Power battery box positioning monitoring method based on low power consumption application

Abstract

The invention discloses a power battery box positioning and monitoring method based on low power consumption application, relates to the technical field of battery box positioning and monitoring, and is used for solving the problem of high power consumption in a power battery box monitoring process. According to the method, the battery remaining capacity is calculated through voltage, current and temperature data, temperature compensation and open-circuit voltage correction are combined, high-reliability electric quantity characteristics are constructed, the motion state is detected according to the three-axis acceleration sensor, the charge level, the environmental risk and the moving event are fused to generate a dynamic decision vector, and the geographical fence range is intelligently adjusted. A monitoring area is expanded when the electric quantity is high, a safety core area is contracted when the electric quantity is low, a global positioning technology or an indoor positioning technology is automatically switched based on indoor and outdoor scenes, invalid positioning energy consumption is reduced through a mobile triggering mechanism, a positioning state is analyzed in real time, a graded response signal is generated, and redundant positioning is started under abnormal conditions to guarantee monitoring continuity. And the balance of full-period safety protection and low-power-consumption operation of the power battery box is realized, and the cruising ability is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring and management of power battery boxes, and more specifically, to a positioning and monitoring method for power battery boxes based on low-power applications. Background Art

[0002] With the rapid development of new energy vehicles, energy storage systems, and battery swapping models, as the core energy carrier, the safety, reliability, and full-life cycle management requirements of power batteries have become increasingly prominent. During the transportation, storage, and operation of power battery boxes, they may face risks such as illegal displacement, environmental out-of-control (such as high temperature, water immersion), or abnormal charging and discharging. In the lightest case, it may lead to battery performance degradation, and in the most serious case, it may trigger safety accidents such as thermal runaway.

[0003] Deficiencies of the prior art: The monitoring of power battery boxes mostly relies on fixed geographical fences and continuous high-power positioning (such as pure GPS tracking), which cannot dynamically adapt to the battery power state and environmental changes, resulting in the system failing prematurely due to excessive energy consumption at low battery levels. In complex scenarios (such as urban canyons, indoor warehouses), positioning blind spots frequently appear. There is a lack of a multi-mode redundant fault tolerance mechanism, and the battery life is severely limited. It is unable to dynamically adjust the monitoring strategy according to the state of charge and environmental conditions of the battery, resulting in monitoring blind spots or false alarms easily occurring at low battery levels or in complex scenarios, and relying on a large amount of manual intervention, causing high operation and maintenance costs. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the following solutions are provided to solve the problem of high power consumption in the monitoring process of power battery boxes in the above background art.

[0005] To achieve the above object, the present invention provides the following technical solutions: A positioning and monitoring method for a power battery box based on low-power applications, comprising the following steps: Determine the remaining battery power based on the collected data of voltage, current, and temperature, and perform error correction by combining temperature compensation and open-circuit voltage curves to extract the state-of-charge characteristics; Detect the motion state by a three-axis acceleration sensor, discriminate valid movement events through gravity compensation and variance analysis, and generate a fusion vector that combines the state of charge, environmental risks, and motion state; Dynamically adjust the fence radius according to the state-of-charge level, environmental risks, and motion state, switch the positioning mode in combination with indoor and outdoor scenarios, and trigger the activation of the positioning process when a movement event occurs; Analyze the operating state after the activation of the positioning process of the power battery box, obtain the positioning state information generated during the analysis of the operating state, and generate different signals according to the analyzed positioning state information to adjust the positioning monitoring strategy.

[0006] In a preferred embodiment, the remaining battery capacity is determined based on the collected data of voltage, current, and temperature. The specific steps are as follows: The total voltage and monomer voltage of the battery are collected by a voltage sensor, the charge and discharge current is collected by a current sensor, and the temperature near the power battery box is collected by a temperature sensor; The collected voltage and current signals are filtered using a moving average filter to suppress high-frequency noise, and the temperature data is filtered using a median filter to eliminate transient interference. When the instantaneous jump of the current exceeds 3 times the standard deviation of the historical mean, it is determined as noise and interpolated for repair; The remaining battery capacity is calculated by accumulating the charge and discharge of the battery.

[0007] In a preferred embodiment, error correction is performed by combining temperature compensation and the open-circuit voltage curve, and the state-of-charge characteristics are extracted. The specific steps include: Perform curve fitting and correction of the open-circuit voltage. After the battery charge and discharge are completed, let it stand for 2 hours to allow the polarization voltage to decay to a stable state. At 25°C, construct a reference curve , and conduct experiments at -10°C, 0°C, 25°C, and 45°C to establish a three-dimensional lookup table of temperature-SOC-OCV; The OCV interpolation calculation expression is: , where is the temperature coefficient, which is determined by fitting experimental data; Perform temperature compensation, and the effective capacity of the battery is modeled based on the Arrhenius equation: , where is the activation energy of the battery, R is the ideal gas constant, is the set fixed temperature; Correct the state of charge according to the effective capacity: ; Use the corrected state of charge, voltage, current, and temperature as the input for the dynamic geofencing strategy.

[0008] In a preferred embodiment, the motion state is detected according to a triaxial acceleration sensor, and effective movement events are discriminated through gravity compensation and variance analysis. The specific steps are as follows: When stationary, the acceleration sensor continuously senses the gravity component, which needs to be removed through coordinate transformation: , where is the tilt and pitch angles of the battery box installation; , , respectively represent the acceleration components of the object in the x-axis, y-axis, and z-axis directions; Simplify the discrimination of the motion state, and convert the triaxial acceleration into a scalar modulus: , and the modulus Reflect the overall motion intensity of the battery box, , , respectively represent the motion accelerations of the three axes; Calculate the variance of the real-time acceleration magnitude through a sliding window: , where N = 10 is the window length, is the average acceleration within the window; Set a discrimination threshold to determine the movement event.

[0009] In a preferred embodiment, set a discrimination threshold to determine the movement event, and the specific steps are as follows: Set a discrimination threshold. If the continuous movement duration meets the discrimination threshold determination condition, it is determined as a valid movement event; After the valid movement event is confirmed, immediately wake up the positioning module and obtain the current position. If the position does not exceed the geographical fence range corresponding to the current state of charge, put the positioning module into sleep and record the status. When crossing the boundary, activate the sound and light alarm and upload the alarm information to the cloud; If there is no movement event within the continuous movement duration, turn off the positioning module and run the IMU at a frequency of 1Hz.

[0010] In a preferred embodiment, generate a fusion vector that combines the state of charge, environmental risk, and motion state, including the following steps: Perform hierarchical discretization determination on the state of charge after correcting the available capacity. When the state of charge after correcting the available capacity is greater than or equal to 80%, it is a high-level state; If it is less than 20%, it is a low-level state, indicating that it is approaching the power shortage state, and the fence range needs to be forced to be reduced to ensure basic safety; The remaining states are medium-level states, and an equalization strategy is adopted to balance safety and power consumption; Classify the environmental risk level. When the temperature is greater than 50°C, it is a high-risk; when the temperature is greater than 40°C and less than or equal to 50°C, it is a medium-risk; in other cases, it is safe; Generate a state vector S = [SOC level, environmental risk level, motion state], where the environmental risk level includes three levels: high risk, medium risk, and safe, the motion state includes moving and stationary states, and the SOC level includes high, medium, and low states.

[0011] In a preferred embodiment, dynamically adjust the fence radius according to the state of charge level, environmental risk, and motion state, and switch the positioning mode in combination with indoor and outdoor scenarios, including the following steps: Determine the high state-of-charge interval according to the battery discharge curve display and calculate the basic fence radius: , where, , The theoretical maximum and minimum values ​​of the fence radius respectively; , represents the nonlinear coefficient; , They are the lower and upper limits of the state of charge range adjusted by the dynamic fence radius. is the actual state of charge value of the battery; In outdoor scenarios, the system dynamically selects a positioning strategy based on the battery state of charge: when the state of charge is at a high level greater than or equal to 80%, positioning is performed using the global positioning system and inertial measurement unit fusion positioning technology; When the state of charge is less than 80%, it switches to the combined mode of base station cellular identification and IMU dead reckoning; In indoor scenarios, if the power battery box is in motion, ultra-wideband and geomagnetic fingerprint matching technology is used to match the magnetic field characteristics through the pre-stored warehouse geomagnetic map combined with the dynamic time warping algorithm; if the battery box is stationary, the UWB and geomagnetic modules are turned off, and positioning is performed based on the IMU's accelerometer and gyroscope.

[0012] In a preferred embodiment, the positioning process is triggered to be activated when a movement event occurs, including the following steps: When the daily average power consumption of the GPS module for continuous positioning exceeds 50%, motion status detection is performed; Activate displacement-triggered positioning, perform gravity compensation and acceleration extraction: ,in, They represent the acceleration of the x, y, and z axes respectively, and g represents the acceleration due to gravity; The instantaneous trigger conditions for motion event identification are: ,in, is the preset acceleration threshold; When the trigger condition is met, the hardware is activated to switch positioning according to the positioning mode identifier.

[0013] In a preferred embodiment, analyzing the running state of the power battery box positioning process after activation, and obtaining the positioning state information generated during the running state analysis process, includes the following steps: Acquire the positioning status information generated in the process of analyzing the operation status after activation, wherein the positioning status information includes positioning operation information and switching use information; The positioning operation information includes the positioning operation stability index, and the switching use information includes the standby switching effectiveness index; The positioning operation stability index and the standby switching efficiency index are combined to generate an operation determination coefficient; The positioning operation stability index and the standby switching efficiency index are both positively correlated with the operation determination coefficient.

[0014] In a preferred embodiment, different signals are generated according to the analyzed positioning status information to adjust the positioning monitoring strategy, including the following steps: Compare the operation determination coefficient with the positioning operation determination threshold; If the operation determination coefficient is greater than or equal to the positioning operation determination threshold, a stable positioning status monitoring signal is generated at this time, and there is no need for immediate intervention. Continue to collect positioning data at the default frequency; If the operation determination coefficient is less than the positioning operation determination threshold, an abnormal positioning status monitoring signal is generated, and the positioning intervention operation is immediately executed to adjust the positioning strategy.

[0015] The technical effects and advantages of a power battery box positioning monitoring method based on low-power applications of the present invention: The present invention realizes high-precision calculation of the state of charge of the battery by fusing multi-modal data such as voltage, current, and temperature, and combines temperature compensation and open-circuit voltage curve correction to significantly improve the reliability of power estimation; based on the motion state detection and variance analysis of a three-axis acceleration sensor, a multi-dimensional fusion vector of state of charge - environmental risk - motion state is constructed to realize intelligent adjustment of the dynamic geographical fence radius, expand the monitoring range at high state of charge to match transportation requirements, and focus on the core area at low state of charge to reduce power consumption; through the adaptive switching of positioning modes for indoor and outdoor scenarios combined with a mobile event trigger mechanism; at the same time, the positioning status information is analyzed in real time and a hierarchical response signal is generated, and redundant positioning is forcibly activated in case of abnormal displacement or environmental risk to ensure uninterrupted safety monitoring, taking into account the full-cycle safety protection and ultra-low power operation of the power battery box to improve the battery life of the power battery box. Description of the Drawings

[0016] Figure 1 It is a schematic flowchart of a power battery box positioning monitoring method based on low-power applications of the present invention. Detailed Embodiments

[0017] 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 a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] To achieve the above object, Figure 1 A structural schematic diagram of a power battery box positioning monitoring method based on low-power applications of the present invention is given, specifically including the following steps; Determine the remaining battery power based on the collected data of voltage, current, and temperature, and perform error correction by combining temperature compensation and open-circuit voltage curve to extract the state of charge characteristics; Detect the motion state according to the triaxial acceleration sensor, distinguish valid movement events through gravity compensation and variance analysis, and generate a fusion vector that combines the state of charge, environmental risk, and motion state; Dynamically adjust the fence radius according to the state of charge level, environmental risk, and motion state, switch the positioning mode in combination with indoor and outdoor scenarios, and trigger the activation of the positioning process when a movement event occurs; Analyze the operating state after the activation of the positioning process for the power battery box, obtain the positioning state information generated during the analysis of the operating state, and generate different signals according to the analyzed positioning state information to adjust the positioning monitoring strategy.

[0019] Step 1, perform multi-dimensional state perception and dynamic modeling of the power battery box, construct a real-time state representation of the battery box, and provide a data basis for the dynamic geofence strategy. The specific steps are as follows: The state of charge SOC (State of Charge) of the power battery box is the core parameter reflecting the remaining available battery power. Its accurate calculation requires multi-dimensional real-time data collection and fusion analysis. Therefore, physical quantities such as the voltage, current, and temperature of the battery are sampled at high frequency, and through experimental calibration and physical model compensation, the state of charge value with an error ≤ 3% is finally output Collect the total battery voltage and monomer voltage (if it is a multi-string battery pack) through a voltage sensor, use a current sensor (such as a Hall effect sensor) to collect the charge and discharge current I, with a positive value for charging and a negative value for discharging, use a temperature sensor (such as DS18B20) to collect the temperature near the power battery box, deploy at least 3 temperature measurement points (positive electrode, negative electrode, environment), and take the weighted average; Suppress high-frequency noise for the collected voltage and current signals through moving average filtering, and use median filtering for temperature data to eliminate transient interference. If the current instantaneous jump exceeds 3 times the standard deviation of the historical mean (lasting < 10ms), it is determined as noise and interpolated for repair; Calculate the remaining battery power through cumulative battery charge and discharge. The formula is as follows: , where is the initial state of charge, is the nominal battery capacity (such as 100Ah), is the number of real-time charge and discharge current times, and t represent time, within the time interval from to t.

[0020] Perform open-circuit voltage (OCV) curve fitting and correction. The specific steps are as follows: After the battery charge and discharge are completed, let it stand for 2 hours to make the polarization voltage decay to a stable state. At 25°C, measure the corresponding OCV values at 10% SOC intervals (0%, 10%,..., 100%) to construct a reference curve Repeat the experiment at different temperatures (-10°C, 0°C, 25°C, 45°C) to establish a three-dimensional lookup table of temperature - SOC - OCV; The OCV interpolation calculation expression is: , where is the temperature coefficient, obtained by fitting experimental data; Perform temperature compensation. The effective capacity of the battery exponentially decays with the increase of temperature and can be modeled based on the Arrhenius equation: , where is the battery activation energy (experimentally calibrated value), R is the ideal gas constant, is the reference temperature, which is set to 25 degrees Celsius in this example; Correct the state of charge according to the effective capacity: ; In summary, jointly correct the voltage, current, and temperature as, avoiding the SOC deviation caused by the error of a single sensor, thus providing high-precision input for the dynamic geofencing strategy.

[0021] During the low-power positioning and monitoring of the power battery box, continuously activating the high-precision positioning module (such as GPS) will cause a sharp increase in energy consumption and significantly shorten the system's endurance. However, if relying entirely on the positioning strategy at fixed time intervals, it may lead to safety risks due to response delays (such as the battery box being stolen and not being discovered in time). Therefore, set the intelligent control logic to sleep when stationary and trigger on demand when moving. The specific steps are as follows: The output state of charge value (used to dynamically adjust the trigger sensitivity), the compensated temperature data (the false trigger rate needs to be reduced in high-temperature environments), and the original acceleration signal collected in real-time through the three-axis acceleration sensor (IMU); The power battery box is usually fixed in a vehicle or energy storage cabinet. When it is stationary, the acceleration sensor will continuously sense the gravity component (about g = 9.8 m / s²), which needs to be removed through coordinate transformation: , where is the installation tilt and elevation angles of the battery box, pre-stored through factory calibration to eliminate static gravity interference; , , respectively represent the acceleration components of the object in the x-axis, y-axis, and z-axis directions, retaining the motion acceleration of the three axes , , ; Simplify the motion state discrimination and convert the three-axis acceleration to a scalar magnitude: , and the magnitude reflects the overall motion intensity of the battery box; The variance of the acceleration magnitude characterizes the intensity of motion, and the real-time variance is calculated through a sliding window: , where N = 10 is the window length (corresponding to 1 second of data, sampling rate 10 Hz), balancing real-time performance and anti-noise ability, is the average acceleration within the window; Set a discrimination threshold (corresponding to the scenario of the vehicle driving at a constant speed or with slight bumps) to determine the intensity. At the same time, to avoid false triggering caused by instantaneous vibrations (such as road bumps), it is necessary to detect the continuous movement duration. If 10 consecutive windows (for example, 10 seconds) all meet the discrimination threshold determination conditions, it is determined as a valid movement event; After the movement event is confirmed, immediately wake up the positioning module (GPS / base station) and obtain the current position. If the position does not exceed the geographical fence range corresponding to the current state of charge, put the positioning module into sleep and record the status. When crossing the boundary, activate the sound and light alarm and upload the alarm information to the cloud; If there is no movement event for a continuous movement duration (for example, 5 minutes), turn off the positioning module and only maintain the IMU to run at a frequency of 1 Hz.

[0022] The state of charge after correcting the effective capacity is subjected to hierarchical discretization determination. When the state of charge after correcting the effective capacity is greater than or equal to 80%, it is a high-level state, indicating that the battery in the battery box has a high discharge efficiency in this interval and is suitable for large-scale monitoring and high-frequency positioning. If it is less than 20%, it is a low-level state, indicating that it is approaching the power shortage state, and it is necessary to forcibly reduce the fence range to ensure basic safety. The remaining states are medium-level states, and an equilibrium strategy is adopted to balance safety and power consumption; Similarly, the environmental risk level is divided. When the temperature is greater than 50 °C, it is a high-risk, when the temperature is greater than 40 °C and less than or equal to 50 °C, it is a medium-risk, and in other cases it is safe; Generate a state vector S = [SOC level, environmental risk level, motion state]. Among them, the environmental risk level has three levels: high risk, medium risk, and safe, the motion state has 2 states (moving / still), and the SOC level has 3 states (high / medium / low).

[0023] Step 2, perform dynamic geographical fence parameter mapping and decision optimization, dynamically adjust the geographical fence parameters (fence radius, positioning mode, communication frequency) to achieve a balance between low power consumption and safety monitoring. The specific steps are as follows: The state vector output by Step 1 only represents the real-time state of the battery box. It is necessary to convert it into executable monitoring strategy parameters (fence radius, positioning mode, communication frequency). Therefore, when the battery is at high power, a large range and high-precision monitoring are required; when the battery is at low power, the fence needs to be shrunk and the power consumption reduced. When switching between indoor and outdoor environments, the positioning mode needs to be adjusted seamlessly to avoid monitoring failure caused by signal blind spots, and the data transmission frequency needs to be dynamically adjusted according to the battery power and motion state to reduce redundant communication energy consumption; The fixed fence radius cannot cover the transportation path at high battery power, and it wastes energy due to the excessive range at low battery power. The radius is dynamically adjusted according to the state of charge level, environmental risk, and motion state. The specific steps are as follows: According to the battery discharge curve, in the high state of charge interval (80%-100%), the battery has a high power utilization rate, and it is necessary to expand the monitoring range to match the transportation demand. The basic radius is calculated as follows: , where 、 are the theoretical maximum and minimum values of the fence radius respectively, , which represents the non-linear coefficient, reflecting the rapid expansion of the fence radius at high SOC (for example, when the SOC increases from 80% to 100%, the radius increase accounts for 70% of the total), 、 are the lower and upper limit values of the state of charge interval for dynamic fence radius adjustment respectively, is the actual state of charge value of the battery; A single positioning mode cannot adapt to complex scenarios (such as urban canyons, indoor warehouses). The optimal positioning combination is selected according to SOC, environmental risk, motion state, and signal strength, as follows: The indoor and outdoor scenarios are discriminated by the GPS signal strength threshold. When the GPS signal strength is -145dBm, it is judged as outdoor, otherwise it is indoor; In the outdoor scenario, the system dynamically selects the positioning strategy according to the state of charge (SOC) of the battery: when the SOC is at high power (≥80%), the global positioning system (GPS) and inertial measurement unit (IMU) fusion positioning technology is adopted. The Kalman filter algorithm is used to assign 70% weight to the GPS data, and combined with the short-term motion compensation of the IMU, high-precision positioning with an accuracy of ≤5 meters can be achieved. Although the power consumption is high, it can meet the wide-area monitoring requirements; when the SOC drops to medium and low power (<80%), it switches to the combination mode of base station cellular identification (CID / TA) and IMU dead reckoning. The base station provides a coarse-grained position reference, and the IMU calculates the short-term movement trajectory. The positioning accuracy is ≤50 meters, and the overall power consumption is lower than that of the pure GPS scheme, significantly extending the battery life; In the indoor scenario, the positioning strategy is further refined: if the battery box is in a moving state, ultra-wideband (UWB) and geomagnetic fingerprint matching technology are adopted. By pre-storing the geomagnetic map of the warehouse and combining with the dynamic time warping (DTW) algorithm, the magnetic field characteristics are matched in real time. UWB provides centimeter-level calibration, and the overall accuracy is ≤1 meter; if the battery box is stationary, the UWB and geomagnetic modules are turned off, and only the accelerometer and gyroscope of the IMU are relied on for dead reckoning. The positioning accuracy is relaxed to ≤200 meters, and the power consumption can be controlled below 1 mA to achieve ultra-low power standby. This strategy realizes the global optimization of positioning accuracy and power consumption through indoor and outdoor environment recognition and the linkage of power and motion state.

[0024] Fixed-frequency communication may miss key events when the battery is fully charged, and may prematurely deplete energy due to frequent transmissions when the battery is low. It is necessary to dynamically adjust the communication interval according to the state of charge and motion state, determine the communication frequency, and optimize the network resource occupancy. For example, when moving, the position changes frequently, and the communication interval is shortened to 50% of the current value to avoid event omission. In the indoor-outdoor transition area (such as the warehouse entrance), positioning jumps are likely to occur due to signal mutations. It is necessary to achieve smooth switching through a signal attenuation model and error compensation. The UWB signal attenuation compensation expression is: , where and are the reference error and reference signal power respectively, is the actually measured UWB signal power, is the path loss exponent, which characterizes the influence intensity of the environment on signal attenuation (for example, 2 outdoors and 3-6 indoors).

[0025] To sum up, by integrating the environment, motion, and signal strength, the indoor and outdoor scenarios are adaptively switched, the abstract state data is converted into executable monitoring strategies, and the daily power consumption is reduced on the premise of ensuring safety through multi-dimensional parameter optimization.

[0026] Step 3: Execute the energy consumption optimization strategy according to event-driven, and the specific steps are as follows: After generating the dynamic geofence parameters (fence radius, positioning mode, communication frequency) in Step 2, through the event-driven mechanism and adaptive control strategy, the on-demand activation of hardware and energy consumption optimization are realized; Continuous positioning (such as updating every second) causes the daily power consumption of the GPS module to account for more than 50%. It is necessary to detect the motion state and activate the positioning only when the battery box is moving to reduce the ineffective energy consumption; Perform displacement-triggered positioning activation, gravity compensation, and acceleration extraction: , where represent the accelerations of the x, y, and z axes respectively, and g represents the acceleration due to gravity; The instantaneous trigger condition for mobile event discrimination is as follows: , where is the preset acceleration threshold, ; After the trigger condition is met, the corresponding hardware is activated according to the positioning mode identifier (GPS / base station / UWB).

[0027] During the positioning process of the power battery box, the analysis process of verifying the stability of the main positioning process after activation and the switching efficiency of the standby module is the core link to ensure that the power battery box positioning system can still maintain high reliability under low-power constraints. This process quantifies and evaluates the fault tolerance and response speed of the system by real-time monitoring the operating status of the positioning process (such as GPS signal strength, packet loss rate, positioning accuracy attenuation) and the switching performance of the standby module (such as switching time consumption, function degradation degree). For example, when positioning frequently fails due to signal occlusion, analyzing its stability can identify root causes such as hardware aging or environmental interference; while analyzing the switching efficiency of the standby module can expose deficiencies in the redundancy strategy (such as switching delay caused by unregistered base station positioning). This process provides data support for dynamic optimization and avoids monitoring interruption caused by the coordinated failure of the main and standby modules; Analyze the operating status of the power battery box positioning process after activation, and obtain the positioning status information generated during the analysis of the operating status after activation. The positioning status information includes positioning operation information and switching usage information; The positioning operation information includes the positioning operation stability index calibrated as PSI, and the switching usage information includes the standby switching efficiency index calibrated as RSEI; The positioning operation stability index is used to represent the continuous stable operation ability of the power battery box positioning after the main positioning module (such as GPS, UWB, etc.) is activated. The positioning operation stability index is an important indicator for measuring whether the power battery box positioning system can continuously and stably work after startup. By comprehensively evaluating the failure rate, accuracy retention ability, and data credibility of the positioning module, it comprehensively reflects the anti-interference ability and long-term reliability of the positioning process in a complex environment. Its core role is to early warn of potential risks, guide maintenance decisions, and optimize system resource allocation to ensure that the power battery box is always under effective monitoring during transportation, storage, and use; The positioning operation stability index can intuitively display the working status of the main positioning module (such as the satellite positioning module). For example, during long-distance transportation, if the positioning module frequently causes positioning interruption due to signal occlusion or hardware aging, the positioning operation stability index will drop significantly, prompting the operation and maintenance personnel to check the antenna connection or replace the damaged components in time. By tracking the index change for a long time, the service life of the module can be predicted to avoid sudden failures affecting the overall monitoring effect; For example, when a logistics vehicle transports a power battery box across regions, the positioning module needs to adapt to various environments such as mountains, tunnels, and urban canyons. When the vehicle enters a tunnel and the satellite signal is interrupted, the positioning operation stability index reflects the failure duration and recovery efficiency of the positioning module in real time. If the positioning operation stability index continuously drops below the safety threshold, the system automatically activates the inertial navigation module to take over temporarily and notifies the dispatching center to adjust the route to prevent the battery box from losing monitoring in the signal blind area; The acquisition logic of the positioning operation stability index is as follows: Obtain the total duration during which the main positioning module fails to work properly due to signal loss or hardware failure within the statistical period as the cumulative failure duration Obtain the total working time of the main positioning module from activation to the current moment as the total operation duration , obtain the initial accuracy after activation And periodically collect the current accuracy , calculate the attenuation amount as: ; Obtain the original coordinate data The effective positioning data volume after filtering out outliers , calculate the positioning operation stability index, and the formula is as follows: ; It should be noted that the cumulative failure duration is obtained by extracting the start and end timestamps of all module failure events (such as GPS satellite loss, UWB disconnection) recorded in the system log; the periodic collection can be set to once per hour, once per day, etc.; the filtering rule for the effective positioning data volume can be to eliminate data points outside the preset fence range, or if the displacement between two adjacent positionings exceeds the physical limit (such as moving 200 meters within 1 second), it is determined as an abnormal jump, and data points with discontinuous or disordered timestamps are regarded as invalid data points.

[0028] The standby switching efficiency index is used to measure the switching efficiency and function retention ability of the standby module in the power battery box positioning after the main positioning module fails. The standby switching efficiency index comprehensively evaluates the switching speed, accuracy loss degree, and switching success rate, and comprehensively reflects the emergency response ability of the system under sudden failures or environmental interferences. Its core role is to ensure seamless connection between the main and standby modules, minimize the risk of monitoring interruption, and provide data support for optimizing the redundancy strategy, so as to ensure continuous and reliable monitoring of the power battery box in all weather and all scenarios; When the main positioning module fails due to signal loss, hardware failure or environmental interference, the backup module needs to quickly take over the positioning task. The backup switching efficiency index can quantify the total time from the failure of the main module to the successful activation of the backup module and the output of the valid position. For example, when a logistics vehicle passes through a tunnel and causes satellite positioning to be interrupted, if the backup base station positioning module completes the switch within 5 seconds, the index will reflect its efficiency; if the switch takes more than 30 seconds, the index will drop significantly, indicating that the warm-up process or communication protocol needs to be optimized; In multiple active-standby switching events, the standby module may fail to switch due to weak signals, configuration errors, or hardware failures. The standby switching efficiency index counts the historical switching success rate and identifies high-frequency failure scenarios. For example, due to severe metal shielding in a battery swap station, the base station positioning module switching success rate is only 60%. A continuously low index may prompt the addition of indoor positioning anchor points or the use of a geomagnetic matching solution with stronger anti-interference properties. For example, when a vehicle enters a long tunnel, the satellite positioning signal is completely lost. At this time, the backup switching efficiency index is used to determine whether it is necessary to forcibly switch to the inertial navigation module (such as gyroscope + accelerometer). If the index shows that the switching time is short and the accuracy loss is controllable, the current strategy is maintained; if the index continues to be low, the driver is prompted to slow down or start the manual takeover mode to prevent the battery box from losing control in the blind spot. The logic for obtaining the standby switching effectiveness index is as follows: Get the total time from the failure of the main positioning module to the first output of the valid position by the backup module , get the average positioning accuracy before the main module fails Average positioning accuracy after switching to the backup module , calculate the loss ratio of positioning accuracy relative to the main module as the functional loss value, and the calculation expression is: , get the upper limit of the allowed function loss , get the number of times the standby module completes effective positioning in a unit time Total number of switches , calculate the standby switching effectiveness index, the calculation expression is: .

[0029] It should be noted that the switching time is based on the main module failure timestamp and the backup module first valid positioning timestamp in the system log; the unit time is set according to actual needs.

[0030] The positioning operation information and the switching use information are combined to generate the operation determination coefficient, that is, the obtained positioning operation stability index and the standby switching efficiency index are combined to generate the operation determination coefficient. The expression is: , where , is a preset proportionality coefficient for the positioning operation stability index and the standby switching efficiency index, and , are both greater than 0.

[0031] Specific methods for jointly generating the operation determination coefficient may involve various algorithms and models, which depend on the actual situation and application requirements. In this embodiment, the weighted summation method can be used to combine the positioning operation stability index and the standby switching efficiency index to generate a comprehensive operation determination coefficient. This operation determination coefficient can be used as an input for comprehensively evaluating the overall reliability of the activated power battery box positioning system to determine the final operating state.

[0032] It should be noted that the size of the preset proportionality coefficient is a specific value obtained by quantifying each parameter. It is for the convenience of subsequent comparison. Regarding the size of the coefficient, it depends on the amount of sample data and the initial setting of the corresponding preset proportionality coefficient for each group of sample data by those skilled in the art; it is not unique as long as it does not affect the proportional relationship between the parameter and the quantified value. For example, the positioning operation stability index is directly proportional to the operation determination coefficient. Normalize the positioning operation stability index and the standby switching efficiency index to have the same dimension and range, which can be achieved by subtracting the mean from the original data and dividing by the standard deviation, or by mapping the data to the range of [0, 1].

[0033] The larger the positioning operation stability index and the larger the standby switching efficiency index, the larger the jointly generated operation determination coefficient, indicating that the power battery box positioning performs excellently in both the stability of the main module and the standby switching efficiency, and the overall reliability reaches a higher level. Specifically, a high positioning operation stability index value represents that the main positioning module (such as GPS) has a low failure rate, controllable accuracy decay, and stable data output during operation, and can maintain accurate monitoring for a long time; while a high standby switching efficiency index value reflects that the standby module (such as base station + IMU) responds quickly when the main module fails, has minimal function loss, and a high switching success rate, thus ensuring that the monitoring does not interrupt in extreme scenarios, can reduce the risk of out-of-control caused by sudden failures of the main module, and can minimize the positioning service interruption time through rapid switching, providing a full cycle for the safety management of the power battery box; The smaller the positioning operation stability index and the smaller the standby switching efficiency index, the smaller the generated operation determination coefficient, indicating that the overall reliability of the power battery box positioning faces serious risks, the stability of the main positioning module is insufficient (such as frequent failures, rapid accuracy decay, or high data abnormality rate), resulting in a significant decline in the quality of daily monitoring; at the same time, the switching efficiency of the standby module is low (such as long switching time, excessive function loss, or frequent switching failures), making the system unable to quickly restore effective positioning when the main module fails, leading to a sharp increase in the risk of positioning service interruption. The power battery box may completely lose monitoring in a complex environment, thus triggering safety hazards such as transportation path deviation, energy storage management out of control, or swapping operation accidents; Compare the generated operation determination coefficient with the pre-set positioning operation determination threshold to generate a positioning status monitoring stable signal and a positioning status monitoring abnormal signal; After obtaining the operation determination coefficient, compare the operation determination coefficient with the positioning operation determination threshold; If the operation determination coefficient is greater than or equal to the positioning operation determination threshold, at this time, generate a positioning status monitoring stable signal, indicating that the overall reliability of the power battery box in positioning is within the safe and controllable range, the main positioning module (such as GPS or UWB) operates stably, with low failure rate, controllable accuracy decay, and effective data output; at the same time, the standby module (such as base station positioning or inertial navigation) has a rapid switching response, the function loss meets expectations, and the historical switching success rate is high, and can continuously provide accurate position monitoring services for the battery box without immediate intervention. Continue to collect positioning data at the default frequency without increasing the self-check or alarm level; If the operation determination coefficient is less than the positioning operation determination threshold, generate a positioning status monitoring abnormal signal, indicating that the stability of the main module or the standby switching efficiency of the power battery box positioning system has fallen below the safety baseline, there is a risk of frequent failure of the main module, slow standby response, or both, which may cause the battery box to lose real-time monitoring in a complex environment, triggering safety hazards such as transportation path deviation, energy storage management out of control, or swapping operation accidents. It is necessary to immediately perform a positioning intervention operation to adjust the positioning strategy. The specific intervention and adjustment include: Check whether the environmental interference sources (such as electromagnetic fields, metal shielding) exceed the designed tolerance range: Restrict the movement or charging and discharging operations of the battery box, trigger an audible and visual alarm, and notify the operation and maintenance personnel to intervene; Enhance the image acquisition quality: Check the settings in aspects such as light source, exposure, and focus to ensure that the image acquisition process is not interfered with and improve the image clarity; Save the logs of the fault period (such as positioning interruption time, number of switching failures), generate an emergency work order, give priority to repairing the faulty module (such as replacing the antenna, adding positioning anchors), and conduct a preheating test on the standby module.

[0034] It should be noted that the threshold information related in this embodiment is set in advance by professionals and will not be explained in detail here. In the embodiment, there are some cases where the English letters of some parameters are the same, but different meanings are explained when they are used, and they will not be explained one by one here.

[0035] The present invention realizes high-precision calculation of the state of charge of the battery by fusing multi-modal data such as voltage, current, and temperature. Combining temperature compensation and open-circuit voltage curve correction significantly improves the reliability of power estimation; based on the motion state detection and variance analysis of the triaxial acceleration sensor, a multi-dimensional fusion vector of the state of charge, environmental risk, and motion state is constructed to realize intelligent adjustment of the dynamic geographical fence radius, expanding the monitoring range at high battery levels to match transportation needs and focusing on the core area at low battery levels to reduce power consumption; through the adaptive switching of positioning modes indoors and outdoors combined with the mobile event trigger mechanism; at the same time, real-time analyzing the positioning state information and generating a hierarchical response signal, forcibly activating redundant positioning in case of abnormal displacement or environmental risk to ensure uninterrupted safety monitoring, and improving the battery life of the power battery box while taking into account the full-cycle safety protection and ultra-low power operation of the power battery box.

[0036] The above formulas are all dimensionless and take their numerical calculations. The formulas are obtained by collecting a large amount of data for software simulation to obtain a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0037] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0038] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0039] In addition, in each embodiment of the present application, the functional modules can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0040] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims described above.

[0041] Finally: The above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A power battery box positioning monitoring method based on low power consumption application, characterized in that: The steps include: Determine the remaining battery capacity based on the collected data of voltage, current and temperature, and perform error correction based on temperature compensation and open circuit voltage curve to extract the state of charge characteristics; The motion state is detected by the three-axis acceleration sensor, and effective movement events are identified through gravity compensation and variance analysis, and a fusion vector is generated that integrates the charge state, environmental risk, and motion state. Dynamically adjust the fence radius according to the state of charge level, environmental risks and motion status, switch the positioning mode based on indoor and outdoor scenes, and trigger the positioning process activation when a motion event occurs; The operating status of the power battery box positioning process after activation is analyzed, the positioning status information generated during the operating status analysis is obtained, and different signals are generated according to the analysis of the positioning status information to adjust the positioning monitoring strategy.

2. According to claim 1, a power battery box positioning monitoring method based on low power consumption application is characterized in that: Determine the remaining battery capacity based on the collected data of voltage, current, and temperature. The specific steps are as follows: The total battery voltage and single cell voltage are collected through the voltage sensor, the charge and discharge current is collected through the current sensor, and the temperature near the power battery box is collected through the temperature sensor; The collected voltage and current signals are filtered using a sliding average filter to suppress high-frequency noise, and the temperature data is filtered using a median filter to eliminate transient interference. When the instantaneous jump in current exceeds three times the standard deviation of the historical mean, it is determined to be noise and interpolated and repaired; The remaining battery capacity is calculated by accumulating battery charge and discharge.

3. According to claim 2, a power battery box positioning monitoring method based on low power consumption application is characterized in that: The error correction is performed by combining temperature compensation and open circuit voltage curve to extract the state of charge characteristics. The specific steps include: Perform open circuit voltage curve fitting correction, let the battery stand for 2 hours after charging and discharging, so that the polarization voltage decays to a stable state, and construct a benchmark curve at 25°C. , and conduct experiments at -10℃, 0℃, 25℃, and 45℃ to establish a temperature-SOC-OCV three-dimensional lookup table; The OCV interpolation calculation expression is: ,in, is the temperature coefficient, which is determined by fitting the experimental data; Temperature compensation is performed and the effective capacity of the battery is obtained based on the Arrhenius equation model: ,in, is the battery activation energy, R is the ideal gas constant, To set a fixed temperature; Correct the state of charge according to the effective capacity: ; The corrected state of charge, voltage, current, and temperature are used as inputs for the dynamic geo-fencing strategy.

4. According to claim 3, a method for positioning and monitoring a power battery box based on low-power consumption application is characterized in that: The motion state is detected by the three-axis acceleration sensor, and effective movement events are identified through gravity compensation and variance analysis. The specific steps are as follows: When the acceleration sensor is stationary, it will continue to sense the gravity component, which needs to be removed through coordinate transformation: ,in, Install the tilt and elevation angles for the battery box; , , Respectively represent the acceleration components of the object in the x-axis, y-axis, and z-axis directions; Simplify the motion state identification and convert the three-axis acceleration into a scalar modulus: , mold length Reflects the overall movement intensity of the battery box. , , Respectively represent the motion acceleration of the three axes; Calculate the variance of the real-time acceleration modulus through the sliding window: , where N=10 is the window length, is the mean acceleration in the window; Set the discrimination threshold to determine motion events.

5. The method for positioning and monitoring a power battery box based on low-power consumption application according to claim 4 is characterized in that: Set the discrimination threshold to determine the motion event. The specific steps are as follows: Set a discrimination threshold, and if the duration of continuous movement meets the discrimination threshold, it will be judged as a valid movement event; After a valid movement event is confirmed, the positioning module is immediately awakened and the current location is obtained. If the location does not exceed the geographical fence range corresponding to the current state of charge, the positioning module is dormant and the status is recorded. When the boundary is crossed, an audible and visual alarm is activated, and the alarm information is uploaded to the cloud. If there is no movement event within the continuous movement time, turn off the positioning module and run the IMU at a frequency of 1Hz.

6. The method for positioning and monitoring a power battery box based on low-power consumption application according to claim 5 is characterized in that: And generate a fusion vector that integrates the charge state, environmental risk and motion state, including the following steps: The state of charge after the effective capacity correction is discretized into levels. When the state of charge after the effective capacity correction is greater than or equal to 80%, it is a high-level state. If it is less than 20%, it is a low-level state, indicating that it is close to a power shortage state, and the fence range must be forcibly reduced to ensure basic safety; The remaining states are intermediate states, which use a balanced strategy to balance security and power consumption; The environmental risk level is divided into high risk when the temperature is greater than 50℃, medium risk when the temperature is greater than 40℃ and less than or equal to 50℃, and safe in other cases; The state vector S=[SOC level, environmental risk level, motion state] is generated, where the environmental risk level includes three levels: high risk, medium risk and safe; the motion state includes moving and stationary states; and the SOC level includes high, medium and low states.

7. The method for positioning and monitoring a power battery box based on low-power consumption application according to claim 6 is characterized in that: The fence radius is dynamically adjusted according to the state of charge level, environmental risk, and motion status, and the positioning mode is switched in combination with indoor and outdoor scenes, including the following steps: Determine the high state of charge interval based on the battery discharge curve and calculate the fence base radius: ,in, , The theoretical maximum and minimum values ​​of the fence radius respectively; , represents the nonlinear coefficient; , They are the lower and upper limits of the state of charge range adjusted by the dynamic fence radius. is the actual state of charge value of the battery; In outdoor scenarios, the system dynamically selects a positioning strategy based on the battery state of charge: when the state of charge is at a high level greater than or equal to 80%, positioning is performed using the global positioning system and inertial measurement unit fusion positioning technology; When the state of charge is less than 80%, it switches to the combined mode of base station cellular identification and IMU dead reckoning; In indoor scenarios, if the power battery box is in motion, ultra-wideband and geomagnetic fingerprint matching technology is used to match the magnetic field characteristics through the pre-stored warehouse geomagnetic map combined with the dynamic time warping algorithm; if the battery box is stationary, the UWB and geomagnetic modules are turned off, and positioning is performed based on the IMU's accelerometer and gyroscope.

8. The method for positioning and monitoring a power battery box based on low-power consumption application according to claim 7 is characterized in that: When a mobile event occurs, the positioning process is triggered to activate, including the following steps: When the daily average power consumption of the GPS module for continuous positioning exceeds 50%, motion status detection is performed; Activate displacement-triggered positioning, perform gravity compensation and acceleration extraction: ,in, They represent the acceleration of the x, y, and z axes respectively, and g represents the acceleration due to gravity; The instantaneous trigger conditions for motion event identification are: ,in, is the preset acceleration threshold; When the trigger condition is met, the hardware is activated to switch positioning according to the positioning mode identifier.

9. The method for positioning and monitoring a power battery box based on low-power consumption application according to claim 8, characterized in that: Analyzing the running status of the power battery box positioning process after activation, and obtaining the positioning status information generated during the running status analysis process, including the following steps: Acquire the positioning status information generated in the process of analyzing the operation status after activation, wherein the positioning status information includes positioning operation information and switching use information; The positioning operation information includes the positioning operation stability index, and the switching use information includes the standby switching effectiveness index; The positioning operation stability index and the standby switching efficiency index are combined to generate an operation determination coefficient; The positioning operation stability index and the standby switching efficiency index are both positively correlated with the operation determination coefficient.

10. A method for positioning and monitoring a power battery box based on low power consumption application according to claim 9, characterized in that: According to the analysis of the positioning status information, different signals are generated to adjust the positioning monitoring strategy, including the following steps: Compare the operation determination coefficient with the positioning operation determination threshold; If the operation determination coefficient is greater than or equal to the positioning operation determination threshold, a positioning status monitoring stable signal is generated at this time, and no immediate intervention is required, and positioning data continues to be collected at the default frequency; If the operation determination coefficient is less than the positioning operation determination threshold, a positioning status monitoring abnormal signal is generated, and the positioning intervention operation is immediately performed to adjust the positioning strategy.

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