Accurate calculation method of carbon footprint of lithium ion battery based on regional energy structure

Abstract

The application discloses a lithium ion battery carbon footprint accurate accounting method based on regional energy structure, relates to the technical field of data accounting, determines the energy structure in each region and the corresponding proportion, obtains the corresponding unit carbon emission factor of the energy structure based on a database for calculation, obtains the comprehensive power carbon emission factor in each region, and a comprehensive power carbon emission factor model is constructed; and a whole life cycle accounting stage model is constructed. The comprehensive power carbon emission factor model can mark and store the corresponding region of the comprehensive power carbon emission factor, the carbon emission of the lithium ion battery can be quickly and accurately calculated based on the comprehensive power carbon emission factor model and the energy consumption data of the lithium ion battery in each stage and region, and the carbon footprint of the lithium ion battery under the whole life cycle is accounted in a regional manner, which is more accurate than accounting according to a fixed factor.

Description

Technical Field

[0001] This invention relates to the field of data accounting technology, specifically to a method for accurate accounting of the carbon footprint of lithium-ion batteries based on regional energy structures. Background Technology

[0002] In mainstream international carbon footprint databases, carbon emission data for different regions generally suffer from outdated information, insufficient representativeness, and ambiguous accounting boundaries, failing to accurately reflect the high proportion of clean energy in some regions. Using this data for calculations would lead to distorted results, impacting lithium battery exports. Furthermore, the entire lifecycle of a lithium-ion battery requires a certain amount of time, making it difficult to systematically store the energy consumption data generated during storage. Secure management of this data during storage is also challenging, affecting the accurate calculation of the lithium-ion battery's carbon footprint. Moreover, it's difficult to establish a one-to-one correspondence between the resulting carbon footprint and the lithium-ion battery, hindering carbon footprint traceability for lithium-ion batteries. Summary of the Invention

[0003] The purpose of this invention is to provide a method for accurately calculating the carbon footprint of lithium-ion batteries based on regional energy structures, in order to address the shortcomings in the prior art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a method for accurate calculation of the carbon footprint of lithium-ion batteries based on regional energy structure, comprising the following steps:

[0005] The energy structure and corresponding proportion of each region are determined, and the unit carbon emission factor corresponding to the energy structure is obtained from the database for calculation to obtain the comprehensive electricity carbon emission factor of each region, and a comprehensive electricity carbon emission factor model is constructed.

[0006] A full life-cycle accounting stage model is constructed, and energy consumption data of lithium-ion batteries at each stage are collected based on the accounting stage model. The data is then used to construct a comprehensive electricity carbon emission factor model for protection in real time.

[0007] Based on the energy consumption data of lithium-ion batteries at various stages and the corresponding comprehensive power carbon emission factor model, the carbon footprint emissions of lithium-ion batteries at each stage are obtained, and a carbon footprint line is generated.

[0008] Generate a battery carbon footprint report based on the carbon footprint line.

[0009] In a preferred embodiment, the steps of determining the energy structure and corresponding proportion of each region, calculating the unit carbon emission factor corresponding to the energy structure based on the database, obtaining the comprehensive electricity carbon emission factor for each region, and constructing the comprehensive electricity carbon emission factor model include:

[0010] The management covers multiple regions, and the energy structure and corresponding proportion of each region are determined. The energy structure includes multiple energy types.

[0011] Set up a database that stores multiple energy types and their corresponding unit carbon emission factors;

[0012] The unit carbon emission factor corresponding to the energy structure in each region is obtained from the database. The comprehensive electricity carbon emission factor in each region is calculated based on the proportion of the energy structure and the unit carbon emission factor.

[0013] A comprehensive electricity carbon emission factor model is constructed based on the comprehensive electricity carbon emission factor of each region.

[0014] In a preferred embodiment, the step of constructing a comprehensive electricity carbon emission factor model based on the comprehensive electricity carbon emission factors of each region includes:

[0015] We jointly construct electronic maps for multiple regions, store these electronic maps on an accounting platform, and set up multiple accounting packages and multiple data chains corresponding to the electronic maps on the accounting platform to obtain carbon footprint pins.

[0016] By marking the comprehensive electricity carbon emission factors of each region on an electronic map, a comprehensive electricity carbon emission factor model is obtained.

[0017] In a preferred embodiment, the step of obtaining carbon footprint pins by setting up multiple accounting packages and multiple data chains in the corresponding electronic map accounting platform includes:

[0018] In the accounting platform, multiple accounting packages are set up corresponding to the electronic map, and each accounting package is connected to all data chains. The data chain consists of multiple data points connected in a chain.

[0019] In the accounting platform, data surfaces are configured corresponding to the electronic map. Based on the data surfaces, multiple synchronization points are marked in each area of ​​the electronic map, and the synchronization points in a single area are interconnected.

[0020] Electronic maps containing accounting packages and data chains are used as carbon footprint pins.

[0021] In a preferred embodiment, the step of constructing a full life-cycle accounting stage model, collecting energy consumption data of lithium-ion batteries at each stage based on the accounting stage model, and constructing protection measures in a comprehensive electricity carbon emission factor model in real time includes:

[0022] The accounting stages of the entire life cycle of lithium-ion batteries are determined, including the raw material mining stage, the production and manufacturing stage, the usage stage, and the recycling and processing stage. Corresponding cloud servers are configured for each accounting stage and connected in sequence to obtain the accounting stage model.

[0023] Energy consumption data of lithium-ion batteries at each stage are collected according to the accounting stage model;

[0024] An accounting package is activated whenever there is a raw material mining stage, and the energy consumption data of the raw material mining stage is recorded through the accounting package;

[0025] Once the production and manufacturing stage begins and the quantity of lithium-ion batteries is obtained, the corresponding data chain for the number of lithium-ion batteries is activated through the accounting package, and the data chain is bound one-to-one with the lithium-ion batteries.

[0026] The data points in the data chain are matched sequentially with the corresponding calculation stages of the lithium-ion battery, and the energy consumption data of the calculation stages are recorded.

[0027] The accounting package binds multiple corresponding data chains together. The accounting package assigns a unique movement rule to data points in the same accounting stage in multiple data chains. The movement rule is the movement path between multiple synchronization points in the corresponding area of ​​the lithium-ion battery data point in the electronic map. Multiple data chains complete the construction in the comprehensive power carbon emission factor model, and the comprehensive power carbon emission factor model is used to monitor the anomalies of data points.

[0028] In a preferred embodiment, the step of monitoring data points for anomalies using a comprehensive electricity carbon emission factor model includes:

[0029] Based on the accounting package, data points in multiple data chains that are enabled will be sequentially bound to each other, and movement rules will be assigned to the corresponding bound data points.

[0030] The connection channel between the corresponding synchronization points is temporarily opened according to the movement rules, and the data points are transferred to the next synchronization point according to the movement rules. The connection channels between the remaining synchronization points are disconnected.

[0031] The authorized network records the movement rules, and a temporary space is set up in the accounting platform. The authorized network and the data point are connected through the temporary space. The authorized network moves with the data point according to the movement rules to access and obtain energy consumption data. When the data point moves to the next synchronization point according to the movement rules, the connection between the authorized network and the data point is disconnected during the transfer process. The energy consumption data before the disconnection is temporarily stored in the temporary space until all the energy consumption data in the corresponding data point is obtained according to the movement rules. After the access is completed, the energy consumption data in the temporary space is cleared.

[0032] When a data point is accessed by an unauthorized network, the data point will move between multiple synchronization points in the corresponding area according to the movement rules. When the unauthorized network accesses the data point for more than the preset conditions, it is regarded as an abnormal data point. The energy consumption data in the data point is copied to generate a new data point to replace the abnormal data point, the energy consumption data in the abnormal data point is destroyed, and the abnormal data point is connected to the unauthorized network.

[0033] In a preferred embodiment, the step of obtaining the carbon footprint emissions of the lithium-ion battery at each stage based on energy consumption data of the lithium-ion battery at each stage and the corresponding comprehensive electricity carbon emission factor model, and generating a carbon footprint line, includes:

[0034] Energy consumption data for each stage recorded in the data points of the accounting platform are obtained through the authorized network, and the comprehensive electricity carbon emission factor of the region where the energy consumption data is located is determined based on the comprehensive electricity carbon emission factor model.

[0035] Based on energy consumption data and comprehensive electricity carbon emission factor calculations, the carbon footprint emissions of lithium-ion batteries at each stage are obtained. The carbon footprint emissions are arranged according to the accounting stage to obtain the carbon footprint line.

[0036] In a preferred embodiment, the step of generating a battery carbon footprint report based on the carbon footprint line includes:

[0037] The reference carbon footprint total emissions were obtained based on the EU fixed factor method and energy consumption data of lithium-ion batteries at various stages.

[0038] Based on the carbon footprint line, the total carbon footprint emissions of lithium-ion batteries and the emission ratio of each stage are obtained, and a battery carbon footprint report is generated. The battery carbon footprint report includes the total carbon footprint emissions, the emission ratio of each stage, and a comparison report of the differences between the total carbon footprint emissions and the EU fixed factor method.

[0039] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0040] This invention uses a comprehensive electricity carbon emission factor model to mark and store regions corresponding to the comprehensive electricity carbon emission factor. Based on the comprehensive electricity carbon emission factor model and the energy consumption data of lithium-ion batteries at various stages and within regions, the carbon emissions of lithium-ion batteries can be calculated quickly and accurately. The carbon footprint calculation of lithium-ion batteries throughout their entire life cycle by region is more accurate than the calculation based on fixed factors. Based on the comprehensive electricity carbon emission factor model, independent carbon footprint management of lithium-ion batteries can also be carried out.

[0041] The integrated electricity carbon emission factor model can store the carbon footprint of lithium-ion batteries corresponding to energy consumption data independently, while also providing assistance in data storage security. Subsequently, the carbon footprint of lithium-ion batteries can be calculated through the energy consumption data stored in the data chain, which has a good role in the traceability and management of the carbon footprint of lithium-ion batteries. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0043] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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.

[0045] Example 1, please refer to Figure 1 As shown in this embodiment, the method for accurately calculating the carbon footprint of lithium-ion batteries based on regional energy structure includes the following steps:

[0046] S1. Determine the energy structure and corresponding proportion in each region, obtain the unit carbon emission factor corresponding to the energy structure from the database, calculate the comprehensive electricity carbon emission factor in each region, and construct the comprehensive electricity carbon emission factor model.

[0047] S2. Construct a full life cycle accounting stage model, collect energy consumption data of lithium-ion batteries at each stage based on the accounting stage model, and construct a comprehensive power carbon emission factor model for protection in real time.

[0048] S3. Based on the energy consumption data of lithium-ion batteries at each stage and the corresponding comprehensive power carbon emission factor model, the carbon footprint emissions of lithium-ion batteries at each stage are obtained, and a carbon footprint line is generated.

[0049] S4. Generate a battery carbon footprint report based on the carbon footprint line (a comparative report on the differences between the total carbon footprint emissions, the emission percentage of each stage, and the total carbon footprint emissions using the EU fixed factor method).

[0050] As described in steps S1-S4 above, the integrated electricity carbon emission factor model allows for the marking and storage of regions corresponding to the integrated electricity carbon emission factor. Based on this model and energy consumption data of lithium-ion batteries at various stages and within each region, the carbon emissions of lithium-ion batteries can be calculated quickly and accurately. Calculating the carbon footprint of lithium-ion batteries across their entire lifecycle by region is more accurate than calculating using fixed factors. The integrated electricity carbon emission factor model also enables independent carbon footprint management for lithium-ion batteries, facilitating better traceability. Furthermore, the integrated electricity carbon emission factor model allows for the independent storage of energy consumption data corresponding to the carbon footprint of lithium-ion batteries, while also providing support for data storage security. Subsequently, the carbon footprint of lithium-ion batteries can be calculated using the energy consumption data stored via a data chain, providing effective traceability and management of lithium-ion battery carbon footprints.

[0051] In one embodiment, step S1, which involves determining the energy structure and corresponding proportion of each region, calculating the unit carbon emission factor corresponding to the energy structure based on the database, obtaining the comprehensive electricity carbon emission factor for each region, and constructing the comprehensive electricity carbon emission factor model, includes:

[0052] S11. Determine the multiple regions under management, and determine the energy structure and corresponding proportion of each region. The energy structure includes multiple energy types (coal-fired power, gas-fired power, hydropower, wind power, photovoltaic power, and nuclear power; the proportion here is the ratio of the energy structure to the total power generation in the region).

[0053] S12. Set up a database, which stores multiple energy types and their corresponding unit carbon emission factors;

[0054] S13. Obtain the unit carbon emission factor corresponding to the energy structure in each region based on the database, and calculate the comprehensive electricity carbon emission factor in each region based on the proportion of the energy structure and the unit carbon emission factor.

[0055] S14. Construct a comprehensive electricity carbon emission factor model based on the comprehensive electricity carbon emission factors of each region.

[0056] In one embodiment, step S14 of constructing a comprehensive electricity carbon emission factor model based on the comprehensive electricity carbon emission factors of each region includes:

[0057] S141. Jointly construct electronic maps of multiple regions, store the electronic maps in the accounting platform, set up multiple accounting packages and multiple data chains in the accounting platform corresponding to the electronic maps, and obtain carbon footprint pins.

[0058] S142. Mark the comprehensive electricity carbon emission factor of each region on the electronic map to obtain the comprehensive electricity carbon emission factor model.

[0059] In one embodiment, the corresponding electronic map sets up multiple accounting packages and multiple data chains in the accounting platform. Step S141, which obtains the carbon footprint pin, includes:

[0060] S1411. In the accounting platform, multiple accounting packages are set up corresponding to the electronic map, and each accounting package is connected to all data chains. The data chain consists of multiple data points connected in a chain.

[0061] S1412. In the accounting platform, a data surface is configured corresponding to the electronic map. Based on the data surface, multiple synchronization points are marked in each area of ​​the electronic map, and the synchronization points in a single area are interconnected.

[0062] S1413. Use an electronic map with a calculation package and data link as a carbon footprint pin.

[0063] As described in steps S11-S14 above, the energy structure within the management area must first be collected. This energy structure includes coal-fired power, gas-fired power, hydropower, wind power, photovoltaic power, and nuclear power. The percentage here refers to the proportion of total power generation within the area. For coal-fired power, the percentage is calculated as: (coal consumption * coal carbon content * oxidation rate - desulfurization and carbon sequestration) / power generation, typically ranging from 0.75 to 0.90. kgCO2 / kWh, this refers to the range for mainstream coal types; for gas-fired power: (natural gas consumption * natural gas carbon content * oxidation rate) / power generation, typically ranging from 0.30-0.40 kgCO2 / kWh; for hydropower: only indirect carbon emissions during the construction phase (such as dams and power plants) and operation and maintenance are considered, direct emissions are negligible, typically ranging from 0.01-0.03 kgCO2 / kWh; for wind / solar power: only indirect carbon emissions during equipment production (such as wind turbines and solar panels), transportation, and installation are considered, typically ranging from 0.01-0.02 kgCO2 / kWh; for nuclear power: only indirect carbon emissions during nuclear fuel extraction, processing, and transportation are considered, typically ranging from 0.01-0.05 kgCO2 / kWh; the corresponding unit carbon emission factor range is obtained for each energy type. Within a region, such as a province, there may be multiple energy types, and the energy structure is not singular. Therefore, after obtaining the unit carbon emission factor for a single energy type, and combining it with the proportion of electricity generated by that energy type within the region, the comprehensive electricity carbon emission factor for the region can be calculated. For example, if a region has 60% thermal power, 20% hydropower, and 20% wind power, then the power structure for that region is: 60% thermal power (unit carbon emission factor: 0.8 kg CO2 / kWh), 20% hydropower (unit carbon emission factor: 0.02 kg CO2 / kWh), and 20% wind power (unit carbon emission factor: 0.015 kg CO2 / kWh). Therefore, the comprehensive electricity carbon emission factor for that region is: 0.6 × 0.8 + 0.2 × 0.02 + 0.2 × 0.015 = 0.The target emission rate is 487 kg CO2 / kWh. Since this involves multiple regions (provinces), it's necessary to obtain the comprehensive electricity carbon emission factor for each region (province) using this method. Obtaining the comprehensive electricity carbon emission factor for each region based on its energy structure allows for more accurate calculation of the lithium-ion battery carbon footprint. The aforementioned unit carbon emission factor is stored in a database and can be directly used in the analysis of comprehensive electricity carbon emission factors within each region. The unit carbon emission factor is obtained based on locally released energy consumption data and other relevant data. After determining the comprehensive electricity carbon emission factor for each region, a comprehensive electricity carbon emission factor model can be constructed to facilitate the calculation of the lithium-ion battery carbon footprint. Corresponding electronic maps are generated for the relevant regions and stored in the calculation platform. The electronic maps are allocated within the storage space of the calculation platform. A data plane, serving as storage space, is allocated to an electronic map and configured. Multiple synchronization points, virtual machines within the data plane, are then marked in each region of the electronic map. These synchronization points are interconnected via connection channels, which are opened and closed according to movement rules during subsequent use. The carbon footprint of each lithium-ion battery is calculated and recorded using an accounting package and data chain, enabling subsequent tracking and traceability. This provides effective management of the lithium-ion battery carbon footprint. The electronic map containing the accounting package and data chain serves as the carbon footprint pin. After obtaining the comprehensive electricity carbon emission factor for each region, it is marked on the electronic map, resulting in the comprehensive electricity carbon emission factor model. This model effectively records relevant data on the lithium-ion battery carbon footprint within the managed area, facilitating carbon footprint calculation and storage management.

[0064] In one embodiment, step S2, which involves constructing a full life-cycle accounting stage model, collecting energy consumption data of lithium-ion batteries at various stages based on the accounting stage model, and constructing protection measures in a comprehensive electricity carbon emission factor model in real time, includes:

[0065] S21. Determine the accounting stages of the entire life cycle of lithium-ion batteries. The accounting stages include the raw material mining stage, the production and manufacturing stage, the usage stage, and the recycling and processing stage. Configure the corresponding cloud server for each accounting stage and connect them in sequence to obtain the accounting stage model.

[0066] S22. Collect energy consumption data of lithium-ion batteries at each stage according to the accounting stage model;

[0067] S23. Whenever there is a raw material mining stage, an accounting package is activated to record the energy consumption data of the raw material mining stage (e.g., energy consumption for mining and transportation of minerals such as lithium, cobalt, and nickel).

[0068] S24. When the production and manufacturing stage is entered, the number of lithium-ion batteries is obtained. The corresponding data chain of lithium-ion batteries is activated through the accounting package, and the data chain is bound one-to-one with the lithium-ion batteries. (In the same raw material mining stage, after entering the production and manufacturing stage, the number of lithium-ion batteries is continuously generated, so the corresponding data chain of lithium-ion batteries is added during the process.)

[0069] S25. Match the data points in the data chain with the corresponding calculation stages of the lithium-ion battery in sequence and record the energy consumption data of the calculation stages.

[0070] S26. Based on the accounting package, bind the corresponding multiple data chains together, and assign a unique movement rule to the data points in the same accounting stage in the multiple data chains based on the accounting package (in the management of multiple data chains corresponding to an accounting package, the movement rules of the data points corresponding to the same accounting stage in the multiple data chains are different, which can increase the security of data access. Accessing data in different stages requires different movement rules. The authorized port must have the corresponding movement rules to access the energy consumption data in the corresponding data point. Otherwise, it is impossible to obtain the complete energy consumption data in the data point). Among them, the movement rule is the movement path between multiple synchronization points in the corresponding area of ​​the lithium-ion battery data point in the electronic map. The multiple data chains complete the construction in the comprehensive power carbon emission factor model, and the comprehensive power carbon emission factor model is used to monitor the data points for anomalies.

[0071] In one embodiment, step S26, which involves anomaly monitoring of data points using a comprehensive electricity carbon emission factor model, includes:

[0072] S261. Based on the accounting package, the data points in the multiple data chains that are enabled are sequentially bound to each other (here, binding is not connection, but only correspondence), and the corresponding bound data points are assigned movement rules.

[0073] S262. Temporarily open the connection channel between the corresponding synchronization points according to the movement rules, transfer the data points to the next synchronization point according to the movement rules, and keep the connection channels between the remaining synchronization points disconnected.

[0074] S263. The corresponding authorized network records the movement rules. A temporary space is set up in the accounting platform. The authorized network and the data point are connected through the temporary space. The authorized network moves with the data point according to the movement rules to access and obtain energy consumption data. When the data point moves to the next synchronization point according to the movement rules, the connection between the authorized network and the data point is disconnected during the transfer process. The energy consumption data before the disconnection is temporarily stored in the temporary space until all the energy consumption data in the corresponding data point is obtained according to the movement rules. After the access is completed, the energy consumption data in the temporary space is cleared.

[0075] S264. When a data point is accessed by an unauthorized network, the data point will move between multiple synchronization points in the corresponding area according to the movement rules. When the unauthorized network accesses the data point for more than the preset conditions, it is regarded as an abnormal data point. The energy consumption data in the data point is copied to generate a new data point to replace the abnormal data point, the energy consumption data in the abnormal data point is destroyed, and the abnormal data point is connected to the unauthorized network.

[0076] As described in steps S21-S26 above, after obtaining the comprehensive electricity carbon emission factor model and completing the preparation work for calculating the carbon footprint of lithium-ion batteries, energy consumption data for the entire life cycle of lithium-ion batteries can be collected. The calculation stages of the entire life cycle of lithium-ion batteries are divided into four stages: raw material mining, production and manufacturing, usage, and recycling. Corresponding cloud servers are configured for each calculation stage and connected in sequence to obtain the calculation stage model. This calculation stage model is used to store the energy consumption data of the entire production stage of lithium-ion batteries. Then, the collected energy consumption data is transferred to the comprehensive electricity carbon emission factor model, and independent carbon footprint tracking is performed for each lithium-ion battery. Whenever there is a raw material mining stage, an accounting package is activated to record the raw materials. The energy consumption data during the mining phase represents the source of a batch of lithium-ion battery production. The accounting package is used to calibrate the raw material mining supply for a batch. Here, the accounting package is a virtual machine, and there are multiple accounting packages, each corresponding to a single raw material mining operation (for example, the mining of raw materials in a cycle or the mining in a specific area can be defined as a single raw material mining operation in this application). At this stage, there is no quantity of lithium-ion batteries yet. Here, the energy consumption data for the raw material mining phase is stored in the accounting package. After entering the production and manufacturing stage, the quantity of lithium-ion batteries is continuously generated. Therefore, a data chain corresponding to the lithium-ion battery is added during the process, and the data chain is bound one-to-one with the lithium-ion battery. In this way, the carbon footprint of the corresponding lithium-ion battery can be stored in an orderly and secure manner through the data chain, which has a good data management function. The data points in the data chain are sequentially mapped to the corresponding accounting stages of the lithium-ion battery, and the energy consumption data of the accounting stages are recorded. Here, multiple regions may correspond to one lithium-ion battery stage, so the number of data points is at least no less than the number of lithium-ion battery stages. There are four stages here, and the specific number of data points is uncertain and needs to be determined based on the actual needs of the lithium-ion battery. Each region has multiple data points, and the stages of the lithium-ion battery may involve multiple regions. For example, the production process may involve the joint production of multiple manufacturers in multiple regions. Multiple data chains are bound together based on an accounting package. Each accounting package assigns a unique movement rule to data points in the same accounting stage across these chains. One accounting package corresponds to multiple data chains, spanning four stages. The movement rules for data points in each stage are different and unique. These data points are virtual machines used to store the energy consumption data of the corresponding lithium-ion batteries in that specific area at that stage. In the comprehensive electricity carbon emission factor model, after storing the energy consumption data of lithium-ion batteries through the data chains, the model performs anomaly monitoring on the data points. Specifically, the accounting package binds all lithium-ion batteries and their corresponding data points across the corresponding stages.Assign movement rules to the corresponding bound data points. This allows all data points corresponding to lithium-ion batteries to move between synchronization points according to these rules. These synchronization points are virtual machines set up in the data plane. Data points move between synchronization points through the connection channels between them. Data points can be stored within synchronization points, and the storage space corresponding to each synchronization point can be dynamically allocated. For example, if there are four synchronization points in a region, when a data point is stored in one of these synchronization points, that point is allocated the largest amount of storage space, sufficient to at least meet the data point's storage needs. The other synchronization points are given a preset amount of storage space. During the transfer, the storage space is allocated to the data to be transferred. The next synchronization point is then used to dynamically adjust storage space, which satisfies the transfer of data points while reducing the use of system storage space and deployment complexity. Data points are continuously transferred according to movement rules, regardless of whether they are accessed or not. Therefore, a temporary connection channel is opened between corresponding synchronization points according to the movement rules, and the data point is transferred to the next synchronization point. Connection channels between other synchronization points are disconnected. After the transfer is complete, the connection channel with the previous synchronization point is immediately disconnected. Since the synchronization points themselves have the ability to connect to and accept network access from external networks, the disconnection of the connection channel after the transfer prevents external networks from accessing the network. Accessing data points is inherently intermittent, even with authorized network access, as these points are constantly moving. Therefore, movement rules are recorded within the authorized network, and a temporary space is set up in the computing platform to store the accessed data. This allows for immediate reconnection in case of interruption. Since the authorized network follows the data point's movement according to the rules, the time difference is short and has minimal impact on data access efficiency. The temporary storage preserves previously accessed data, allowing for continued access even as the authorized network moves with the data point. The temporary space is used to prevent interruptions, but its effectiveness is limited. While the efficiency is almost negligible, without setting up a temporary space and not resuming retrieval based on the previous access, there will be situations where accessing the same data repeatedly results in not obtaining all the data. Efficiency is not affected, but data acquisition and accumulation are impacted. A temporary space connects the authorized network and data points. The authorized network follows the data point's movement according to movement rules to access and acquire energy consumption data. When a data point moves to the next synchronization point according to the movement rules, the connection between the authorized network and the data point is disconnected during the transfer process. The energy consumption data before the disconnection is temporarily stored in the temporary space until all energy consumption data for the corresponding data point is acquired according to the movement rules. After the access is complete, the energy consumption data in the temporary space is cleared. By using a comprehensive electricity carbon emission factor model, the carbon footprint of the lithium-ion battery corresponding to the energy consumption data can be stored independently, while also contributing to data storage security.The energy consumption data stored in the data chain can then be used to calculate the carbon footprint of lithium-ion batteries, providing effective traceability and management of their carbon footprint. When a data point is accessed by an unauthorized network, it moves between multiple synchronization points in the corresponding area according to movement rules. If the number of unauthorized network accesses exceeds a preset limit (potentially obtaining all data from the data point), a limit of two accesses is set for security. After two accesses, the data point is considered an abnormal data point. The energy consumption data within the abnormal data point is copied to create a new data point to replace it, and the energy consumption data within the abnormal data point is destroyed. The abnormal data point is then connected to the unauthorized network. Thus, the abnormal data point acts as a virtual machine removed from the data chain, yet it can still support unauthorized network access, providing deception. By using a comprehensive electricity carbon emission factor model, the data points can be protected, thereby protecting the energy consumption data within them.

[0077] In one embodiment, step S3, which involves obtaining the carbon footprint emissions of the lithium-ion battery at each stage based on energy consumption data and the corresponding comprehensive electricity carbon emission factor model, and generating a carbon footprint line, includes:

[0078] S31. Obtain energy consumption data for each stage recorded in the data points of the accounting platform through the authorized network, and determine the comprehensive power carbon emission factor of the region where the energy consumption data is located based on the comprehensive power carbon emission factor model.

[0079] S32. Based on energy consumption data and comprehensive electricity carbon emission factor calculation, the carbon footprint emissions of lithium-ion batteries at each stage are obtained. The carbon footprint emissions are arranged according to the accounting stage to obtain the carbon footprint line.

[0080] As described in steps S31 and S32 above, by using the data points storing energy consumption data in the integrated electricity carbon emission factor model and the integrated electricity carbon emission factor marked in the integrated electricity carbon emission factor model, the energy consumption data on a single data chain is multiplied by the integrated electricity carbon emission factor of the corresponding region, and the results of the entire data chain are integrated to obtain the total carbon footprint emissions of lithium-ion batteries. Each data point on the data chain stores the energy consumption data of the corresponding lithium-ion battery production. Based on the data point and the corresponding integrated electricity carbon emission factor in the integrated electricity carbon emission factor model, the carbon emission of the data point on the data chain is obtained, and corresponding data points are processed. By tagging carbon emissions and integrating the total carbon emissions across the entire data chain, we obtain the total carbon footprint of a lithium-ion battery. Each data point corresponds to a specific carbon footprint (carbon emissions). Since each data point in a single data chain carries a corresponding carbon emissions amount, a carbon footprint line is created. For example, in the production of a lithium-ion battery, there are four data points, corresponding to the stages of raw material mining, manufacturing, use, and recycling. Each stage has at least one corresponding data point. For example, the energy consumption of the data point corresponding to the raw material mining stage for a single lithium-ion battery is 0.6 kWh. The energy consumption data for each of the four stages—production, use, and recycling—is 0.7 kWh / cell. Approximately 0.00096 kWh is consumed per cycle during use, and approximately 0.02 kWh / cell during recycling. This energy consumption data is stored at corresponding data points. The carbon emissions for each stage are: 0.6 kWh * (comprehensive carbon emission factor for raw material mining), 0.7 kWh * (comprehensive carbon emission factor for production), 0.00096 kWh * (comprehensive carbon emission factor for use), and 0.02 kWh * (comprehensive carbon emission factor for recycling). The combined carbon emissions from these four stages constitute the carbon footprint of the lithium-ion battery at each stage. The stage lines, marked with data points corresponding to the carbon emissions for each stage, represent the carbon footprint lines arranged according to the accounting stage. Lithium-ion batteries have independent carbon footprint lines, enabling traceability of a single carbon footprint for each battery, resulting in more organized data management.

[0081] In one embodiment, step S4 of generating a battery carbon footprint report based on the carbon footprint line includes:

[0082] S41. The total emissions of the reference carbon footprint are obtained based on the EU fixed factor method and energy consumption data of lithium-ion batteries at various stages.

[0083] S42. Based on the carbon footprint line, obtain the total carbon footprint emissions of lithium-ion batteries and the emission ratio of each stage, and generate a battery carbon footprint report. The battery carbon footprint report includes the total carbon footprint emissions, the emission ratio of each stage, and a comparison report of the differences between the total carbon footprint emissions and the EU fixed factor method.

[0084] As described in steps S41 and S42 above, the total carbon footprint emissions are obtained based on the EU fixed factor method and energy consumption data of lithium-ion batteries at various stages. The EU fixed factor method is one of the core methods used by the EU under the new Battery Law to calculate the carbon footprint of products such as lithium batteries. Its core is to set a unified carbon emission accounting factor for each stage of the battery's entire life cycle, especially the electricity consumption stage, thereby simplifying the accounting process and ensuring the uniformity of accounting standards within the EU. However, this method does not consider the differences in energy structures within other regions, therefore the carbon footprint calculation is inaccurate and difficult to adapt to the carbon footprint calculation of regions with different energy structures. This leads to regions with a high proportion of clean energy such as hydropower and wind power having higher actual carbon footprints than they actually are. Even if battery companies have very low actual carbon emissions, the results will still be higher according to this fixed factor method. Conversely, in regions with a high proportion of thermal power, the calculation results are difficult to reflect the true emission differences. Therefore, carbon emission calculation based on the regional energy structure is more accurate, and accurate carbon emission calculation can provide better industry development for enterprises.

[0085] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for accurate calculation of the carbon footprint of lithium-ion batteries based on regional energy structure, characterized in that, Includes the following steps: The energy structure and corresponding proportion of each region are determined. Based on the database, the unit carbon emission factor corresponding to the energy structure is obtained and calculated to obtain the comprehensive electricity carbon emission factor for each region. A comprehensive electricity carbon emission factor model is then constructed, including: The management covers multiple regions, and the energy structure and corresponding proportion of each region are determined. The energy structure includes multiple energy types. Set up a database that stores multiple energy types and their corresponding unit carbon emission factors; The unit carbon emission factor corresponding to the energy structure in each region is obtained from the database. The comprehensive electricity carbon emission factor in each region is calculated based on the proportion of the energy structure and the unit carbon emission factor. A comprehensive electricity carbon emission factor model is constructed based on the comprehensive electricity carbon emission factors of each region. A full life-cycle accounting stage model is constructed, and energy consumption data of lithium-ion batteries at each stage are collected based on the accounting stage model. The data is then used to construct a comprehensive electricity carbon emission factor model for protection in real time. Based on the energy consumption data of lithium-ion batteries at various stages and the corresponding comprehensive power carbon emission factor model, the carbon footprint emissions of lithium-ion batteries at each stage are obtained, and a carbon footprint line is generated. Generate a battery carbon footprint report based on the carbon footprint line.

2. The method for accurate calculation of the carbon footprint of lithium-ion batteries based on regional energy structure according to claim 1, characterized in that, The steps for constructing a comprehensive electricity carbon emission factor model based on comprehensive electricity carbon emission factors for each region include: We jointly construct electronic maps for multiple regions, store these electronic maps on an accounting platform, and set up multiple accounting packages and multiple data chains corresponding to the electronic maps on the accounting platform to obtain carbon footprint pins. By marking the comprehensive electricity carbon emission factors of each region on an electronic map, a comprehensive electricity carbon emission factor model is obtained.

3. The method for accurate calculation of the carbon footprint of lithium-ion batteries based on regional energy structure according to claim 2, characterized in that, The corresponding electronic map is configured with multiple accounting packages and multiple data chains in the accounting platform to obtain carbon footprint pins. The steps include: In the accounting platform, multiple accounting packages are set up corresponding to the electronic map, and each accounting package is connected to all data chains. The data chain consists of multiple data points connected in a chain. In the accounting platform, data surfaces are configured corresponding to the electronic map. Based on the data surfaces, multiple synchronization points are marked in each area of ​​the electronic map, and the synchronization points in a single area are interconnected. Electronic maps containing accounting packages and data chains are used as carbon footprint pins.

4. The method for accurate calculation of the carbon footprint of lithium-ion batteries based on regional energy structure according to claim 1, characterized in that, The steps of constructing a full life-cycle accounting model, collecting energy consumption data of lithium-ion batteries at each stage based on the accounting model, and constructing a comprehensive electricity carbon emission factor model for protection in real time include: The accounting stages of the entire life cycle of lithium-ion batteries are determined, including the raw material mining stage, the production and manufacturing stage, the usage stage, and the recycling and processing stage. Corresponding cloud servers are configured for each accounting stage and connected in sequence to obtain the accounting stage model. Energy consumption data of lithium-ion batteries at each stage are collected according to the accounting stage model; An accounting package is activated whenever there is a raw material mining stage, and the energy consumption data of the raw material mining stage is recorded through the accounting package; Once the production and manufacturing stage begins and the quantity of lithium-ion batteries is obtained, the corresponding data chain for the number of lithium-ion batteries is activated through the accounting package, and the data chain is bound one-to-one with the lithium-ion batteries. The data points in the data chain are matched sequentially with the corresponding calculation stages of the lithium-ion battery, and the energy consumption data of the calculation stages are recorded. The accounting package binds multiple corresponding data chains together. The accounting package assigns a unique movement rule to data points in the same accounting stage in multiple data chains. The movement rule is the movement path between multiple synchronization points in the corresponding area of ​​the lithium-ion battery data point in the electronic map. Multiple data chains complete the construction in the comprehensive power carbon emission factor model, and the comprehensive power carbon emission factor model is used to monitor the anomalies of data points.

5. The method for accurate calculation of the carbon footprint of lithium-ion batteries based on regional energy structure according to claim 4, characterized in that, The steps for anomaly monitoring of data points using a comprehensive electricity carbon emission factor model include: Based on the accounting package, data points in multiple data chains that are enabled will be sequentially bound to each other, and movement rules will be assigned to the corresponding bound data points. The connection channel between the corresponding synchronization points is temporarily opened according to the movement rules, and the data points are transferred to the next synchronization point according to the movement rules. The connection channels between the remaining synchronization points are disconnected. The authorized network records the movement rules, and a temporary space is set up in the accounting platform. The authorized network and the data point are connected through the temporary space. The authorized network moves with the data point according to the movement rules to access and obtain energy consumption data. When the data point moves to the next synchronization point according to the movement rules, the connection between the authorized network and the data point is disconnected during the transfer process. The energy consumption data before the disconnection is temporarily stored in the temporary space until all the energy consumption data in the corresponding data point is obtained according to the movement rules. After the access is completed, the energy consumption data in the temporary space is cleared. When a data point is accessed by an unauthorized network, the data point will move between multiple synchronization points in the corresponding area according to the movement rules. When the unauthorized network accesses the data point for more than the preset conditions, it is regarded as an abnormal data point. The energy consumption data in the data point is copied to generate a new data point to replace the abnormal data point, the energy consumption data in the abnormal data point is destroyed, and the abnormal data point is connected to the unauthorized network.

6. The method for accurate carbon footprint calculation of lithium-ion batteries based on regional energy structure according to claim 1, characterized in that, The steps for obtaining the carbon footprint emissions of lithium-ion batteries at each stage based on energy consumption data and corresponding comprehensive electricity carbon emission factor models, and generating carbon footprint lines, include: Energy consumption data for each stage recorded in the data points of the accounting platform are obtained through the authorized network, and the comprehensive electricity carbon emission factor of the region where the energy consumption data is located is determined based on the comprehensive electricity carbon emission factor model. Based on energy consumption data and comprehensive electricity carbon emission factor calculations, the carbon footprint emissions of lithium-ion batteries at each stage are obtained. The carbon footprint emissions are arranged according to the accounting stage to obtain the carbon footprint line.

7. The method for accurate carbon footprint calculation of lithium-ion batteries based on regional energy structure according to claim 1, characterized in that, The step of generating a battery carbon footprint report based on the carbon footprint line includes: The reference carbon footprint total emissions were obtained based on the EU fixed factor method and energy consumption data of lithium-ion batteries at various stages. Based on the carbon footprint line, the total carbon footprint emissions of lithium-ion batteries and the emission ratio of each stage are obtained, and a battery carbon footprint report is generated. The battery carbon footprint report includes the total carbon footprint emissions, the emission ratio of each stage, and a comparison report of the differences between the total carbon footprint emissions and the EU fixed factor method.

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