Carbon footprint accounting method, system, device and medium based on optimal allocation mode

Abstract

This invention provides a carbon footprint accounting method, system, device, and medium based on optimal allocation, including: acquiring accounting data and a historical score matrix, and determining a factor score set based on the accounting data; acquiring a weight matrix corresponding to all allocation methods, adaptively optimizing the weight matrix based on the accounting data to obtain an optimized weight matrix, and then calculating a comprehensive practicality score corresponding to each allocation method based on the optimized weight matrix and the factor score set; calculating a selection threshold based on the historical score matrix, allocating the accounting data using allocation methods with a comprehensive practicality score greater than the selection threshold, and performing vehicle carbon footprint accounting based on the allocation results. This invention solves the problem in the prior art where it is difficult to determine the most suitable data allocation method to be used in the carbon footprint accounting process, resulting in an inaccurate final carbon footprint accounting structure.

Description

Technical Field

[0001] This invention relates to the field of carbon emission measurement technology in the automotive industry, and in particular to carbon footprint accounting methods, systems, equipment and media based on optimal allocation methods. Background Technology

[0002] Automobile products consist of tens of thousands of parts, involving various materials such as steel, aluminum, plastics, rubber, glass, and electronic components. The manufacturing process includes stamping, welding, painting, final assembly, injection molding, die casting, and machining. Many of these processes are multi-output processes, meaning that waste or by-products are generated while producing the main product. According to carbon footprint accounting rule manuals such as GBT24067, ISO14067, and Catena-X, the total environmental load must be reasonably allocated among these outputs.

[0003] However, due to the reliance on qualitative judgment in the selection of data allocation methods during the allocation process, different accountants may reach different conclusions. In addition, the entire process involves multiple supply chain levels, and the confidence level of the data provided by suppliers in each supply chain is different. This makes it difficult to determine the most suitable data allocation method to be used in the carbon footprint accounting process, resulting in inaccurate final carbon footprint accounting results. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a carbon footprint accounting method based on optimal allocation, which solves the problem in existing technologies where it is difficult to determine the most suitable data allocation method to be used in the carbon footprint accounting process, resulting in an inaccurate final carbon footprint accounting structure.

[0005] According to an embodiment of the present invention, a carbon footprint accounting method based on optimal allocation includes: Obtain the accounting data and historical score matrix, and determine the factor score set based on the accounting data; Obtain the weight matrix corresponding to all allocation methods, adaptively optimize the weight matrix based on the accounting data to obtain the optimized weight matrix, and then calculate the comprehensive practical score corresponding to each allocation method based on the optimized weight matrix and the factor scoring set; The selection threshold is calculated based on the historical score matrix. The accounting data is allocated using the allocation method where the comprehensive practicality score is greater than the selection threshold. The vehicle carbon footprint is then calculated based on the allocation results.

[0006] Preferably, the factor scoring set includes an industry guideline fit score, a process segmentation feasibility score, a dominant substitute identification score, an economic value ratio rationality score, and a data quality and availability score.

[0007] Preferably, the calculation method for the dominant substitute identification score is as follows: Market share, technology maturity, emissions stability, and price fluctuation sequences are determined based on accounting data; The price volatility index is calculated based on the price volatility sequence, and then market share, technological maturity, and emission stability are weighted to obtain the dominant alternative identification score.

[0008] Preferably, the formula for calculating the economic value ratio rationality score is as follows: in, The regional adjusted economic value ratio, R is the measured ratio of main product price to by-product price; This serves as a reference value for the industry's optimal economic value ratio. / Regional consumer price index correction coefficient.

[0009] Preferably, the method for adaptively optimizing the weight matrix based on the calculated data to obtain the optimized weight matrix includes: A quality assessment function is constructed based on the accounting data. Then, based on the quality assessment function, the weight matrix is ​​adjusted using the gradient descent method to obtain a new weight matrix. Repeat the above steps until the weight matrix no longer changes, and use the weight matrix obtained from the last repetition as the optimized weight matrix.

[0010] Preferably, the formula for calculating the selection threshold is as follows: in, , These represent the standard deviation and mean of the comprehensive practicality score for the previous N carbon footprint calculations. The fluctuation sensitivity coefficient The threshold value used in the previous carbon footprint calculation.

[0011] On the other hand, according to embodiments of the present invention, a carbon footprint accounting system based on an optimal allocation method is also provided. This system uses the aforementioned carbon footprint accounting method based on an optimal allocation method, and includes: The data acquisition module is used to acquire accounting data, historical score matrix and weight matrix corresponding to all allocation methods, and determine factor score set based on accounting data; A weight optimization module is used to adaptively optimize the weight matrix based on the calculated data to obtain an optimized weight matrix. The allocation selection module is used to calculate the selection threshold based on the historical score matrix, and then calculate the comprehensive practical score corresponding to each allocation method based on the optimized weight matrix and the factor score set. The carbon footprint accounting module is used to allocate accounting data using the allocation method with the highest comprehensive practicality score, and to perform vehicle carbon footprint accounting based on the allocation results.

[0012] On the other hand, according to an embodiment of the present invention, a computer is also provided, including at least one processor and a memory, the memory storing a computer program configured to be executed by the processor to implement the above-described carbon footprint accounting method based on optimal allocation.

[0013] On the other hand, according to embodiments of the present invention, a storage medium is also provided, which is a computer-readable storage medium storing a computer program that can be executed by one or more processors to implement the above-described carbon footprint accounting method based on optimal allocation.

[0014] Compared with the prior art, the present invention has the following beneficial effects: This invention determines the factor score set of the data based on the accounting data, and then adaptively optimizes the preset weight matrix corresponding to all allocation methods to process accounting data of different scales and confidence levels, so as to normalize them to the same dimension. At the same time, it combines historical scores that reflect historical situations to make a comprehensive judgment on the practicality of all allocation methods, improves the sensitivity to recent data, and then allocates the accounting data according to the allocation method with the highest comprehensive practicality score, and performs vehicle carbon footprint accounting based on the allocation results. Attached Figure Description

[0015] Figure 1 This is a diagram illustrating the carbon footprint calculation method based on the optimal allocation method according to an embodiment of the present invention. Detailed Implementation

[0016] The technical solutions of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0017] like Figure 1 As shown, this embodiment of the invention proposes a carbon footprint accounting method based on optimal allocation, including: Obtain the accounting data and historical score matrix, and determine the factor score set based on the accounting data; After obtaining the accounting data for automotive products, it is now determined whether the process is a multi-output process, i.e., a situation where two or more main products (or by-products) are generated simultaneously in the automotive product production system. If not, carbon footprint accounting begins directly without needing to allocate the accounting data using an allocation method. If so, a set of factor scores is determined based on the accounting data, including industry guideline fit score, process segmentation feasibility score, dominant substitute identification score, economic value ratio rationality score, and data quality and availability score, as shown in Table 1: Table 1: The calculation methods for the above five scoring methods are as follows: (1) Industry guideline compatibility score (including international mutual recognition index) in, The matching degree between the guideline and the product (0-1) is calculated based on the text similarity between the product category and the scope of application of the PCR. To ensure the timeliness of the guidelines (0-1), the publication / update date is normalized; Authoritativeness of the issuing organization (0-1): OEM > Industry Association > Research Institution > Company-defined; The international mutual recognition index (0-1) is 1.0 for those that have been formally adopted, 0.6-0.8 for those that have only been cited but not formally adopted, and 0 for those that have not been included. All are weighting coefficients, satisfying sun( )=1, and In scenarios where mandatory standards or rules require a value of not less than 0.3.

[0018] (2) Feasibility assessment of process breakdown in: For technical feasibility (0-1), the possibility of independent production line / station measurement is usually ≤0.2 when multiple products are co-produced in stamping, injection molding, and die casting. For data availability (0-1), existing metering instruments and sensor coverage, if workstation-level electricity meters have been installed, then It is 0.6-0.8; The cost-benefit ratio (0-1) is calculated by breaking down the ratio of retrofit costs to expected carbon emission reduction benefits and normalizing it using the threshold method. All are weight coefficients, satisfying sum( =1.

[0019] (3) Dominant substitute identification score (including price volatility index) Among them, MS represents market share (0-1), the proportion of scrap steel → electric arc furnace steel and the proportion of scrap aluminum → recycled aluminum, based on regional statistical data; TRL represents technology maturity (0-1), with TRL1-9 mapped to 0-1; Emission stability (0-1), 1 (coefficient of variation / 2).

[0020] This is a price volatility index that reflects the degree of price fluctuation between substitutes and the original good. It also determines the price volatility series over the past three years based on accounting data. The calculation formula is as follows: Where R= For price ratio, Let be the standard deviation of all prices in the price fluctuation series. The mean; All are weight coefficients, satisfying sum( =1.

[0021] (4) Rationality score of economic value ratio (including regional difference correction) in: The regional adjusted economic value ratio, R is the measured ratio of main product price to by-product price; The optimal economic value ratio for the industry is determined by taking the top 20% percentile from historical data. / This is the adjustment factor for the regional consumer price index, with Chinese data relative to European and American benchmarks.

[0022] (5) Data quality and availability score (including supply chain level weight) in, For the data quality index (0-1), the actual measurement > industry average > database > estimated. For data availability (0-1), API real-time reporting > periodic reporting > manual entry; Data validation rate (0-1): Third-party verification > Internal audit > Unverified; The weights for each supply chain level are as follows: 1.0 for the first level, 0.8 for the second level, 0.6 for the third level, and 0.4 for levels below the third level. All are weighting coefficients.

[0023] In addition, when there are multiple levels of supplier data for the same material, a confidence-weighted average is used, with the weights proportional to F5. The calculation formula is as follows: in, Let k be the emission factor of the kth data source. This represents the purchase quantity of materials corresponding to this source. The confidence coefficient and = Then the final As a score for data quality and availability.

[0024] Obtain the weight matrix corresponding to all allocation methods, adaptively optimize the weight matrix based on the accounting data to obtain the optimized weight matrix, and then calculate the comprehensive practical score corresponding to each allocation method based on the optimized weight matrix and the factor scoring set; The following five allocation methods are mainly applicable in the automotive field: The formula for calculating the overall suitability score of allocation method j is as follows: in, The weight coefficient of factor i on method j; : The normalization function of factor i score, , The baseline compliance score (0-1) for allocation method j is the degree of matching of authoritative standards or rules such as GBT24067, ISO14067, and Catena-X. The expected emission reduction incentive effect of allocation method j is scored (0-1) based on the potential promotion of the procurement of recycled materials by this method. Assign historical performance scores (0-1) to method j based on satisfaction feedback on the application of this method in the case library; , , Weighting coefficient.

[0025] In addition, in the initial state, , , , , , , These parameters need to be preset by the company based on its own production conditions. , , The value itself is set according to the national standard, so there is no error. The value is set manually and will inevitably have some error, therefore it needs to be adjusted. To optimize the process, the gradient descent method is used in this invention.

[0026] First, based on the accounting data, the quality assessment function Q is constructed as follows: This is a quality evaluation function, related to accuracy, compliance, stability, incentive effect, efficiency, etc., and its calculation method is as follows: Where: A represents accuracy -- consistency with third-party verification results (0-1); C represents compliance – the degree to which standards and rules such as GBT24067, ISO14067, and Catena-X are met (0-1). S represents stability – the reciprocal of the coefficient of variation (0-1) of the accounting results of different batches of the same product. I represents the incentive effect – the normalized rate of change in the amount of recycled materials purchased by enterprises under this method (0-1). T represents efficiency – normalized (0-1) – the rate of reduction in decision-making time. - This is the weighting coefficient, which is configurable.

[0027] Then, based on the quality evaluation function, gradient descent is used for optimization: in Let be the weight coefficient at the t-th iteration. Through multiple iterations, the weight coefficient will gradually stop changing. When the weight matrix stops changing, the weight matrix obtained in the last iteration is used as the optimized weight matrix. The optimized weight matrix is ​​then substituted into the above formula to calculate the comprehensive applicability score corresponding to all allocation methods.

[0028] The selection threshold is calculated based on the historical score matrix. The accounting data is allocated using the allocation method where the comprehensive practicality score is greater than the selection threshold. The vehicle carbon footprint is then calculated based on the allocation results.

[0029] To improve the sensitivity of the overall applicability score to changes in the market environment, this invention introduces a historical score matrix. This matrix represents the overall applicability scores of the five allocation methods calculated in previous carbon footprint accounting processes. Based on this matrix, a selection threshold for the current carbon footprint accounting is calculated to determine which allocation method should be used. The formula for calculating the selection threshold is as follows: in, , These represent the standard deviation and mean of the comprehensive practicality score for all allocation methods in the previous N carbon footprint calculations. The fluctuation sensitivity coefficient The threshold value used in the previous carbon footprint calculation.

[0030] In the current carbon footprint accounting, all allocation methods are sorted in descending order based on the comprehensive practicality score. If the comprehensive practicality score of the first allocation method is greater than the selection threshold, and the difference between the comprehensive practicality score of the first allocation method and the second allocation method is greater than the preset value, then the first allocation method is directly selected to allocate the accounting data, and the vehicle carbon footprint is calculated based on the allocation result.

[0031] If the overall practicality score of the first allocation method is greater than the selection threshold and the difference between the overall practicality score of the first allocation method and the second allocation method is less than the preset value, then manual judgment will be performed.

[0032] If the overall usability score of the first allocation method is less than the selection threshold, a data quality warning will be issued, and additional data needs to be added and recalculated.

[0033] On the other hand, embodiments of the present invention also provide a carbon footprint accounting system based on an optimal allocation method. This system uses the aforementioned carbon footprint accounting method based on an optimal allocation method, including: The data acquisition module is used to acquire accounting data, historical score matrix and weight matrix corresponding to all allocation methods, and determine factor score set based on accounting data; A weight optimization module is used to adaptively optimize the weight matrix based on the calculated data to obtain an optimized weight matrix. The allocation selection module is used to calculate the selection threshold based on the historical score matrix, and then calculate the comprehensive practical score corresponding to each allocation method based on the optimized weight matrix and the factor score set. The carbon footprint accounting module is used to allocate accounting data using the allocation method with the highest comprehensive practicality score, and to perform vehicle carbon footprint accounting based on the allocation results.

[0034] On the other hand, embodiments of the present invention also provide a computer, including at least one processor and a memory, the memory storing a computer program configured to be executed by the processor to implement the above-described carbon footprint accounting method based on optimal allocation.

[0035] On the other hand, embodiments of the present invention also provide a storage medium, which is a computer-readable storage medium, on which a computer program is stored. The computer program can be executed by one or more processors to implement the above-described carbon footprint accounting method based on optimal allocation.

[0036] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A carbon footprint accounting method based on optimal allocation, characterized in that: include: Obtain the accounting data and historical score matrix, and determine the factor score set based on the accounting data; Obtain the weight matrix corresponding to all allocation methods, adaptively optimize the weight matrix based on the accounting data to obtain the optimized weight matrix, and then calculate the comprehensive practical score corresponding to each allocation method based on the optimized weight matrix and the factor scoring set; The selection threshold is calculated based on the historical score matrix. The accounting data is allocated using the allocation method where the comprehensive practicality score is greater than the selection threshold. The vehicle carbon footprint is then calculated based on the allocation results.

2. The carbon footprint accounting method based on optimal allocation as described in claim 1, characterized in that: The factor scoring set includes industry guideline fit score, process segmentation feasibility score, dominant substitute identification score, economic value ratio rationality score, and data quality and availability score.

3. The carbon footprint accounting method based on optimal allocation as described in claim 1, characterized in that: The calculation method for the dominant substitute identification score is as follows: Market share, technology maturity, emissions stability, and price fluctuation sequences are determined based on accounting data; The price volatility index is calculated based on the price volatility sequence, and then market share, technological maturity, and emission stability are weighted to obtain the dominant alternative identification score.

4. The carbon footprint accounting method based on optimal allocation as described in claim 1, characterized in that: The formula for calculating the economic value ratio rationality score is as follows: in, The regional adjusted economic value ratio, R is the measured ratio of main product price to by-product price; This serves as a reference value for the industry's optimal economic value ratio. / Regional consumer price index correction coefficient.

5. The carbon footprint accounting method based on optimal allocation as described in claim 1, characterized in that: Methods for adaptively optimizing the weight matrix based on the calculated data to obtain the optimized weight matrix include: A quality assessment function is constructed based on the accounting data. Then, based on the quality assessment function, the weight matrix is ​​adjusted using the gradient descent method to obtain a new weight matrix. Repeat the above steps until the weight matrix no longer changes, and use the weight matrix obtained from the last repetition as the optimized weight matrix.

6. The carbon footprint accounting method based on optimal allocation as described in claim 1, characterized in that: The formula for calculating the selection threshold is as follows: in, , These represent the standard deviation and mean of the comprehensive practicality score for the previous N carbon footprint calculations. The fluctuation sensitivity coefficient The threshold value used in the previous carbon footprint calculation.

7. A carbon footprint accounting system based on optimal allocation, characterized in that: The system uses a carbon footprint accounting method based on optimal allocation as described in any one of claims 1-6, comprising: The data acquisition module is used to acquire accounting data, historical score matrix and weight matrix corresponding to all allocation methods, and determine factor score set based on accounting data; A weight optimization module is used to adaptively optimize the weight matrix based on the calculated data to obtain an optimized weight matrix. The allocation selection module is used to calculate the selection threshold based on the historical score matrix, and then calculate the comprehensive practical score corresponding to each allocation method based on the optimized weight matrix and the factor score set. The carbon footprint accounting module is used to allocate accounting data using the allocation method with the highest comprehensive practicality score, and to perform vehicle carbon footprint accounting based on the allocation results.

8. A computer, characterized in that: It includes at least one processor and a memory, the memory storing a computer program configured to be executed by the processor to implement a carbon footprint accounting method based on an optimal allocation method as described in any one of claims 1-6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a computer program is stored. The computer program can be executed by one or more processors to implement a carbon footprint accounting method based on optimal allocation as described in any one of claims 1-6.

Images