Sodium-ion battery thermal runaway monitoring method based on multi-parameter grading early warning

Abstract

The invention relates to the technical field of sodium-ion battery fault diagnosis, in particular to a sodium-ion battery thermal runaway monitoring method based on multi-parameter grading early warning, which induces thermal runaway of a sodium-ion battery by performing an overcharge experiment under different charging multiplying powers. An explosion-proof box, a strain sensor, a temperature sensor and a gas concentration sensor are used for monitoring the state of the battery in real time to ensure that the experiment is carried out safely; acquiring, recording and acquiring voltage, temperature, strain and gas concentration data of the sodium ion battery in the thermal runaway process in real time through corresponding sensors; the method has the beneficial effects that a multi-parameter grading early warning method is integrated into the battery management system (BMS), so that the method has very high practical value, the BMS can monitor each parameter in the battery pack in real time, compare the parameters with a preset threshold value and automatically trigger an early warning signal, and the automation level and the response speed of early warning are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of sodium ion battery fault diagnosis, and in particular to a sodium ion battery thermal runaway monitoring method based on multi-parameter graded early warning. Background Art

[0002] In recent years, sodium-ion battery technology has been gradually developed. Compared with lithium-ion batteries, sodium-ion batteries have the advantages of high safety and low cost. Therefore, sodium batteries have the potential to replace lithium batteries in energy storage systems. In terms of thermal behavior, sodium batteries have a higher internal resistance, which makes it less likely to generate heat when an internal short circuit occurs, thereby enhancing safety.

[0003] However, although the safety performance of sodium-ion batteries is expected to exceed that of lithium-ion batteries in energy storage scenarios, research on the thermal safety of sodium batteries is still limited. Similar to lithium batteries, sodium batteries may also cause thermal runaway under conditions of electrical abuse, mechanical abuse, and thermal abuse. Some scholars have conducted a comprehensive review of research in the field of thermal safety of sodium batteries, explored the correlation between the thermal behaviors of lithium batteries and sodium batteries, and proposed that the thermal runaway of sodium batteries has a very similar mechanism to that of lithium batteries.

[0004] In order to warn of thermal runaway of lithium batteries, the evolution of multiple parameters such as voltage, temperature, exhaust, and expansion during the thermal runaway process was analyzed. In previous studies, the changing trend of expansion strain during thermal runaway was analyzed, and early warning signals were provided through strain detection. In addition, scholars have conducted in-depth research on the exhaust components during thermal runaway of lithium batteries. At the same time, thermal runaway early warning methods based on gas detection are summarized. Compared with traditional voltage and temperature signals, these methods can achieve more timely advance warnings and provide more response time for responding to thermal runaway. Although the detection technology of thermal runaway of lithium batteries has become mature, the detection methods of thermal runaway of sodium-ion batteries are still limited, and more comprehensive and efficient detection methods are still needed. Summary of the invention

[0005] The object of the present invention is to provide a sodium ion battery thermal runaway monitoring method based on multi-parameter graded early warning to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a sodium ion battery thermal runaway monitoring method based on multi-parameter graded early warning, comprising the following steps:

[0007] By conducting overcharge experiments at different charging rates, thermal runaway of sodium-ion batteries was induced. During the experiment, explosion-proof boxes, strain sensors, temperature sensors, and gas concentration sensors were used to monitor the battery status in real time to ensure the safety of the experiment.

[0008] The voltage, temperature, strain and gas concentration data of the sodium-ion battery during thermal runaway are collected and recorded in real time through corresponding sensors;

[0009] According to the changes of various parameters under different charging rates, the evolution process of thermal runaway of sodium-ion batteries is analyzed. The analysis content includes voltage drop, temperature rise rate, strain change and gas concentration change, and the thermal runaway evolution coefficient and thermal runaway risk assessment coefficient are generated;

[0010] According to the analysis results, the thermal runaway process of sodium-ion batteries is divided into multiple stages, and graded warnings are given according to the parameter change characteristics of each stage, including the first stage, the second stage, and the third stage;

[0011] The above-mentioned multi-parameter graded warning method is integrated into the BMS system to monitor the battery status in real time by collecting parameters such as voltage, temperature, strain and gas in the battery pack.

[0012] Preferably, the overcharge experiment includes conducting experiments at different charging rates, specifically 0.5C, 1C and 2C.

[0013] Preferably, the specific formula of the thermal runaway evolution coefficient is as follows:

[0014]

[0015] Where T is the time interval in seconds (s), ΔV is the voltage drop, i.e. the change in battery voltage in volts (V), is the temperature rise rate, that is, the rate of change of temperature with time, in degrees Celsius per second (℃ / s), Δ∈ is the strain change, that is, the physical deformation of the battery during thermal runaway, ΔG is the gas concentration change, that is, the gas concentration change generated during thermal runaway, and α, β, γ, δ are weight coefficients.

[0016] Preferably, the specific method of obtaining the thermal runaway risk assessment coefficient is as follows:

[0017] S1. Data collection:

[0018] Collect data on the voltage drop and temperature rise rate of lithium batteries under different conditions, including experimental data under various charging rates, temperatures, usage cycles, etc.;

[0019] S2. Data processing:

[0020] Calculate the percentage of voltage drop V using the formula:

[0021]

[0022] Calculate the real-time temperature rise rate T in units of (℃ / s);

[0023] S3, threshold setting:

[0024] The voltage drop threshold is set to 25%, that is, when V>25%, the battery is in thermal runaway;

[0025] The temperature rise rate threshold is set to 1°C / s, that is, when T>1°C / s, the battery is in thermal runaway.

[0026] Preferably, the thermal runaway process is divided into three stages: the first stage is the collapse of the positive electrode structure, releasing a large amount of heat and oxygen; the second stage is the rupture of the battery shell, and the strain and gas concentration signals suddenly change; the third stage is the complete decomposition of the battery diaphragm, causing serious internal short circuit and rapid temperature rise.

[0027] Preferably, the graded warning includes: using the change of surface strain when the battery expands for warning; warning of thermal runaway by detecting early exhaust gas; using traditional voltage and temperature signals for warning.

[0028] Preferably, the formula for the thermal runaway risk assessment coefficient is:

[0029]

[0030] Where V is the voltage drop percentage and T is the temperature rise rate.

[0031] Preferably, the BMS system achieves real-time monitoring and automatic early warning of the battery status by comparing various parameters in the battery pack with set thresholds.

[0032] Preferably, the method is applicable to different types of sodium ion batteries, including but not limited to soft-pack batteries, hard-shell batteries and cylindrical batteries.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention proposes a sodium ion battery thermal runaway monitoring method based on multi-parameter graded early warning. Firstly, by conducting overcharging experiments at different charging rates, the wide applicability and reliability of the monitoring method are ensured, and the various situations that the sodium ion battery may encounter in practical applications can be more comprehensively reflected, thereby enhancing the practicality and accuracy of the early warning technology. Meanwhile, the multi-parameter graded early warning method is integrated into the battery management system (BMS), so that the method has high practical value. The BMS system can realize real-time monitoring of various parameters in the battery pack, compare them with preset thresholds, automatically trigger early warning signals, and improve the automation level and response speed of the early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 The present invention is a schematic structural diagram of a sodium ion battery thermal runaway monitoring method based on multi-parameter graded early warning. DETAILED DESCRIPTION

[0036] In order to make the purpose and technical solution of the present invention clearly and completely described, and the advantages more clearly understood, the embodiments of the present invention are further described in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are part of the embodiments of the present invention, rather than all of the embodiments, and are only used to explain the embodiments of the present invention, and are not used to limit the embodiments of the present invention. All other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] Embodiment 1

[0038] See also Figure 1 The present invention provides a sodium ion battery thermal runaway monitoring method based on multi-parameter graded early warning, comprising the following steps:

[0039] By conducting overcharge experiments at different charging rates (0.5C, 1C and 2C), thermal runaway of sodium-ion batteries was induced. During the experiment, explosion-proof boxes, strain sensors, temperature sensors, and gas concentration sensors were used to monitor the battery status in real time to ensure the safety of the experiment. The explosion-proof box can effectively isolate the high temperature, high pressure or harmful gases that may be generated when the battery is in thermal runaway. At the same time, the use of strain sensors, temperature sensors, and gas concentration sensors and other equipment to monitor the battery status in real time can provide accurate data on the physical and chemical changes inside the battery, which is helpful for subsequent analysis and early warning.

[0040] The voltage, temperature, strain and gas concentration data of the sodium-ion battery during thermal runaway are collected and recorded in real time through corresponding sensors. This data is the key basis for analyzing the evolution process of battery thermal runaway.

[0041] According to the changes of various parameters under different charging rates, the evolution process of thermal runaway of sodium-ion batteries is analyzed. The analysis content includes voltage drop, temperature rise rate, strain change and gas concentration change, and the thermal runaway evolution coefficient and thermal runaway risk assessment coefficient are generated. It can quantitatively describe the risk degree of battery thermal runaway and provide a basis for subsequent early warning;

[0042] According to the analysis results, the thermal runaway process of sodium-ion batteries is divided into multiple stages, and graded warnings are given according to the parameter change characteristics of each stage, including the first stage, the second stage, and the third stage;

[0043] The above-mentioned multi-parameter graded warning method is integrated into the BMS system to monitor the battery status in real time by collecting parameters such as voltage, temperature, strain and gas in the battery pack.

[0044] The specific formula of the thermal runaway evolution coefficient is as follows:

[0045]

[0046] Where T is the time interval in seconds (s), ΔV is the voltage drop, i.e. the change in battery voltage in volts (V), is the temperature rise rate, that is, the rate of change of temperature with time, in degrees Celsius per second (℃ / s), Δ∈ is the strain change, that is, the physical deformation of the battery during thermal runaway, ΔG is the gas concentration change, that is, the gas concentration change generated during thermal runaway, and α, β, γ, δ are weight coefficients.

[0047] It can be seen from the above formula that the thermal runaway evolution coefficient (TREC) is a comprehensive indicator. By integrating key parameters such as voltage drop, temperature rise rate, strain change and gas concentration change, it quantitatively describes the thermal runaway evolution process of sodium-ion batteries in overcharge experiments in a time-dependent manner. This coefficient allows the safety assessment in different application scenarios to be optimized by adjusting the weight coefficient, and can be integrated into the BMS system to realize real-time monitoring and early warning, thereby significantly improving the safety performance and reliability of the battery system.

[0048] The specific method for obtaining the thermal runaway risk assessment coefficient is as follows:

[0049] S1. Data collection:

[0050] Collect data on the voltage drop and temperature rise rate of lithium batteries under different conditions, including experimental data under various charging rates, temperatures, usage cycles, etc.;

[0051] S2. Data processing:

[0052] Calculate the percentage of voltage drop V using the formula:

[0053]

[0054] Calculate the real-time temperature rise rate T in units of (℃ / s);

[0055] S3, threshold setting:

[0056] The voltage drop threshold is set to 25%, that is, when V>25%, the battery is in thermal runaway;

[0057] The temperature rise rate threshold is set to 1°C / s, that is, when T>1°C / s, the battery is in thermal runaway. The formula for the thermal runaway risk assessment coefficient is:

[0058]

[0059] Where V is the voltage drop percentage and T is the temperature rise rate.

[0060] This formula determines whether the battery is in a thermal runaway state based on threshold conditions. When the voltage drop exceeds 25% and the temperature rise rate exceeds 1°C / s, K is set to 1, indicating that the battery has triggered thermal runaway; in other cases, K is set to 0, indicating that the battery has not reached thermal runaway conditions.

[0061] In summary, the thermal runaway risk assessment coefficient K is obtained through steps such as collecting data, processing data, setting thresholds and calculating coefficients. This method can accurately determine whether the battery is in a thermal runaway state, providing strong support for battery safety management. At the same time, since this method is based on threshold condition judgment, it has the advantages of being simple and easy to implement. The thermal runaway process is divided into three stages: the first stage is the collapse of the positive electrode structure, releasing a large amount of heat and oxygen; the second stage is the rupture of the battery shell, and the strain and gas concentration signals suddenly change; the third stage is the complete decomposition of the battery diaphragm, causing serious internal short circuits and rapid temperature rise; the graded warning includes: using the change in surface strain when the battery expands for warning; warning of thermal runaway by detecting early exhaust; using traditional voltage and temperature signals for warning. In the first stage, the collapse of the positive electrode structure causes the internal reaction of the battery to run away, releasing a large amount of heat and oxygen. In order to accurately monitor the status of this stage, it is necessary to monitor the voltage and temperature of the battery in real time. When the battery voltage rises sharply or the temperature rises abnormally, it indicates that the internal reaction has run away from control. Therefore, the corresponding voltage threshold and temperature threshold are set. Once these thresholds are exceeded, an early warning signal is triggered to remind the user to take timely countermeasures.

[0062] After entering the second stage, the battery shell ruptures, causing a sudden change in strain and gas concentration signals. At this time, sensors are needed to monitor the deformation of the battery shell and detect changes in gas concentration in the battery's surrounding environment. Once the deformation of the battery shell exceeds the preset threshold or the gas concentration in the environment exceeds the upper limit, an early warning signal is also triggered, which helps to promptly detect potential safety hazards and take corresponding preventive measures.

[0063] In the third stage, the battery diaphragm completely decomposes and causes a serious internal short circuit, resulting in a rapid rise in temperature. At this time, in addition to continuing to monitor the voltage and temperature of the battery, it is also necessary to monitor the current inside the battery in real time. Once the battery current increases rapidly or the temperature rises further to a higher upper limit, a more serious warning signal is triggered. These warning signals indicate that thermal runaway has intensified to a very dangerous level and emergency measures need to be taken immediately to prevent accidents. In summary, the state changes of the battery at different stages can be effectively monitored through the graded warning method, and corresponding countermeasures can be taken in time to ensure the safe and stable operation of the battery system. At the same time, using the changes in surface strain when the battery expands to warn the occurrence of thermal runaway by detecting early exhaust are effective methods to further improve the accuracy and reliability of monitoring.

[0064] Embodiment 2

[0065] Based on the first embodiment, the BMS system realizes real-time monitoring and automatic early warning of the battery status by comparing various parameters in the battery pack with the set thresholds. Specifically, the BMS system collects key parameters in the battery pack in real time, such as voltage, temperature, strain and gas concentration, and compares these parameters with the pre-set thresholds. If a parameter exceeds or falls below its corresponding threshold, the BMS system will trigger a corresponding early warning signal to remind the user to take timely countermeasures.

[0066] In summary, by comparing various parameters in the battery pack with the set thresholds, the BMS system achieves real-time monitoring and automatic early warning of the battery status. This method not only improves the accuracy and reliability of monitoring, but also provides strong support for battery safety management, helping to ensure the safe and stable operation of the battery system.

[0067] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A sodium ion battery thermal runaway monitoring method based on multi-parameter graded early warning, characterized in that: The following steps are involved: By conducting overcharge experiments at different charging rates, thermal runaway of sodium-ion batteries was induced. During the experiment, explosion-proof boxes, strain sensors, temperature sensors, and gas concentration sensors were used to monitor the battery status in real time to ensure the safety of the experiment. The voltage, temperature, strain and gas concentration data of the sodium-ion battery during thermal runaway are collected and recorded in real time through corresponding sensors; According to the changes of various parameters under different charging rates, the evolution process of thermal runaway of sodium-ion batteries is analyzed. The analysis content includes voltage drop, temperature rise rate, strain change and gas concentration change, and the thermal runaway evolution coefficient and thermal runaway risk assessment coefficient are generated; According to the analysis results, the thermal runaway process of sodium-ion batteries is divided into multiple stages, and graded warnings are given according to the parameter change characteristics of each stage, including the first stage, the second stage, and the third stage; The above-mentioned multi-parameter graded warning method is integrated into the BMS system to monitor the battery status in real time by collecting parameters such as voltage, temperature, strain and gas in the battery pack.

2. According to claim 1, a sodium ion battery thermal runaway monitoring method based on multi-parameter graded warning is characterized in that: The overcharge experiment includes conducting experiments at different charging rates, specifically 0.5C, 1C and 2C.

3. The method for monitoring thermal runaway of a sodium ion battery based on multi-parameter graded early warning according to claim 1, characterized in that: The specific formula of the thermal runaway evolution coefficient is as follows: Where T is the time interval in seconds (s), ΔV is the voltage drop, i.e. the change in battery voltage in volts (V), is the temperature rise rate, that is, the rate of change of temperature with time, in degrees Celsius per second (℃ / s), Δ∈ is the strain change, that is, the physical deformation of the battery during thermal runaway, ΔG is the gas concentration change, that is, the gas concentration change generated during thermal runaway, and α, β, γ, δ are weight coefficients.

4. A sodium ion battery thermal runaway monitoring method based on multi-parameter graded warning according to claim 1, characterized in that: The specific method for obtaining the thermal runaway risk assessment coefficient is as follows: S1. Data collection: Collect data on the voltage drop and temperature rise rate of lithium batteries under different conditions, including experimental data under various charging rates, temperatures, usage cycles, etc.; S2. Data processing: Calculate the percentage of voltage drop V using the formula: Calculate the real-time temperature rise rate T in units of (℃ / s); S3, threshold setting: The voltage drop threshold is set to 25%, that is, when V>25%, the battery is in thermal runaway; The temperature rise rate threshold is set to 1°C / s, that is, when T>1°C / s, the battery is in thermal runaway.

5. The method for monitoring thermal runaway of sodium ion batteries based on multi-parameter graded early warning according to claim 1 is characterized in that: The thermal runaway process is divided into three stages: the first stage is the collapse of the positive electrode structure, releasing a large amount of heat and oxygen; the second stage is the rupture of the battery shell, and the strain and gas concentration signals suddenly change; the third stage is the complete decomposition of the battery diaphragm, causing serious internal short circuit and rapid temperature rise.

6. The method for monitoring thermal runaway of sodium ion batteries based on multi-parameter graded early warning according to claim 1, characterized in that: The graded warning includes: using the change of surface strain when the battery expands for warning; warning of thermal runaway by detecting early exhaust; and using traditional voltage and temperature signals for warning.

7. The method for monitoring thermal runaway of sodium ion batteries based on multi-parameter graded early warning according to claim 1, characterized in that: The formula for the thermal runaway risk assessment coefficient is: Where V is the voltage drop percentage and T is the temperature rise rate.

8. The method for monitoring thermal runaway of sodium ion batteries based on multi-parameter graded early warning according to claim 1, characterized in that: The BMS system achieves real-time monitoring and automatic early warning of the battery status by comparing various parameters in the battery pack with set thresholds.

9. The method according to any one of claims 1 to 9, characterized in that: The method is applicable to different types of sodium ion batteries, including but not limited to soft-pack batteries, hard-shell batteries and cylindrical batteries.

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