Battery anomaly detection and safety protection method and system for battery replacement cabinet

Abstract

The invention provides a battery abnormity detection and safety protection method and system for a battery replacement cabinet, and belongs to the technical field of battery replacement cabinets. The method comprises the steps that S1, a control panel of the battery replacement cabinet collects monitoring data of the battery replacement cabinet; s2, the control panel carries out preprocessing and feature extraction on the monitoring data of each power conversion cabinet; s3, when a charger of the bin body is in a charging state, the control panel carries out current anomaly detection based on the battery replacement cabinet monitoring data, and a current anomaly detection result is obtained; s4, when a charger of the bin body is in a stop state, the control panel performs voltage anomaly detection and temperature anomaly detection based on the battery replacement cabinet monitoring data to obtain a voltage anomaly detection result and a temperature anomaly detection result; and S5, the control panel automatically executes safety protection operation based on the current anomaly detection result, the voltage anomaly detection result and the temperature anomaly detection result. The method has the advantage that the operation safety and reliability of the battery changing cabinet are greatly improved.

Description

Technical Field

[0001] This invention relates to the field of battery swapping cabinet technology, and in particular to a method and system for battery anomaly detection and safety protection in battery swapping cabinets. Background Technology

[0002] With the rapid expansion of the food delivery industry and the continuous increase in the number of delivery personnel, the operating model using two-wheeled electric vehicles (hereinafter referred to as "two-wheelers") as the main delivery tool has gradually become mainstream. However, due to the structural layout and overall size of two-wheelers, their battery capacity is usually small, resulting in limited range and requiring frequent recharging. Against this backdrop, battery swapping, with its advantage of rapid energy replenishment, has become an effective solution to alleviate range anxiety for electric vehicles, and battery swapping cabinets specifically designed for replacing two-wheeler batteries have emerged.

[0003] However, in actual operation, due to battery aging, improper use, or external environmental factors, batteries may experience faults such as abnormal voltage, excessive temperature, and current overload, which may lead to safety hazards or even accidents in the battery swapping cabinet.

[0004] Currently, battery swapping cabinets mostly use periodic sampling for safety protection, which makes it difficult to detect sudden anomalies in real time and results in poor real-time performance. At the same time, they usually only monitor single parameters such as voltage or temperature, lacking a multi-dimensional comprehensive judgment of the overall battery status. After an anomaly occurs, there is often a lack of efficient emergency handling mechanisms, which can easily lead to the spread of faults, delayed response, and difficulty in effectively suppressing cascading risks.

[0005] Therefore, how to provide a method and system for battery anomaly detection and safety protection in battery swapping cabinets, so as to improve the safety and reliability of battery swapping cabinet operation, has become an urgent technical problem to be solved. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a method and system for battery anomaly detection and safety protection in battery swapping cabinets, so as to improve the safety and reliability of battery swapping cabinet operation.

[0007] In a first aspect, the present invention provides a method for battery anomaly detection and safety protection in a battery swapping cabinet, comprising the following steps: Step S1: The control board of the battery swapping cabinet collects real-time monitoring data of the battery swapping cabinet, including battery data, compartment charging data, cabinet data, and compartment data. Step S2: The control board preprocesses and extracts features from the monitoring data of each battery swapping cabinet; Step S3: When the charger in the battery compartment is in the charging state, the control board performs current anomaly detection based on the monitoring data of the battery swapping cabinet and obtains the current anomaly detection result. Step S4: When the charger in the battery compartment is in a stopped state, the control board performs voltage anomaly detection and temperature anomaly detection based on the monitoring data of the battery swapping cabinet, and obtains the voltage anomaly detection results and temperature anomaly detection results. Step S5: The control board automatically performs safety protection operations based on the current anomaly detection results, voltage anomaly detection results, and temperature anomaly detection results.

[0008] Furthermore, in step S1, the battery data includes at least the battery voltage, battery current, battery temperature, SOC, and SOH collected from the battery BMS. The charging data for the compartment includes at least the charging voltage and charging current collected from the charger; The cabinet data includes at least the cabinet smoke concentration and cabinet temperature collected by the cabinet sensor group; The data of the chamber includes at least the smoke concentration and temperature of the chamber, which are collected by the chamber's sensor array. Step S2 specifically involves: The control board performs preprocessing on the monitoring data of each battery swapping cabinet, including at least noise reduction and missing value imputation, and performs feature extraction on the preprocessed monitoring data of each battery swapping cabinet, including at least temperature change rate, voltage consistency and SOC jump.

[0009] Furthermore, step S3 specifically includes: The control board presets a current threshold Cmaxa, a current threshold Cmaxb, a current threshold Cmaxc and a first duration threshold, where Cmaxa > Cmaxb > Cmaxc. When the charger in the battery compartment is charging, the control board calculates the current difference ΔC between the charging current and the battery current based on the monitoring data of the battery swapping cabinet, and determines whether ΔC > Cmaxa and whether it persists for the first duration threshold. If yes, a current anomaly detection result carrying a Class A anomaly is generated; otherwise: Determine whether ΔC > Cmaxb and persists for the first duration threshold. If yes, generate a current anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔC > Cmaxc and remains above the first duration threshold. If yes, generate a current anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

[0010] Furthermore, step S4 specifically includes: The control board presets a voltage threshold Vmaxa, a voltage threshold Vmaxb, a voltage threshold Vmaxc, and a second duration threshold, where Vmaxa > Vmaxb > Vmaxc. When the charger in the battery compartment is stopped, the control board calculates the voltage difference ΔV between the charging voltage and the battery voltage based on the monitoring data of the battery swapping cabinet, and determines whether ΔV > Vmaxa and whether it continues for the second duration threshold. If yes, a voltage anomaly detection result carrying a Class A anomaly is generated; if not, then: Determine whether ΔV > Vmaxb and persists for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Type B anomaly; otherwise: Determine whether ΔV > Vmaxc and continues for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring. The control board presets a temperature threshold Tmaxa, a temperature threshold Tmaxb, a temperature threshold Tmaxc, and a third time threshold, where Tmaxa > Tmaxb > Tmaxc. When the charger in the battery swapping compartment is stopped, the control board calculates the temperature rise ΔT based on the monitoring data of the battery swapping cabinet: ; Among them, I charge Indicates charging current; C th This indicates the thermal fusion of the battery; t represents the charging time. This indicates a problem with the cabinet. Indicates battery temperature; e represents the time constant; e represents the natural constant. Determine whether ΔT > Tmaxa and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type A anomaly; otherwise: Determine whether ΔT > Tmaxb and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔT > Tmaxc and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

[0011] Furthermore, step S5 specifically includes: The control board monitors the current anomaly detection results, voltage anomaly detection results, and temperature anomaly detection results in real time. When the current anomaly detection results, voltage anomaly detection results, or temperature anomaly detection results carry a Class A anomaly, the power supply circuit of the corresponding battery is immediately cut off and the aerosol is activated; when carrying a Class B anomaly, the charging and discharging operation of the corresponding battery is suspended, the fan cooling system is activated, or the vent is opened; when carrying a Class C anomaly, the abnormal behavior is recorded and the corresponding battery is marked as pending inspection, and a suggested repair prompt is displayed on the screen.

[0012] Secondly, the present invention provides a battery anomaly detection and safety protection system for a battery swapping cabinet, comprising the following modules: The battery swapping cabinet monitoring data acquisition module is used by the control board of the battery swapping cabinet to collect real-time monitoring data of the battery swapping cabinet, including battery data, compartment charging data, cabinet data, and compartment data. The battery swapping cabinet monitoring data preprocessing module is used by the control board to preprocess and extract features from the monitoring data of each battery swapping cabinet. The current anomaly detection module is used by the control board to perform current anomaly detection based on the monitoring data of the battery swapping cabinet when the charger in the compartment is in the charging state, and to obtain the current anomaly detection result. The voltage and temperature anomaly detection module is used by the control board to perform voltage and temperature anomaly detection based on the monitoring data of the battery swapping cabinet when the charger in the compartment is in a stopped state, and to obtain the voltage and temperature anomaly detection results. The safety protection module is used to control the board to automatically perform safety protection operations based on the current abnormality detection results, voltage abnormality detection results, and temperature abnormality detection results.

[0013] Furthermore, in the battery swapping cabinet monitoring data acquisition module, the battery data includes at least the battery voltage, battery current, battery temperature, SOC, and SOH collected from the battery BMS; The charging data for the compartment includes at least the charging voltage and charging current collected from the charger; The cabinet data includes at least the cabinet smoke concentration and cabinet temperature collected by the cabinet sensor group; The data of the chamber includes at least the smoke concentration and temperature of the chamber, which are collected by the chamber's sensor array. The battery swapping cabinet monitoring data preprocessing module is specifically used for: The control board performs preprocessing on the monitoring data of each battery swapping cabinet, including at least noise reduction and missing value imputation, and performs feature extraction on the preprocessed monitoring data of each battery swapping cabinet, including at least temperature change rate, voltage consistency and SOC jump.

[0014] Furthermore, the current anomaly detection module is specifically used for: The control board presets a current threshold Cmaxa, a current threshold Cmaxb, a current threshold Cmaxc and a first duration threshold, where Cmaxa > Cmaxb > Cmaxc. When the charger in the battery compartment is charging, the control board calculates the current difference ΔC between the charging current and the battery current based on the monitoring data of the battery swapping cabinet, and determines whether ΔC > Cmaxa and whether it persists for the first duration threshold. If yes, a current anomaly detection result carrying a Class A anomaly is generated; otherwise: Determine whether ΔC > Cmaxb and persists for the first duration threshold. If yes, generate a current anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔC > Cmaxc and remains above the first duration threshold. If yes, generate a current anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

[0015] Furthermore, the voltage and temperature anomaly detection module is specifically used for: The control board presets a voltage threshold Vmaxa, a voltage threshold Vmaxb, a voltage threshold Vmaxc, and a second duration threshold, where Vmaxa > Vmaxb > Vmaxc. When the charger in the battery compartment is stopped, the control board calculates the voltage difference ΔV between the charging voltage and the battery voltage based on the monitoring data of the battery swapping cabinet, and determines whether ΔV > Vmaxa and whether it continues for the second duration threshold. If yes, a voltage anomaly detection result carrying a Class A anomaly is generated; if not, then: Determine whether ΔV > Vmaxb and persists for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Type B anomaly; otherwise: Determine whether ΔV > Vmaxc and continues for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring. The control board presets a temperature threshold Tmaxa, a temperature threshold Tmaxb, a temperature threshold Tmaxc, and a third time threshold, where Tmaxa > Tmaxb > Tmaxc. When the charger in the battery swapping compartment is stopped, the control board calculates the temperature rise ΔT based on the monitoring data of the battery swapping cabinet: ; Among them, I charge Indicates the charging current; C th This indicates the thermal fusion of the battery; t represents the charging time. This indicates a problem with the cabinet. Indicates battery temperature; e represents the time constant; e represents the natural constant. Determine whether ΔT > Tmaxa and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type A anomaly; otherwise: Determine whether ΔT > Tmaxb and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔT > Tmaxc and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

[0016] Furthermore, the security protection module is specifically used for: The control board monitors the current anomaly detection results, voltage anomaly detection results, and temperature anomaly detection results in real time. When the current anomaly detection results, voltage anomaly detection results, or temperature anomaly detection results carry a Class A anomaly, the power supply circuit of the corresponding battery is immediately cut off and the aerosol is activated; when carrying a Class B anomaly, the charging and discharging operation of the corresponding battery is suspended, the fan cooling system is activated, or the vent is opened; when carrying a Class C anomaly, the abnormal behavior is recorded and the corresponding battery is marked as pending inspection, and a suggested repair prompt is displayed on the screen.

[0017] The advantages of this invention are: 1. The control board of the battery swapping cabinet collects real-time monitoring data, including battery data, compartment charging data, cabinet data, and compartment data. It preprocesses and extracts features from the monitoring data of each battery swapping cabinet. When the charger in the compartment is charging, the control board performs current anomaly detection based on the battery swapping cabinet monitoring data. When the charger is stopped, it performs voltage and temperature anomaly detection based on the monitoring data, obtaining the corresponding results. The control board automatically executes safety protection operations based on these results. In other words, the battery swapping cabinet control board collects real-time monitoring data... The battery swapping cabinet integrates multi-dimensional monitoring data from the battery, charging bay, cabinet, and bay. During charging, it continuously compares the current difference with a threshold to achieve graded detection of current anomalies (A / B / C categories). When charging stops, it combines voltage difference with a multi-parameter temperature rise model that integrates charging current, battery thermal capacity, and ambient temperature to determine voltage and temperature anomalies. Finally, it automatically triggers precise protection operations based on the anomaly level: for A-category anomalies, it immediately cuts off power supply and initiates aerosol fire suppression; for B-category anomalies, it suspends charging and discharging and initiates forced cooling; and for C-category anomalies, it marks them for inspection and prompts maintenance. This constructs a safety closed loop of "real-time monitoring - multi-dimensional diagnosis - graded response," which greatly improves the safety and reliability of the battery swapping cabinet operation.

[0018] 2. By comprehensively collecting battery data (BMS), compartment charging data (charger), cabinet environment data (sensor group), and compartment environment data (sensor group), this comprehensive data collection system forms a three-dimensional monitoring network. It can cross-verify from three dimensions: battery internal status, charger working status, and external environment. This greatly avoids misjudgment or omission caused by single sensor failure or incomplete data, and provides a solid and reliable data foundation for subsequent anomaly analysis.

[0019] 3. By preprocessing the raw data (noise reduction, missing value imputation) and extracting features (temperature change rate, voltage consistency, SOC jump), the data quality is improved, ensuring the accuracy and stability of subsequent analysis algorithms. Feature extraction goes beyond simple threshold judgment, introducing dynamic change trends (such as temperature change rate) and consistency analysis (such as voltage consistency), enabling the system to identify more complex and earlier potential fault modes (such as accelerated temperature rise caused by the initial stage of internal short circuit), demonstrating the algorithm's advanced and intelligent level.

[0020] 4. By adopting a state-based detection strategy: during the charging state, the focus is on detecting current anomalies, and during the stationary state, the focus is on detecting voltage and temperature anomalies. Since the main risk points of the battery are different in different states (high risk of excessive current during charging, and high risk of voltage anomalies and temperature rise during stationary states), this strategy concentrates detection resources on the most likely anomalies, making the target clear and the detection efficiency higher. It avoids unnecessary voltage detection during charging (which is greatly affected by charging voltage) or invalid current detection during stationary states, making the entire method logically clear.

[0021] 5. In the judgment of current, voltage, and temperature anomalies, multi-level thresholds (Class A / B / C) are set, and a duration threshold judgment condition is introduced, requiring that the abnormal signal must last for a certain period of time before it is confirmed. This can effectively filter out short-term signal anomalies caused by instantaneous interference (such as power grid fluctuations and sensor noise), and significantly reduce the false alarm rate of the system. Different levels (Class A / B / C) are defined for anomalies of different severity, providing a precise basis for the subsequent implementation of differentiated safety protection measures and avoiding the crude "one-size-fits-all" approach.

[0022] 6. The temperature rise ΔT used in the temperature anomaly detection is a physical model that includes multiple parameters such as charging current, heat capacity, time constant, and ambient temperature, rather than a simple judgment of absolute temperature value. It can more scientifically predict the temperature rise trend of the battery, rather than just reflecting the current temperature value. This allows the system to issue an early warning based on the abnormal temperature rise rate before the absolute temperature value reaches the dangerous critical point, realizing early prediction of thermal runaway and buying valuable time for safety intervention.

[0023] 7. Based on the three levels of anomalies (A, B, and C), distinctly different but highly reasonable protective actions are taken: from the most urgent power cut-off and fire suppression (Class A), to the secondary measures of suspending use and active cooling (Class B), and finally to the basic measures of recording, marking, and prompting for maintenance (Class C). This means that the most dangerous anomalies are addressed with the most thorough and rapid physical isolation and fire suppression measures, maximizing the protection of personnel and property; moderate anomalies are addressed with measures to restrict use and attempt recovery; and minor anomalies are addressed with only recording and prompting, avoiding the shutdown of the entire battery swapping cabinet due to minor anomalies and ensuring equipment availability and operational efficiency. This tiered response mechanism demonstrates the system's high level of "decision-making" capability, intelligently balancing safety and operational needs while ensuring safety.

[0024] 8. By comprehensively collecting battery, charger, and environmental data, combined with preprocessing and intelligent feature extraction, multi-level current anomaly detection in charging mode and multi-level voltage / temperature anomaly detection in idle mode are realized. It also innovatively adopts a physical model to predict temperature rise trends. Its graded threshold judgment mechanism effectively avoids false alarms. The supporting layered safety response strategy (from power cut-off to early warning prompts) ensures safety while maximizing equipment availability. Overall, it constructs a precise, efficient, and proactive closed loop for battery safety management of the battery swapping cabinet. Attached Figure Description

[0025] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0026] Figure 1 This is a flowchart of a battery anomaly detection and safety protection method for a battery swapping cabinet according to the present invention.

[0027] Figure 2 This is a schematic diagram of the structure of a battery anomaly detection and safety protection system for a battery swapping cabinet according to the present invention.

[0028] Figure 3 This is a circuit diagram of the battery swapping cabinet of the present invention. Detailed Implementation

[0029] The overall concept of the technical solution in this application embodiment is as follows: The battery swapping cabinet control board collects real-time monitoring data on the battery, charging bays, cabinet, and bays from multiple dimensions. During charging, current anomalies are detected by continuous comparison of current difference and threshold values. When charging stops, voltage and temperature anomalies are determined by combining voltage difference and a multi-parameter temperature rise model that integrates charging current, battery thermal capacity, and ambient temperature. Finally, precise protection operations are automatically triggered based on the anomaly level: for Class A anomalies, power is immediately cut off and aerosol fire suppression is initiated; for Class B anomalies, charging and discharging are suspended and forced cooling is initiated; for Class C anomalies, they are marked for inspection and maintenance is prompted. This constructs a safety closed loop of "real-time monitoring - multi-dimensional diagnosis - graded response" to improve the safety and reliability of the battery swapping cabinet operation.

[0030] Please refer to Figures 1 to 3 As shown, a preferred embodiment of the battery anomaly detection and safety protection method for a battery swapping cabinet according to the present invention includes the following steps: Step S1: The control board of the battery swapping cabinet collects real-time monitoring data of the battery swapping cabinet, including battery data, compartment charging data, cabinet data, and compartment data. Step S2: The control board preprocesses and extracts features from the monitoring data of each battery swapping cabinet; Step S3: When the charger in the battery compartment is in the charging state, the control board performs current anomaly detection based on the monitoring data of the battery swapping cabinet and obtains the current anomaly detection result. Step S4: When the charger in the battery compartment is in a stopped state, the control board performs voltage anomaly detection and temperature anomaly detection based on the monitoring data of the battery swapping cabinet, and obtains the voltage anomaly detection results and temperature anomaly detection results. Step S5: The control board automatically performs safety protection operations based on the current anomaly detection results, voltage anomaly detection results, and temperature anomaly detection results.

[0031] In step S1, the battery data includes at least the battery voltage, battery current, battery temperature, SOC, and SOH collected from the battery BMS. The charging data for the compartment includes at least the charging voltage and charging current collected from the charger; The cabinet data includes at least the cabinet smoke concentration and cabinet temperature collected by the cabinet sensor group; The data of the chamber includes at least the smoke concentration and temperature of the chamber, which are collected by the chamber's sensor array. The cabinet sensor group includes at least a cabinet smoke sensor and a cabinet temperature sensor; the warehouse sensor group includes at least a warehouse smoke sensor, a warehouse temperature sensor, and a warehouse door status sensor; the warehouse is also equipped with an aerosol for fire suppression, a heater for heating in low temperatures, and a warehouse fan for cooling in high temperatures. Step S2 specifically involves: The control board performs preprocessing on the monitoring data of each battery swapping cabinet, including at least noise reduction and missing value imputation, and performs feature extraction on the preprocessed monitoring data of each battery swapping cabinet, including at least temperature change rate, voltage consistency and SOC jump.

[0032] Step S3 specifically involves: The control board presets a current threshold Cmaxa, a current threshold Cmaxb, a current threshold Cmaxc and a first duration threshold, where Cmaxa > Cmaxb > Cmaxc. When the charger in the battery compartment is charging, the control board calculates the current difference ΔC between the charging current and the battery current based on the monitoring data of the battery swapping cabinet, and determines whether ΔC > Cmaxa and whether it persists for the first duration threshold. If yes, a current anomaly detection result carrying a Class A anomaly is generated; otherwise: Determine whether ΔC > Cmaxb and persists for the first duration threshold. If yes, generate a current anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔC > Cmaxc and remains above the first duration threshold. If yes, generate a current anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

[0033] Step S4 specifically involves: The control board presets a voltage threshold Vmaxa, a voltage threshold Vmaxb, a voltage threshold Vmaxc, and a second duration threshold, where Vmaxa > Vmaxb > Vmaxc. When the charger in the battery compartment is stopped, the control board calculates the voltage difference ΔV between the charging voltage and the battery voltage based on the monitoring data of the battery swapping cabinet, and determines whether ΔV > Vmaxa and whether it continues for the second duration threshold. If yes, a voltage anomaly detection result carrying a Class A anomaly is generated; if not, then: Determine whether ΔV > Vmaxb and persists for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Type B anomaly; otherwise: Determine whether ΔV > Vmaxc and continues for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring. The control board presets a temperature threshold Tmaxa, a temperature threshold Tmaxb, a temperature threshold Tmaxc, and a third time threshold, where Tmaxa > Tmaxb > Tmaxc. When the charger in the battery swapping compartment is stopped, the control board calculates the temperature rise ΔT based on the monitoring data of the battery swapping cabinet: ; Among them, I chargeIndicates the charging current; C th This indicates the thermal fusion of the battery; t represents the charging time. This indicates a problem with the cabinet. Indicates battery temperature; e represents the time constant; e represents the natural constant. Determine whether ΔT > Tmaxa and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type A anomaly; otherwise: Determine whether ΔT > Tmaxb and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔT > Tmaxc and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

[0034] Step S5 specifically involves: The control board monitors the current anomaly detection results, voltage anomaly detection results, and temperature anomaly detection results in real time. When the current anomaly detection results, voltage anomaly detection results, or temperature anomaly detection results carry a Class A anomaly, the power supply circuit of the corresponding battery is immediately cut off, and aerosol is activated (in specific implementation, water mist spraying or dry powder fire extinguishers can also be used); when carrying a Class B anomaly, the charging and discharging operation of the corresponding battery is suspended, and the fan cooling system (cabinet fan) is activated or the ventilation vents are opened; when carrying a Class C anomaly, the abnormal behavior is recorded and the corresponding battery is marked as pending inspection, and a suggested maintenance prompt is displayed on the screen.

[0035] Type A anomalies indicate a serious threat to safety and require immediate attention; Type B anomalies indicate potential risks and require timely intervention; Type C anomalies indicate an initial warning and suggest investigation.

[0036] A preferred embodiment of the battery anomaly detection and safety protection system for a battery swapping cabinet according to the present invention includes the following modules: The battery swapping cabinet monitoring data acquisition module is used by the control board of the battery swapping cabinet to collect real-time monitoring data of the battery swapping cabinet, including battery data, compartment charging data, cabinet data, and compartment data. The battery swapping cabinet monitoring data preprocessing module is used by the control board to preprocess and extract features from the monitoring data of each battery swapping cabinet. The current anomaly detection module is used by the control board to perform current anomaly detection based on the monitoring data of the battery swapping cabinet when the charger in the compartment is in the charging state, and to obtain the current anomaly detection result. The voltage and temperature anomaly detection module is used by the control board to perform voltage and temperature anomaly detection based on the monitoring data of the battery swapping cabinet when the charger in the compartment is in a stopped state, and to obtain the voltage and temperature anomaly detection results. The safety protection module is used to control the board to automatically perform safety protection operations based on the current abnormality detection results, voltage abnormality detection results, and temperature abnormality detection results.

[0037] In the battery swapping cabinet monitoring data acquisition module, the battery data includes at least the battery voltage, battery current, battery temperature, SOC, and SOH collected from the battery BMS; The charging data for the compartment includes at least the charging voltage and charging current collected from the charger; The cabinet data includes at least the cabinet smoke concentration and cabinet temperature collected by the cabinet sensor group; The data of the chamber includes at least the smoke concentration and temperature of the chamber, which are collected by the chamber's sensor array. The cabinet sensor group includes at least a cabinet smoke sensor and a cabinet temperature sensor; the warehouse sensor group includes at least a warehouse smoke sensor, a warehouse temperature sensor, and a warehouse door status sensor; the warehouse is also equipped with an aerosol for fire suppression, a heater for heating in low temperatures, and a warehouse fan for cooling in high temperatures. The battery swapping cabinet monitoring data preprocessing module is specifically used for: The control board performs preprocessing on the monitoring data of each battery swapping cabinet, including at least noise reduction and missing value imputation, and performs feature extraction on the preprocessed monitoring data of each battery swapping cabinet, including at least temperature change rate, voltage consistency and SOC jump.

[0038] The current anomaly detection module is specifically used for: The control board presets a current threshold Cmaxa, a current threshold Cmaxb, a current threshold Cmaxc and a first duration threshold, where Cmaxa > Cmaxb > Cmaxc. When the charger in the battery compartment is charging, the control board calculates the current difference ΔC between the charging current and the battery current based on the monitoring data of the battery swapping cabinet, and determines whether ΔC > Cmaxa and whether it persists for the first duration threshold. If yes, a current anomaly detection result carrying a Class A anomaly is generated; otherwise: Determine whether ΔC > Cmaxb and persists for the first duration threshold. If yes, generate a current anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔC > Cmaxc and remains above the first duration threshold. If yes, generate a current anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

[0039] The voltage and temperature anomaly detection module is specifically used for: The control board presets a voltage threshold Vmaxa, a voltage threshold Vmaxb, a voltage threshold Vmaxc, and a second duration threshold, where Vmaxa > Vmaxb > Vmaxc. When the charger in the battery compartment is stopped, the control board calculates the voltage difference ΔV between the charging voltage and the battery voltage based on the monitoring data of the battery swapping cabinet, and determines whether ΔV > Vmaxa and whether it continues for the second duration threshold. If yes, a voltage anomaly detection result carrying a Class A anomaly is generated; if not, then: Determine whether ΔV > Vmaxb and persists for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Type B anomaly; otherwise: Determine whether ΔV > Vmaxc and continues for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring. The control board presets a temperature threshold Tmaxa, a temperature threshold Tmaxb, a temperature threshold Tmaxc, and a third time threshold, where Tmaxa > Tmaxb > Tmaxc. When the charger in the battery swapping compartment is stopped, the control board calculates the temperature rise ΔT based on the monitoring data of the battery swapping cabinet: ; Among them, I charge Indicates the charging current; C th This indicates the thermal fusion of the battery; t represents the charging time. This indicates a problem with the cabinet. Indicates battery temperature; e represents the time constant; e represents the natural constant. Determine whether ΔT > Tmaxa and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type A anomaly; otherwise: Determine whether ΔT > Tmaxb and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔT > Tmaxc and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

[0040] The security protection module is specifically used for: The control board monitors the current anomaly detection results, voltage anomaly detection results, and temperature anomaly detection results in real time. When the current anomaly detection results, voltage anomaly detection results, or temperature anomaly detection results carry a Class A anomaly, the power supply circuit of the corresponding battery is immediately cut off, and aerosol is activated (in specific implementation, water mist spraying or dry powder fire extinguishers can also be used); when carrying a Class B anomaly, the charging and discharging operation of the corresponding battery is suspended, and the fan cooling system (cabinet fan) is activated or the ventilation vents are opened; when carrying a Class C anomaly, the abnormal behavior is recorded and the corresponding battery is marked as pending inspection, and a suggested maintenance prompt is displayed on the screen.

[0041] Type A anomalies indicate a serious threat to safety and require immediate attention; Type B anomalies indicate potential risks and require timely intervention; Type C anomalies indicate an initial warning and suggest investigation.

[0042] In summary, the advantages of this invention are as follows: 1. The control board of the battery swapping cabinet collects real-time monitoring data, including battery data, compartment charging data, cabinet data, and compartment data. It preprocesses and extracts features from the monitoring data of each battery swapping cabinet. When the charger in the compartment is charging, the control board performs current anomaly detection based on the battery swapping cabinet monitoring data. When the charger is stopped, it performs voltage and temperature anomaly detection based on the monitoring data, obtaining the corresponding results. The control board automatically executes safety protection operations based on these results. In other words, the battery swapping cabinet control board collects real-time monitoring data... The battery swapping cabinet integrates multi-dimensional monitoring data from the battery, charging bay, cabinet, and bay. During charging, it continuously compares the current difference with a threshold to achieve graded detection of current anomalies (A / B / C categories). When charging stops, it combines voltage difference with a multi-parameter temperature rise model that integrates charging current, battery thermal capacity, and ambient temperature to determine voltage and temperature anomalies. Finally, it automatically triggers precise protection operations based on the anomaly level: for A-category anomalies, it immediately cuts off power supply and initiates aerosol fire suppression; for B-category anomalies, it suspends charging and discharging and initiates forced cooling; and for C-category anomalies, it marks them for inspection and prompts maintenance. This constructs a safety closed loop of "real-time monitoring - multi-dimensional diagnosis - graded response," which greatly improves the safety and reliability of the battery swapping cabinet operation.

[0043] 2. By comprehensively collecting battery data (BMS), compartment charging data (charger), cabinet environment data (sensor group), and compartment environment data (sensor group), this comprehensive data collection system forms a three-dimensional monitoring network. It can cross-verify from three dimensions: battery internal status, charger working status, and external environment. This greatly avoids misjudgment or omission caused by single sensor failure or incomplete data, and provides a solid and reliable data foundation for subsequent anomaly analysis.

[0044] 3. By preprocessing the raw data (noise reduction, missing value imputation) and extracting features (temperature change rate, voltage consistency, SOC jump), the data quality is improved, ensuring the accuracy and stability of subsequent analysis algorithms. Feature extraction goes beyond simple threshold judgment, introducing dynamic change trends (such as temperature change rate) and consistency analysis (such as voltage consistency), enabling the system to identify more complex and earlier potential fault modes (such as accelerated temperature rise caused by the initial stage of internal short circuit), demonstrating the algorithm's advanced and intelligent level.

[0045] 4. By adopting a state-based detection strategy: during the charging state, the focus is on detecting current anomalies, and during the stationary state, the focus is on detecting voltage and temperature anomalies. Since the main risk points of the battery are different in different states (high risk of excessive current during charging, and high risk of voltage anomalies and temperature rise during stationary states), this strategy concentrates detection resources on the most likely anomalies, making the target clear and the detection efficiency higher. It avoids unnecessary voltage detection during charging (which is greatly affected by charging voltage) or invalid current detection during stationary states, making the entire method logically clear.

[0046] 5. In the judgment of current, voltage, and temperature anomalies, multi-level thresholds (Class A / B / C) are set, and a duration threshold judgment condition is introduced, requiring that the abnormal signal must last for a certain period of time before it is confirmed. This can effectively filter out short-term signal anomalies caused by instantaneous interference (such as power grid fluctuations and sensor noise), and significantly reduce the false alarm rate of the system. Different levels (Class A / B / C) are defined for anomalies of different severity, providing a precise basis for the subsequent implementation of differentiated safety protection measures and avoiding the crude "one-size-fits-all" approach.

[0047] 6. The temperature rise ΔT used in the temperature anomaly detection is a physical model that includes multiple parameters such as charging current, heat capacity, time constant, and ambient temperature, rather than a simple judgment of absolute temperature value. It can more scientifically predict the temperature rise trend of the battery, rather than just reflecting the current temperature value. This allows the system to issue an early warning based on the abnormal temperature rise rate before the absolute temperature value reaches the dangerous critical point, realizing early prediction of thermal runaway and buying valuable time for safety intervention.

[0048] 7. Based on the three levels of anomalies (A, B, and C), distinctly different but highly reasonable protective actions are taken: from the most urgent power cut-off and fire suppression (Class A), to the secondary measures of suspending use and active cooling (Class B), and finally to the basic measures of recording, marking, and prompting for maintenance (Class C). This means that the most dangerous anomalies are addressed with the most thorough and rapid physical isolation and fire suppression measures, maximizing the protection of personnel and property; moderate anomalies are addressed with measures to restrict use and attempt recovery; and minor anomalies are addressed with only recording and prompting, avoiding the shutdown of the entire battery swapping cabinet due to minor anomalies and ensuring equipment availability and operational efficiency. This tiered response mechanism demonstrates the system's high level of "decision-making" capability, intelligently balancing safety and operational needs while ensuring safety.

[0049] 8. By comprehensively collecting battery, charger, and environmental data, combined with preprocessing and intelligent feature extraction, multi-level current anomaly detection in charging mode and multi-level voltage / temperature anomaly detection in idle mode are realized. It also innovatively adopts a physical model to predict temperature rise trends. Its graded threshold judgment mechanism effectively avoids false alarms. The supporting layered safety response strategy (from power cut-off to early warning prompts) ensures safety while maximizing equipment availability. Overall, it constructs a precise, efficient, and proactive closed loop for battery safety management of the battery swapping cabinet.

[0050] 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 method for battery anomaly detection and safety protection in a battery swapping cabinet, characterized in that: Includes the following steps: Step S1: The control board of the battery swapping cabinet collects real-time monitoring data of the battery swapping cabinet, including battery data, compartment charging data, cabinet data, and compartment data. Step S2: The control board preprocesses and extracts features from the monitoring data of each battery swapping cabinet; Step S3: When the charger in the battery compartment is in the charging state, the control board performs current anomaly detection based on the monitoring data of the battery swapping cabinet and obtains the current anomaly detection result. Step S4: When the charger in the battery compartment is in a stopped state, the control board performs voltage anomaly detection and temperature anomaly detection based on the monitoring data of the battery swapping cabinet, and obtains the voltage anomaly detection results and temperature anomaly detection results. Step S5: The control board automatically performs safety protection operations based on the current anomaly detection results, voltage anomaly detection results, and temperature anomaly detection results.

2. The battery anomaly detection and safety protection method for a battery swapping cabinet as described in claim 1, characterized in that: In step S1, the battery data includes at least the battery voltage, battery current, battery temperature, SOC, and SOH collected from the battery BMS. The charging data for the compartment includes at least the charging voltage and charging current collected from the charger; The cabinet data includes at least the cabinet smoke concentration and cabinet temperature collected by the cabinet sensor group; The data of the chamber includes at least the smoke concentration and temperature of the chamber, which are collected by the chamber's sensor array. Step S2 specifically involves: The control board performs preprocessing on the monitoring data of each battery swapping cabinet, including at least noise reduction and missing value imputation, and performs feature extraction on the preprocessed monitoring data of each battery swapping cabinet, including at least temperature change rate, voltage consistency and SOC jump.

3. The battery anomaly detection and safety protection method for a battery swapping cabinet as described in claim 1, characterized in that: Step S3 specifically involves: The control board presets a current threshold Cmaxa, a current threshold Cmaxb, a current threshold Cmaxc and a first duration threshold, where Cmaxa > Cmaxb > Cmaxc. When the charger in the battery compartment is charging, the control board calculates the current difference ΔC between the charging current and the battery current based on the monitoring data of the battery swapping cabinet, and determines whether ΔC > Cmaxa and whether it persists for the first duration threshold. If yes, a current anomaly detection result carrying a Class A anomaly is generated; otherwise: Determine whether ΔC > Cmaxb and persists for the first duration threshold. If yes, generate a current anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔC > Cmaxc and remains above the first duration threshold. If yes, generate a current anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

4. The battery anomaly detection and safety protection method for a battery swapping cabinet as described in claim 1, characterized in that: Step S4 specifically involves: The control board presets a voltage threshold Vmaxa, a voltage threshold Vmaxb, a voltage threshold Vmaxc, and a second duration threshold, where Vmaxa > Vmaxb > Vmaxc. When the charger in the battery compartment is stopped, the control board calculates the voltage difference ΔV between the charging voltage and the battery voltage based on the monitoring data of the battery swapping cabinet, and determines whether ΔV > Vmaxa and whether it continues for the second duration threshold. If yes, a voltage anomaly detection result carrying a Class A anomaly is generated; if not, then: Determine whether ΔV > Vmaxb and persists for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Type B anomaly; otherwise: Determine whether ΔV > Vmaxc and continues for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring. The control board presets a temperature threshold Tmaxa, a temperature threshold Tmaxb, a temperature threshold Tmaxc, and a third time threshold, where Tmaxa > Tmaxb > Tmaxc. When the charger in the battery swapping compartment is stopped, the control board calculates the temperature rise ΔT based on the monitoring data of the battery swapping cabinet: ; Among them, I charge Indicates the charging current; C th This indicates the thermal fusion of the battery; t represents the charging time. This indicates a problem with the cabinet. Indicates battery temperature; e represents the time constant; e represents the natural constant. Determine whether ΔT > Tmaxa and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type A anomaly; otherwise: Determine whether ΔT > Tmaxb and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔT > Tmaxc and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

5. A method for battery anomaly detection and safety protection in a battery swapping cabinet as described in claim 1, characterized in that: Step S5 specifically involves: The control board monitors the current anomaly detection results, voltage anomaly detection results, and temperature anomaly detection results in real time. When the current anomaly detection results, voltage anomaly detection results, or temperature anomaly detection results carry a Class A anomaly, the power supply circuit of the corresponding battery is immediately cut off and the aerosol is activated; when carrying a Class B anomaly, the charging and discharging operation of the corresponding battery is suspended, the fan cooling system is activated, or the vent is opened; when carrying a Class C anomaly, the abnormal behavior is recorded and the corresponding battery is marked as pending inspection, and a suggested repair prompt is displayed on the screen.

6. A battery anomaly detection and safety protection system for a battery swapping cabinet, characterized in that: Includes the following modules: The battery swapping cabinet monitoring data acquisition module is used by the control board of the battery swapping cabinet to collect real-time monitoring data of the battery swapping cabinet, including battery data, compartment charging data, cabinet data, and compartment data. The battery swapping cabinet monitoring data preprocessing module is used by the control board to preprocess and extract features from the monitoring data of each battery swapping cabinet. The current anomaly detection module is used by the control board to perform current anomaly detection based on the monitoring data of the battery swapping cabinet when the charger in the compartment is in the charging state, and to obtain the current anomaly detection result. The voltage and temperature anomaly detection module is used by the control board to perform voltage and temperature anomaly detection based on the monitoring data of the battery swapping cabinet when the charger in the compartment is in a stopped state, and to obtain the voltage and temperature anomaly detection results. The safety protection module is used to control the board to automatically perform safety protection operations based on the current abnormality detection results, voltage abnormality detection results, and temperature abnormality detection results.

7. A battery anomaly detection and safety protection system for a battery swapping cabinet as described in claim 6, characterized in that: In the battery swapping cabinet monitoring data acquisition module, the battery data includes at least the battery voltage, battery current, battery temperature, SOC, and SOH collected from the battery BMS; The charging data for the compartment includes at least the charging voltage and charging current collected from the charger; The cabinet data includes at least the cabinet smoke concentration and cabinet temperature collected by the cabinet sensor group; The data of the chamber includes at least the smoke concentration and temperature of the chamber, which are collected by the chamber's sensor array. The battery swapping cabinet monitoring data preprocessing module is specifically used for: The control board performs preprocessing on the monitoring data of each battery swapping cabinet, including at least noise reduction and missing value imputation, and performs feature extraction on the preprocessed monitoring data of each battery swapping cabinet, including at least temperature change rate, voltage consistency and SOC jump.

8. A battery anomaly detection and safety protection system for a battery swapping cabinet as described in claim 6, characterized in that: The current anomaly detection module is specifically used for: The control board presets a current threshold Cmaxa, a current threshold Cmaxb, a current threshold Cmaxc and a first duration threshold, where Cmaxa > Cmaxb > Cmaxc. When the charger in the battery compartment is charging, the control board calculates the current difference ΔC between the charging current and the battery current based on the monitoring data of the battery swapping cabinet, and determines whether ΔC > Cmaxa and whether it persists for the first duration threshold. If yes, a current anomaly detection result carrying a Class A anomaly is generated; otherwise: Determine whether ΔC > Cmaxb and persists for the first duration threshold. If yes, generate a current anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔC > Cmaxc and remains above the first duration threshold. If yes, generate a current anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

9. A battery anomaly detection and safety protection system for a battery swapping cabinet as described in claim 6, characterized in that: The voltage and temperature anomaly detection module is specifically used for: The control board presets a voltage threshold Vmaxa, a voltage threshold Vmaxb, a voltage threshold Vmaxc, and a second duration threshold, where Vmaxa > Vmaxb > Vmaxc. When the charger in the battery compartment is stopped, the control board calculates the voltage difference ΔV between the charging voltage and the battery voltage based on the monitoring data of the battery swapping cabinet, and determines whether ΔV > Vmaxa and whether it continues for the second duration threshold. If yes, a voltage anomaly detection result carrying a Class A anomaly is generated; if not, then: Determine whether ΔV > Vmaxb and persists for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Type B anomaly; otherwise: Determine whether ΔV > Vmaxc and continues for the second duration threshold. If yes, generate a voltage anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring. The control board presets a temperature threshold Tmaxa, a temperature threshold Tmaxb, a temperature threshold Tmaxc, and a third time threshold, where Tmaxa > Tmaxb > Tmaxc. When the charger in the battery swapping compartment is stopped, the control board calculates the temperature rise ΔT based on the monitoring data of the battery swapping cabinet: ; Among them, I charge Indicates the charging current; C th This indicates the thermal fusion of the battery; t represents the charging time. This indicates a problem with the cabinet. Indicates battery temperature; e represents the time constant; e represents the natural constant. Determine whether ΔT > Tmaxa and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type A anomaly; otherwise: Determine whether ΔT > Tmaxb and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a type B anomaly; otherwise: Determine whether ΔT > Tmaxc and continues for the third duration threshold. If yes, generate a temperature anomaly detection result carrying a Class C anomaly; otherwise, continue monitoring.

10. A battery anomaly detection and safety protection system for a battery swapping cabinet as described in claim 6, characterized in that: The security protection module is specifically used for: The control board monitors the current anomaly detection results, voltage anomaly detection results, and temperature anomaly detection results in real time. When the current anomaly detection results, voltage anomaly detection results, or temperature anomaly detection results carry a Class A anomaly, the power supply circuit of the corresponding battery is immediately cut off and the aerosol is activated; when carrying a Class B anomaly, the charging and discharging operation of the corresponding battery is suspended, the fan cooling system is activated, or the vent is opened; when carrying a Class C anomaly, the abnormal behavior is recorded and the corresponding battery is marked as pending inspection, and a suggested repair prompt is displayed on the screen.

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