Internet of things based intelligent monitoring method and system for automobile emergency starting power supply

Abstract

The application provides an automobile emergency starting power supply intelligent monitoring method based on the Internet of Things, which comprises the following steps: acquiring the phased response data of a battery pack in low-energy self-checking; calculating the short-time load pressure drop, the sustained load pressure drop and the recovery pressure drop according to the phased response data; combining the corresponding test temperature conditions, the instantaneous pressure drop state, the sustained load state, the recovery state, the weakest monomer state, the weakest monomer position and the test phase into a starting response state; selecting and determining an effective starting margin according to the starting response state; determining the highest level with the effective starting margin greater than zero as the current allowable starting level, and determining the state with the smallest residual proportion in the level with the effective starting margin not greater than zero as the limiting reason; inputting the current allowable starting level and the limiting reason into a preset starting permission determination rule, and finally controlling the starting output loop according to the starting permission state. The application improves the state knowability and starting reliability of the automobile emergency starting power supply before the actual emergency use.

Description

Technical Field

[0001] This invention belongs to the field of automotive emergency jump starters, and particularly relates to an intelligent monitoring method and system for automotive emergency jump starters based on the Internet of Things. Background Technology

[0002] Automotive emergency jump starters are portable power devices that provide short-term, high-current auxiliary starting when a vehicle's battery is depleted, its performance deteriorates at low temperatures, or it fails to start the starter motor properly. Their usage differs significantly from ordinary power batteries and energy storage batteries. These devices are mostly stored or in standby mode, but when a vehicle needs to be started, they must provide an instantaneous output capacity far exceeding daily load for a short period. Therefore, for automotive emergency jump starters, simply confirming sufficient remaining charge does not equate to confirming reliable vehicle starting capability. Existing products typically utilize battery management systems to collect parameters such as battery pack voltage, individual cell voltage, current, and temperature, and use preset thresholds to determine states such as undervoltage, overcurrent, overtemperature, and individual cell abnormalities. Some networked products also upload device status to a server for remote viewing and maintenance reminders. Existing battery testing technologies can also evaluate voltage changes under load by applying pulses or measuring internal resistance. Furthermore, during product development and factory verification, high-power load devices can be used to directly conduct high-rate output tests to verify whether the product can achieve its designed starting level. These technologies can address issues related to daily status monitoring, low-load characteristic testing, and performance verification during the R&D phase. However, significant gaps remain in their application during long-term idle periods. Emergency start-up power supplies may retain a normal static voltage after months of storage, but the cell's load-bearing characteristics, continuous output capability, or consistency of individual cells in a series may have changed. This can lead to rapid voltage drops, insufficient continuous driving capacity, or premature reaching of limits by certain cells when actually connected to a vehicle. Direct verification through periodic high-rate discharge would consume the reserve energy intended for emergency starting and increase the testing burden, making it unsuitable for long-term online implementation. A single low-current pulse test typically only yields a single voltage drop or equivalent internal resistance, failing to simultaneously describe the instantaneous response upon load connection, subsequent changes after load sustainment, recovery after load removal, and premature deviation of weaker cells during load application. Furthermore, it's difficult to determine the actual starting level corresponding to these low-energy test results. Therefore, what existing technologies truly lack is a stable correlation between real high-rate capability verification during the R&D phase and low-energy online detection during the usage phase. Because the R&D verification phase can confirm the actual start-up level under different conditions through real high-rate tests, while the usage phase can obtain the battery's dynamic response with lower energy.

[0003] Therefore, if the same low-energy testing process and the same dynamic state expression are used in the R&D phase and the actual use phase, and the judgment boundary corresponding to each real start-up level is established in advance, the on-site dynamic response after long-term idleness can be used to determine the actual start-up level that the device can currently achieve. Furthermore, this level can be directly used for start-up permission management and IoT status monitoring, thereby solving the problem that it is difficult to confirm the real start-up capability of long-term idle devices online. Summary of the Invention

[0004] The purpose of this invention is to propose an intelligent monitoring method and system for automotive emergency jump starters based on the Internet of Things (IoT) to solve the above-mentioned problems.

[0005] To achieve the above objectives, a first aspect of the present invention provides an intelligent monitoring method for automotive emergency jump starters based on the Internet of Things, the method comprising the following steps: S1. Obtain the phased response data of the battery pack during the low-energy self-test; the phased response data includes sampling records of the static reference, short-term load, continuous load and load removal recovery stages, and each sampling record includes the test stage, sampling order, battery pack voltage, individual cell voltage, actual test current and battery temperature. The phased response data is obtained by sequentially forming static baseline, short-term load, continuous load, and unload recovery when the battery pack meets the self-test allowable conditions. S2. Calculate the short-time load voltage drop, continuous load voltage drop, and recovery voltage drop based on the phased response data, and determine the instantaneous voltage drop state, continuous load state, and recovery state respectively; calculate the corresponding phase deviation based on the voltage of each individual cell in the series, take the maximum deviation as the weakest cell state, and record the position of the weakest cell and the corresponding test stage. The corresponding test temperature conditions, instantaneous pressure drop state, continuous load state, recovery state, weakest single-cell state, weakest single-cell location, and test phase are combined into a start-up response state. S3. Select and determine the effective startup margin based on the startup response status; and determine the highest level with the effective startup margin greater than zero as the current allowed startup level, and determine the restriction reason from the level with the smallest remaining proportion among the levels with the first effective startup margin not greater than zero. S4. Input the current allowed startup level and the reason for restriction into the preset startup permission determination rule, and output the startup permission status in combination with the rated startup level and the lowest available startup level. Finally, control the startup output circuit according to the startup permission status.

[0006] Preferably, the testing phase includes a static reference, a short-term load, a continuous load, and a load removal and recovery phase; The static reference is formed in the following way: after the battery pack meets the self-test allowable conditions, the test branch is kept disconnected, and the battery pack voltage and the voltage of each cell are continuously collected; when the continuous sampling results are kept within the preset fluctuation range, the subsequent continuous sampling records are taken as the static reference.

[0007] Preferably, the self-test parameters of the self-test allowable conditions include at least the self-test allowable voltage range, the self-test allowable temperature range, the sampling period, the static stability fluctuation range, the test current allowable range, and the test termination conditions. Then, the battery pack meets the self-test allowable conditions, including: comparing the battery pack voltage, minimum single cell voltage and battery temperature with the self-test allowable conditions preset for the current product model. If all items are within the corresponding allowable range, it is determined that the self-test allowable conditions are met and the test preparation state is entered.

[0008] Preferably, the instantaneous voltage drop state is determined as follows: taking the reference voltage obtained at the end of the static reference stage before loading as a reference, taking the average value of continuous voltage sampling after the test current stabilizes in the later part of the short-time load stage as the representative voltage of the short-time load, and determining the difference between the reference voltage before loading and the representative voltage of the short-time load as the instantaneous voltage drop state. The method for determining the continuous load state is as follows: taking the short-time load representative voltage as the starting point, taking the average value of continuous sampling at the end of the continuous load stage as the continuous load representative voltage, and determining the continuous load state by the difference between the short-time load representative voltage and the continuous load representative voltage. The recovery state is determined as follows: the average result of continuous sampling at the end of the recovery observation phase is read as the representative voltage at the end of the recovery phase, and the remaining difference between the reference voltage before loading and the representative voltage at the end of the recovery phase is determined as the recovery state; when the representative voltage at the end of the recovery phase has reached or exceeded the reference voltage before loading, the recovery state is recorded as zero.

[0009] Preferably, the reference voltage before loading is determined by obtaining the reference voltage of the battery pack and the reference voltage of each cell before loading from the continuous sampling at the end of the static reference stage, and determining the average result of the continuous temperature sampling at the end of the static reference stage as the temperature condition for this test.

[0010] Preferably, the step of calculating the corresponding stage deviation based on the voltage of each individual cell, taking the maximum deviation as the weakest cell state, and recording the position of the weakest cell and the corresponding test stage is as follows: For each individual unit, calculate its deviation from the intermediate level of dynamic changes of all units in the same stage during the short-term loading stage, continuous loading stage, and unloading recovery stage. Take the maximum value of the deviation of the corresponding unit in each stage as the degree of dynamic weakening of that unit. Then, select the weakest monomer state from all monomers with the maximum dynamic weakening degree, and record the position of the monomer and its corresponding test stage.

[0011] Preferably, the step of selecting and determining the effective startup margin based on the startup response state includes: Based on the corresponding test temperature conditions, select the start-up capability judgment boundary group for the corresponding temperature range. For each temperature range, set multiple candidate start-up levels from low to high. The start-up capability judgment boundary group includes multiple candidate start-up levels arranged from low to high. Each candidate start-up level corresponds to the instantaneous pressure drop boundary, continuous load boundary, recovery boundary, and weakest single-cell boundary. Starting from the lowest candidate start-up level, the instantaneous pressure drop state, continuous load state, recovery state, and weakest single-unit state are compared with the corresponding level boundary to obtain the remaining proportion of each state. The minimum value of the remaining proportion of each state is taken, and the boundary contraction amount of the corresponding candidate start-up level is subtracted to obtain the effective start-up margin. Among them, when the current state is within the allowable region, the current remaining proportion is positive; when it just reaches the boundary, it is zero; and when it exceeds the boundary, it is negative.

[0012] Preferably, determining the highest level where the effective startup margin is greater than zero as the currently allowed startup level includes: The effective startup margin is calculated sequentially from low to high according to the candidate startup levels. When the effective startup margin reaches zero or is lower than zero for the first time, the level is stopped from being increased, and the previous level with an effective startup margin greater than zero is determined as the current allowed startup level. If the lowest candidate startup level has an effective startup margin of zero or lower than zero, the current allowed startup level is recorded as lower than the lowest available startup level, and startup is prohibited. The reason for the limitation is determined by the state with the smallest remaining proportion among the levels where the initial effective start margin is not greater than zero, including: When the effective start margin is less than or equal to zero for the first time, the state with the smallest remaining proportion in the corresponding candidate start level is determined as the limiting cause; among them, the instantaneous voltage drop state corresponds to the instantaneous voltage drop limit, the continuous load state corresponds to the continuous load limit, the recovery state corresponds to the recovery limit, and the weakest cell state corresponds to the weakest cell limit. When the weakest cell limit is applied, the location of the weakest cell and the corresponding test stage are added.

[0013] Preferably, the preset startup permission determination rule includes: Based on a comparison between the currently allowed startup level and the two fixed levels mentioned above: A normal startup permission is granted when the current allowed startup level reaches the rated startup level. A downgraded start permission is granted when the current permitted start level is lower than the rated start level but still reaches the minimum available start level. A boot-prohibited state is created when the current allowed boot level is lower than the minimum available boot level. The control of the startup output circuit based on the startup permission status includes: When the current allowed start level reaches the rated start level, a normal start permission is granted and the start output circuit is enabled. When the current allowed start level is lower than the rated start level but not lower than the minimum available start level, a downgrade start permission is granted, and the start output circuit is enabled only when the target start level is not higher than the current allowed start level. When the current allowed start level is lower than the minimum available start level, a start-prohibited state is established and the start output circuit is disabled.

[0014] A second aspect of the invention provides an Internet of Things-based intelligent monitoring system for automotive emergency jump starters, the system comprising: The phased self-test execution module is used to acquire phased response data of the battery pack during low-energy self-test. The phased response data includes sampling records of the static reference, short-term load, continuous load and load removal recovery stages. Each sampling record includes the test stage, sampling order, battery pack voltage, individual cell voltage, actual test current and battery temperature. The phased response data is obtained by sequentially forming static baseline, short-term load, continuous load, and unload recovery when the battery pack meets the self-test allowable conditions. The response state determination module is used to calculate the short-time load voltage drop, continuous load voltage drop, and recovery voltage drop based on the phased response data, and determine the instantaneous voltage drop state, continuous load state, and recovery state respectively; calculate the corresponding stage deviation based on the voltage of each individual cell, take the maximum deviation as the weakest cell state, and record the position of the weakest cell and the corresponding test stage. The corresponding test temperature conditions, instantaneous pressure drop state, continuous load state, recovery state, weakest single-cell state, weakest single-cell location, and test phase are combined into a start-up response state. The startup level determination module is used to select and determine the effective startup margin based on the startup response status; and to determine the highest level with the effective startup margin greater than zero as the current allowed startup level, and to determine the restriction reason based on the state with the smallest remaining proportion among the levels with the first effective startup margin not greater than zero. The startup permission and IoT communication module is used to input the current allowed startup level and the reason for restriction into the preset startup permission judgment rule, and output the startup permission status in combination with the rated startup level and the lowest available startup level, and finally control the startup output loop according to the startup permission status.

[0015] The beneficial technical effects of the present invention are at least as follows: This invention addresses the problem of difficulty in confirming the actual starting capability of automotive emergency jump starters after long-term idleness with low testing costs. It further refines the monitoring target from static power or general health status to the current permissible starting level, and establishes a continuous technical relationship from low-energy dynamic detection to actual starting capability determination and starting permission processing.

[0016] When the equipment meets self-test conditions, it forms a continuous static, short-term load, continuous load, and unload recovery process through controlled test branches. From the same test, it obtains response information reflecting instantaneous load-bearing capacity, continuous output maintenance capacity, post-load recovery characteristics, and weak individual unit dynamic differences, and forms a startup response state according to a unified processing method. During the product development and verification phase, real high-rate load tests confirm the actual startup levels that can be stably achieved under different conditions. Simultaneously, low-energy testing and state formation methods consistent with actual operation are used to establish fixed judgment boundaries corresponding to each startup level, ensuring that the field response after long-term idleness directly corresponds to the level boundaries verified by real high-rate testing. During equipment operation, the current allowed startup level is determined based on the matching results between the current startup response state and different level judgment boundaries. Simultaneously, the reasons preventing the equipment from entering a higher startup level are determined, and the current allowed startup level is directly converted to a normal startup permission, downgraded startup permission, or prohibited startup state. At the same time, the current allowed startup level, the reason for the restriction, and the startup permission status are sent to a remote terminal via IoT communication. Therefore, this invention establishes a direct correspondence between the real high-rate capability verification that can be implemented in the R&D phase but is not suitable for frequent online execution and the low-energy dynamic self-test that can be implemented for a long time in the operation phase. This enables the emergency jump starter to determine its current actual starting capability even when no real vehicle starts have occurred for a long time, and allows the monitoring results to directly affect the starting output authority, thereby improving the knowability of the status and starting reliability of the automotive emergency jump starter before actual emergency use. Attached Figure Description

[0017] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0018] Figure 1 This is a flowchart of an embodiment of the intelligent monitoring method for automotive emergency jump starters based on the Internet of Things (IoT).

[0019] Figure 2 This is a framework diagram of an IoT-based intelligent monitoring system for automotive emergency jump starters, as described in an embodiment of the present invention. Detailed Implementation

[0020] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0021] like Figure 1 As shown in the figure, the intelligent monitoring method for automotive emergency jump starters based on the Internet of Things provided in this embodiment of the invention includes: S1. Obtain the phased response data of the battery pack during the low-energy self-test; the phased response data includes sampling records of the static reference, short-term load, continuous load and load removal recovery stages, and each sampling record includes the test stage, sampling order, battery pack voltage, individual cell voltage, actual test current and battery temperature. The phased response data is obtained by sequentially forming static baseline, short-term load, continuous load, and unload recovery data when the battery pack meets the self-test allowable conditions.

[0022] Specifically, the controller reads the current battery pack voltage, individual cell voltage, and battery temperature, and calls the pre-set self-test parameters for the corresponding product model.

[0023] The self-test parameters include at least the self-test allowable voltage range, self-test allowable temperature range, sampling period, static stability fluctuation range, test current allowable range, and test termination conditions. These parameters are written into the controller after being adjusted by the safe operating range of the battery cell model, the rated output capacity of the starting power supply, the load-bearing capacity of the test branch, and the low-energy self-test test during the product development stage.

[0024] Furthermore, the battery pack voltage is obtained through a voltage sampling branch between the main positive and main negative terminals. The voltage of each individual cell is collected sequentially through the cell monitoring front-end in the battery management system. The battery temperature is obtained through a temperature sensor located inside the battery pack. The test current is obtained through a current sampling element set in the test branch and sent to the controller via a current detection circuit. The controller compares the current battery pack voltage, the lowest individual cell voltage, and the battery temperature with the self-test allowable conditions for the corresponding model. When all parameters are within the allowable range, the system enters the test preparation state.

[0025] Subsequently, the test branch is kept disconnected while the battery pack voltage and individual cell voltages are continuously collected to form a static reference immediately before the load is applied. The controller uses the changing trend of several consecutive sampling results to determine whether the static state is stable. When the continuous sampling results remain within a preset fluctuation range, the subsequent continuous sampling records are used as the pre-load reference for this test. Taking a specific model as an example, 20 sets of static samples can be continuously obtained before the test begins, and the last 5 stable samples are taken as the pre-load reference, so that the subsequent load-bearing stage directly corresponds to the actual static state in the same self-test.

[0026] Furthermore, after the static baseline is established, the controller drives the power switch in the test branch to conduct, causing the battery to undergo controlled discharge through a preset test load, and continuously enter the short-term load stage and the continuous load stage. This test load is determined by the product model, and the resulting test current is lower than the high-rate output current of a real vehicle startup, but should be able to create a distinguishable difference in voltage response between normal batteries and batteries with degraded capacity, and establish a correspondence with subsequent real high-rate load tests during the R&D phase. The short-term load stage focuses on collecting the battery pack voltage, individual cell voltages, actual test current, and battery temperature immediately after the load is connected, to preserve the rapid voltage change process. The continuous load stage keeps the same test branch continuously conducting and continues to collect the same data, to preserve whether the voltage continues to decrease after the initial voltage drop and whether the differences between individual cells further increase. The two load stages maintain the same electrical connection, allowing for continuous observation of the instantaneous and continuous responses under the same load. In actual implementation, several sets of high-density samples can be continuously obtained during the short-term load stage, and then continuous sampling can be obtained over a longer time range during the continuous load stage.

[0027] In a specific implementation, for example, 10 initial load samples can be recorded during the short-term load phase. Subsequently, the test branch remains open, and 40 continuous load samples are recorded to form a complete change sequence from load connection to continuous load. Throughout the load process, the controller continuously monitors the actual test current, minimum single-cell voltage, and battery temperature. When any of these reach the preset test termination condition for the corresponding model, the test branch is immediately shut down, and the stage of termination and triggering condition are recorded, so that this dynamic response can fully reflect the limiting characteristics of the equipment during low-energy testing.

[0028] Furthermore, immediately after the test branch is shut down, the unload recovery phase begins. The controller continues to continuously collect battery pack voltage, individual cell voltage, and battery temperature, maintaining the same sampling time sequence as the aforementioned load phase to obtain the complete recovery process from the load state to the resting state. Recovery observation continues until the end of the pre-set observation period for the corresponding model. The controller saves each sampling record of the recovery phase with the pre-load reference using the same data structure. For example, if two starting power supplies show similar voltage drops during the short-term load phase, one of them rapidly approaches the pre-load state in the first few sets of samples after unloading, while the other remains significantly deviated at the end of the recovery observation, then the two form different recovery records. After the test is completed, the controller organizes the sampling results of the resting reference phase, short-term load phase, continuous load phase, and unload recovery phase into phased response data according to the actual occurrence sequence. Each record includes the test phase, sampling sequence, battery pack voltage, individual cell voltage, actual test current, and battery temperature. If the voltage or temperature of any single cell reaches the preset safety termination condition during the load process, the data obtained before termination will still be saved, and the termination stage, triggering condition and corresponding cell position will be recorded at the same time; if the actual test current does not enter the allowable test current range specified for this model, the self-test will be terminated and will not proceed to the subsequent start-up level determination.

[0029] S2. Calculate the short-time load voltage drop, continuous load voltage drop, and recovery voltage drop based on the phased response data, and determine the instantaneous voltage drop state, continuous load state, and recovery state respectively; calculate the corresponding phase deviation based on the voltage of each individual cell in the series, take the maximum deviation as the weakest cell state, and record the position of the weakest cell and the corresponding test stage. The corresponding test temperature conditions, instantaneous pressure drop state, continuous load state, recovery state, weakest single-cell state, weakest single-cell location, and test stage are combined into a start-up response state.

[0030] Specifically, S2 receives complete phased response data and performs continuous parsing according to the previously indicated static baseline phase, short-term load phase, continuous load phase, and load removal and recovery phase.

[0031] The controller first obtains the reference voltage of the battery pack and the reference voltage of each individual cell before loading from continuous sampling at the end of the static reference stage, and determines the average result of continuous temperature sampling at the end of the static reference stage as the test temperature condition. This test temperature condition is obtained in the same way during R&D calibration and actual use, providing the start-up capability judgment boundary for step 3 to select the corresponding temperature range.

[0032] In step 1, the actual test current is recorded to confirm that both the short-time load stage and the continuous load stage are within the allowable test current range specified for this model. Then, the state is directly extracted according to the stage markings determined in step 1, without re-dividing the test waveform.

[0033] Furthermore, the controller first compares the reference voltage before loading with the continuous voltage samples at the end of the short-term load phase, when the test current has stabilized, and determines the voltage drop of the battery pack between the two as the instantaneous voltage drop state. The representative value of the continuous samples at the end of the short-term load phase is obtained by averaging the results of the corresponding sampling segments, thereby reducing the impact of a single switch transient sample on the state result. Subsequently, using this representative voltage of the short-term load as the starting point of continuous change and the average result of the continuous samples at the end of the continuous load phase as the ending point, the voltage drop generated between the two is determined as the continuous load state. In this way, the instantaneous voltage drop state only describes the rapid drop after the test load is applied, and the continuous load state only describes the additional drop caused by continued loading after the rapid drop has already occurred. The two states correspond to the different output characteristics when the vehicle starter is first turned on and during subsequent continuous dragging, respectively.

[0034] In the load removal and recovery phase, the pre-load reference voltage established in step 1 is used as the recovery target. The controller reads the average result of continuous sampling at the end of the recovery observation phase as the representative voltage at the end of the recovery phase. The remaining difference between the pre-load reference voltage and this representative voltage at the end of the recovery phase is defined as the recovery state. When the representative voltage at the end of the recovery phase has reached or exceeded the pre-load reference voltage, the recovery state is recorded as zero. Therefore, the larger the recovery state, the more significant the residual voltage recovery after load removal. The R&D calibration phase uses the exact same recovery observation location and calculation method to establish the recovery state boundary, enabling direct comparison of similar states in step 3.

[0035] Furthermore, during the formation of the battery pack's three states (instantaneous voltage drop state, continuous load state, and recovery state), the controller processes the voltage of each individual cell in the same sampling location. For each cell in the same string, its short-term load voltage drop, continuous load additional voltage drop, and residual difference after load removal are obtained, and the dynamic change of that cell is compared with the median level of the dynamic changes of all cells in the same stage at each test phase. The maximum additional deviation exhibited by a cell relative to other cells in the same stage is taken as the degree of dynamic weakening of that cell in this test. The controller then selects the maximum degree of dynamic weakening from all cells and all test phases as the weakest cell state, and records the location of the weakest cell that produces the maximum deviation and the corresponding test phase. If step 1 ends prematurely because a cell first reaches the safe termination condition, that cell is directly taken as the weakest cell, and its triggering phase and the obtained dynamic changes are written together into the weakest cell state. With this processing, cells with similar resting voltages but significant weakening after loading can be directly identified, and the weakest cell state still maintains a state quantity with the same physical basis as other voltage dynamic states.

[0036] The controller ultimately integrates the test temperature conditions, instantaneous voltage drop state, continuous load state, recovery state, weakest cell state, weakest cell location, and corresponding test stages into a unified startup response state. All of these states are directly obtained from the same low-energy phased self-test in step 1. The instantaneous voltage drop state, continuous load state, recovery state, and weakest cell state are all expressed as voltage difference or dynamic deviation of the same voltage type, in volts. During the R&D and verification phase, the exact same calculation method is used to establish fixed judgment boundaries corresponding to different startup levels.

[0037] S3. Select and determine the effective startup margin based on the startup response status; and determine the highest level with the effective startup margin greater than zero as the current allowed startup level, and determine the restriction reason from the level with the smallest remaining proportion among the levels with the first effective startup margin not greater than zero.

[0038] Specifically, the controller receives the startup response status and uses the test temperature conditions, instantaneous voltage drop status, continuous load status, recovery status, weakest cell status, weakest cell location, and corresponding test stage. Based on the test temperature conditions, the controller selects the pre-defined startup capability judgment boundary group corresponding to the product model. Each temperature range is continuously divided during the R&D verification phase, covering the temperature range within which the product is allowed to perform self-tests. Each temperature range has multiple candidate startup levels set from low to high.

[0039] In a specific implementation, for each candidate start-up level, the R&D phase first performs the same low-energy phased self-test according to S1, then forms a start-up response state with the same structure according to S2, and subsequently applies the corresponding real high-rate load to the same test sample. Samples that can maintain the battery pack and individual cells meeting the start-up requirements within specified continuous conditions are recorded as samples that pass that level. Based on this, the instantaneous voltage drop boundary, continuous load boundary, recovery boundary, and weakest cell boundary are determined. All four states adopt the definition that "the larger the value, the closer the dynamic response is to the unfavorable state," thus allowing for a unified boundary comparison direction for each candidate level.

[0040] During the research and development calibration, steps 1 and 2 were repeated under the same samples and test conditions to obtain the repeatability of the four states. The maximum repeatability deviation ratio relative to the corresponding level boundary was calculated for the instantaneous pressure drop state, continuous load state, recovery state, and weakest single-cell state. The maximum value among the four repeatability deviation ratios was then taken as the boundary contraction amount for the candidate start-up level. The resulting boundary contraction amount has been converted into a dimensionless ratio and saved as a fixed calibration parameter for the corresponding model and start-up level. The boundaries of the four states for each start-up level are arranged in a progressively tighter relationship from low to high, ensuring that higher start-up levels have an allowable state range no wider than lower start-up levels.

[0041] In actual judgment, the controller starts from the lowest candidate start level and compares the four states output in step 2 with the corresponding boundary of that level. Since all four states are indicators that an increase in value represents a deterioration in the state, the remaining proportion of each state is uniformly obtained by subtracting the current state value from the corresponding boundary value and then dividing by the corresponding boundary value. The remaining proportion is positive when the current state is within the allowable region; zero when it just reaches the boundary; and negative when it exceeds the boundary. After the four remaining proportions are formed, the effective start margin of the candidate start level is determined according to the following formula: ; in, Indicates the current startup response status relative to the first... Effective start margin for each candidate start level; Indicates the instantaneous pressure drop state according to the first The remaining proportion obtained by converting the instantaneous pressure drop boundary of each startup level; This represents the remaining percentage of the continuous load condition calculated according to the continuous load boundary of this level. This indicates the remaining percentage of the recovery status calculated according to the recovery boundary of this level. This represents the remaining proportion obtained by converting the weakest single-unit state according to the boundary of the weakest single-unit at that level; Indicates the first The boundary contraction values ​​obtained from repeated R&D experiments for each candidate initiation level. All boundary values ​​of the same type for each candidate initiation level are positive. The four residual proportions are all obtained by converting the same state variable with the same type of boundary value; all are dimensionless proportions. It is also a dimensionless margin. This relationship is based on the minimum safety margin principle in engineering constraint determination. The state closest to the limit boundary at the current level is determined by the minimum residual proportion among the four necessary starting constraints, and then the fixed boundary shrinkage formed by repeated test discretization is deducted.

[0042] For example, under a certain candidate start-up level, the remaining proportions for instantaneous pressure drop, sustained load, recovery, and weakest monomer are 0.31, 0.22, 0.26, and 0.18, respectively. The boundary contraction determined by repeated R&D tests for this level is 0.04. Therefore, the effective start-up margin is 0.18 minus 0.04, resulting in 0.14, and this level is deemed acceptable. Moving on to the next candidate start-up level, if the remaining proportions for the four items are 0.20, 0.11, 0.14, and 0.02, respectively, and the boundary contraction for this level is 0.04, then the effective start-up margin is 0.02 minus 0.04, resulting in -0.02. This level is deemed unacceptable, and the previously accepted level is determined as the current permissible start-up level.

[0043] The controller performs the above comparisons sequentially from low to high candidate start levels. It stops increasing the start level when the effective start margin first reaches zero or is below zero, and the previous start level with a positive effective start margin is designated as the current allowed start level. If the lowest candidate start level already has an effective start margin of zero or below zero, the current allowed start level is recorded as below the lowest available start level, allowing step 4 to directly enter the prohibited start state. The limiting cause is directly determined by the state with the smallest remaining percentage among the first failed levels: when the instantaneous voltage drop remaining percentage is the smallest, the limiting cause is recorded as instantaneous voltage drop limitation; when the continuous load remaining percentage is the smallest, the limiting cause is recorded as continuous load limitation; when the recovery remaining percentage is the smallest, the limiting cause is recorded as recovery limitation; when the weakest cell remaining percentage is the smallest, the limiting cause is recorded as weakest cell limitation, with the weakest cell location and corresponding test stage already determined in step 2 added as additional content for this limiting cause. If step 1 was prematurely terminated due to the cell reaching the safe termination condition, the premature termination stage is simultaneously incorporated into the weakest cell limiting cause. Therefore, the limiting cause itself already carries the abnormal location and occurrence stage information required for step 4.

[0044] The final output includes the current allowed start-up level and the reason for the limitation. The current allowed start-up level represents the highest start-up level that the current start-up response state can stably meet in the fixed boundary system established by real high-rate tests during the R&D phase; the reason for the limitation indicates the dynamic state that must first be reached when further increasing the start-up level, and includes both the location of the weakest monomer and the corresponding test stage under the weakest monomer limitation condition.

[0045] S4. Input the current allowed startup level and the reason for restriction into the preset startup permission determination rule, and output the startup permission status in combination with the rated startup level and the lowest available startup level. Finally, control the startup output circuit according to the startup permission status.

[0046] Specifically, the controller receives the current allowed startup level and the reason for the restriction, and reads the pre-defined rated startup level and minimum available startup level for the corresponding product model. The controller first compares the current allowed startup level with these two fixed levels: if the current allowed startup level reaches the rated startup level, a normal startup permission is granted; if the current allowed startup level is lower than the rated startup level but still reaches the minimum available startup level, a downgraded startup permission is granted; if the current allowed startup level is lower than the minimum available startup level, a startup prohibition state is established. Both the rated startup level and the minimum available startup level are determined by startup performance verification results during the product development phase and written to the controller's non-volatile storage area; therefore, the corresponding model parameters are directly called during actual device use.

[0047] Under normal start permission conditions, the controller maintains the start enable of the start output circuit, and subsequent start operations continue to be executed according to the product's existing polarity detection, short-circuit protection, and start triggering logic. In degraded start permission conditions, the controller displays the currently allowed start level on the local interface or sends it to the user terminal, and obtains the target start level before the user initiates the start. The target start level is obtained through local buttons, the display interface, or the user terminal connected to the device. Its selectable levels adopt the same level system as the currently allowed start level and are available for user selection according to the vehicle's pre-configured start capability range. The controller maintains the start output circuit enabled only when the target start level is not higher than the currently allowed start level; when the target start level is higher than the currently allowed start level, the controller prohibits the start relay from closing or disables the start power switch drive. Therefore, the currently allowed start level determined in step 3 directly participates in the actual start permission judgment in degraded conditions, rather than merely serving as display information.

[0048] Specifically, when the current allowed start level is lower than the minimum available start level, the controller directly establishes a start-prohibited state and cancels the high-current start enable of the start output circuit. For relay-controlled start ports, the controller prevents the relay from obtaining closed drive; for power switch-controlled start circuits, the controller disables the drive enable of the corresponding power switch. The limitation reason is saved synchronously with the current allowed start level, where instantaneous voltage drop limitation, continuous load limitation, and recovery limitation respectively form corresponding capability limitation prompts; when the limitation reason is the weakest single-unit limitation, the location of the weakest single-unit and the corresponding test stage already carried in the limitation reason are directly read for local maintenance records and remote operation and maintenance display.

[0049] Furthermore, after the startup permission status is established, the controller writes the current allowed startup level, restriction reason, and startup permission status into its local status storage area. The IoT communication module then combines this information with the device ID and monitoring time to form an IoT monitoring record. The device ID is obtained from the terminal identifier permanently embedded at the product's factory, and the monitoring time is obtained from the controller's system clock. The communication module sends the monitoring record to the server via the product's existing wireless communication link. The server saves the latest status according to the device ID and monitoring time, and provides the current allowed startup level, restriction reason, and startup permission status to the corresponding user terminal or maintenance terminal. If communication is temporarily interrupted, the controller continues to control its local output circuit according to the established startup permission status, while sequentially saving any monitoring records that have not yet been uploaded. Once communication is restored, the records are uploaded according to their recording times.

[0050] In a specific implementation, for example, when the current allowed start level of a certain model of equipment reaches the rated start level, the controller grants normal start permission. After long-term storage, a self-test is performed. If the current allowed start level drops to an intermediate level, a downgraded start permission is granted. If the target start level selected by the user is within this intermediate level range, a start loop is allowed; if a target start level higher than the current allowed start level is selected, the start loop is prohibited. When it is subsequently determined that the current allowed start level is lower than the minimum available start level, the controller directly cancels the start output enable and enters a prohibited start state. Thus, the low-energy dynamic response obtained in step 1 is transformed into a start response state in step 2, then the current allowed start level and the reason for the restriction are determined in step 3, and finally converted into actual start permission and IoT monitoring results in step 4.

[0051] like Figure 2 As shown in the figure, this embodiment of the invention also provides an intelligent monitoring system for automotive emergency jump starters based on the Internet of Things, the system comprising: The phased self-test execution module 10 is used to acquire phased response data of the battery pack during low-energy self-test. The phased response data includes sampling records of the static reference, short-term load, continuous load and load removal recovery stages. Each sampling record includes the test stage, sampling order, battery pack voltage, individual cell voltage, actual test current and battery temperature. The phased response data is obtained by sequentially forming static baseline, short-term load, continuous load, and unload recovery when the battery pack meets the self-test allowable conditions. The response state determination module 20 is used to calculate the short-time load voltage drop, continuous load voltage drop, and recovery voltage drop based on the phased response data, and determine the instantaneous voltage drop state, continuous load state, and recovery state respectively; calculate the corresponding phase deviation based on the voltage of each individual cell, take the maximum deviation as the weakest individual cell state, and record the position of the weakest individual cell and the corresponding test stage. The corresponding test temperature conditions, instantaneous pressure drop state, continuous load state, recovery state, weakest single-cell state, weakest single-cell location, and test stage are combined into a start-up response state. The startup level determination module 30 is used to select and determine the effective startup margin based on the startup response status; and to determine the highest level with the effective startup margin greater than zero as the current allowed startup level, and to determine the restriction reason based on the state with the smallest remaining proportion among the levels with the first effective startup margin not greater than zero. The startup permission and IoT communication module 40 is used to input the current allowed startup level and the reason for restriction into the preset startup permission judgment rule, and output the startup permission status in combination with the rated startup level and the lowest available startup level, and finally control the startup output loop according to the startup permission status.

[0052] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0053] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of apparatuses or units may be electrical, mechanical, or other forms.

[0054] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0055] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A smart monitoring method for automotive emergency jump starters based on the Internet of Things, characterized in that, The method includes: S1. Obtain the phased response data of the battery pack during the low-energy self-test; the phased response data includes sampling records of the static reference, short-term load, continuous load and load removal recovery stages, and each sampling record includes the test stage, sampling order, battery pack voltage, individual cell voltage, actual test current and battery temperature. The phased response data is obtained by sequentially forming static baseline, short-term load, continuous load, and unload recovery when the battery pack meets the self-test allowable conditions. S2. Calculate the short-time load voltage drop, continuous load voltage drop, and recovery voltage drop based on the phased response data, and determine the instantaneous voltage drop state, continuous load state, and recovery state respectively; calculate the corresponding phase deviation based on the voltage of each individual cell in the series, take the maximum deviation as the weakest cell state, and record the position of the weakest cell and the corresponding test stage. The corresponding test temperature conditions, instantaneous pressure drop state, continuous load state, recovery state, weakest single-cell state, weakest single-cell location, and test phase are combined into a start-up response state. S3. Select and determine the effective startup margin based on the startup response status; and determine the highest level with the effective startup margin greater than zero as the current allowed startup level, and determine the restriction reason from the level with the smallest remaining proportion among the levels with the first effective startup margin not greater than zero. S4. Input the current allowed startup level and the reason for restriction into the preset startup permission determination rule, and output the startup permission status in combination with the rated startup level and the lowest available startup level. Finally, control the startup output circuit according to the startup permission status.

2. The intelligent monitoring method for automotive emergency jump starters based on the Internet of Things according to claim 1, characterized in that, The testing phase includes static baseline, short-term load, continuous load, and load removal and recovery phases. The static reference is formed in the following way: after the battery pack meets the self-test allowable conditions, the test branch is kept disconnected, and the battery pack voltage and the voltage of each cell are continuously collected; when the continuous sampling results are kept within the preset fluctuation range, the subsequent continuous sampling records are taken as the static reference.

3. The intelligent monitoring method for automotive emergency jump starters based on the Internet of Things according to claim 1, characterized in that, The self-test parameters for the self-test allowable conditions include at least the self-test allowable voltage range, the self-test allowable temperature range, the sampling period, the static stability fluctuation range, the test current allowable range, and the test termination conditions. Then, the battery pack meets the self-test allowable conditions, including: comparing the battery pack voltage, minimum single cell voltage and battery temperature with the self-test allowable conditions preset for the current product model. If all items are within the corresponding allowable range, it is determined that the self-test allowable conditions are met and the test preparation state is entered.

4. The intelligent monitoring method for automotive emergency jump starters based on the Internet of Things according to claim 1, characterized in that, The instantaneous voltage drop state is determined as follows: taking the reference voltage obtained at the end of the static reference stage before loading as the reference, the average value of continuous voltage sampling after the test current stabilizes in the later part of the short-time load stage is taken as the representative voltage of the short-time load, and the difference between the reference voltage before loading and the representative voltage of the short-time load is determined as the instantaneous voltage drop state. The method for determining the continuous load state is as follows: taking the short-time load representative voltage as the starting point, taking the average value of continuous sampling at the end of the continuous load stage as the continuous load representative voltage, and determining the continuous load state by the difference between the short-time load representative voltage and the continuous load representative voltage. The recovery state is determined as follows: the average result of continuous sampling at the end of the recovery observation phase is read as the representative voltage at the end of the recovery phase, and the remaining difference between the reference voltage before loading and the representative voltage at the end of the recovery phase is determined as the recovery state. When the voltage at the recovery terminal has reached or exceeded the reference voltage before loading, the recovery status is recorded as zero.

5. The intelligent monitoring method for automotive emergency jump starters based on the Internet of Things according to claim 4, characterized in that, The method for determining the reference voltage before loading is as follows: the reference voltage before loading of the battery pack and the reference voltage before loading of each cell are obtained from the continuous sampling at the end of the static reference stage, and the average result of the continuous temperature sampling at the end of the static reference stage is determined as the temperature condition for this test.

6. The intelligent monitoring method for automotive emergency jump starters based on the Internet of Things according to claim 1, characterized in that, The process involves calculating the corresponding stage deviation based on the voltage of each individual cell, taking the maximum deviation as the weakest cell state, and recording the position of the weakest cell and the corresponding test stage. Specifically: For each individual unit, calculate its deviation from the intermediate level of dynamic changes of all units in the same stage during the short-term loading stage, continuous loading stage, and unloading recovery stage. Take the maximum value of the deviation of the corresponding unit in each stage as the degree of dynamic weakening of that unit. Then, select the weakest monomer state from all monomers with the maximum dynamic weakening degree, and record the position of the monomer and its corresponding test stage.

7. The intelligent monitoring method for automotive emergency jump starters based on the Internet of Things according to claim 1, characterized in that, The step of selecting and determining the effective startup margin based on the startup response status includes: Based on the corresponding test temperature conditions, select the start-up capability judgment boundary group for the corresponding temperature range. For each temperature range, set multiple candidate start-up levels from low to high. The start-up capability judgment boundary group includes multiple candidate start-up levels arranged from low to high. Each candidate start-up level corresponds to the instantaneous pressure drop boundary, continuous load boundary, recovery boundary, and weakest single-cell boundary. Starting from the lowest candidate start-up level, the instantaneous pressure drop state, continuous load state, recovery state, and weakest single-unit state are compared with the corresponding level boundary to obtain the remaining proportion of each state. The minimum value of the remaining proportion of each state is taken, and the boundary contraction amount of the corresponding candidate start-up level is subtracted to obtain the effective start-up margin. Among them, when the current state is within the allowable region, the current remaining proportion is positive; when it just reaches the boundary, it is zero; and when it exceeds the boundary, it is negative.

8. The intelligent monitoring method for automotive emergency jump starters based on the Internet of Things according to claim 7, characterized in that, The step of determining the highest level with an effective startup margin greater than zero as the currently allowed startup level includes: The effective startup margin is calculated sequentially from low to high according to the candidate startup levels. When the effective startup margin reaches zero or is lower than zero for the first time, the level is stopped from being increased, and the previous level with an effective startup margin greater than zero is determined as the current allowed startup level. If the lowest candidate startup level has an effective startup margin of zero or lower than zero, the current allowed startup level is recorded as lower than the lowest available startup level, and startup is prohibited. The reason for the limitation is determined by the state with the smallest remaining proportion among the levels where the initial effective start margin is not greater than zero, including: When the effective start margin is less than or equal to zero for the first time, the state with the smallest remaining proportion in the corresponding candidate start level is determined as the limiting cause; among them, the instantaneous voltage drop state corresponds to the instantaneous voltage drop limit, the continuous load state corresponds to the continuous load limit, the recovery state corresponds to the recovery limit, and the weakest cell state corresponds to the weakest cell limit. When the weakest cell limit is applied, the location of the weakest cell and the corresponding test stage are added.

9. The intelligent monitoring method for automotive emergency jump starters based on the Internet of Things according to claim 1, characterized in that, The preset startup permission determination rules include: Based on a comparison of the current allowed start level with the rated start level and the minimum available start level: A normal startup permission is granted when the current allowed startup level reaches the rated startup level. A downgraded start permission is granted when the current permitted start level is lower than the rated start level but still reaches the minimum available start level. A boot-prohibited state is created when the current allowed boot level is lower than the minimum available boot level. The control of the startup output circuit based on the startup permission status includes: When the current allowed start level reaches the rated start level, a normal start permission is granted and the start output circuit is enabled. When the current allowed start level is lower than the rated start level but not lower than the minimum available start level, a downgrade start permission is granted, and the start output circuit is enabled only when the target start level is not higher than the current allowed start level. When the current allowed start level is lower than the minimum available start level, a start-prohibited state is established and the start output circuit is disabled.

10. An intelligent monitoring system for automotive emergency jump starters based on the Internet of Things, characterized in that, The system includes: The phased self-test execution module is used to acquire phased response data of the battery pack during low-energy self-test. The phased response data includes sampling records of the static reference, short-term load, continuous load and load removal recovery stages. Each sampling record includes the test stage, sampling order, battery pack voltage, individual cell voltage, actual test current and battery temperature. The phased response data is obtained by sequentially forming static baseline, short-term load, continuous load, and unload recovery when the battery pack meets the self-test allowable conditions. The response state determination module is used to calculate the short-time load voltage drop, continuous load voltage drop, and recovery voltage drop based on the phased response data, and determine the instantaneous voltage drop state, continuous load state, and recovery state respectively; calculate the corresponding stage deviation based on the voltage of each individual cell, take the maximum deviation as the weakest cell state, and record the position of the weakest cell and the corresponding test stage. The corresponding test temperature conditions, instantaneous pressure drop state, continuous load state, recovery state, weakest single-cell state, weakest single-cell location, and test phase are combined into a start-up response state. The startup level determination module is used to select and determine the effective startup margin based on the startup response status; and to determine the highest level with the effective startup margin greater than zero as the current allowed startup level, and to determine the restriction reason based on the state with the smallest remaining proportion among the levels with the first effective startup margin not greater than zero. The startup permission and IoT communication module is used to input the current allowed startup level and the reason for restriction into the preset startup permission judgment rule, and output the startup permission status in combination with the rated startup level and the lowest available startup level, and finally control the startup output loop according to the startup permission status.

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