Charging and discharging detection method, device and equipment for mining lithium battery and medium

Abstract

The invention belongs to the technical field of battery detection, and particularly provides a mine lithium battery charging and discharging detection method, which comprises the following steps: acquiring mine environment parameters and lithium battery state parameters in real time; obtaining a historical construction log, and calculating a corresponding construction stage of the mine environment parameter based on the historical construction log through time sequence analysis according to the mine environment parameter; inputting the mine environment parameters and the corresponding construction stage into a trained environment risk assessment model to output a current environment risk level; according to the lithium battery state parameters and the current environment risk level, the battery detection frequency and the charge and discharge protection threshold are dynamically adjusted, and a control instruction containing adjustment parameters is generated; switching a communication protocol based on the environmental risk level and sending the control instruction to the battery management system; by calculating the environmental risk level, corresponding measures can be taken according to the risk level; and the environmental risk level is added as a switching condition, so that the communication reliability and stability in different environments are ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery detection, and particularly relates to a charge and discharge detection method, device, equipment and medium for mine lithium batteries. Background Art

[0002] With the acceleration of the intelligent and electrification processes of mine exploitation, mine explosion-proof lithium batteries have been widely used in the power supply systems of underground electric equipment (such as mine trucks and drilling equipment) due to their advantages of high energy density and long cycle life. However, the mine environment has extreme working condition characteristics such as high gas concentration, high dust density, and strong vibration, which pose severe challenges to the safety management of lithium batteries. In the current existing technologies, there are some defects, for example: Single environmental parameter monitoring: Most solutions only focus on battery body parameters (such as voltage and temperature), while ignoring the unique environmental factors in mines, such as gas concentration and dust density, resulting in incomplete risk assessment.

[0003] Static threshold setting: Traditional methods use fixed charge and discharge thresholds (such as charging voltage ≤ 4.2V) and cannot dynamically adjust according to the environmental risk level. For example, in a high-risk scenario where the gas concentration > 1%, even if the battery parameters are normal, it is still necessary to significantly reduce the charge and discharge power to prevent electric sparks, but the existing technologies lack such a flexible control mechanism.

[0004] Insufficient communication reliability: Most of the existing solutions use a single communication protocol (such as CAN bus). Due to problems such as electromagnetic interference, signal attenuation, and equipment occlusion in mine tunnels, a single communication protocol is prone to data loss or data delay when the environment deteriorates, resulting in response lag and inability to trigger the protection mechanism in a timely manner.

[0005] In view of the above problems, there is an urgent need for a charge and discharge detection method that can integrate multiple environmental parameters, dynamically adjust the detection strategy, and adaptively optimize the communication link to achieve the full-life cycle safety control of lithium batteries in a complex mine environment. Summary of the Invention

[0006] In order to overcome the deficiencies of the prior art, the present invention provides a charge and discharge detection method, device, equipment and medium for mine lithium batteries to solve the problems in the prior art.

[0007] One embodiment of the present invention provides a charge and discharge detection method for mine lithium batteries, including the following steps: Real-time collect mine environmental parameters and lithium battery state parameters, where the mine environmental parameters at least include gas concentration, dust density, and vibration frequency, and the lithium battery state parameters at least include voltage, current, and temperature; Obtain historical construction logs. According to the collected mine environmental parameters, calculate the corresponding construction stages of the mine environmental parameters based on the historical construction logs through time series analysis; Input the mine environmental parameters and the corresponding construction stages into the trained environmental risk assessment model, and output the current environmental risk level through the environmental risk assessment model; According to the lithium battery state parameters and the current environmental risk level, dynamically adjust the battery detection frequency and the charge and discharge protection threshold, and generate a control instruction including the adjusted parameters; Switch the communication protocol based on the environmental risk level, and use the switched communication protocol to send the control instruction to the battery management system; Among them, in the step of dynamically adjusting the battery detection frequency and the charge and discharge protection threshold according to the lithium battery state parameters and the current environmental risk level and generating a control instruction including the adjusted parameters, the dynamic adjustment includes: When the environmental risk level increases, increase the detection frequency and decrease the upper limit of the charge and discharge current; When the environmental risk level decreases, decrease the detection frequency and increase the upper limit of the charge and discharge current.

[0008] By adopting the above solution, mine environmental parameters are collected and historical construction logs are obtained. The collected mine environmental parameters and the obtained historical construction logs are input into the environmental risk assessment model to obtain the risk level of the current environment in the mine, and corresponding measures can be taken according to the current risk level; the historical construction logs are the construction arrangements, completed projects, construction time arrangements, etc. in the mine. By using time series analysis, the current construction stage corresponding to the collected mine environmental parameters can be calculated based on the historical construction logs. By inputting the mine environmental parameters and the obtained corresponding construction stage into the trained environmental risk assessment model, the credibility of the output current environmental risk level can be increased. The state parameters of the lithium battery are collected. According to the collected state parameters of the lithium battery and the obtained current risk level, the detection frequency and the dynamic adjustment of the charge and discharge protection threshold of the explosion-proof lithium battery for mines can be made accordingly to adapt to the current risk level. For example, when it is found that the current risk level increases, the detection frequency is increased and the charge and discharge current is reduced. If an abnormality occurs, the detection frequency is increased to detect the abnormality faster. At the same time, the current is reduced to prevent the battery from overloading and causing danger in a high-risk environment. When it is found that the risk level decreases, it is restored; through dynamic adjustment, it can quickly respond in a high-risk situation and gradually recover after the risk decreases, thus avoiding the burden on the equipment caused by frequent switching. At the same time, the corresponding communication protocol is determined and switched according to the current risk level. For example, when the risk level is relatively low, CAN bus communication can be used to ensure the real-time transmission of control instructions. When the risk level is relatively high, in order to avoid problems such as signal attenuation, decreased stability, and even signal interruption caused by the deterioration of the mine internal environment, such as an increase in gas concentration, an increase in dust density, or an increase in vibration frequency, and the failure to trigger the protection mechanism in time, resulting in danger, the communication protocol is automatically switched to LoRa spread spectrum communication and data compression is enabled to ensure the stability of the transmission of control instructions. By adding the environmental risk level as a switching condition, the reliability and stability of communication in different environments are ensured, especially in the complex mine environment, achieving the effect of adaptive switching.

[0009] In one embodiment, after the step of switching the communication protocol based on the environmental risk level and sending the control instruction to the battery management system by using the switched communication protocol, the following steps are further included: The battery management system receives the control instruction and adjusts the output parameters according to the control instruction; Among them, adjusting the output parameters according to the control instruction specifically includes: If the real-time current in the collected state parameters of the lithium battery is within the range of the upper limit threshold of the charge and discharge current corresponding to the current environmental risk level, and the real-time voltage is within the safety threshold range, the output parameters of the battery management system only include the adjustment of the detection frequency; If the real-time current in the state parameters of the lithium battery being collected is greater than the upper threshold of the charge and discharge current corresponding to the current environmental risk level, and the real-time voltage is within the safety threshold range, the output parameters of the battery management system include adjustments to the detection frequency and current.

[0010] By adopting the above scheme, the safety values of the upper limits of the charge and discharge currents corresponding to different environmental risk levels are set, and the adjustment situation of the lithium battery is determined according to the current and voltage values of the state parameters of the lithium battery being collected, so that the charge and discharge of the lithium battery can be adjusted under different environmental risk levels, and the current voltage value is considered during the adjustment to prevent damage to the explosion-proof lithium battery caused by overvoltage or undervoltage and the occurrence of safety accidents.

[0011] In one embodiment, in the step of inputting the mine environmental parameters and the corresponding construction stage into the trained environmental risk assessment model and outputting the current environmental risk level through the environmental risk assessment model, the construction and training of the environmental risk assessment model include the following steps: Collect historical mine environmental parameters, their corresponding historical accident data, and obtain historical construction logs for preprocessing to obtain standardized feature data applied to the machine model as input data; Use the learning algorithm to train the environmental risk assessment model with the standardized feature data obtained after preprocessing to obtain the trained environmental risk assessment model, which is used to receive the mine environmental parameters and the corresponding construction stage in real time and output the current risk level.

[0012] By adopting the above scheme, the collected historical mine environmental parameters, their corresponding historical accident data, and the obtained historical construction logs are preprocessed to make the data suitable for the input requirements of the machine learning model; using the learning algorithm to train the environmental risk assessment model with the preprocessed data can enable the obtained environmental risk assessment model to output corresponding risk assessment results according to the input data in the future.

[0013] In one embodiment, in the step of collecting historical mine environmental parameters, their corresponding historical accident data, and obtaining historical construction logs for preprocessing to obtain standardized feature data applied to the machine model as input data, the following steps are specifically included: Collect historical mine environmental parameters and their corresponding historical accident data, and label the risk level for each historical environmental parameter according to the type and severity of the historical accident data, and the risk level includes level L1 to level L4; Perform normalization processing on the labeled historical environmental parameters and historical construction logs to obtain standardized feature data, and the standardized feature data includes at least historical gas concentration, historical dust density, historical vibration frequency, and historical construction logs.

[0014] By adopting the above - mentioned solution, risk level labels are assigned to the collected historical mine environmental parameters and their corresponding historical accident data, enabling the subsequent output of real - time environmental risk levels based on real - time environmental parameters. The labeled data and historical construction logs are normalized to obtain standardized feature data, making the data suitable for the input requirements of machine learning models.

[0015] In one embodiment, the step of training an environmental risk assessment model using the learning algorithm with the standardized feature data obtained after pre - processing to obtain a trained environmental risk assessment model, and using the trained environmental risk assessment model to receive real - time mine environmental parameters and corresponding construction stages and output the current risk level specifically includes the following steps: Divide the standardized feature data into a training set and a test set; Using the standardized feature data in the training set, with gas concentration, dust density, vibration frequency, and construction logs as input features, and using the random forest algorithm to train the environmental risk assessment model to obtain a trained environmental risk assessment model, and output risk levels L1 - L4; Use the test set to verify the performance of the environmental risk assessment model, require that the recall rate of L4 - level risk is not lower than the preset threshold, and optimize the parameters of the environmental risk assessment model according to the verification results; Based on the optimized environmental risk assessment model, it is used to receive real - time mine environmental parameters and corresponding construction stages and output the risk level.

[0016] By adopting the above - mentioned solution, the standardized feature data is divided into a training set and a test set. The training set is used to train the machine learning model to obtain a trained model and output the corresponding risk level. The test set is used to verify the performance of the trained model, and the model is optimized according to the verification results, so as to improve the performance and accuracy of the model. The trained and optimized model is used to receive real - time mine environmental parameters and output the risk level, so that corresponding measures can be taken according to the output risk level.

[0017] In one embodiment, in the step of dynamically adjusting the battery detection frequency and charge - discharge protection threshold according to the lithium - battery state parameters and the current environmental risk level and generating a control instruction containing the adjusted parameters, the dynamic adjustment further includes: When the temperature in the lithium - battery state parameters exceeds the first preset threshold, forcibly increase the detection frequency and decrease the upper limit of the charge - discharge current; When the temperature exceeds the second preset threshold, trigger a charge - discharge circuit cut - off instruction.

[0018] By adopting the above scheme, temperature is used as an independent parameter to trigger the protection action prior to the environmental risk level, so as to ensure a quick response under extreme working conditions. The temperature value in the state parameters of the lithium battery is monitored in real time, and the current environmental risk level is adjusted according to the temperature value. When it is detected that the temperature exceeds the first preset threshold, regardless of the mine environmental parameters and the current environmental risk level, a control instruction for forcibly increasing the detection frequency and reducing the upper limit of the charge and discharge current is directly generated to the battery management system for early warning; when it is detected that the temperature exceeds the second preset threshold, the charge and discharge circuit is forcibly cut off to prevent accidents from occurring.

[0019] In one embodiment, the collected state parameters of the lithium battery further include the battery health state. In the step of dynamically adjusting the battery detection frequency and the charge and discharge protection threshold according to the state parameters of the lithium battery and the current environmental risk level and generating a control instruction including the adjusted parameters, the dynamic adjustment further includes: Based on the available value of the current battery health state, if the available value is within the preset threshold range and when the environmental risk level increases, the detection frequency is increased and the upper limit of the charge and discharge current is reduced based on the loss value of the battery health state; If the available value of the current battery health state is less than the preset threshold, a charge and discharge circuit cut-off instruction is triggered.

[0020] By adopting the above scheme, the collected state parameters of the lithium battery further include the battery health state. When dynamically adjusting the charge and discharge detection parameters of the lithium battery, the current health state of the battery is considered. If the loss value of the battery health state reaches a certain value, the charge and discharge circuit is cut off to prevent accidents from occurring; if the available value of the battery health state is still within the preset threshold range, when reducing the upper limit of the charge and discharge current, the loss value of the battery health state is added to the calculation, so as to avoid that when normally reducing the upper limit of the charge and discharge current, due to a certain loss of the battery health state, it may still conduct at a relatively high current after reducing the upper limit of the charge and discharge current.

[0021] This application also relates to a charge and discharge detection device for a mine-used lithium battery, including: A data acquisition module, configured to collect mine environmental parameters and lithium battery state parameters in real time, where the mine environmental parameters at least include gas concentration, dust density and vibration frequency, and the lithium battery state parameters at least include voltage, current and temperature; An analysis module, configured to obtain historical construction logs, and calculate the corresponding construction stage of the mine environmental parameters based on the historical construction logs through time series analysis according to the collected mine environmental parameters; A risk assessment module, configured to input the mine environmental parameters and the corresponding construction stage into a trained environmental risk assessment model, and output the current environmental risk level through the environmental risk assessment model; A dynamic adjustment module, configured to dynamically adjust the battery detection frequency and the charge and discharge protection threshold according to the lithium battery state parameters and the current environmental risk level, and generate a control instruction including the adjustment parameters; A communication switching module, configured to switch the communication protocol based on the environmental risk level, and send the control instruction to the battery management system by using the switched communication protocol.

[0022] By adopting the above solution, mine environmental parameters are collected and historical construction logs are obtained. The collected mine environmental parameters and the obtained historical construction logs are input into the environmental risk assessment model to obtain the risk level of the current environment in the mine, and corresponding measures can be taken according to the current risk level; the historical construction logs include the construction arrangements, the completed projects, the construction time arrangements, etc. in the mine. Through time series analysis, the current construction stage corresponding to the collected mine environmental parameters can be calculated based on the historical construction logs. By inputting the mine environmental parameters and the obtained corresponding construction stage into the trained environmental risk assessment model, the credibility of the output current environmental risk level can be increased. The lithium battery state parameters are collected. According to the collected lithium battery state parameters and the obtained current risk level, the detection frequency and the charge and discharge protection threshold of the explosion-proof lithium battery for mine use can be dynamically adjusted accordingly to adapt to the current risk level. For example, when it is found that the current risk level increases, the detection frequency is increased and the charge and discharge current is decreased. If an abnormality occurs, the detection frequency is increased to detect the abnormality faster. At the same time, the current is decreased to prevent the battery from overloading and causing danger in a high-risk environment. When it is found that the risk level decreases, it is restored; through dynamic adjustment, a quick response is made in a high-risk situation and gradually restored after the risk decreases, thus avoiding the burden on the equipment caused by frequent switching. At the same time, the corresponding communication protocol is determined and switched according to the current risk level. For example, when the risk level is relatively low, CAN bus communication can be used to ensure the real-time transmission of the control instruction. When the risk level is relatively high, in order to avoid problems such as signal attenuation, decreased stability, and even signal interruption caused by the deterioration of the internal environment of the mine, such as an increase in gas concentration, an increase in dust density, or an increase in vibration frequency, and the failure to trigger the protection mechanism in time, resulting in danger, the communication protocol is automatically switched to LoRa spread spectrum communication and data compression is enabled to ensure the stability of the control instruction transmission. By adding the environmental risk level as the switching condition, the reliability and stability of communication in different environments are ensured, especially in the complex environment of the mine, achieving the effect of adaptive switching.

[0023] This application also relates to a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above method for detecting the charge and discharge of an explosion-proof lithium battery for mine use are implemented.

[0024] The present application further relates to a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-mentioned charge and discharge detection method for a mine-used lithium battery.

[0025] The charge and discharge detection method, device, equipment and medium for a mine-used lithium battery provided by the above embodiments have the following beneficial effects: By collecting mine environmental parameters and obtaining historical construction logs, inputting the collected mine environmental parameters and the obtained historical construction logs into an environmental risk assessment model to obtain the risk level of the current environment in the mine, corresponding measures can be taken according to the current risk level; the historical construction logs are the construction arrangements, completed projects, construction time arrangements, etc. in the mine. By using time series analysis, the current construction stage corresponding to the collected mine environmental parameters can be calculated based on the historical construction logs. By inputting the mine environmental parameters and the obtained corresponding construction stage into the trained environmental risk assessment model, the credibility of the output current environmental risk level can be increased. Collect the state parameters of the lithium battery. According to the collected state parameters of the lithium battery and the obtained current risk level, the detection frequency and the dynamic adjustment of the charge and discharge protection threshold of the mine explosion-proof lithium battery can be made accordingly to adapt to the current risk level. For example, when it is found that the current risk level increases, the detection frequency is increased and the charge and discharge current is reduced. If an abnormality occurs, the detection frequency is increased to detect the abnormality faster. At the same time, the current is reduced to prevent the battery from overloading and causing danger in a high-risk environment. When it is found that the risk level decreases, it is restored; through dynamic adjustment, it can quickly respond in high-risk situations and gradually recover after the risk decreases, thus avoiding the burden on the equipment caused by frequent switching. At the same time, the corresponding communication protocol is determined and switched according to the current risk level. For example, when the risk level is low, CAN bus communication can be used to ensure the real-time transmission of control instructions. When the risk level is high, in order to avoid problems such as signal attenuation, decreased stability or signal interruption caused by the deterioration of the mine internal environment, such as an increase in gas concentration, an increase in dust density or an increase in vibration frequency, and the failure to trigger the protection mechanism in time, resulting in danger, the communication protocol is automatically switched to LoRa spread spectrum communication and data compression is enabled to ensure the stability of the control instruction transmission. By adding the environmental risk level as a switching condition, the reliability and stability of communication in different environments are ensured, especially in the complex mine environment, achieving the effect of adaptive switching. Description of the Drawings

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on the structures shown in these drawings.

[0027] Figure 1 It is a flowchart of a charge and discharge detection method for a mine-used lithium battery provided by an embodiment of the present invention; Figure 2 It is a schematic block diagram of a computer device provided by an embodiment of the present invention. Specific embodiments

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0029] It should be noted that if there are directional indications (such as up, down, left, right, front, back,...) involved in the embodiments of the present invention, the directional indications are only used to explain the relative positional relationship and movement conditions between components in a specific posture. If the specific posture changes, the directional indications will also change accordingly.

[0030] In addition, if there are descriptions such as "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In addition, if "and / or" or "and / or" appears throughout the text, its meaning includes three parallel solutions. Taking "A and / or B" as an example, it includes solution A, solution B, or the solution where A and B are satisfied simultaneously. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the ability of those of ordinary skill in the art to implement. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0031] Referring to Figure 1 , one embodiment of the present invention provides a charge and discharge detection method for a mine-used lithium battery, including the following steps: S10. Real - time collect mine environmental parameters and lithium - battery state parameters. The mine environmental parameters at least include gas concentration, dust density, and vibration frequency. The lithium - battery state parameters at least include voltage, current, and temperature.

[0032] As described in step S10 above, in this embodiment, the collected mine environmental parameters at least include gas concentration, dust density, and vibration frequency, and the collected lithium - battery state parameters at least include voltage, current, and temperature. For the collection of gas concentration, it can be monitored and collected in real - time through an infrared gas sensor, with a measurement range of 0 - 5% CH 4 , an accuracy of ±0.1%, and a sampling frequency of 1H; for the collection of dust density, it can be monitored and collected in real - time through a laser - scattering dust sensor, with a measurement range of 0 - 100mg / m³, a resolution of 0.1mg / m³, and the data is transmitted through the RS485 interface; for the collection of vibration frequency, it can be monitored and collected in real - time by installing a tri - axis acceleration sensor on the outer shell of the explosion - proof lithium - battery pack, with a monitored vibration frequency spectrum range of 0 - 2000Hz and a dynamic response time of ≤5ms; for the collection of voltage and current, it can be monitored and collected in real - time through a Hall voltage sensor and a closed - loop current sensor, with a sampling frequency of 10kHz and an accuracy of ±0.5%; for the collection of temperature, it can be monitored and collected in real - time by arranging NTC thermistors on the surface and inside of the explosion - proof lithium - battery module, with a temperature measurement range of - 40°C to 125°C and an error of ±0.5°C. Perform data fusion and data pre - processing on the collected mine environmental parameters and lithium - battery state parameters. For example, use an STM32F407 micro - controller to align the timestamps of multi - source data, adopt a sliding - window filter (window length 10s) to eliminate noise, and pack and upload the data to the edge - computing gateway device through the CAN bus.

[0033] S20. Obtain historical construction logs. According to the collected mine environmental parameters, calculate the corresponding construction stages of the mine environmental parameters based on the historical construction logs through time - series analysis.

[0034] As described in step S20 above, the historical construction log includes the construction arrangements in the mine (such as the construction process and stage arrangements of the entire mine), the completed projects (such as which step and stage have been completed according to the progress of the construction arrangements), the construction time arrangements (such as what type of construction is carried out in which time period / morning / afternoon), etc. According to the real-time time of the collected mine environmental parameters and the historical construction log, time series analysis is used to calculate which construction stage in the historical construction log the currently collected mine environmental parameters correspond to, so as to obtain the currently corresponding construction stage. Due to different construction situations, the corresponding mine environmental parameters will be different. For example, in a certain construction stage arrangement, when mechanical cutting, drilling and other operations are carried out, the dust concentration will be relatively high, and when excavation, deep mining, and mechanical equipment operation are carried out, the vibration frequency will be relatively large, etc. Therefore, according to the historical construction log, by using time series analysis, the currently corresponding construction stage of the collected mine environmental parameters can be calculated based on the historical construction log, that is, it can be known what changes may occur in the mine environmental parameters corresponding to the currently corresponding construction stage. By inputting the mine environmental parameters and the obtained corresponding construction stage into the trained environmental risk assessment model, the credibility of the currently output environmental risk level by the subsequent environmental risk assessment model can be increased.

[0035] S30. Input the mine environmental parameters and the corresponding construction stage into the trained environmental risk assessment model, and output the current environmental risk level through the environmental risk assessment model.

[0036] As described in step S30 above, the environmental risk assessment model is a pre-trained machine learning model deployed in the edge computing gateway device in the mine, and is used to calculate the risk level of the current environment in the mine. By taking the collected mine environmental parameters (gas concentration, dust density and vibration frequency) and the corresponding construction stage as inputs, the current environmental situation in the mine can be accurately obtained, and according to the preset risk levels, the risk level of the current environment can be output, so as to take corresponding measures according to the current risk level to prevent accidents. For example, the preset risk levels are L1~L4. When the gas concentration ≥ 2% and / or the dust density ≥ 50mg / m³ and / or the vibration frequency ≥ 1500Hz, the environmental risk assessment model outputs level L4 (extremely high risk); if the gas concentration < 0.5%, the dust density < 10mg / m³ and the vibration frequency < 500Hz, it outputs level L1 (low risk).

[0037] Among them, the construction and training of the environmental risk assessment model include the following steps: S310. Collect the historical mine environmental parameters, their corresponding historical accident data, and obtain the historical construction log for preprocessing to obtain the standardized feature data applied to the machine model as input data. Specifically, it includes the following steps: S311. Collect historical mine environmental parameters and their corresponding historical accident data. According to the type and severity of the historical accident data, label a risk level for each piece of historical environmental parameter. The risk levels include level L1 to level L4. For example, the corresponding historical accident data includes mine environmental monitoring records (gas concentration, dust density, vibration frequency) in the past year and corresponding accident reports (such as gas explosion, thermal runaway of the battery caused by equipment short circuit, etc.). Then, according to the accident severity and the corresponding environmental parameter thresholds, the data is labeled into 4 risk levels.

[0038] S312. Normalize the labeled historical environmental parameters and historical construction logs to obtain standardized feature data. The standardized feature data includes at least historical gas concentration, historical dust density, historical vibration frequency, and historical construction logs.

[0039] S320. Use the learning algorithm to train an environmental risk assessment model with the standardized feature data obtained after preprocessing to obtain a trained environmental risk assessment model. The trained environmental risk assessment model is used to receive real-time mine environmental parameters and corresponding construction stages and output the current risk level. Specifically, it includes the following steps: S321. Divide the standardized feature data into a training set and a test set; S322. Use the standardized feature data in the training set, with gas concentration, dust density, vibration frequency, and construction logs as input features, and use the random forest algorithm to train an environmental risk assessment model to obtain a trained environmental risk assessment model and output risk levels from L1 to L4; S323. Use the test set to verify the performance of the environmental risk assessment model, requiring that the recall rate of level L4 risk is not lower than a preset threshold. For example, it is required that the recall rate of level L4 risk is not lower than 98%, and optimize the parameters of the environmental risk assessment model according to the verification results; S324. Based on the optimized environmental risk assessment model, receive real-time mine environmental parameters and corresponding construction stages and output the risk level.

[0040] S40. Dynamically adjust the battery detection frequency and charge-discharge protection threshold according to the lithium battery state parameters and the current environmental risk level, and generate a control instruction containing the adjusted parameters. The dynamic adjustment includes: When the environmental risk level increases, increase the detection frequency and decrease the upper limit of the charge-discharge current; When the environmental risk level decreases, decrease the detection frequency and increase the upper limit of the charge-discharge current.

[0041] As described in step S40 above, according to the collected lithium battery state parameters and the obtained current risk level, the detection frequency and the dynamic adjustment of the charge and discharge protection threshold of the mine explosion-proof lithium battery can be correspondingly adjusted to adapt to the current risk level. Among them, the battery detection frequency is the number of times of sampling the battery state (current, voltage) per unit time, and the charge and discharge protection threshold is the safety upper limit of the current allowed for charge and discharge. For the dynamic adjustment rule: the detection frequency increases step by step according to the risk level. For example, when the risk level is L1, the detection frequency is 10 s / time; when the risk level is L2, the detection frequency is 5 s / time, and the frequency is doubled; when the risk level is L3, the detection frequency is 2 s / time, and the frequency is increased by 5 times; when the risk level is L4, the detection frequency is 1 s / time, and the frequency is increased by 10 times. The charge and discharge protection threshold decreases linearly according to the risk level. For example, when the risk level is L1, the safety upper limit of the current is 100%; when the risk level is L2, the safety upper limit of the current is 80%; when the risk level is L3, the safety upper limit of the current is 60%; when the risk level is L4, the safety upper limit of the current is 40%.

[0042] Taking a mine explosion-proof lithium battery device as an example: Initial state: The environmental risk level is L1, the detection frequency is 10 s / time, the upper limit of the charge and discharge current is 100 A, the upper limit of the charge and discharge voltage is 54.6 V, and the lower limit is 42.0 V; Risk upgrade and generation of corresponding control instructions: When it is detected that the gas concentration increases and the risk level rises to L3, a control instruction is generated to adjust the battery detection frequency to 2 seconds / time and the upper limit of the charge and discharge current to 60 A.

[0043] S50. Switch the communication protocol based on the environmental risk level, and use the switched communication protocol to send the control instruction to the battery management system.

[0044] As described in step S50 above, since CAN bus communication has the advantages of high reliability, low latency, and high bandwidth, and LoRa spread spectrum communication has the advantages of long-distance wireless transmission, anti-interference, and low power consumption, when the risk level is relatively low, CAN bus communication is preset as the communication protocol for risk levels L1 to L2. When the risk level increases, LoRa spread spectrum communication is preset as the communication protocol for risk levels L3 to L4. In this embodiment, the communication protocol to be used in the current environment is determined according to the current risk level. For example, in the initial state, the environmental risk level is L1, and CAN bus communication is used. When the environmental risk assessment model outputs that the current environmental risk level has risen to L3, the communication protocol is switched from CAN bus communication to LoRa spread spectrum communication, and then the control instruction is sent to the battery management system using LoRa spread spectrum communication. For the switch between the two communication protocols, a dual-mode hot standby mechanism is adopted to ensure seamless switching between the communication protocols. Usually, CAN bus communication is used, and at the same time, LoRa spread spectrum communication is in a low-power listening state. When it is detected that the CAN bus communication is interrupted or the risk level ≥ L3, LoRa spread spectrum communication + compression is immediately enabled. For the compression algorithm, it is a preset differential coding + Huffman compression to ensure that the switching delay is less than 100 ms. By adding the environmental risk level as the switching condition, the reliability and stability of communication in different environments are ensured, especially in the complex environment of a mine, achieving the effect of adaptive switching.

[0045] As described in steps S10 to S50 above, in this embodiment, taking a lithium battery loader in a mine as an example, if the gas concentration in the mine suddenly increases to 2%: the environmental risk assessment model quickly determines that the risk level is L4; at this time, the detection frequency of the lithium battery is increased to 1 time / second, and the upper limit of the charge and discharge current is reduced from 100 A to 40 A; the communication protocol is switched to LoRa spread spectrum communication, and the control instruction is successfully sent to the battery management system to achieve emergency load reduction of the equipment and avoid gas explosion caused by electric sparks.

[0046] In one embodiment, after step S50, the following steps are further included: S60. The battery management system receives the control instruction and adjusts the output parameters according to the control instruction.

[0047] Among them, adjusting the output parameters according to the control instruction specifically includes: If the real-time current in the collected lithium battery state parameters is within the range of the charge and discharge current upper limit threshold corresponding to the current environmental risk level, and the real-time voltage is within the safety threshold range, the output parameters of the battery management system only include the adjustment of the detection frequency; If the real-time current in the collected lithium battery state parameters is greater than the upper threshold of the charge and discharge current corresponding to the current environmental risk level, and the real-time voltage is within the safety threshold range, the output parameters of the battery management system include adjustments to the detection frequency and the current.

[0048] As described in step S60 above, for example, when the risk level is L3, the safety upper limit of the charge and discharge current is adjusted to 60%. If the initial upper limit of the charge and discharge current is 100A, then the adjusted safety upper limit of the charge and discharge current is 60A. Among the collected lithium battery state parameters, when the real-time current ≤ 60A and the voltage is normal, the current state is maintained, and the generated control instructions only include adjustments to the detection frequency; when the real-time current > 60A, such as 70A, and the voltage is normal, the current is limited to 60A, and the generated control instructions include adjustments to the detection frequency and current limiting control.

[0049] Among them, when the real-time charge and discharge voltage exceeds 54.6V or is lower than 42.0V, regardless of the current risk level and whether the real-time charge and discharge current exceeds the safety upper limit, the charge and discharge circuit is directly cut off to prevent damage to the explosion-proof lithium battery due to overvoltage or undervoltage and the occurrence of safety accidents.

[0050] In one embodiment, in step S40, the dynamic adjustment further includes: When the temperature in the lithium battery state parameters exceeds the first preset threshold, the detection frequency is forcibly increased and the upper limit of the charge and discharge current is decreased; When the temperature exceeds the second preset threshold, a charge and discharge circuit cut-off instruction is triggered.

[0051] In this embodiment, it is assumed that the first preset threshold of the temperature is 50°C and the second preset threshold of the temperature is 65°C; when dynamically adjusting the battery detection frequency and the charge and discharge protection threshold, if the temperature in the collected lithium battery state parameters exceeds 50°C but does not exceed 65°C, even if the environmental risk level is low, the detection frequency of the lithium battery charge and discharge is forcibly increased for early warning, and the upper limit of the charge and discharge current is decreased to prevent continuous operation at a high current from causing the temperature to continue to rise and lead to accidents. If the temperature in the collected lithium battery state parameters exceeds 65°C, a charge and discharge circuit cut-off instruction is directly triggered and sent to the battery management system.

[0052] In one embodiment, the collected lithium battery state parameters further include the battery health state; in step S40, the dynamic adjustment further includes: Based on the available value of the current battery health state, if the available value is within the preset threshold range, and when the environmental risk level increases, the detection frequency is increased and the upper limit of the charge and discharge current is decreased based on the loss value of the battery health state; When the available value of the current battery health state is less than the preset threshold, a charge and discharge circuit cut-off command is triggered.

[0053] In this embodiment, among the battery state parameters collected in step S10, the battery health state (SOH) is also included. The initial available value of the battery health state is 100%. Assume that the preset threshold range of the available value of the battery health state is 50% - 100%. In the dynamic adjustment of step S40, assume that when the current environmental risk level is L3, normally a control command for adjusting the battery detection frequency to 2 seconds / time and the upper limit of the charge and discharge current to 60A is generated. However, during the use of the battery, there will be a situation of performance degradation. Since a certain value of the battery health state is lost, it may occur that after reducing the upper limit of the charge and discharge current according to the increase of the risk level, it still operates at a relatively high current. Therefore, during the process of adjusting the upper limit of the charge and discharge current, the available value of the battery health state also needs to be considered. During dynamic adjustment, based on the collected battery state parameters, the available value of the current battery health state is obtained. If the available value is within the preset threshold range (50% - 100%), assume that the current available value of the battery health state is 85%, that is, the loss value of the battery health state is 15%. Therefore, for the current environmental risk level of L3, the adjustment (reduction) of the upper limit of the charge and discharge current is 100A * 60% * (100% - 15%) = 51A. If the available value of the current battery health state is less than the preset threshold, assume it is 45%, at this time, a charge and discharge circuit cut-off command is triggered and sent to the battery management system to prevent accidents.

[0054] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and the numerical values explained in each step are only for reference explanation to facilitate the understanding of those skilled in the art. This is clear to those skilled in the art and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0055] In one of the embodiments, a charge and discharge detection device for a mine-used lithium battery is provided. The charge and discharge detection device for a mine-used lithium battery corresponds to the charge and discharge detection method for a mine-used lithium battery in the above embodiment. The charge and discharge detection device for a mine-used lithium battery includes: A data acquisition module for real-time collecting mine environment parameters and lithium battery state parameters. The mine environment parameters at least include gas concentration, dust density, and vibration frequency. The lithium battery state parameters at least include voltage, current, and temperature; An analysis module for obtaining historical construction logs and calculating the corresponding construction stage of the mine environment parameters based on the historical construction logs through time series analysis according to the collected mine environment parameters; A risk assessment module, configured to input the mine environmental parameters and the corresponding construction stage into a trained environmental risk assessment model, and output the current environmental risk level through the environmental risk assessment model; A dynamic adjustment module, configured to dynamically adjust the battery detection frequency and the charge and discharge protection threshold according to the lithium battery state parameters and the current environmental risk level, and generate a control instruction including the adjustment parameters; A communication switching module, configured to switch the communication protocol based on the environmental risk level, and send the control instruction to the battery management system by using the switched communication protocol.

[0056] Optionally, it further includes: A first dynamic adjustment sub-module, configured to forcibly increase the detection frequency and decrease the upper limit of the charge and discharge current when the temperature in the lithium battery state parameters exceeds a first preset threshold; A second dynamic adjustment sub-module, configured to trigger a charge and discharge circuit cut-off instruction when the temperature exceeds a second preset threshold.

[0057] Optionally, it further includes: A third dynamic adjustment sub-module, configured to, based on the available value of the current battery health state, if the available value is within a preset threshold range, and when the environmental risk level increases, increase the detection frequency and decrease the upper limit of the charge and discharge current based on the loss value of the battery health state.

[0058] A fourth dynamic adjustment sub-module, configured to trigger a charge and discharge circuit cut-off instruction if the available value of the current battery health state is less than the preset threshold.

[0059] For the specific limitations of a charge and discharge detection device for a mine-used lithium battery, reference can be made to the limitations of a charge and discharge detection method for a mine-used lithium battery in the above text, which will not be elaborated here. Each module in the above-mentioned charge and discharge detection device for a mine-used lithium battery can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processor of the computer device in hardware form or be independent of it, or be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0060] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 2Shown. The computer device includes a processor, a memory, a network interface, and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the historical environmental parameters of the mine and their corresponding historical accident data, data processing, etc. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements a method for detecting the charging and discharging of a mine-used lithium battery.

[0061] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements a method for detecting the charging and discharging of a mine-used lithium battery.

[0062] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, it implements a method for detecting the charging and discharging of a mine-used lithium battery.

[0063] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or an external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0064] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0065] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A charge and discharge detection method for a mining lithium battery, characterized in that: The steps include: Real-time collection of mine environment parameters and lithium battery status parameters, wherein the mine environment parameters include at least gas concentration, dust density and vibration frequency, and the lithium battery status parameters include at least voltage, current and temperature; Obtain historical construction logs, and calculate the corresponding construction stages of the mine environmental parameters based on the historical construction logs through time series analysis according to the collected mine environmental parameters; Inputting the mine environmental parameters and the corresponding construction stage into a trained environmental risk assessment model, and outputting the current environmental risk level through the environmental risk assessment model; According to the lithium battery status parameters and the current environmental risk level, dynamically adjust the battery detection frequency and the charge and discharge protection threshold and generate a control instruction containing the adjustment parameters; Switching the communication protocol based on the environmental risk level, and sending the control instruction to the battery management system using the switched communication protocol; Among them, in the step of dynamically adjusting the battery detection frequency and the charge and discharge protection threshold according to the lithium battery status parameters and the current environmental risk level and generating a control instruction containing the adjustment parameters, the dynamic adjustment includes: When the environmental risk level increases, the detection frequency is increased and the upper limit of charge and discharge current is reduced; When the environmental risk level decreases, the detection frequency is reduced and the upper limit of the charge and discharge current is increased.

2. The charge and discharge detection method for a mining lithium battery according to claim 1, characterized in that: After the step of switching the communication protocol based on the environmental risk level and using the switched communication protocol to send the control instruction to the battery management system, the following steps are also included: The battery management system receives the control command and adjusts the output parameters according to the control command; Wherein, adjusting the output parameters according to the control instruction specifically includes: If the real-time current in the collected lithium battery status parameters is within the upper limit threshold range of the charge and discharge current corresponding to the current environmental risk level, and the real-time voltage is within the safety threshold range, the output parameters of the battery management system only include the adjustment of the detection frequency; If the real-time current in the collected lithium battery status parameters is greater than the upper limit threshold of the charge and discharge current corresponding to the current environmental risk level, and the real-time voltage is within the safety threshold range, the output parameters of the battery management system include adjustment of the detection frequency and current.

3. The charge and discharge detection method for a mining lithium battery according to claim 1, characterized in that: In the step of inputting the mine environmental parameters and the corresponding construction stage into the trained environmental risk assessment model and outputting the current environmental risk level through the environmental risk assessment model, the construction and training of the environmental risk assessment model includes the following steps: Collect historical mine environmental parameters and their corresponding historical accident data and obtain historical construction logs for preprocessing to obtain standardized feature data applied to the machine model as input data; The standardized feature data obtained after preprocessing is used to train the environmental risk assessment model using a learning algorithm to obtain a trained environmental risk assessment model. The trained environmental risk assessment model is used to receive mine environmental parameters and corresponding construction stages in real time and output the current risk level.

4. The charge and discharge detection method for a mining lithium battery as claimed in claim 3, characterized in that: The step of collecting historical mine environmental parameters and corresponding historical accident data and obtaining historical construction logs for preprocessing to obtain standardized feature data applied to the machine model as input data specifically includes the following steps: Collect historical environmental parameters of the mine and the corresponding historical accident data, and mark the risk level for each historical environmental parameter according to the type and severity of the historical accident data, wherein the risk level includes L1 to L4; The annotated historical environmental parameters and historical construction logs are normalized to obtain standardized feature data, wherein the standardized feature data includes at least historical gas concentration, historical dust density, historical vibration frequency and historical construction logs.

5. The charge and discharge detection method for a mining lithium battery as claimed in claim 4, characterized in that: The step of using the standardized feature data obtained after preprocessing to train the environmental risk assessment model using a learning algorithm to obtain a trained environmental risk assessment model, and using the trained environmental risk assessment model to receive the mine environmental parameters and the corresponding construction stage in real time and output the current risk level, specifically includes the following steps: Dividing the standardized feature data into a training set and a test set; Using the standardized feature data in the training set, taking gas concentration, dust density, vibration frequency and construction log as input features, and using the random forest algorithm to train the environmental risk assessment model, a trained environmental risk assessment model is obtained, and L1-L4 risk levels are output; The performance of the environmental risk assessment model is verified using the test set, requiring that the L4 risk recall rate is not lower than a preset threshold, and the parameters of the environmental risk assessment model are optimized according to the verification results; Based on the optimized environmental risk assessment model, it is used to receive mine environmental parameters and corresponding construction stages in real time and output risk levels.

6. The charge and discharge detection method for a mining lithium battery according to claim 1, characterized in that: In the step of dynamically adjusting the battery detection frequency and the charge and discharge protection threshold according to the lithium battery status parameters and the current environmental risk level and generating a control instruction containing the adjustment parameters, the dynamic adjustment also includes: When the temperature in the lithium battery status parameter exceeds a first preset threshold, the detection frequency is forcibly increased and the upper limit of the charge and discharge current is reduced; When the temperature exceeds a second preset threshold, a charge-discharge circuit cut-off instruction is triggered.

7. The charge and discharge detection method for a mining lithium battery according to claim 1, characterized in that: The collected lithium battery status parameters also include the battery health status. In the step of dynamically adjusting the battery detection frequency and the charge and discharge protection threshold according to the lithium battery status parameters and the current environmental risk level and generating a control instruction containing the adjustment parameters, the dynamic adjustment also includes: Based on the available value of the current battery health status, if the available value is within the preset threshold range and when the environmental risk level increases, the detection frequency is increased and the upper limit of the charge and discharge current is reduced based on the loss value of the battery health status; If the available value of the current battery health status is less than the preset threshold, the charge and discharge circuit cut-off instruction is triggered.

8. A charge and discharge detection device for a mining lithium battery, used to implement the steps of a charge and discharge detection method for a mining lithium battery as described in any one of claims 1 to 7, characterized in that: include: A data acquisition module, used for real-time acquisition of mine environment parameters and lithium battery status parameters, wherein the mine environment parameters at least include gas concentration, dust density and vibration frequency, and the lithium battery status parameters at least include voltage, current and temperature; An analysis module is used to obtain historical construction logs and calculate the corresponding construction stages of the mine environmental parameters based on the historical construction logs through time series analysis according to the collected mine environmental parameters; A risk assessment module, used to input the mine environmental parameters and the corresponding construction stage into a trained environmental risk assessment model, and output the current environmental risk level through the environmental risk assessment model; A dynamic adjustment module, used to dynamically adjust the battery detection frequency and charge and discharge protection threshold according to the lithium battery status parameters and the current environmental risk level and generate a control instruction containing the adjustment parameters; A communication switching module is used to switch the communication protocol based on the environmental risk level and send the control instruction to the battery management system using the switched communication protocol.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the charge and discharge detection method for a mining lithium battery as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, the steps of the charge and discharge detection method of a mining lithium battery as described in any one of claims 1 to 7 are implemented.

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