A positioning and monitoring method for power battery boxes based on low-power applications

Abstract

The present invention discloses a positioning and monitoring method for a power battery box based on low-power applications, which relates to the technical field of battery box positioning and monitoring and is used to solve the problem of high power consumption during the monitoring process of the power battery box. The present invention calculates the remaining battery power through voltage, current, and temperature data, constructs a highly reliable power characteristic by combining temperature compensation and open-circuit voltage correction, detects the motion state according to a three-axis acceleration sensor, generates a dynamic decision vector by integrating the state of charge, environmental risk, and movement events, intelligently adjusts the range of the geographical fence, expands the monitoring area when the battery power is high, and shrinks to the safe core area when the battery power is low. And based on indoor and outdoor scenarios, it automatically switches between global positioning or indoor positioning technology, reduces the energy consumption of ineffective positioning through a mobile trigger mechanism, analyzes the positioning state in real time and generates a hierarchical response signal, and enables redundant positioning in case of anomalies to ensure the continuity of monitoring, achieving a balance between the full-cycle safety protection and low-power operation of the power battery box and improving the endurance ability.

Description

Technical Field

[0001] The present invention relates to the technical field of power battery box monitoring and management, and more specifically, the present invention relates to a method for positioning and monitoring a power battery box 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 charge and discharge. In mild cases, it may lead to battery performance degradation, and in severe cases, 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 status 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 occur, lacking 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, there are the following solutions 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:

[0006] A method for positioning and monitoring a power battery box based on low-power applications, comprising the following steps:

[0007] 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;

[0008] Detect the motion state through a three-axis acceleration sensor, discriminate effective movement events through gravity compensation and variance analysis, and generate a fusion vector that combines the state of charge, environmental risks, and motion state;

[0009] 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;

[0010] Analyze the operating state after activating the positioning process of the power battery box, obtain the positioning status information generated during the analysis of the operating state, and generate different signals according to the analyzed positioning status information to adjust the positioning monitoring strategy.

[0011] In a preferred embodiment, determine the remaining battery charge based on the collected data of voltage, current, and temperature. The specific steps are as follows:

[0012] Collect the total battery voltage and cell voltage through a voltage sensor, collect the charge and discharge current using a current sensor, and collect the temperature near the power battery box using a temperature sensor;

[0013] Use a moving average filter for the collected voltage and current signals to suppress high-frequency noise, and use a median filter for the temperature data to eliminate transient interference. When the current instantaneous jump exceeds 3 times the standard deviation of the historical mean, it is determined as noise and interpolated for repair;

[0014] Calculate the remaining battery charge by accumulating the battery charge and discharge.

[0015] In a preferred embodiment, and perform error correction by combining temperature compensation and open-circuit voltage curve to extract the state-of-charge characteristics. The specific steps include:

[0016] Perform open-circuit voltage curve fitting and correction. 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 environment, construct a reference curve , and conduct experiments at -10°C, 0°C, 25°C, 45°C to establish a three-dimensional look-up table of temperature-SOC-OCV;

[0017] The OCV interpolation calculation expression is: , where is the temperature coefficient, determined by fitting experimental data;

[0018] Perform temperature compensation, and model the effective capacity of the battery based on the Arrhenius equation: , where is the battery activation energy, R is the ideal gas constant, is the set fixed temperature;

[0019] Correct the state of charge according to the effective capacity: ;

[0020] Use the corrected state of charge, voltage, current, and temperature as the input of the dynamic geofencing strategy.

[0021] In a preferred embodiment, detect the motion state according to a three-axis acceleration sensor, and distinguish effective movement events through gravity compensation and variance analysis. The specific steps are as follows:

[0022] When the acceleration sensor is at rest, it continuously senses the gravity component, which needs to be removed through coordinate transformation: , where is the installation tilt and elevation angles of the battery box; and and respectively represent the acceleration components of the object in the x-axis, y-axis, and z-axis directions;

[0023] To simplify the determination of the motion state, the three-axis acceleration is converted into a scalar magnitude: , and the magnitude reflects the overall motion intensity of the battery box, and and respectively represent the motion accelerations of the three axes;

[0024] 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;

[0025] Set a discrimination threshold to determine the movement event.

[0026] In a preferred embodiment, set a discrimination threshold to determine the movement event, and the specific steps are as follows:

[0027] Set a discrimination threshold. If the continuous movement duration meets the discrimination threshold determination condition, it is determined as a valid movement event;

[0028] 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 to sleep and record the status. When crossing the boundary, activate the audible and visual alarm and upload the alarm information to the cloud;

[0029] 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.

[0030] In a preferred embodiment, and generate a fusion vector that combines the state of charge, environmental risk, and motion state, including the following steps:

[0031] Perform hierarchical discretization determination on the state of charge corrected by the available capacity. When the state of charge corrected by the available capacity is greater than or equal to 80%, it is a high-level state;

[0032] If it is less than 20%, it is a low-level state, indicating that the battery is approaching the depleted state, and the fence range needs to be forced to be reduced to ensure basic safety;

[0033] The remaining states are medium-level states, and an equalization strategy is adopted to balance safety and power consumption;

[0034] Divide the environmental risk levels. When the temperature is greater than 50°C, it is a high-risk level. When the temperature is greater than 40°C and less than or equal to 50°C, it is a medium-risk level. In other cases, it is safe.

[0035] Generate a state vector S = [SOC level, environmental risk level, motion state]. Among them, the environmental risk level includes three levels: high-risk, medium-risk, and safe. The motion state includes moving and stationary states. The SOC level includes high, medium, and low states.

[0036] 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:

[0037] Determine the high state of charge interval according to the battery discharge curve display and calculate the basic fence radius: , where 、 Respectively, the theoretical maximum and minimum values of the fence radius; , representing the non-linear coefficient; 、 Respectively, the lower and upper limits of the state of charge interval for dynamic fence radius adjustment, is the actual state of charge value of the battery;

[0038] In the outdoor scenario, the system dynamically selects a positioning strategy according to the state of charge of the battery: When the state of charge is at a high level greater than or equal to 80%, use the integrated positioning technology of the global positioning system and the inertial measurement unit for positioning;

[0039] When the state of charge is less than 80%, switch to the combined mode of the base station cellular identifier and IMU dead reckoning;

[0040] In the indoor scenario, if the power battery box is in a moving state, adopt the ultra-wideband and geomagnetic fingerprint matching technology, and match the magnetic field characteristics by pre-storing the geomagnetic map of the warehouse and combining the dynamic time warping algorithm; if the battery box is stationary, turn off the UWB and geomagnetic modules and perform positioning according to the accelerometer and gyroscope of the IMU.

[0041] In a preferred embodiment, trigger the activation of the positioning process when a movement event occurs, including the following steps:

[0042] When the daily average power consumption ratio of the continuously positioned GPS module exceeds 50%, perform motion state detection;

[0043] Activate positioning by displacement trigger and perform gravity compensation and acceleration extraction: , where Respectively represent the accelerations of the x, y, and z axes, and g represents the acceleration due to gravity;

[0044] The instantaneous trigger conditions for motion event identification are: ,in, is the preset acceleration threshold;

[0045] When the trigger condition is met, the hardware is activated to switch positioning according to the positioning mode identifier.

[0046] 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:

[0047] 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;

[0048] The positioning operation information includes the positioning operation stability index, and the switching use information includes the standby switching effectiveness index;

[0049] The positioning operation stability index and the standby switching efficiency index are combined to generate an operation determination coefficient;

[0050] The positioning operation stability index and the standby switching efficiency index are both positively correlated with the operation determination coefficient.

[0051] In a preferred embodiment, the following steps are included to generate different signals according to the analysis of the positioning state information to adjust the positioning monitoring strategy:

[0052] Compare the operation determination coefficient with the positioning operation determination threshold;

[0053] 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;

[0054] 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.

[0055] The technical effects and advantages of the power battery box positioning monitoring method based on low power consumption application of the present invention are as follows:

[0056] 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 the triaxial 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 battery levels to match transportation needs, and focus on the core area at low battery levels to reduce power consumption; through the switching of positioning modes adapted to indoor and outdoor scenarios combined with a mobile event trigger mechanism; at the same time, real-time analyze the positioning status information and generate hierarchical response signals, and forcibly activate redundant positioning in case of abnormal displacement or environmental risk to ensure uninterrupted safety monitoring, while 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 FIG. is a schematic flow chart of a method for positioning and monitoring a power battery box based on low-power applications according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0058] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the 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 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.

[0059] To achieve the above object, Figure 1 a schematic structural diagram of a method for positioning and monitoring a power battery box based on low-power applications according to the present invention is given, which specifically includes the following steps;

[0060] 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;

[0061] Detect the motion state according to the triaxial acceleration sensor, discriminate effective movement events through gravity compensation and variance analysis, and generate a fusion vector that combines the state of charge, environmental risk, and motion state;

[0062] 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;

[0063] Analyze the operating state after the activation of the positioning process of the power battery box, obtain the positioning status information generated during the analysis of the operating state, and generate different signals according to the analyzed positioning status information to adjust the positioning monitoring strategy.

[0064] Step 1: Conduct 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 geofencing strategy. The specific steps are as follows:

[0065] The state of charge (SOC) of the power battery box is a 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 a high frequency, and through experimental calibration and physical model compensation, a state of charge value with an error ≤ 3% is finally output.

[0066] Collect the total battery voltage and single-cell 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 charging and discharging current I, where a positive value indicates charging and a negative value indicates discharging, and use a temperature sensor (such as DS18B20) to collect the temperature near the power battery box. At least 3 temperature measurement points (positive electrode, negative electrode, environment) are deployed, and the weighted average value is taken.

[0067] 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 < 10 ms), it is determined as noise and interpolated for repair.

[0068] Calculate the remaining battery power through the cumulative battery charging and discharging. The formula is as follows: , where is the initial state of charge, is the nominal battery capacity (such as 100 Ah), is the number of real-time charging and discharging current times, and t represent time, within the time interval from to t.

[0069] Conduct open-circuit voltage (OCV) curve fitting and correction. The specific steps are as follows:

[0070] After the battery charging and discharging are completed, let it stand for 2 hours to allow the polarization voltage to 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 temperature-SOC-OCV three-dimensional lookup table.

[0071] The OCV interpolation calculation expression is: , where is the temperature coefficient, obtained by fitting experimental data;

[0072] Perform temperature compensation on the effective capacity of the battery The effective capacity of the battery decays exponentially with the increase in temperature and can be modeled based on the Arrhenius equation: , where is the activation energy of the battery (experimentally calibrated value), R is the ideal gas constant, is the reference temperature, which is set to 25 degrees Celsius in this example;

[0073] Correct the state of charge according to the effective capacity: ;

[0074] In summary, the voltage, current, and temperature are corrected collaboratively as, avoiding the SOC deviation caused by the error of a single sensor, thereby providing high-precision input for the dynamic geofencing strategy.

[0075] During the low-power positioning and monitoring process 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, there may be 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:

[0076] 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 triaxial acceleration sensor (IMU);

[0077] 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 angle of the battery box, which is 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 , , ;

[0078] Simplify the motion state discrimination and convert the triaxial acceleration to a scalar modulus: , and the modulus reflects the overall motion intensity of the battery box;

[0079] The variance of the acceleration modulus characterizes the severity of the 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 noise resistance, is the average acceleration within the window;

[0080] Set the discrimination threshold (corresponding to the scenario of the vehicle driving at a constant speed or with slight bumps), determine the severity level. 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;

[0081] After the movement event is confirmed, immediately wake up the positioning module (GPS / base station) and obtain the current location. If the location 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;

[0082] If there is no movement event during the 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.

[0083] The state of charge after correcting the effective capacity Perform 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;

[0084] Similarly, divide the environmental risk level. When the temperature is greater than 50 °C, it is a high-risk level. When the temperature is greater than 40 °C and less than or equal to 50 °C, it is a medium-risk level. In other cases, it is safe;

[0085] Generate the state vector S = [SOC level, environmental risk level, motion state]. Among them, the environmental risk level has three levels: high-risk level, medium-risk level, and safe. The motion state has 2 states (moving / still), and the SOC level has 3 states (high / medium / low).

[0086] 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 the balance between low power consumption and safety monitoring. The specific steps are as follows:

[0087] 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). Thus, when the battery is at high power, a large range and high-precision monitoring are required; when the power is low, 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 failures caused by signal blind spots, and the data transmission frequency should be dynamically adjusted according to the power and motion state to reduce redundant communication energy consumption;

[0088] The fixed fence radius cannot cover the transportation path at high power, and it wastes energy due to the excessive range at low power. Dynamically adjust the radius according to the state of charge level, environmental risk, and motion state. The specific steps are as follows:

[0089] According to the battery discharge curve, in the high state of charge interval (80% - 100%), the power utilization rate is high, and it is necessary to expand the monitoring range to match the transportation demand. Calculate the basic radius: , where 、 are the theoretical maximum and minimum values of the fence radius respectively, , 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;

[0090] A single positioning mode cannot adapt to complex scenarios (such as urban canyons, indoor warehouses). Select the optimal positioning combination according to SOC, environmental risk, motion state, and signal strength. The specific details are as follows:

[0091] Discriminate indoor and outdoor scenarios through the GPS signal strength threshold. When the GPS signal strength is -145 dBm, it is judged as outdoor, otherwise it is indoor;

[0092] 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%), adopt the integrated positioning technology of the Global Positioning System (GPS) and Inertial Measurement Unit (IMU). Assign 70% weight to the GPS data through the Kalman filter algorithm, and combine the short-term motion compensation of the IMU to achieve high-precision positioning of ≤5 meters. Although the power consumption is high, it can meet the wide-area monitoring requirements; when the SOC drops to medium and low power (<80%), switch to the combined 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;

[0093] 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.

[0094] 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 states.

[0095] Fixed-frequency communication may miss key events at high battery levels and prematurely deplete energy due to frequent transmissions at low battery levels. 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.

[0096] In the indoor-outdoor transition area (such as the warehouse entrance), positioning jumps are likely to occur due to signal mutations, and smooth switching needs to be achieved 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).

[0097] 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 through multi-dimensional parameter optimization while ensuring safety.

[0098] Step 3, execute the energy consumption optimization strategy according to event-driven, and the specific steps are as follows:

[0099] 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;

[0100] Continuous positioning (such as updating every second) causes the daily power consumption ratio of the GPS module to exceed 50%. It is necessary to detect the motion state and only activate the positioning when the battery box is moving to reduce the ineffective energy consumption;

[0101] Perform displacement-triggered positioning activation, gravity compensation, and acceleration extraction: , where respectively represent the accelerations of the x, y, and z axes, and g represents the acceleration due to gravity;

[0102] The instantaneous trigger condition for mobile event discrimination is: , where is a preset acceleration threshold, ;

[0103] After the trigger condition is satisfied, the corresponding hardware is activated according to the positioning mode identifier (GPS / base station / UWB).

[0104] 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 monitors the operating status of the positioning process in real time (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), and quantitatively evaluates the fault tolerance ability and response speed of the system. 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 the analysis of the standby module switching efficiency can expose the deficiencies of 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;

[0105] Analyze the operating status of the power battery box positioning process after activation, obtain the positioning status information generated during the analysis of the operating status after activation, and the positioning status information includes positioning operation information and switching usage information;

[0106] The positioning operation information includes a positioning operation stability index calibrated as PSI, and the switching usage information includes a standby switching efficiency index calibrated as RSEI;

[0107] 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 work continuously and stably 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 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;

[0108] 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 is frequently interrupted due to signal blocking or hardware aging, the positioning operation stability index will drop significantly, prompting the operation and maintenance personnel to check the antenna connection or replace damaged parts in time. By tracking the index changes over a long period of time, the module service life can be predicted to avoid sudden failures affecting the overall monitoring effect.

[0109] For example, when logistics vehicles transport power battery boxes across regions, the positioning module needs to adapt to various environments such as mountainous areas, tunnels, and urban canyons. When the vehicle enters a tunnel and causes the satellite signal to be 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 continues to be lower than the safety threshold, the system automatically enables the inertial navigation module to take over temporarily and notifies the dispatch center to adjust the route to avoid the battery box losing monitoring in the signal blind area.

[0110] The logic for obtaining the positioning operation stability index is as follows:

[0111] The total duration of the main positioning module failing to work normally due to signal loss or hardware failure during the statistical period is the cumulative failure duration. , Get the total working time of the main positioning module from activation to the current moment as the total running time , get the initial accuracy after activation And periodically collect the current accuracy , the calculated attenuation is: ;

[0112] Get the original coordinate data The amount of valid positioning data after filtering outliers , the positioning operation stability index is calculated, and the formula is as follows: ;

[0113] It should be noted that the cumulative fault duration is the module fault events recorded in the system log (such as GPS satellite loss, UWB disconnection), and the start and end timestamps of all fault events are extracted from the log; periodic collection can be set to every hour, every day, etc.; the filtering rules for the effective positioning data volume can be to exclude data points that exceed the preset fence range or if the displacement of two adjacent positioning exceeds the physical limit (such as moving 200 meters within 1 second), it is judged as abnormal jump and data points with discontinuous or disordered timestamps are regarded as invalid data points.

[0114] The standby switching efficiency index is used to measure the switching efficiency and function retention ability of the standby module after the main positioning module fails in the positioning of the power battery box. The standby switching efficiency index comprehensively evaluates the switching speed, the degree of accuracy loss, and the switching success rate, and comprehensively reflects the emergency response ability of the system under sudden failures or environmental disturbances. 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 redundancy strategies, so as to ensure continuous and reliable monitoring of the power battery box in all-weather and full-scenario conditions;

[0115] When the main positioning module fails due to signal loss, hardware failure, or environmental interference, the standby module needs to quickly take over the positioning task. The standby switching efficiency index can quantify the total time from the failure of the main module to the successful activation of the standby module and the output of the effective position. For example, when a logistics vehicle passes through a tunnel and causes satellite positioning interruption, if the standby base station positioning module completes the switching within 5 seconds, the index will reflect its high efficiency; if the switching time exceeds 30 seconds, the index will drop significantly, indicating that the warm-up process or communication protocol needs to be optimized;

[0116] In multiple main-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, in a battery swapping station, due to severe metal shielding, the switching success rate of the base station positioning module is only 60%. The continuously low index can prompt to add indoor positioning anchors or switch to a geomagnetic matching scheme with stronger anti-interference ability;

[0117] For example, when a vehicle enters a long tunnel and the satellite positioning signal is completely lost, at this time, it is judged whether to forcibly switch to the inertial navigation module (such as gyroscope + accelerometer) according to the standby switching efficiency index. If the index shows that the switching time is short and the accuracy loss is controllable, the current strategy is maintained; if the index remains low, the driver is prompted to slow down or start the manual takeover mode to avoid the battery box getting out of control in the blind area

[0118] The acquisition logic of the standby switching efficiency index is as follows:

[0119] Obtain the total time from the failure of the main positioning module to the first output of the effective position by the standby module , obtain the average positioning accuracy before the failure of the main module and the average positioning accuracy after the standby module switches , calculate the loss ratio of the positioning accuracy relative to the main module as the function loss value, and the calculation expression is: , obtain the upper limit value of the allowable function loss , obtain the number of times the standby module completes effective positioning per unit time and the total number of switches , calculate the standby switching efficiency index, and the calculation expression is: .

[0120] 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.

[0121] 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 the preset proportional coefficient of the positioning operation stability index and the standby switching efficiency index, and , Both are greater than 0.

[0122] The specific method of jointly generating the operation determination coefficient may involve multiple algorithms and models, which depends on the actual situation and application requirements. In this embodiment, a 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 a comprehensive evaluation of the overall reliability of the activated power battery box positioning system, and is used to determine the final operating status.

[0123] It should be noted that the size of the preset proportional coefficient is a specific value obtained by quantifying each parameter. In order to facilitate subsequent comparison, the size of the coefficient depends on the amount of sample data and the preset proportional coefficient initially set by technical personnel in this field for each group of sample data. It is not unique, as long as it does not affect the proportional relationship between the parameter and the quantized value. For example, the positioning operation stability index is proportional to the operation determination coefficient. The positioning operation stability index and the standby switching efficiency index are normalized to have the same dimension and range. This can be achieved by subtracting the mean from the original data and dividing it by the standard deviation, or mapping the data to the range of [0, 1].

[0124] The larger the positioning operation stability index and the larger the backup switching efficiency index, the larger the jointly generated operation determination coefficient, indicating that the power battery box positioning has excellent performance in both main module stability and backup switching efficiency, and the overall reliability has reached a higher level. Specifically, a high positioning operation stability index value means that the main positioning module (such as GPS) has a low failure rate, controllable accuracy attenuation, and stable data output during operation, and can maintain accurate monitoring for a long time; while a high backup switching efficiency index value reflects that the backup module (such as base station + IMU) responds quickly when the main module fails, with minimal functional loss and a high switching success rate, thereby ensuring uninterrupted monitoring in extreme scenarios, which can not only reduce the risk of loss of control caused by sudden failure of the main module, but also minimize the interruption time of positioning services through rapid switching, providing a full cycle for the safety management of the power battery box;

[0125] The smaller the positioning operation stability index and the backup switching efficiency index, the smaller the jointly generated operation determination coefficient, indicating that the overall reliability of the power battery box positioning is facing serious risks. The main positioning module is not stable enough (such as frequent failures, rapid attenuation of accuracy or high data anomaly rate), resulting in a significant decline in the quality of daily monitoring. At the same time, the backup module switching efficiency is low (such as long switching time, excessive functional loss or frequent switching failures), making it impossible for the system to quickly restore effective positioning when the main module fails, resulting in a surge in the risk of positioning service interruption. The power battery box may completely lose monitoring in a complex environment, which in turn leads to safety hazards such as transportation path deviation, out-of-control energy storage management or battery replacement operation accidents.

[0126] Compare the generated operation determination coefficient with the preset positioning operation determination threshold to generate a positioning state monitoring stable signal and a positioning state monitoring abnormal signal;

[0127] After obtaining the operation determination coefficient, compare the operation determination coefficient with the positioning operation determination threshold;

[0128] If the operation determination coefficient is greater than or equal to the positioning operation determination threshold, a positioning status monitoring stable signal is generated, indicating that the overall reliability of the power battery box in positioning is within a safe and controllable range, and the main positioning module (such as GPS or UWB) operates stably, with a low failure rate, controllable accuracy attenuation, and valid data output; at the same time, the backup module (such as base station positioning or inertial navigation) has a fast switching response, expected functional loss, and a high historical switching success rate, and can continue to provide accurate location monitoring services for the battery box without immediate intervention, and continues to collect positioning data at the default frequency without increasing the self-test or alarm level;

[0129] If the running determination coefficient is less than the positioning running determination threshold, a positioning status monitoring abnormal signal is generated, 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, and 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, leading to 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 and adjust the positioning strategy. The specific intervention and adjustment include:

[0130] Check whether the environmental interference sources (such as electromagnetic fields, metal shielding) exceed the design tolerance range:

[0131] Restrict the movement or charge and discharge operations of the battery box, trigger an audible and visual alarm, and notify the operation and maintenance personnel to intervene;

[0132] 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;

[0133] 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 anchor points), and conduct a preheating test on the standby module.

[0134] It should be noted that the threshold information related in this embodiment is pre-set by professionals and will not be explained in detail here. In the embodiment, some parameter English letters are the same, but different meanings are explained during use, and they will not be explained one by one here.

[0135] The present invention realizes the high-precision calculation of the state of charge of the battery by fusing multi-modal data such as voltage, current, and temperature, combines temperature compensation and open-circuit voltage curve correction, and significantly improves the reliability of the state of charge estimation; based on the motion state detection and variance analysis of the triaxial acceleration sensor, constructs a multi-dimensional fusion vector of the state of charge, environmental risk, and motion state, and realizes the intelligent adjustment of the dynamic geographical fence radius, expands the monitoring range at high state of charge to match the transportation demand, and focuses on the core area at low state of charge to reduce power consumption; through the indoor and outdoor scene adaptive positioning mode switching combined with the mobile event trigger mechanism; at the same time, real-time analyzes the positioning state information and generates a hierarchical response signal, and forcibly activates redundant positioning in case of abnormal displacement or environmental risk to ensure that the safety monitoring is not interrupted, taking into account the full-cycle safety protection and ultra-low power consumption operation of the power battery box, and improving the battery life of the power battery box.

[0136] 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 get a formula closest to the real situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0137] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0138] 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 a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician 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.

[0139] In addition, each functional module in the various embodiments of this application 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.

[0140] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0141] 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 should all be included within the protection scope of the present invention.

Claims

1. A positioning and monitoring method for a power battery box based on low-power applications, characterized in that: It includes 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 through a three-axis 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; 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. The specific steps include: Collect the total battery voltage and single-cell voltage through a voltage sensor, collect the charge and discharge current through a current sensor, and collect the temperature near the power battery box through a temperature sensor; Use a moving average filter to suppress high-frequency noise for the collected voltage and current signals, use a median filter for temperature data to eliminate transient interference, and determine it as noise and perform interpolation repair when the instantaneous jump of the current exceeds 3 times the standard deviation of the historical mean; Calculate the remaining battery power by accumulating the battery charge and discharge; Perform open-circuit voltage curve fitting and correction. 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. Under a 25°C environment, construct a reference curve , and conduct experiments at -10°C, 0°C, 25°C, and 45°C to establish a three-dimensional look-up table of temperature-SOC-OCV; The OCV interpolation calculation expression is as follows: , where is the temperature coefficient, which is determined by fitting experimental data; Perform temperature compensation and model the effective capacity of the battery 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 based on the available capacity: ; Use the corrected state of charge, voltage, current, and temperature as the input of the dynamic geofence strategy; And 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 effective capacity. When the state of charge after correcting the effective 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 equilibrium strategy is adopted to balance safety and power consumption; Divide the environmental risk level. When the temperature is greater than 50°C, it is a high-risk situation. When the temperature is greater than 40°C and less than or equal to 50°C, it is a medium-risk situation. Otherwise, it is safe; Generate a state vector S = [SOC level, environmental risk level, motion state]. Among them, the environmental risk level includes three levels: high-risk, medium-risk, and safe. The motion state includes moving and stationary states. The SOC level includes high, medium, and low states.

2. The positioning and monitoring method of a power battery box based on low-power applications according to claim 1, wherein: Detect the motion state through a three-axis acceleration sensor, and distinguish valid movement events through gravity compensation and variance analysis. The specific steps are as follows: When the acceleration sensor is at rest, it continuously senses the gravity component, which needs to be removed through coordinate transformation: , where is the installation pitch and roll angles of the battery box; , , respectively represent the acceleration components of the object in the x-axis, y-axis, and z-axis directions; Simplify the determination of the motion state, and convert the three-axis acceleration into a scalar magnitude: , the magnitude reflects 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.

3. A positioning and monitoring method for a power battery box based on low-power applications according to claim 2, characterized in that: Set a discrimination threshold to determine the movement event. The specific steps are as follows: Set a discrimination threshold. If the detected continuous movement duration meets the discrimination threshold determination condition, it is determined as a valid movement event; After confirming the valid movement event, 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, sleep the positioning module and record the state. 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 time, turn off the positioning module and run the IMU at a frequency of 1Hz.

4. A positioning and monitoring method for a power battery box based on low-power applications according to claim 3, 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 according to the battery discharge curve display, and calculate the radius of the fence foundation: , where and are the theoretical maximum and minimum values of the fence radius respectively; , representing the non-linear coefficient; and are the lower limit and upper limit of the state of charge interval for dynamic fence radius adjustment respectively, 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.

5. A positioning and monitoring method for a power battery box based on low-power applications according to claim 4, 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; Perform displacement-triggered positioning activation, gravity compensation, and acceleration extraction: , where respectively represent the accelerations along the x, y, and z axes, and g represents the acceleration due to gravity; The instantaneous trigger condition for mobile event discrimination is: , where is a preset acceleration threshold; When the trigger condition is met, the hardware is activated to switch positioning according to the positioning mode identifier.

6. The positioning and monitoring method of a power battery box based on low-power applications according to claim 5, wherein: 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.

7. A positioning and monitoring method for a power battery box based on low-power applications according to claim 6, 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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