Battery safety management and value regeneration method and system

Abstract

The application discloses a battery safety management and value regeneration method and system, relates to the technical field of battery whole cycle management, and comprises the following steps: allocating a unique physical code to a battery and generating a bound digital license plate, and storing battery multi-source data to the corresponding digital license plate; performing scene-based risk assessment based on the digital license plate in the running stage, generating a safety buffer scheme and triggering a graded power supply switching when preset conditions are met, and synchronously updating the execution record to the digital license plate; in the recycling stage, identity verification is completed through battery data fingerprints, the residual value is evaluated and a resource disposal path is matched after the verification, and the associated value-added rights and interests are unlocked after the disposal is completed and a digital acceptance report is generated and synchronized with the digital license plate; the method has the beneficial effects that the whole-link management process of the whole life cycle of the battery is connected through the establishment of the double identity identification of the physical code and the digital license plate for the battery.

Description

Technical Field

[0001] This invention relates to the field of battery lifecycle management technology, and in particular to a method and system for battery safety management and value recovery. Background Technology

[0002] With the rapid development of new energy and modular energy storage technologies, batteries, as core energy storage devices, are directly related to the sustainable development of the industry through their safe operation throughout their entire life cycle and their resource utilization after retirement.

[0003] However, the existing battery application and management system faces a core technical bottleneck: the lack of a unified and reliable data identity carrier and connection mechanism in the entire life cycle of existing batteries leads to a disconnect between the "operational safety governance" at the front end and the "retirement value regeneration" at the back end. It is impossible to achieve cross-system traceability and collaborative safety management during the battery operation stage, and it is also impossible to obtain objective and complete historical operation data as support for residual value assessment and responsibility determination during the retirement stage. Ultimately, it is difficult to achieve efficient and closed-loop management of the entire battery life cycle.

[0004] Therefore, a method and system for battery safety management and value recycling are proposed. Summary of the Invention

[0005] In view of the aforementioned state of the prior art, this application is hereby proposed. Embodiments of this application provide a battery safety governance and value regeneration method and system, which enables data traceability and querying of batteries at every stage of their entire lifecycle through digital licenses. This establishes a complete governance process, from multi-source data collection, scenario-based risk assessment and tiered emergency response, identity verification based on internal data fingerprints, residual value assessment and resource disposal path matching, to unlocking value-added rights and data asset applications.

[0006] According to one aspect of this application, a battery safety management and value regeneration method is provided, comprising: assigning a unique physical code to a battery and generating a digital license plate uniquely bound to the physical code; acquiring multi-source data of the battery and storing it in association with the corresponding digital license plate, wherein the multi-source data includes at least: historical battery operation data, external environment perception data, and user behavior characteristic data; performing a scenario-based risk assessment based on the multi-source data associated with the digital license plate during the battery's operation phase; and generating a safety margin buffer scheme and triggering a graded power supply switching command for the battery when the result of the scenario-based risk assessment meets preset conditions, and linking the safety margin buffer scheme with the graded power supply... The execution record of the battery switching command is updated to the digital license plate; during the battery recycling phase, the digital license plate bound to the physical code of the battery is retrieved, and the historical operation data associated with the digital license plate is extracted to generate an internal data fingerprint of the battery; the battery is verified for identity through the internal data fingerprint of the battery; only when the identity verification is successful, the multi-source data is retrieved to perform a residual value assessment of the battery, and the corresponding resource disposal path is matched according to the result of the residual value assessment; the battery is recycled and disposed of according to the resource disposal path, and the value-added rights associated with the digital license plate are unlocked only after a digital acceptance report based on the resource disposal path is generated and synchronized to the corresponding digital license plate.

[0007] According to another aspect of this application, a battery safety management and value regeneration system is provided, comprising: an identity coding module for assigning a unique physical code to a battery and generating a digital license plate uniquely bound to the physical code; a data collection module for acquiring multi-source data of the battery and storing it in association with the corresponding digital license plate, wherein the multi-source data includes at least: historical battery operation data, external environment perception data, and user behavior characteristic data; and a risk management module for performing scenario-based risk assessment based on the multi-source data associated with the digital license plate during the battery's operation phase; when the result of the scenario-based risk assessment meets preset conditions, generating a safety margin buffer scheme and triggering a graded power supply switching command for the battery, and connecting the safety margin buffer scheme with the graded power supply... The execution record of the battery switching command is updated to the digital license plate; the identity verification module is used to retrieve the digital license plate bound to the physical code of the battery during the battery recycling stage, and extract the historical operation data associated with the digital license plate to generate the battery's internal data fingerprint; the battery's identity is verified through the battery's internal data fingerprint; the residual value assessment module is used to retrieve the multi-source data to assess the battery's residual value only when the identity verification is passed, and match the corresponding resource disposal path according to the result of the residual value assessment; the resource disposal module is used to recycle and dispose of the battery according to the resource disposal path, and unlock the value-added rights associated with the digital license plate only after a digital acceptance report based on the resource disposal path is generated and synchronized to the corresponding digital license plate.

[0008] According to another aspect of this application, an electronic device is provided, including a memory and a processor, the memory being used to store computer-executable instructions, and the processor being used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the method described above.

[0009] According to another aspect of this application, a computer storage medium is provided that stores computer-executable instructions thereon, which, when executed by a processor, implement the steps of the method described above.

[0010] Compared with existing technologies, the battery safety governance and value regeneration method and system according to the embodiments of this application can establish a dual identity for batteries by physical coding and digital licenses, and use the digital license as the core data carrier to open up the entire governance process from multi-source data collection, scenario-based risk assessment and graded emergency response, identity verification based on internal data fingerprints, residual value assessment and resource disposal path matching, to unlocking value-added rights and data asset application. Attached Figure Description

[0011] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0012] Figure 1 This is a flowchart of a battery safety management and value recovery method according to the present invention.

[0013] Figure 2 This is a block diagram of a battery safety management and value recovery system according to the present invention.

[0014] Figure 3 This is a block diagram of an electronic device according to the present invention. Detailed Implementation

[0015] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0016] Exemplary method:

[0017] Figure 1 The illustration shows a battery safety management and value recovery method according to an embodiment of this application, including steps S1 to S6.

[0018] To facilitate understanding, we will use the power lithium battery of a certain electric two-wheeler as an example. Assume that the battery's serial number is BAT-2026-00583, its rated capacity is 72V35Ah, its positive electrode material is ternary lithium (nickel-cobalt-manganese), its manufacturer is Company A, and it has accumulated approximately 800 charge-discharge cycles. It is installed on the electric two-wheeler of user Zhang and is used for daily commuting in the city.

[0019] like Figure 1 As shown, in step S1, a unique physical code is assigned to the battery, and a digital license plate uniquely bound to the physical code is generated.

[0020] In this step, the physical code refers to a unique identifier physically attached to the battery body. Its carrier form includes, but is not limited to, laser-etched codes, sprayed QR codes, and etched barcodes. The physical code possesses tamper-proof and easily identifiable characteristics, enabling rapid reading and identification at every stage of the battery's lifecycle. The physical code may contain encrypted encoding of basic information such as battery production information, specifications, and batch information.

[0021] A digital license plate is a digital identity record that maps one-to-one with a physical code and is stored in a data management platform. The license plate information includes at least the battery's unique identifier, complete production information (such as manufacturer, production date, production line number, etc.), and the battery's initial parameters (such as rated capacity, rated voltage, initial internal resistance, etc.). The digital license plate completes network registration when the battery leaves the factory and forms a permanent binding relationship with the physical code, constituting a battery identity confirmation system with "physical code + digital license plate" as the dual core.

[0022] It should be noted that the binding relationship between the physical code and the digital license plate is unchangeable once established to ensure the uniqueness and traceability of the battery's identity throughout its entire lifecycle. The location for attaching the physical code can be selected based on the battery's shape and structure, choosing an area that is easy to scan and identify and not easily worn.

[0023] In a preferred embodiment, the physical code can adopt a structured multi-character combination encoding scheme, with the following specific encoding rules: The code begins with a fixed prefix identifier to indicate that it belongs to the battery digital license plate system, for example, using the letter "S" as a unified prefix identifier; the main body of the code following the prefix consists of a free combination of English letters and Arabic numerals, where English letters support uppercase and lowercase forms (i.e., 48 characters to choose from: A~Z and a~z), and Arabic numerals 0~9 can be used cyclically and repeatedly. The order and frequency of each character in the code are unrestricted; the code length has no fixed upper limit and can be dynamically expanded according to business needs such as battery category expansion and module addition. The above encoding rules make the theoretical combination capacity approach infinity, which can meet the unlimited expansion needs of the number and length of license plate codes in future large-scale, multi-category, and multi-module battery management scenarios, avoiding a hard restriction on the issuance of licenses for new battery modules due to insufficient encoding space.

[0024] For example, one optional physical encoding format is "SaB3cD7eF2gH", where "S" is a fixed prefix, and the "aB3cD7eF2gH" part is a free combination of uppercase and lowercase English letters and numbers. This encoding is attached to the battery body in the form of a barcode or QR code and can be quickly read by a scanning device to retrieve the corresponding full information of the digital license plate. Compared with pure digital encoding schemes, the above multi-character combination encoding can provide an order of magnitude larger encoding space for the same length, and the encoding length can be extended indefinitely according to business needs, fundamentally eliminating the risk of license plate encoding resource depletion.

[0025] It should be noted that the above-mentioned multi-character combination encoding scheme is a preferred implementation of physical encoding, and this application does not impose unique limitations on the specific character composition and format of the physical encoding. For ease of explanation, the following embodiments still use a simplified factory serial number format as an example, which should not be construed as a restriction on the physical encoding format.

[0026] Using the aforementioned battery example, a physical code "BAT-2026-00583" is etched onto the battery, and a digital license plate is generated simultaneously. The license plate records: manufacturer is Company A, production date is January 15, 2026, rated capacity is 72V 35Ah, positive electrode material is ternary lithium, and initial internal resistance is 15mΩ. After the physical code and digital license plate are bound together, the battery's identity verification is complete.

[0027] The above scheme establishes a dual identity for each battery, encompassing both physical and digital layers, providing a unified data carrier for subsequent multi-source data collection, risk assessment, recycling, and disposal—a comprehensive governance process.

[0028] return Figure 1 In step S2, multi-source data of the battery is acquired and associated with and stored in the corresponding digital license plate. The multi-source data includes at least: battery historical operation data, external environment perception data and user behavior characteristic data.

[0029] In this step, multi-source data refers to various types of data from different collection sources that are related to battery operation and usage scenarios. All collected data are mapped to the corresponding digital license plate through the battery's physical code, achieving a unique association between data and license plate storage.

[0030] Specifically, historical battery operating data refers to battery operating status data continuously collected by the Battery Management Unit (BMS), including but not limited to: charge / discharge curve data, voltage and current change data, temperature change data, internal resistance change data, and cumulative cycle count. External environment perception data refers to data related to the battery's operating environment, including at least the distribution characteristics of surrounding sensitive areas, such as the distribution of sensitive locations like schools, hospitals, and gas stations near the battery's current location. User behavior characteristic data refers to data related to the battery user's usage habits and travel scenarios, including at least travel plan characteristics (such as travel destination, estimated travel distance, and estimated arrival time) and scenario characteristics (such as long-distance commuting, freight transportation, and short-distance transportation).

[0031] It should be noted that user behavior data can be obtained through user authorization in the terminal application, or inferred based on the battery's historical usage patterns. External environment perception data can be obtained through the vehicle's positioning device combined with map data. The collected multi-source data is encrypted and transmitted before being stored in the data management platform, and a battery lifecycle database indexed by the digital license plate is established.

[0032] Using the aforementioned battery example, the battery's BMS continuously records its charge / discharge curves, temperature changes, and other operational data; the vehicle positioning device detects a primary school and a gas station within a 500-meter radius of the current location, and this information is collected as a distribution characteristic of sensitive surrounding areas; user Zhang authorized travel plan data in the terminal application, and the current scenario is characterized as "urban commuting," with a daily journey of approximately 15 kilometers. All of the above data is mapped to the corresponding digital license plate through the physical code "BAT-2026-00583" for associated storage.

[0033] The above approach establishes a multi-dimensional data foundation for each battery, encompassing operational status, environmental information, and user behavior, providing data support for subsequent scenario-based risk assessments.

[0034] After completing battery identification and the associated storage of multi-source data, the method moves on to the safety governance phase of battery operation. The core of this phase is to conduct scenario-based risk assessments and emergency responses for batteries based on multi-source data associated with digital license plates, rather than relying solely on a single state parameter of the battery itself.

[0035] return Figure 1 In step S3, during the battery's operation phase, a scenario-based risk assessment is performed based on the multi-source data associated with the corresponding digital license plate. When the result of the scenario-based risk assessment meets the preset conditions, a safety margin buffer scheme is generated and a graded power supply switching instruction for the battery is triggered. The execution records of the safety margin buffer scheme and the graded power supply switching instruction are then updated to the digital license plate.

[0036] External environment perception data should at least include the distribution characteristics of surrounding sensitive areas; user behavior characteristic data should at least include travel plan characteristics and scenario characteristics; scenario-based risk assessment specifically includes:

[0037] Predict the probability of battery thermal runaway based on historical battery operating data;

[0038] The characteristics of travel plans, scenarios, distribution of surrounding sensitive areas, and probability of battery thermal runaway are quantified, and a comprehensive risk coefficient is calculated as the result of scenario-based risk assessment.

[0039] In this step, predicting the probability of battery thermal runaway based on historical battery operating data means calculating the probability of the battery experiencing thermal runaway in the current state based on historical operating data such as charge and discharge curve data, temperature change data, and internal resistance change trends collected by the BMS, using a preset thermal runaway prediction algorithm (such as trend extrapolation based on battery aging models, abnormal pattern recognition based on machine learning, etc.).

[0040] Quantifying travel plan characteristics, scenario characteristics, distribution characteristics of surrounding sensitive areas, and the probability of battery thermal runaway involves converting the data from each dimension into quantifiable scores or coefficients, and then calculating a comprehensive risk coefficient through weighted summation, fuzzy comprehensive evaluation, or other pre-defined comprehensive calculation methods. For example, corresponding weight coefficients can be assigned to each dimension, with the weight of the probability of battery thermal runaway set to a higher value, the weight of the distribution characteristics of surrounding sensitive areas determined based on the type and distance of sensitive locations, and the weights of travel plan characteristics and scenario characteristics determined based on the urgency of travel and the risk level of the scenario.

[0041] It should be noted that the calculation method for the comprehensive risk coefficient is not limited to the weighted summation method described above. Other multi-factor comprehensive assessment methods can also be used, as long as they can integrate risk factors from multiple dimensions into a comparable quantitative indicator. The preset condition can be that the comprehensive risk coefficient reaches or exceeds a pre-set risk threshold.

[0042] Furthermore, in the above quantitative processing, the mapping of raw data to scores for each dimension can be achieved through preset mapping rules. For example, for the distribution characteristics of surrounding sensitive areas, scores can be mapped based on the number and type of sensitive locations within a preset range: locations with high-risk sensitive locations such as gas stations and chemical facilities within the preset range are mapped to higher scores; locations with densely populated locations such as schools and hospitals are mapped to medium-high scores; and locations without sensitive locations are mapped to lower scores. For scenario characteristics, mapping can be based on the risk level of the usage scenario: scenarios such as freight transportation and long-distance commuting are mapped to higher scores, while scenarios such as short-distance transportation are mapped to lower scores. For travel plan characteristics, mapping can be based on the urgency of the trip: scenarios such as emergency medical treatment are mapped to higher scores (corresponding to a longer buffer tolerance), while daily commuting is mapped to medium scores. The above mapping rules can be set and adjusted according to actual business needs.

[0043] Using the aforementioned battery example, assuming that based on the battery's historical operating data, the thermal runaway prediction algorithm outputs a thermal runaway probability of 0.25 (i.e., 25%); the current scenario is characterized as "urban commuting," and according to the mapping rules, the corresponding scenario risk level is medium, with a mapping score of 0.5; there is a primary school and a gas station within 500 meters, and according to the mapping rules, the corresponding sensitive area risk is high, with a mapping score of 0.8; the travel plan is characterized as daily commuting, with a distance of 15 kilometers, and according to the mapping rules, the corresponding urgency level is moderate, with a mapping score of 0.3. Assuming a weighted summation method is used, the weights and scores for each dimension are as follows: thermal runaway probability score 0.25 × weight 0.4 = 0.10, scene feature score 0.5 × weight 0.2 = 0.10, sensitive area score 0.8 × weight 0.25 = 0.20, and travel plan score 0.3 × weight 0.15 = 0.045. Therefore, the comprehensive risk coefficient = 0.10 + 0.10 + 0.20 + 0.045 = 0.445. Assuming a preset risk threshold of 0.40, this comprehensive risk coefficient meets the preset condition, triggering the subsequent safety margin buffer scheme and tiered power supply switching command.

[0044] When the overall risk coefficient meets preset conditions, a safety margin buffer plan is generated and a tiered power supply switching command for the battery is triggered. The safety margin buffer plan refers to a safe transition plan provided to the user based on the urgency and risk level of the current scenario after the overall risk coefficient meets preset conditions but before the formal power outage is implemented. The safety margin buffer plan includes at least the buffer duration and handling suggestions during the buffer period: the buffer duration refers to the transition time from triggering the warning to executing the tiered power supply switching. This duration is dynamically determined based on the overall risk coefficient and scenario characteristics; the higher the overall risk coefficient, the shorter the buffer duration; the higher the urgency of the scenario, the longer the buffer duration is appropriately extended within the safety allowance. Handling suggestions during the buffer period include, but are not limited to, pushing information on available battery swapping stations or repair points along the route to the user, and advising the user to reduce speed and drive to a safe area.

[0045] Specifically, generating a safety margin buffer scheme and triggering a tiered power supply switching command for the battery includes:

[0046] Switch the battery power supply mode to emergency driving power supply mode;

[0047] In this step, the emergency driving power supply mode refers to the provision of limited power support to the vehicle by a backup power source (such as a low-voltage backup battery) after the main power supply circuit of the power battery is disconnected, enabling the vehicle to continue driving to the nearest safe stopping location at a limited speed (e.g., not exceeding 30 km / h). In this mode, the vehicle's high-power functions (such as acceleration, high-speed driving, etc.) are limited, retaining only basic low-speed driving capabilities and necessary safety functions (such as steering, braking, lights, etc.).

[0048] Based on the digital license plate, information on vehicles to be served is generated, and based on the preset vehicle-road cooperative network, the information on vehicles to be served is synchronously pushed to the rear vehicle nodes, battery swapping station nodes and battery manufacturer nodes in the vehicle-road cooperative network for coordinated scheduling.

[0049] In this step, the vehicle information to be served refers to service request information generated based on data such as battery code, battery specifications, and vehicle information recorded in the digital license plate. This information is used to notify relevant nodes in the vehicle-road cooperative network to coordinate a response. Specifically, upon receiving the information, the following vehicle node can take avoidance or deceleration actions in advance; upon receiving the information, the battery swapping station node can prepare a backup battery that matches the specified battery specifications to shorten the waiting time after the user arrives; and upon receiving the information, the battery manufacturer node can initiate pre-processing preparations for the faulty battery.

[0050] It should be noted that information dissemination in the vehicle-road cooperative network can be achieved through V2X (Vehicle-to-Everything) communication technology, including but not limited to V2V (vehicle-to-vehicle) and V2I (vehicle-to-infrastructure) communication methods. The scope of cooperative scheduling can be adjusted according to the actual network coverage.

[0051] In response to the battery-powered vehicle reaching a safe parking position, the battery power supply mode is switched from emergency driving power supply mode to safe parking power supply mode;

[0052] In this step, the safe parking power supply mode refers to the low-power power supply state after the vehicle has reached a safe position. In this mode, only the necessary safety indication functions (such as hazard warning lights, central control display, etc.) are retained to reduce the power consumption of the backup power supply.

[0053] If no rescue confirmation signal is received within a preset time, the battery power supply mode will be switched from safe parking power supply mode to low-power rescue waiting power supply mode.

[0054] In this step, the preset duration can be set according to the actual rescue response capability, for example, 10 minutes. The low-power rescue standby power mode further reduces power consumption, maintaining only the minimum communication and location beacon functions to extend the backup power's runtime, for example, extending the power supply runtime to 120 minutes, thereby providing ample time for rescue to arrive.

[0055] Using the aforementioned battery example, the battery's overall risk coefficient is 0.445, exceeding the risk threshold of 0.40, triggering a tiered power supply switch. First, the main power supply circuit of the power battery is disconnected, and the vehicle switches to emergency driving power mode, traveling at a speed not exceeding 30 km / h. Simultaneously, based on the digital license plate, information about the vehicle awaiting service is generated (including battery code "BAT-2026-00583", battery specification 72V35Ah, estimated arrival location, etc.), and pushed via the V2X network to following vehicles, the nearest battery swapping station, and battery manufacturer Company A. Upon receiving the information, the battery swapping station prepares a 72V35Ah backup battery in advance. After user Zhang drives to the nearest safe parking point, the power supply mode automatically switches to safe parking power mode, retaining only the hazard warning lights and central control display. If no rescue confirmation signal is received within 10 minutes, the power supply mode further switches to low-power rescue waiting power mode, extending the backup power range to approximately 120 minutes. All the above-mentioned handling data is updated in real-time to the battery's digital license plate.

[0056] The above solution enables scenario-based risk assessment and tiered emergency response based on multi-dimensional data, and links early warning and handling data to digital license plates in real time, providing traceable data records for subsequent liability determination and recovery and disposal.

[0057] After completing the early warning and emergency response phases during battery operation, the method proceeds to the recycling phase for faulty batteries determined to need to be taken out of service. The primary challenge in the recycling phase is verifying the battery's true identity to prevent forgery such as swapping casings or altering coding. To address this, this application introduces an identity verification method based on the battery's internal data fingerprint.

[0058] return Figure 1 In step S4, during the battery recycling phase, the digital license plate bound to the physical code of the battery is retrieved, and the historical operating data associated with the digital license plate is extracted to generate the internal data fingerprint of the battery; the battery is then verified for identity through the internal data fingerprint of the battery.

[0059] In this step, the battery's internal data fingerprint refers to a set of data features that reflect the individual characteristics of the battery, constructed based on the historical operating data accumulated during its use. Since each battery experiences different charging and discharging conditions, temperature environments, and aging paths in actual use, its historical operating data is unique and can therefore serve as the "intrinsic fingerprint" of the battery's identity.

[0060] Historical battery operating data includes charge / discharge curve features, temperature change trend features, and historical internal resistance features; historical battery operating data associated with digital license plates is retrieved to generate internal battery data fingerprints, including: extracting charge / discharge curve features, temperature change trend features, and historical internal resistance features to construct internal battery data fingerprints.

[0061] Specifically, charge-discharge curve characteristics refer to the morphological characteristics of the voltage-capacity curves recorded during each charge-discharge cycle. Different batteries exhibit distinct individual differences in their charge-discharge curves due to variations in cell consistency and aging levels. Temperature change trend characteristics refer to the regularity of temperature changes over time during battery operation. Influenced by the internal thermal resistance distribution and usage conditions, different batteries exhibit different temperature response patterns. Historical internal resistance characteristics refer to the sequence of changes in internal resistance values ​​measured at multiple time points. The trend of internal resistance changes reflects the battery's aging path, which varies among different batteries due to differences in usage conditions.

[0062] The three features mentioned above together constitute the battery's internal data fingerprint. This fingerprint can be constructed by extracting features from the charge / discharge curve, temperature change trend, and historical internal resistance separately and combining them into a multi-dimensional feature set. Alternatively, the features can be concatenated into a feature vector or stored in a structured record format. During identity verification, one or more features can be selected and compared with the current detection data based on the on-site testing conditions. Historical internal resistance features, due to their convenient detection method (only a portable internal resistance testing device is needed to quickly obtain current internal resistance data on-site), can be used as the primary comparison dimension for identity verification. Charge / discharge curve features and temperature change trend features can be used as auxiliary comparison dimensions when more complete testing conditions are available, further improving the reliability of verification.

[0063] Battery identification is performed using internal data fingerprints, including:

[0064] Obtain the current internal resistance data of the battery;

[0065] The current internal resistance data is compared with the historical internal resistance characteristics in the battery's internal data fingerprint to obtain the internal resistance deviation value.

[0066] If the internal resistance deviation value is within the preset range and the consistency verification between the physical code and the digital license plate is passed, the identity verification is deemed to be successful.

[0067] In response to an internal resistance deviation exceeding a preset threshold range, an abnormal alarm command is triggered and the battery recycling process is frozen.

[0068] In this step, the current internal resistance data of the battery can be obtained through real-time detection at the recycling site using a portable internal resistance detection device. The internal resistance deviation value refers to the degree of difference between the current internal resistance data and the most recent internal resistance value recorded in the historical internal resistance characteristics, and can be expressed as absolute deviation, percentage deviation, etc. The preset range and preset threshold range can be set according to the battery type and the internal resistance detection accuracy. For example, an internal resistance deviation value not exceeding 5% can be set as being within the preset range, and an internal resistance deviation value exceeding 5% can be set as exceeding the preset threshold range.

[0069] It should be noted that the consistency verification of physical codes and digital license plates refers to verifying whether the digital license plate information corresponding to the physical code on the battery body is consistent with the license plate information stored in the data management platform, in order to rule out the possibility of physical codes being copied or forged. Identity verification combines internal data fingerprints with external code verification, forming a "dual internal and external verification" verification method: even if the battery's external casing or code is forged or replaced, its internal data fingerprint, because it relies on historical data accumulation during the actual use of the battery, cannot be imitated or tampered with.

[0070] Using the aforementioned battery example, during the recycling phase, the battery's physical code "BAT-2026-00583" is scanned to retrieve its digital license plate and extract historical operating data. Based on this data, the battery's charge-discharge curve exhibits capacity decay characteristics after 800 cycles, and its temperature trend shows a stable pattern with a temperature rise of approximately 8°C at the end of charging. The most recently recorded internal resistance value is 22 mΩ. An internal data fingerprint of the battery is constructed based on these characteristics. Subsequently, a portable internal resistance testing device is used to perform on-site testing, measuring the current internal resistance to be 22.8 mΩ. Comparing the current internal resistance of 22.8 mΩ with the historical internal resistance of 22 mΩ, the deviation is approximately 3.6%, within the preset 5% range; simultaneously, the consistency verification between the physical code and the digital license plate is successful, therefore, the battery's identity verification is deemed successful. If we assume another scenario, and the measured internal resistance is 30mΩ, the internal resistance deviation is approximately 36.4%, which exceeds the preset threshold range. This indicates that the battery may have had its casing replaced or its coding tampered with. In this case, an abnormal alarm is triggered and the recycling process is frozen.

[0071] By utilizing the historical operating data naturally accumulated during battery use as the basis for identity verification, the above scheme can effectively identify battery counterfeiting and provide a reliable identity foundation for subsequent residual value assessment and resource disposal.

[0072] After the battery identity verification is successful, the method proceeds to the residual value assessment and resource recovery path matching stage. The purpose of this stage is to match an appropriate subsequent disposal method based on the actual condition of the battery, thereby avoiding resource mismatch.

[0073] return Figure 1 In step S5, only when identity verification is passed, multi-source data is retrieved to perform residual value assessment on the battery, and the corresponding resource disposal path is matched according to the result of the residual value assessment.

[0074] In this step, passing identity verification is a prerequisite for residual value assessment. This is to ensure that the object of subsequent assessment and disposal is indeed the real battery corresponding to the digital license plate, thereby guaranteeing the credibility of the residual value assessment results.

[0075] Specifically, the process involves retrieving multi-source data to assess the residual value of the battery, and then matching the corresponding resource recovery and disposal path based on the assessment results. This includes the following steps:

[0076] Input multi-source data into a preset residual value assessment model to obtain the battery's residual value pre-assessment results;

[0077] In this step, the residual value assessment model refers to a predictive model that assesses the current remaining value of the battery based on multi-source battery data. The input to the residual value assessment model includes at least historical battery operating data (such as cumulative cycle count, capacity decay rate, internal resistance growth rate, etc.) and initial battery parameters (such as rated capacity, cathode material, etc.). The output of the residual value assessment model is the preliminary residual value assessment result, used to characterize the current level of remaining usable value of the battery. The preliminary residual value assessment result can include multiple assessment indicators, such as the ratio of remaining capacity to rated capacity, the internal resistance growth rate (the proportion of current internal resistance growth relative to initial internal resistance), etc., or these multiple indicators can be combined into a residual value score or residual value grade. The residual value assessment model can employ machine learning models (such as regression models, gradient boosting trees, etc.) or assessment models based on physical degradation mechanisms; the specific model type is not limited.

[0078] In response to the residual value pre-assessment results meeting the preset tiered utilization standards, the corresponding resource disposal path is matched as a tiered utilization path, and a transaction matching instruction pointing to the tiered utilization demand node is generated based on the residual value pre-assessment results.

[0079] In response to the fact that the residual value pre-assessment results do not meet the tiered utilization standard, the corresponding resource disposal path is matched as a dismantling and recycling path, and a scheduling and allocation instruction is generated based on the residual value pre-assessment results, pointing to the nodes of the dismantling and recycling demand party.

[0080] In this step, the cascade utilization standard refers to the conditions that batteries must meet for cascade utilization, such as remaining capacity not being less than a certain percentage of rated capacity (e.g., 60%) and internal resistance growth not exceeding a certain multiple of the initial internal resistance. Cascade utilization demand-side nodes refer to entities that require batteries for cascade utilization, such as energy storage companies and low-speed electric vehicle manufacturers. Dismantling and recycling demand-side nodes refer to entities with battery dismantling and material recycling qualifications, such as cathode material recycling companies. The transaction matching instruction is used to match the residual value assessment information of the batteries with the needs of cascade utilization demand-side nodes; the scheduling and allocation instruction is used to allocate batteries to corresponding dismantling and recycling companies.

[0081] It should be noted that after the transaction matching instruction and the scheduling and allocation instruction are generated, they are pushed to the corresponding demand-side nodes through the data management platform. For the transaction matching instruction, after receiving the matching request containing battery residual value assessment information (such as remaining capacity, internal resistance status, positive electrode material, etc.), the demand-side node can confirm or reject it according to its own needs. Once confirmed, the matching and connection are completed. For the scheduling and allocation instruction, the data management platform automatically completes the allocation based on the battery dismantling and recycling needs and the processing capacity and geographical location of each dismantling and recycling demand-side node, and notifies the corresponding dismantling and recycling company to prepare for receipt.

[0082] Batteries are recycled and disposed of according to resource recovery and disposal pathways, including:

[0083] Based on the matched resource disposal path and the corresponding demand node location, the multi-point along-the-way collection algorithm is invoked to plan the physical recycling route for the target recycling vehicle.

[0084] In this step, the multi-point along-the-route collection algorithm refers to integrating the pickup location of the target battery with other battery pickup locations along the same route when planning the recycling vehicle's route, thus planning an optimized route that can collect multiple batteries along the same path. Specifically, other battery pickup locations can be searched within a preset range (e.g., within 3 kilometers) of the target pickup location, and multiple pickup locations that meet the along-the-route condition can be included in the same recycling route to reduce the empty driving distance of the recycling vehicle and the number of individual trips. The multi-point along-the-route collection algorithm can be implemented based on route optimization methods such as shortest path algorithms and traveling salesman problem solving algorithms.

[0085] Using the aforementioned battery example, after the battery's identity verification is successful, its multi-source data (cumulative cycle count of 800, current internal resistance of 22.8 mΩ, initial internal resistance of 15 mΩ, rated capacity of 72V35Ah, cathode material of ternary lithium, etc.) is input into the residual value assessment model. Assume the model's output residual value pre-assessment results indicate that the battery's remaining capacity is approximately 68% of its rated capacity, and the internal resistance growth rate is approximately 52%. If the preset tiered utilization standard is that the remaining capacity is not less than 60% and the internal resistance growth does not exceed 80%, then the battery meets the tiered utilization standard, the resource disposal path is matched to the tiered utilization path, and a transaction matching instruction is generated pointing to a certain energy storage company (tiered utilization demand node). Subsequently, a multi-point along-the-way collection algorithm is invoked to search for other batteries to be recycled within a 3-kilometer radius of the battery's pickup location. Assuming there are two batteries to be recycled in the same direction, the three pickup locations are integrated into an optimized recycling route, which is then collected in one go by a recycling vehicle.

[0086] If we assume another scenario, where the remaining capacity of the battery is only 45% of its rated capacity, which does not meet the standard for cascade utilization, then the resource disposal path is matched to the dismantling and recycling path, generating a scheduling and allocation instruction pointing to a certain cathode material recycling company (the node for dismantling and recycling demand).

[0087] Based on the residual value assessment results, the above scheme matched a suitable resource disposal path for the battery and optimized the transportation efficiency of physical recycling through a multi-point along-the-way collection algorithm.

[0088] After the battery has been disposed of as a resource, the method enters the value closed-loop realization stage. The core of this stage is to use a digital acceptance report as the confirmation of the completion of resource disposal, and to link the unlocking of value-added rights with the actual completion status of resource disposal, so as to avoid issuing rights in advance if disposal is not completed or acceptance is not passed.

[0089] return Figure 1 In step S6, the battery is recycled and disposed of according to the resource recovery and disposal path. Only after a digital acceptance report based on the resource recovery and disposal path is generated and synchronized to the corresponding digital license is the value-added rights associated with the digital license unlocked.

[0090] In this step, the digital acceptance report refers to an electronic report generated after the battery has completed its resource recovery process (cascade utilization testing or dismantling and recycling acceptance), recording information such as the recovery method, results, and time. The unlocking of value-added benefits is only triggered after the digital acceptance report is generated and synchronized to the corresponding digital license. This mechanism constitutes a three-dimensional locking relationship of "status-authority-value": the "status" of the battery's resource recovery determines the "authority" for issuing value-added benefits, and the unlocking of authority triggers the allocation of "value."

[0091] Unlocking the value-added benefits associated with this digital license includes the following steps:

[0092] Obtain data on battery fulfillment time and recycling completion rate during the recycling and disposal process;

[0093] In this step, the fulfillment time data refers to the actual time taken from when the battery enters the recycling process to when resource recovery is completed. The recycling completion rate data refers to the actual completion rate of each stage in the resource recovery process, such as whether recycling and transportation are completed on time, and whether all cascade utilization testing or dismantling acceptance meets the standards.

[0094] The contract fulfillment time data, recycling completion rate data, and digital acceptance report are stored on the pre-set consortium blockchain via smart contracts;

[0095] In this step, the consortium blockchain refers to a blockchain network jointly maintained by multiple parties involved in battery lifecycle governance (such as battery manufacturers, recycling companies, and regulatory agencies). By storing the aforementioned data on the blockchain through smart contracts, compensation data, disposal records, and credit changes become traceable and tamper-proof, supporting traceability and verification by all participating parties and regulatory agencies.

[0096] Based on the smart contract of the consortium blockchain, an ecological credit score is calculated and generated according to the performance time data and recycling completion rate data, and a corresponding environmental protection score is generated.

[0097] In this step, the eco-credit score refers to a credit indicator used to quantitatively evaluate a manufacturer's performance in the battery recycling and disposal process. The eco-credit score can be calculated based on preset scoring rules, such as assigning different scores to different time intervals based on fulfillment time data (e.g., a first score is given for completion within a first preset time period, and a second score is given for completion within a second preset time period, with the first score being higher than the second score); and based on recycling completion rate data, a higher completion rate corresponds to a higher score. The eco-credit score can serve as a credit credential for manufacturers in subsequent business, such as influencing their order priority and adjusting deposit ratios. Environmental points are points issued to battery users, who can redeem certain benefits, such as battery swapping discounts and charging incentives. Environmental points can be calculated based on the battery's resource recovery method and disposal results. For example, for batteries disposed of through tiered utilization, environmental points can be calculated by multiplying the battery's rated capacity by a preset unit point coefficient; for batteries disposed of through dismantling and recycling, environmental points can be calculated by multiplying the weight of recyclable materials in the battery by the corresponding unit point coefficient. Specific point calculation rules can be set according to actual business needs.

[0098] In response to the synchronous completion status of the digital acceptance report, a preset three-dimensional lock-and-unlock mechanism is triggered to allocate ecological credit points to the manufacturer nodes associated with the digital license and environmental protection points to the user accounts associated with the digital license.

[0099] Using the aforementioned battery example, after the battery undergoes tiered utilization testing, a digital acceptance report is generated. The report records: the disposal method is tiered utilization, the test result is qualified, and the disposal completion time is 18 hours after the recycling process is started. After the digital acceptance report is synchronized to the battery's digital license plate, the three-dimensional lock-unlock mechanism is triggered. Subsequently, the fulfillment time data (18 hours), recycling completion rate data (100% completion), and the digital acceptance report are stored on the blockchain via a smart contract. According to the preset scoring rules, assuming that fulfillment is completed within 24 hours, a credit score of 10 is given, and a recycling completion rate of 100% is given a credit score of 15, then the ecological credit score generated for this disposal is 25 points, which is allocated to the manufacturer node of battery manufacturer A. At the same time, according to the calculation rules of environmental protection points, assuming that the unit point coefficient for tiered utilization disposal is 2 points per Ah, and the rated capacity of this battery is 35Ah, then the generated environmental protection points are 35×2=70 points, which are allocated to user Zhang's user account.

[0100] The above scheme binds the unlocking of value-added rights to the actual completion status of resource disposal, and ensures the traceability of data throughout the entire process through blockchain storage.

[0101] Building upon step S6 above, the resource recovery and disposal of the battery have been completed and the added value has been unlocked. However, the data accumulated throughout the battery's lifecycle still has value for further exploration and reuse. On one hand, the resource recovery process itself generates quantifiable environmental benefits (such as carbon emission reductions), which can serve as the basis for accounting in scenarios such as carbon trading. On the other hand, after aggregation and analysis, a large amount of battery lifecycle data can provide data support for cross-industry applications such as battery design optimization, insurance rate setting, and industry regulation. Therefore, this application further proposes that after generating a digital acceptance report based on the resource recovery and disposal path, the method also includes:

[0102] Based on the resource recovery and disposal pathways and the material parameters of the batteries, the estimated carbon emission reduction during the recycling and disposal process of the batteries is calculated.

[0103] In this step, the carbon emission reduction estimate refers to the estimated amount of carbon emissions reduced through resource-based disposal methods such as cascade utilization or dismantling and recycling, compared to a baseline scenario where the battery is not disposed of in a standardized manner. The carbon emission reduction estimate can be calculated based on the battery's material parameters (such as cathode material type, total battery weight, and content of key materials) and the resource-based disposal method adopted, referring to a preset carbon emission factor. Specifically, the carbon emission reduction estimate can be calculated as follows: based on the content of each key material in the battery, multiply each by the unit carbon emission difference between obtaining the material through resource recycling and obtaining it through ore refining (i.e., the carbon emission factor), and then sum the carbon emission reduction amounts of each material to obtain the estimated carbon emission reduction for the battery. For example, ternary lithium batteries recover metals such as nickel, cobalt, and manganese through dismantling and recycling. Compared to refining these metals from ore, this reduces carbon emissions to a certain extent; this reduction is the estimated carbon emission reduction. For batteries using a cascaded utilization path, the estimated carbon emission reduction can be calculated based on the carbon emissions required to produce new batteries that are replaced by the extended lifespan of the batteries from cascaded utilization. Carbon emission factors can be set with reference to industry standards or data in relevant databases.

[0104] The carbon emission reduction forecast is written into the digital acceptance report and a digital resource pass is generated to serve as the accounting voucher for carbon trading data.

[0105] In this step, the digital resource pass refers to an electronic certificate that is generated based on the digital acceptance report and contains environmental benefit data such as carbon emission reduction estimates. This certificate can be used as the basic accounting data for manufacturers to participate in carbon trading.

[0106] Extract multi-source data associated with digital license plates and digital acceptance reports to construct a battery risk map and value regeneration model;

[0107] In this step, the battery risk map refers to a knowledge graph constructed based on the digital license data of multiple batteries, reflecting the failure modes and risk distribution characteristics of batteries of different types and under different usage conditions. The value recycling model refers to a model constructed based on the resource disposal data of multiple batteries, used to predict and evaluate the residual value and resource recovery benefits of batteries. By aggregating and analyzing a large amount of battery lifecycle data, it is possible to uncover the common patterns of battery failures and the influencing factors of resource recovery value.

[0108] The battery risk map and value regeneration model are made available to pre-defined authorized nodes to provide data asset application services.

[0109] In this step, authorized nodes refer to data users who have been authorized and licensed, including but not limited to: battery manufacturers (who can use high-frequency failure mode data in the battery risk map to optimize the design and manufacturing process of new batteries), insurance institutions (who can use historical failure probability data in the battery risk map to assist in formulating battery insurance rate schemes), and regulatory authorities (who can use data in the battery risk map and value recycling model as a reference for formulating battery safety governance and resource recycling policies). By opening up the above data and models to authorized nodes, cross-industry reuse of battery lifecycle data can be achieved, transforming data from a single management tool into a data asset with application value.

[0110] Using the aforementioned battery example, after the battery completes its cascade utilization disposal, based on its material parameters (ternary lithium, battery weight 12kg, nickel-cobalt-manganese content, etc.) and the resource-based disposal method of cascade utilization, the estimated carbon emission reduction is approximately 15kg CO2 equivalent. This carbon emission reduction estimate is written into the digital acceptance report, and a digital resource utilization pass is generated accordingly. Furthermore, the battery's full lifecycle data (operational data, fault records, disposal data, etc.), along with the digital acceptance report, are incorporated into the data used to construct the battery risk map and value regeneration model. For example, the record of the battery triggering a warning due to its comprehensive risk coefficient exceeding the threshold after 800 cumulative cycles is included in the risk map as a risk sample; its qualified cascade utilization test results and 68% remaining capacity data are included in the value regeneration model as a value regeneration sample. The aforementioned maps and models can be made available to authorized battery manufacturers, insurance institutions, and regulatory authorities to provide data asset application services.

[0111] In summary, the battery safety governance and value regeneration method proposed in this application establishes a dual identity for batteries—a physical code and a digital license—and uses the digital license as the core data carrier. This streamlines the entire governance process, from multi-source data collection, scenario-based risk assessment and tiered emergency response, identity verification based on internal data fingerprints, residual value assessment and resource-based disposal path matching, to unlocking value-added rights and applying data assets. Throughout this process, all business data is associated with, stored, and updated with the digital license, enabling data traceability and querying at every stage of the battery's lifecycle.

[0112] Exemplary system:

[0113] Figure 2The illustration depicts a battery safety management and value regeneration system according to an embodiment of this application, comprising: an identity coding module for assigning a unique physical code to a battery and generating a digital license plate uniquely bound to the physical code; a data collection module for acquiring multi-source data of the battery and storing it in association with the corresponding digital license plate, the multi-source data including at least: battery historical operating data, external environment perception data, and user behavior characteristic data; and a risk management module for performing scenario-based risk assessment based on the multi-source data associated with the corresponding digital license plate during the battery's operation phase; when the result of the scenario-based risk assessment meets preset conditions, a safety margin buffer scheme is generated and a graded power supply switching instruction for the battery is triggered, and the safety margin buffer scheme is associated with the graded power supply switching instruction for the battery. The execution record of the power supply switching command is updated to the digital license plate; the identity verification module is used to retrieve the digital license plate bound to the physical code of the battery during the battery recycling stage, and extract the historical operation data associated with the digital license plate to generate the internal data fingerprint of the battery; the battery identity is verified by the internal data fingerprint of the battery; the residual value assessment module is used to retrieve multi-source data to assess the residual value of the battery only when the identity verification is passed, and match the corresponding resource disposal path according to the result of the residual value assessment; the resource disposal module is used to recycle and dispose of the battery according to the resource disposal path, and unlock the value-added rights associated with the digital license plate only after a digital acceptance report based on the resource disposal path is generated and synchronized to the corresponding digital license plate.

[0114] In one example, the external environment perception data includes at least the distribution characteristics of surrounding sensitive areas, and the user behavior characteristic data includes at least travel plan characteristics and scenario characteristics. The scenario-based risk assessment specifically includes: predicting the probability of battery thermal runaway based on the battery's historical operating data; quantifying the travel plan characteristics, scenario characteristics, distribution characteristics of surrounding sensitive areas, and probability of battery thermal runaway, and calculating the comprehensive risk coefficient as the result of the scenario-based risk assessment.

[0115] In one example, a safety margin buffer scheme is generated and a tiered power supply switching command for the battery is triggered, including: switching the battery power supply mode to emergency driving power supply mode; generating information about vehicles to be served based on digital license plates, and synchronously pushing the information to rear vehicle nodes, battery swapping station nodes, and battery manufacturer nodes in the vehicle-road cooperative network for coordinated scheduling based on a preset vehicle-road cooperative network; switching the battery power supply mode from emergency driving power supply mode to safe parking power supply mode in response to the vehicle carrying the battery arriving at a safe parking location; and switching the battery power supply mode from safe parking power supply mode to low-power rescue waiting power supply mode in response to no rescue confirmation signal received within a preset time.

[0116] In one example, the battery's historical operating data includes charge-discharge curve features, temperature change trend features, and historical internal resistance features; the battery's historical operating data associated with the digital license plate is retrieved to generate the battery's internal data fingerprint, including: extracting charge-discharge curve features, temperature change trend features, and historical internal resistance features to construct the battery's internal data fingerprint.

[0117] In one example, battery identity verification is performed using the battery's internal data fingerprint, including: obtaining the battery's current internal resistance data; comparing the current internal resistance data with historical internal resistance features in the battery's internal data fingerprint to obtain an internal resistance deviation value; determining that identity verification is successful if the internal resistance deviation value is within a preset range and the consistency verification between the physical code and the digital license plate is passed; and triggering an abnormal alarm command and freezing the battery recycling and disposal process if the internal resistance deviation value exceeds a preset threshold range.

[0118] In one example, multi-source data is retrieved to assess the residual value of the battery, and the corresponding resource disposal path is matched based on the residual value assessment results. This includes: inputting multi-source data into a preset residual value assessment model to obtain the battery's residual value pre-assessment result; in response to the residual value pre-assessment result meeting the preset tiered utilization standard, matching the corresponding resource disposal path as a tiered utilization path, and generating a transaction matching instruction pointing to the tiered utilization demand node based on the residual value pre-assessment result; in response to the residual value pre-assessment result not meeting the tiered utilization standard, matching the corresponding resource disposal path as a dismantling and recycling path, and generating a scheduling and allocation instruction pointing to the dismantling and recycling demand node based on the residual value pre-assessment result.

[0119] In one example, the battery is recycled and disposed of according to the resource disposal path, including: according to the matched resource disposal path and the corresponding demand-side node location, calling the multi-point along-the-way collection algorithm to plan the physical recycling route for the target recycling vehicle.

[0120] In one example, unlocking the value-added benefits associated with the digital license includes: obtaining data on the battery's performance time and recycling completion rate during the recycling process; storing the performance time data, recycling completion rate data, and digital acceptance report on a pre-defined consortium blockchain via a smart contract; calculating an ecological credit score based on the performance time data and recycling completion rate data using the smart contract on the consortium blockchain, and generating corresponding environmental protection points; and triggering a pre-defined three-dimensional lock-unlock mechanism in response to the synchronous completion status of the digital acceptance report, allocating the ecological credit score to the manufacturer nodes associated with the digital license, and allocating the environmental protection points to the user accounts associated with the digital license.

[0121] In one example, after generating a digital acceptance report based on the resource recovery and disposal path, the method further includes: calculating the estimated carbon emission reduction of the battery during the recycling and disposal process based on the resource recovery and disposal path and the material parameters corresponding to the battery; writing the estimated carbon emission reduction into the digital acceptance report and generating a digital resource recovery pass as an accounting voucher for carbon trading data; extracting multi-source data associated with the digital license and the digital acceptance report to construct a battery risk map and value regeneration model; and opening the battery risk map and value regeneration model to preset authorized nodes to provide data asset application services.

[0122] Exemplary electronic device:

[0123] Figure 3 A block diagram of an electronic device according to an embodiment of this application is illustrated.

[0124] like Figure 3 As shown, the electronic device includes one or more processors and memory.

[0125] A processor can be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.

[0126] The memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0127] In one example, the electronic device may also include input devices and output devices, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0128] Of course, for the sake of simplicity, Figure 3 Only some of the components of the electronic device relevant to this application are shown in this illustration; components such as buses, input / output interfaces, etc., are omitted. In addition, the electronic device may include any other suitable components depending on the specific application.

[0129] Exemplary computer-readable medium:

[0130] Embodiments of this application may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps described in the "Exemplary Methods" section above according to the various embodiments of this application.

[0131] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0132] The basic principles of this application have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not restrict the application from being implemented using the specific details described above.

[0133] The block diagrams of devices, apparatuses, devices, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0134] It should also be noted that in the apparatus, equipment, and methods of this application, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions of this application.

[0135] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0136] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for battery safety management and value recovery, characterized in that, include: Assign a unique physical code to the battery and generate a digital license plate that is uniquely bound to the physical code; The battery's multi-source data is acquired and associated with and stored in the corresponding digital license plate. The multi-source data includes at least: battery historical operation data, external environment perception data, and user behavior characteristic data. During the operation of the battery, a scenario-based risk assessment is performed based on the multi-source data associated with the digital license plate. When the result of the scenario-based risk assessment meets the preset conditions, a safety margin buffer scheme is generated and a graded power supply switching instruction for the battery is triggered. The execution records of the safety margin buffer scheme and the graded power supply switching instruction are then updated to the digital license plate. During the battery recycling phase, the digital license plate bound to the physical code of the battery is retrieved, and the historical operating data associated with the digital license plate is extracted to generate an internal data fingerprint of the battery; the battery is then verified for identity through the internal data fingerprint of the battery. Only when the identity verification is passed, the multi-source data is retrieved to perform a residual value assessment on the battery, and the corresponding resource disposal path is matched according to the result of the residual value assessment. Batteries are recycled and disposed of according to the resource recovery and disposal path. Only after a digital acceptance report based on the resource recovery and disposal path is generated and synchronized to the corresponding digital license will the value-added rights associated with the digital license be unlocked.

2. The battery safety management and value recovery method according to claim 1, characterized in that, The external environment perception data includes at least the distribution characteristics of surrounding sensitive areas, and the user behavior characteristic data includes at least travel plan characteristics and scenario characteristics. The scenario-based risk assessment specifically includes: Predict the probability of battery thermal runaway based on the battery's historical operating data; The travel plan characteristics, scenario characteristics, distribution characteristics of surrounding sensitive areas, and probability of battery thermal runaway are quantified, and a comprehensive risk coefficient is calculated as the result of the scenario-based risk assessment.

3. The battery safety management and value recovery method according to claim 1, characterized in that, The generation of the safety margin buffer scheme and the triggering of the battery's graded power supply switching command include: Switch the battery's power supply mode to emergency driving power supply mode; Based on the digital license plate, information on vehicles to be served is generated, and based on the preset vehicle-road cooperative network, the information on vehicles to be served is synchronously pushed to the rear vehicle nodes, battery swapping station nodes and battery manufacturer nodes in the vehicle-road cooperative network for coordinated scheduling. In response to the vehicle equipped with the battery reaching a safe parking position, the power supply mode of the battery is switched from the emergency driving power supply mode to the safe parking power supply mode; If no rescue confirmation signal is received within a preset time period, the power supply mode of the battery is switched from the safe parking power supply mode to the low-power rescue waiting power supply mode.

4. The battery safety management and value recovery method according to claim 1, characterized in that, The battery's historical operating data includes charge / discharge curve characteristics, temperature change trend characteristics, and historical internal resistance characteristics. The step of retrieving the battery's historical operating data associated with the digital license plate to generate the battery's internal data fingerprint includes: extracting the charge-discharge curve features, the temperature change trend features, and the historical internal resistance features to construct the battery's internal data fingerprint. The step of verifying the identity of the battery through the internal data fingerprint of the battery includes: Obtain the current internal resistance data of the battery; The current internal resistance data is compared with the historical internal resistance features in the battery internal data fingerprint to obtain the internal resistance deviation value; In response to the internal resistance deviation value being within a preset range, and the consistency verification between the physical code and the digital license plate being passed, the identity verification is determined to be passed; In response to the internal resistance deviation value exceeding the preset threshold range, an abnormal alarm command is triggered and the battery recycling process is frozen.

5. The battery safety management and value recovery method according to claim 1, characterized in that, The step of retrieving the multi-source data to perform residual value assessment on the battery, and matching the corresponding resource recovery disposal path based on the residual value assessment results, includes: The multi-source data is input into a preset residual value assessment model to obtain the residual value pre-assessment result of the battery; In response to the residual value pre-assessment result meeting the preset tiered utilization standard, the corresponding resource disposal path is matched as a tiered utilization path, and a transaction matching instruction pointing to the tiered utilization demand node is generated based on the residual value pre-assessment result. In response to the fact that the residual value pre-assessment result does not meet the tiered utilization standard, the corresponding resource disposal path is matched as a dismantling and recycling path, and a scheduling and allocation instruction pointing to the dismantling and recycling demand node is generated based on the residual value pre-assessment result. The recycling and disposal of batteries according to the resource recovery and disposal path includes: Based on the matched resource disposal path and the corresponding demand-side node location, the multi-point along-the-way collection algorithm is invoked to plan the physical recycling route for the target recycling vehicle.

6. The battery safety management and value recovery method according to claim 1, characterized in that, The unlocking of the value-added rights associated with the digital license includes: Obtain the fulfillment time data and recycling completion rate data of the battery during the recycling and disposal process; The performance time data, the recycling completion rate data, and the digital acceptance report are stored on the pre-set consortium blockchain via smart contracts. Based on the smart contract of the consortium blockchain, an ecological credit score is calculated and generated according to the performance time data and the recycling completion rate data, and a corresponding environmental protection score is generated. In response to the synchronous completion status of the digital acceptance report, a preset three-dimensional lock-unlock mechanism is triggered to allocate the ecological credit points to the manufacturer nodes associated with the digital license, and the environmental protection points to the user accounts associated with the digital license.

7. The battery safety management and value recovery method according to claim 1, characterized in that, After generating a digital acceptance report based on the aforementioned resource disposal path, the method further includes: Based on the resource recovery and disposal path and the material parameters of the battery, the estimated carbon emission reduction of the battery during the recycling and disposal process is calculated. The estimated carbon emission reduction is written into the digital acceptance report and a digital resource pass is generated to serve as the accounting voucher for carbon trading data. Extract the multi-source data associated with the digital license plate and the digital acceptance report to construct a battery risk map and value regeneration model; and The battery risk map and the value regeneration model are made available to pre-defined authorized nodes to provide data asset application services.

8. A battery safety management and value recovery system, characterized in that, include: The identity coding module is used to assign a unique physical code to the battery and generate a digital license plate that is uniquely bound to the physical code; The data collection module is used to acquire multi-source data of the battery and associate and store it in the corresponding digital license plate. The multi-source data includes at least: battery historical operation data, external environment perception data and user behavior characteristic data. The risk management module is used to perform scenario-based risk assessment based on multi-source data associated with the digital license plate during the operation phase of the battery; when the result of the scenario-based risk assessment meets the preset conditions, a safety margin buffer scheme is generated and a graded power supply switching instruction for the battery is triggered, and the execution records of the safety margin buffer scheme and the graded power supply switching instruction are updated to the digital license plate. The identity verification module is used during the battery recycling stage to retrieve the digital license plate bound to the physical code of the battery and extract the historical operating data associated with the digital license plate to generate an internal data fingerprint of the battery; and to verify the identity of the battery through the internal data fingerprint of the battery. The residual value assessment module is used to retrieve the multi-source data to assess the residual value of the battery only when the identity verification is passed, and to match the corresponding resource disposal path according to the result of the residual value assessment. The resource recovery and disposal module is used to recycle and dispose of batteries according to the resource recovery and disposal path. Only after a digital acceptance report based on the resource recovery and disposal path is generated and synchronized to the corresponding digital license will the value-added rights associated with the digital license be unlocked.

9. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the method as described in any one of claims 1 to 7.

10. A computer storage medium storing computer-executable instructions thereon, characterized in that: When the computer-executable instructions are executed by a processor, they implement the steps of the method as described in any one of claims 1 to 7.

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