footprint threshold for the life cycle of the j-th battery product is J. total,j , when E total,j >J total,j , triggering an alarm. The carbon footprint threshold of a single-stage product is J i,j , when E i,j >J i,j , triggering an alarm.

[0095] The energy-saving and carbon-reduction module analyzes the carbon footprint value of the battery throughout its life cycle, or the carbon footprint data of each stage, determines the carbon emission composition, and assists in formulating reasonable energy-saving and carbon-reduction recommendations and goals.

[0096] The continuous monitoring module monitors the carbon footprint of lithium-ion batteries throughout their life cycle and at each stage in real time, issues early warnings when they exceed the standard, takes corresponding emission reduction measures, and continuously tracks and monitors. The monitored data is then transmitted to the carbon data collection module to enrich the carbon database.

[0097] The battery comprehensive benefit evaluation module is mainly used to build a comprehensive benefit evaluation index system framework for lithium-ion batteries. Figure 4 is a flow chart of an optional battery comprehensive benefit evaluation module method according to an embodiment of the present invention, such as Figure 4 As shown, the specific steps include:

[0098] 1) Starting from the three aspects of battery carbon footprint, cost and battery performance, a comprehensive benefit evaluation index system for lithium-ion batteries is constructed. The specific framework of the evaluation index system is shown in Table 1 below.

[0099] 2) Select corresponding indicators from 10 factors, including carbon footprint in the raw material collection and processing stage, carbon footprint in the manufacturing stage, carbon footprint in the use stage and carbon footprint in the waste disposal stage, direct cost, indirect cost, life cycle, electrical properties, dynamic properties and safety performance.

[0100] 3) Construct a comprehensive benefit evaluation index system framework for lithium-ion batteries.

[0101] 4) According to the relative importance of various indicators on the comprehensive benefits of the battery, the basic principles of AHP are used to calculate the basic weight of each indicator through hierarchical structure, judgment matrix construction, consistency test and other steps.

[0102] 5) According to the normalization requirements and the influencing factors related to the impact of each factor on the comprehensive benefit of the battery and its proportion, a "variable weight" calculation method is designed to comprehensively reflect the relative importance of a certain indicator in the evaluation process.

[0103] Table 1 Evaluation index system framework

[0104]

[0105]

[0106] In this embodiment, by collecting carbon emission data of lithium-ion batteries at each stage, the carbon footprint data of lithium-ion batteries at each stage and throughout their life cycle are automatically calculated. When the carbon footprint value of the product at this stage exceeds the threshold, or the single-stage threshold of the carbon footprint of the product at any stage, an early warning is triggered, and combined with the carbon footprint data, energy-saving and carbon reduction technical recommendations are given. At the same time, this standard establishes a comprehensive evaluation method for battery benefits from the three levels of carbon footprint, cost, and battery performance, reflecting the integrity of the evaluation indicators.

[0107] According to an embodiment of the present application, an embodiment of a non-volatile storage medium is also provided. Optionally, in this embodiment, the non-volatile storage medium includes a stored program, wherein when the program is executed, the device where the non-volatile storage medium is located is controlled to execute any of the above-mentioned lithium-ion battery evaluation methods.

[0108] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group, and the non-volatile storage medium includes a stored program.

[0109] Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: obtaining carbon footprint information of the lithium-ion battery, wherein the carbon footprint information includes the carbon footprints corresponding to the lithium-ion battery in multiple processing stages, and the multiple processing stages include at least: raw material collection and processing stage, manufacturing stage, use stage and waste treatment stage; obtaining cost information and battery performance information of the lithium-ion battery; and determining a comprehensive evaluation result of the lithium-ion battery based on the carbon footprint information, cost information and battery performance information corresponding to the multiple processing stages.

[0110] According to an embodiment of the present application, an embodiment of a processor is also provided. Optionally, in this embodiment, the processor is used to run a program, wherein the program executes any one of the above-mentioned lithium-ion battery evaluation methods when it is run.

[0111] According to an embodiment of the present application, an embodiment of a computer program product is also provided. When executed on a data processing device, it is suitable for executing a program that initializes any one of the steps of the lithium-ion battery evaluation method described above.

[0112] Optionally, the above-mentioned computer program product, when executed on a data processing device, is suitable for executing a program that initializes the following method steps: obtaining carbon footprint information of a lithium-ion battery, wherein the carbon footprint information includes the carbon footprints corresponding to the lithium-ion battery in multiple processing stages, and the multiple processing stages include at least: raw material collection and processing stage, manufacturing stage, use stage and waste treatment stage; obtaining cost information and battery performance information of the lithium-ion battery; and determining a comprehensive evaluation result of the lithium-ion battery based on the carbon footprint information, cost information and battery performance information corresponding to the multiple processing stages.

[0113] An embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the following steps are implemented: obtaining carbon footprint information of a lithium-ion battery, wherein the carbon footprint information includes carbon footprints corresponding to the lithium-ion battery in multiple processing stages, and the multiple processing stages include at least: a raw material collection and processing stage, a manufacturing stage, a use stage, and a waste treatment stage; obtaining cost information and battery performance information of the lithium-ion battery; and determining a comprehensive evaluation result of the lithium-ion battery based on the carbon footprint information, cost information, and battery performance information corresponding to the multiple processing stages.

[0114] The above sequence of the embodiments of the present invention is for description only and does not represent the superiority or inferiority of the embodiments.

[0115] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0116] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the above modules can be a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, modules or indirect coupling or communication connection of modules, which can be electrical or other forms.

[0117] The modules described above as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0118] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of software functional modules.

[0119] If the above-mentioned integrated module is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a non-volatile storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present invention. The aforementioned non-volatile storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0120] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A lithium-ion battery evaluation method, characterized in that: include: Acquire carbon footprint information of the lithium-ion battery, wherein the carbon footprint information includes carbon footprints of the lithium-ion battery corresponding to multiple processing stages, and the multiple processing stages include at least: raw material collection and processing stage, manufacturing stage, use stage, and waste treatment stage; Obtaining cost information and battery performance information of the lithium-ion battery; Based on the carbon footprint information, the cost information, and the battery performance information respectively corresponding to the multiple processing stages, a comprehensive evaluation result of the lithium-ion battery is determined.

2. The method according to claim 1, characterized in that: The step of determining a comprehensive evaluation result of the lithium-ion battery based on the carbon footprint information, the cost information, and the battery performance information respectively corresponding to the multiple processing stages includes: Determining, based on the carbon footprint information, the cost information, and the battery performance information, a plurality of indicators for evaluation, and relative importances corresponding to the plurality of indicators; Determining static weights corresponding to the multiple indicators based on the relative importances corresponding to the multiple indicators; Determine the dynamic weights corresponding to the multiple indicators based on the static weights corresponding to the multiple indicators and the state values ​​corresponding to the multiple indicators, wherein the state values ​​are used to indicate the specific values ​​of the corresponding indicators; Based on the dynamic weights respectively corresponding to the multiple indicators, a comprehensive evaluation result of the lithium-ion battery is determined.

3. The method according to claim 2, characterized in that The determining, based on the relative importances respectively corresponding to the multiple indicators, the static weights respectively corresponding to the multiple indicators comprises: Based on the relative importances respectively corresponding to the multiple indicators, a judgment matrix is ​​constructed, wherein the elements in the judgment matrix are used to indicate the relative importance between any two indicators; Performing a consistency check on the judgment matrix; When the consistency check of the judgment matrix passes, solving the maximum eigenvector of the judgment matrix; Based on the maximum eigenvector, static weights corresponding to the multiple indicators are obtained.

4. The method according to claim 2, characterized in that: The carbon footprint information includes the carbon footprint of the raw material collection and processing stage, the carbon footprint of the manufacturing stage, the carbon footprint of the use stage and the carbon footprint of the waste treatment stage; the cost information includes the direct cost, indirect cost and life cycle of the lithium-ion battery; the battery performance information includes the electrical performance, kinetic performance and safety performance of the lithium-ion battery.

5. The method according to claim 1, characterized in that: The method further comprises: Obtaining carbon footprints corresponding to the multiple processing stages respectively; Determining the full life cycle carbon footprint of the lithium-ion battery based on the carbon footprints corresponding to the multiple processing stages respectively; Detecting whether the carbon footprints corresponding to the multiple processing stages respectively exceed the preset thresholds of the corresponding stages, and whether the whole life cycle carbon footprint exceeds the preset total threshold; In the carbon footprints corresponding to the multiple processing stages, if the carbon footprint of any stage exceeds the preset threshold of the corresponding stage, or the whole life cycle carbon footprint exceeds the preset total threshold, an alarm indication is issued.

6. The method according to claim 5, characterized in that The method further comprises: In the case where the carbon footprint of any stage among the carbon footprints corresponding to the multiple processing stages exceeds the preset threshold of the corresponding stage, or the carbon footprint of the whole life cycle exceeds the preset total threshold, based on the carbon footprint difference between the carbon footprint of any stage and the preset threshold of the corresponding stage, or the carbon footprint difference between the carbon footprint of the whole life cycle and the preset total threshold, determine the energy conservation and emission reduction strategy of the lithium-ion battery; Based on the energy-saving and emission-reduction strategy, the carbon emission of the lithium-ion battery is optimized.

7. The method according to any one of claims 1 to 6, characterized in that: The obtaining of carbon footprint information of lithium-ion batteries includes: The carbon footprint of the lithium-ion battery during the raw material collection and processing stage is obtained by: Among them, E ycl,j is the carbon footprint of the j-th unit quantity of the lithium-ion battery in the raw material collection and processing stage, in kgCO2 / unit product; j is the battery type identifier of the lithium-ion battery; X S The amount of raw materials of type s required to produce unit batteries of type j; E ycl,s is the product carbon footprint of the sth type of unit raw material obtained in the processing stage of the lithium-ion battery, and n is the total number of types of raw materials used in the raw material collection and processing stage; AD i1 Data on activities of category i1 involved in processing the raw materials of the said category s unit; EF i1 The carbon emission factor of the activity data of category i1 involved in processing the raw materials of category s; GWP i1 The global warming trend value of carbon dioxide converted from the i1th type of greenhouse gas emissions involved in processing the sth type of unit raw material; n1 represents the total number of activity data involved in the processing stage.

8. The method according to any one of claims 1 to 6, characterized in that: The obtaining of carbon footprint information of lithium-ion batteries includes: The carbon footprint of the lithium-ion battery in the manufacturing stage is obtained as follows: Among them, E zz，j is the carbon footprint of the lithium-ion battery in the manufacturing stage, in kgCO2 / unit product; AD i2 Data on activities in category i2 involved in manufacturing the unit quantity of the lithium-ion battery; EF i2 The carbon emission factor of the activity data of category i2 involved in manufacturing a unit quantity of the lithium-ion battery; GWP i2 The i2th category greenhouse gas emissions involved in manufacturing a unit number of the lithium-ion batteries are converted into a global warming trend value of carbon dioxide, and n2 represents the total number of categories of activity data involved in the manufacturing stage.

9. The method according to any one of claims 1 to 6, characterized in that: The obtaining of carbon footprint information of lithium-ion batteries includes: The carbon footprint of the lithium-ion battery in the use phase is obtained by: Among them, E ss，j is the carbon footprint of the lithium-ion battery in the use phase, in kgCO2 / unit product; AD i3 Data on activities of category i3 involving the use of a unit quantity of the lithium-ion battery; EF i3 The carbon emission factor for the i3th activity data involved in the use of a unit quantity of the lithium-ion battery; GWP i3 The i3th category greenhouse gas emissions involved in using a unit number of the lithium-ion batteries are converted into a global warming trend value of carbon dioxide, and n3 represents the total number of categories of activity data involved in the use phase.

10. The method according to any one of claims 1 to 6, characterized in that: The obtaining of carbon footprint information of lithium-ion batteries includes: The carbon footprint of the lithium-ion battery at the waste treatment stage is obtained by: Among them, E fq，j is the carbon footprint of the lithium-ion battery in the waste treatment stage, in kgCO2 / unit product; AD i4 Data on the i4th category of activities related to the number of units of lithium-ion batteries for waste treatment; EF i4 The carbon emission factor of the i4th activity data related to the number of lithium-ion batteries disposed of; GWP i4 The i4th type of greenhouse gas emissions involved in the waste treatment unit number of the lithium-ion batteries are converted into the global warming trend value of carbon dioxide, and n4 represents the total number of types of activity data involved in the waste treatment stage.

11. An electronic device, characterized in that: The invention comprises one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the lithium ion battery evaluation method according to any one of claims 1 to 10.

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