Lithium battery thermal runaway detection method based on shock waves
By deploying shock wave sensors in lithium batteries to collect and process shock wave signals in real time, the problems of response lag and insufficient sensitivity in the thermal runaway detection of lithium batteries in the prior art are solved, and rapid and accurate thermal runaway early warning is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-28
- Publication Date
- 2026-03-31
AI Technical Summary
Existing technologies are unable to detect early signs of thermal runaway in lithium batteries quickly and sensitively, resulting in delayed responses that may cause them to miss the best time for early warning and intervention, and pose a risk of misjudgment or missed detection.
Shock wave sensors are used to collect shock wave signals generated by thermal runaway in real time. The peak pressure, rise time and decay characteristics are extracted by the signal processing module, and a judgment function is constructed to comprehensively judge the thermal runaway event. The judgment is made in combination with the energy ratio Ei/E.
It achieves rapid response within milliseconds, improves the sensitivity and accuracy of thermal runaway detection, reduces false positives and false negatives, and is applicable to various lithium battery packaging forms without requiring significant modifications to the battery structure.
Smart Images
Figure CN121763103A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of lithium battery testing technology, and specifically to a method for detecting thermal runaway in lithium batteries based on shock waves. Background Technology
[0002] Solid-state batteries possess high energy density, meaning they can store more electrical energy within the same volume or weight, thus providing electric vehicles with longer driving ranges and meeting people's needs for long-distance travel. At the same time, their excellent thermal stability makes solid-state batteries relatively safer and more reliable during operation, reducing safety risks caused by overheating.
[0003] However, despite the numerous advantages of solid-state batteries, they cannot completely avoid the serious problem of thermal runaway during practical use, especially under extreme conditions. When solid-state batteries encounter extreme situations such as overcharging, over-discharging, short circuits, high-temperature environments, or mechanical damage, the internal chemical reactions can become uncontrolled, leading to a rapid increase in temperature. This violent chemical reaction not only accelerates the decomposition and aging of the battery's internal materials but also triggers the rapid release of gases. The rapid accumulation of large amounts of gas inside can generate a huge impact force on the battery's casing structure, resulting in transient shock waves. These shock waves are characterized by concentrated energy and rapid propagation. Once generated, if they are not detected and handled in time, they are highly likely to cause further damage to the battery, or even lead to serious safety accidents such as battery fires and explosions, posing a huge threat to the safety of people and property.
[0004] Currently, monitoring technologies for battery thermal runaway mainly rely on the detection of parameters such as temperature, voltage, and current. While these traditional monitoring methods can reflect the battery's operating status to some extent, they have many insurmountable limitations in practical applications.
[0005] In terms of response speed, temperature sensors typically require a certain amount of time to detect changes in battery temperature. Due to the inherent delay in heat conduction, external temperature sensors may not immediately detect a significant temperature rise when thermal runaway has already begun inside the battery, resulting in a response lag. For example, in some cases, a violent chemical reaction may have already occurred inside the battery, generating a large amount of heat, but the temperature sensor may not detect that the temperature exceeds a set threshold for several seconds or even longer. These precious few seconds are often crucial in responding to thermal runaway incidents, potentially missing the optimal window for warning and intervention. Voltage and current detection methods also suffer from response lag. Changes in battery voltage and current are often indirect manifestations of thermal runaway after it has developed to a certain stage, and cannot directly and quickly reflect the early characteristics of thermal runaway. Moreover, during normal operation, battery voltage and current fluctuate due to various factors, such as load changes and battery aging. This makes it more difficult to accurately determine thermal runaway events through voltage and current changes, and it is easy to misjudge or miss the detection.
[0006] In terms of sensitivity, existing monitoring technologies are insufficient to capture the weak signals in the early stages of thermal runaway. Thermal runaway is a gradual process, and in its early stages, the signals it generates may be extremely weak. Traditional temperature, voltage, and current detection methods struggle to detect these subtle changes. For example, in the initial stages of thermal runaway, the battery may only experience minor gas releases and localized temperature increases. These changes may not be enough to elicit a noticeable response from temperature sensors, nor can they accurately determine the occurrence of thermal runaway through abnormal changes in voltage and current. However, this early stage is crucial for preventing and controlling thermal runaway accidents. If abnormal signals can be detected promptly and appropriate measures taken during this stage, further deterioration of the accident can be effectively prevented. Summary of the Invention
[0007] The purpose of this invention is to propose a method for detecting thermal runaway of lithium batteries based on shock waves. This technical solution can improve the response speed and sensitivity of battery thermal runaway detection.
[0008] To achieve the above objectives, this invention proposes a method for detecting thermal runaway in lithium batteries based on shock waves, comprising: Shock wave sensor arrangement, wherein the shock wave sensor is electrically connected to the signal acquisition and processing module, for real-time acquisition of shock wave signals generated by thermal runaway; The shock wave sensor converts the physical impact signal into an analog electrical signal and transmits it to the signal processing module; the analog electrical signal is converted into a digital signal by an analog-to-digital converter; the digital signal is processed to extract the pressure peak value, rise time, and decay characteristics, and the energy ratio Ei / E is calculated, where Ei is the energy of each impact component and E is the total energy; Set the peak pressure threshold, rise time threshold, and decay characteristic threshold; Construct the decision function, as shown in the formula below:
[0009] Where w1, w2, and w3 are weighting coefficients; when F ≥ threshold F0, it is determined to be a thermal runaway event.
[0010] Beneficial effects of the basic solution: When a battery (especially a solid-state battery) experiences thermal runaway, the internal electrolyte decomposition and gas expansion rapidly breach the vent valve, generating an instantaneous shock wave. This process is much faster than the physical process of temperature rise and slow gas leakage. The shock wave sensor, deployed directly at the vent valve, can capture the shock signal within milliseconds after thermal runaway is triggered. Compared to traditional detection methods that rely on temperature conduction and gas diffusion, the response delay is significantly reduced, providing a more sufficient time window for subsequent protective actions.
[0011] The sensor directly converts physical impact signals into electrical signals, and after analog-to-digital conversion, it quickly extracts key parameters (pressure peak, rise time, etc.), avoiding the complex process of "gas collection-concentration analysis" in traditional gas detection, further shortening the signal processing cycle and ensuring the real-time nature of detection and judgment.
[0012] This approach does not rely solely on a single parameter, but comprehensively extracts three core physical characteristics: peak pressure (reflecting impact intensity), rise time (reflecting the abrupt change in impact characteristics), and attenuation characteristics (reflecting the duration of impact). It also introduces the energy ratio Ei / E (quantifying the contribution percentage of each impact component) to fully reflect the properties of thermal runaway shock waves. Compared to traditional judgment logic based solely on temperature and gas concentration thresholds, this approach effectively avoids misjudgments caused by interference factors such as external vibrations, ambient temperature fluctuations, and minor gas leaks.
[0013] Whether it's a single battery cell or a module, detection can be achieved simply by deploying the shock wave sensor on the outer surface of the battery module or at the vent valve location. No major modifications to the battery structure are required. It is compatible with different systems such as solid-state batteries and liquid lithium batteries, as well as various packaging forms such as square, cylindrical, and pouch cells, making it flexible for various application scenarios.
[0014] As a feasible preferred solution, a shock wave sensor is fixedly installed on the outer surface of a selected battery module and / or at the location of a battery cell vent valve within the battery pack.
[0015] As a feasible preferred solution, when selecting the outer surface of the battery module as the sensor mounting location, 4-6 shock wave sensors are arranged according to the size and shape of the battery module.
[0016] As a feasible preferred option, when installing a sensor at the location of the battery cell vent valve, at least one shock wave sensor is fixedly installed.
[0017] As a feasible and preferred option, the total energy E is calculated using the following formula:
[0018] Where P(t) is the pressure value of the shock wave signal at time t. and These are the start and end times of the signal, respectively.
[0019] As a feasible and preferred solution, after a thermal runaway event is determined, the thermal runaway level is classified according to the energy ratio and the corresponding alarm signal is triggered. At the same time, the thermal runaway event information and level result are sent to the battery management system (BMS) so that the BMS can implement safety protection measures.
[0020] As a feasible preferred solution, the threshold of the decision function is obtained by statistical analysis of experimental data on thermal runaway of solid-state batteries under different operating conditions, and is dynamically updated using machine learning or statistical regression methods. Attached Figure Description Figure 1 This is a logic diagram of a lithium battery thermal runaway detection method based on shock waves.
[0021] Figure 2 A schematic diagram of the overall installation structure for arranging shock wave sensors in a battery pack module.
[0022] Figure 3 A schematic diagram of the overall structure for arranging a shock wave sensor on the battery pack exhaust valve.
[0023] Figure 4 A schematic diagram of the battery cell mounting structure for arranging a shock wave sensor on the battery pack vent valve.
[0024] Attached reference numerals: 1. Pipe socket; 2. Lifting lug assembly; 3. Battery module; 4. Shock wave sensor; 5. BMS management system; 6. Grille; 7. Positive electrode; 8. Negative electrode; 9. Gas valve. Detailed Implementation
[0025] To make the technical solution and advantages of this application clearer, the technical solution of the present invention will be further described in detail below with reference to the accompanying drawings. It is understood that the specific embodiments described herein are only some embodiments of the present invention, and are only used to explain this application, not to limit it. It should be noted that the technical features or combinations of technical features described in the following embodiments should not be considered isolated; they can be combined with each other to achieve better technical effects. The same reference numerals appearing in the accompanying drawings of the following embodiments represent the same features or components, and can be applied to different embodiments.
[0026] Furthermore, unless otherwise defined, the technical or scientific terms used in this invention description shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains.
[0027] The present invention will now be described in further detail with reference to the accompanying drawings.
[0028] Reference Figure 1This disclosure provides a method for detecting thermal runaway of lithium batteries based on shock waves, including the following steps.
[0029] Step S100: Shock wave sensor arrangement. The shock wave sensor is used to collect shock wave signals in real time when the battery module 3 experiences thermal runaway. It is preferably arranged on the top cover or side of the battery module. This includes: Reference Figure 2 The sensor mounting location is chosen on the surface of battery module 3 within the battery pack's internal structure. Depending on the size and shape of battery module 3, 4-6 shock wave sensors are arranged and electrically connected to the signal acquisition and processing module to ensure comprehensive capture of shock wave signals generated during thermal runaway. By placing a sensor at the exhaust valve 9, transient information of the exhaust shock wave can be directly captured.
[0030] Specifically, the line conduit socket 1 is used for electrical connection and signal transmission, the lifting lug assembly 2 is used for battery pack hoisting and fixing, the BMS management system 5 is used to provide protection and management functions, and the grille 6 is used to enhance structural stability and heat dissipation.
[0031] Or, refer to Figure 3 and Figure 4 The battery cell exhaust valve 9 is arranged as follows: For a battery cell with exhaust valve 9, a shock wave sensor is installed at the position of exhaust valve 9 to monitor the shock wave signal accompanying the exhaust process.
[0032] A sensor 3 is installed at the vent valve 9 of the battery cell to collect the shock wave signal accompanying the venting process. The battery pack includes a positive electrode 7, a vent valve 9, a sensor 3, a lifting lug 4, and a negative electrode 8. When the vent valve 9 experiences thermal runaway, it releases high-pressure gas. The sensor 3 detects the venting shock wave signal and transmits it to the signal acquisition system. Subsequently, the system uses the same threshold logic as that applied to the surface of the battery module 3 for judgment and alarm.
[0033] During installation, use a dedicated sensor mounting bracket or adhesive to secure the shock wave sensor to the selected mounting location, ensuring tight contact between the sensor and battery module 3 or exhaust valve 9 to minimize signal attenuation during transmission. Connect the sensor's signal cable, ensuring a secure connection to prevent loosening or breakage during vibration or impact.
[0034] Step S200, shock wave signal acquisition and processing, including: Step S201: Signal Acquisition. During thermal runaway, the shock wave sensor acquires the shock wave signal and converts the physical shock signal into an analog electrical signal. The analog electrical signal is then transmitted to the signal processing module via a signal line.
[0035] Step S202, Analog-to-Digital Conversion: After the sensor acquires the shock wave signal, it is converted into a digital signal by an analog-to-digital converter. The sampling rate and resolution of the analog-to-digital converter should be selected according to actual needs to ensure that the details of the shock wave signal can be accurately captured.
[0036] Step S203, feature parameter extraction, including: The feature extraction unit in the signal processing module processes the digital signal to obtain relevant characteristic parameters of the shock wave, including peak pressure A, rise time τ, and attenuation characteristic ζ.
[0037] Peak pressure (P_max): The maximum pressure value in a shock wave signal, reflecting the intensity of the shock wave. It can be calculated by finding the maximum value in the digital signal.
[0038] Rise time (T_r): The time required for a shock wave signal to rise from its initial point to reach its peak pressure, reflecting the shock wave's response rate. It can be approximated by calculating the time required for the signal to reach 90% of its maximum value from its initial point.
[0039] Attenuation characteristic (D): The time or attenuation rate required for a shock wave signal to decay from its peak pressure to a specific level (e.g., 10% of the maximum value), reflecting the dissipation process of the shock wave. It can be characterized by calculating the time or attenuation rate required for the signal to decay from its maximum value to a specific level.
[0040] Simultaneously calculate the energy ratio Ei / E, where Ei is the energy of each impact component and E is the total energy. The energy can be calculated by integrating the square of the shock wave signal, i.e.:
[0041] Where P(t) is the pressure value of the shock wave signal at time t. and These are the start and end times of the signal, respectively.
[0042] Step S300, thermal runaway time determination, includes: Step S301: Set preset thresholds. Based on experimental data and statistical analysis, set preset thresholds for characteristic parameters such as peak pressure (P_max_threshold), rise time (T_r_threshold), and decay characteristics (D_threshold).
[0043] These thresholds should be able to distinguish between shock wave signals under normal operating conditions and thermal runaway conditions.
[0044] In step S302, the decision module constructs a decision function based on the threshold comparison, as shown in the following formula:
[0045] Among them, w1, w2, and w3 are weight coefficients, which can be set based on experimental experience or data training.
[0046] Through thermal runaway experiments on solid-state batteries under different operating conditions, the distribution range of shock wave parameters was statistically analyzed, and a critical value that can distinguish between "normal" and "thermal runaway" was selected as a threshold. When F ≥ threshold F0, it is determined to be a thermal runaway event; otherwise, monitoring continues.
[0047] Step S303, Shock Wave Screening Mechanism: The system is equipped with a shock wave screening mechanism to analyze signals that meet the characteristics of thermal runaway and distinguish between shock waves generated by vehicle operation or external impact and shock waves generated by internal thermal runaway of the battery. For example, the shock waves generated by external impact and internal thermal runaway can be distinguished by analyzing the frequency characteristics and propagation direction of the shock wave signal.
[0048] Step S400, Energy Grading and Early Warning: If a thermal runaway event is determined, it is further graded based on the energy ratio Ei / E, and different levels of alarm signals are triggered to achieve rapid determination of thermal runaway in solid-state batteries. For example, the following grading criteria can be set: Level 1 thermal runaway: Ei / E≥0.7, indicating that the thermal runaway process involves violent energy release and is highly dangerous.
[0049] Second-order thermal runaway: 0.3≤Ei / E<0.7, indicating that the energy release during the thermal runaway process is moderate and the degree of danger is moderate.
[0050] Level 3 thermal runaway: Ei / E < 0.3, indicating that the energy release during the thermal runaway process is weak and the degree of danger is low.
[0051] Upon confirmation of a thermal runaway event, the alarm module triggers alarm signals of different levels based on the energy classification results. For example, a level 1 thermal runaway triggers a red alarm signal, a level 2 thermal runaway triggers a yellow alarm signal, and a level 3 thermal runaway triggers a blue alarm signal.
[0052] Simultaneously, the alarm module communicates with the battery management system (BMS), sending thermal runaway event information and energy classification results to the BMS to achieve real-time alarm and safety protection for thermal runaway events. The BMS can take corresponding safety measures based on the alarm information, such as cutting off battery power or activating the fire suppression system.
[0053] This disclosure also provides a solid-state battery thermal runaway shock wave detection system, including a shock wave acquisition module, a signal processing module, a judgment module, and an alarm module.
[0054] in: The shock wave acquisition module consists of shock wave sensors arranged on the surface of the battery module 3 and at the position of the battery cell exhaust valve 9, which are used to acquire shock wave signals when thermal runaway occurs. The signal processing module converts the analog signal output by the sensor into a digital signal and extracts the characteristic parameters of the shock wave, including the peak pressure, rise time and attenuation characteristics, while calculating the energy ratio of each shock component. The determination module performs a logical comparison between the feature parameters and a preset threshold. If the threshold condition is met, the thermal runaway event is confirmed, and energy grading is achieved by combining the energy ratio. If the threshold condition is not met, continuous monitoring is maintained. When the alarm module determines that a thermal runaway event has occurred, it triggers an alarm signal.
[0055] The above content is merely an embodiment of the present invention. Commonly known structures and characteristics of the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all prior art in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can improve and implement this solution based on the guidance provided in this application and their own capabilities. Some typical well-known structures or systems should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.
Claims
1. A shockwave-based lithium battery thermal runaway detection method, characterized in that, Comprise: A shock wave sensor arrangement, which is electrically connected with a signal acquisition and processing module, is used to collect shock wave signals generated by thermal runaway in real time; The shock wave sensor converts the physical impact signal into an analog electrical signal and transmits it to the signal processing module; The analog electrical signal is converted into a digital signal by an analog-to-digital converter; the digital signal is processed to extract the pressure peak value, rising edge time, and attenuation characteristics, and to calculate the energy ratio Ei / E, where Ei is the energy of each impact component and E is the total energy; Set the pressure peak value threshold, rising edge time threshold, and attenuation characteristic threshold; Construct a decision function with the following formula: Where w1, w2, and w3 are weight coefficients; when F≥threshold F0, it is determined to be a thermal runaway event.
2. The shockwave-based lithium battery thermal runaway detection method of claim 1, wherein, Install shock wave sensors at selected locations on the outer surface of the battery module and / or the exhaust valve of the battery cell in the battery pack.
3. The shockwave-based lithium battery thermal runaway detection method of claim 1, wherein, When the outer surface of the battery module is selected as the sensor installation location, arrange 4-6 shock wave sensors according to the size and shape of the battery module.
4. The shockwave-based lithium battery thermal runaway detection method of claim 1, wherein, When the sensor is installed at the exhaust valve position of the battery cell, at least one shock wave sensor is fixedly installed.
5. The shockwave-based lithium battery thermal runaway detection method of claim 1, wherein, The formula for calculating the total energy E is as follows: Wherein, P(t) is the pressure value of the shock wave signal at time t, and are the start and end time of the signal, respectively.
6. The shockwave-based lithium battery thermal runaway detection method of claim 1, wherein, After determining a thermal runaway event, divide the thermal runaway level according to the energy ratio and trigger the corresponding level alarm signal, and send the thermal runaway event information and level results to the battery management system BMS for the BMS to execute safety protection measures.
7. The shockwave-based lithium battery thermal runaway detection method of claim 1, wherein, The threshold of the decision function is obtained by statistical analysis of solid-state battery thermal runaway experimental data under different working conditions and dynamically updated using machine learning or statistical regression methods.