Method for accounting for carbon emissions

Abstract

The application provides a carbon emission accounting method, and relates to the technical field of energy saving and emission reduction and carbon emission accounting. The method comprises the following steps: determining an accounting target and a boundary range, wherein the accounting target is an electric bicycle used in a distribution process, and the boundary range is determined according to the whole life cycle of the electric bicycle, and the whole life cycle comprises a production stage, a use stage and a waste stage; obtaining basic data of resource consumption and / or energy consumption associated with carbon emission of the accounting target within the boundary range; determining a carbon source list of the accounting target in each stage of the whole life cycle according to the basic data; obtaining a plurality of carbon emission factors corresponding to the carbon source list; calculating carbon emission amounts of the accounting target in each stage according to the basic data and the plurality of carbon emission factors; and obtaining a total carbon emission amount of the accounting target within the boundary range according to the carbon emission amounts of the accounting target in each stage. The method improves the accuracy and adaptability of carbon emission accounting of the electric bicycle in the distribution scenario.

Description

Technical Field

[0001] This application relates to the field of energy conservation, emission reduction and carbon emission accounting technology, and in particular to a carbon emission accounting method. Background Technology

[0002] With the explosive growth of the on-demand delivery and e-commerce logistics industries, carbon emissions from last-mile delivery have attracted increasing attention. As a core mode of transportation for "last-mile" delivery, the carbon emission accounting of electric bicycles throughout their entire life cycle is of significant practical importance for promoting the green transformation of the logistics industry.

[0003] In existing technologies, carbon emission accounting for electric bicycles or similar vehicles typically employs macro-statistical methods based on fuel or energy consumption. In practice, the total carbon emissions are often estimated by directly multiplying the vehicle's total mileage or total electricity consumption within a specific statistical period by a uniform average carbon emission factor (such as the grid average emission factor or fuel emission factor).

[0004] However, existing technologies lack detailed coverage of all stages of the entire life cycle of electric bicycles, resulting in low accuracy of the accounting results and difficulty in reflecting the true carbon emission level. Summary of the Invention

[0005] This application provides a carbon emission accounting method to address the aforementioned technical problems. This method is designed for electric bicycles used in the delivery process. By defining the accounting target and the entire lifecycle boundary, it obtains basic data on resource consumption and / or energy consumption at each stage and determines a carbon source inventory. Combined with corresponding carbon emission factors, it calculates the carbon emissions at each stage and finally summarizes the total carbon emissions, thereby improving the accuracy and adaptability of carbon emission accounting in delivery scenarios.

[0006] Firstly, this application provides a carbon emission accounting method, which includes:

[0007] The accounting target and boundary scope are determined. The accounting target is the electric bicycles used in the delivery process, and the boundary scope is determined according to the entire life cycle of the electric bicycle, which includes the production stage, the use stage, and the disposal stage.

[0008] Obtain basic data on resource consumption and / or energy consumption associated with carbon emissions within the accounting target's boundary range;

[0009] Based on the basic data, determine the carbon source inventory for the accounting target at each stage of the entire life cycle;

[0010] Obtain multiple carbon emission factors corresponding to the carbon source inventory, and calculate the carbon emissions of the accounting target at each stage based on the basic data and multiple carbon emission factors.

[0011] Based on the carbon emissions of the accounting target at each stage, the total carbon emissions of the accounting target within the boundary range are obtained.

[0012] In one possible implementation, the production phase includes a raw material mining phase, a raw material processing phase, a component manufacturing phase, and a vehicle assembly phase.

[0013] The basic data includes the amount of various raw materials mined during the raw material mining stage, as well as the amount of various energy consumed during the raw material processing stage, the parts manufacturing stage, and the vehicle assembly stage.

[0014] Carbon emission factors include implicit carbon emission factors and energy carbon emission factors;

[0015] Calculate the carbon emissions of the accounting target at each stage, including:

[0016] Calculate the carbon emissions during the raw material extraction stage based on the amount of raw materials mined and the corresponding implicit carbon emission factors.

[0017] Based on the consumption of various types of energy and the corresponding energy carbon emission factors in the raw material processing stage, the component manufacturing stage, and the vehicle assembly stage, the carbon emissions of the raw material processing stage, the component manufacturing stage, and the vehicle assembly stage are calculated respectively.

[0018] In one possible implementation, the formula for calculating carbon emissions during the raw material extraction stage, based on the amount of raw materials mined and the corresponding implicit carbon emission factor, is as follows:

[0019]

[0020] Among them, C sc,kc For carbon emissions during the raw material extraction stage, m i,kc Let EF be the amount of raw material i being mined. cl,i Let I be the implicit carbon emission factor corresponding to the i-th raw material, and I be the total number of raw material types.

[0021] The formula for calculating carbon emissions during the raw material processing stage is:

[0022]

[0023] Among them, C sc,jg E represents carbon emissions during the raw material processing stage. j,jg Let EF be the consumption of the j-th energy source in the raw material processing stage. yx,j Let J be the energy carbon emission factor corresponding to the j-th energy source, and J be the total number of energy types in the raw material processing stage.

[0024] The formula for calculating carbon emissions during the component manufacturing stage is as follows:

[0025]

[0026] Among them, C sc,lj For carbon emissions during the component manufacturing stage, E k,lj Let EF be the consumption of the k-th energy source during the component manufacturing stage. yx,k Let K be the energy carbon emission factor corresponding to the kth energy source, and K be the total number of energy types in the component manufacturing stage;

[0027] The formula for calculating carbon emissions during the vehicle assembly stage is as follows:

[0028]

[0029] Among them, C sc,zc E represents carbon emissions during the vehicle assembly phase. l,zc For the consumption of the first type of energy during the vehicle assembly stage, EF yx,l Let L be the energy carbon emission factor corresponding to the l-th energy source, and L be the total number of energy types in the vehicle assembly stage.

[0030] In one possible implementation, the basic data includes the total number of cycles throughout the battery's lifespan;

[0031] Carbon emission factors include grid carbon emission factors;

[0032] Calculate the carbon emissions of the accounting target at each stage, including:

[0033] Obtain the battery relative capacity loss model, and calculate the battery relative capacity loss in each cycle based on the battery relative capacity loss model;

[0034] Based on the relative capacity loss in each cycle, calculate the cumulative input electrical energy of the accounting target throughout its entire life cycle.

[0035] The carbon emissions generated by the target during the charging operation phase are calculated based on the cumulative input electrical energy and the grid carbon emission factor.

[0036] In one possible implementation, the formula for calculating the relative capacity loss of the battery in each cycle, based on the battery relative capacity loss model, is as follows:

[0037]

[0038] in, Let A be the relative capacity loss of the battery during the nth cycle, and E be a preset constant. α The activation energy is R, the gas constant is T, the ambient temperature is z, the power law coefficient is n, and the cycle number is n.

[0039] Based on the relative capacity loss of the battery and the total number of cycles throughout the battery's lifespan, the formula for calculating the cumulative input electrical energy of the target over its entire lifespan is as follows:

[0040]

[0041] Among them, E In To calculate the cumulative electrical energy input of the target over its entire lifespan, N represents the total number of cycles in the battery's lifespan, and E... I Where α is the initial nominal capacity of the battery, DoD is the depth of discharge of the battery, and α is the charge / discharge efficiency of the battery.

[0042] Based on the cumulative input electrical energy and the grid carbon emission factor, the formula for calculating the carbon emissions generated by the charging operation during the usage phase of the accounting target is as follows:

[0043]

[0044] Among them, C sy,yx For the carbon emissions generated during the charging operation phase, EF yx,i This is a carbon emission factor for the power grid.

[0045] In one possible implementation, the disposal phase includes a vehicle dismantling phase and a recycling phase;

[0046] The basic data includes the consumption of various types of energy during the vehicle dismantling and recycling stages;

[0047] Carbon emission factors include energy carbon emission factors;

[0048] Calculate the carbon emissions of the accounting target at each stage, including:

[0049] The carbon emissions during the vehicle dismantling phase are calculated based on the consumption of various types of energy and the corresponding energy carbon emission factors.

[0050] The carbon emissions during the recycling and treatment phase are calculated based on the consumption of various energy sources and their corresponding carbon emission factors.

[0051] In one possible implementation, the formula for calculating carbon emissions during the vehicle dismantling phase is:

[0052]

[0053] Among them, C fq,cj E represents the carbon emissions during the vehicle dismantling phase. o,cj For the consumption of the oth energy source during the vehicle dismantling phase, EF cj,o Let be the energy carbon emission factor corresponding to the o-th energy source, and O be the total number of energy types in the vehicle dismantling stage;

[0054] The formula for calculating carbon emissions during the recycling and treatment phase is:

[0055]

[0056] Among them, C fq,cl E represents the carbon emissions during the recycling and treatment phase. q,cl EF represents the consumption of the qth type of energy during the recycling and processing phase. cl,q Let q be the carbon emission factor corresponding to the q-th energy source, and Q be the total number of energy types in the recycling and treatment stage.

[0057] In one possible implementation, the method further includes;

[0058] Obtain the average daily number of charging sessions and the average daily number of delivery orders for the accounting target;

[0059] The average energy consumed per charge is calculated based on the cumulative input electrical energy and the total number of cycles throughout the battery's lifespan.

[0060] The energy consumed per delivery is calculated based on the average energy consumption per charge, the average number of charges per day, and the average number of delivery orders per day.

[0061] The carbon emissions generated by a single delivery are calculated based on the electrical energy consumed in a single delivery and the grid carbon emission factor.

[0062] In one possible implementation, calculating the carbon emissions of the accounting target at each stage further includes:

[0063] Obtain the number of battery replacements throughout its entire lifecycle, the carbon emissions during the production phase of a single battery, and the carbon emissions during the disposal phase of a single battery.

[0064] The total carbon emissions generated by battery replacement are calculated based on the number of replacements, the carbon emissions during the production stage of a single battery, and the carbon emissions during the disposal stage of a single battery.

[0065] In one possible implementation, multiple carbon emission factors corresponding to the carbon source inventory are obtained, including:

[0066] Determine the operating area for electric bicycles;

[0067] The average or real-time carbon emission factor of the power grid corresponding to the operating area during the accounting period is used as the power grid carbon emission factor.

[0068] Secondly, this application provides a carbon emission accounting device, which includes:

[0069] The determination module is used to determine the accounting target and boundary range. The accounting target is the electric bicycles used in the delivery process, and the boundary range is determined according to the entire life cycle of the electric bicycle, which includes the production stage, the usage stage, and the disposal stage.

[0070] The acquisition module is used to acquire basic data on resource consumption and / or energy consumption associated with carbon emissions within the boundary range of the accounting target;

[0071] The data processing module is used to determine the carbon source inventory of the accounting target at each stage of the entire life cycle based on the basic data.

[0072] The calculation module is used to obtain multiple carbon emission factors corresponding to the carbon source inventory, and calculate the carbon emissions of the accounting target at each stage based on the basic data and multiple carbon emission factors.

[0073] The aggregation module is used to obtain the total carbon emissions of the accounting target within the boundary range based on the carbon emissions of the accounting target at each stage.

[0074] In one possible implementation, the production phase includes a raw material mining phase, a raw material processing phase, a component manufacturing phase, and a vehicle assembly phase.

[0075] The basic data includes the amount of various raw materials mined during the raw material mining stage, as well as the amount of various energy consumed during the raw material processing stage, the parts manufacturing stage, and the vehicle assembly stage.

[0076] Carbon emission factors include implicit carbon emission factors and energy carbon emission factors;

[0077] The calculation module is specifically used for:

[0078] Calculate the carbon emissions during the raw material extraction stage based on the amount of raw materials mined and the corresponding implicit carbon emission factors.

[0079] Based on the consumption of various types of energy and the corresponding energy carbon emission factors in the raw material processing stage, the component manufacturing stage, and the vehicle assembly stage, the carbon emissions of the raw material processing stage, the component manufacturing stage, and the vehicle assembly stage are calculated respectively.

[0080] In one possible implementation, the calculation module uses the following formula to calculate the carbon emissions during the raw material extraction stage, based on the amount of raw materials extracted and the corresponding implicit carbon emission factor:

[0081]

[0082] Among them, C sc,kc For carbon emissions during the raw material extraction stage, m i,kc Let EF be the amount of raw material i being mined. cl,iLet I be the implicit carbon emission factor corresponding to the i-th raw material, and I be the total number of raw material types.

[0083] The formula for calculating carbon emissions during the raw material processing stage is:

[0084]

[0085] Among them, C sc,jg E represents carbon emissions during the raw material processing stage. j,jg Let EF be the consumption of the j-th energy source in the raw material processing stage. yx,j Let J be the energy carbon emission factor corresponding to the j-th energy source, and J be the total number of energy types in the raw material processing stage.

[0086] The formula for calculating carbon emissions during the component manufacturing stage is as follows:

[0087]

[0088] Among them, C sc,lj For carbon emissions during the component manufacturing stage, E k,lj Let EF be the consumption of the k-th energy source during the component manufacturing stage. yx,k Let K be the energy carbon emission factor corresponding to the kth energy source, and K be the total number of energy types in the component manufacturing stage;

[0089] The formula for calculating carbon emissions during the vehicle assembly stage is as follows:

[0090]

[0091] Among them, C sc,zc E represents carbon emissions during the vehicle assembly phase. l,zc For the consumption of the first type of energy during the vehicle assembly stage, EF yx,l Let L be the energy carbon emission factor corresponding to the l-th energy source, and L be the total number of energy types in the vehicle assembly stage.

[0092] In one possible implementation, the basic data includes the total number of cycles throughout the battery's lifespan;

[0093] Carbon emission factors include grid carbon emission factors;

[0094] The calculation module is also used for:

[0095] Obtain the battery relative capacity loss model, and calculate the battery relative capacity loss in each cycle based on the battery relative capacity loss model;

[0096] Based on the relative capacity loss in each cycle, calculate the cumulative input electrical energy of the accounting target throughout its entire life cycle.

[0097] The carbon emissions generated by the target during the charging operation phase are calculated based on the cumulative input electrical energy and the grid carbon emission factor.

[0098] In one possible implementation, the calculation module calculates the relative capacity loss of the battery in each cycle using the battery relative capacity loss model, as follows:

[0099]

[0100] in, Let A be the relative capacity loss of the battery during the nth cycle, and E be a preset constant. α The activation energy is R, the gas constant is T, the ambient temperature is z, the power law coefficient is n, and the cycle number is n.

[0101] Based on the relative capacity loss of the battery and the total number of cycles throughout the battery's lifespan, the formula for calculating the cumulative input electrical energy of the target over its entire lifespan is as follows:

[0102]

[0103] Among them, E In To calculate the cumulative electrical energy input of the target over its entire lifespan, N represents the total number of cycles in the battery's lifespan, and E... I Where α is the initial nominal capacity of the battery, DoD is the depth of discharge of the battery, and α is the charge / discharge efficiency of the battery.

[0104] Based on the cumulative input electrical energy and the grid carbon emission factor, the formula for calculating the carbon emissions generated by the charging operation during the usage phase of the accounting target is as follows:

[0105]

[0106] Among them, C sy,yx For the carbon emissions generated during the charging operation phase, EF yx,i This is a carbon emission factor for the power grid.

[0107] In one possible implementation, the disposal phase includes a vehicle dismantling phase and a recycling phase;

[0108] The basic data includes the consumption of various types of energy during the vehicle dismantling and recycling stages;

[0109] Carbon emission factors include energy carbon emission factors;

[0110] The calculation module is also used for:

[0111] The carbon emissions during the vehicle dismantling phase are calculated based on the consumption of various types of energy and the corresponding energy carbon emission factors.

[0112] The carbon emissions during the recycling and treatment phase are calculated based on the consumption of various energy sources and their corresponding carbon emission factors.

[0113] In one possible implementation, the formula for calculating carbon emissions during the vehicle dismantling phase in the calculation module is:

[0114]

[0115] Among them, C fq,cj E represents the carbon emissions during the vehicle dismantling phase. o,cj For the consumption of the oth energy source during the vehicle dismantling phase, EF cj,o Let be the energy carbon emission factor corresponding to the o-th energy source, and O be the total number of energy types in the vehicle dismantling stage;

[0116] The formula for calculating carbon emissions during the recycling and treatment phase is:

[0117]

[0118] Among them, C fq,cl E represents the carbon emissions during the recycling and treatment phase. q,cl EF represents the consumption of the qth type of energy during the recycling and processing phase. cl,q Let q be the carbon emission factor corresponding to the q-th energy source, and Q be the total number of energy types in the recycling and treatment stage.

[0119] In one possible implementation, the computing module is further configured to:

[0120] Obtain the average daily number of charging sessions and the average daily number of delivery orders for the accounting target;

[0121] The average energy consumed per charge is calculated based on the cumulative input electrical energy and the total number of cycles throughout the battery's lifespan.

[0122] The energy consumed per delivery is calculated based on the average energy consumption per charge, the average number of charges per day, and the average number of delivery orders per day.

[0123] The carbon emissions generated by a single delivery are calculated based on the electrical energy consumed in a single delivery and the grid carbon emission factor.

[0124] In one possible implementation, the computing module is further configured to:

[0125] Obtain the number of battery replacements throughout its entire lifecycle, the carbon emissions during the production phase of a single battery, and the carbon emissions during the disposal phase of a single battery.

[0126] The total carbon emissions generated by battery replacement are calculated based on the number of replacements, the carbon emissions during the production stage of a single battery, and the carbon emissions during the disposal stage of a single battery.

[0127] In one possible implementation, the computing module is further configured to:

[0128] Determine the operating area for electric bicycles;

[0129] The average or real-time carbon emission factor of the power grid corresponding to the operating area during the accounting period is used as the power grid carbon emission factor.

[0130] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor.

[0131] The memory stores the instructions that the computer executes.

[0132] The processor executes computer execution instructions stored in memory to implement a carbon emission accounting method according to the first aspect of the invention.

[0133] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement a carbon emission accounting method according to the first aspect of the invention.

[0134] Fifthly, this application provides a computer program product, including a computer program, which, when executed by a processor, is used to implement a carbon emission accounting method according to the first aspect of the invention.

[0135] In a sixth aspect, this application provides a chip including at least one processor for executing program instructions to implement a carbon emission accounting method according to the first aspect of the invention.

[0136] Based on the implementation methods provided in the above aspects, this application can be further combined to provide more implementation methods.

[0137] This application provides a carbon emission accounting method, comprising: First, determining the accounting target and boundary range, wherein the accounting target is an electric bicycle used in the delivery process, and the boundary range is determined according to the entire life cycle of the electric bicycle, including the production stage, the use stage, and the disposal stage; Next, obtaining basic data on resource consumption and / or energy consumption associated with carbon emissions within the boundary range of the accounting target; Then, based on the basic data, determining the carbon source inventory of the accounting target at each stage of its entire life cycle; Subsequently, obtaining multiple carbon emission factors corresponding to the carbon source inventory, and calculating the carbon emissions of the accounting target at each stage based on the basic data and the multiple carbon emission factors; Finally, obtaining the total carbon emissions of the accounting target within the boundary range based on the carbon emissions of the accounting target at each stage. The following technical effects were achieved: By identifying the electric bicycles used in the delivery process as the accounting target and determining their full life cycle boundary according to the production, use, and disposal stages, carbon emission accounting can cover the main emission links related to the accounting target; by obtaining basic data on resource consumption and / or energy consumption associated with carbon emissions within the boundary range of the accounting target, and determining the carbon source inventory for each stage of the full life cycle, the targeting and completeness of emission source identification at each stage can be enhanced; furthermore, by combining multiple carbon emission factors corresponding to the carbon source inventory, the carbon emissions of the accounting target at each stage can be calculated and the total carbon emissions within the boundary range can be obtained, thereby improving the accuracy and scenario adaptability of the full life cycle carbon emission accounting of electric bicycles in the delivery scenario. Attached Figure Description

[0138] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0139] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0140] Figure 1 A schematic flowchart illustrating a carbon emission accounting method provided in this application embodiment;

[0141] Figure 2 This is a schematic diagram of the structure of a carbon emission accounting device provided in an embodiment of this application;

[0142] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0143] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0144] In the embodiments of this application, the terms "first" and "second" are used to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply difference. It should be noted that in the embodiments of this application, the words "exemplary" or "for example" are used to indicate that something is being used as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being better or more advantageous than other embodiments or design schemes. Specifically, the use of "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner. In the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more.

[0145] It should be noted that the phrase "at...time" in the embodiments of this application can refer to the instant at which a certain situation occurs, or to a period of time after the occurrence of a certain situation; the embodiments of this application do not specifically limit this. Furthermore, the carbon emission accounting method provided in the embodiments of this application is merely an example; a carbon emission accounting method may include more or fewer elements.

[0146] Carbon emission management of vehicles in the delivery industry falls at the intersection of life cycle assessment, operational data analysis, and green management, primarily targeting "last-mile" delivery scenarios such as food delivery, instant retail, same-city errands, and last-mile express delivery. In these scenarios, electric bicycles are widely deployed as primary transportation tools due to their high mobility, adaptability, and low purchase and operating costs. Their operation typically involves frequent starts and stops, high loads, long-term continuous operation, and frequent charging and discharging. Carbon emission accounting for these vehicles usually requires a relatively complete data processing architecture in practice. This architecture involves at least multiple information sources, including vehicle basic files, production and procurement data, operational scheduling records, charging and energy consumption records, and scrapping and recycling records. A unified data aggregation standard is used to correlate and organize the resource and energy consumption of electric bicycles in the production, use, and disposal stages. For delivery companies, platform operators, park managers, and industry regulators, it is often necessary to continuously assess the carbon emission performance of different vehicle models, component configurations, and operational intensities under conditions of parallel operation across regions, multiple sites, and multiple batches of vehicles. This assessment is crucial for supporting management needs such as vehicle selection, capacity deployment, cost accounting, energy conservation and emission reduction assessments, and low-carbon governance. Therefore, the life-cycle carbon emission accounting of electric bicycles used in the delivery process is no longer a static statistical problem of energy consumption for a single vehicle or at a specific point in time. Instead, it is a comprehensive technical problem that requires systematic processing of boundary ranges, basic data, carbon source composition, and phased emission results within complex business scenarios. Its application scenarios exhibit significant industry specificity, operational complexity, and heterogeneous data from multiple sources.

[0147] In existing technologies, carbon emission accounting for transportation vehicles typically employs a life cycle assessment-based approach, uniformly evaluating the production, use, and disposal stages. The basic idea is to first identify the accounting object, then collect relevant material, energy, and process data according to preset life cycle boundaries, and subsequently match corresponding carbon emission factors to sum the emissions from each stage, thus obtaining the total carbon emission result. This approach is applicable to conventional passenger vehicles, shared mobility devices, or general-purpose electric vehicles, enabling the quantification of product environmental impact at a macro level. However, when this method is directly applied to the electric bicycle scenario in the delivery industry, its limitations are significantly amplified. Firstly, existing methods often set boundaries based on general traffic conditions, assuming relatively stable vehicle operation, long lifespan of key components, and low maintenance frequency. This fails to reflect the realities of high-frequency starts and stops, high-load commuting, multiple daily refueling trips, and high component wear and tear in delivery scenarios, leading to a deviation between the boundary settings for the production, use, and disposal stages and actual operational characteristics. Secondly, existing methods often rely on static data, with resource and energy consumption data primarily derived from averages, industry reference values, or annual statistics. This makes it difficult to adapt to the significant differences in the performance of delivery vehicles across different regions, times, and task densities. While the accounting results may appear complete, their explanatory power for specific business operations is insufficient. Thirdly, existing solutions do not adequately address the connections between different stages. Component input during the production stage, wear and tear during the usage stage, and dismantling and recycling during the disposal stage are often calculated separately, lacking the ability to continuously track and uniformly map around a common accounting objective. This can easily lead to incomplete carbon source identification, duplication or omission between stages, and distortion of total results. Especially for delivery companies, if the accounting results cannot accurately reflect the true carbon emission structure of frontline vehicles, it is difficult to support operational management and emission reduction strategy formulation. Existing technologies have significant shortcomings in accuracy, adaptability, and business usability.

[0148] Therefore, improving the accuracy and adaptability of carbon emission accounting for the entire life cycle of electric bicycles in delivery scenarios has become an urgent technical problem to be solved.

[0149] Based on this, this application proposes a carbon emission accounting method, which can be used in the fields of energy conservation, emission reduction, and carbon emission accounting, aiming to solve the above-mentioned technical problems of the prior art. The method first identifies the electric bicycles used in the delivery process as the accounting target, and defines the boundary range according to the entire life cycle of the electric bicycle as the production stage, usage stage, and disposal stage. Within the boundary range, it acquires basic data on resource consumption and / or energy consumption related to carbon emissions, and determines the carbon source inventory of the accounting target at each stage of its life cycle based on the basic data. It further acquires multiple carbon emission factors corresponding to the carbon source inventory, calculates the carbon emissions of the accounting target at each stage based on the basic data and multiple carbon emission factors, and then obtains the total carbon emissions of the accounting target within the boundary range based on the carbon emissions at each stage. Combined with the actual application environment of the delivery industry, this method can be deployed in a business architecture consisting of a data acquisition layer, a carbon measurement model layer, and a result output layer. The data acquisition layer is used to receive basic information such as management data, environmental impact assessment data, and literature data; the carbon measurement model layer is used to perform calculations around the production stage, usage stage, and disposal stage; and the result output layer is used to generate accounting results oriented towards operation management. By adopting the above technical approach, a unified accounting logic covering the entire life cycle of electric bicycles used in the delivery process can be formed, which can improve the completeness of carbon emission identification, the consistency of stage calculations, and the reliability of total results, thus providing a foundation for more refined low-carbon management in the future.

[0150] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0151] Figure 1 This is a flowchart illustrating a carbon emission accounting method provided in an embodiment of this application. Figure 1 As shown, the method includes:

[0152] S101. Determine the accounting target and boundary scope. The accounting target is the electric bicycles used in the delivery process. The boundary scope is determined according to the entire life cycle of the electric bicycle, which includes the production stage, the usage stage, and the disposal stage.

[0153] In this embodiment, electric bicycles are used as the specific object of the accounting target to carry out the full life cycle carbon emission accounting. The implementation is based on using vehicles actually put into operation in the delivery business as a unified accounting unit, and continuously tracking the resource input, energy consumption, and disposal destination of these vehicles during the production, use, and disposal stages. The term "full life cycle" defines the complete scope of electric bicycle carbon emission accounting, covering the production, use, and disposal stages. Its function is to incorporate data originally scattered across manufacturing, operation, and disposal stages into a single accounting boundary, avoiding distorted results due to unclear accounting objects or inconsistent boundary truncation.

[0154] In practice, the implementing entity can be a carbon accounting server deployed in the delivery company's information system, an analysis node in the park management platform, or a terminal device with data processing capabilities. This entity first receives the tasks to be calculated. These tasks can be manually entered into the management interface or automatically triggered by the dispatch system, asset management system, or vehicle file system. When manually entered, the vehicle number, model number, station, deployment area, purchase batch, and activation time can be input. When automatically triggered, the unique vehicle identifier can be read from the vehicle master data table, and vehicle configuration parameters, procurement information, and historical operating records can be extracted simultaneously. Subsequently, the vehicle is identified as an electric bicycle used in the delivery process. Identification criteria may include vehicle purpose label, business line, dispatch frequency, delivery task binding relationship, and battery charging / swapping records. Vehicles meeting the delivery capacity attributes are identified as accounting targets; ordinary commuter vehicles, test vehicles, or idle vehicles not used for delivery are excluded from this calculation.

[0155] In determining the boundary scope, constraints can be imposed according to three dimensions: time boundary, process boundary, and object boundary. The time boundary begins with the raw material input and component manufacturing time corresponding to vehicle production, proceeds through vehicle delivery, actual distribution and use, maintenance and operation, until the vehicle is scrapped, the battery is retired, components are dismantled, and materials are recycled. Within the process boundary, the production stage can include resource and energy consumption during the manufacturing of components such as the chassis, wheels, motor, battery, controller, plastic parts, and fasteners, as well as the assembly of the entire vehicle; the usage stage can include electricity consumption during vehicle operation, electricity consumption during recharging, additional resource consumption corresponding to the replacement of key components due to high-frequency operation, and auxiliary energy input related to maintenance; the disposal stage can include processes such as vehicle dismantling, classified transportation, recycling, harmless disposal, and pre-treatment for the reuse of recyclable materials. The object boundary includes data directly related to the vehicle in the calculation; general operational energy consumption such as office energy consumption and station lighting, which is not directly related to the vehicle, is not included in the current vehicle's full life-cycle carbon emission results.

[0156] In one possible embodiment, the boundary range can also be standardized according to the enterprise's management system. For example, a unified boundary template can be established, which pre-defines the main component types included in the production stage, the energy replenishment and replacement items included in the usage stage, and the dismantling and recycling items included in the disposal stage. The executing entity calls the template after identifying a specific vehicle and instantiates the template based on vehicle model differences. For example, for electric bicycles equipped with lithium batteries, cell manufacturing, battery assembly, and retired battery recycling can be listed separately; for vehicles using lead-acid batteries, differentiated boundaries can be formed according to the corresponding battery type. Through the above processing, the accounting target and boundary range can stably correspond to the actual working conditions of high-frequency start-stop, high load, and multiple rounds of energy replenishment in the delivery industry, so that subsequent data collection and carbon emission calculation are carried out around a unified standard, reducing accounting deviations caused by boundary omissions, boundary overlaps, or inconsistencies in cross-stage statistics.

[0157] S102. Obtain basic data on resource consumption and / or energy consumption associated with carbon emissions within the boundary range of the accounting target.

[0158] In this embodiment, the basic data serves as the raw information required for subsequent carbon source identification and carbon emission calculation. Its core content involves recording, organizing, and structurally mapping the resource and / or energy consumption occurring at each stage within the target's boundary. Resource consumption typically includes the input quantities of raw materials, components, replacement parts, packaging materials, and auxiliary materials used in the disposal process; energy consumption typically includes electricity, gas, and fuel consumption during production and processing, as well as charging electricity during the usage stage and energy usage during transportation and disposal. By acquiring the basic data, electric bicycles used in the delivery process can be transformed from static archive objects into accounting objects with quantifiable input conditions, providing a direct basis for forming a carbon source inventory.

[0159] In practice, the implementing entity can construct a data acquisition layer and extract information corresponding to the accounting objectives from management data, environmental impact assessment data, and literature data. Management data can come from purchase lists, supplier material lists, vehicle entry and exit records, maintenance work orders, charging platform logs, battery swapping system data, scrapping approval records, and recycling ledgers. Environmental impact assessment data can come from publicly disclosed manufacturing energy consumption data of production enterprises, component production line energy consumption reports, and environmental impact assessment documents of dismantling and recycling facilities. Literature data is used to provide industry average reference values ​​when some original data is missing, such as the production energy consumption per unit mass of a certain type of frame material, typical emission parameters of a certain type of motor manufacturing process, and processing energy consumption of a certain type of battery recycling process. After receiving multi-source data, the implementing entity can aggregate the data according to vehicle unique identifier, component code, date, station, and stage label, and form a vehicle-level basic data set through timestamp alignment and primary key association.

[0160] For the production stage, basic data can include information such as the total vehicle weight, frame material and weight, motor type and rated power, battery type and capacity, controller specifications, number of tires, weight of plastic coverings, amount of packaging materials used, and energy consumption during vehicle assembly. For the usage stage, basic data can include information such as cumulative vehicle mileage, average daily order count, energy consumption per unit mileage, energy consumption per charge, number of charges, grid area of ​​the charging station, total battery cycle count over its entire lifespan, number of battery replacements, number of tires and brake pads replaced, and auxiliary energy consumption during maintenance. For the disposal stage, basic data can include information such as the end-of-life date, number of retired batteries, total vehicle dismantling weight, weight of various recycled materials, weight of non-recyclable waste, transportation distance, and energy consumption for dismantling and processing.

[0161] In one possible embodiment, the data acquisition process includes not only direct extraction but also data cleaning, missing data completion, and standardization. For example, abnormal peak values ​​in charging records can be filtered based on the vehicle battery's rated capacity and charging curve; missing component weights in repair work orders can be supplemented based on the vehicle model's bill of materials; and original records from different suppliers using different units of measurement can be uniformly converted to standard units such as kilograms, kilowatt-hours, units, or kilometers. For instance, if battery capacity records exist in both ampere-hours and watt-hours, they can be converted to a unified unit of electricity based on the nominal voltage; if material weights exist in both net and gross weight formats, net weight data, which has a higher correlation with carbon emissions, can be retained according to pre-set rules. After the basic data is processed, it can be generated as a data table categorized by stage, a data cube aggregated by vehicle, or an operational database record stored in time series, triggering the next stage of carbon source inventory construction.

[0162] Based on the above analysis, it can be seen that the basic data acquisition step solves the problem that existing technologies rely on average values ​​or annual statistics, which are difficult to reflect the real differences in different regions and different operating intensities. This step transforms the accounting input from static average values ​​into dynamic data that matches specific vehicles and specific operating conditions, thereby improving the adaptability and interpretability of subsequent carbon emission accounting.

[0163] S103. Based on the basic data, determine the carbon source inventory of the accounting target at each stage of the entire life cycle.

[0164] In this embodiment, the carbon source inventory is used to list and quantify the sources related to carbon emissions at each stage of the accounting target, so as to establish a mapping relationship between basic data and carbon emission factors. The carbon source inventory can be the result of identifying, merging, classifying, and coding resource consumption and energy consumption sources based on stage boundaries and emission association rules. By forming a carbon source inventory, material and manufacturing inputs in the production stage, energy replenishment and loss inputs in the usage stage, and dismantling and recycling inputs in the disposal stage can be transformed into calculable carbon emission source units, avoiding duplicate or omission calculations between stages.

[0165] In practice, the implementing entity can first establish a carbon source identification rule base. This rule base pre-defines typical carbon source categories, identification conditions, and attribution principles for each stage. For example, in the production stage, steel, aluminum, plastics, rubber, motor materials, battery materials, and assembly electricity can be identified as independent carbon sources; in the usage stage, charging electricity, battery swapping electricity, battery replacement, tire replacement, and brake component replacement can be identified as usage-related carbon sources; in the disposal stage, energy consumption from vehicle dismantling, retired battery processing, metal material recycling, and non-recyclable waste disposal can be identified as end-of-life disposal carbon sources. After obtaining the basic data, the implementing entity can map each data item to the corresponding carbon source category based on the field meaning, data source tags, and stage attributes, forming a set of carbon source entries per vehicle.

[0166] In the specific processing flow, primary classification can be performed by stage, followed by secondary classification by resource type or energy type, and finally, tertiary carbon source entries can be formed based on the smallest calculable unit. For example, in the production stage, the consumption of steel for the vehicle frame, copper for the motor, input of positive and negative electrode materials for the battery, and the power consumption of the entire vehicle assembly can each form different entries; in the usage stage, the total charging power within a certain statistical period can be used as an electricity carbon source entry, and the number of tire replacements multiplied by the average weight of a single tire forms a tire replacement carbon source entry; in the disposal stage, the power consumption of dismantling equipment forms an energy consumption carbon source entry, the weight of retired batteries forms a disposal carbon source entry, and the weight of recyclable metals forms a recycling and processing related entry. Each entry can include at least the following fields: carbon source code, stage identifier, carbon source name, activity data, unit of measurement, data source, corresponding carbon emission factor category, and time range. Among them, the activity data can be the cleaned and unit-consistent values ​​of basic data on resource consumption and / or energy consumption associated with carbon emissions.

[0167] In one possible embodiment, the carbon source inventory can be further refined or aggregated based on the granularity of the basic data. When management data is complete, the battery can be broken down into finer-grained carbon sources such as cells, casings, and management modules; when only the entire battery pack information is available, it is treated as a carbon source for the battery assembly. For electricity consumption during the usage phase, a regional inventory can be constructed based on the power grid structure of the charging location, so that the charging volume at different sites and at different times corresponds to different electricity carbon source entries. For the recycling phase, if independent processing data for each type of material cannot be obtained, a higher-level carbon source inventory can be formed according to the total amount of vehicle dismantling and the proportion of material composition. For example, the four main destinations of steel, aluminum, plastic, and batteries generated after the dismantling of the scrapped vehicle can be listed separately to ensure that the main emission sources are covered.

[0168] After constructing the carbon source inventory using the above method, the implementing entity can perform integrity and duplication checks on the inventory. Integrity checks confirm that at least one type of valid carbon source entry exists in each of the three stages: production, usage, and disposal. Duplication checks identify whether the same replacement part is counted both in the usage stage's replacement entries and in the initial vehicle configuration during the production stage. Based on the above analysis, it can be seen that the carbon source inventory determination steps can achieve continuous collection and unified mapping of carbon emission sources throughout the entire lifecycle around the same accounting objective, solving the problems of insufficient connection between stages and incomplete carbon source identification in existing technologies, thereby improving the consistency and accuracy of subsequent emission calculations.

[0169] S104. Obtain multiple carbon emission factors corresponding to the carbon source inventory, and calculate the carbon emissions of the accounting target at each stage based on the basic data and multiple carbon emission factors.

[0170] In this embodiment, carbon emission factors are a set of parameters used to convert resource consumption and energy consumption in basic data into carbon emissions. Essentially, they are conversion parameters characterizing the carbon emission contribution corresponding to a unit of activity data. Multiple carbon emission factors correspond to different carbon source categories in the carbon source inventory, such as the implicit carbon emission factor per unit mass of steel, the carbon emission factor per unit of electricity generated by the regional power grid, and the carbon emission factor per unit mass of recycled waste batteries. By associating the carbon source inventory with multiple carbon emission factors, multi-source, heterogeneous material and energy consumption data can be transformed into comparable and summable carbon emissions.

[0171] In practice, the implementing entity can construct a carbon emission factor database, storing carbon emission factors applicable to different stages, carbon source categories, regions, and times. Sources of carbon emission factors can include databases published by relevant institutions or industries, internally verified factor tables of enterprises, screened factor values ​​from publicly available literature, and parameter sets provided by third-party evaluation agencies. Each factor record in the database can include a factor code, applicable object, applicable stage, unit, value, regional label, time label, version number, and data source level. During the correlation processing, candidate carbon emission factors can be first screened based on the factor category, regional label, and time range of the carbon source entry, and then the final carbon emission factor used can be determined according to priority rules. Priority rules can be set such that measured or verified enterprise factors are higher than the industry average factor, regional time-of-use grid carbon emission factors are higher than the regional average electricity factor, and the latest version factor is higher than the historical version factor.

[0172] During the calculation process, the following relationship can be applied to each carbon source entry: the emission of a carbon source equals the activity data corresponding to that carbon source multiplied by the matching carbon emission factor; the carbon emission of a certain stage equals the sum of the emissions of all carbon sources in that stage. In the above relationship, the activity data can be the value of the basic data after cleaning and unit unification, and the carbon emission factor can be the emission parameter corresponding to the unit activity level. Multiplying the two can realize the conversion from consumption to emission. For example, if the total charging amount during the statistical period of a vehicle's use stage is G kWh, and the corresponding regional power grid carbon emission factor is F kg CO2e / kWh, then this part of the emission can be expressed as the product of G and F; if the mass of the frame steel in the production stage is M kg, and the corresponding implicit carbon emission factor of steel manufacturing is H kg CO2e / kg, then the emissions related to the frame steel can be expressed as the product of M and H. In the case of multiple carbon source entries within a certain stage, the implementing entity can calculate the emissions of each entry in sequence and accumulate them within the stage to obtain the carbon emissions of the production stage, the use stage and the disposal stage respectively.

[0173] In one possible embodiment, the selection and calculation of carbon emission factors can be updated according to actual conditions. For example, for electricity carbon emissions during the usage phase, if the vehicle is charged at different sites in different regions, the corresponding grid carbon emission factor can be matched according to the actual charging location; if the grid structure changes significantly in different months in the same region, the real-time grid carbon emission factor can also be used on a monthly basis. For recycling and disposal during the disposal phase, different carbon emission factors can be selected for different recycling processes. For components lacking detailed process energy consumption data in the production phase, a component-level comprehensive carbon emission factor can be used for direct calculation. After completing the calculation, the executing entity can also output an intermediate result table, which can record the activity data of each carbon source item, the corresponding value of the carbon emission factor, the carbon emission amount, and the calculation basis to support subsequent audit traceability.

[0174] Based on the above analysis, this step establishes a correspondence between carbon sources and carbon emission factors, and performs phased calculations according to a unified formula. This allows the diverse resource and energy consumption generated by electric bicycles used in the delivery process under complex operating conditions to be converted into standardized carbon emission results. This solves the problem of existing technologies that only perform rough summaries and are difficult to process differently for different stages. The dynamic matching of carbon emission factors with activity data further enhances the adaptability of the accounting results to changes in region, time, and operating conditions.

[0175] S105. Based on the carbon emissions of the accounting target at each stage, obtain the total carbon emissions of the accounting target within the boundary range.

[0176] In this embodiment, the total carbon emissions represent the sum of carbon emissions at each stage within the boundary of the accounting target. It is a comprehensive indicator characterizing the overall carbon impact of electric bicycles used in the delivery process throughout their entire life cycle. This total is formed by adding up the carbon emissions calculated separately for the production, usage, and disposal stages. Its significance lies in unifying the carbon emission contributions from the manufacturing, operation, and disposal ends under the same measurement caliber, thereby supporting enterprises in making quantitative comparisons of vehicle selection, capacity allocation, and emission reduction measures.

[0177] In practice, after obtaining the carbon emissions of the accounting target at each stage, the implementing entity can first verify the validity of the stage results. For example, it can check whether the emission values ​​of each stage are non-negative, whether there are any abnormal omissions, and whether the units are uniformly converted to carbon dioxide equivalent. After verification, the carbon emissions of the production stage, usage stage, and disposal stage can be summed according to preset summation rules to generate the total carbon emissions of the accounting target within the boundary range. This preset summation rule can use a direct summation method, or it can be further converted into carbon emissions per unit mileage, per unit order, or per unit service time when periodic display is required. However, when outputting the total amount for the entire life cycle, it is still based on the sum of the three stages. After generating the total amount result, it can be written to the result database and associated with and stored metadata such as vehicle number, accounting period, boundary version, carbon emission factor version, and calculation time.

[0178] In the output layer, total carbon emissions can be further divided into various management-oriented viewpoints. For example, a single vehicle's full lifecycle carbon emission report can be output, showing the proportions of emissions during the production, usage, and disposal phases. A comparative analysis of different batches of the same vehicle model can be provided to support procurement decisions. The average carbon emission levels of electric bicycles at different stations and operating areas can also be output to identify high-emission areas and operating conditions. For instance, if a batch of vehicles contributes significantly more to emissions during the usage phase than during the production and disposal phases, further analysis can be conducted to determine if there are issues such as low charging efficiency, high regional power grid carbon emission factors, or frequent component replacements. If the proportion during the production phase is significantly higher, this can guide the selection of lower-carbon materials and better component configurations.

[0179] In one possible embodiment, after obtaining the total carbon emissions, the implementing entity can also calculate the stage contribution rate, which can be expressed as the ratio of carbon emissions in a certain stage to the total carbon emissions, reflecting the degree of contribution of each stage to the total emissions over the entire life cycle. This processing does not change the total carbon emissions themselves, but rather enhances the interpretability of the results, enabling users to identify key emission reduction areas based on the same accounting results. Furthermore, the implementing entity can also combine the total carbon emissions with mileage, delivery volume, and vehicle lifespan to generate derived indicators for operational analysis, supporting capacity management and low-carbon assessment.

[0180] Based on the above analysis, by sequentially associating the accounting target, boundary range, basic data, carbon source inventory, multiple carbon emission factors, and carbon emissions at each stage, the embodiments of this application can realize the carbon emission accounting of electric bicycles used in the delivery process throughout their entire life cycle, and uniformly aggregate the emission contributions scattered in the production, use, and disposal stages into a total carbon emission. This method is designed for the actual working conditions of electric bicycles in the delivery industry, which involve frequent starts and stops, high loads, rapid component wear, and frequent recharging. It can improve the completeness of carbon emission identification, the consistency of stage calculations, and the reliability of the total result, so that the accounting result is no longer limited to a static average estimate of general transportation vehicles, but can reflect the real emission structure of specific vehicles in specific business scenarios.

[0181] This application provides a carbon emission accounting method, including: determining the accounting target and boundary range, where the accounting target is an electric bicycle used in the delivery process, and the boundary range is determined according to the entire life cycle of the electric bicycle, including the production stage, the usage stage, and the disposal stage; acquiring basic data on resource consumption and / or energy consumption associated with carbon emissions within the boundary range of the accounting target; determining a carbon source inventory for the accounting target at each stage of the entire life cycle based on the basic data; acquiring multiple carbon emission factors corresponding to the carbon source inventory, and calculating the carbon emissions of the accounting target at each stage based on the basic data and the multiple carbon emission factors; and obtaining the total carbon emissions of the accounting target within the boundary range based on the carbon emissions of the accounting target at each stage. In this embodiment, by establishing a unified full life cycle accounting boundary around the electric bicycle used in the delivery process, and continuously processing resource consumption, energy consumption, carbon source identification, carbon emission factor matching, and carbon emission calculation for the production stage, usage stage, and disposal stage, refined carbon emission accounting for the actual working conditions of the delivery industry is achieved. Compared to processing methods that rely solely on general operating conditions or average parameters, this solution can more fully reflect the emission differences under different vehicle models, regions, operating intensities, and component configurations. It reduces accounting errors caused by deviations in boundary settings, static data definitions, and insufficient stage transitions, thus providing an accurate data foundation for delivery companies, platform operators, park managers, and industry regulators to conduct vehicle selection, emission reduction assessments, operational optimization, and green governance.

[0182] Based on the aforementioned embodiments, the production stage further includes a raw material mining stage, a raw material processing stage, a component manufacturing stage, and a vehicle assembly stage; the basic data includes the mining volume of various raw materials in the raw material mining stage, and the consumption of various energy sources in the raw material processing stage, component manufacturing stage, and vehicle assembly stage; the carbon emission factors include implicit carbon emission factors and energy carbon emission factors; the calculation of the carbon emissions of the accounting target in each stage includes: calculating the carbon emissions of the raw material mining stage based on the mining volume of raw materials and the corresponding implicit carbon emission factors; and calculating the carbon emissions of the raw material processing stage, component manufacturing stage, and vehicle assembly stage respectively based on the consumption of various energy sources and the corresponding energy carbon emission factors in the raw material processing stage, component manufacturing stage, and vehicle assembly stage.

[0183] In this embodiment, the raw material mining stage characterizes the acquisition process of metal ores, rubber raw materials, and plastic base materials before they enter the production system. The amount of raw materials mined can be statistically analyzed by mass unit and matched with the implicit carbon emission factor of the mining stage. This implicit carbon emission factor characterizes the carbon emission intensity per unit of raw material during mining, primary sorting, and raw ore transportation. The specific value of the implicit carbon emission factor can be obtained from environmental databases, industry accounting benchmarks, or audited supplier information. The energy consumed in the raw material processing stage, component manufacturing stage, and vehicle assembly stage includes electricity, natural gas, steam, or other process fuels. The consumption of various energy types can be obtained from meters, workshop energy consumption systems, or production ledgers and matched with the corresponding energy carbon emission factor to convert it into the carbon emission amount of the corresponding stage. The energy carbon emission factor can be determined based on the regional power grid carbon emission factor, the lower heating value of fuel, and the standard emission coefficient to ensure consistency in the accounting standards of different processes.

[0184] In practical implementation, the extraction volume of each raw material can first be summarized by category, and the summarized result can be multiplied with the corresponding implicit carbon emission factor to obtain the carbon emissions of the raw material extraction stage. If the same raw material has multiple sources, the emissions can be calculated separately for each source before summarizing to avoid discrepancies caused by source differences. For the raw material processing stage, component manufacturing stage, and vehicle assembly stage, energy consumption records for each stage can be read separately, converted item by item according to energy type and corresponding energy carbon emission factor, and then the emissions results of each energy source within the same stage can be summed to form the carbon emissions output for that stage. The above calculation results can serve as the basis for carbon emission structure analysis in the production stage, providing a basis for subsequent identification of high-emission processes, optimization of material procurement, and improvement of manufacturing processes.

[0185] By further refining the production process into four stages—raw material mining, raw material processing, component manufacturing, and vehicle assembly—and using corresponding implicit carbon emission factors or energy carbon emission factors for each, it is possible to distinguish between carbon emissions from raw material acquisition and those from processing and manufacturing. This avoids mixing carbon emissions from different sources in statistical analysis, thereby improving the accuracy, traceability, and stage-specific interpretability of carbon accounting during the production phase. This approach also adapts to production differences across batches, supply chain sources, and process configurations, providing a stable data foundation for the full lifecycle carbon emission management of electric bicycles in the delivery industry.

[0186] Based on the aforementioned embodiments, the formula for calculating carbon emissions during the raw material extraction stage, according to the amount of raw materials mined and the corresponding implicit carbon emission factors, is as follows:

[0187]

[0188] Among them, C sc,kc For carbon emissions during the raw material extraction stage, m i,kc Let EF be the amount of raw material i being mined. cl,i Let I be the implicit carbon emission factor corresponding to the i-th raw material, and I be the total number of raw material types.

[0189] The formula for calculating carbon emissions during the raw material processing stage is:

[0190]

[0191] Among them, C sc,jg E represents carbon emissions during the raw material processing stage. j,jg Let EF be the consumption of the j-th energy source in the raw material processing stage. yx,j Let J be the energy carbon emission factor corresponding to the j-th energy source, and J be the total number of energy types in the raw material processing stage.

[0192] The formula for calculating carbon emissions during the component manufacturing stage is as follows:

[0193]

[0194] Among them, C sc,lj For carbon emissions during the component manufacturing stage, E k,lj Let EF be the consumption of the k-th energy source during the component manufacturing stage. yx,k Let K be the energy carbon emission factor corresponding to the kth energy source, and K be the total number of energy types in the component manufacturing stage;

[0195] The formula for calculating carbon emissions during the vehicle assembly stage is as follows:

[0196]

[0197] Among them, C sc,zc E represents carbon emissions during the vehicle assembly phase. l,zc For the consumption of the first type of energy during the vehicle assembly stage, EF yx,l Let L be the energy carbon emission factor corresponding to the l-th energy source, and L be the total number of energy types in the vehicle assembly stage.

[0198] In this embodiment, C sc,kc The carbon emissions used to represent the raw material extraction stage can be calculated by multiplying the extraction volume of various raw materials with their corresponding implicit carbon emission factors and then summing the results; m i,kc The quantity of raw material i mined can be obtained from mine ledgers, procurement records, or supply chain bills of materials; EF cl,i The implicit carbon emission factor corresponding to the i-th raw material can be determined from industry databases, life cycle assessment literature, or a verified carbon emission factor library. sc,jg C sc,lj and C sc,zc These are used to represent carbon emissions during the raw material processing stage, the component manufacturing stage, and the vehicle assembly stage, respectively. They can be calculated by mapping energy consumption at each stage to the energy carbon emission factor; E j,jg E k,lj and E l,zc These represent the energy consumption at each stage, and the energy type can include electricity, natural gas, diesel, or steam, etc.; EF yx,j EF yx,k and EF yx,l These represent the carbon emission factors for the corresponding energy sources. I, J, K, and L are used to limit the total number of raw materials or energy types involved in the accumulation, ensuring consistency in the accounting boundaries.

[0199] In practical implementation, the extraction volume during the raw material mining stage can be uniformly converted to kilograms or tons by mass unit. A mapping table is established based on the type of raw material, and the actual input of each type of raw material is multiplied by its implicit carbon emission factor and then summed to form the carbon emission amount for that stage. Energy consumption during the raw material processing, component manufacturing, and vehicle assembly stages can be collected from electricity meters, gas meters, fuel metering units, or production management systems, and then calculated in conjunction with the energy carbon emission factors corresponding to the energy types. The calculation results for each stage are output as the stage-specific carbon emission amount, which can serve as the data basis for summarizing the carbon emissions of the entire vehicle lifecycle.

[0200] In operation, this implementation method allows the implementing entity to calculate carbon emissions at each stage based on raw material extraction volume, various energy consumption amounts, and corresponding implicit or energy carbon emission factors. Specifically, carbon emissions for the raw material extraction stage, raw material processing stage, component manufacturing stage, and vehicle assembly stage can be calculated independently according to stage boundaries to avoid mixing data from different sources. By calculating implicit and energy carbon emissions in stages, the traceability of emission sources at each stage can be enhanced, and the degree of matching between the full life cycle accounting results and the actual production process can be improved. This approach accurately reflects emission differences under different materials and energy structures, improving the completeness, consistency, and comparability of carbon emission accounting.

[0201] In one possible implementation, the basic data includes the total number of cycles throughout the battery's life cycle; the carbon emission factor includes the grid carbon emission factor; the calculation of the carbon emissions of the accounting target at each stage includes: obtaining the battery's relative capacity loss model, and calculating the relative capacity loss of the battery in each cycle based on the battery's relative capacity loss model; calculating the cumulative input electrical energy of the accounting target throughout its life cycle based on the relative capacity loss in each cycle; and calculating the carbon emissions generated by the accounting target during charging operation in the usage stage based on the cumulative input electrical energy and the grid carbon emission factor.

[0202] The total number of battery cycles throughout its entire lifespan characterizes the total number of charge-discharge cycles a battery can complete during its usage phase, serving as a time benchmark for battery degradation calculation. The grid carbon emission factor characterizes the carbon emission intensity per unit of electrical energy, and its value can be determined by combining the average emission level of the power grid in the calculation area. The battery relative capacity loss model describes the relationship between battery capacity degradation and the number of cycles during cyclic use; this model can be established based on ambient temperature, depth of discharge, charging rate, and cumulative number of cycles. Cumulative input energy characterizes the total electrical energy required to complete charging within the battery's entire lifespan, serving as an intermediate quantity for energy consumption calculation during the usage phase.

[0203] In practical implementation, a relative capacity loss model for the battery can be established first based on the total number of cycles throughout the battery's lifespan. The number of cycles is then input into the relative capacity loss model to calculate the relative capacity loss for each cycle. The relative capacity loss model can employ an empirical decay function, a piecewise linear function, or a capacity decay curve fitted based on historical operating data to adapt to different battery systems and distribution conditions. After obtaining the relative capacity loss in each cycle, the input energy throughout the entire lifespan can be accumulated by combining the battery's initial nominal capacity, battery charge / discharge efficiency, and battery depth of discharge to obtain the cumulative input energy. Multiplying the cumulative input energy by the corresponding grid carbon emission factor yields the carbon emissions generated during the charging operation phase.

[0204] This approach models the relationship between battery capacity degradation and cycle count, transforming the long-term energy replenishment needs of e-bikes used in delivery into calculable input energy. It further couples this with the grid's carbon emission factor, allowing carbon emissions during the usage phase to dynamically change with battery aging and cycle depth. This avoids the bias caused by simply estimating energy consumption at a fixed value. Adopting this method improves the accuracy and adaptability of carbon emission accounting for e-bikes in delivery scenarios, ensuring the results reflect the impact of battery degradation on charging energy consumption. This provides a reliable basis for capacity scheduling, vehicle selection, and low-carbon management.

[0205] Based on the aforementioned embodiments, further, according to the battery relative capacity loss model, the calculation formula for the relative capacity loss of the battery in each cycle is as follows:

[0206]

[0207] in, Let A be the relative capacity loss of the battery during the nth cycle, and E be a preset constant. α The activation energy is R, the gas constant is T, the ambient temperature is z, the power law coefficient is n, and the cycle number is n.

[0208] Based on the relative capacity loss of the battery and the total number of cycles throughout the battery's lifespan, the formula for calculating the cumulative input electrical energy of the target over its entire lifespan is as follows:

[0209]

[0210] Among them, E In To calculate the cumulative electrical energy input of the target over its entire lifespan, N represents the total number of cycles in the battery's lifespan, and E... I Where α is the initial nominal capacity of the battery, DoD is the depth of discharge of the battery, and α is the charge / discharge efficiency of the battery.

[0211] Based on the cumulative input electrical energy and the grid carbon emission factor, the formula for calculating the carbon emissions generated by the charging operation during the usage phase of the accounting target is as follows:

[0212]

[0213] Among them, C sy,yx For the carbon emissions generated during the charging operation phase, EF yx,i This is a carbon emission factor for the power grid.

[0214] Among them, the relative capacity loss of the battery is used to characterize the degree of battery degradation at a corresponding number of cycles, the preset constant A is used to calibrate the basic loss level of the relative capacity loss model of the battery, and the activation energy Eα The gas constant R and activation energy E are used to reflect the effect of temperature on the decay rate. α The ambient temperature T and the power-law coefficient z together constitute the exponential term, and the power-law coefficient z is used to characterize the nonlinear relationship between capacity loss and the number of cycles. The initial nominal capacity E of the battery... I The capacity benchmark is used to represent the battery's initial capacity at full capacity. Depth of discharge (DoD) characterizes the percentage of energy released in a single cycle. Charge / discharge efficiency (α) characterizes energy conversion losses during charging and discharging. Grid carbon emission factor (EF) yx,i The values ​​used to characterize the indirect carbon emission level corresponding to a unit of input electrical energy can be determined based on the power source structure and regional statistical data. Specifically, the gas constant, activation energy, and power-law coefficient, among other constants, can be obtained by conducting charge-discharge aging tests on different batches of batteries and fitting the data.

[0215] In practical implementation, battery operating data on delivery vehicles, ambient temperature data, and cycle count variables can be input into the battery relative capacity loss model. Combined with pre-calibrated constants, activation energy, gas constant, and power-law coefficients, the relative capacity loss for each cycle can be calculated, and the total charging power consumption over the battery's entire lifespan can be calculated accordingly. Furthermore, the battery's initial nominal capacity, depth of discharge, charge / discharge efficiency, and total cycle count over the entire lifespan are substituted into the formula for calculating cumulative input energy to obtain the cumulative input energy consumed by the target battery over its entire lifespan. This cumulative input energy is then multiplied by the grid carbon emission factor to output the carbon emissions generated during the charging operation phase. These parameters can be collaboratively provided by the battery management system, charging record system, and environmental monitoring module. Model calculations can be performed by computing modules deployed in servers or edge computing units, which can utilize a combination of conventional processors and memory.

[0216] By adopting this calculation relationship, the cyclic decay characteristics of electric bicycles in delivery scenarios, the total charging power consumption throughout their entire life cycle, and the grid emission level can be linked. This allows carbon emissions during the usage phase to no longer rely on static average values ​​for estimation, but to be matched with actual cycle intensity and environmental conditions. This improves the accuracy and adaptability of the calculation results and enhances the comparability of carbon emissions for different vehicles, different operating conditions, and different regions.

[0217] Based on the aforementioned embodiments, the disposal stage further includes a vehicle dismantling stage and a recycling stage; the basic data includes the consumption of various types of energy in the vehicle dismantling stage and the recycling stage; the carbon emission factor includes the energy carbon emission factor; the calculation of the carbon emissions of the target at each stage includes: calculating the carbon emissions of the vehicle dismantling stage based on the consumption of various types of energy and the corresponding energy carbon emission factor in the vehicle dismantling stage; and calculating the carbon emissions of the recycling stage based on the consumption of various types of energy and the corresponding energy carbon emission factor in the recycling stage.

[0218] The "abandonment phase" defines the carbon accounting scope for electric bicycles after they are scrapped, and breaks down the post-scrap disposal process into a vehicle dismantling phase and a recycling phase to reflect the impact of dismantling and recycling on energy consumption, respectively. The vehicle dismantling phase refers to the operational steps involved in removing the outer shell, separating components, disassembling the battery, and dismantling metal parts of the scrapped vehicle. The recycling phase refers to the operational steps involved in classifying, compressing, transferring, regenerating, and harmlessly disposing of the dismantled materials. The energy carbon emission factor refers to the carbon emission coefficient corresponding to the unit consumption of energy sources such as electricity, diesel, and natural gas. Its value can be determined using industry databases, local power grid emission benchmarks, or approved statistical data. In practical applications, other sources can also be selected for this energy carbon emission factor; this application does not specifically limit this.

[0219] In practical implementation, energy consumption data for each work unit during the disposal phase can be collected first. This data can come from dismantling station electricity meters, recycling line energy consumption ledgers, fuel requisition records, or workshop energy consumption metering terminals. The collected electricity and fuel consumption data are then converted into units of measurement that match the energy carbon emission factor. Subsequently, the energy consumption of each type during the vehicle dismantling phase is multiplied by the corresponding energy carbon emission factor and summed to obtain the carbon emissions for the vehicle dismantling phase. Then, the energy consumption of each type during the recycling phase is multiplied by the corresponding energy carbon emission factor and summed to obtain the carbon emissions for the recycling phase. The results of these two sub-phases can be further summarized into the carbon emissions for the disposal phase, providing component data for total lifecycle accounting.

[0220] This approach enables independent measurement and separate accounting of energy consumption for different disposal activities, avoiding the ambiguity caused by mixing dismantling and recycling energy consumption in statistics. Since each type of energy is matched with its corresponding energy carbon emission factor for calculation, the consistency between carbon emission results at the disposal stage and actual operational conditions is improved, and the comparability between different batches of vehicles and different recycling processes is enhanced. This approach helps to form a complete carbon accounting chain at the disposal stage, providing a reliable data foundation for the full lifecycle carbon emission management of electric bicycles in delivery scenarios.

[0221] In one possible implementation, the formula for calculating carbon emissions during the vehicle dismantling phase is:

[0222]

[0223] Among them, C fq,cj E represents the carbon emissions during the vehicle dismantling phase. o,cj For the consumption of the oth energy source during the vehicle dismantling phase, EF cj,o Let be the energy carbon emission factor corresponding to the o-th energy source, and O be the total number of energy types in the vehicle dismantling stage;

[0224] The formula for calculating carbon emissions during the recycling and treatment phase is:

[0225]

[0226] Among them, C fq,cl E represents the carbon emissions during the recycling and treatment phase. q,cl EF represents the consumption of the qth type of energy during the recycling and processing phase. cl,q Let q be the carbon emission factor corresponding to the q-th energy source, and Q be the total number of energy types in the recycling and treatment stage.

[0227] Among them, C fq,cj The carbon emissions used to represent the vehicle dismantling stage are calculated by multiplying each type of energy consumption in that stage by its corresponding energy carbon emission factor and then summing the results; E o,cj This is used to indicate the consumption of the oth type of energy during the vehicle dismantling phase. Energy sources may include electricity, diesel, liquefied petroleum gas, or other energy types used in the dismantling operation; EF cj,o The energy carbon emission factor corresponding to the o-th energy source is used to characterize the carbon emission intensity corresponding to a unit of energy consumption; O represents the total number of energy types involved in the cumulative calculation during the vehicle dismantling stage. C fq,cl The carbon emissions used to represent the recycling and processing stage are calculated by multiplying each type of energy consumption in that stage by its corresponding energy carbon emission factor and then summing the results; E q,cl Used to represent the consumption of the q-th energy source in the recycling and processing stage; EF cl,q Q is used to represent the energy carbon emission factor corresponding to the q-th energy source; Q is used to represent the total number of energy types participating in the cumulative calculation during the recycling and processing stage.

[0228] In practical implementation, the whole vehicle dismantling stage corresponds to the dismantling process after the abandoned vehicle enters the dismantling station. Energy consumption data can be collected from energy-consuming units such as dismantling equipment, auxiliary lighting, ventilation devices, and handling machinery, and then converted into a unified metering standard to form E. o,cjEnergy carbon emission factors can be determined based on regional power grid emission benchmarks, lower heating value of fuels, and standard emission coefficients, and stored in a carbon emission factor database for later retrieval. The recycling and processing stage corresponds to the sorting, compression, packaging, cleaning, smelting pretreatment, and recyclable material transfer processes after dismantling. E can be calculated based on the electricity, fuel, and heat consumption of each process stage. q,cl and match the corresponding EF. cl,q For scenarios using variable frequency drives (VFDs) or intermittent operation equipment, the collected instantaneous power can be integrated over the operation duration to obtain the total consumption for that stage. For scenarios primarily relying on manual assistance, the electricity and fuel consumption related to the equipment can be calculated separately and then aggregated. The carbon emissions from the vehicle dismantling and recycling stages can be treated as outputs from different sub-stages of the waste disposal process, and then incorporated into the calculation of total life-cycle carbon emissions.

[0229] The above calculation method can independently account for carbon emissions from different energy-consuming stages during the waste disposal phase, and limits the accumulation range by the total number of energy types, thereby avoiding omissions or double counting. Since each stage uses a unified form of consumption multiplied by the corresponding energy carbon emission factor, it can maintain consistent data standards, improve the comparability and traceability of vehicle dismantling and recycling results, and thus improve the accuracy and applicability of carbon emission accounting during the vehicle waste disposal phase.

[0230] Based on the foregoing embodiments, the method further includes: obtaining the average daily number of charging cycles and the average daily number of delivery orders for the accounting target; calculating the average energy consumption per charging cycle based on the cumulative input energy and the total number of cycles throughout the battery's life cycle; calculating the energy consumption per delivery cycle based on the average energy consumption per charging cycle, the average daily number of charging cycles, and the average daily number of delivery orders; and calculating the carbon emissions generated per delivery cycle based on the energy consumption per delivery cycle and the grid carbon emission factor.

[0231] The carbon emissions generated per delivery are used to allocate the charging energy consumption of the target during use to a single delivery, reflecting the operational carbon burden corresponding to a single delivery order. The average daily charging frequency characterizes the frequency at which the target completes charging within a day, while the average daily delivery volume characterizes the number of delivery orders completed by the target within a day; these two together form the basis for allocating energy consumption between delivery operations and charging. The average energy consumed per charge represents the average input energy per charge, calculated by correlating the cumulative input energy with the total number of cycles throughout the battery's lifespan. The energy consumed per delivery represents the energy consumption allocated to a single delivery, calculated by correlating the average energy consumed per charge with the average daily charging frequency and the average daily delivery volume. The carbon emissions generated per delivery represent the carbon emissions from the charging process corresponding to a single delivery, obtained by multiplying the energy consumed per delivery by the grid carbon emission factor.

[0232] In practical implementation, the cumulative input energy during the operation phase can use the results from the usage phase. The total number of battery cycles throughout its lifespan can be obtained from battery management records, charging records, or maintenance files, both of which serve as inputs for calculating the average energy consumption per charge. After summarizing the charging records within the set statistical period, the average daily charging frequency is calculated, and combined with the order completion records generated in the delivery scheduling system, the average daily delivery volume is calculated. Then, based on the correspondence between charging and delivery, the average energy consumption per charge is allocated to the average daily delivery volume according to the average daily charging frequency, thus obtaining the energy consumed per delivery. Subsequently, the grid carbon emission factor is called, which can be determined from regional power structure data, publicly available emission inventories, or regulatory data, and multiplied with the energy consumed per delivery to output the carbon emissions generated per delivery. To ensure calculation consistency, the average daily charging frequency, daily delivery volume, and cumulative input energy can be limited to values ​​within the same statistical period.

[0233] Specifically, based on the cumulative input electrical energy and the total number of cycles throughout the battery's lifespan, the formula for calculating the average energy consumption per charge is as follows:

[0234]

[0235] Where E is the average energy consumed in a single charge.

[0236] The formula for calculating the energy consumption per delivery is as follows, based on the average energy consumption per charge, the average number of charges per day, and the average number of delivery orders per day:

[0237]

[0238] Where E1 is the energy consumed in a single delivery, a is the average number of charging times per day, and X1 is the average number of delivery orders per day.

[0239] This single-delivery carbon emission accounting converts the input electrical energy at the battery's entire lifecycle level into energy consumption allocation results at the delivery business level, and then combines this with the grid carbon emission factor to form carbon emission output at the order granularity, establishing a unified mapping relationship between charging energy consumption and delivery operations. This approach avoids the problem of simply relying on total vehicle energy consumption statistics failing to reflect the carbon emission intensity of a single delivery, and improves the interpretability and traceability of carbon emission results in delivery scenarios.

[0240] This implementation method allows for the precise allocation of charging energy consumption during the electric bicycle usage phase to a single delivery, resulting in carbon emission figures based on order volume. This improves the granularity and management accuracy of carbon emission accounting in the delivery industry. Because the calculation process incorporates average daily charging frequency, average daily delivery volume, total battery lifecycle cycles, and grid carbon emission factors, it takes into account both equipment usage characteristics and regional electricity emission characteristics. This makes the calculation results closer to actual operating conditions and provides a basis for delivery companies to conduct low-carbon scheduling, capacity optimization, and emission reduction assessments.

[0241] Based on the aforementioned embodiments, the calculation of the carbon emissions of the accounting target at each stage further includes: obtaining the number of times the battery is replaced throughout its entire life cycle, the carbon emissions of a single battery during the production stage, and the carbon emissions of a single battery during the disposal stage; and calculating the total carbon emissions generated by battery replacement based on the number of replacements, the carbon emissions of a single battery during the production stage, and the carbon emissions of a single battery during the disposal stage.

[0242] In this embodiment, the replacement count is used to characterize the cumulative number of batteries replaced due to capacity decay, malfunction, or maintenance during the entire life cycle of the electric bicycle. The carbon emissions during the production stage of a single battery represent the implicit carbon emissions generated during the raw material acquisition, manufacturing, assembly, and transportation of a single battery. The carbon emissions during the disposal stage of a single battery represent the carbon emissions generated during the dismantling, recycling, disposal, and resource regeneration of a single battery after its retirement. The above data can be obtained by associating and matching vehicle files, spare parts requisition records, scrapping and recycling records, and battery ledgers, and uniformly converted into emission values ​​expressed in carbon dioxide equivalent.

[0243] In practical implementation, a replacement association can be established based on battery serial numbers. Battery records for the same accounting target replaced at different times are aggregated into a replacement sequence. The carbon emissions from each battery replacement are then summed based on the carbon emissions from the production and disposal phases of the individual battery, resulting in the total carbon emissions generated by battery replacement. If the accounting target undergoes multiple battery replacements throughout its lifecycle, the carbon emissions from the production and disposal phases of the individual battery for each replacement can be separately included, and then accumulated based on the number of replacements. This avoids underestimating the emissions based on only one replacement. This calculation result can serve as a supplementary emission item beyond the usage phase, and together with the emission results from the production, usage, and disposal phases, constitutes the total lifecycle carbon emissions of the accounting target.

[0244] By adopting the above method, the implicit carbon emissions introduced by battery replacement and the carbon emissions from disposal can be included in a unified accounting caliber, avoiding the underestimation of the true carbon emission level of electric bicycles due to ignoring the battery replacement process. At the same time, it enhances the comparability and traceability of accounting results under different vehicle, different operating intensities and different battery life conditions, thus providing a more accurate basis for delivery companies to carry out battery selection, operation and maintenance management and low-carbon assessment.

[0245] Based on the aforementioned embodiments, further, multiple carbon emission factors corresponding to the carbon source inventory are obtained, including: determining the operating area of ​​the electric bicycle; and using the average or real-time carbon emission factor of the power grid corresponding to the operating area during the accounting period as the power grid carbon emission factor.

[0246] In this embodiment, the operating area is used to characterize the geographical range in which electric bicycles actually carry out delivery operations. It is typically determined by a combination of factors, including the station affiliation information bound to the vehicle, the order dispatch area, trajectory positioning information, or management backend registration information, and mapped to the corresponding power grid area. The power grid carbon emission factor characterizes the power supply carbon intensity of the power grid within the accounting period and serves as a basic parameter for converting charging electricity consumption into carbon emissions during the usage phase. The average carbon emission factor can be obtained from periodic statistics published by the power authority, industry databases, or regional power grids, reflecting the overall average power supply level within the accounting period. The real-time carbon emission factor can be calculated in real-time from grid-side load, generation structure, and marginal emission information, characterizing the instantaneous power supply carbon intensity at different points in time. In practical applications, the power grid carbon emission factor can be updated uniformly on a daily, monthly, or accounting cycle basis, or it can correspond one-to-one with the charging time to improve the spatiotemporal matching accuracy of the accounting during the usage phase. In this embodiment, the power grid carbon emission factor acquisition module can use the operating area identification result as input, automatically retrieve the corresponding power grid carbon emission factor, and output it to the carbon accounting model.

[0247] The working principle of this method is to first identify the grid boundary where the electric bicycle is located by defining the operating area, and then select the calculation basis from the average carbon emission factor or real-time carbon emission factor corresponding to that grid during the accounting period, so that the carbon emission calculation during the usage phase is consistent with the actual operating area of ​​the vehicle. Since the energy structure, clean power ratio, and load fluctuations of different regional grids vary, using regional grid carbon emission factors can avoid the deviation caused by uniform values ​​and make the calculation results closer to the actual operating status of the delivery business.

[0248] By adopting this implementation method, the regional adaptability and temporal precision of carbon emission accounting during the use of electric bicycles can be improved, and errors caused by cross-regional operation, differences in different power grid structures, and the use of fixed average values ​​can be reduced. This ensures that the power grid carbon emission factor corresponding to the carbon source inventory is consistent with the actual charging environment, thereby improving the accuracy of the carbon emission results throughout the entire life cycle.

[0249] This application uses electric bicycles used in the delivery process as the accounting target. First, the accounting boundary is defined as the entire lifecycle of the electric bicycle, including the production stage, the usage stage, and the disposal stage. Then, basic data on resource and energy consumption related to carbon emissions are collected around this boundary, and a carbon source inventory is established accordingly. The production stage is further subdivided into raw material mining, raw material processing, component manufacturing, and vehicle assembly stages. The basic data includes the mining volume of various raw materials in the raw material mining stage, as well as the energy consumption of various types of energy in the raw material processing, component manufacturing, and vehicle assembly stages. The disposal stage is subdivided into vehicle dismantling and recycling stages, with basic data including the energy consumption of various types of energy in both stages. The usage stage's basic data includes the total number of battery cycles throughout its lifecycle, which, combined with battery operation data, forms the carbon source inventory for the usage stage.

[0250] In one possible implementation, multiple carbon emission factors are obtained from the carbon source inventory, including implicit carbon emission factors, energy carbon emission factors, and grid carbon emission factors. For determining the grid carbon emission factor, the operating area of ​​the electric bicycles is first determined, and then the average or real-time carbon emission factor of the corresponding grid during the accounting period is used as the grid carbon emission factor. For the accounting of the production stage, the carbon emissions C during the raw material mining stage are calculated based on the mining volume of various raw materials and their corresponding implicit carbon emission factors. sc,kc The calculation formula is the mining volume of various raw materials in m. i,kc With the corresponding implicit carbon emission factor EF cl,i The summation of the products, where i takes values ​​ranging from the total number of raw material types I; based on the energy consumption E of each type during the raw material processing stage. j,jg and the corresponding energy carbon emission factor EF yx,j Calculate carbon emissions C during the raw material processing stage sc,jg The value of j ranges from the total number of energy types J in that stage; based on the energy consumption E of each type in the component manufacturing stage. k,lj and the corresponding energy carbon emission factor EF yx,k Calculate carbon emissions C during the component manufacturing stage sc,lj The value of k ranges from the total number of energy types K in this stage; based on the energy consumption E of each type in the vehicle assembly stage. l,zc and the corresponding energy carbon emission factor EF yx,lCalculate the carbon emissions C during the vehicle assembly stage sc,zc The value of l is L, which is the total number of energy types in this stage.

[0251] For the usage phase, first obtain the battery's relative capacity loss model, and then calculate the battery's relative capacity loss in each cycle according to the number of cycles. The battery's relative capacity loss in the nth cycle is calculated based on a preset constant A and activation energy E. α The calculations are performed using the gas constant R, ambient temperature T, power-law coefficient z, and cycle number variable n. The calculations are based on the relative capacity loss in each cycle, combined with the total number of cycles N over the battery's lifespan and the battery's initial nominal capacity E. I Using the battery depth of discharge (DoD) and battery charge / discharge efficiency (α), calculate the cumulative electrical energy input (E) of the electric bicycle over its entire lifespan. In Then the accumulated input electrical energy E In With the power grid carbon emission factor EF yx,i Multiplying these together yields the carbon emissions C generated during the charging operation phase. sy,yx If the delivery business is analyzed in more detail, the average number of daily charging times and the average number of daily delivery orders for electric bicycles can be obtained. The average energy consumption per charge can be calculated based on the cumulative input energy and the total number of cycles throughout the battery's life cycle. Then, the energy consumption per delivery can be calculated based on the average energy consumption per charge, the average number of daily charging times, and the average number of daily delivery orders. Finally, this energy consumption is multiplied by the grid carbon emission factor to obtain the carbon emissions generated per delivery.

[0252] When batteries require replacement, the total number of replacements throughout the battery's lifecycle, the carbon emissions during the production phase of a single battery, and the carbon emissions during the disposal phase of a single battery can also be obtained. The total carbon emissions generated by battery replacement are calculated based on the number of replacements and the aforementioned two types of single-battery carbon emissions, and then incorporated into the corresponding lifecycle accounting results. For the disposal phase, the carbon emissions are calculated based on the various energy consumption amounts E during the vehicle dismantling phase. o,cj and the corresponding energy carbon emission factor EF cj,o Calculate the carbon emissions C during the vehicle dismantling phase fq,cj The value of o ranges from the total number of energy types O during the vehicle dismantling stage; to the energy consumption E of each type during the recycling and processing stage. q,cl and the corresponding energy carbon emission factor EF cl,q Calculate carbon emissions (Cf) during the recycling and treatment phase. q,cl The value of q is the total number of energy types Q in the recycling and processing stage. After calculating the carbon emissions of each sub-stage of the production stage, usage stage, and disposal stage, the carbon emissions of the raw material mining stage, raw material processing stage, component manufacturing stage, vehicle assembly stage, usage stage charging operation, battery replacement-related emissions, vehicle dismantling stage, and recycling and processing stage can be summarized to obtain the total carbon emissions of the electric bicycle within the boundary range.

[0253] This application embodiment can divide an electronic device or main control device into functional modules according to the above method examples. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software functional module. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division; in actual implementation, there may be other division methods.

[0254] Figure 2 This is a schematic diagram of a carbon emission accounting device provided in an embodiment of this application. Figure 2 As shown, the device includes: a determination module 210, an acquisition module 220, an organization module 230, a calculation module 240, and a summary module 250.

[0255] The determination module 210 is used to determine the accounting target and boundary range. The accounting target is the electric bicycles used in the delivery process, and the boundary range is determined according to the entire life cycle of the electric bicycles, which includes the production stage, the usage stage and the disposal stage.

[0256] The acquisition module 220 is used to acquire basic data on resource consumption and / or energy consumption associated with carbon emissions within the boundary range of the accounting target;

[0257] The sorting module 230 is used to determine the carbon source inventory of the accounting target at each stage of the entire life cycle based on the basic data;

[0258] The calculation module 240 is used to obtain multiple carbon emission factors corresponding to the carbon source inventory, and calculate the carbon emissions of the accounting target at each stage based on the basic data and multiple carbon emission factors.

[0259] The summary module 250 is used to obtain the total carbon emissions of the accounting target within the boundary range based on the carbon emissions of the accounting target at each stage.

[0260] In one possible implementation, the production phase includes a raw material mining phase, a raw material processing phase, a component manufacturing phase, and a vehicle assembly phase.

[0261] The basic data includes the amount of various raw materials mined during the raw material mining stage, as well as the amount of various energy consumed during the raw material processing stage, the parts manufacturing stage, and the vehicle assembly stage.

[0262] Carbon emission factors include implicit carbon emission factors and energy carbon emission factors;

[0263] Calculation module 240 is specifically used for:

[0264] Calculate the carbon emissions during the raw material extraction stage based on the amount of raw materials mined and the corresponding implicit carbon emission factors.

[0265] Based on the consumption of various types of energy and the corresponding energy carbon emission factors in the raw material processing stage, the component manufacturing stage, and the vehicle assembly stage, the carbon emissions of the raw material processing stage, the component manufacturing stage, and the vehicle assembly stage are calculated respectively.

[0266] In one possible implementation, the calculation module 240 calculates the carbon emissions during the raw material extraction stage using the following formula, based on the amount of raw materials extracted and the corresponding implicit carbon emission factor:

[0267]

[0268] Among them, C sc,kc For carbon emissions during the raw material extraction stage, m i,kc Let EF be the amount of raw material i mined. cl,i Let I be the implicit carbon emission factor corresponding to the i-th raw material, and I be the total number of raw material types.

[0269] The formula for calculating carbon emissions during the raw material processing stage is:

[0270]

[0271] Among them, C sc,jg E represents carbon emissions during the raw material processing stage. j,jg Let EF be the consumption of the j-th energy source in the raw material processing stage. yx,j Let J be the energy carbon emission factor corresponding to the j-th energy source, and J be the total number of energy types in the raw material processing stage.

[0272] The formula for calculating carbon emissions during the component manufacturing stage is as follows:

[0273]

[0274] Among them, C sc,lj For carbon emissions during the component manufacturing stage, E k,lj Let EF be the consumption of the k-th energy source during the component manufacturing stage. yx,k Let K be the energy carbon emission factor corresponding to the kth energy source, and K be the total number of energy types in the component manufacturing stage;

[0275] The formula for calculating carbon emissions during the vehicle assembly stage is as follows:

[0276]

[0277] Among them, C sc,zc E represents carbon emissions during the vehicle assembly phase. l,zcFor the consumption of the first type of energy during the vehicle assembly stage, EF yx,l Let L be the energy carbon emission factor corresponding to the l-th energy source, and L be the total number of energy types in the vehicle assembly stage.

[0278] In one possible implementation, the basic data includes the total number of cycles throughout the battery's lifespan;

[0279] Carbon emission factors include grid carbon emission factors;

[0280] Calculation module 240 is also used for:

[0281] Obtain the battery relative capacity loss model, and calculate the battery relative capacity loss in each cycle based on the battery relative capacity loss model;

[0282] Based on the relative capacity loss in each cycle, calculate the cumulative input electrical energy of the accounting target throughout its entire life cycle.

[0283] The carbon emissions generated by the target during the charging operation phase are calculated based on the cumulative input electrical energy and the grid carbon emission factor.

[0284] In one possible implementation, the calculation module 240 calculates the relative capacity loss of the battery in each cycle according to the battery relative capacity loss model using the following formula:

[0285]

[0286] in, Let A be the relative capacity loss of the battery during the nth cycle, and E be a preset constant. α The activation energy is R, the gas constant is T, the ambient temperature is z, the power law coefficient is n, and the cycle number is n.

[0287] Based on the relative capacity loss of the battery and the total number of cycles throughout the battery's lifespan, the formula for calculating the cumulative input electrical energy of the target over its entire lifespan is as follows:

[0288]

[0289] Among them, E In To calculate the cumulative electrical energy input of the target over its entire lifespan, N represents the total number of cycles in the battery's lifespan, and E... I Where α is the initial nominal capacity of the battery, DoD is the depth of discharge of the battery, and α is the charge / discharge efficiency of the battery.

[0290] Based on the cumulative input electrical energy and the grid carbon emission factor, the formula for calculating the carbon emissions generated by the charging operation during the usage phase of the accounting target is as follows:

[0291]

[0292] Among them, C sy,yx For the carbon emissions generated during the charging operation phase, EF yx,i This is a carbon emission factor for the power grid.

[0293] In one possible implementation, the disposal phase includes a vehicle dismantling phase and a recycling phase;

[0294] The basic data includes the consumption of various types of energy during the vehicle dismantling and recycling stages;

[0295] Carbon emission factors include energy carbon emission factors;

[0296] Calculation module 240 is also used for:

[0297] The carbon emissions during the vehicle dismantling phase are calculated based on the consumption of various types of energy and the corresponding energy carbon emission factors.

[0298] The carbon emissions during the recycling and treatment phase are calculated based on the consumption of various energy sources and their corresponding carbon emission factors.

[0299] In one possible implementation, the formula for calculating carbon emissions during the vehicle dismantling phase in the calculation module 240 is as follows:

[0300]

[0301] Among them, C fq,cj E represents the carbon emissions during the vehicle dismantling phase. o,cj For the consumption of the oth energy source during the vehicle dismantling phase, EF cj,o Let be the energy carbon emission factor corresponding to the o-th energy source, and O be the total number of energy types in the vehicle dismantling stage;

[0302] The formula for calculating carbon emissions during the recycling and treatment phase is:

[0303]

[0304] Among them, C fq,cl E represents the carbon emissions during the recycling and treatment phase. q,cl EF represents the consumption of the qth type of energy during the recycling and processing phase. cl,q Let q be the carbon emission factor corresponding to the q-th energy source, and Q be the total number of energy types in the recycling and treatment stage.

[0305] In one possible implementation, the computing module 240 is further configured to:

[0306] Obtain the average daily number of charging sessions and the average daily number of delivery orders for the accounting target;

[0307] The average energy consumed per charge is calculated based on the cumulative input electrical energy and the total number of cycles throughout the battery's lifespan.

[0308] The energy consumed per delivery is calculated based on the average energy consumption per charge, the average number of charges per day, and the average number of delivery orders per day.

[0309] The carbon emissions generated by a single delivery are calculated based on the electrical energy consumed in a single delivery and the grid carbon emission factor.

[0310] In one possible implementation, the computing module 240 is further configured to:

[0311] Obtain the number of battery replacements throughout its entire lifecycle, the carbon emissions during the production phase of a single battery, and the carbon emissions during the disposal phase of a single battery.

[0312] The total carbon emissions generated by battery replacement are calculated based on the number of replacements, the carbon emissions during the production stage of a single battery, and the carbon emissions during the disposal stage of a single battery.

[0313] In one possible implementation, the computing module 240 is further configured to:

[0314] Determine the operating area for electric bicycles;

[0315] The average or real-time carbon emission factor of the power grid corresponding to the operating area during the accounting period is used as the power grid carbon emission factor.

[0316] The carbon emission accounting device provided in this embodiment can execute a carbon emission accounting method of the above embodiment. Its implementation principle and technical effect are similar, and will not be described again in this embodiment.

[0317] In a specific implementation of the aforementioned carbon emission accounting device, each module can be implemented as a processor. The processor can execute computer execution instructions stored in the memory, thereby enabling the processor to execute the aforementioned carbon emission accounting method.

[0318] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 3 As shown, the electronic device includes at least one processor 310 and a memory 320. The electronic device also includes a communication component 330. The processor 310, memory 320, and communication component 330 are connected via a bus 340.

[0319] In the specific implementation process, at least one processor 310 executes computer execution instructions stored in memory 320, causing at least one processor 310 to execute a carbon emission accounting method as executed on the electronic device side as described above.

[0320] The specific implementation process of processor 310 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0321] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0322] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage.

[0323] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0324] The above description of the functions implemented by electronic devices and main control devices has introduced the solutions provided by the embodiments of the present invention. It is understood that, in order to implement the above functions, the electronic device or main control device includes hardware structures and / or software modules corresponding to the execution of each function. By combining the units and algorithm steps of the various examples described in the embodiments of the present invention, the embodiments of the present invention can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the technical solutions of the embodiments of the present invention.

[0325] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the carbon emission accounting method described above.

[0326] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0327] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in an electronic device or a host device.

[0328] This application also provides a computer program product, which includes a computer program stored in a readable storage medium. At least one processor of an electronic device can read the computer program from the readable storage medium, and the at least one processor executes the computer program to cause the electronic device to perform the solution provided in the above embodiments.

[0329] This application also provides a chip, which includes at least one processor for executing program instructions to perform the scheme provided in the above embodiments. A carbon emission accounting method can be applied to terminal devices, chips in terminal devices, or chip modules.

[0330] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disk, or optical disk.

[0331] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it is readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. The above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A carbon emission accounting method, characterized in that, include: The accounting target and boundary range are determined. The accounting target is the electric bicycle used in the delivery process, and the boundary range is determined according to the entire life cycle of the electric bicycle, which includes the production stage, the usage stage, and the disposal stage. Obtain basic data on resource consumption and / or energy consumption associated with carbon emissions within the boundary range of the accounting target; Based on the aforementioned basic data, determine the carbon source inventory for the accounting target at each stage of the entire life cycle; Obtain multiple carbon emission factors corresponding to the carbon source inventory, and calculate the carbon emissions of the accounting target at each stage based on the basic data and the multiple carbon emission factors; Based on the carbon emissions of the accounting target at each stage, the total carbon emissions of the accounting target within the boundary range are obtained.

2. The method according to claim 1, characterized in that, The production stages include the raw material mining stage, the raw material processing stage, the parts manufacturing stage, and the vehicle assembly stage. The basic data includes the amount of various raw materials mined in the raw material mining stage, as well as the amount of various energy consumed in the raw material processing stage, the parts manufacturing stage, and the vehicle assembly stage. The carbon emission factors include implicit carbon emission factors and energy carbon emission factors; The calculation of the carbon emissions of the accounting target at each stage includes: Calculate the carbon emissions during the raw material extraction stage based on the extraction volume of the raw materials and the corresponding implicit carbon emission factors. Based on the consumption of various types of energy and the corresponding energy carbon emission factors in the raw material processing stage, the component manufacturing stage, and the vehicle assembly stage, the carbon emissions of the raw material processing stage, the component manufacturing stage, and the vehicle assembly stage are calculated respectively.

3. The method according to claim 2, characterized in that, The formula for calculating the carbon emissions during the raw material mining stage, based on the amount of raw material mined and the corresponding implicit carbon emission factor, is as follows: Wherein, the C sc,kc The carbon emissions during the raw material extraction stage, m i,kc For the amount of the i-th raw material mined, the EF cl,i Let I be the implicit carbon emission factor corresponding to the i-th raw material, where I is the total number of raw material types. The formula for calculating carbon emissions during the raw material processing stage is as follows: Wherein, the C sc,jg The carbon emissions during the raw material processing stage, E j,jg Let EF be the consumption of the j-th energy source in the raw material processing stage. yx,j Let J be the energy carbon emission factor corresponding to the j-th energy source, where J is the total number of energy types in the raw material processing stage; The formula for calculating carbon emissions during the component manufacturing stage is as follows: Wherein, the C sc,lj The carbon emissions during the manufacturing stage of the aforementioned components, the E k,lj Let EF be the consumption of the k-th energy source during the component manufacturing stage. yx,k Let K be the energy carbon emission factor corresponding to the kth energy source, where K is the total number of energy types in the component manufacturing stage; The formula for calculating carbon emissions during the vehicle assembly stage is as follows: Wherein, the C sc,zc The carbon emissions during the vehicle assembly stage, E l,zc The EF represents the consumption of the first type of energy during the vehicle assembly stage. yx,l Let L be the energy carbon emission factor corresponding to the l-th energy source, where L is the total number of energy types in the vehicle assembly stage.

4. The method according to claim 1, characterized in that, The basic data includes the total number of cycles throughout the battery's entire lifespan; The carbon emission factor includes the power grid carbon emission factor; The calculation of the carbon emissions of the accounting target at each stage includes: Obtain the battery relative capacity loss model, and calculate the battery relative capacity loss in each cycle based on the battery relative capacity loss model; Based on the relative capacity loss in each cycle, calculate the cumulative input electrical energy of the accounting target over its entire life cycle. Based on the cumulative input electrical energy and the grid carbon emission factor, the carbon emissions generated by the accounting target during the charging operation in the usage phase are calculated.

5. The method according to claim 4, characterized in that, The formula for calculating the relative capacity loss of the battery in each cycle, based on the battery relative capacity loss model, is as follows: Among them, the The relative capacity loss of the battery during the nth cycle is given by A, which is a preset constant, and E is the relative capacity loss of the battery during the nth cycle. α The activation energy is defined as R, which is a gas constant, T, which is an ambient temperature, z, which is a power-law coefficient, and n, which is a variable representing the number of cycles. The formula for calculating the cumulative input electrical energy of the target over its entire life cycle, based on the relative capacity loss of the battery and the total number of cycles throughout the battery's life cycle, is as follows: Wherein, E In The cumulative electrical energy input to the target over its entire lifespan is N, where N is the total number of cycles in the battery's entire lifespan, and E is... I The initial nominal capacity of the battery is denoted by DoD, the depth of discharge of the battery is denoted by α, and the charge / discharge efficiency of the battery is denoted by α. The formula for calculating the carbon emissions generated by the target during the charging operation in the usage phase, based on the cumulative input electrical energy and the grid carbon emission factor, is as follows: Wherein, the C sy,yx The carbon emissions generated during the charging operation of the aforementioned usage phase, the EF yx,i The carbon emission factor of the power grid is denoted as .

6. The method according to claim 1, characterized in that, The disposal phase includes the vehicle dismantling phase and the recycling phase; The basic data includes the consumption of various types of energy during the vehicle dismantling and recycling stages; The carbon emission factors include energy carbon emission factors; The calculation of the carbon emissions of the accounting target at each stage includes: The carbon emissions during the vehicle dismantling phase are calculated based on the consumption of various types of energy and the corresponding energy carbon emission factors. The carbon emissions of the recycling process are calculated based on the consumption of various types of energy and their corresponding carbon emission factors during the recycling process.

7. The method according to claim 6, characterized in that, The formula for calculating carbon emissions during the vehicle dismantling phase is as follows: Wherein, the C fq,cj The E represents the carbon emissions during the vehicle dismantling phase. o,cj The EF represents the consumption of the oth type of energy during the vehicle dismantling phase. cj,o The energy carbon emission factor corresponding to the o-th energy source is denoted as , where O represents the total number of energy types during the vehicle dismantling phase. The formula for calculating the carbon emissions during the recycling and treatment stage is as follows: Wherein, the C fq,cl For the carbon emissions during the recycling and treatment phase, the E q,cl For the consumption of the qth type of energy in the recycling and processing stage, the EF cl,q Let Q be the energy carbon emission factor corresponding to the qth energy source, where Q is the total number of energy types in the recycling and processing stage.

8. The method according to claim 4 or 5, characterized in that, The method further includes; Obtain the average daily number of charging sessions and the average daily number of delivery orders for the target calculation. Based on the cumulative input electrical energy and the total number of cycles throughout the battery's lifespan, calculate the average electrical energy consumed per charge. The energy consumed per delivery is calculated based on the average energy consumption per charge, the average number of charges per day, and the average number of delivery orders per day. The carbon emissions generated by a single delivery are calculated based on the electrical energy consumed in the single delivery and the carbon emission factor of the power grid.

9. The method according to claim 4, characterized in that, The calculation of the carbon emissions of the accounting target at each stage also includes: Obtain the number of battery replacements during the entire life cycle, the carbon emissions during the production phase of a single battery, and the carbon emissions during the disposal phase of a single battery. The total carbon emissions generated by battery replacement are calculated based on the number of replacements, the carbon emissions during the production phase of a single battery, and the carbon emissions during the disposal phase of a single battery.

10. The method according to claim 4, characterized in that, The acquisition of multiple carbon emission factors corresponding to the carbon source inventory includes: Determine the operating area of ​​the electric bicycle; The average or real-time carbon emission factor of the power grid corresponding to the operating area during the accounting period is used as the power grid carbon emission factor.

Images