Waste lithium battery regeneration process carbon data management method based on block chain

Abstract

The invention discloses a waste lithium battery regeneration process carbon data management method based on a block chain, and belongs to the technical field of information. The method comprises the following steps: establishing a carbon data model in combination with life cycle evaluation (LCA)-based waste lithium battery regeneration process carbon footprint evaluation; a waste lithium battery regeneration process carbon emission monitoring-reporting-checking (MRV) system based on a block chain is constructed, and a regeneration process carbon footprint is credibly obtained. A privacy carbon data distributed cloud storage scheme is based on a secret sharing technology, and data integrity is ensured through a block chain. The non-privacy carbon data are stored through the cloud, and digital fingerprints of the non-privacy carbon data are stored on the block chain. And designing an access strategy according to the user role and the carbon data attribute, and storing the access strategy in the block chain to realize safe sharing of the carbon data. The invention provides an effective carbon data model and management method for the regeneration process of the waste lithium battery, provides a basis for energy conservation and emission reduction of the regeneration process, and supports the evaluation of the carbon footprint in the whole life cycle of the lithium battery product.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and particularly relates to a carbon data management method for the recycling process of waste lithium batteries based on blockchain. Background Art

[0002] The recycling of waste lithium batteries refers to the process of resource recovery of retired power batteries and energy storage batteries through physical and chemical methods to extract valuable metals such as lithium, cobalt, nickel, etc. and achieve material recycling. The recycling process of waste lithium batteries consumes energy and generates solid waste and wastewater, causing environmental pollution. Using the Life Cycle Assessment (LCA) method to evaluate the carbon footprint of the waste lithium battery recycling process can quantitatively evaluate the carbon emissions in the recycling process, identify key process nodes and main influencing factors with the potential to reduce pollution and carbon emissions, and provide a basis for environmentally friendly process improvement. The carbon data management in the waste lithium battery recycling process is to control the LCA evaluation process, carbon data storage and sharing in the recycling process, support the carbon footprint evaluation and analysis of the entire life cycle of lithium battery products, meet the requirements of domestic and foreign battery regulations for the disclosure of lithium battery carbon footprint, and help achieve the goals of "carbon peak and carbon neutrality".

[0003] The carbon data in the waste lithium battery recycling process mainly includes waste lithium battery recycling lines, carbon emission activity data (raw material input, energy consumption, waste emissions, etc.), carbon footprint information (carbon emission value, accounting method, functional unit, emission factor), etc. The management work involves carbon data acquisition, storage and sharing. For the acquisition process, the collected data needs to be true and reliable, the analysis process needs to ensure the accuracy of carbon data, and the results of the verification calculation process need to be credible; the storage process should have data integrity and privacy security and adopt an efficient storage solution; the sharing process needs to be transparent and controllable to ensure data sharing while protecting privacy.

[0004] In terms of carbon footprint data acquisition, currently, the LCA method is mainly used to evaluate and analyze the carbon footprint of the waste lithium battery recycling process. The evaluation and analysis are mainly in manual mode or use LCA software (such as SimaPro). In addition, the emission data for carbon footprint analysis mainly comes from resources such as environmental databases or industry reports, rather than production site data, which is difficult to ensure the objectivity and accuracy of carbon footprint assessment and analysis, and the assessment cost is relatively high. The digital Monitoring, Reporting, and Verification (MRV) system is the key process for carbon emission quantification and data quality assurance. Currently, there is no relevant research on the carbon footprint evaluation of the waste lithium battery recycling process.

[0005] In terms of carbon data storage, existing research has utilized cloud storage and blockchain technology for carbon data storage in product supply chains. Storing carbon data of product supply chains using cloud platforms may lead to problems in data security and privacy protection. While using blockchain to store carbon data can effectively prevent data tampering, there are still deficiencies in aspects such as data privacy protection and storage scalability.

[0006] In terms of carbon data sharing, existing research mainly uses blockchain to achieve decentralized carbon data storage management in supply chains. However, there is still insufficient research in constructing effective access control strategies to ensure enterprises' data autonomy management rights and enable effective carbon data sharing.

[0007] In summary, this patent provides a carbon data management method for the recycling process of waste lithium batteries to ensure the authenticity and reliability of the carbon data acquisition process, the integrity and security of the stored carbon data, the efficiency of the process, and the transparency and controllability of the carbon data sharing process. Summary of the Invention

[0008] The present invention discloses a carbon data management method for the recycling process of waste lithium batteries based on blockchain. It is used to achieve efficient management of carbon data acquisition, storage, and sharing of waste lithium batteries during the recycling process.

[0009] The specific technical solution of the present invention is as follows:

[0010] A carbon data management method for the recycling process of waste lithium batteries based on blockchain, the method flow is as Figure 1 shown. The data model example of the recycling process of waste lithium batteries based on LCA of the present invention is as Figure 2 shown, and the system flow is as Figure 3 shown: The overall management model includes the full-chain management of carbon data acquisition, storage, and sharing, and the entire model is supported by blockchain technology. The specific carbon data management method for the recycling process of waste lithium batteries includes the following steps: Step 1: Carbon data acquisition: Conduct a carbon footprint evaluation and analysis following the LCA method. Build a digital MRV system for the recycling process of waste lithium batteries. Collect carbon emission activity data during the recycling process through Internet of Things devices, calculate the carbon footprint using the IPCC method, design a carbon footprint calculation correctness verification method in combination with blockchain and zero-knowledge proof, and use smart contracts to achieve automated verification and proof; Step 2: Carbon data storage: Store the acquired carbon data. Classify the carbon data into public data and private data according to data sensitivity, and generate digital fingerprints respectively. Use the Shamir secret sharing technology to split the fragments of private data, and store the digital fingerprints, public data, private data fragment content, and metadata in the blockchain, centralized cloud database, and distributed cloud database respectively; Step 3: Carbon data sharing: Based on the carbon data model and the sharing purpose, the recycling enterprise designs an access policy according to the user role, data content, operation attributes, and environmental attributes, and stores it in the blockchain. Deploy relevant smart contracts to implement an attribute-based access control method to determine whether a data applicant has access rights. After determining access, the carbon data is obtained by combining the cloud storage address and the secret reconstruction method in Step 2. Integrating the access control and acquisition processes, secure sharing of carbon data among various suppliers, users, and auditing agencies throughout the entire life cycle of lithium batteries is achieved.

[0011] Furthermore, in Step 1, the specific steps for managing the carbon data acquisition process are as follows: Step 1.1 First, collect carbon emission activity data and other key carbon evaluation data generated during the recycling of waste lithium batteries through the enterprise's Internet of Things devices, enterprise information systems, manual collection, etc., and upload them to the local database within the enterprise. Step 1.2 Design a carbon footprint impact assessment and analysis process based on LCA within the system, which is divided into goal and scope determination, inventory analysis, carbon footprint assessment, and result interpretation. The enterprise calculates the carbon footprint based on the carbon emission data collected by the Internet of Things and in combination with the IPCC method. Step 1.3 Based on the accounting method, carbon emission activity data, emission factors, and allocation methods, the enterprise uses zero-knowledge proof technology to verify the effectiveness of the calculation process, and realizes automatic verification of the proof in combination with smart contracts.

[0012] Furthermore, in Step 2, the specific steps for carbon data storage management are as follows: Step 2.1 The enterprises related to the recycling process label the attributes of the carbon data, which are divided into publicly available data and private data. Step 2.2 For publicly available carbon data, the enterprise directly uploads the data to a centralized cloud database, and uploads the storage address of the cloud database to the blockchain for deposit. For private carbon data, the enterprise locally uses the Shamir secret sharing technology. First, based on the parameters (k, n), the private data is divided into n secret fragments and stored in n distributed cloud databases, and the metadata and storage addresses of each fragment are uploaded to the blockchain for deposit. Step 2.3 The enterprise locally calculates the hash values of the publicly available carbon data and the private carbon data, and stores the data digest and the hash value corresponding to the deposit in the blockchain to prevent data untrustworthiness caused by third-party cloud tampering, and realizes verifiability during the carbon data storage process.

[0013] Furthermore, in Step 3, the specific steps for carbon data sharing management are as follows: Step 3.1 System participants need to first register their identities through a blockchain certification authority and obtain a digital identity to ensure a unique identifier in the blockchain. Step 3.2 During the regeneration process, relevant enterprises, as data owners, design access policies for the datasets of the carbon data model according to the sharing purpose. Specific descriptions are provided in the specific implementation methods, including four parts: identity attributes, data content, operation attributes, and environmental attributes. The access policies are stored on the blockchain. Step 3.3 Data applicants (including battery manufacturers, raw material suppliers, users, auditing institutions, and regeneration enterprises) send access requests to the blockchain, carrying identity information, data information to be accessed, and request operations. The access permission is determined by a written permission policy judgment contract, and the result returns a boolean type to determine whether the user has permission to access the applied data. Step 3.4 If the applicant has permission to access the data, the blockchain returns the storage address of the cloud database (centralized or distributed) and the hash value of the data to be accessed to the applicant. If the data to be accessed is stored in a privacy data storage method, the applicant needs to obtain k fragments from multiple distributed cloud databases and then perform secret reconstruction to obtain the data content. Step 3.5 The data applicant performs a hash operation on the obtained data and compares it with the hash value stored on the blockchain for verification. If they are consistent, it indicates that the data has not been tampered with, realizing the verifiability of shared data.

[0014] Compared with the existing technical solutions, the beneficial effects of the present invention are as follows:

[0015] 1. The present invention constructs a digital process for carbon emission quantification and carbon footprint data quality verification, combines Internet of Things devices, enterprise information systems, and manual input methods to collect carbon emission data in real time, uses the LCA method to analyze and quantify carbon data to obtain carbon footprint information, then combines zero-knowledge proof to verify the effectiveness of the carbon footprint calculation process generated during the above regeneration process to generate a proof, and combines smart contracts to automatically verify the effectiveness of the proof, thereby ensuring the correctness of the calculation process and parameters without disclosing any privacy activity data, and thus ensuring that the obtained carbon data is true and reliable, and the carbon data acquisition process is verifiable and trustworthy.

[0016] 2. The present invention combines blockchain technology with the storage architectures of centralized and distributed cloud databases, which not only improves the data storage efficiency but also significantly optimizes the blockchain storage performance problem. In addition, considering the sensitivity of carbon data, public and private carbon data are divided, and the secret sharing technology is used to protect the privacy of private carbon data. Compared with symmetric encryption technology, it reduces the possibility of private carbon data leakage caused by the cracking or leakage and loss of keys, solves the single-point failure problem, improves data security and availability, and enhances the privacy protection ability of the system.

[0017] 3. The attribute - based access control method (ABAC) and secret reconstruction method of the present invention are used to construct a carbon data access control and acquisition model, ensuring the privacy and security of carbon data during the data sharing process. At the same time, hash operations are used to compare the digital fingerprints of carbon data stored on the blockchain, realizing the verifiability of shared carbon data usage and further enhancing the integrity and reliability of the carbon data management system.

[0018] 4. The present invention makes full use of the technical advantages of the blockchain, such as anti - tampering, decentralization, and data traceability. The whole process of carbon data collection, acquisition, storage, access, and management is recorded and stored on the blockchain, ensuring that the entire data operation process leaves a trace, making the management process of carbon data traceable and verifiable. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flowchart of the method of the present invention.

[0020] Figure 2 It is an example diagram of the carbon data model of the present invention.

[0021] Figure 3 It is an architecture diagram of the carbon data management method for the regeneration process of the present invention.

[0022] Figure 4 It is a schematic diagram of the carbon data acquisition management process for the regeneration process of the present invention.

[0023] Figure 5 It is a structure diagram of the public data and private data of the present invention.

[0024] Figure 6 It is a structure diagram of the on - chain data and off - chain data of the present invention.

[0025] Figure 7 It is a schematic diagram of the carbon data storage management process for the regeneration process of the present invention.

[0026] Figure 8 It is a schematic diagram of the shared carbon data access policy of the present invention.

[0027] Figure 9 It is a schematic diagram of the carbon data access control process for the regeneration process of the present invention.

[0028] Figure 10 It is a schematic diagram of the carbon data sharing management process for the regeneration process of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0029] The following describes the specific implementation manners of the present invention to facilitate those skilled in the art to understand the present invention. The technical solutions of the present invention are further described in conjunction with the accompanying drawings and embodiments.

[0030] Embodiment

[0031] The following is a detailed description of the carbon data management method for the recycling process of waste lithium batteries based on blockchain, which includes four entities, namely blockchain, cloud database, waste lithium battery recycling enterprise, and data applicant. The method flow is as follows Figure 1 shown, and the carbon data model for the recycling process established based on this is as follows Figure 2 shown, and the method architecture is as follows Figure 3 shown.

[0032] The specific implementation process of this embodiment is as follows:

[0033] Step 1: Carbon data acquisition: The enterprise first uses methods such as Internet of Things devices, enterprise information systems, and manual entry to monitor and collect all activity carbon data generated during the recycling process, and conducts a comprehensive analysis of this process based on the LCA method. The research boundary is defined as the recycling process, and the main sources of carbon emissions generated within this boundary are determined, including activity data such as raw material consumption, energy consumption, and waste treatment. A data list is established for carbon footprint analysis. During the analysis process, carbon footprint information is generated based on accounting methods, activity data, emission factors, and allocation methods. Finally, based on zero-knowledge proof technology, the effectiveness of the carbon footprint calculation process generated during the above recycling process is verified and a proof is generated. Combining with smart contracts, the effectiveness of the automated verification proof is ensured, and privacy data is guaranteed not to be leaked. The management process of overall carbon data acquisition is as follows Figure 4 shown:

[0034] Furthermore, in Step 1, the zero-knowledge proof process for generating the carbon emission value calculation process needs to follow the following steps: Step 1: Define the calculation process for the recycling process of waste lithium batteries, which will serve as the basis for zkSpec. To clearly represent the calculation process, the carbon footprint calculation process is defined according to the formula: where CF recycle represents the carbon footprint of the recycling process of waste lithium batteries, AD i is the activity data of the i-th unit process of the recycling enterprise, EF i is the carbon emission factor corresponding to the activity data of the i-th unit process of the enterprise, and GWP is the global warming potential; Step 2: Assume that the activity data AD i , emission factor EF i , and global warming potential GWP of each unit process are used as input variables, and the calculation process is the above-defined formula. Now, define the R1CS constraints between them. Each multiplication formula AD i ×EF i can be transformed into the following form of constraints: A i ×B i =Ci where A i = [AD i , EF i , GWP], B i = [z i , z j , 1], C i = [CF recycle ; Step 3: Convert the defined constraints into specific mathematical expressions. Taking three unit processes as an example: A 1 = [AD 1 , EF 1 , GWP], B 1 = [z 1 , z 2 , 1], C 1 = [CF 1 ; A 2 = [AD 2 , EF 2 , GWP], B 2 = [z 3 , z 4 , 1], C 2 = [CF 2 ; A 3 = [AD 3 , EF 3 , GWP], B 3 = [z 5 , z 6 , 1], C 3 = [CF 3 ; Convert the addition formula into the following expression: A 4 = [CF 1 , CF 2 , CF 3 , B i = [1, 1, 1], C i = [CF recycle ; ZoKrates compiles these constraints into the above R1CS format and represents them as linear equations. Each equation will have its corresponding A(i), B(i), and C(i) vectors, representing the relationship between the input data, constraints, and output results; Step 4: Generate the proof key (PK) and verification key (VK). Use the proof key (PK) and input data (such as active data AD i , emission factor EF ietc.), the enterprise performs calculations and generates zero-knowledge proofs. The generated proofs include the encrypted proof Proof, public input data PublicInputs, and private input data PrivateInputs; Step 5: The blockchain deploys a smart contract, receives Proof and PublicInputs, and uses the verification key (VK) to verify whether the zero-knowledge proof is valid. If the verification passes, subsequent deposit and sharing requests can be made; if the verification fails, the request is rejected.

[0035] Step 2: Carbon data storage. The enterprise needs to store all the obtained carbon data. According to the descriptions of carbon data in multiple documents, including the "Global Battery Alliance Battery Passport Guide", EU DPP, GDPR, "White Paper on Carbon Footprint and Low-Carbon Circular Development of Power Batteries", etc., some carbon data is private and cannot be fully publicly shared. This patent classifies carbon data into public data and private data. First, both public data and private data are hashed to generate digital fingerprints and stored in the blockchain. Then, the public data is stored in a centralized cloud server; while for private data, the Shamir secret sharing technology is used to secretly slice the private data to obtain several fragments, and the content and metadata are respectively stored in a distributed cloud database. At the same time, the metadata of the public data and private data fragments and the addresses of the stored cloud databases are uploaded to the blockchain. The classified carbon data information such as Figure 5 , the data storage location such as Figure 6 , the overall flowchart such as Figure 7 :

[0036] Furthermore, in Step 2, the process of secretly slicing and depositing private data is all based on the following steps: Step 1: The private data is D. First, select a large prime number P to construct a field; Step 2: Randomly generate a polynomial P(x) of degree k - 1: where a 0 = D, which is the value of the polynomial at x = 0 for the private data, a 1 , a 2 ,..., a k-1 are randomly generated systems to increase the randomness and security of the polynomial; Step 3: Set the number of slices n and the recovery threshold k, and calculate the values of the polynomial P(x) at n different points x 1 , x 2 , …, x n : Each (x i , P(x i)) corresponds to a fragment, and n is greater than k, supporting the fault tolerance of the distributed system; Step 4: Store each fragment (x i , P(x i )) in different nodes of the distributed cloud server respectively, where x i is the number corresponding to the fragment, and P(x i ) is the corresponding fragment value; the metadata includes x i , the fragment storage address Addr i , and the threshold values k and n are stored on the blockchain;

[0037] Step 3: Carbon data sharing. Carbon data sharing is divided into two parts, namely the application stage and the acquisition stage. Based on the carbon data model, in the application stage, an attribute-based access control method is used. The recycling enterprise designs an access policy according to the user identity attributes, the corresponding access data content, operation attributes, and environmental attributes, and uploads it to the blockchain. An intelligent contract for permission determination is designed to determine whether the data applicant has access rights according to the policy; after determining that access is allowed, when the applicant obtains the data, public data can be directly obtained, and private data needs to combine the cloud storage address in Step 2 to obtain fragments, and the fragments are reconstructed secretly to obtain the data. Calculate the data hash value of the obtained data and compare it with the corresponding hash value on the blockchain to ensure the consistency of the carbon data. Integrating the carbon data application and acquisition processes, the secure sharing of carbon data among various suppliers, users, and auditing agencies in the whole life cycle of lithium batteries is realized. The access policy designed according to the user role attributes is as Figure 8 , and the overall data access control flow chart is as Figure 9 , and the full flow chart of data sharing management is as Figure 10 :

[0038] Furthermore, in Step 3, it is divided into two parts: permission determination and data acquisition. The processes of determining access permissions and reconstructing and verifying private data fragments are all based on the following steps: Step 1: Design an access policy according to the user identity and carbon data attributes. The user identity attributes U = {Role}, the data attributes D = {Content, operational}, the environmental attributes E = {StartTime, EndTime}, and the access policy P = {AllowedRole, UserContent, UserOperational, AllowedTime}. The recycling enterprise can modify the access policy content according to the change of the subsequent shared data purpose; Step 2: When the data applicant sends an access request to the blockchain, upload the identity role and the data to be accessed {Role u , Content u , Operational u, {Time}, design a decision-making contract. The input is the information uploaded by the applicant, which is compared with the access policy P: RoleCheck = Role u ∈ AllowedRoles ContentCheck = Content u ∈ UserContent OperationalCheck = Operational u ∈ UserOperational TimeCheck = Time ∈ [StartTime, EndTime] Final decision: AccessGranted = RoleCheck ∧ ContentCheck ∧ OperationalCheck ∧ TimeCheck. If the decision is passed, return the cloud database address url: ProvideAccess(userID, requestedData, blockchainHash) → dataURL where userID is the identity identifier of the data applicant, indicating the user address to be returned, requestData is the data identifier of the application, and blockHash is the hash value of the applied data, used to compare data integrity after acquisition; If the decision fails, return access denied; Step 3: The data applicant obtains the cloud database storage address url returned by the blockchain in the access stage, i.e., Addr i , if the applied data is in the privacy data storage mode, obtain the fragment information (x i , P(x i )) from the distributed cloud database. If the applied data is in the public carbon data storage mode, directly proceed to Step 4; Step 4: After obtaining at least k fragments (x 1 , P(x 1 ))), (x 2 , P(x 2 ))), (x 3 , P(x 3 ))),..., (x k , P(x k ))), use the Lagrange interpolation polynomial for recovery: When x = 0, the obtained result is the privacy data D: Step 5: Perform a hash verification on the acquired data D and compare for consistency: H D = SHA-256(D) where H D is the value after performing the hash operation, and blockchainHash is the digital fingerprint stored on the blockchain. Comparing the two can verify the authenticity of the carbon data obtained by the data applicant.

Claims

1. A blockchain-based carbon data management method for the regeneration process of waste lithium batteries; characterized in that: The following steps are involved: Step 1: Carbon data acquisition: Follow the LCA method to evaluate and analyze the carbon footprint; build a digital MRV system for the recycling process of waste lithium batteries; Collect carbon emission activity data of the regeneration process through IoT devices, calculate carbon footprint using IPCC method, design a method to verify the correctness of carbon footprint calculation by combining blockchain and zero-knowledge proof, and use smart contracts to realize automated verification and proof; Step 2: Carbon data storage: Store the acquired carbon data; divide the carbon data into public data and private data according to the sensitivity of the data, and generate digital fingerprints for each; and use Shamir's secret sharing technology to split the private data into fragments, and store the digital fingerprints, public data, private data fragment content and metadata in the blockchain, centralized cloud database and distributed cloud database respectively; Step 3: Carbon data sharing: Based on the carbon data model and sharing purpose, the recycling enterprise designs access strategies according to user roles, data content, operation attributes and environmental attributes, and stores them in the blockchain; Deploy relevant smart contracts to implement attribute-based access control methods to determine whether data applicants have access rights; After determining that it is accessible, the cloud storage address and secret reconstruction method in step 2 are used to obtain carbon data; the integrated access control and acquisition process enables the secure sharing of carbon data among suppliers, users and auditing agencies throughout the life cycle of lithium batteries.

2. A blockchain-based carbon data management method for waste lithium battery regeneration process as claimed in claim 1, characterized in that: In step 1, the carbon data acquisition process is as follows: The first step is to collect carbon emission activity data and other key carbon assessment data generated during the recycling process of waste lithium batteries through the company's Internet of Things devices, enterprise information systems, manual collection, etc., and upload them to the company's internal local database; In the second step, a carbon footprint impact assessment and analysis process based on LCA was designed within the system, which is divided into purpose and scope determination, inventory analysis, carbon footprint assessment, and result interpretation. The carbon footprint of enterprises is calculated based on the carbon emission data collected by the Internet of Things and combined with the IPCC method; In the third step, based on accounting methods, activity data, emission factors and allocation methods, the company uses zero-knowledge proof technology to verify the validity of the calculation process, and combines it with smart contracts to realize automated verification of the proof.

3. A blockchain-based carbon data management method for waste lithium battery regeneration process as claimed in claim 1, characterized in that: In step 2, the carbon data storage process is as follows: In the first step, companies involved in the recycling process will annotate carbon data and divide it into public data and private data; In the second step, for public carbon data, the enterprise directly uploads the data to a centralized cloud database, and the storage address of the cloud database is uploaded to the blockchain for evidence storage; for private carbon data, the enterprise locally uses Shamir's secret sharing technology, firstly divides the private data into n secret fragments based on the parameters (k, n), stores them in n distributed cloud databases, and uploads the metadata and storage address of each fragment to the blockchain for evidence storage; In the third step, the enterprise locally calculates the hash values ​​of public carbon data and private carbon data, and stores the data summary and hash value in the blockchain accordingly, to prevent the data from being tampered with by a third-party cloud and causing it to become unreliable, and to achieve verifiability during the carbon data storage process.

4. A blockchain-based carbon data management method for waste lithium battery regeneration process as claimed in claim 1, characterized in that: In step 3, the carbon data sharing process is as follows: In the first step, system participants need to register their identities through blockchain certification agencies and obtain digital identities to ensure that they have unique identification in the blockchain; In the second step, the enterprises involved in the recycling process, as data owners, design access strategies for the data sets of the carbon data model according to the purpose of sharing when uploading carbon data. The specific implementation method is explained in detail, including identity attributes, data content, operation attributes and environmental attributes, and the access strategies are stored in the blockchain; In the third step, the data applicant sends an access request to the blockchain, carrying identity information, data information requested for access, and requested operations. The access rights are determined by the written permission policy determination contract, and the result is returned as a Boolean type to determine whether the user has the authority to access the requested data. Data applicants include battery manufacturers, raw material suppliers, users, auditing agencies, and other recycling companies; Step 4: If the applicant has the right to access the data, the blockchain returns the storage address of the cloud database (centralized or distributed) and the hash value of the data requested for access to the applicant; if the data requested for access is stored in a private data storage format, the applicant needs to obtain k fragments from multiple distributed cloud databases and perform secret reconstruction to obtain the data content; In the fifth step, the data applicant performs a hash operation on the acquired data and compares and verifies it with the hash value stored on the blockchain. If they are consistent, it means that the data has not been tampered with, making the shared data verifiable.

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