Power battery carbon footprint accounting method and system, device, and storage medium

Abstract

The present invention relates to the technical field of carbon footprint accounting. Disclosed are a power battery carbon footprint accounting method and system, a device, and a storage medium. The method comprises: obtaining the battery model and service time of a power battery; inputting the battery model and the service time into a fixed carbon footprint accounting model for carbon emission calculation to obtain fixed carbon emission data; inputting the battery model and the service time into a non-fixed carbon footprint accounting model for carbon emission calculation to obtain non-fixed carbon emission data; and adding the fixed carbon emission data and the non-fixed carbon emission data together to obtain a carbon footprint accounting result of the power battery. According to the present invention, by means of aging analysis and recycling analysis, accurate carbon footprint accounting for the full lifecycle of the power battery is achieved; moreover, according to the present invention, calculation of echelon carbon emission data is performed down to the component level, achieving accurate estimation of the carbon emission data in an echelon utilization phase, further improving the accuracy of carbon footprint accounting of the power battery.

Description

A power battery carbon footprint accounting method, system, device and storage medium Technical Field

[0001] The present invention relates to the technical field of carbon footprint calculation, and in particular to a method, system, device and storage medium for calculating the carbon footprint of a power battery. Background Art

[0002] According to a report by the European Transport & Environment Federation (T&E), battery production emissions range from 61 to 106 kgCO2 / kWh, accounting for up to 60% of an electric vehicle's lifecycle carbon emissions. This is a significant issue that should not be underestimated. Currently, a growing number of battery companies are realizing the importance of strengthening carbon emissions management during battery production. For energy-intensive power battery material companies, constrained by electricity prices, energy consumption, and carbon emissions targets, the most significant challenge they face is how to meet energy consumption targets under the pressure of dual energy consumption control.

[0003] At present, the most common method for carbon emission reduction is to calculate the carbon emissions from the production or recycling of power batteries. However, these methods only calculate carbon emissions from a single aspect and lack the monitoring of carbon emissions from the entire product life cycle. Compared with single carbon dioxide emissions, carbon footprint uses a life cycle assessment method to evaluate the greenhouse gas emissions directly or indirectly generated by the research object during its life cycle. For the same object, the calculation difficulty and scope of carbon footprint are greater than carbon emissions. Its calculation results contain information on carbon emissions and can more accurately reflect the carbon emission data of the product life cycle. However, there is currently no relevant calculation method for the carbon footprint of power batteries.

[0004] Summary of the Invention

[0005] In order to solve the above technical problems, the present invention provides a power battery carbon footprint accounting method, system, device and storage medium. Starting from the battery's product life cycle, it comprehensively monitors the carbon footprint of the entire power battery to achieve the technical effect of providing accurate data support for energy conservation and emission reduction for enterprises.

[0006] In a first aspect, the present invention provides a method for calculating the carbon footprint of a power battery, the method comprising:

[0007] Obtain the battery model and battery life of the power battery;

[0008] Inputting the battery model and the battery usage time into a fixed carbon footprint accounting model to calculate carbon emissions and obtain fixed carbon emission data;

[0009] Inputting the battery model and the battery usage time into a non-stationary carbon footprint accounting model to calculate carbon emissions and obtain non-stationary carbon emission data;

[0010] The fixed carbon emission data and the non-fixed carbon emission data are added together to obtain a carbon footprint calculation result of the power battery.

[0011] Furthermore, the step of inputting the battery model and the battery usage time into a fixed carbon footprint accounting model to calculate carbon emissions and obtain fixed carbon emission data includes:

[0012] Extract the corresponding battery components from the battery product library according to the battery model, and obtain the carbon emission data of raw materials, battery production and battery transportation based on the battery components;

[0013] Obtaining battery usage carbon emission data according to the battery model and the battery usage time;

[0014] The raw material carbon emission data, the battery production carbon emission data and the battery use carbon emission data are added together to obtain fixed carbon emission data.

[0015] Furthermore, the step of inputting the battery model and the battery usage time into a non-stationary carbon footprint accounting model to calculate carbon emissions and obtain non-stationary carbon emission data includes:

[0016] Calculate the carbon emission data of power battery recycling based on the battery model;

[0017] Inputting the battery model and the battery usage time into a battery aging prediction model to perform battery aging prediction, thereby obtaining a component aging value of the power battery, and obtaining a utilization type of the power battery based on the component aging value, wherein the utilization type includes recycling and cascade utilization;

[0018] When the utilization type is recycling, the recycling carbon emission data is used as non-fixed carbon emission data;

[0019] When the utilization type is cascade utilization, the carbon emission data of cascade utilization is calculated according to the battery model and the component aging value;

[0020] The sum of the recycling carbon emission data and the secondary utilization carbon emission data is taken as the non-fixed carbon emission data.

[0021] Furthermore, the step of calculating the carbon emission data of secondary utilization according to the battery model and the component aging value includes:

[0022] Determining a cascade utilization type of the power battery according to the battery model and the component aging value, and obtaining a cascade utilization rate according to the cascade utilization type;

[0023] Calculate the carbon emission data of the power battery's second-use according to the second-use type and the second-use rate.

[0024] Furthermore, the step of determining the cascade utilization type of the power battery according to the battery model and the component aging value, and obtaining the cascade utilization rate according to the cascade utilization type includes:

[0025] Obtaining a cascade utilization type of the power battery according to the aging values ​​of each component corresponding to the battery model, the cascade utilization type including downgraded utilization, combined utilization, and split utilization;

[0026] When the cascade utilization type is degraded utilization or combined utilization, a cascade utilization rate is obtained according to the battery model and the component aging value;

[0027] When the cascade utilization type is split utilization, the sub-cascade utilization rate corresponding to each component is obtained according to the battery model and the component aging value.

[0028] Furthermore, the step of calculating the carbon emission data of the power battery's second-use according to the second-use type and the second-use rate includes:

[0029] When the cascade utilization type is degraded utilization or combined utilization, a utilization level of the power battery is obtained according to the cascade utilization rate, and the utilization level includes a degraded level and a combined level;

[0030] According to the utilization level, carbon emission data of the power battery's secondary utilization is obtained;

[0031] When the cascade utilization type is split utilization, component decomposition carbon emission data is obtained according to the battery model;

[0032] According to the utilization rate of each component and the corresponding sub-echelon, the carbon emission data of component assembly and the carbon emission data of each sub-echelon utilization are obtained;

[0033] The component decomposition carbon emission data, the component assembly carbon emission data and each sub-echelon utilization carbon emission data are added together to obtain the echelon utilization carbon emission data of the power battery.

[0034] Furthermore, the step of obtaining the carbon emission data of the second-use of the power battery according to the utilization level includes:

[0035] Obtaining a predicted utilization duration according to the utilization level and the tiered utilization rate;

[0036] Carbon emission data of the power battery's secondary utilization is obtained according to the utilization level and the predicted utilization duration.

[0037] In a second aspect, the present invention provides a power battery carbon footprint calculation system, the system comprising:

[0038] A data acquisition module is used to obtain the battery model and battery usage time of the power battery;

[0039] a fixed data calculation module, configured to input the battery model and the battery usage time into a fixed carbon footprint accounting model to calculate carbon emissions and obtain fixed carbon emission data;

[0040] a non-fixed data calculation module, configured to input the battery model and the battery usage time into a non-fixed carbon footprint accounting model to calculate carbon emissions and obtain non-fixed carbon emission data;

[0041] The carbon footprint calculation module is used to add the fixed carbon emission data and the non-fixed carbon emission data to obtain a carbon footprint calculation result of the power battery.

[0042] In a third aspect, an embodiment of the present invention further provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0043] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0044] This invention provides a method, system, device, and storage medium for calculating the carbon footprint of power batteries. This method monitors and predicts the carbon footprint of power batteries throughout their product lifecycle, enabling accurate calculation of the carbon footprint of power batteries. This provides accurate and effective data support for energy conservation and emission reduction efforts by enterprises, which is highly significant for the power battery industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] FIG1 is a schematic flow chart of a method for calculating the carbon footprint of a power battery according to an embodiment of the present invention;

[0046] FIG2 is a schematic diagram of the structure of a power battery carbon footprint calculation system according to an embodiment of the present invention;

[0047] FIG3 is a diagram showing the internal structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying 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 making creative efforts shall fall within the scope of protection of the present invention.

[0049] Referring to FIG. 1 , a method for calculating the carbon footprint of a power battery proposed in a first embodiment of the present invention includes steps S10 to S40 :

[0050] Step S10, obtaining the battery model and battery usage time of the power battery;

[0051] Step S20: inputting the battery model and the battery usage time into a fixed carbon footprint calculation model to calculate carbon emissions and obtain fixed carbon emission data;

[0052] Step S30: Inputting the battery model and the battery usage time into a non-stationary carbon footprint calculation model to calculate carbon emissions and obtain non-stationary carbon emission data;

[0053] Step S40 : Adding the fixed carbon emission data and the non-fixed carbon emission data to obtain a carbon footprint calculation result of the power battery.

[0054] The carbon footprint of a power battery refers to the greenhouse gas emissions generated directly or indirectly throughout its entire life cycle, including carbon emissions data generated throughout the entire process from the collection and transportation of raw materials to the complete failure of the power battery. Based on this principle, the present invention analyzes the carbon footprint of the power battery throughout its life cycle and divides the carbon footprint into two categories: fixed carbon emission data and non-fixed carbon emission data. Among them, fixed carbon emission data refers to the carbon emission data generated throughout the entire production process for different battery models after the product is completed. After the battery enters the use stage, the carbon emission data generated throughout the entire use process is also fixed. Therefore, the present invention treats these two parts of data as fixed carbon emission data and uses a fixed carbon footprint accounting model for calculation. The specific steps include:

[0055] Step S201: extracting corresponding battery components from a battery product library according to the battery model, and obtaining raw material carbon emission data, battery production carbon emission data, and battery transportation carbon emission data based on the battery components;

[0056] Step S202, obtaining battery usage carbon emission data according to the battery model and the battery usage time;

[0057] Step S203 , adding the raw material carbon emission data, the battery production carbon emission data, and the battery use carbon emission data to obtain fixed carbon emission data.

[0058] In this embodiment, the fixed carbon footprint accounting model includes a production accounting unit and a usage accounting unit. The production accounting unit is used to calculate the carbon emission data generated by the power battery in the entire production process. Specifically, first, according to the battery model of the power battery, the corresponding battery component is extracted from the battery product library. The battery product library is a pre-established product information library, including information such as battery components of different battery models, raw materials corresponding to the components, and battery production and assembly processes. According to the type of raw materials and the location and transportation conditions of the raw material supplier, the carbon emission data generated in the process from the collection of raw materials to the transportation to the production line, that is, the raw material carbon emission data, can be calculated through historical data; then, according to the production process of the production line corresponding to the power battery, the carbon emission data generated in the assembly process of the battery component and the carbon emission data generated in the assembly process of the battery can be calculated, and these two types of carbon emission data can be used as battery production carbon emission data; based on the calculated raw material carbon emission data and battery production carbon emission data, the carbon emission data generated in the entire production process of the power battery can be obtained.

[0059] The carbon emission data generated during use is calculated by the usage accounting unit. Specifically, based on the battery model and usage time, the carbon emission data generated by the power battery in its application environment for a certain period of time can be calculated, that is, the carbon emission data generated during use is obtained. The carbon emission data generated during the production process and the carbon emission data generated during use are added together to obtain the fixed carbon emission data, wherein the fixed carbon emission data is expressed by the following formula: T g =T1+T2+T3

[0060] In the formula, T1 represents the carbon emission data of raw materials, T2 represents the carbon emission data of battery production, and T3 represents the carbon emission data of battery use.

[0061] It should be noted that since fixed carbon emission data is generated by actions that have already occurred, the fixed carbon footprint accounting model can use linear fitting of historical data to obtain fixed carbon emission data based on battery model and usage time. Of course, neural networks or statistical algorithms can also be used to construct a fixed carbon footprint accounting model, and no specific restrictions are made here.

[0062] The non-fixed carbon emission data refers to the carbon emission data generated by the power battery in the future, that is, the prediction of the subsequent carbon emissions of the power battery. Obviously, the carbon emission data generated in the future must be non-fixed. In order to more accurately calculate this part of the non-fixed carbon emission data, the present invention also analyzes this part of the carbon emission data, divides the future time period, and calculates the carbon emission data generated in each time period, thereby accurately predicting the non-fixed carbon emission data. The specific steps include:

[0063] Step S301, calculating the carbon emission data of power battery recycling according to the battery model;

[0064] Step S302: Inputting the battery model and the battery usage time into a battery aging prediction model to perform battery aging prediction, obtaining a component aging value of the power battery, and obtaining a utilization type of the power battery based on the component aging value, wherein the utilization type includes recycling and cascade utilization;

[0065] Step S303: When the utilization type is recycling, the recycling carbon emission data is used as non-fixed carbon emission data;

[0066] Step S304, when the utilization type is cascade utilization, calculating cascade utilization carbon emission data according to the battery model and the component aging value;

[0067] Step S305: taking the sum of the recycling carbon emission data and the secondary utilization carbon emission data as the non-stationary carbon emission data.

[0068] In this embodiment, the carbon emission data for the future period can be divided into carbon emission data generated in the recycling stage and carbon emission data generated in the cascade utilization stage. That is, the non-stationary carbon emission data can be expressed as:

[0069] Where, T h Represents the carbon emission data generated in the recycling stage, T t Represents the carbon emission data generated in the cascade utilization stage.

[0070] The carbon emission data generated during the recycling phase in this embodiment refers to the carbon emission data generated by the recycling of power batteries after they are no longer used through disassembly, crushing, and metal recovery. This data includes both the carbon emission data generated during recycling and the carbon emission data saved during metal reuse. The two carbon emission data are combined and offset to form the carbon emission data generated by the power battery during the recycling phase. The carbon emission data generated during this phase is generated by each power battery during the final recycling phase, so this data is the fixed data part of the non-fixed carbon emission data. That is, the carbon emission data generated during the recycling phase is expressed using the following formula: T h =T` h -T L

[0071] Where, T` h Indicates the carbon emission data generated during recycling, T L Indicates the carbon emissions saved when metals are reused.

[0072] Similarly, the calculation of fixed data can also be done by fitting historical data to obtain the carbon emission data generated by different battery models during the recycling stage, or by using other statistical models, etc., which will not be detailed here.

[0073] The carbon emissions data generated during the secondary utilization phase represents the portion of the non-fixed carbon emissions data that requires prediction, i.e., the non-fixed data portion. In this embodiment, secondary battery recycling involves classifying batteries according to their service life and performance, and then recycling them. This method can maximize the battery lifespan, minimize battery waste, and reduce environmental pollution. A battery's lifespan is limited, generally related to the number of times it's used and the environment in which it's used. When a battery reaches the end of its lifespan, it can no longer be used. However, even at the end of a battery's lifespan, it can still be reused. The cascade utilization in this embodiment can be categorized into downgraded utilization, combined utilization, and split utilization. Downgraded utilization refers to the use of retired batteries with high remaining capacity that meet overall usage requirements, which, after appropriate repair and standardization, are deployed in battery applications that meet local requirements, such as energy storage (grid frequency regulation and peak shifting, peak shaving, wind and solar energy storage, tower base stations, etc.) and low-speed electric vehicles. For example, a power battery typically has a service life of 5-8 years. When the battery's actual capacity decays to 80%, it theoretically no longer meets automotive standards and needs to be replaced. Retired power batteries with a capacity between 20% and 80% are suitable for downgraded utilization. Key utilization scenarios include home energy storage, low-speed vehicles, solar street lights, outdoor mobile power supplies, and tower base station backup power supplies. Combined utilization involves combining multiple power batteries to form a larger capacity battery pack to extend the battery's lifespan. Split utilization involves splitting a power battery into multiple components and combining the usable parts into new batteries to achieve battery reuse. Obviously, different types of cascade utilization will generate different carbon emission data, so it is necessary to first determine the type of cascade utilization of power batteries.

[0074] Specifically, first, the aging degree of the power battery components is predicted based on the battery model and battery usage time of the power battery. In this embodiment, a recurrent neural network model is used to construct a battery aging prediction model. The input data of the recurrent neural network model includes the battery model, usage time and application scenario. The training data is the historical usage data of the power battery. The output data is the aging degree of each component of the power battery, that is, the component aging value. In addition, a classification decision unit is added after the output layer of the recurrent neural network model. The aging degree of the power battery is judged by the output aging value of each component, that is, whether the power battery can be recycled. If the aging degree of the power battery is not sufficient for cascade utilization, the subsequent processing is to directly enter the recycling stage. At this time, the recycling carbon emission data calculated previously is the non-fixed carbon emission data. If the power battery can be recycled, it is necessary to calculate the carbon emission data generated during cascade utilization based on the battery model and the corresponding component aging value. The specific calculation steps include:

[0075] Determining a cascade utilization type of the power battery according to the battery model and the component aging value, and obtaining a cascade utilization rate according to the cascade utilization type;

[0076] Calculate the carbon emission data of the power battery's second-use according to the second-use type and the second-use rate.

[0077] In this embodiment, the type of cascade utilization is determined based on the degree of aging of each battery component. Preferably, the above-mentioned classification decision device can be used to implement this function. In fact, a variety of classification decision devices can be applied to this embodiment to implement classification judgment, which will not be repeated here.

[0078] Furthermore, this embodiment obtains the cascade utilization rate based on the cascade utilization type, thereby calculating the cascade utilization carbon emission data of the power battery. Specifically, the classification decision device will determine the cascade utilization type of the battery based on the battery model and the degree of aging of each component. For example, when the degree of aging of each component is low, the power battery can be downgraded for utilization. When the degree of aging of each component is low and the battery model meets the requirements for combined reuse, the power battery can be combined for utilization. When some components are severely aged, the power electricity can be split for utilization. It should be noted that, in fact, for power electricity with a short usage time, it may still be in normal use when the carbon footprint is calculated. At this time, this state can be classified as a downgraded utilization type. After determining the type of cascade utilization of the power battery, the cascade utilization rate of the power battery can be calculated according to the cascade utilization type. For power batteries that are degraded or used in combination, the cascade utilization rate can be calculated according to the battery model and the corresponding component aging degree. The cascade utilization rate in this embodiment refers to the battery utilization rate when degraded or used in combination. This can be calculated according to the aging degree of the components, mainly the aging degree of the battery cells, such as the remaining capacity of the battery cells, to calculate the utilization rate of the battery for subsequent use. Then, the utilization level of the power battery is determined according to the cascade utilization rate. For degraded utilization, the application scenario of degraded utilization can be selected according to the cascade utilization rate, such as home energy storage or solar street lights. For combined utilization, the battery scale of the combination can be selected according to the cascade utilization rate. Different battery scales correspond to different application scenarios. Therefore, after obtaining the utilization level, the carbon emission data of the cascade utilization of the power battery can be calculated. The specific calculation steps include:

[0079] Obtaining a predicted utilization duration according to the utilization level and the tiered utilization rate;

[0080] Carbon emission data of the power battery's secondary utilization is obtained according to the utilization level and the predicted utilization duration.

[0081] In this embodiment, the utilization time of the cascade utilization is predicted based on data such as the utilization level, cascade utilization rate, and application scenarios of the power battery to obtain the predicted utilization time. The time prediction here is preferably implemented using a convolutional neural network model. After obtaining the predicted utilization time, the cascade utilization carbon emission data can be obtained based on the utilization level and the predicted utilization time of the power battery. This step actually determines the subsequent application scenarios and usage time of the power battery. Therefore, the cascade utilization carbon emission data of the power battery can be obtained based on historical data prediction.

[0082] For power batteries that are downgraded, the corresponding degradation level is first set according to different application scenarios. Assuming that the degradation level of the power battery that continues to be used in the original scenario is 0, the degradation level is set to 1, 2, etc. according to the power requirements of the application scenario. The carbon emission data of power batteries with different degradation levels within the predicted period can be calculated. Since there is also a cascade utilization rate, the carbon emission data obtained under the original degradation level application scenario is multiplied by the cascade utilization rate to obtain the carbon emission data generated by the downgraded power battery. That is, the carbon emission data generated by the downgraded power battery can be expressed as: T J =T j,t *S t

[0083] Where, T j,t S represents the carbon emission data of the power battery within the predicted duration t at degradation level j, t Indicates the tiered utilization rate, at this time T t Equal to T J .

[0084] Similarly, for combined power batteries, the corresponding combination level is first determined based on the different combined battery capacities, that is, the combination level corresponds to battery packs of different capacities. For the combined battery pack, since the usage time is predicted, the carbon emissions data generated by the combined battery pack during use can be predicted based on the historical usage data of battery packs of different capacities. In addition, the combined power battery is only part of the battery pack, and there is also a cascade utilization rate. Therefore, the calculated carbon emission data of the battery pack is multiplied by the proportion of the power battery in the battery pack and multiplied by the corresponding cascade utilization rate to obtain the cascade utilization carbon emission data of the combined power battery. The calculation formula can be expressed as: T Z =T` Z *a*S t

[0085] Where, T` Z represents the carbon emission data of the battery pack, a represents the proportion of power batteries in the battery pack, S t Indicates the tiered utilization rate, at this time Tt Equal to T Z .

[0086] For power batteries that are disassembled for reuse, it is necessary to first determine which components require disassembly and assembly based on the component aging values ​​of the power batteries. For components that meet the requirements for disassembly and reuse, the carbon emissions data generated during the component disassembly process can be obtained based on the battery model. The sub-tier utilization rate of each component is calculated based on the component's subsequent utilization rate, calculated based on its aging degree. The component assembly carbon emissions data and the sub-tier utilization carbon emissions data are then calculated based on each sub-tier utilization rate. Specifically, different components may be assembled into different power batteries. In this embodiment, a battery recycling database is pre-established based on historical power battery recycling data. Optimal combination schemes are set for different components and corresponding sub-tier utilization rates, such as combining components with the same sub-tier utilization rate. Therefore, the battery recycling database can be used to determine the carbon emissions data generated by each component during battery assembly. The sub-tier utilization rates of the power battery and each component obtained after assembly can be used to estimate the service life of the assembled power battery. The sub-tier utilization carbon emissions data for each component are then calculated based on the service life and the preset proportion of the component in the power battery. The sub-echelon carbon emission data refers to the carbon emission data generated by each component during use. This data is the carbon emission data generated by the power battery in which the component is located during its use time, multiplied by the preset proportion of the component in the power battery, and multiplied by the sub-echelon utilization rate of the component to obtain the carbon emission data. The sub-echelon carbon emission data is expressed using the following formula: T` i =T i,t,zd *b i *S i,t

[0087] Where, T` i,t represents the carbon emission data of the sub-tier utilization of component i, T i,t,zd represents the carbon emission data generated by the power battery where component i is located during the use time t, b i represents the carbon emission proportion of component i in the power battery zd, S i,t represents the sub-tier utilization of component i.

[0088] Finally, by adding the component decomposition carbon emission data, component assembly carbon emission data and each sub-echelon utilization carbon emission data, we can get the cascade utilization carbon emission data of the power battery during the split utilization. That is, the cascade utilization carbon emission data during the split utilization can be expressed as:

[0089] Where, T i,fj represents the decomposed carbon emission data of component i, T i,zjrepresents the assembly carbon emission data of component i, T` i represents the sub-tier carbon emission data of component i, n represents the total number of components that are split and utilized, and T t Equal to T T .

[0090] Through the above description, we can get the non-fixed carbon emission data of power batteries under different recycling conditions, namely T f , after obtaining the fixed carbon emission data T g and non-stationary carbon emission data T f Then, the carbon footprint of the power battery throughout its life cycle can be obtained based on the sum of the two. That is, the carbon footprint of the power battery throughout its life cycle can be expressed as: T = T g +T f

[0091] This embodiment provides a method for calculating the carbon footprint of a power battery. By analyzing the degree of aging of the power battery, classifying the power battery by recycling type, and calculating corresponding cascade carbon emission data for different recycling types, it is possible to accurately calculate the carbon footprint of the power battery throughout its life cycle. Furthermore, the present invention calculates the cascade carbon emission data accurately down to the component level, enabling accurate estimation of carbon emission data during the cascade utilization phase, further improving the accuracy of the power battery carbon footprint calculation. Furthermore, the power battery carbon footprint calculation method provided by the present invention can also provide effective data support for energy conservation and emission reduction efforts by enterprises. By calculating the carbon footprint, it can accurately identify the stage in the current battery production and recycling process where carbon emission issues exist, providing clear directions for rectification for energy conservation and emission reduction efforts by enterprises, thereby providing effective data support for energy conservation and emission reduction efforts by enterprises.

[0092] Referring to FIG. 2 , based on the same inventive concept, a second embodiment of the present invention proposes a power battery carbon footprint calculation system, including:

[0093] The data acquisition module 10 is used to obtain the battery model and battery usage time of the power battery;

[0094] A fixed data calculation module 20 is configured to input the battery model and the battery usage time into a fixed carbon footprint calculation model to calculate carbon emissions and obtain fixed carbon emission data;

[0095] The non-fixed data calculation module 30 is configured to input the battery model and the battery usage time into a non-fixed carbon footprint calculation model to calculate carbon emissions and obtain non-fixed carbon emission data;

[0096] The carbon footprint calculation module 40 is configured to add the fixed carbon emission data and the non-fixed carbon emission data to obtain a carbon footprint calculation result of the power battery.

[0097] The technical features and effects of the power battery carbon footprint calculation system proposed in the embodiment of the present invention are the same as those of the method proposed in the embodiment of the present invention and are not described in detail here. Each module in the above-mentioned power battery carbon footprint calculation system can be implemented in whole or in part through software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0098] In addition, an embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0099] Please refer to Figure 3, which is an internal structure diagram of a computer device in one embodiment. The computer device can specifically be a terminal or a server. The computer device includes a processor, a memory, a network interface, a display, and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements a power battery carbon footprint accounting method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0100] It will be understood by those skilled in the art that the structure shown in FIG3 is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computing device may include more or fewer components than those shown in the figure, or combine certain components, or have the same component arrangement.

[0101] In addition, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above method when the computer program is executed by a processor.

[0102] In summary, the embodiments of the present invention propose a method, system, device and storage medium for calculating the carbon footprint of a power battery. The method obtains the battery model and battery usage time of the power battery; inputs the battery model and battery usage time into a fixed carbon footprint calculation model to calculate carbon emissions, thereby obtaining fixed carbon emission data; inputs the battery model and battery usage time into a non-fixed carbon footprint calculation model to calculate carbon emissions, thereby obtaining non-fixed carbon emission data; and adds the fixed carbon emission data and the non-fixed carbon emission data to obtain the carbon footprint calculation result of the power battery. The present invention analyzes the degree of aging of the power battery, divides the power battery into recycling types, and calculates corresponding cascade carbon emission data for different recycling types, thereby achieving accurate calculation of the carbon footprint of the power battery throughout its life cycle. In addition, the present invention calculates the cascade carbon emission data accurately to the component level, thereby achieving accurate estimation of the carbon emission data in the cascade utilization stage, further improving the accuracy of the carbon footprint calculation of the power battery. In addition, the carbon footprint accounting method for power batteries provided by the present invention can also provide effective data support for enterprises' energy conservation and emission reduction. Through the calculation of the carbon footprint, it can accurately point out the stage where carbon emission problems exist in the current battery production and recycling process, and point out a clear direction for rectification for enterprises' energy conservation and emission reduction, thereby providing effective data support for enterprises' energy conservation and emission reduction.

[0103] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be directly referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the various technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0104] The above-described embodiments merely represent several preferred implementations of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art could make several improvements and substitutions without departing from the technical principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be based on the scope of protection of the claims.

Claims

1. A method for calculating the carbon footprint of a power battery, characterized in that, Including: Obtain the battery model and battery usage duration of the power battery; Input the battery model and the battery usage duration into a fixed carbon footprint accounting model for carbon emission calculation to obtain fixed carbon emission data; Input the battery model and the battery usage duration into a non-fixed carbon footprint accounting model for carbon emission calculation to obtain non-fixed carbon emission data; Add the fixed carbon emission data and the non-fixed carbon emission data to obtain the carbon footprint accounting result of the power battery.

2. The method for calculating the carbon footprint of a power battery according to claim 1, wherein The step of inputting the battery model and the battery usage duration into a fixed carbon footprint accounting model for carbon emission calculation to obtain fixed carbon emission data includes: Extract the corresponding battery components from the battery product library according to the battery model, and obtain raw material carbon emission data, battery production carbon emission data, and battery transportation carbon emission data based on the battery components; Obtain battery usage carbon emission data according to the battery model and the battery usage duration; Add the raw material carbon emission data, the battery production carbon emission data, and the battery usage carbon emission data to obtain fixed carbon emission data.

3. The method for calculating the carbon footprint of a power battery according to claim 1, characterized in that, The step of inputting the battery model and the battery usage duration into a non-fixed carbon footprint accounting model for carbon emission calculation to obtain non-fixed carbon emission data includes: Calculate the carbon emission data for the recycling and utilization of the power battery according to the battery model; Input the battery model and the battery usage duration into a battery aging prediction model for battery aging prediction to obtain the component aging value of the power battery, and obtain the utilization type of the power battery according to the component aging value, where the utilization type includes recycling and cascaded utilization; When the utilization type is recycling, use the carbon emission data for recycling as Non-fixed carbon emission data; When the utilization type is cascaded utilization, calculate the carbon emission data for cascaded utilization according to the battery model and the component aging value; Take the sum of the carbon emission data for recycling and the carbon emission data for cascaded utilization as non-fixed carbon emission data.

4. The method for calculating the carbon footprint of a power battery according to claim 3, wherein The step of calculating the carbon emission data for cascaded utilization according to the battery model and the component aging value includes: Judge the cascaded utilization type of the power battery according to the battery model and the component aging value, and obtain the cascaded utilization rate according to the cascaded utilization type; Calculate the carbon emission data for the cascaded utilization of the power battery according to the cascaded utilization type and the cascaded utilization rate.

5. The method for calculating the carbon footprint of a power battery according to claim 4, characterized in that, The step of judging the cascaded utilization type of the power battery according to the battery model and the component aging value, and obtaining the cascaded utilization rate according to the cascaded utilization type includes: Obtain the cascaded utilization type of the power battery according to each component aging value corresponding to the battery model, where the cascaded utilization type includes downcycling, combined utilization, and disassembly utilization; When the cascaded utilization type is downcycling or combined utilization, obtain the cascaded utilization rate according to the battery model and the component aging value; When the cascaded utilization type is disassembly utilization, obtain the sub-cascaded utilization rate corresponding to each component according to the battery model and the component aging value.

6. The carbon footprint accounting method for power batteries according to claim 5, characterized in that The steps of calculating the secondary utilization carbon emission data of the power battery according to the secondary utilization type and the secondary utilization rate include: When the secondary utilization type is degradation utilization or combined utilization, obtain the utilization level of the power battery according to the secondary utilization rate, where the utilization level includes a degradation level and a combined level; Obtain the secondary utilization carbon emission data of the power battery according to the utilization level; When the secondary utilization type is disassembly utilization, obtain the component decomposition carbon emission data according to the battery model; Obtain the component assembly carbon emission data and the secondary utilization carbon emission data of each sub-level according to each component and the corresponding sub-secondary utilization rate; Add the component decomposition carbon emission data, the component assembly carbon emission data and the secondary utilization carbon emission data of each sub-level to obtain the secondary utilization carbon emission data of the power battery.

7. The method for calculating the carbon footprint of a power battery according to claim 6, wherein The steps of obtaining the secondary utilization carbon emission data of the power battery according to the utilization level include: Obtain the utilization prediction duration according to the utilization level and the secondary utilization rate; Obtain the secondary utilization carbon emission data of the power battery according to the utilization level and the utilization prediction duration.

8. A carbon footprint accounting system for power batteries, characterized in that, Including: A data acquisition module for acquiring the battery model and the battery usage duration of the power battery; A fixed data calculation module for inputting the battery model and the battery usage duration into a fixed carbon footprint accounting model for carbon emission calculation to obtain fixed carbon emission data; A non-fixed data calculation module for inputting the battery model and the battery usage duration into a non-fixed carbon footprint accounting model for carbon emission calculation to obtain non-fixed carbon emission data; A carbon footprint accounting module for adding the fixed carbon emission data and the non-fixed carbon emission data to obtain the carbon footprint accounting result of the power battery.

9. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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