Battery detection system and method for cloud-side collaborative battery replacement cabinet

Abstract

The invention provides a system and a method for detecting a battery of a cloud-side collaborative battery changing cabinet in the technical field of safety of battery changing cabinets. The system comprises a cloud platform; the plurality of battery changing cabinets are connected with the cloud platform; the plurality of batteries are connected with the battery changing cabinet; the battery changing cabinet comprises a battery changing cabinet control module; the plurality of battery changing cabins are connected with the battery changing cabinet control module; the plurality of battery safety detection modules are connected with the battery replacement cabins and the batteries and are respectively arranged in the battery replacement cabins; and one end of the platform docking communication module is connected with the battery changing cabinet control module, and the other end of the platform docking communication module is connected with the cloud platform. The method has the advantages that the depth, the precision and the intelligent level of battery safety detection of the battery changing cabinet are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of battery swapping cabinet safety technology, and in particular to a cloud-edge collaborative battery swapping cabinet battery detection system and method. Background Technology

[0002] Electric bicycle battery swapping stations, as a key infrastructure of urban green transportation systems, are experiencing significant development opportunities. The battery swapping station model effectively alleviates users' (especially delivery riders') anxieties about mileage (i.e., "range anxiety") while significantly improving charging safety through centralized charging and management of lithium batteries. This model centrally manages compliant batteries (such as lithium iron phosphate batteries) procured through unified procurement, replacing inferior or illegally modified batteries used by users (such as batteries assembled using recycled cells or privately upgraded batteries). This significantly reduces the risk of fires caused by unauthorized wiring, illegal indoor charging, the circulation of inferior batteries, and illegal modifications. Furthermore, battery swapping stations are typically equipped with aerosol fire suppression systems, smoke detectors, and flame-retardant compartments, enabling rapid automatic isolation and extinguishing of fires in a single battery compartment (e.g., within 30 seconds), effectively preventing the spread of fire.

[0003] However, the cloud platform supporting the current battery swapping cabinets mainly focuses on basic operations such as battery swapping service scheduling and battery static information management, and has the following key shortcomings:

[0004] 1. Lack of in-depth battery safety monitoring capabilities: The system is unable to acquire and analyze key parameters characterizing the battery's electrical properties and safety status, such as the changing trend of the battery's internal resistance and the measurement accuracy error of voltage / current.

[0005] 2. Local computing power limits complex analysis: Due to the limited local computing resources of the battery swapping cabinet, it can only achieve basic real-time status monitoring and cannot complete complex tasks that require high computing power, such as battery state of health (SOH) assessment and performance degradation trend prediction.

[0006] 3. Lack of cloud-edge collaboration mechanism: An effective closed-loop collaboration mechanism of "local perception - cloud intelligent analysis - proactive safety decision-making" has not yet been established, making it difficult to achieve forward-looking early warning of potential safety hazards of batteries and safety tracking and management throughout their entire life cycle.

[0007] Therefore, how to provide a cloud-edge collaborative battery swapping cabinet battery testing system and method to improve the depth (acquiring more core data), accuracy (improving the accuracy of status analysis), and intelligence level (achieving predictive warning and closed-loop management) of battery safety testing in battery swapping cabinets has become an urgent technical problem to be solved. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to provide a cloud-edge collaborative battery swapping cabinet battery detection system and method, so as to improve the depth, accuracy and intelligence level of battery safety detection in battery swapping cabinets.

[0009] In a first aspect, the present invention provides a cloud-edge collaborative battery swapping cabinet battery detection system, comprising:

[0010] A cloud platform;

[0011] Several battery swapping cabinets are connected to the cloud platform;

[0012] Several batteries are connected to the battery swapping cabinet;

[0013] The battery swapping cabinet includes:

[0014] A battery swapping cabinet control module;

[0015] Several battery swapping compartments are connected to the battery swapping cabinet control module;

[0016] Several battery safety detection modules are connected to the battery swapping compartment and the battery, and are respectively located in one of the battery swapping compartments;

[0017] A platform interface communication module is provided, with one end connected to the battery swapping cabinet control module and the other end connected to the cloud platform.

[0018] Furthermore, the battery is equipped with a battery power line and a battery communication line;

[0019] The battery swapping compartment is equipped with a charging power line and a charging communication line.

[0020] Furthermore, the battery safety detection module includes:

[0021] A detection controller;

[0022] A voltmeter for detecting battery voltage, with its control terminal connected to the detection controller and its detection terminal connected to the battery power line of the battery;

[0023] An ammeter for detecting the charging and discharging current of the battery, with its control terminal connected to the detection controller and its detection terminal connected to the charging power line of the battery swapping compartment;

[0024] A battery charging circuit switch for switching the battery charging circuit on and off, with the control terminal connected to the detection controller and connected in series between the battery power line of the battery and the charging power line of the battery swapping compartment;

[0025] A battery communication circuit switch for switching the battery communication circuit on and off, with the control terminal connected to the detection controller and connected in series between the battery communication line of the battery and the charging communication line of the battery swapping compartment;

[0026] An AC internal resistance detection module for detecting the AC internal resistance of a battery, wherein the control terminal is connected to the detection controller and the detection terminal is connected to the battery power line of the battery;

[0027] A sub-communication module is connected to the detection controller.

[0028] Furthermore, the battery charging circuit switch and the battery communication circuit switch are in the off state by default.

[0029] Secondly, this invention provides a battery detection method for a cloud-edge collaborative battery swapping cabinet, comprising the following steps:

[0030] Step S1: When swapping batteries, take out a fully charged battery from the battery swapping compartment of the battery swapping cabinet, put the depleted battery into the battery swapping compartment, and connect it to the battery safety detection module.

[0031] Step S2: The detection controller operates in communication data hijacking mode. The detection controller obtains the data reading command sent by the battery swapping cabinet control module through the charging communication line, and forwards the data reading command to the battery through the battery communication line; the detection controller obtains the battery charging data through the battery communication line, and forwards the charging data to the battery swapping cabinet control module through the charging communication line.

[0032] Step S3: The detection controller obtains the data monitoring command sent by the battery swapping cabinet control module through the charging communication line, closes the battery communication circuit switch based on the data monitoring command, and switches to the communication data monitoring mode to monitor the communication bus composed of the charging communication line and the battery communication line.

[0033] Step S4: The controller detects the voltage accuracy using a voltmeter;

[0034] Step S5: The detection controller closes the battery charging circuit switch, the current accuracy is detected by the ammeter, the AC internal resistance is detected by the AC internal resistance detection module, and the DC internal resistance is detected by the voltmeter and ammeter.

[0035] Step S6: The detection controller performs local safety protection operations based on the battery charging data and the monitored BMS data;

[0036] Step S7: The battery swapping cabinet control module uploads electrical performance data, status data, charging data, and identity information to the cloud platform through the platform connection communication module; the electrical performance data includes voltage accuracy, current accuracy, AC internal resistance, and DC internal resistance; the status data includes battery charging status and battery safety detection module operating status; the identity information is the battery's unique identifier.

[0037] Step S8: The cloud platform creates a full life cycle information database for the battery based on the received electrical performance data, status data, charging data, and identity information. It then performs intelligent analysis on the data stored in the full life cycle information database and conducts safety management and control of the battery swapping cabinet based on the analysis results.

[0038] Furthermore, step S2 also includes:

[0039] Before forwarding the data read command or running data, the data read command or running data is parsed and modified based on a preset communication protocol;

[0040] Step S3 further includes:

[0041] During the monitoring of the communication bus, the monitored data is parsed to obtain the battery charging data, and the charging data is sent to the battery swapping cabinet control module.

[0042] Furthermore, step S4 specifically includes:

[0043] The detection controller detects the battery voltage V11 through a voltmeter and acquires the voltage V12 from the battery BSM through the battery communication line. Based on the voltages V11 and V12, it calculates the voltage accuracy.

[0044] Furthermore, in step S5, the accuracy of current detection via ammeter specifically refers to:

[0045] The detection controller detects the battery's current curve Clist1 through an ammeter, and acquires the current curve Clist2 from the battery BSM through the battery communication line. Based on the current curves Clist1 and Clist2, it calculates the current accuracy.

[0046] The specific steps for detecting DC internal resistance using a voltmeter and an ammeter are as follows:

[0047] The detection controller modifies the battery's requested current to adjust the battery's charging current. It collects the voltage V21 and current I21 at different times using a voltmeter and an ammeter, respectively, and calculates the DC internal resistance based on the voltage V21 and current I21.

[0048] Furthermore, step S6 specifically includes:

[0049] The detection controller performs safety monitoring on battery charging data and BMS data by setting preset monitoring thresholds. When a safety event is detected, the battery charging circuit switch is disconnected to perform local safety protection operations.

[0050] Furthermore, step S8 specifically includes:

[0051] The cloud platform creates a full life cycle information database for the battery based on the received electrical performance data, status data, charging data, and identity information. The full life cycle information database is stored and dynamically updated, and the full life cycle information database supports data classification and retrieval.

[0052] The cloud platform combines big data technology and machine learning algorithms to intelligently analyze the data stored in the full lifecycle information database. Based on the analysis results, it sends control commands to the corresponding battery swapping cabinets or pushes alarm notifications to pre-associated management terminals to manage the battery swapping cabinets safely.

[0053] The advantages of this invention are:

[0054] 1. By deeply integrating multi-dimensional sensing capabilities at the edge layer with a cloud-based intelligent analysis engine, a battery safety detection module (including voltage / current / internal resistance detection units) is embedded in the battery compartment of the battery swapping cabinet to collect core electrical parameters such as battery voltage accuracy, current accuracy, and AC / DC internal resistance in real time. Simultaneously, through a dual-mode collaboration of communication data hijacking and monitoring, the system dynamically analyzes the original battery BMS data and cross-verifies it with local sensor data, significantly improving monitoring accuracy. A full lifecycle information database for batteries is built in the cloud, integrating big data and machine learning algorithms to intelligently analyze massive amounts of historical and real-time data, enabling battery health status prediction and proactive early warning of safety risks. Control commands or alarm information are then sent from the cloud platform to the edge layer (battery swapping cabinet / management terminal), forming a closed-loop management system of "local real-time protection - cloud-based intelligent decision-making," thereby greatly improving the depth, accuracy, and intelligence level of battery safety detection in the battery swapping cabinet.

[0055] 2. By adopting a collaborative architecture of cloud platform and multiple battery swapping cabinets, data interaction is achieved through platform-interfaced communication modules; edge devices (battery swapping cabinets) process local data (such as voltage and current detection), reducing dependence on the cloud platform and reducing communication latency and bandwidth consumption; the cloud platform integrates global data for analysis and achieves large-scale resource optimization, which is more efficient than a pure cloud solution and is particularly suitable for high-frequency battery swapping scenarios (such as shared electric vehicle services), improving response speed and system throughput.

[0056] 3. Each battery swapping compartment integrates a battery safety detection module (including voltmeter, ammeter, switch, etc.), which can directly perform safety monitoring locally; the detection controller can detect parameters such as voltage accuracy, current accuracy, and internal resistance in real time, and immediately disconnect the charging circuit when an abnormality is detected. This design achieves millisecond-level risk response, prevents accidents such as battery overcharging and overheating, and significantly improves safety, especially ensuring local safety during network interruptions.

[0057] 4. Through a full lifecycle information database, the system integrates electrical performance data, status data, charging data, and identity information, and applies big data and machine learning algorithms for analysis. This supports dynamic prediction of battery health status (such as changes in internal resistance indicating battery aging), facilitating the implementation of preventive maintenance and replacement strategies, and extending battery life. At the same time, the cloud platform can send control commands or push alarms based on the analysis results, optimize the safety management of the battery swapping cabinet, improve resource utilization, and reduce operating costs and unexpected downtime.

[0058] 5. By adopting modular components, including standardized voltmeters and ammeters, it is easy to deploy and maintain; the number of battery swapping cabinets can be expanded, and new equipment can be seamlessly connected to the cloud platform through the platform's communication module; in addition, the battery charging circuit switch and communication circuit switch are disconnected by default to ensure plug-and-play safety.

[0059] 6. During battery swapping, the system automatically enters data hijacking or monitoring mode after the battery is connected. It can complete accuracy detection and internal resistance calculation without manual intervention. Users only need to perform simple actions (remove / insert the battery), which improves user experience and battery swapping efficiency.

[0060] 7. By combining cloud resources and edge computing, the system optimizes resource allocation: local processing reduces cloud storage and computing overhead, while intelligent analysis can predict battery failure, avoid excessive replacement, and reduce operation and maintenance costs (such as reducing on-site inspections) and accident risks (local safety mechanisms reduce potential compensation); at the same time, the full life cycle management facilitates the tracking of battery history through classification and retrieval functions, helping decision-makers optimize procurement and retirement strategies.

[0061] 8. By introducing communication data hijacking and monitoring modes, and supporting protocol parsing and modification, data can be obtained "transparently" on the battery communication line without modifying the original battery communication protocol. This ensures data accuracy (such as the comparison calculation of voltage V11 and BMS-collected voltage V12), and is easy to adapt to different brands of batteries (good compatibility). It solves the delay problem of data interception in traditional systems and improves the real-time performance and reliability of detection.

[0062] 9. By combining a cloud-edge collaborative architecture with a localized battery safety detection module, efficient, intelligent, and safe full lifecycle management of batteries is achieved. The cloud platform is responsible for global data analysis and decision-making, while the dedicated detection module (including voltage / current / internal resistance detection units and smart switches) deployed locally in the battery swapping cabinet collects multi-dimensional data in real time during battery charging and discharging. It can execute local safety protection (such as automatic power-off in case of abnormality) with millisecond-level response, and obtain core battery parameters without loss through communication data hijacking and monitoring mechanisms. At the same time, the system aggregates data such as electrical performance and operating status into a dynamic information database (full lifecycle information database) built by the cloud platform. Relying on big data and machine learning, it realizes battery health prediction, fault warning, and resource optimization scheduling, which significantly improves battery safety, extends service life, and greatly reduces operation and maintenance costs and operational risks.

[0063] 10. Full-chain safety protection: Combining edge-side local detection and protection with cloud-based deep analysis, it achieves full-process safety management of "pre-event warning - in-event intervention - post-event traceability," overcoming the shortcomings of existing battery swapping cabinets that rely solely on post-event fire suppression; Proactive risk warning: Through trend analysis of parameters such as internal resistance and error rate, it identifies signs of battery performance degradation in advance, avoiding sudden safety accidents; Enhanced intelligence level: Utilizing cloud platform computing power to achieve big data analysis and model warning, solving the problem of insufficient edge-side computing power and improving detection accuracy (such as distinguishing between normal aging and abnormal degradation); Full battery life cycle management: Based on historical databases, it can trace the changes in the health status of each battery, optimize battery scheduling (such as prioritizing the deployment of healthy batteries) and elimination strategies (such as forcibly retiring high-risk batteries); Strong compatibility: The edge-side detection module can be adapted to the transformation of existing battery swapping cabinets, and the cloud platform can be expanded based on the existing charging management platform, reducing implementation costs. Attached Figure Description

[0064] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0065] Figure 1 This is a circuit diagram of a cloud-edge collaborative battery swapping cabinet battery detection system according to the present invention.

[0066] Figure 2 This is a circuit diagram of the battery safety detection module of the present invention.

[0067] Figure 3 This is a flowchart of a cloud-edge collaborative battery swapping cabinet battery detection method according to the present invention. Detailed Implementation

[0068] The overall approach of the technical solution in this application is as follows: Deeply integrating multi-dimensional sensing capabilities at the edge layer with a cloud-based intelligent analysis engine, a battery safety detection module is embedded within the battery compartment of the battery swapping cabinet to collect core electrical parameters such as battery voltage accuracy, current accuracy, and AC / DC internal resistance in real time. Simultaneously, through a dual-mode collaboration of communication data hijacking and monitoring, the original battery BMS data is dynamically parsed and cross-validated with local sensor data, significantly improving monitoring accuracy. A full lifecycle information database for batteries is built in the cloud, integrating big data and machine learning algorithms to intelligently analyze massive amounts of historical and real-time data, enabling prediction of battery health status and proactive warnings of safety risks. Control commands or alarm information are then sent to the edge layer via the cloud platform, forming a closed-loop management system of "local real-time protection - cloud-based intelligent decision-making," thereby improving the depth, accuracy, and intelligence level of battery safety detection in the battery swapping cabinet.

[0069] Please refer to Figures 1 to 3 As shown, a preferred embodiment of the cloud-edge collaborative battery swapping cabinet battery detection system of the present invention includes:

[0070] A cloud platform;

[0071] Several battery swapping cabinets are connected to the cloud platform;

[0072] Several batteries are connected to the battery swapping cabinet;

[0073] The battery swapping cabinet includes:

[0074] A battery swapping cabinet control module;

[0075] Several battery swapping compartments are connected to the battery swapping cabinet control module;

[0076] Several battery safety detection modules are connected to the battery swapping compartment and the battery, and are respectively located in one of the battery swapping compartments;

[0077] A platform interface communication module is provided, with one end connected to the battery swapping cabinet control module and the other end connected to the cloud platform.

[0078] The battery is equipped with a battery power line and a battery communication line;

[0079] The battery swapping compartment is equipped with a charging power line and a charging communication line.

[0080] The battery safety detection module includes:

[0081] A detection controller is responsible for collecting relevant data, controlling relevant switches, performing relevant charging protection, and carrying out electrical performance testing and safety testing, etc.

[0082] A voltmeter for detecting battery voltage, with its control terminal connected to the detection controller and its detection terminal connected to the battery power line of the battery;

[0083] An ammeter for detecting the charging and discharging current of the battery, with its control terminal connected to the detection controller and its detection terminal connected to the charging power line of the battery swapping compartment;

[0084] A battery charging circuit switch for switching the battery charging circuit on and off, with the control terminal connected to the detection controller and connected in series between the battery power line of the battery and the charging power line of the battery swapping compartment; the battery charging circuit switch is connected in series in the charging circuit of the battery swapping cabinet and the battery to realize charging protection. The left IN is connected to the charging power line of the battery swapping cabinet, and the right OUT is connected to the battery power line of the battery. It is in the off state by default, and is engaged during operation and disengaged during protection.

[0085] A battery communication circuit switch for switching the battery communication circuit on and off is connected to the detection controller and connected in series between the battery communication line of the battery and the charging communication line of the battery swapping compartment. The battery communication circuit switch is connected in series in the communication circuit between the battery swapping cabinet and the battery for switching between communication data hijacking and non-hijacking. The left IN is connected to the charging communication line of the battery swapping cabinet, and the right OUT is connected to the battery communication line of the battery. When the switch is engaged, the detection controller does not participate in the communication between the battery swapping cabinet and the battery and is in the off state by default.

[0086] An AC internal resistance detection module for detecting the AC internal resistance of a battery, wherein the control terminal is connected to the detection controller and the detection terminal is connected to the battery power line of the battery;

[0087] A sub-communication module, connected to the detection controller, is used for external communication to report data or receive control commands.

[0088] The battery charging circuit switch and the battery communication circuit switch are in the off state by default.

[0089] A preferred embodiment of the cloud-edge collaborative battery swapping cabinet battery detection method of the present invention includes the following steps:

[0090] Step S1: When swapping batteries, take out a fully charged battery from the battery swapping compartment of the battery swapping cabinet, put the depleted battery into the battery swapping compartment, and connect it to the battery safety detection module.

[0091] Step S2: The detection controller operates in communication data hijacking mode. The detection controller obtains the data reading command sent by the battery swapping cabinet control module through the charging communication line, and forwards the data reading command to the battery through the battery communication line; the detection controller obtains the battery charging data through the battery communication line, and forwards the charging data to the battery swapping cabinet control module through the charging communication line.

[0092] Step S3: The detection controller obtains the data monitoring command sent by the battery swapping cabinet control module through the charging communication line, closes the battery communication circuit switch based on the data monitoring command, and switches to the communication data monitoring mode (without the function of sending commands) to monitor the communication bus composed of the charging communication line and the battery communication line (monitoring can be performed from one side only).

[0093] Step S4: The controller detects the voltage accuracy using a voltmeter;

[0094] Step S5: The detection controller closes the battery charging circuit switch, the current accuracy is detected by the ammeter, the AC internal resistance is detected by the AC internal resistance detection module, and the DC internal resistance is detected by the voltmeter and ammeter.

[0095] Step S6: The detection controller performs local safety protection operations based on the battery charging data and the monitored BMS data;

[0096] Step S7: The battery swapping cabinet control module uploads electrical performance data, status data, charging data, and identity information to the cloud platform via the platform connection communication module. The electrical performance data includes voltage accuracy, current accuracy, AC internal resistance, and DC internal resistance. The status data includes battery charging status and battery safety detection module operating status. The identity information is the battery's unique identifier. In specific implementations, electrical performance data, status data, charging data, and identity information can also be uploaded to the cloud platform via a sub-communication module, supporting real-time upload (critical data), timed upload (trend analysis data), and event-triggered upload (abnormal status).

[0097] Step S8: The cloud platform creates a full life cycle information database for the battery based on the received electrical performance data, status data, charging data, and identity information. It then performs intelligent analysis on the data stored in the full life cycle information database and conducts safety management and control of the battery swapping cabinet based on the analysis results.

[0098] This invention integrates multiple protection functions, enabling not only post-incident protection but also proactive protection through pre-incident electrical performance and safety testing. This reduces the risk of battery thermal runaway from the source, significantly improving the safety of the battery swapping cabinet. It also enables safe charging by monitoring and protecting the charging process in real time, preventing safety accidents caused by charging anomalies.

[0099] This invention enables closed-loop management of "local detection - data upload - cloud analysis - intelligent decision-making - edge execution".

[0100] Step S2 further includes:

[0101] Before forwarding the data read command or running data, the data read command or running data is parsed and modified based on a preset communication protocol; in specific implementation, the hijacked data read command or running data may be modified or not modified.

[0102] Step S3 further includes:

[0103] During the monitoring of the communication bus, the monitored data is parsed to obtain the battery charging data, and the charging data is sent to the battery swapping cabinet control module.

[0104] Step S4 specifically involves:

[0105] The detection controller detects the battery voltage V11 using a voltmeter (the voltage across P+ and P- is obtained from the voltmeter and denoted as V11), and acquires the voltage V12 from the battery BMS via the battery communication line (there are two acquisition methods: one is that the detection controller directly issues an acquisition command and parses the BMS data in the feedback; the other is that the detection controller listens to the data on the communication bus and parses the BMS data). Based on the voltages V11 and V12, the voltage accuracy is calculated (the detection controller calculates the difference between V11 and V12 to determine whether it exceeds the abnormal range).

[0106] In step S5, the accuracy of current detection via ammeter specifically refers to:

[0107] The detection controller detects the battery's current curve Clist1 through an ammeter and acquires the current curve Clist2 from the battery BSM through the battery communication line. Based on the current curves Clist1 and Clist2, the current accuracy is calculated (the detection controller calculates the difference between Clist1 and Clist2 to determine whether it exceeds the abnormal range, or it can determine the maximum value, average value, or only the data of a few points of the entire curve).

[0108] The specific steps for detecting DC internal resistance using a voltmeter and an ammeter are as follows:

[0109] The detection controller modifies the battery's requested current to adjust the battery's charging current. Voltage V21 and current I21 are collected at different times using a voltmeter and an ammeter, respectively. The DC internal resistance is calculated based on these voltages and currents. The formula for calculating the DC internal resistance is ΔV / ΔI. In real-time, multiple data points can be detected to calculate the internal resistance curve.

[0110] Step S6 specifically involves:

[0111] The detection controller performs safety monitoring on battery charging data and BMS data based on preset monitoring thresholds. When a safety event is detected, it disconnects the battery charging circuit switch to execute local safety protection operations. Specifically, this triggers a local alarm (such as indicator light flashing) and records the abnormal event. Upon receiving a clear protection command, it then closes the battery charging circuit switch.

[0112] Step S8 specifically involves:

[0113] The cloud platform creates a full life cycle information database for the battery based on the received electrical performance data, status data, charging data, and identity information. The full life cycle information database is stored and dynamically updated. The full life cycle information database supports data classification retrieval (e.g., retrieval by battery identity information, time, test items, etc.).

[0114] The cloud platform combines big data technology and machine learning algorithms to intelligently analyze the data stored in the full lifecycle information database. Based on the analysis results, it sends control commands to the corresponding battery swapping cabinets or pushes alarm notifications to pre-associated management terminals to manage the battery swapping cabinets safely. This includes stopping battery charging, locking the battery (preventing user access), and notifying maintenance personnel for handling (via cloud platform message push).

[0115] The cloud platform can dynamically track the trends of key battery parameters, including: AC internal resistance change trend: if the increase exceeds a preset threshold (e.g., 10% / week) in a short period, it is judged as a performance degradation warning; DC internal resistance change trend: if the change rate exceeds the safe range, a safety warning is triggered; voltage / current accuracy error rate trend: if the error rate continues to expand, it is judged as a battery BMS abnormality warning. After the warning is triggered, an alarm notification is automatically generated (including battery identity, abnormal parameters, and location information).

[0116] In summary, the advantages of this invention are:

[0117] 1. By deeply integrating multi-dimensional sensing capabilities at the edge layer with a cloud-based intelligent analysis engine, a battery safety detection module (including voltage / current / internal resistance detection units) is embedded in the battery compartment of the battery swapping cabinet to collect core electrical parameters such as battery voltage accuracy, current accuracy, and AC / DC internal resistance in real time. Simultaneously, through a dual-mode collaboration of communication data hijacking and monitoring, the system dynamically analyzes the original battery BMS data and cross-verifies it with local sensor data, significantly improving monitoring accuracy. A full lifecycle information database for batteries is built in the cloud, integrating big data and machine learning algorithms to intelligently analyze massive amounts of historical and real-time data, enabling battery health status prediction and proactive early warning of safety risks. Control commands or alarm information are then sent from the cloud platform to the edge layer (battery swapping cabinet / management terminal), forming a closed-loop management system of "local real-time protection - cloud-based intelligent decision-making," thereby greatly improving the depth, accuracy, and intelligence level of battery safety detection in the battery swapping cabinet.

[0118] 2. By adopting a collaborative architecture of cloud platform and multiple battery swapping cabinets, data interaction is achieved through platform-interfaced communication modules; edge devices (battery swapping cabinets) process local data (such as voltage and current detection), reducing dependence on the cloud platform and reducing communication latency and bandwidth consumption; the cloud platform integrates global data for analysis and achieves large-scale resource optimization, which is more efficient than a pure cloud solution and is particularly suitable for high-frequency battery swapping scenarios (such as shared electric vehicle services), improving response speed and system throughput.

[0119] 3. Each battery swapping compartment integrates a battery safety detection module (including voltmeter, ammeter, switch, etc.), which can directly perform safety monitoring locally; the detection controller can detect parameters such as voltage accuracy, current accuracy, and internal resistance in real time, and immediately disconnect the charging circuit when an abnormality is detected. This design achieves millisecond-level risk response, prevents accidents such as battery overcharging and overheating, and significantly improves safety, especially ensuring local safety during network interruptions.

[0120] 4. Through a full lifecycle information database, the system integrates electrical performance data, status data, charging data, and identity information, and applies big data and machine learning algorithms for analysis. This supports dynamic prediction of battery health status (such as changes in internal resistance indicating battery aging), facilitating the implementation of preventive maintenance and replacement strategies, and extending battery life. At the same time, the cloud platform can send control commands or push alarms based on the analysis results, optimize the safety management of the battery swapping cabinet, improve resource utilization, and reduce operating costs and unexpected downtime.

[0121] 5. By adopting modular components, including standardized voltmeters and ammeters, it is easy to deploy and maintain; the number of battery swapping cabinets can be expanded, and new equipment can be seamlessly connected to the cloud platform through the platform's communication module; in addition, the battery charging circuit switch and communication circuit switch are disconnected by default to ensure plug-and-play safety.

[0122] 6. During battery swapping, the system automatically enters data hijacking or monitoring mode after the battery is connected. It can complete accuracy detection and internal resistance calculation without manual intervention. Users only need to perform simple actions (remove / insert the battery), which improves user experience and battery swapping efficiency.

[0123] 7. By combining cloud resources and edge computing, the system optimizes resource allocation: local processing reduces cloud storage and computing overhead, while intelligent analysis can predict battery failure, avoid excessive replacement, and reduce operation and maintenance costs (such as reducing on-site inspections) and accident risks (local safety mechanisms reduce potential compensation); at the same time, the full life cycle management facilitates the tracking of battery history through classification and retrieval functions, helping decision-makers optimize procurement and retirement strategies.

[0124] 8. By introducing communication data hijacking and monitoring modes, and supporting protocol parsing and modification, data can be obtained "transparently" on the battery communication line without modifying the original battery communication protocol. This ensures data accuracy (such as the comparison calculation of voltage V11 and BMS-collected voltage V12), and is easy to adapt to different brands of batteries (good compatibility). It solves the delay problem of data interception in traditional systems and improves the real-time performance and reliability of detection.

[0125] 9. By combining a cloud-edge collaborative architecture with a localized battery safety detection module, efficient, intelligent, and safe full lifecycle management of batteries is achieved. The cloud platform is responsible for global data analysis and decision-making, while the dedicated detection module (including voltage / current / internal resistance detection units and smart switches) deployed locally in the battery swapping cabinet collects multi-dimensional data in real time during battery charging and discharging. It can execute local safety protection (such as automatic power-off in case of abnormality) with millisecond-level response, and obtain core battery parameters without loss through communication data hijacking and monitoring mechanisms. At the same time, the system aggregates data such as electrical performance and operating status into a dynamic information database (full lifecycle information database) built by the cloud platform. Relying on big data and machine learning, it realizes battery health prediction, fault warning, and resource optimization scheduling, which significantly improves battery safety, extends service life, and greatly reduces operation and maintenance costs and operational risks.

[0126] 10. Full-chain safety protection: Combining edge-side local detection and protection with cloud-based deep analysis, it achieves full-process safety management of "pre-event warning - in-event intervention - post-event traceability," overcoming the shortcomings of existing battery swapping cabinets that rely solely on post-event fire suppression; Proactive risk warning: Through trend analysis of parameters such as internal resistance and error rate, it identifies signs of battery performance degradation in advance, avoiding sudden safety accidents; Enhanced intelligence level: Utilizing cloud platform computing power to achieve big data analysis and model warning, solving the problem of insufficient edge-side computing power and improving detection accuracy (such as distinguishing between normal aging and abnormal degradation); Full battery life cycle management: Based on historical databases, it can trace the changes in the health status of each battery, optimize battery scheduling (such as prioritizing the deployment of healthy batteries) and elimination strategies (such as forcibly retiring high-risk batteries); Strong compatibility: The edge-side detection module can be adapted to the transformation of existing battery swapping cabinets, and the cloud platform can be expanded based on the existing charging management platform, reducing implementation costs.

[0127] While specific embodiments of the present invention have been described above, those skilled in the art should understand that the specific embodiments described are merely illustrative and not intended to limit the scope of the present invention. Equivalent modifications and variations made by those skilled in the art in accordance with the spirit of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A cloud-edge collaborative battery swapping cabinet battery detection system, characterized in that: include: A cloud platform; Several battery swapping cabinets are connected to the cloud platform; Several batteries are connected to the battery swapping cabinet; The battery swapping cabinet includes: A battery swapping cabinet control module; Several battery swapping compartments are connected to the battery swapping cabinet control module; Several battery safety detection modules are connected to the battery swapping compartment and the battery, and are respectively located in one of the battery swapping compartments; A platform interface communication module is provided, with one end connected to the battery swapping cabinet control module and the other end connected to the cloud platform.

2. The cloud-edge collaborative battery swapping cabinet battery detection system as described in claim 1, characterized in that: The battery is equipped with a battery power line and a battery communication line; The battery swapping compartment is equipped with a charging power line and a charging communication line.

3. The cloud-edge collaborative battery swapping cabinet battery detection system as described in claim 1, characterized in that: The battery safety detection module includes: A detection controller; A voltmeter for detecting battery voltage, with its control terminal connected to the detection controller and its detection terminal connected to the battery power line of the battery; An ammeter for detecting the charging and discharging current of the battery, with its control terminal connected to the detection controller and its detection terminal connected to the charging power line of the battery swapping compartment; A battery charging circuit switch for switching the battery charging circuit on and off, with the control terminal connected to the detection controller and connected in series between the battery power line of the battery and the charging power line of the battery swapping compartment; A battery communication circuit switch for switching the battery communication circuit on and off, with the control terminal connected to the detection controller and connected in series between the battery communication line of the battery and the charging communication line of the battery swapping compartment; An AC internal resistance detection module for detecting the AC internal resistance of a battery, wherein the control terminal is connected to the detection controller and the detection terminal is connected to the battery power line of the battery; A sub-communication module is connected to the detection controller.

4. The cloud-edge collaborative battery swapping cabinet battery detection system as described in claim 3, characterized in that: The battery charging circuit switch and the battery communication circuit switch are in the off state by default.

5. A method for detecting batteries in a cloud-edge collaborative battery swapping cabinet, characterized in that: The method requires the use of the cloud-edge collaborative battery swapping cabinet battery detection system as described in any one of claims 1 to 4, and includes the following steps: Step S1: When swapping batteries, take out a fully charged battery from the battery swapping compartment of the battery swapping cabinet, put the depleted battery into the battery swapping compartment, and connect it to the battery safety detection module. Step S2: The detection controller operates in communication data hijacking mode. The detection controller obtains the data reading command sent by the battery swapping cabinet control module through the charging communication line, and forwards the data reading command to the battery through the battery communication line; the detection controller obtains the battery charging data through the battery communication line, and forwards the charging data to the battery swapping cabinet control module through the charging communication line. Step S3: The detection controller obtains the data monitoring command sent by the battery swapping cabinet control module through the charging communication line, closes the battery communication circuit switch based on the data monitoring command, and switches to the communication data monitoring mode to monitor the communication bus composed of the charging communication line and the battery communication line. Step S4: The controller detects the voltage accuracy using a voltmeter; Step S5: The detection controller closes the battery charging circuit switch, the current accuracy is detected by the ammeter, the AC internal resistance is detected by the AC internal resistance detection module, and the DC internal resistance is detected by the voltmeter and ammeter. Step S6: The detection controller performs local safety protection operations based on the battery charging data and the monitored BMS data; Step S7: The battery swapping cabinet control module uploads electrical performance data, status data, charging data, and identity information to the cloud platform through the platform connection communication module; the electrical performance data includes voltage accuracy, current accuracy, AC internal resistance, and DC internal resistance; the status data includes battery charging status and battery safety detection module operating status; the identity information is the battery's unique identifier. Step S8: The cloud platform creates a full life cycle information database for the battery based on the received electrical performance data, status data, charging data, and identity information. It then performs intelligent analysis on the data stored in the full life cycle information database and conducts safety management and control of the battery swapping cabinet based on the analysis results.

6. The battery detection method for a cloud-edge collaborative battery swapping cabinet as described in claim 5, characterized in that: Step S2 further includes: Before forwarding the data read command or running data, the data read command or running data is parsed and modified based on a preset communication protocol; Step S3 further includes: During the monitoring of the communication bus, the monitored data is parsed to obtain the battery charging data, and the charging data is sent to the battery swapping cabinet control module.

7. The battery detection method for a cloud-edge collaborative battery swapping cabinet as described in claim 5, characterized in that: Step S4 specifically involves: The detection controller detects the battery voltage V11 through a voltmeter and acquires the voltage V12 from the battery BSM through the battery communication line. Based on the voltages V11 and V12, it calculates the voltage accuracy.

8. The battery detection method for a cloud-edge collaborative battery swapping cabinet as described in claim 5, characterized in that: In step S5, the accuracy of current detection via ammeter specifically refers to: The detection controller detects the battery's current curve Clist1 through an ammeter, and acquires the current curve Clist2 from the battery BSM through the battery communication line. Based on the current curves Clist1 and Clist2, it calculates the current accuracy. The specific steps for detecting DC internal resistance using a voltmeter and an ammeter are as follows: The detection controller modifies the battery's requested current to adjust the battery's charging current. It collects the voltage V21 and current I21 at different times using a voltmeter and an ammeter, respectively, and calculates the DC internal resistance based on the voltage V21 and current I21.

9. The battery detection method for a cloud-edge collaborative battery swapping cabinet as described in claim 5, characterized in that: Step S6 specifically involves: The detection controller performs safety monitoring on battery charging data and BMS data by setting preset monitoring thresholds. When a safety event is detected, the battery charging circuit switch is disconnected to perform local safety protection operations.

10. The battery detection method for a cloud-edge collaborative battery swapping cabinet as described in claim 5, characterized in that: Step S8 specifically involves: The cloud platform creates a full life cycle information database for the battery based on the received electrical performance data, status data, charging data, and identity information. The full life cycle information database is stored and dynamically updated, and the full life cycle information database supports data classification and retrieval. The cloud platform combines big data technology and machine learning algorithms to intelligently analyze the data stored in the full lifecycle information database. Based on the analysis results, it sends control commands to the corresponding battery swapping cabinets or pushes alarm notifications to pre-associated management terminals to manage the battery swapping cabinets safely.

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