A shared electric bicycle charging and changing power safety intelligent monitoring system

Abstract

The application is suitable for the technical field of charging and battery swapping, and provides a shared electric bicycle charging and battery swapping safety intelligent monitoring system, which comprises a distributed battery compartment unit, a main control unit, an environmental safety sensor, a vibration sensor, a fire-fighting linkage device, a first communication unit, a cloud platform, a second communication unit, a user mobile terminal and a terminal server; the cloud platform judges the working state of each battery compartment in the distributed battery compartment unit based on the received monitoring data, divides monitoring priority groups for differential analysis, generates analysis results containing battery state information, battery early warning information, fault details and fire early warning signals, and sends the analysis results to the user mobile terminal, the terminal server and the main control unit for feedback; the accuracy of monitoring and the resource utilization efficiency are significantly improved, thereby effectively solving the problems of single monitoring dimension, early warning lag and low operation and maintenance response efficiency in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of charging and battery swapping, in particular to a shared electric bicycle charging and battery swapping safety intelligent monitoring system. BACKGROUND

[0002] As an important tool for urban short-distance travel, the supporting charging and battery swapping facility network of shared electric bicycles is the key infrastructure to ensure operation. At present, the commonly used scheme in the industry for charging and battery swapping safety monitoring is to deploy basic voltage and current sensors in the charging cabinet and set a unified threshold for overcharge and overcurrent and overvoltage protection. This monitoring method is relatively simple to implement, and is usually judged by a local controller on the collected electrical parameters, and if it is out of limit, the circuit is cut off. In actual application, due to the inability to monitor the battery temperature, connection point heating, electrolyte leakage and volatilization and other key safety states, it is difficult to effectively prevent serious safety accidents such as thermal runaway; on the other hand, the fixed frequency data collection and reporting mode is adopted for all battery compartments, the calculation resource allocation is unreasonable, and it is difficult to monitor the high-risk batteries, resulting in low overall monitoring efficiency and difficulty in achieving comprehensive and efficient safety monitoring of the shared electric bicycle battery charging and battery swapping process.

[0003] In view of this, a shared electric bicycle charging and battery swapping safety intelligent monitoring system is provided. SUMMARY

[0004] The present application provides a shared electric bicycle charging and battery swapping safety intelligent monitoring system, which solves the problem of insufficient comprehensive and efficient safety monitoring of the shared electric bicycle battery charging and battery swapping process.

[0005] The present application provides a shared electric bicycle charging and battery swapping safety intelligent monitoring system, which includes:

[0006] Distributed battery compartment unit, main control unit, environmental safety sensor, vibration sensor, fire-fighting linkage device, first communication unit, cloud platform, second communication unit, user mobile terminal and terminal server;

[0007] The main control unit is connected to the distributed battery compartment unit, environmental safety sensor, vibration sensor and fire-fighting linkage device; the main control unit is connected to the cloud platform through the first communication unit; the cloud platform is connected to the user mobile terminal and terminal server through the second communication unit;

[0008] The cloud platform judges the working state of each battery compartment in the distributed battery compartment unit based on the received monitoring data, divides monitoring priority groups for differential analysis, generates analysis results including battery state information, battery early warning information, fault details and fire warning signals, and sends the analysis results to the user mobile terminal, terminal server and master control unit; so that the user mobile terminal generates state display feedback to the user according to the battery state information, and generates early warning notification feedback to the user according to the battery early warning information; the terminal server generates operation and maintenance alarm disposal instructions feedback to the operation and maintenance personnel according to the battery early warning information and fault details; the master control unit starts the fire-fighting linkage device according to the fire warning signal.

[0009] Further, the distributed battery compartment unit is arranged in a charging and battery replacement cabinet, and the distributed battery compartment unit includes a plurality of battery compartments, each of which is independently provided with a charge and discharge control submodule, a voltage sensor, a current sensor, a first temperature sensor, a second temperature sensor and a connector state sensor; wherein:

[0010] The voltage sensor is used to collect the real-time voltage value of the battery;

[0011] The current sensor is used to collect the real-time charging current value of the battery;

[0012] The first temperature sensor is attached to the surface of the battery and is used to collect the temperature of the battery body;

[0013] The second temperature sensor is arranged near the battery electrode connector in the battery compartment and is used to collect the temperature of the connection point to monitor abnormal heating caused by excessive contact resistance;

[0014] The connector state sensor is used to detect whether the battery plug and the in-compartment connector are physically connected in place;

[0015] The charge and discharge control submodule is used to execute the operation of turning on or turning off the charging circuit of the battery compartment according to the instructions of the cloud platform or the master control unit.

[0016] Further, the master control unit includes a master micro control module and a plurality of slave micro control modules; each slave micro control module is arranged in a battery compartment and is used to collect the original data of the voltage sensor, the current sensor, the first temperature sensor, the second temperature sensor and the connector state sensor in the battery compartment; the master micro control module communicates with all slave micro control modules through an internal bus and is used to preprocess the data collected by the slave micro control modules.

[0017] Further, the environmental safety sensors include a smoke sensor and a combustible gas sensor; the smoke sensor and the combustible gas sensor are respectively arranged in different monitoring areas in the charging and swapping cabinet, each monitoring area covering one or more adjacent battery compartments; wherein:

[0018] The smoke sensor is used to detect visible smoke caused by battery thermal runaway;

[0019] The combustible gas sensor is used to detect volatile combustible gas generated by decomposition of battery electrolyte.

[0020] Further, the working states include a charging state, a full-electricity standing state and an idle empty compartment state; the charging state is that the battery is being charged; the full-electricity standing state is that the battery has been fully charged but is still stored in the compartment; and the idle empty compartment state is that the battery compartment is empty.

[0021] Further, the cloud platform determines the working state of each battery compartment in the distributed battery compartment unit based on the received monitoring data, including:

[0022] For any battery compartment,

[0023] If the current value of the battery compartment is greater than the charging start-stop threshold, and the connector state of the battery compartment is connected, and the condition that the current value is greater than the charging start-stop threshold continues to exceed the first preset time, it is determined that the battery compartment is in the charging state;

[0024] If the current value of the battery compartment is less than or equal to the charging start-stop threshold, and the connector state of the battery compartment is connected, and the condition that the current value is less than or equal to the charging start-stop threshold continues to exceed the second preset time, it is determined that the battery compartment is in the full-electricity standing state;

[0025] If the connector state of the battery compartment is not connected, it is determined that the battery compartment is in the idle empty compartment state.

[0026] Further, the cloud platform determines the working state of each battery compartment in the distributed battery compartment unit based on the received monitoring data, further including:

[0027] For the battery compartment in the charging state, if the rising rate of the battery body temperature calculated based on the first temperature sensor data exceeds the safe temperature rising rate threshold, the battery compartment is marked as about to enter the full-electricity standing state or the abnormal charging state in advance before the current of the battery compartment drops to the threshold;

[0028] Or,

[0029] calculating the average temperature of all battery bays in charging state at the same time; for any battery bay in charging state, if the absolute value of the difference between the temperature data of the battery bay and the average temperature exceeds the preset range, it is determined that the battery bay is in abnormal charging state.

[0030] Further, the division of the monitoring priority groups for differential analysis includes:

[0031] calculating the comprehensive risk score corresponding to each battery bay , the calculation formula is:

[0032]

[0033] wherein: is the voltage sampling value, is the current sampling value, is the first temperature value, is the second temperature value, is the first temperature change rate, is the environmental safety risk value, is the normalization processing function, , , , , are the weighting coefficients, respectively;

[0034] comparing the comprehensive risk score with a preset threshold value, and dividing the battery bay into different monitoring priority groups:

[0035] if , it is divided into the emergency disposal group;

[0036] if , it is divided into the key attention group;

[0037] if , it is divided into the regular monitoring group;

[0038] wherein, is the emergency disposal threshold value, is the regular monitoring threshold value, and .

[0039] Further, the division of the monitoring priority groups for differential analysis generates analysis results including battery state information, battery warning information, fault details and fire warning signals, including:

[0040] for the battery bay divided into the emergency disposal group:

[0041] obtaining the raw data of the voltage, current, first temperature and second temperature of the battery bay at a first preset frequency;

[0042] matching the raw data with a battery thermal runaway feature library in real time;

[0043] if the matching degree exceeds a first risk threshold, generating a fire warning signal, and the fault details including the specific thermal runaway feature matched;

[0044] if no thermal runaway feature is matched but the first temperature value exceeds an absolute safety threshold, generating a battery warning information of the highest priority, and the fault details including the sensor location and value of over-temperature;

[0045] for the battery compartment drawn into the focus group:

[0046] acquiring voltage, current and temperature data of the battery compartment at a second preset frequency, the second preset frequency being lower than the first preset frequency;

[0047] predicting future trends of voltage curve and temperature curve of the battery compartment based on historical data;

[0048] if the deviation of the prediction result from a standard charging model exceeds an allowable error threshold, generating a battery warning information of a medium priority, and the fault details including the predicted abnormal trend and the deviation value;

[0049] for the battery compartment drawn into the regular monitoring group:

[0050] acquiring voltage, current and connector state data of the battery compartment at a third preset frequency, the third preset frequency being lower than the second preset frequency;

[0051] comparing the acquired data with a preset normal working range;

[0052] if the data are all within the normal working range, generating battery status information including current power and health status;

[0053] if the data exceed the normal working range, recalculating the comprehensive risk score of the battery compartment and triggering a new grouping determination.

[0054] Further, the terminal server generates operation and maintenance alarm handling instructions according to the battery warning information and fault details respectively and feeds back to operation and maintenance personnel, including:

[0055] analyzing the warning priority and warning type contained in the battery warning information;

[0056] analyzing the fault code, fault battery compartment number, sensor data triggering the fault and occurrence time contained in the fault details;

[0057] According to the early warning priority, early warning type and fault code, a corresponding standardized operation and maintenance work order is generated, and the operation and maintenance work order includes a treatment suggestion and a completion time limit.

[0058] From the above technical solutions, the present application has the following advantages:

[0059] In the system of the present application, multi-dimensional data of each battery compartment is collected by a distributed battery compartment unit, and is uploaded to a cloud platform through a first communication unit after being preprocessed by a master control unit; the cloud platform judges the working state of each battery compartment based on the received monitoring data, and divides monitoring priority groups for differential analysis, and generates analysis results including battery state information, battery early warning information, fault details and fire warning signals; the analysis results are respectively sent to a user mobile terminal, a terminal server and a master control unit, triggering different response mechanisms; wherein the user mobile terminal generates state display and early warning notification feedback to the user, the terminal server generates operation and maintenance alarm disposal instructions to feedback to the operation and maintenance personnel, and the master control unit starts a fire-fighting linkage device according to the fire warning signal. Therefore, through the combination of hardware cooperation and cloud intelligent processing, comprehensive and multi-level monitoring of the charging and battery swapping process from electrical parameters to environmental safety is realized, and the accuracy and resource utilization efficiency of monitoring are significantly improved through differential processing of battery compartments with different risk levels, thereby effectively solving the problems of single monitoring dimension, early warning lag and low operation and maintenance response efficiency in the prior art, and improving the system safety. BRIEF DESCRIPTION OF DRAWINGS

[0060] Figure 1 It is an architecture diagram of a shared electric bicycle charging and battery swapping safety intelligent monitoring system in the present application.

[0061] Figure 2 It is an embodiment flowchart of a shared electric bicycle charging and battery swapping safety intelligent monitoring system in the present application. DETAILED DESCRIPTION

[0062] The terms "first", "second", "third", "fourth" and the like in the specification of this application and the above drawings, if any, are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "correspond to" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0063] Embodiment one

[0064] Referring to Figure 1 The shared electric bicycle charging and changing safety intelligent monitoring system comprises a distributed battery compartment unit 1, a master control unit 2, an environmental safety sensor 3, a vibration sensor 4, a fire linkage device 5, a first communication unit 6, a cloud platform 7, a second communication unit 8, a user mobile terminal 9 and a terminal server 10. The master control unit 2 is connected with the distributed battery compartment unit 1, the environmental safety sensor 3, the vibration sensor 4 and the fire linkage device 5 respectively. The master control unit 2 is connected with the cloud platform 7 through the first communication unit 6. The cloud platform 7 is connected with the user mobile terminal 9 and the terminal server 10 through the second communication unit 8. The cloud platform 7 judges the working state of each battery compartment in the distributed battery compartment unit 1 based on the received monitoring data, divides monitoring priority groups for differential analysis, generates analysis results containing battery state information, battery early warning information, fault details and fire warning signals, and sends the analysis results to the user mobile terminal 9, the terminal server 10 and the master control unit 2. The user mobile terminal 9 generates state display feedback to the user according to the battery state information, and generates early warning notification feedback to the user according to the battery early warning information. The terminal server 10 generates operation and maintenance alarm disposal instructions to the operation and maintenance personnel according to the battery early warning information and the fault details. The master control unit 2 starts the fire linkage device 5 according to the fire warning signal.

[0065] In this embodiment, the distributed battery compartment unit 1 is arranged in the charging and changing cabinet. The distributed battery compartment unit 1 comprises a plurality of battery compartments (1-n), each of which is independently provided with a voltage sensor 101, a current sensor 102, a first temperature sensor 103, a second temperature sensor 104, a connector state sensor 105 and a charging and discharging control submodule 106. The voltage sensor 101 is used to collect the real-time voltage value of the battery. The current sensor 102 is used to collect the real-time charging current value of the battery. The first temperature sensor 103 is attached to the surface of the battery and is used to collect the temperature of the battery body. The second temperature sensor 104 is arranged near the battery electrode connector in the battery compartment and is used to collect the temperature of the connection point to monitor the abnormal heating caused by excessive contact resistance. The connector state sensor 105 is used to detect whether the battery plug and the in-compartment connector are physically connected in place. The charging and discharging control submodule 106 is used to perform the operation of connecting or disconnecting the charging loop of the battery compartment according to the instructions of the master control unit 2 or the cloud platform 7.

[0066] Specifically, each battery compartment in the distributed battery compartment unit 1 constitutes an independent monitoring unit, wherein the first temperature sensor 103 directly contacts the surface of the battery shell with a patch negative temperature coefficient thermistor for monitoring the core temperature of the battery cell; the second temperature sensor 104 uses an infrared temperature sensor to point to the metal contact point of the battery electrode and the cabinet connector, which is specially used to detect the local overheating caused by the increase of contact resistance due to poor contact and oxidation corrosion. The fundamental reason for setting double temperature sensors is that the shared electric bicycle battery is frequently plugged and used, which easily leads to physical wear and tear of the connector and changes in contact resistance. Monitoring only the battery cell temperature cannot early warn of the risk of overheating of the connection point, and overheating of the connection point is often the direct cause of fire.

[0067] When the battery is inserted into the compartment, the connector state sensor 105 (using a microswitch structure) first detects the physical connection in place signal, the voltage sensor 101 (analog-to-digital converter sampling circuit) and the current sensor 102 (Hall effect sensor) continuously collect charging and discharging parameters, and the first temperature sensor 103 and the second temperature sensor 104 synchronously collect temperature data at a frequency of 1 Hz. All sensor data are preliminarily processed by the charging and discharging control submodule 106 (smart switch circuit with built-in MCU) dedicated to the compartment; the submodule has local decision-making capability, and when it detects that the current or temperature exceeds the local safety threshold, it can immediately cut off the loop of the compartment (response time <100 ms), while receiving remote control instructions issued by the main control unit 2 or the cloud platform 7.

[0068] In this embodiment, the main control unit 2 includes a main micro control module 201 and a plurality of slave micro control modules 202; each slave micro control module is arranged in a battery compartment for collecting raw data of the voltage sensor 101, the current sensor 102, the first temperature sensor 103, the second temperature sensor 104 and the connector state sensor 105 in the battery compartment; the main micro control module 201 communicates with all slave micro control modules through an internal bus for preprocessing the data collected by the slave micro control modules 202.

[0069] Specifically, the master control unit 2 adopts a distributed control system architecture, wherein the slave micro control module 202 adopts a low-power ARM Cortex-M0 core chip embedded in each battery compartment, directly collects all sensor raw data in the compartment through an I2C / SPI interface; the master micro control module 201 adopts a multi-core Cortex-A7 industrial processor, establishes communication with all slave micro control modules 202 through a CAN bus, and adopts a time division multiple access polling mechanism to obtain each compartment data packet. In implementation, taking a 12-compartment battery charging and replacing cabinet as an example, 12 slave micro control modules 202 synchronously collect sensor data in the compartment, the master micro control module 201 polls a slave module to obtain a compressed data packet every 100 ms, after completing all polling, performs time stamp alignment, Kalman filter anti-jitter, and outlier rejection on 12 battery compartment data for preprocessing, generates a standard structured data frame, and uploads the cloud platform through the first communication unit 6. When a slave module fails, the master module can automatically isolate the node and alarm, without affecting the normal monitoring of other compartments.

[0070] In the embodiment, the environmental safety sensor 3 includes a smoke sensor 301 and a flammable gas sensor 302; the smoke sensor 301 and the flammable gas sensor 302 are respectively arranged in different monitoring areas in the battery charging and replacing cabinet, each monitoring area covers one or more adjacent battery compartments; wherein: the smoke sensor 301 is used to detect visible smoke caused by battery thermal runaway; the flammable gas sensor 302 is used to detect volatile flammable gas produced by decomposition of battery electrolyte.

[0071] Specifically, the smoke sensor 301 adopts a photoelectric sensing principle, and identifies smoke particles by monitoring the scattering change of light of a specific wavelength in a detection cavity; the flammable gas sensor 302 adopts a metal oxide semiconductor sensing principle, and identifies flammable gas by detecting the conductivity change caused by the oxidation-reduction reaction between volatile organic compounds produced by electrolyte decomposition and sensitive materials. The two sensors are arranged in different zones to form a three-dimensional monitoring network: a flammable gas sensor 302 is arranged at the center of each monitoring area for early warning (electrolyte decomposition occurs earlier than fire), and a smoke sensor 301 is arranged at the top of the cabinet where smoke is easy to accumulate for fire confirmation.

[0072] In implementation, taking the monitoring area covering 4 battery compartments as an example, the combustible gas sensor 302 is installed at the middle ventilation of the compartment body to monitor the concentrations of hydrogen, carbon monoxide and hydrocarbons in real time. When the concentration of volatile organic compounds is detected to continuously increase at a rate exceeding the threshold value, a first-level early warning is immediately sent to the main control unit 2. The smoke sensor 301 is installed at the top of the cabinet and triggers a second-level confirmation alarm when visible smoke particles are detected. The data of the two sensors are jointly involved in the risk assessment of the cloud platform 7 through a weighted fusion algorithm to achieve a graded response in different stages of battery thermal runaway, which is 3-5 minutes earlier than the traditional single smoke detection method to issue a warning and gain critical time for emergency disposal.

[0073] In this embodiment, the vibration sensor 4 adopts a high-precision micro-electro-mechanical system accelerometer installed on the main load-bearing beam or mounting plate inside the battery charging and swapping cabinet. The sensing axis direction is consistent with the vertical direction of the cabinet body, which is used to monitor whether the cabinet is subjected to external impact, illegal handling or abnormal vibration. The working principle is to continuously monitor the three-axis acceleration data. When the vibration amplitude exceeds the safety threshold value, such as the inclination angle > 5° or the impact acceleration > 3g, it is determined as an abnormal event, triggering the anti-theft alarm. The fire linkage device 5 adopts a distributed unit design, including a fire extinguishing agent storage container, a distribution pipeline and a fire extinguishing nozzle corresponding to each battery compartment. The fire extinguishing nozzle is controlled by an electromagnetic valve and located above each battery compartment. The fire extinguishing agent delivery pipeline is made of high-pressure resistant insulating material. The working principle is that when the main control unit 2 receives the fire warning signal issued by the cloud platform 7, the electromagnetic valve of the corresponding battery compartment is started to release insulating fire extinguishing agents such as perfluorohexone to the fire extinguishing nozzle of the specified battery compartment through the distribution pipeline for point firefighting, while the power supply loop of the compartment is cut off.

[0074] In this embodiment, the first communication unit 6 is an industrial-grade 4G / 5G or NB-IoT Internet of Things communication module integrated in the main control unit 2. It adopts TCP / IP protocol to establish a secure tunnel connection with the cloud platform 7 for reliable transmission of encrypted data packets preprocessed by the main control unit 2 to the cloud platform 7. The second communication unit 8 is an Internet API interface and mobile network communication gateway deployed on the cloud service platform side, which adopts HTTPS / SSL encryption communication protocol to establish a bidirectional data channel between the cloud platform 7 and the user mobile terminal 9 and the terminal server 10, realizing the delivery of analysis results and the upload of user instructions.

[0075] Embodiment Two

[0076] Please refer to Figure 2 This embodiment describes in detail the core processing flow of the cloud platform 7 for intelligent analysis based on monitoring data. The principle of this embodiment is described in detail below in conjunction with the flowchart:

[0077] First, check the connector state of each battery compartment. If the connector state is not connected, it is directly determined that the compartment is in an idle empty compartment state. If the connector state is connected, further analyze the current value and its duration. If the current value is greater than the charge start-stop threshold and the condition lasts more than a first preset time (such as 30 seconds), it is determined that the compartment is in a charging state. If the current value is less than or equal to the charge start-stop threshold and the condition lasts more than a second preset time (such as 5 minutes), it is determined that the compartment is in a stationary full power state. The introduction of duration judgment effectively avoids misjudgment caused by transient current fluctuations.

[0078] For battery compartments determined to be in a charging state, the cloud platform 7 further executes a defined abnormality prediction mechanism. Mechanism one: calculate the battery body temperature change rate based on the first temperature sensor data. If the change rate exceeds the safe temperature rise rate threshold, it indicates that the battery may enter an abnormal heating stage. The system will mark it as an abnormal charging state in advance before its current naturally decreases. Mechanism two: calculate the average temperature of all battery compartments in a charging state at the same time. If the absolute value of the difference between the temperature (first temperature value or second temperature value) of a certain battery compartment and the average temperature exceeds a preset range, it is determined that the compartment is in an abnormal charging state. This design can effectively identify local overheating caused by individual faults (such as connection point oxidation).

[0079] After completing the state judgment, the cloud platform 7 calculates a comprehensive risk score for each battery compartment. This score is a multi-parameter fusion function, and the calculation formula is as follows:

[0080]

[0081] Wherein: is the voltage sampling value, is the current sampling value, is the first temperature value, is the second temperature value, is the first temperature change rate, is the environmental safety risk value, calculated by fusing the monitoring data of the smoke sensor and the flammable gas sensor, is the normalization processing function, , , , , are the weighting coefficients, respectively;

[0082] In specific implementation, the normalization processing function can use the maximum and minimum normalization method to map each parameter to the [0, 1] interval, and the calculation formula is wherein and are parameters preset safety upper and lower limits, where the parameters may be voltage, temperature, etc.

[0083] environmental safety risk value The fusion calculation can be performed according to the following rules: define the flammable gas concentration risk value and the smoke concentration risk value , and use weighted summation for fusion, i.e. , where and may be determined according to the ratio of the sensor reading to its alarm threshold, and are preset weights, and to reflect the importance of flammable gas as an earlier warning indicator.

[0084] The values of the above weighting coefficients , , , , reflect the contribution of each monitoring parameter to the comprehensive risk score, which can be determined through historical failure data training or expert experience. In one preferred configuration example, temperature-related parameters, in particular the temperature change rate have the highest weight, i.e. ; for example, a set of example values can be set as: , , , , , and the sum of the coefficients is 1. The threshold values and may be set based on the statistical distribution of a large number of normal and abnormal state samples, for example , .

[0085] The calculated comprehensive risk score is compared with the preset threshold value, and the battery compartment is divided into different monitoring priority groups:

[0086] If , it is classified into the emergency disposal group;

[0087] If , it is classified into the key attention group;

[0088] If , it is classified into the regular monitoring group;

[0089] where is the emergency disposal threshold value, is the regular monitoring threshold value, and .

[0090] Finally, the cloud platform 7 performs a differentiated analysis strategy on different priority groups to generate the final analysis results:

[0091] For the battery compartment classified into the emergency treatment group, the system immediately starts the highest level of monitoring response. The first preset frequency is set to 1 Hz (i.e., 1 acquisition per second), and the acquired voltage, current, and two-point temperature raw data streams are input into a preset battery thermal runaway feature library in real time for parallel matching. The feature library is generated by machine learning algorithm training and contains multiple-dimensional feature patterns such as typical voltage drop, current abnormal fluctuation, and temperature exponential rise in the early and middle stages of battery thermal runaway. The matching process uses a dynamic time warping algorithm to calculate the similarity between the real-time data sequence and the feature sequence. If the matching degree exceeds the first risk threshold (such as 85%), it is determined that the thermal runaway risk is extremely high, and a fire warning signal is immediately generated; if the matching degree does not exceed the limit but the first temperature value exceeds the absolute safety threshold (such as 80°C) for 2 seconds, it is determined as serious overheating, and the highest priority battery warning information is generated. The fault details include the specific feature code, value, and timestamp of the triggering alarm, providing accurate basis for operation and maintenance.

[0092] For the battery compartment classified into the key attention group, the system starts the preventive monitoring mode. The second preset frequency is set to 0.2 Hz (i.e., 1 acquisition every 5 seconds) to balance the monitoring depth and system load. The system uses a time series analysis algorithm to predict the future short-term trend of the voltage curve and temperature curve of the compartment. The prediction result is compared with the standard charging model. If the deviation of the prediction value exceeds the allowed error threshold, such as voltage prediction error > 5% or temperature prediction error > 3°C, a medium-priority battery warning information is generated. This warning aims to prompt potential risks and prompt the system to pay attention in advance, and the fault details will include the predicted abnormal trend, deviation value, and confidence.

[0093] For the battery compartment classified into the regular monitoring group, the system adopts a resource-saving inspection strategy. The third preset frequency is set to 0.02 Hz (i.e., 1 acquisition every 50 seconds). The analysis strategy is simplified to threshold comparison of the acquired data with the preset normal working range; for example, voltage range: 41V-58V; current range: 0A-5A. If all data are within the normal range, the battery status information containing the current power, health, etc. is generated to update the system status and user display. If any data exceeds the normal working range, the compartment's comprehensive risk score is recalculated immediately, and a new grouping determination is triggered according to the new score result.

[0094] In this embodiment, the terminal server generates operation and maintenance alarm handling instructions according to the battery warning information and fault details, respectively, and feeds back to the operation and maintenance personnel, including:

[0095] 1. Analyze the warning priority and warning type contained in the battery warning information;

[0096] 2. Analyze the fault code, fault battery compartment number, sensor data triggering the fault, and occurrence time contained in the fault details;

[0097] 3. According to the early warning priority, early warning type and fault code, a corresponding standardized operation and maintenance work order is generated, which contains treatment suggestions and completion time limit.

[0098] The specific process includes: first, analyzing the received battery early warning information, extracting the early warning priority (such as highest, intermediate) and early warning type (such as over-temperature, connection fault, gas leakage, etc.) therein; at the same time, analyze the fault details to obtain the fault code (such as F001 representing temperature anomaly), fault battery compartment number (such as A07 compartment), sensor data specific value triggering the fault and its occurrence time. The terminal server 10 automatically generates a standardized operation and maintenance work order according to the above information. The work order not only contains the basic information of the fault, but also has intelligent treatment suggestions and clear completion time limit, such as emergency inspection of A07 compartment connector and temperature measurement, highest priority work order needs to be accepted within 15 minutes, and automatically distributed to the mobile terminal of the operation and maintenance personnel through the message queue, to drive the on-site personnel to carry out accurate and efficient treatment.

[0099] At the same time, the user mobile terminal 9 provides state visualization and safety warning service to the terminal user, which receives the battery state information and battery early warning information issued by the cloud platform 7, and after analysis, clearly shows the current state of the vehicle such as power, health, and estimated full charge time to the user through a graphical interface. When receiving the early warning information, different intensity of push notification will be triggered according to the early warning level to inform the user that your battery is being safely charged or abnormality is detected, please replace the battery, which improves the user experience.

[0100] The principles of the embodiments of the present application will be described in detail in conjunction with actual application scenarios:

[0101] Taking a shared electric bicycle centralized charging station on Minzu Avenue in Qingxiu District, Nanning City as an example, the working process of the 16-compartment intelligent charging and replacing cabinet configured at the site after accessing the system is as follows:

[0102] When the operation and maintenance personnel batch-insert a batch of used batteries into the cabinet, the connector state sensor 105 in each battery compartment first detects the physical connection signal, and the charge and discharge control submodule 106 immediately closes the loop to start charging. The slave microcontrol module 202 in each battery compartment collects the voltage, current and two-point temperature data (cell surface temperature T1 and electrode connection point temperature T2) in the compartment at a frequency of 10Hz, and the master microcontrol module 201 obtains all data packets through CAN bus polling, and then performs timestamp alignment and filtering processing.

[0103] During the charging process, the cloud platform 7 continuously receives the monitoring data uploaded by the first communication unit 6; first, according to the current threshold and the connection state, the working state of each bin is judged, for example, 12 bins are in the charging state, and 4 bins are in the idle state; then, based on multi-dimensional data, the comprehensive risk score is calculated In the example, the battery in the A09 bin increases the contact resistance due to the aging of the electrode connector, the second temperature sensor 104 monitors that the connection point temperature abnormally rises to 65°C (25°C higher than the adjacent bin), and at the same time, the current fluctuation value of the bin exceeds the normal range by 30%. After the risk assessment model of the cloud platform 7 comprehensively considers these parameters, it calculates that The value exceeds the emergency disposal threshold The A09 bin is immediately included in the emergency disposal group.

[0104] The cloud platform 7 sends the highest priority alarm to the terminal server 10 through the second communication unit 8, generates an operation and maintenance work order containing the accurate positioning (A09 bin at the site of the National Avenue in the Qingxiu District), the fault type (overheating of the connection point), and the disposal suggestion (immediately replace the connector); at the same time, a safety reminder is pushed to the user mobile terminal 9 that is using the batch of batteries. The cloud platform issues an instruction to the main control unit 2 to control the charge-discharge control submodule 106 of the A09 bin to cut off the charging circuit and start the standby state of the fire sprinkler corresponding to the bin. During the entire process, the charging operation of other normal battery bins is completely unaffected.

[0105] Through the implementation of the system, the early warning is successfully sent 15 minutes before the potential thermal accident occurs, the operation and maintenance personnel arrive at the scene to complete the fault processing within 8 minutes, and the possible fire accident is avoided. The system is particularly suitable for the shared electric bicycle operation scene in the high temperature and high humidity environment in Nanning, and through distributed monitoring and centralized intelligent analysis, multi-dimensional protection from electrical parameters to environmental safety is realized, and the safety and operation efficiency of the charging and battery replacement facility are significantly improved.

[0106] It can be understood that those skilled in the art can combine various embodiments in the above embodiments under the guidance of the above embodiments to obtain technical solutions of various embodiments.

[0107] The above only describes the preferred embodiments of the present application and should not be used to limit the present application. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A shared electric bicycle charging and battery swapping safety intelligent monitoring system, characterized in that, include: Distributed battery compartment unit, main control unit, environmental safety sensor, vibration sensor, fire alarm linkage device, first communication unit, cloud platform, second communication unit, user mobile terminal and terminal server; The main control unit is connected to the distributed battery compartment unit, environmental safety sensor, vibration sensor, and fire alarm linkage device respectively; the main control unit is connected to the cloud platform through the first communication unit; the cloud platform is connected to the user mobile terminal and terminal server through the second communication unit. The cloud platform determines the working status of each battery compartment in the distributed battery compartment unit based on the received monitoring data, and divides the monitoring priority groups for differentiated analysis. It generates analysis results including battery status information, battery warning information, fault details, and fire warning signals, and sends the analysis results to the user's mobile terminal, terminal server, and main control unit. This enables the user's mobile terminal to generate status displays based on the battery status information and send them back to the user, and at the same time generate warning notifications based on the battery warning information and send them back to the user. The terminal server generates maintenance alarm handling instructions based on the battery warning information and fault details, and feeds them back to the maintenance personnel. The main control unit activates the fire-fighting linkage device according to the fire warning signal; The process of dividing monitoring priority groups for differential analysis includes: Calculate the overall risk score for each battery compartment. The calculation formula is: in: This is the voltage sample value. This is the current sample value. The first temperature value. This is the second temperature value. The first rate of temperature change, Environmental safety risk value, This is the normalization function. , , , , These are the weighting coefficients; The comprehensive risk score is compared with a preset threshold, and the battery compartment is divided into different monitoring priority groups: like If so, it will be assigned to the emergency response team; like If so, they will be placed in the key monitoring group; like If so, it will be assigned to the regular monitoring group; in, As an emergency response threshold, This is a standard monitoring threshold, and .

2. The shared electric bicycle charging and battery swapping safety intelligent monitoring system according to claim 1, characterized in that, The distributed battery compartment unit is located within the charging and swapping cabinet. The distributed battery compartment unit includes several battery compartments, each of which independently houses a charging / discharging control submodule, a voltage sensor, a current sensor, a first temperature sensor, a second temperature sensor, and a connector status sensor; wherein: The voltage sensor is used to collect the real-time voltage value of the battery; The current sensor is used to collect the real-time charging current value of the battery; The first temperature sensor is attached to the surface of the battery and is used to collect the temperature of the battery body; The second temperature sensor is located near the battery electrode connector inside the battery compartment to collect the temperature of the connection point in order to monitor abnormal heating caused by excessive contact resistance. The connector status sensor is used to detect whether the battery plug and the connector inside the compartment are physically connected in place. The charging and discharging control submodule is used to perform the operation of connecting or disconnecting the charging circuit of the battery compartment according to the instructions of the cloud platform or the main control unit.

3. The shared electric bicycle charging and battery swapping safety intelligent monitoring system according to claim 2, characterized in that, The main control unit includes a main microcontroller module and multiple slave microcontroller modules; each slave microcontroller module is located in a battery compartment and is used to collect raw data from the voltage sensor, current sensor, first temperature sensor, second temperature sensor and connector status sensor in the battery compartment; the main microcontroller module communicates with all slave microcontroller modules through an internal bus and is used to preprocess the data collected by the slave microcontroller modules.

4. The shared electric bicycle charging and battery swapping safety intelligent monitoring system according to claim 1, characterized in that, The environmental safety sensors include smoke sensors and combustible gas sensors; the smoke sensors and combustible gas sensors are respectively installed in different monitoring areas within the charging and swapping cabinet, and each monitoring area covers one or more adjacent battery compartments; wherein: The smoke sensor is used to detect visible smoke caused by battery thermal runaway; The combustible gas sensor is used to detect volatile combustible gases produced by the decomposition of battery electrolyte.

5. The shared electric bicycle charging and battery swapping safety intelligent monitoring system according to claim 1, characterized in that, The operating states include charging state, fully charged resting state, and empty compartment state; the charging state is when the battery is being charged; the fully charged resting state is when the battery has been fully charged but is still stored in the compartment; the empty compartment state is when no battery is placed in the battery compartment.

6. The shared electric bicycle charging and battery swapping safety intelligent monitoring system according to claim 2, characterized in that, The cloud platform determines the working status of each battery compartment in the distributed battery compartment unit based on the received monitoring data, including: For any battery compartment If the current value of the battery compartment is greater than the charging start / stop threshold, and the connector status of the battery compartment is connected, and the condition that the current value is greater than the charging start / stop threshold continues for more than a first preset time, then the battery compartment is determined to be in a charging state. If the current value of the battery compartment is less than or equal to the charging start / stop threshold, and the connector status of the battery compartment is connected, and the condition that the current value is less than or equal to the charging start / stop threshold continues for more than a second preset time, then the battery compartment is determined to be in a static fully charged state. If the connector of the battery compartment is not connected, the battery compartment is determined to be in an empty state.

7. The shared electric bicycle charging and battery swapping safety intelligent monitoring system according to claim 6, characterized in that, The cloud platform determines the working status of each battery compartment in the distributed battery compartment unit based on the received monitoring data, and also includes: For a battery compartment that is in a charging state, if the rate of increase of the battery body temperature calculated based on the data from the first temperature sensor exceeds the safe temperature rise rate threshold, the battery compartment will be marked as about to enter a fully charged static state or an abnormal charging state before the current in the battery compartment drops to the threshold. or, Calculate the average temperature of all battery compartments that are charging at the same time. For any battery compartment that is charging, if the absolute value of the difference between the temperature data of the battery compartment and the average temperature exceeds a preset range, the battery compartment is determined to be in an abnormal charging state.

8. The shared electric bicycle charging and battery swapping safety intelligent monitoring system according to claim 1, characterized in that, The process of dividing monitoring priority groups for differential analysis generates analysis results including battery status information, battery warning information, fault details, and fire warning signals, including: Regarding the battery compartment that is assigned to the aforementioned emergency response group: The raw data of the voltage, current, first temperature and second temperature of the battery compartment are acquired at a first preset frequency. The raw data is matched in real time with the battery thermal runaway feature library; If the matching degree exceeds the first risk threshold, a fire warning signal is generated, and the fault details include the specific thermal runaway characteristics matched. If no thermal runaway characteristics are matched but the first temperature value exceeds the absolute safety threshold, a battery warning message with the highest priority is generated. The fault details include the location and value of the over-temperature sensor. For the battery compartments that fall under the aforementioned key concern group: The voltage, current and temperature data of the battery compartment are acquired at a second preset frequency, where the second preset frequency is lower than the first preset frequency. Predict the future trends of the voltage and temperature curves of the battery compartment based on historical data; If the deviation of the prediction result from the standard charging model exceeds the allowable error threshold, a medium-priority battery warning message is generated, and the fault details include the predicted abnormal trend and deviation value. For the battery compartment that is classified into the aforementioned regular monitoring group: The voltage, current and connector status data of the battery compartment are acquired at a third preset frequency, which is lower than the second preset frequency. The acquired data is compared with the preset normal working range; If all data are within the normal operating range, battery status information including current battery level and health status will be generated. If the data exceeds the normal operating range, the overall risk score of the battery compartment will be recalculated and a new grouping decision will be triggered.

9. The shared electric bicycle charging and battery swapping safety intelligent monitoring system according to claim 1, characterized in that, The terminal server generates maintenance alarm handling instructions based on the battery warning information and fault details, and sends them back to the maintenance personnel, including: Analyze the warning priority and warning type contained in the battery warning information; The fault details include the fault code, faulty battery compartment number, sensor data that triggered the fault, and the time of occurrence. Based on the warning priority, warning type and fault code, a corresponding standardized operation and maintenance work order is generated, which includes handling suggestions and completion deadlines.

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