Lithium battery pack charging risk multidimensional monitoring and early warning system based on fast charging technology

Abstract

The application discloses a lithium battery pack charging risk multidimensional monitoring and early warning system based on fast charging technology, relates to the field of charging risk monitoring and early warning, and mainly aims at a lithium battery pack charging terminal, only sets a single fault alarm and power-off protection mode, and cannot distinguish different grades of hidden troubles such as slight parameter deviation, capacity anomaly and severe thermal runaway risk, specifically, a multidimensional perception module relies on built-in micro sensors of battery cells and module key point sensors, synchronously collects core parameters, realizes double risk perception of the microscopic dimension of the battery cell and the macroscopic dimension of the module, then a risk assessment module accurately identifies linear progressive hidden troubles and nonlinear sudden faults in the fast charging process based on multidimensional perception data through linear ratio change law, temperature rise and temperature difference increase rate superposition threshold determination, and finally a hierarchical early warning module divides early warning grades in combination with the temperature rise expansion speed of internal elements of the lithium battery pack and the capacity deviation characteristics.

Description

Technical Field

[0001] This invention relates to the field of charging risk monitoring and early warning, specifically a multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology. Background Technology

[0002] With the rapid development of the new energy industry, lithium batteries, with their advantages of high energy density and long cycle life, are being widely used in core fields such as electric vehicles, grid energy storage, and portable power equipment. Fast charging technology has become a core requirement for lithium battery devices. As fast charging power continues to increase and charging rate continues to rise, the electrochemical reaction rate, heat generation efficiency, and current carrying capacity of lithium battery packs during fast charging have increased significantly. Consequently, various charging safety risks have emerged, becoming the core bottleneck restricting the popularization of fast charging technology.

[0003] Under fast charging conditions, lithium battery pack failures are characterized by being hidden, gradual, and sudden. Early problems such as microscopic anomalies inside the cells, contact hazards at module connection points, and abnormal coupling of parameters of multiple components cannot be detected by traditional external monitoring methods. Furthermore, traditional technologies cannot distinguish between individual cell anomalies and overall module anomalies. Changes in various parameters interfere with each other, making it easy to have false or missed warnings.

[0004] Meanwhile, conventional risk assessment mechanisms lack the ability to perform multi-parameter linkage analysis, rely solely on a single parameter threshold to determine risk, and cannot identify the coupled fault patterns between temperature rise, resistance, and voltage parameters. They also lack effective means of identifying both linearly slow-deteriorating latent faults and nonlinear sudden faults.

[0005] In addition, the industry's traditional early warning system lacks refined classification standards. Most devices only have a single fault alarm and power failure protection mode, which cannot distinguish between different levels of hidden dangers such as slight parameter deviations, capacity abnormalities, and severe thermal runaway risks. This either leads to excessive protection, resulting in a significant reduction in fast charging efficiency, or insufficient protection, which can cause safety accidents such as thermal runaway, fire, and explosion.

[0006] To address the aforementioned technical shortcomings, a multi-dimensional monitoring and early warning system for lithium battery pack charging risks based on fast charging technology is proposed. This system is adapted to the safety management needs of lithium batteries in high-rate fast charging scenarios and possesses refined charging risk monitoring and early warning functions, including multi-dimensional perception, dynamic assessment, and hierarchical prevention and control. Summary of the Invention

[0007] The purpose of this invention is to solve the problems mentioned above by proposing a multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology.

[0008] The objective of this invention can be achieved through the following technical solution: a multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology, including a monitoring and early warning platform, wherein the monitoring and early warning platform is connected to a multi-dimensional perception module, a risk assessment module, and a graded early warning module.

[0009] The multi-dimensional sensing module performs multi-dimensional sensing and identification of lithium battery packs, and provides early warning of lithium battery charging risks through multi-dimensional data collection and analysis.

[0010] After completing the multi-dimensional perception, the risk assessment module conducts a risk assessment of the lithium battery pack based on the data collected from the multi-dimensional perception.

[0011] The graded early warning module provides graded early warnings for lithium battery packs and implements targeted prevention and control measures based on the warning level.

[0012] Furthermore, the multi-dimensional perception and recognition process in the multi-dimensional perception module is as follows:

[0013] Miniaturized sensors are integrated inside or on the surface of each battery cell to collect data on the voltage fluctuation range of each cell during the charging phase, as well as the temperature rise range inside the cell during the charging phase. These data are then compared with voltage fluctuation range thresholds and temperature rise range thresholds, respectively.

[0014] If the voltage fluctuation range of a single cell exceeds the voltage fluctuation range threshold during the charging phase, or if the temperature rise range inside the cell exceeds the temperature rise range threshold during the charging phase, it is inferred that there is an abnormality in the internal dimension perception of the current cell, a cell dimension risk signal is generated and sent to the monitoring and early warning platform, and the monitoring and early warning platform performs corresponding cell maintenance after receiving it.

[0015] If the voltage fluctuation range of a single cell does not exceed the voltage fluctuation range threshold during the charging phase, and the temperature rise range inside the cell does not exceed the temperature rise range threshold during the charging phase, it is inferred that the current internal dimension perception of the cell is normal, and a cell dimension safety signal is generated and sent to the monitoring and early warning platform.

[0016] Furthermore, sensors are placed on the module busbars and key connection points, and the real-time resistance fluctuation range of the corresponding contact resistance setting points is collected through the sensors, while the temperature difference range between modules is also obtained.

[0017] If the real-time resistance fluctuation range of the corresponding contact resistance setting point exceeds the resistance fluctuation range threshold, or the temperature difference range between modules exceeds the temperature difference range threshold, it is inferred that the current module temperature sensing is abnormal, a module-level risk signal is generated and sent to the monitoring and early warning platform. After receiving the signal, the monitoring and early warning platform performs module control and makes charging decisions based on the control situation.

[0018] If the real-time resistance fluctuation range of the corresponding contact resistance setting point does not exceed the resistance fluctuation range threshold, and the temperature difference range between modules does not exceed the temperature difference range threshold, it is inferred that the current module temperature sensing is normal, a module-level safety signal is generated and sent to the monitoring and early warning platform.

[0019] Furthermore, the risk assessment process in the risk assessment module is as follows:

[0020] The system acquires the increase in the temperature rise span within the cell and the increase in the temperature difference span between the modules at the same time, and establishes a span increase curve. The corresponding curves within the cell and the modules are compared. If the corresponding values ​​of the two types of curves are linearly related, and the linear ratio between the increase in the temperature rise span within the cell and the increase in the temperature difference span between the modules continues to increase, a charging linearity warning signal is generated and sent to the monitoring and warning platform. After receiving the signal, the monitoring and warning platform performs flash charging control and maintains each component of the lithium battery pack.

[0021] Furthermore, when the linear ratio between the increase in the temperature rise range inside the battery cell and the increase in the temperature difference range of the module remains constant, a charging linear stability signal is generated and sent to the monitoring and early warning platform.

[0022] If the corresponding values ​​of the two types of curves are in a non-linear relationship, the sum of the speed values ​​of the internal temperature rise rate of the cell and the temperature difference rise rate of the module that exceed the corresponding speed thresholds of the two types is collected. If the sum of the speed values ​​of the internal temperature rise rate of the cell and the temperature difference rise rate of the module exceeds the corresponding speed thresholds of the two types, it is inferred that the risk assessment of the lithium battery pack during the charging stage is abnormal, a non-linear warning signal is generated and sent to the monitoring and warning platform. After receiving the signal, the monitoring and warning platform performs internal checks on the cell and module hardware, traces the cause of the temperature rise, and implements targeted control.

[0023] Furthermore, if the rate of temperature rise inside the cell and the rate of temperature difference rise in the module exceed the corresponding two types of speed thresholds, and if they do not exceed the speed values ​​and thresholds, it is inferred that the risk assessment of the lithium battery pack during the charging phase is normal, a nonlinear stable signal is generated and sent to the monitoring and early warning platform.

[0024] Furthermore, the specific process for graded early warning of lithium battery packs in the graded early warning module is as follows:

[0025] The cells or modules are uniformly labeled as internal components of the lithium battery pack. The rate of increase of the local temperature rise range of the internal components of the lithium battery pack during the fast charging execution phase is obtained. At the same time, when the local temperature rise range increases, the deviation between the actual increase of the lithium battery pack capacity and the preset increase value when the fast charging parameter settings are unchanged is obtained.

[0026] Furthermore, if the rate of increase of the local temperature rise range of the internal components of the lithium battery pack exceeds the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase does not exceed the increase deviation threshold when the fast charging parameters are not changed, then a first-level temperature rise warning signal is set and sent to the monitoring and warning platform.

[0027] If the rate of increase of the local temperature rise range of the internal components of the lithium battery pack does not exceed the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase exceeds the increase deviation threshold when the fast charging parameter settings are unchanged, then a first-level capacity warning signal is set and sent to the monitoring and warning platform.

[0028] If the rate of increase of the local temperature rise range of the internal components of the lithium battery pack does not exceed the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase does not exceed the increase deviation threshold when the fast charging parameter settings are not changed, then a level zero monitoring and early warning signal is set and sent to the monitoring and early warning platform.

[0029] If the rate of increase of the local temperature rise range of the internal components of the lithium battery pack exceeds the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase exceeds the increase deviation threshold when the fast charging parameters are not changed, then a level two prevention and control early warning signal is set and sent to the monitoring and early warning platform.

[0030] Furthermore, after receiving the corresponding level signal, the monitoring and early warning platform will control the charging of the lithium battery pack.

[0031] Compared with the prior art, the beneficial effects of the present invention are:

[0032] 1. The multi-dimensional sensing module breaks through the dimensional limitations of traditional lithium battery charging monitoring, constructing a dual-layer monitoring system that combines microscopic sensing inside the cell with macroscopic sensing outside the module. By integrating micro-sensors inside the cell, it accurately captures the voltage fluctuation range and hidden temperature rise range inside the cell during fast charging, solving the blind spot problem of traditional external monitoring being unable to identify early electrochemical anomalies and internal heat accumulation in the cell. By placing sensors on the module busbar and key connection points, it achieves real-time monitoring of contact resistance fluctuations and module temperature difference ranges, accurately identifying hidden faults such as loose module connections, oxidation, and heat dissipation failure.

[0033] This invention abandons the traditional instantaneous value judgment mode and adopts the parameter change span judgment logic to effectively identify the slow and gradual hidden faults and instantaneous sudden faults during fast charging. It greatly improves the comprehensiveness and accuracy of fault perception, avoids the fast charging safety hazards caused by cell failure and module contact failure from the source, and provides comprehensive, accurate and multi-dimensional basic data support for subsequent risk assessment.

[0034] 2. The risk assessment module innovatively constructs a multi-parameter coupled dynamic assessment model, overcoming the one-sidedness of traditional single-parameter assessments. By establishing a comparison mechanism between the increasing value curves of cell temperature rise and module temperature difference, it accurately captures the progressive deterioration faults with continuously increasing linear ratios during fast charging, predicts hidden risks such as battery aging and the continuous aggravation of internal side reactions in advance, and promptly triggers flash charging control and component maintenance to avoid the accumulation and deterioration of faults. Furthermore, through the nonlinear relationship acceleration superposition judgment logic, it accurately distinguishes sudden nonlinear anomalies caused by hardware faults, achieving accurate classification of fault types and enabling targeted hardware inspection and temperature rise tracing and rectification.

[0035] This invention upgrades the assessment of lithium battery fast charging risks from "post-fault determination" to "pre-event trend prediction and in-event accurate identification," covering various types of charging risks, including gradual, sudden, single, and coupled risks, and greatly improving the scientific rigor and accuracy of risk assessment.

[0036] 3. The graded early warning module establishes a four-level refined early warning system: Level 0 routine monitoring, Level 1 temperature rise early warning, Level 1 capacity early warning, and Level 2 severe control, to address the shortcomings of traditional early warning systems that are crude and homogeneous. Combining the dual characteristics of temperature rise diffusion rate and capacity deviation, it accurately distinguishes between pure temperature rise anomalies, pure capacity anomalies, and high-risk faults involving both temperature and capacity. Differentiated control strategies are matched for different levels and types of risks: Level 0 signals ensure stable operation under normal fast charging conditions; Level 1 temperature rise early warning specifically regulates charging heat dissipation and power; Level 1 capacity early warning investigates battery capacity degradation faults; and Level 2 early warning implements comprehensive hardware control and power limiting.

[0037] This invention avoids the decrease in fast charging efficiency caused by over-protection under minor hidden dangers, and eliminates safety accidents caused by insufficient protection under severe hidden dangers. It achieves the technical effect of "graded risk, precise prevention and control, and on-demand management", taking into account both fast charging safety and charging efficiency, while providing precise guidance for targeted battery maintenance. Attached Figure Description

[0038] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0039] Figure 1 This is a system principle block diagram of the present invention. Detailed Implementation

[0040] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0042] Please see Figure 1 As shown, a multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology includes a monitoring and early warning platform, and the monitoring and early warning platform has communication connections to a multi-dimensional perception module, a risk assessment module, and a graded early warning module.

[0043] The monitoring and early warning platform generates multi-dimensional sensing signals and sends them to the multi-dimensional sensing module;

[0044] After receiving the multi-dimensional sensing signal, the multi-dimensional sensing module performs multi-dimensional sensing and identification of the lithium battery pack, and conducts lithium battery charging risk warning through multi-dimensional data collection and analysis.

[0045] Miniaturized sensors are integrated inside or on the surface of each battery cell to collect data on the voltage fluctuation range of each cell during the charging phase, as well as the temperature rise range inside the cell during the charging phase. These data are then compared with voltage fluctuation range thresholds and temperature rise range thresholds, respectively.

[0046] If the voltage fluctuation range of a single cell exceeds the voltage fluctuation range threshold during the charging phase, or if the temperature rise range inside the cell exceeds the temperature rise range threshold during the charging phase, it is inferred that there is an abnormality in the internal dimension perception of the current cell, a cell dimension risk signal is generated and sent to the monitoring and early warning platform, and the monitoring and early warning platform performs corresponding cell maintenance after receiving it.

[0047] If the voltage fluctuation range of a single cell does not exceed the voltage fluctuation range threshold during the charging phase, and the temperature rise range inside the cell does not exceed the temperature rise range threshold during the charging phase, it is inferred that the internal dimension perception of the cell is normal, and a cell dimension safety signal is generated and sent to the monitoring and early warning platform.

[0048] Sensors are placed on the module busbars and key connection points, and the real-time resistance fluctuation range of the corresponding contact resistance setting points is collected by the sensors. At the same time, the temperature difference range between modules is obtained.

[0049] The real-time resistance fluctuation range and the temperature difference range between modules at the corresponding contact resistance setting points are compared with the resistance fluctuation range threshold and the temperature difference range threshold, respectively.

[0050] If the real-time resistance fluctuation range of the corresponding contact resistance setting point exceeds the resistance fluctuation range threshold, or the temperature difference range between modules exceeds the temperature difference range threshold, it is inferred that the current module temperature sensing is abnormal, a module-level risk signal is generated and sent to the monitoring and early warning platform. After receiving the signal, the monitoring and early warning platform performs module control and makes charging decisions based on the control situation.

[0051] If the real-time resistance fluctuation range of the corresponding contact resistance setting point does not exceed the resistance fluctuation range threshold, and the temperature difference range between modules does not exceed the temperature difference range threshold, it is inferred that the current module temperature sensing is normal, a module-level safety signal is generated and sent to the monitoring and early warning platform.

[0052] It is important to explain the voltage fluctuation range threshold: This threshold is obtained based on standard fast-charging test calibration of lithium battery packs of the same model, batch, and aging degree. By conducting rated fast-charging power tests on a large number of new, semi-aged, and fully aged lithium battery packs, the maximum fluctuation range of the voltage of all individual cells during the entire normal charging stage is collected. After removing data from extreme environmental interference, the maximum fluctuation value within the 95% confidence interval is taken as the basic threshold. Simultaneously, dynamic corrections are made based on battery cycle count and ambient temperature to adapt to the monitoring needs of batteries in different aging states, and this is used to determine potential abnormal voltage fluctuations within the cells.

[0053] Temperature rise range threshold: obtained through high and low temperature environment simulation fast charging test. Under full working conditions from -20℃ to 60℃, the maximum range of normal temperature rise inside the cell during standard fast charging of lithium battery pack is collected. The basic threshold is calibrated by combining battery capacity and charging rate parameters. At the same time, the battery aging degradation correction coefficient is superimposed to avoid normal temperature rise of aging battery being misjudged as fault and to accurately identify abnormal heating problems inside the cell.

[0054] Resistance fluctuation span threshold: Based on the standard electrical parameter calibration of the module bus and connection points, the contact resistance fluctuation data of brand new modules, slightly oxidized modules, and loose modules are collected under the high current conditions of fast charging. The maximum span of resistance fluctuation under normal connection conditions is statistically analyzed and set as the basic threshold. It can be adaptively fine-tuned according to the module usage time, ambient humidity, and degree of oxidation to identify loose connection points, oxidation, and poor contact faults.

[0055] Temperature difference span threshold: obtained through module array temperature difference comparison test. Synchronous fast charging test is performed on all modules of the lithium battery pack. The maximum temperature difference span between modules under normal working conditions is collected. Combined with the module layout and heat dissipation conditions, a fixed threshold is calibrated to distinguish between normal heat dissipation temperature difference and abnormal fault temperature difference, and to identify module local heat accumulation and heat dissipation failure faults.

[0056] After completing multi-dimensional perception, the monitoring and early warning platform generates a risk assessment signal and sends it to the risk assessment module;

[0057] After receiving the risk assessment signal, the risk assessment module performs a risk assessment on the lithium battery pack based on multi-dimensional sensing and data collection.

[0058] The system acquires the increase in the temperature rise span within the battery cell and the increase in the temperature difference span between the modules at the same time, and establishes a span increase curve. It then compares the corresponding curves within the battery cell and the module. If the values ​​of the two types of curves are linearly related, and the linear ratio between the increase in the temperature rise span within the battery cell and the increase in the temperature difference span between the modules continues to increase, a charging linearity warning signal is generated and sent to the monitoring and warning platform. Upon receiving the signal, the monitoring and warning platform performs flash charging control and maintains each component of the lithium battery pack. The linear ratio represents the numerical proportion between the two parameters; that is, if the temperature rise within the battery cell increases by 1, the temperature difference span between the modules increases by 2, and the numerical proportion is 2.

[0059] When the linear ratio between the increase in the temperature rise inside the battery cell and the increase in the temperature difference of the module remains constant, a charging linear stability signal is generated and sent to the monitoring and early warning platform.

[0060] If the corresponding values ​​of the two types of curves are in a non-linear relationship, the sum of the speed values ​​of the internal temperature rise rate of the cell and the temperature difference rise rate of the module that exceed the corresponding speed thresholds of the two types is collected. If the sum of the speed values ​​of the internal temperature rise rate of the cell and the temperature difference rise rate of the module exceeds the corresponding speed thresholds of the two types, it is inferred that the risk assessment of the lithium battery pack during the charging stage is abnormal, a non-linear warning signal is generated and sent to the monitoring and warning platform. After receiving the signal, the monitoring and warning platform performs internal checks on the cell and module hardware, traces the cause of the temperature rise, and implements targeted control.

[0061] If the rate of temperature rise inside the cell and the rate of temperature difference rise in the module exceed the corresponding two types of speed thresholds, or if they do not exceed the speed values ​​and thresholds, it is inferred that the risk assessment of the lithium battery pack during the charging phase is normal, and a nonlinear stable signal is generated and sent to the monitoring and early warning platform.

[0062] It needs to be explained that the dual-type speed threshold (cell temperature rise speed threshold and module temperature difference rise speed threshold) is calibrated through multiple sets of fast charging gradient tests. Test groups with different charging rates, different battery aging states, and different heat dissipation conditions are set up. The maximum rate of increase of cell temperature rise and the maximum rate of increase of module temperature difference under normal operating conditions are collected. The extreme rate of increase under stable operating conditions of each group is taken as the corresponding speed threshold to distinguish between the rate of increase of normal parameters and the rate of increase of abnormal faults.

[0063] Speed ​​values ​​and thresholds: Based on the extreme growth rate values ​​corresponding to the two types of speed thresholds mentioned above, they are obtained through fault simulation tests. The tests simulate scenarios such as local overheating of the battery cell, abnormal heat dissipation of the module, and parameter coupling faults. The superimposed values ​​of the two types of growth rates exceeding the thresholds under abnormal operating conditions are statistically analyzed. The maximum value of the superimposed growth rates under normal operating conditions is taken as the speed value and threshold, which are used to determine the risk of nonlinear faults.

[0064] Linearity ratio judgment benchmark: The steady-state ratio of the increase in cell temperature rise span to the increase in module temperature difference span under the standard fast charging conditions of the new battery is used as the benchmark ratio. This benchmark ratio is a fixed operating condition calibration value. Subsequently, the linear deterioration trend of the fault is determined by the dynamic comparison between the real-time ratio and the benchmark ratio.

[0065] After receiving a linear or nonlinear charging warning signal, the monitoring and early warning platform generates a graded warning signal and sends it to the graded warning module while simultaneously implementing early warning and prevention measures.

[0066] After receiving the graded warning signal, the graded warning module will issue graded warnings for the lithium battery pack and carry out targeted prevention and control measures according to the warning level.

[0067] The cells or modules are uniformly labeled as internal components of the lithium battery pack. The local temperature rise range of the internal components of the lithium battery pack is increased at a certain rate during the fast charging execution phase. At the same time, when the local temperature rise range increases, the deviation between the actual increase in the lithium battery pack capacity and the preset increase is obtained when the fast charging parameter settings are unchanged. The local temperature rise range increase rate of the internal components of the lithium battery pack and the deviation between the actual increase in the lithium battery pack capacity and the preset increase are compared with the range increase rate threshold and the increase deviation threshold, respectively. The fast charging parameters are the power and other parameters set for fast charging.

[0068] If the local temperature rise rate of the internal components of the lithium battery pack exceeds the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase does not exceed the increase deviation threshold when the fast charging parameters are not changed, then a first-level temperature rise warning signal is set and sent to the monitoring and warning platform.

[0069] If the rate of increase of the local temperature rise range of the internal components of the lithium battery pack does not exceed the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase exceeds the increase deviation threshold when the fast charging parameter settings are unchanged, then a first-level capacity warning signal is set and sent to the monitoring and warning platform.

[0070] If the rate of increase of the local temperature rise range of the internal components of the lithium battery pack does not exceed the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase does not exceed the increase deviation threshold when the fast charging parameter settings are not changed, then a level zero monitoring and early warning signal is set and sent to the monitoring and early warning platform.

[0071] If the local temperature rise rate of the internal components of the lithium battery pack exceeds the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase exceeds the increase deviation threshold when the fast charging parameters are not changed, then a level two prevention and control early warning signal is set and sent to the monitoring and early warning platform.

[0072] After receiving the corresponding level signal, the monitoring and early warning platform will control the charging of the lithium battery pack to reduce safety hazards during the fast charging phase.

[0073] It needs to be explained that the range increase rate threshold is obtained through lithium battery pack fast charging temperature rise diffusion test. It collects the maximum expansion rate of the local temperature rise range of the internal components of the battery under normal fast charging conditions, and combines the battery packaging structure and heat dissipation performance to determine the risk of abnormal local thermal diffusion.

[0074] Increased capacity deviation threshold: Based on the battery rated capacity fast charging calibration test, under the premise of fixed fast charging parameters, the deviation range between the actual capacity increase and the theoretical preset increase of the battery at different cycle numbers is collected. The maximum value of normal capacity decay and normal charging deviation is taken as the threshold to accurately distinguish between normal capacity fluctuation and abnormal capacity decay fault.

[0075] In summary, this invention constructs a complete multi-dimensional monitoring, dynamic risk assessment, refined graded early warning, and closed-loop safety management system for lithium battery fast charging through the synergistic cooperation of four functional units. The overall technical advantages and beneficial effects are extremely prominent.

[0076] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology, characterized in that, It includes a monitoring and early warning platform, and the platform has communication connections with multi-dimensional perception modules, risk assessment modules, and graded early warning modules. The multi-dimensional sensing module performs multi-dimensional sensing and identification of lithium battery packs, and provides early warning of lithium battery charging risks through multi-dimensional data collection and analysis. After completing the multi-dimensional perception, the risk assessment module performs a risk assessment on the lithium battery pack; The graded early warning module provides graded early warnings for lithium battery packs and implements targeted prevention and control measures based on the warning level.

2. The multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology according to claim 1, characterized in that, The multi-dimensional perception and recognition process in the multi-dimensional perception module is as follows: Miniaturized sensors are integrated inside or on the surface of each battery cell to collect data on the voltage fluctuation range of each cell during the charging phase, as well as the temperature rise range inside the cell during the charging phase. These data are then compared with voltage fluctuation range thresholds and temperature rise range thresholds, respectively. If the voltage fluctuation range of a single cell exceeds the voltage fluctuation range threshold during the charging phase, or if the temperature rise range inside the cell exceeds the temperature rise range threshold during the charging phase, it is inferred that there is an abnormality in the internal dimension perception of the current cell, a cell dimension risk signal is generated and sent to the monitoring and early warning platform, and the monitoring and early warning platform performs corresponding cell maintenance after receiving it. If the voltage fluctuation range of a single cell does not exceed the voltage fluctuation range threshold during the charging phase, and the temperature rise range inside the cell does not exceed the temperature rise range threshold during the charging phase, it is inferred that the current internal dimension perception of the cell is normal, and a cell dimension safety signal is generated and sent to the monitoring and early warning platform.

3. The multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology according to claim 2, characterized in that, Sensors are placed on the module busbars and key connection points, and the real-time resistance fluctuation range of the corresponding contact resistance setting points is collected by the sensors. At the same time, the temperature difference range between modules is obtained. If the real-time resistance fluctuation range of the corresponding contact resistance setting point exceeds the resistance fluctuation range threshold, or the temperature difference range between modules exceeds the temperature difference range threshold, it is inferred that the current module temperature sensing is abnormal, a module-level risk signal is generated and sent to the monitoring and early warning platform. After receiving the signal, the monitoring and early warning platform performs module control and makes charging decisions based on the control situation. If the real-time resistance fluctuation range of the corresponding contact resistance setting point does not exceed the resistance fluctuation range threshold, and the temperature difference range between modules does not exceed the temperature difference range threshold, it is inferred that the current module temperature sensing is normal, a module-level safety signal is generated and sent to the monitoring and early warning platform.

4. The multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology according to claim 1, characterized in that, The risk assessment process in the risk assessment module is as follows: The system acquires the increase in the temperature rise span within the cell and the increase in the temperature difference span between the modules at the same time, and establishes a span increase curve. The corresponding curves within the cell and the modules are compared. If the corresponding values ​​of the two types of curves are linearly related, and the linear ratio between the increase in the temperature rise span within the cell and the increase in the temperature difference span between the modules continues to increase, a charging linearity warning signal is generated and sent to the monitoring and warning platform. After receiving the signal, the monitoring and warning platform performs flash charging control and maintains each component of the lithium battery pack.

5. The multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology according to claim 4, characterized in that, When the linear ratio between the increase in the temperature rise inside the battery cell and the increase in the temperature difference of the module remains constant, a charging linear stability signal is generated and sent to the monitoring and early warning platform. If the corresponding values ​​of the two types of curves are in a non-linear relationship, the sum of the speed values ​​of the internal temperature rise rate of the cell and the temperature difference rise rate of the module that exceed the corresponding speed thresholds of the two types is collected. If the sum of the speed values ​​of the internal temperature rise rate of the cell and the temperature difference rise rate of the module exceeds the corresponding speed thresholds of the two types, it is inferred that the risk assessment of the lithium battery pack during the charging stage is abnormal, a non-linear warning signal is generated and sent to the monitoring and warning platform. After receiving the signal, the monitoring and warning platform performs internal checks on the cell and module hardware, traces the cause of the temperature rise, and implements targeted control.

6. The multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology according to claim 5, characterized in that, If the rate of temperature rise inside the cell and the rate of temperature difference rise in the module exceed the corresponding two types of speed thresholds, or if they do not exceed the speed values ​​and thresholds, it is inferred that the risk assessment of the lithium battery pack during the charging phase is normal, and a nonlinear stable signal is generated and sent to the monitoring and early warning platform.

7. The multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology according to claim 1, characterized in that, The specific process for graded early warning of lithium battery packs in the graded early warning module is as follows: The cells or modules are uniformly labeled as internal components of the lithium battery pack. The rate of increase of the local temperature rise range of the internal components of the lithium battery pack during the fast charging execution phase is obtained. At the same time, when the local temperature rise range increases, the deviation between the actual increase of the lithium battery pack capacity and the preset increase value when the fast charging parameter settings are unchanged is obtained.

8. The multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology according to claim 7, characterized in that, If the local temperature rise rate of the internal components of the lithium battery pack exceeds the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase does not exceed the increase deviation threshold when the fast charging parameters are not changed, then a first-level temperature rise warning signal is set and sent to the monitoring and warning platform. If the rate of increase of the local temperature rise range of the internal components of the lithium battery pack does not exceed the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase exceeds the increase deviation threshold when the fast charging parameter settings are unchanged, then a first-level capacity warning signal is set and sent to the monitoring and warning platform. If the rate of increase of the local temperature rise range of the internal components of the lithium battery pack does not exceed the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase does not exceed the increase deviation threshold when the fast charging parameter settings are not changed, then a level zero monitoring and early warning signal is set and sent to the monitoring and early warning platform. If the rate of increase of the local temperature rise range of the internal components of the lithium battery pack exceeds the range increase rate threshold during the fast charging execution phase, and the deviation between the actual increase in the capacity of the lithium battery pack and the preset increase exceeds the increase deviation threshold when the fast charging parameters are not changed, then a level two prevention and control early warning signal is set and sent to the monitoring and early warning platform.

9. The multi-dimensional monitoring and early warning system for charging risks of lithium battery packs based on fast charging technology according to claim 8, characterized in that, After receiving the corresponding level signal, the monitoring and early warning platform will control the charging of the lithium battery pack.

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