A mobile energy storage safety monitoring method based on multi-source data fusion

Abstract

This invention relates to the field of big data analytics, and more particularly to a mobile energy storage safety monitoring method based on multi-source data fusion. The method includes: collecting ambient temperature and mobile vibration data from the mobile energy storage unit to determine the vibration-thermal coupling factor; acquiring the battery temperature and motor temperature from the energy user unit to determine the working matching coefficient, and combining this with the actual usage time of the energy user unit to determine the fast charging coefficient and charging parameters; during charging, acquiring the battery temperature and battery thickness deformation from the energy user unit to determine the temperature rise coefficient and deformation coefficient, and thus determining the inducing factor; based on the vibration-thermal coupling factor and the inducing factor, determining whether fast charging exacerbates the vibration-thermal coupling risk; if so, determining whether to adjust the charging parameters or disconnect charging based on the temperature rise coefficient and charging progress; and performing periodic continuous monitoring after adjustment to determine whether the energy storage unit needs to recharge the energy user unit. This invention improves the accuracy and efficiency of mobile energy storage safety monitoring.

Description

Technical Field

[0001] This invention relates to the field of big data analytics, and in particular to a mobile energy storage safety monitoring method based on multi-source data fusion. Background Technology

[0002] With the widespread application of drone technology in fields such as inspection, logistics, and agriculture, intelligent mobile drone charging stations, as a key infrastructure to ensure the continuous operation of drones, have experienced rapid development. These charging stations typically integrate energy storage devices onto mobile platforms, providing fast charging services for drones in the field or remote areas. During operation, mobile energy storage devices not only need to withstand the continuous vibration from vehicle movement but also need to cope with high-temperature environments and the thermal shock from high-rate fast charging of drones, making their safety monitoring increasingly important.

[0003] However, existing energy storage safety monitoring methods mainly target stationary energy storage power stations or ordinary charging scenarios, failing to fully consider the coupled effects of mobile vibration and high-temperature environments on the energy storage end, and also failing to integrate the multi-dimensional state information of the drone energy user end with the vibration-thermal state of the energy storage end for analysis. Traditional methods cannot adapt to the dynamic and severe operating conditions caused by the superposition of mobile relocation and fast charging, and are prone to missed or false alarms, making it difficult to effectively prevent energy storage thermal runaway and battery degradation at the energy user end caused by multi-field coupling of vibration, heat, and electricity.

[0004] Chinese Patent Publication No. CN121584888A discloses an energy storage monitoring system and method applied to distributed energy storage equipment, relating to the field of energy storage monitoring. The system includes energy storage equipment and an energy storage system. The energy storage equipment consists of an intelligent control platform, an integrated energy unit, an access unit, a combiner unit, and an equipment management unit. The access unit is connected to the regional power grid. The energy storage system includes a monitoring and acquisition module, a partitioning module, and a processing module. The monitoring method includes acquiring the current operating data, partitioning the data using a k-means clustering algorithm, determining the current energy data based on the net load, and predicting the energy data for the next moment. Furthermore, it combines a condition monitoring model to analyze fault diagnosis and lifespan degradation information, generates control commands to regulate the operation of the power grid, and realizes the monitoring of distributed energy storage equipment.

[0005] Therefore, it is evident that the existing technology has the following problems: Existing technologies do not consider the coupling deterioration effect caused by mobile vibration and high temperature environment on the energy storage end, nor do they consider the dynamic correlation between the state of the energy user battery and motor and the vibration-thermal state of the energy storage end. This makes it impossible to identify early risks caused by coupling deterioration effect in real time during fast charging, which can easily lead to thermal runaway or battery damage. Summary of the Invention

[0006] To address this, the present invention provides a mobile energy storage safety monitoring method based on multi-source data fusion, which overcomes the problems in the prior art that do not consider the coupling deterioration effect caused by mobile vibration and high temperature environment on the energy storage end, and do not consider the dynamic correlation between the state of the battery and motor at the energy consumption end and the vibration-thermal state at the energy storage end, resulting in the inability to identify early risks caused by coupling deterioration effect in real time during fast charging, thus easily leading to thermal runaway or battery damage.

[0007] To achieve the above objectives, the present invention provides a mobile energy storage safety monitoring method based on multi-source data fusion, comprising: Real-time acquisition of ambient temperature and vibration data of the mobile energy storage terminal; The vibration-thermal coupling factor is determined based on the ambient temperature and the moving vibration data. Obtain the battery temperature and motor temperature at the energy consumption end, and determine the working matching coefficient of the energy consumption end based on the battery temperature and motor temperature; The fast charging coefficient of the energy-consuming terminal is determined based on the working matching coefficient and the actual usage time of the energy-consuming terminal, so as to determine the charging parameters, wherein the charging parameters include the charging rate and the target charging ratio. During the charging process, the battery temperature and battery thickness deformation at the energy consumption end are acquired in real time to determine the temperature rise coefficient and deformation coefficient. The inducing factor is determined based on the heating coefficient and the deformation coefficient; Based on the comparison results of the vibration-thermal coupling factor and the inducing factor with the corresponding threshold, it is determined whether there is a risk that fast charging will exacerbate vibration-thermal coupling. If there is a risk that fast charging will exacerbate vibration-thermal coupling, then the charging parameters will be adjusted or charging will be disconnected based on the temperature rise coefficient and the charging progress at the energy-consuming end. Periodic and continuous monitoring is performed on the battery status of the energy user end and the vibration-thermal coupling status of the energy storage end after adjusting the charging parameters or disconnecting the charging, in order to determine whether the energy storage end should recharge the energy user end.

[0008] Furthermore, the process of determining the vibration-thermal coupling factor includes: The extent of ambient temperature exceeding the limit is determined based on the ratio of the maximum ambient temperature at the energy-consuming end within a preset period to a preset ambient temperature threshold. The intensity of mobile vibration is determined based on the ratio of the maximum value of the mobile vibration data at the energy-consuming end within a preset period to the preset threshold value of the mobile vibration data. The vibration-thermal coupling factor is determined based on the product of the ambient temperature exceeding the limit and the moving vibration intensity.

[0009] Furthermore, the process of determining the working matching coefficient at the energy consumption end includes: The first basic energy consumption configuration factor is determined based on the ratio of the battery temperature to a preset battery temperature threshold. The second basic energy consumption configuration factor is determined based on the ratio of the motor temperature to a preset motor temperature threshold. The working matching coefficient of the energy consumption end is determined based on the degree of consistency between the first basic energy consumption configuration factor and the second basic energy consumption configuration factor.

[0010] Furthermore, the process of determining the fast charging coefficient at the energy consumption end includes: The charging urgency factor is determined based on the ratio of the actual usage time at the energy-consuming end to the preset demand time. The fast charging coefficient of the energy-consuming end is determined based on the product of the working matching coefficient and the charging urgency factor.

[0011] Furthermore, the process of determining charging parameters based on the fast charging coefficient includes: The charging rate is determined based on the product of the fast charging coefficient and the preset maximum safe charging rate. The target charging ratio is determined by multiplying the fast charging coefficient by the preset maximum target charging ratio.

[0012] Furthermore, the process of determining the heating coefficient and the deformation coefficient includes: The temperature rise coefficient is determined based on the ratio of the maximum temperature rise rate of the battery at the energy consumption end to the temperature rise rate threshold within a unit cycle. The deformation coefficient is determined by the ratio of the maximum deformation rate of the battery thickness deformation at the energy consumption end to the deformation rate threshold within a unit cycle.

[0013] Furthermore, the process of identifying the triggering factors includes: The inducing factor is determined by weighted summation of the heating coefficient and the deformation coefficient.

[0014] Furthermore, the process of determining whether fast charging exacerbates the risk of vibration-thermal coupling includes: Based on the fact that the inducing factor is greater than the inducing factor threshold and the vibration-thermal coupling factor is greater than the vibration-thermal coupling threshold, it is determined that there is a risk that fast charging will exacerbate vibration-thermal coupling. The inducing factor threshold and the vibration-thermal coupling factor threshold are determined based on the fast charging coefficient.

[0015] Furthermore, given the risk that fast charging exacerbates vibration-thermal coupling, the process of adjusting charging parameters or disconnecting charging based on the temperature rise coefficient and charging progress includes: If the temperature rise coefficient is greater than the preset temperature rise coefficient action threshold, then the charging progress of the energy-consuming end is obtained. Based on the charging progress, determine whether to adjust the charging parameters or disconnect charging, wherein... If the charging progress of the power supply is less than the preset charging progress threshold, it is determined that the charging parameters should be adjusted. Alternatively, if the charging progress of the power supply is greater than or equal to a preset charging progress threshold, the charging is disconnected.

[0016] Furthermore, the process of determining whether the energy storage terminal needs to recharge the energy consumption terminal battery includes: If the status monitoring parameters of both the energy-consuming battery and the energy storage terminal meet the recharge threshold, it is determined that the energy storage terminal will recharge the energy-consuming battery, and the charging parameters will be determined based on the updated fast charging coefficient. Alternatively, if the status monitoring parameters of the energy-consuming battery and the energy storage end do not meet any recharge threshold, it is determined that there is an energy consumption risk at the energy storage end, and the need to suspend the energy consumption task at the energy storage end is determined. The status monitoring parameters include the energy-consuming battery temperature, the energy-consuming battery thickness deformation, the energy storage ambient temperature, and the energy storage vibration data. The recharge thresholds include the energy-consuming battery temperature threshold, the energy-consuming battery thickness deformation threshold, the energy storage ambient temperature threshold, and the energy storage moving vibration data threshold.

[0017] Compared with existing technologies, the advantages of this invention lie in its ability to collect multi-source information in real time, including ambient temperature and vibration data of the mobile energy storage unit, as well as battery temperature, motor temperature, and battery thickness deformation of the energy user unit. This information is then used to sequentially perform vibration-thermal coupling factor calculation, operational matching coefficient analysis, fast charging coefficient determination, adaptive setting of charging parameters, monitoring of temperature rise and deformation during charging, determination of inducing factors, risk identification, charging adjustment or disconnection, and periodic reconnection judgment, thus forming a complete closed-loop safety monitoring method. This method deeply integrates the mobile operating conditions of the energy storage unit with the real-time status of the energy user unit, enabling dynamic adaptation to complex scenarios involving field relocation and drone fast charging. It effectively solves the problems of single monitoring dimensions and delayed response in traditional methods, improving the accuracy and efficiency of mobile energy storage safety monitoring.

[0018] Furthermore, this invention determines the extent of ambient temperature exceeding the limit based on the ratio of the maximum ambient temperature within a preset period to a preset threshold, and determines the intensity of mobile vibration based on the ratio of the maximum value of mobile vibration data to a preset threshold, and determines the vibration-thermal coupling factor, thus achieving a quantitative characterization of the adverse effects of the superposition of high temperature and vibration. Using the maximum value instead of the average value allows for the capture of the most severe instantaneous operating conditions.

[0019] Furthermore, this invention obtains first and second basic energy consumption configuration factors by acquiring the battery temperature and motor temperature at the energy-consuming end, calculating their ratios to corresponding safety thresholds, and then determining the operating matching coefficient based on the consistency between the two. This effectively identifies whether there are abnormal heat dissipation or operating condition mismatches at the energy-consuming end. When the battery and motor temperatures change synchronously, a high matching degree indicates that the energy-consuming end is operating normally; when the difference between the two is significant, the matching coefficient decreases, suggesting a possible internal fault at the energy-consuming end. This coefficient provides crucial prior information for subsequent fast charging decisions, avoiding secondary risks caused by forced fast charging when the energy-consuming end is in an abnormal state.

[0020] Furthermore, this invention determines the charging urgency factor by the ratio of the actual usage time of the energy-consuming terminal to the preset required usage time, and multiplies it by the work matching coefficient to obtain the fast charging coefficient, comprehensively considering both the health of the energy-consuming terminal and its urgent need for power. A higher fast charging coefficient indicates that the energy-consuming terminal is in good condition and urgently needs to replenish its power, thus allowing for a more aggressive charging strategy; conversely, a lower coefficient limits the charging intensity. This design enables dynamic matching of charging behavior with the actual needs of the energy-consuming terminal, avoiding the decrease in operational efficiency caused by blindly fast charging or excessively conservative charging, and achieving an adaptive balance between safety and efficiency.

[0021] Furthermore, this invention obtains the actual charging rate and actual target charging ratio by multiplying the fast charging coefficient by the maximum safe charging rate and the maximum target charging ratio, respectively, so that the charging parameters are entirely driven by the real-time status and demand of the power user. The charging rate determines the current magnitude, and the target charging ratio determines the total amount of electricity charged. When the power user is in poor condition or charging is not urgent, not only is the charging current reduced, but the target amount of electricity charged can also be reduced, thereby significantly reducing the risk of thermal runaway; conversely, under the premise of safety, the power is replenished as quickly as possible to ensure the drone's subsequent mission endurance.

[0022] Furthermore, this invention dynamically captures abnormal thermal and mechanical responses of the energy-consuming end during charging by real-time monitoring of the battery temperature rise rate and thickness deformation rate, and comparing them with preset thresholds to obtain the temperature rise coefficient and deformation coefficient, respectively. A larger temperature rise coefficient indicates excessively rapid temperature rise, which may indicate increased internal resistance or thermal management failure; a larger deformation coefficient indicates unreasonable battery expansion, which may originate from lithium plating, internal short circuit, or gas generation. The two coefficients independently reflect the degree of poor charging status from different physical dimensions, providing reliable basic characteristics for subsequent calculation of inducing factors.

[0023] Furthermore, this invention obtains the inducing factor by weighted summation of the heating coefficient and deformation coefficient, thus integrating the combined contributions of thermal and mechanical effects to charging degradation. As a dimensionless comprehensive indicator, the inducing factor can intuitively reflect the overall risk level of the current charging process.

[0024] Furthermore, this invention dynamically determines the threshold values ​​for the inducing factor and the vibration-thermal coupling factor based on the fast-charging coefficient, and performs logical judgments with the current measured values, achieving adaptive adjustment of the risk identification standard. When the fast-charging coefficient is high, meaning the power supply is in good condition and urgently needs charging, the threshold automatically decreases, making the judgment conditions more stringent and preventing the over-reliance on good conditions from ignoring superimposed risks. When the fast-charging coefficient is low, the threshold increases to avoid oversensitivity leading to frequent false protection. The design of exceeding the threshold values ​​for both the inducing factor and the vibration-thermal coupling factor effectively eliminates the interference of random fluctuations in a single factor, improving the reliability of the judgment.

[0025] Furthermore, this invention, upon determining the risk of increased vibration-thermal coupling due to fast charging, further implements tiered responses—including issuing warnings, slowing down charging, or directly disconnecting charging—based on whether the temperature rise coefficient exceeds an action threshold and whether the charging progress reaches a preset value. This strategy suppresses the risk and continues charging by reducing the charging rate during the initial, manageable charging phase; it decisively disconnects charging in the later, high-risk phase to prevent thermal runaway. This tiered response mechanism ensures safety while minimizing the impact on drone missions and improving safety control precision.

[0026] Furthermore, this invention achieves automatic judgment of charging recovery conditions by periodically and continuously monitoring the battery temperature and deformation at the energy consumption end, as well as the ambient temperature and vibration state at the energy storage end after adjusting or disconnecting charging, and comparing these monitoring results with a recharge threshold. The recharge threshold is based on historical statistics of normal charging states and can objectively reflect the standard for the system to return to a safe state. Recharging is only allowed when all state parameters meet the safety conditions, avoiding secondary risks caused by blindly reconnecting due to an unrecovered state. During recharging, parameters are recalculated based on the updated fast charging coefficient, ensuring that each charging decision is based on the latest operating conditions, improving the adaptive capability of the safety monitoring process and the long-term operational safety of both the energy storage and energy consumption ends. Attached Figure Description

[0027] Figure 1 This is a flowchart of a mobile energy storage safety monitoring method based on multi-source data fusion, as described in an embodiment of the present invention. Figure 2 A flowchart for determining the vibration-thermal coupling factor in an embodiment of the present invention; Figure 3 This is a flowchart illustrating the process of determining the working matching coefficient of the energy-consuming end in an embodiment of the present invention; Figure 4 This is a flowchart for determining the fast charging coefficient of the power consumption terminal in an embodiment of the present invention. Detailed Implementation

[0028] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0029] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0030] It should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0031] Please see Figure 1 The diagram shows a flowchart of a mobile energy storage safety monitoring method based on multi-source data fusion according to an embodiment of the present invention. The mobile energy storage safety monitoring method based on multi-source data fusion according to an embodiment of the present invention includes: Step S1: Real-time acquisition of ambient temperature and vibration data of the mobile energy storage terminal; Step S2: Determine the vibration-thermal coupling factor based on the ambient temperature and the moving vibration data; Step S3: Obtain the battery temperature and motor temperature at the energy-consuming end, and determine the working matching coefficient of the energy-consuming end based on the battery temperature and motor temperature. Step S4: Determine the fast charging coefficient of the power user based on the working matching coefficient and the actual usage time of the power user, so as to determine the charging parameters, wherein the charging parameters include the charging rate and the target charging ratio. Step S5: During the charging process, the battery temperature and battery thickness deformation at the energy-consuming end are acquired in real time to determine the temperature rise coefficient and deformation coefficient. Step S6: Determine the inducing factor based on the heating coefficient and the deformation coefficient; Step S7: Based on the comparison results of the vibration-thermal coupling factor and the inducing factor with the corresponding threshold, determine whether there is a risk of fast charging exacerbating vibration-thermal coupling. Step S8: If there is a risk of increased vibration-thermal coupling due to fast charging, then based on the temperature rise coefficient and the charging progress of the energy-consuming end, determine whether to adjust the charging parameters or disconnect the charging. Step S9 involves periodically and continuously monitoring the battery status at the energy consumption end and the vibration-thermal coupling status at the energy storage end after adjusting the charging parameters or disconnecting the charging process, in order to determine whether the energy storage end should recharge the energy consumption end.

[0032] In this embodiment, in step S1, ambient temperature and vibration data of the mobile energy storage device are collected in real time. Specifically, an ambient temperature sensor is installed on the exterior of the mobile energy storage device's casing or battery box. Simultaneously, a triaxial accelerometer is installed on the bottom of the energy storage device casing or near the battery module to calculate the root mean square (RMS) value of vibration at each sampling moment. The maximum ambient temperature and the maximum RMS value of vibration within the current window are output every 10 seconds. This data is used to subsequently calculate the vibration-thermal coupling factor, reflecting the most unfavorable combined effect of high temperature and vibration on the energy storage device during mobile relocation. The data acquisition process is continuous and unaffected by the charging status.

[0033] Please see Figure 2 As shown, it is a flowchart for determining the vibration-thermal coupling factor in an embodiment of the present invention.

[0034] Specifically, in step S2, the process of determining the vibration-thermal coupling factor includes: Step S21: Determine the extent of ambient temperature exceeding the limit based on the ratio of the maximum ambient temperature at the energy-consuming end within the preset cycle to the preset ambient temperature threshold. Step S22: Determine the moving vibration intensity based on the ratio of the maximum value of the moving vibration data of the energy-consuming end within a preset period to a preset moving vibration data threshold. Step S23: Determine the vibration-thermal coupling factor based on the product of the ambient temperature exceeding the limit and the moving vibration intensity.

[0035] In this embodiment, the maximum ambient temperature in the data corresponding to historical normal operating conditions of the energy storage terminal is sorted in ascending order, and the 95th percentile is taken as the ambient temperature threshold. Similarly, the root mean square value of vibration in the data corresponding to historical normal operating conditions of the energy storage terminal is sorted in ascending order, and the 95th percentile is taken as the moving vibration data threshold. Based on the current maximum ambient temperature collected within a preset period (preferably 5 minutes), the ambient temperature exceedance range is calculated: the maximum ambient temperature is divided by the ambient temperature threshold to obtain the ambient temperature exceedance range, which characterizes the severity of the current high temperature; the higher the temperature, the larger the factor.

[0036] Specifically, the moving vibration intensity is calculated based on the root mean square maximum value of the moving vibration within the same period: the moving vibration intensity is obtained by dividing the root mean square maximum value by the moving vibration data threshold, which characterizes the severity of the current vibration; the stronger the vibration, the larger the factor. Multiplying the ambient temperature factor by the moving vibration intensity factor yields the vibration-thermal coupling factor = ambient temperature exceedance amplitude × moving vibration intensity. The larger the vibration-thermal coupling factor, the stronger the combined adverse effects of high temperature and vibration on the energy storage end under the current moving relocation environment.

[0037] Please see Figure 3 As shown, it is a flowchart for determining the working matching coefficient of the energy-consuming end in an embodiment of the present invention.

[0038] Specifically, in step S3, the process of determining the operating matching coefficient of the energy-consuming end includes: Step S31: Determine the first basic energy consumption configuration factor based on the ratio of the battery temperature to a preset battery temperature threshold. Step S32: Determine the second basic energy consumption configuration factor based on the ratio of the motor temperature to the preset motor temperature threshold. Step S33: Determine the working matching coefficient of the energy consumption end based on the degree of consistency between the first basic energy consumption configuration factor and the second basic energy consumption configuration factor.

[0039] In this embodiment, the power-consuming device, such as a drone, electric bicycle, or electric car, primarily uses its battery to drive mechanical motion. Therefore, the monitoring indicators include the battery and the corresponding motor that drives the mechanical motion. For the power-consuming device, the highest battery temperature and the motor temperature are obtained. For the battery temperature threshold, the 90th percentile of historical battery temperature data under normal operating conditions is calculated and sorted in ascending order. For the motor temperature threshold, the 90th percentile of historical motor temperature data under normal operating conditions is calculated and sorted in ascending order.

[0040] Specifically, the first basic energy consumption configuration factor = battery temperature / battery temperature threshold, and the second basic energy consumption configuration factor = motor temperature / motor temperature threshold.

[0041] The energy consumption matching coefficient is calculated as follows: 1 - |First Basic Energy Consumption Configuration Factor -Second Basic Energy Consumption Configuration Factor| / (First Basic Energy Consumption Configuration Factor + Second Basic Energy Consumption Configuration Factor + 0.01). A coefficient close to 1 indicates that the battery and motor temperatures are synchronized and the operation is normal; a coefficient far from 1 indicates an abnormality.

[0042] Understandably, this implementation obtains the first and second basic energy consumption configuration factors by acquiring the battery temperature and motor temperature at the energy-consuming end, calculating their ratios to the corresponding safety thresholds, and then determining the working matching coefficient based on the consistency between the two. This effectively identifies whether there are abnormal heat dissipation or mismatched operating conditions at the energy-consuming end. When the battery and motor temperatures change synchronously, a high matching degree indicates that the energy-consuming end is operating normally; when the two differ significantly, the matching coefficient decreases, suggesting a possible internal fault at the energy-consuming end. This coefficient provides crucial prior information for subsequent fast charging decisions, avoiding secondary risks caused by forcibly fast charging when the energy-consuming end is in an abnormal state.

[0043] Please see Figure 4 As shown, it is a flowchart for determining the fast charging coefficient of the power consumption terminal in an embodiment of the present invention.

[0044] Specifically, in step S4, the process of determining the fast charging coefficient of the energy-consuming end includes: Step S41: Determine the charging urgency factor based on the ratio of the actual usage time of the energy-consuming terminal to the preset demand time; Step S42: Determine the fast charging coefficient of the energy-consuming end based on the product of the working matching coefficient and the charging urgency factor.

[0045] In this embodiment, the actual usage time of the power-consuming device from the start of the current task to the current moment is obtained. A preset demand duration is calculated based on historical data of the time taken for the power-consuming device to complete the same task to reach 80% power consumption, and the median is used as the demand duration. Charging urgency factor = Actual usage time / Demand duration. Fast charging coefficient = Work matching coefficient × Charging urgency factor. The fast charging coefficient comprehensively reflects the normality of the power-consuming device's status and the urgency of charging. The larger the fast charging coefficient, the more aggressive the charging strategy can be adopted. The demand duration dynamically reflects changes in the battery life for the same task; a decrease in demand duration increases the charging urgency factor, thereby reasonably increasing the fast charging tendency.

[0046] Specifically, in step S4, the process of determining charging parameters based on the fast charging coefficient includes: Step S43: Determine the charging rate based on the product of the fast charging coefficient and the preset maximum safe charging rate; Step S44: Determine the target charging ratio based on the product of the fast charging coefficient and the preset maximum target charging ratio.

[0047] In this embodiment, for the maximum safe charging rate, the 95th percentile of the maximum charging rate data of the energy-consuming battery during historical fast charging processes without exceeding temperature rise or deformation limits is used as the maximum safe charging rate, sorted in ascending order. For the maximum target charging ratio, a safe upper limit is set based on the correlation data between the energy-consuming battery's usage time decay and the state of charge at the end of charging, such that battery decay accelerates after exceeding this limit. Specifically, charging records with usage time decay rates lower than the average are selected from historical safe fast charging processes, and the 95th percentile of the state of charge at the end of charging in these records is taken as the maximum target charging ratio. The current charging rate of the energy-consuming terminal = fast charging coefficient × maximum safe charging rate; the current target charging ratio of the energy-consuming terminal = fast charging coefficient × maximum target charging ratio. All charging parameters increase linearly with the fast charging coefficient.

[0048] Specifically, in step S5, the process of determining the heating coefficient and the deformation coefficient includes: Step S51: Determine the temperature rise coefficient based on the ratio of the maximum temperature rise rate of the battery at the energy consumption end within a unit cycle to the temperature rise rate threshold. Step S52: Determine the deformation coefficient based on the ratio of the maximum deformation rate of the battery thickness deformation at the energy consumption end to the deformation rate threshold within a unit cycle.

[0049] In this embodiment, during charging, the battery temperature and battery thickness deformation at the energy-consuming terminal are acquired in real time. The temperature rise rate is calculated every 30 seconds as (current temperature - temperature 30 seconds ago) / 3, and the maximum temperature rise rate within the last 5 minutes is taken. Simultaneously, the deformation change rate is calculated every 30 seconds as (current thickness - thickness 30 seconds ago) / 3, and the maximum deformation change rate within the last 5 minutes is taken. For the temperature rise rate threshold, the 95th percentile of the maximum temperature rise rate during normal charging in historical data is calculated and sorted in ascending order, and this is used as the temperature rise rate threshold. For the deformation change rate threshold, the 95th percentile of the maximum deformation change rate during normal charging in historical data is calculated and sorted in ascending order, and this is used as the deformation change rate threshold. The temperature rise coefficient = maximum temperature rise rate / temperature rise rate threshold, and the deformation coefficient = maximum deformation rate / deformation rate threshold. A temperature rise coefficient greater than 1 indicates excessively rapid temperature rise and poor charging status; a deformation coefficient greater than 1 indicates unreasonable battery expansion, which may pose a risk of internal short circuit or gas generation.

[0050] Specifically, in step S6, the process of determining the inducing factor includes: Step S61: Determine the inducing factor based on the weighted sum of the heating coefficient and the deformation coefficient.

[0051] In this embodiment, the inducing factor = 0.6 × temperature rise coefficient + 0.4 × deformation coefficient. The larger the inducing factor value, the higher the risk of charging degradation caused by temperature rise or deformation.

[0052] Specifically, in step S7, the process of determining whether fast charging exacerbates the risk of vibration-thermal coupling includes: Based on the fact that the inducing factor is greater than the inducing factor threshold and the vibration-thermal coupling factor is greater than the vibration-thermal coupling threshold, it is determined that there is a risk that fast charging will exacerbate vibration-thermal coupling. The inducing factor threshold and the vibration-thermal coupling factor threshold are determined based on the fast charging coefficient.

[0053] In this embodiment, data on fast charging coefficient, inducing factor, and vibration-thermal coupling factor within 5 minutes prior to the occurrence of historical abnormal events are collected. The fast charging coefficient is evenly divided into five equally spaced intervals. For each interval, the 10th percentile of the inducing factor within that interval is calculated, meaning only 10% of abnormal events occur below this value; this is used as the inducing factor threshold for that interval. Similarly, the 10th percentile of the vibration-thermal coupling factor is calculated as the vibration-thermal coupling factor threshold for that interval. If the current inducing factor is greater than the inducing factor threshold for the interval corresponding to the current fast charging coefficient, and the current vibration-thermal coupling factor is greater than the vibration-thermal coupling factor threshold for the interval corresponding to the current fast charging coefficient, then it is determined that there is a risk of fast charging exacerbating vibration-thermal coupling; otherwise, it is determined that there is no risk of fast charging exacerbating vibration-thermal coupling and monitoring continues. It can be understood that the risk of fast charging exacerbating vibration-thermal coupling is that, under the current charging conditions, the superposition of overheating / deformation at the energy consumption end and high-temperature vibration at the energy storage end may cause a rapidly deteriorating safety hazard.

[0054] Specifically, in step S8, if there is a risk that fast charging will exacerbate vibration-thermal coupling, the process of determining whether to adjust charging parameters or disconnect charging based on the temperature rise coefficient and charging progress includes: Step S81: If the heating coefficient is greater than the preset heating coefficient action threshold, then obtain the charging progress of the power consumption end. Step S82: Based on the charging progress, determine whether to adjust the charging parameters or disconnect the charging process, wherein... If the charging progress of the power supply is less than the preset charging progress threshold, it is determined that the charging parameters should be adjusted. Alternatively, if the charging progress of the power supply is greater than or equal to a preset charging progress threshold, the charging is disconnected.

[0055] In this embodiment, events that ultimately triggered protection and returned to normal after protection are selected from historical abnormal events. The 10th percentile of the temperature rise coefficient in these events is used as the temperature rise coefficient action threshold. If the current temperature rise coefficient is less than or equal to the temperature rise coefficient action threshold, a warning message is issued only through the remote platform without changing the charging parameters. If the current temperature rise coefficient is greater than the temperature rise coefficient action threshold, the current charging progress of the energy user is obtained as (current power ratio - initial power ratio) / (target charging ratio - initial power ratio). For the preset charging progress threshold, based on historical data of events that successfully completed charging without risk, the 90th percentile of the final charging progress at completion is used as the charging progress threshold. If the current charging progress is less than the charging progress threshold, the charging parameters are adjusted: new charging rate = current charging rate × 0.5, keeping the target charging ratio unchanged; if the current charging progress is greater than or equal to the charging progress threshold, charging is directly disconnected, the charging circuit is cut off, and an audible and visual alarm is issued.

[0056] Specifically, in step S9, the process of determining whether the energy storage terminal needs to recharge the energy consumption terminal battery includes: If the status monitoring parameters of both the energy-consuming battery and the energy storage terminal meet the recharge threshold, it is determined that the energy storage terminal will recharge the energy-consuming battery, and the charging parameters will be determined based on the updated fast charging coefficient. Alternatively, if the status monitoring parameters of the energy-consuming battery and the energy storage end do not meet any recharge threshold, it is determined that there is an energy consumption risk at the energy storage end, and the need to suspend the energy consumption task at the energy storage end is determined. The status monitoring parameters include the energy-consuming battery temperature, the energy-consuming battery thickness deformation, the energy storage ambient temperature, and the energy storage vibration data. The recharge thresholds include the energy-consuming battery temperature threshold, the energy-consuming battery thickness deformation threshold, the energy storage ambient temperature threshold, and the energy storage moving vibration data threshold.

[0057] In this embodiment, after adjusting or disconnecting charging, four status parameters are continuously monitored every 30 seconds: battery temperature at the energy consumption end, battery thickness deformation at the energy consumption end, ambient temperature at the energy storage end, and root mean square value of vibration at the energy storage end. For each parameter, data from historical data showing normal charging completion without subsequent risks are selected, and the 90th percentile of the corresponding parameter in these data is calculated as the upper limit of the recharge threshold. If all real-time parameters meet the recharge threshold, it is determined that the energy storage end can recharge the battery at the energy consumption end. At this time, the fast charging coefficient is recalculated based on the updated energy consumption end working matching coefficient and actual usage time, and the charging parameters are re-determined to start a new round of charging. If any parameter does not meet the corresponding recharge threshold, it is determined that there is an energy consumption risk at the energy storage end, a pause command is output, and charging is prohibited until manual intervention or automatic recovery of the status parameters.

[0058] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A mobile energy storage safety monitoring method based on multi-source data fusion, characterized in that, include: Real-time acquisition of ambient temperature and vibration data of the mobile energy storage terminal; The vibration-thermal coupling factor is determined based on the ambient temperature and the moving vibration data. Obtain the battery temperature and motor temperature at the energy consumption end, and determine the working matching coefficient of the energy consumption end based on the battery temperature and motor temperature; The fast charging coefficient of the energy-consuming terminal is determined based on the working matching coefficient and the actual usage time of the energy-consuming terminal, so as to determine the charging parameters, wherein the charging parameters include the charging rate and the target charging ratio. During the charging process, the battery temperature and battery thickness deformation at the energy consumption end are acquired in real time to determine the temperature rise coefficient and deformation coefficient. The inducing factor is determined based on the heating coefficient and the deformation coefficient; Based on the comparison results of the vibration-thermal coupling factor and the inducing factor with the corresponding threshold, it is determined whether there is a risk that fast charging will exacerbate vibration-thermal coupling. If there is a risk that fast charging will exacerbate vibration-thermal coupling, then the charging parameters should be adjusted or charging should be disconnected based on the temperature rise coefficient and the charging progress at the energy-consuming end. Periodic and continuous monitoring is performed on the battery status of the energy user end and the vibration-thermal coupling status of the energy storage end after adjusting the charging parameters or disconnecting the charging, in order to determine whether the energy storage end should recharge the energy user end. 2.The mobile energy storage safety monitoring method based on multi-source data fusion of claim 1, wherein, The process of determining the vibration-thermal coupling factor includes: The extent of ambient temperature exceeding the limit is determined based on the ratio of the maximum ambient temperature at the energy-consuming end within a preset period to a preset ambient temperature threshold. The intensity of mobile vibration is determined based on the ratio of the maximum value of the mobile vibration data at the energy-consuming end within a preset period to the preset threshold value of the mobile vibration data. The vibration-thermal coupling factor is determined based on the product of the ambient temperature exceeding the limit and the intensity of the moving vibration. 3.The mobile energy storage safety monitoring method based on multi-source data fusion of claim 2, wherein, The process of determining the working matching coefficient at the energy consumption end includes: The first basic energy consumption configuration factor is determined based on the ratio of the battery temperature to a preset battery temperature threshold. The second basic energy consumption configuration factor is determined based on the ratio of the motor temperature to a preset motor temperature threshold. The working matching coefficient of the energy consumption end is determined based on the degree of consistency between the first basic energy consumption configuration factor and the second basic energy consumption configuration factor. 4.The mobile energy storage safety monitoring method based on multi-source data fusion of claim 3, wherein, The process of determining the fast charging coefficient at the energy consumption end includes: The charging urgency factor is determined based on the ratio of the actual usage time at the energy-consuming end to the preset demand time. The fast charging coefficient of the energy-consuming end is determined based on the product of the working matching coefficient and the charging urgency factor.

5. The mobile energy storage safety monitoring method based on multi-source data fusion according to claim 4, characterized in that, The process of determining charging parameters based on the fast charging coefficient includes: The charging rate is determined based on the product of the fast charging coefficient and the preset maximum safe charging rate; The target charging ratio is determined by multiplying the fast charging coefficient by the preset maximum target charging ratio.

6. The mobile energy storage safety monitoring method based on multi-source data fusion according to claim 5, characterized in that, The process of determining the temperature rise coefficient and the deformation coefficient includes: The temperature rise coefficient is determined based on the ratio of the maximum temperature rise rate of the battery at the energy consumption end to the temperature rise rate threshold within a unit cycle. The deformation coefficient is determined by the ratio of the maximum deformation rate of the battery thickness deformation at the energy consumption end to the deformation rate threshold within a unit cycle. 7.The mobile energy storage safety monitoring method based on multi-source data fusion of claim 6, wherein, The process of identifying triggering factors includes: The inducing factor is determined by weighted summation of the heating coefficient and the deformation coefficient. 8.The mobile energy storage safety monitoring method based on multi-source data fusion of claim 7, wherein, The process of determining whether fast charging exacerbates the risk of vibration-thermal coupling includes: Based on the fact that the inducing factor is greater than the inducing factor threshold and the vibration-thermal coupling factor is greater than the vibration-thermal coupling threshold, it is determined that there is a risk that fast charging will exacerbate vibration-thermal coupling. The inducing factor threshold and the vibration-thermal coupling factor threshold are determined based on the fast charging coefficient. 9.The mobile energy storage safety monitoring method based on multi-source data fusion of claim 8, wherein, If fast charging exacerbates the risk of vibration-thermal coupling, the process of adjusting charging parameters or disconnecting charging based on the temperature rise coefficient and charging progress includes: If the temperature rise coefficient is greater than the preset temperature rise coefficient action threshold, then the charging progress of the energy-consuming end is obtained. Based on the charging progress, determine whether to adjust the charging parameters or disconnect charging, wherein... If the charging progress of the power supply is less than the preset charging progress threshold, it is determined that the charging parameters should be adjusted. Alternatively, if the charging progress of the power supply is greater than or equal to a preset charging progress threshold, the charging process is disconnected. 10.The mobile energy storage safety monitoring method based on multi-source data fusion of claim 9, wherein, The process of determining whether the energy storage device needs to recharge the energy consumption device's battery includes: If the status monitoring parameters of both the energy-consuming battery and the energy storage terminal meet the recharge threshold, it is determined that the energy storage terminal will recharge the energy-consuming battery, and the charging parameters will be determined based on the updated fast charging coefficient. Alternatively, if the status monitoring parameters of the energy-consuming battery and the energy storage end do not meet any recharge threshold, it is determined that there is an energy consumption risk at the energy storage end, and the need to suspend the energy consumption task at the energy storage end is determined. The status monitoring parameters include the energy-consuming battery temperature, the energy-consuming battery thickness deformation, the energy storage ambient temperature, and the energy storage vibration data. The recharge thresholds include the energy-consuming battery temperature threshold, the energy-consuming battery thickness deformation threshold, the energy storage ambient temperature threshold, and the energy storage moving vibration data threshold.

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