A method for monitoring the health status of sodium batteries based on optical fiber sensors

Abstract

The present invention discloses a method for monitoring the health status of a sodium battery based on an optical fiber sensor, comprising: placing two optical fiber sensors in the middle empty layer of a wound battery core and fixing them, performing the first liquid injection packaging after assembly to obtain a built-in optical fiber sodium ion battery; performing high-temperature closed-end formation after pretreatment of the built-in optical fiber sodium ion battery to obtain a formed battery, collecting current, voltage, and capacity data during the formation, and collecting the battery formation stress strain and heat generation data at the same time; cutting off the air bag of the formed battery, and performing a secondary liquid injection, placing it in a constant temperature box after shelving, and performing a constant current constant voltage charge and discharge test using a constant current charge and discharge instrument; real-time detection and collection of current, voltage, capacity, stress strain and heat generation during the circulation of the secondary liquid injection sodium ion battery; comparing the two collected data to accurately evaluate the health status of the sodium ion battery. The present invention realizes battery health status evaluation and safety improvement by analyzing the sodium battery formation working condition and in-situ detection of the internal real working condition during the circulation.

Description

Technical Field

[0001] The invention belongs to the technical field of battery detection, and in particular relates to a method for monitoring the health status of a sodium battery based on an optical fiber sensor. Background Art

[0002] Lithium-ion batteries are widely used in electric vehicles, electronic devices, and energy storage systems. With the rapid development and increasing demand in these fields, the demand for lithium resources is also rising. However, the current growth in lithium production cannot fully meet the growing consumption. The reason is that lithium resources are very limited and unevenly distributed, and the lithium resources distributed in the salt lake areas in the western region cannot be developed in winter, and the supply-demand relationship is further deteriorated. In order to cope with the shortage of lithium resources, it is necessary to explore alternative energy storage technologies and battery materials, such as potassium ion batteries, magnesium ion batteries, and sodium ion batteries. Among the many technologies, sodium ion batteries are the leading candidates for replacing lithium ion battery technology. They work in the same way as lithium batteries and have similar battery designs and material systems. At the same time, sodium batteries can be mass-produced on the existing manufacturing basis of lithium batteries, making them a powerful alternative power source for electric vehicles and energy storage systems. In addition, sodium ion batteries cost about 30-50% less than lithium ion batteries and have very promising application potential.

[0003] The mainstream negative electrode of sodium-ion batteries uses hard carbon. There is no obvious voltage platform during the charge and discharge process, nor is there an obvious boundary between sodium ion embedding and metallic sodium precipitation. Therefore, there is a dynamic uncertainty in its electrochemical reaction, which is affected by multiple related parameters. Among them, the performance of the solid electrolyte membrane (SEI membrane) has a direct impact on the health of the battery (such as cycle life and voltage decay). Therefore, real-time monitoring of changes inside sodium-ion batteries, especially the evolution of the interface on the negative electrode side, has become a technical direction that has received much attention in the field of life and safety of sodium-ion batteries.

[0004] At present, the assessment of the health status of secondary batteries mainly relies on electrochemical detection and ultrasonic detection technology. Patent CN116265934A discloses a method for detecting battery lithium deposition, which combines electrochemical impedance testing and ultrasonic scanning testing technology to determine the actual operating conditions of the battery by comparing with the established standard database. However, ultrasonic detection has some limitations, and its accuracy is only at the centimeter level, making it difficult to accurately reflect the evolution of actual interface conditions under signal decoupling. At the same time, its detection accuracy is affected by the actual battery configuration, and the compaction density of the multi-layer electrode sheets inside the battery will interfere with its signal. Since electrolyte infiltration is required during normal battery assembly, there will be normal gaps between the multi-layer pole pieces, and the ultrasonic system can only measure the compaction system, so a simple ultrasonic system is difficult to reflect the actual working conditions inside the battery.

[0005] At present, the industry has not disclosed any relevant evaluation methods for the health status of sodium-ion secondary batteries. In order to improve the accuracy of sodium-ion secondary battery health detection, it is necessary to overcome the shortcomings of ultrasonic detection technology and adopt a combination of multiple electrochemical testing methods, but this also increases the complexity and uncertainty of the monitoring method. Therefore, for the health assessment of sodium-ion secondary batteries, further research and improvement of detection technology are needed to improve the accuracy and reliability of the assessment and provide a more reliable basis for the evaluation of battery performance and safety. Summary of the invention

[0006] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0007] In view of the above problems and / or the problems existing in the prior art, the present invention is proposed.

[0008] Therefore, the purpose of the present invention is to overcome the deficiencies in the prior art and provide a method for monitoring the health status of a sodium battery based on an optical fiber sensor.

[0009] In order to solve the above technical problems, the present invention provides the following technical solutions: an optical fiber temperature sensor and an optical fiber pressure sensor are embedded and fixed in situ in the middle empty layer of a wound sodium ion battery cell, and a first liquid injection package is performed after assembly to obtain a built-in optical fiber sodium ion battery;

[0010] The built-in fiber-optic sodium-ion battery was placed for 18 to 32 hours and then closed-cup formation was performed at high temperature to obtain a formed battery. After two weeks of circulation, stress and temperature difference data were collected to obtain the first set of data.

[0011] After the secondary liquid injection, the formed battery is placed aside for 18 to 32 hours and then subjected to constant current and constant voltage charge and discharge test, and stress and temperature difference data are collected to obtain the second set of data;

[0012] The electrochemical data of the wound sodium-ion battery body is the third set of data;

[0013] By comparing the error levels between each set of data, the health status of the sodium battery can be monitored.

[0014] As a preferred solution of the method for monitoring the health status of a sodium battery based on an optical fiber sensor of the present invention, the monitoring of the health status of the sodium battery includes:

[0015] Two groups of data were analyzed separately: the first group, stress mutation and temperature mutation comparison, if the stress mutation is abnormal, the formation effect is not good; the second group, theoretically there is no stress and temperature mutation peak, if there is, there is a problem with the formation;

[0016] When the error between the stress, strain, or temperature difference of the second set of data and the first set of data is greater than 5%, it indicates that the battery health is impaired.

[0017] As a preferred solution of the method for monitoring the health status of a sodium battery based on an optical fiber sensor according to the present invention, the monitoring further comprises collecting stress and strain of the battery under 100% charging state during the formation process. If the heat generation data has no mutation sites, it indicates that there is no sodium precipitation phenomenon during the formation period and the solid interface film is intact.

[0018] As a preferred solution of the sodium battery health status monitoring method based on optical fiber sensor described in the present invention, the structure of the built-in optical fiber sodium ion battery includes a battery body, including a positive electrode sheet and a negative electrode sheet arranged on the battery body, a polyethylene diaphragm arranged on the surface of the battery body, and an optical fiber temperature sensor and an optical fiber pressure sensor wrapped inside the battery body.

[0019] As a preferred solution of the sodium battery health monitoring method based on optical fiber sensor of the present invention, the first liquid injection packaging is sodium ion electrolyte, and the injection volume is 1.0Ahg -1 .

[0020] As a preferred solution of the method for monitoring the health status of sodium batteries based on optical fiber sensors of the present invention, the temperature of the high-temperature closed-end formation is 45° C., and the formation current is 0.1C.

[0021] As a preferred solution of the method for monitoring the health status of a sodium battery based on an optical fiber sensor according to the present invention, the number of formation cycles of the high-temperature closed-cup formation is 2 weeks.

[0022] As a preferred solution of the sodium battery health monitoring method based on optical fiber sensor of the present invention, the injection volume of the secondary injection is 0.5Ahg -1 .

[0023] As a preferred solution of the method for monitoring the health status of a sodium battery based on an optical fiber sensor of the present invention, the test temperature of the constant current and constant voltage charge and discharge test is 25°C.

[0024] As a preferred solution of the method for monitoring the health status of a sodium battery based on an optical fiber sensor according to the present invention, the charging current is set to 0.2C, the discharging current is set to 0.5C, and the rest time after a single charge / discharge is 10 minutes.

[0025] Beneficial effects of the present invention:

[0026] The present invention overcomes the defects of the existing sodium ion battery detection technology that it is unable to detect the real working conditions inside the sodium ion battery in real time in situ, and the measurement accuracy is low, which is easy to cause misjudgment and other problems. It provides a sodium battery health status monitoring method based on optical fiber sensor, realizes the analysis of sodium ion battery formation conditions and the in-situ detection of the real internal conditions during circulation, and finally realizes the health status evaluation and safety improvement of the sodium ion battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0028] Figure 1 This is the charge and discharge curve of the fiber-optic sodium-ion battery cycle.

[0029] Figure 2 The charge and discharge capacity-efficiency curve of the fiber-optic sodium-ion battery cycle.

[0030] Figure 3 This is the fiber optic sodium ion battery soft pack detection process.

[0031] Figure 4 Schematic diagram of the structure of fiber-optic sodium-ion battery. DETAILED DESCRIPTION

[0032] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the embodiments of the specification.

[0033] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0034] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0035] The fiber optic pressure sensor used in the present invention is FISOFOP-M260;

[0036] The optical fiber temperature sensor used in the present invention is LUNAOBR4600.

[0037] Example 1

[0038] Reference Figure 1 , an optical fiber temperature sensor and an optical fiber pressure sensor are embedded and fixed in situ in the middle empty layer of the wound sodium ion battery cell, and a built-in optical fiber sodium ion battery is assembled, specifically:

[0039] Preparation of positive electrode:

[0040] Prepare aluminum foil and coat it with sodium iron phosphate sodium ion battery material, the positive electrode conductive carbon is superP, an oily binder is used, and the coating mass ratio is 95:2.5:2.5;

[0041] The coated aluminum foil is dried and then subjected to secondary roll forming to obtain a positive electrode sheet;

[0042] Among them, the single-sided surface loading of aluminum foil is 9 mg cm -2 ;

[0043] Preparation of negative electrode sheet:

[0044] Prepare copper foil and coat it with hard carbon material, the negative electrode conductive carbon is acetylene black, and a water-based binder is used, with a coating mass ratio of 90:5:5;

[0045] The coated copper foil is dried and then subjected to secondary roll forming to obtain a negative electrode sheet;

[0046] Among them, the single-sided surface loading of copper foil is 6.5mgcm -2 , N / P ratio is 1.08;

[0047] The optical fiber temperature sensor 3 and the optical fiber pressure sensor 4 are bonded and fixed by using potting glue;

[0048] Seal the additional casting holes of the aluminum shell;

[0049] And inject sodium ion electrolyte 0.5Ahg -1 , a battery body 1 with a capacity of 2.8 Ah is obtained.

[0050] Example 2

[0051] This embodiment provides a sodium battery health status monitoring method based on optical fiber sensor on the basis of embodiment 1, specifically:

[0052] 1) The battery body 1 is placed for 24 hours and then fully activated in a constant temperature box at a temperature of 45° C. The formation adopts a constant current and constant voltage charge and discharge mode, the formation current is 0.1C, the operating voltage is 3.8V, the constant voltage cutoff condition in the constant current and constant voltage charging is that the current is less than 0.1A, and the placement time in the formation charge and discharge is 10 minutes. After two weeks of circulation, stress and temperature difference data are collected to obtain the first set of data;

[0053] 2) Fill the battery body 1 with 0.5Ahg of liquid -1 After another 24 hours of storage, the battery was subjected to constant current and constant voltage charge and discharge test. The formation current was 0.1C, the operating voltage was 3.8V, and the temperature was 25°C. During the constant current and constant voltage test, the battery stress and temperature difference data were collected synchronously. The collection time accuracy was 2s, and the second set of data was obtained.

[0054] 3) The electrochemical data of the battery body 1 is set as the third set of data.

[0055] The four sets of data are compared and the results are shown in the following table:

[0056] Table 1

[0057]

[0058] According to Table 1, during the cycle, the stress-strain and temperature difference data errors between the second group of data and the first group of data are less than 5%, and there are no obvious mutations in stress and temperature, indicating that at the cutoff test point, the system has no sodium precipitation safety risk, and the interface remains intact, which is consistent with the results of the third group of data.

[0059] Then the square battery was degassed and refilled with liquid for packaging. After aging, the fiber-optic sodium-ion battery was tested in situ in a 25°C constant temperature box. The actual electrochemical data results and the corresponding fiber-optic data results were analyzed. Figure 1 and attached Figure 2 The curve of the built-in optical fiber dual sodium iron phosphate battery in this example is shown, indicating that the battery operates well overall and its healthy life cycle is up to 400 weeks.

[0060] Example 3

[0061] In this embodiment, the battery main body samples obtained in embodiment 1 are selected for monitoring. The monitoring method is the same as that in embodiment 2, and four groups of data of this embodiment are obtained.

[0062] The four sets of data are compared and the results are shown in the following table:

[0063] Table 2

[0064]

[0065] Example 4

[0066] In this embodiment, the battery main body samples obtained in embodiment 1 are selected for monitoring. The monitoring method is the same as that in embodiment 2, and four groups of data of this embodiment are obtained.

[0067] The four sets of data are compared and the results are shown in the following table:

[0068] Table 3

[0069]

[0070] By comparing the results of Tables 2 to 3 with Table 1, it can be seen that the experimental results of Examples 3 to 4 are slightly different from those of Example 2, but in the cycle, the stress-strain and temperature difference data errors between the second set of data and the first set of data are less than 5%, and there are no obvious mutations in stress and temperature, indicating that at the cutoff test point, the system has no sodium precipitation safety risk, and the interface remains intact, which is consistent with the results of the third set of data and the monitoring results of Example 2.

[0071] Comparative Example 1

[0072] Comparative Example 1 is based on Example 2. The difference between Comparative Example 1 and Example 2 is that the temperature in step 1) is adjusted to 60° C. The remaining monitoring methods are the same as those in Example 2, and four sets of data for Comparative Example 1 are obtained.

[0073] The four sets of data are compared and the results are shown in the following table:

[0074] Table 4

[0075]

[0076] According to Table 4, it can be seen that there is an obvious mutation point at 100% SOC in the first two weeks of formation, and there is an obvious mutation phenomenon in stress and temperature during the period of 0% to 100% SOC in the second week of formation. During the cycle, the stress-strain and temperature difference data errors of the second set of data and the first set of data are greater than 5%, indicating that the health of the battery is impaired and the system has a safety risk of sodium precipitation. This is because as the formation temperature increases, the battery will expand. If the expansion coefficients of different parts are different, it will lead to uneven distribution of stress, and the increase in temperature will increase the thermal conductivity rate inside the material, resulting in more drastic changes in the temperature gradient. Therefore, as the temperature increases, stress mutations and temperature difference mutations will increase, resulting in inaccurate monitoring results.

[0077] Comparative Example 2

[0078] Comparative Example 2 is based on Example 2. The difference between Comparative Example 2 and Example 2 is that the temperature in step 1) is adjusted to 30°C, and the remaining monitoring methods are the same as Example 2, and four sets of data of Comparative Example 1 are obtained.

[0079] The four sets of data are compared and the results are shown in the following table:

[0080] Table 5

[0081]

[0082] According to Table 5, it can be seen that there is an obvious mutation point at 100% SOC in the first two weeks of formation, and there is an obvious mutation phenomenon in stress temperature during the period of 0% to 100% SOC in the second week of formation. During the cycle, the stress-strain data error between the second set of data and the first set of data is greater than 5%, indicating that the health of the battery is impaired and the system has a safety risk of sodium precipitation. This is because when the formation temperature decreases, the material will shrink. If the shrinkage coefficients of different parts are different, it will lead to uneven distribution of stress, and the temperature reduction will reduce the heat conduction rate inside the material, resulting in a slowdown in the change of temperature gradient, which makes the temperature difference mutation smaller. Therefore, as the temperature decreases, the stress mutation will increase, resulting in inaccurate monitoring results.

[0083] Comparative Example 3

[0084] Comparative Example 3 is based on Example 2. The difference between Comparative Example 3 and Example 2 is that the injection amount in step 2) is adjusted to 5Ahg -1 The remaining monitoring methods are the same as those in Example 2, and four sets of data for Comparative Example 3 are obtained.

[0085] The four sets of data are compared and the results are shown in the following table:

[0086] Table 6

[0087]

[0088] According to Table 6, it can be seen that there is an obvious mutation point at 100% SOC in the first two weeks of formation, and there is an obvious mutation phenomenon in stress temperature during the period of 0% to 100% SOC in the second week of formation. During the cycle, the stress-strain data error between the second set of data and the first set of data is greater than 5%, indicating that at the cutoff test point, the system has a sodium precipitation safety risk. This is because increasing the injection volume will increase the liquid capacity inside the battery, thereby increasing the pressure inside the battery, resulting in an increase in stress mutations. At the same time, increasing the injection volume will increase the liquid capacity inside the battery, thereby increasing the heat capacity inside the battery, reducing the temperature difference mutation, and ultimately causing errors in the monitoring results.

[0089] Comparative Example 4

[0090] Comparative Example 4 is based on Example 2. The difference between Comparative Example 4 and Example 2 is that the injection amount in step 2) is adjusted to 5Ahg -1 The remaining monitoring methods are the same as those in Example 2, and four sets of data of Comparative Example 4 are obtained.

[0091] The four sets of data are compared and the results are shown in the following table:

[0092] Table 7

[0093]

[0094]

[0095] According to Table 7, it can be seen that there is an obvious mutation point at 100% SOC in the first two weeks of formation, and there is an obvious mutation phenomenon in stress temperature during the period of 0% to 100% SOC in the second week of formation. During the cycle, the temperature difference mutation data error between the second set of data and the first set of data is greater than 5%, indicating that the system has a sodium precipitation safety risk at the cutoff test point. This is because reducing the injection volume will reduce the liquid capacity inside the battery, thereby reducing the pressure inside the battery, resulting in a reduction in stress mutation. At the same time, reducing the injection volume will reduce the liquid capacity inside the battery, thereby reducing the heat capacity inside the battery, resulting in an increase in temperature difference mutation, and ultimately leading to errors in the monitoring results.

[0096] Comparative Example 5

[0097] Comparative Example 5: Three groups of battery main body samples obtained in Example 1 were selected to detect the sonic characteristics of the sodium ion battery by ultrasound to evaluate the battery life, specifically:

[0098] 1) Place the sodium ion battery on the workbench of the ultrasound scanner;

[0099] 2) Align the probe of the ultrasound scanner with the battery and connect the ultrasound scanner to a computer or data recording device;

[0100] 3) Perform regular ultrasonic scans and record the ultrasonic data inside the battery.

[0101] The measurement results are shown in the following table:

[0102] Table 8

[0103]

[0104] According to Table 6, the same batch of samples have different experimental results under the results of ultrasonic scanning. This is because the ultrasonic system can only measure the compaction system, so the simple ultrasonic system is difficult to reflect the actual working conditions inside the battery. Compared with the current mainstream ultrasonic detection, even if the ultrasonic detection is continuously imaged, its data is still a mixed value of the overall distribution of the battery cell, and the internal safety failure of the battery often occurs gradually from point to surface. Therefore, ultrasonic detection has a lag and cannot truly reflect the internal working conditions of the battery. As the optical fiber detection itself is fixed inside the battery, all its detection values ​​reflect the real values ​​inside the battery. It has extremely high sensitivity to the changes in internal working conditions caused by the abnormal position of local points inside the battery, and it is more suitable for continuous monitoring of battery safety.

[0105] When monitoring the health of the sodium ion battery, the present invention monitors the stress temperature inside the battery in real time through an optical fiber pressure sensor. Since a solid electrolyte membrane is generated on the hard carbon surface during battery formation, which is decomposed from the electrolyte, the process is exothermic and gas is produced at the same time, so there will be stress changes. When the sodium ion battery is formed and discharged, if the stress mutation is significantly higher than the temperature mutation, it means that the local gas production is too high at this time, and there may be a situation where the local formation film quality is not high and the solid interface film is discontinuous.

[0106] Since the negative electrode material of sodium-ion batteries has no obvious charging and discharging platform, it is impossible to directly determine the harm of sodium precipitation under low current through the fourth-order platform like graphite. However, sodium precipitation is a typical heat-generating process, and there is a solid interface film rupture and recombination process. This process produces a lot of gas, so the thermal changes and stress changes collected by the optical fiber temperature sensor and the optical fiber pressure sensor can determine whether it is sodium precipitation. When the battery is close to 100% SOC, if there is no stress mutation peak and temperature mutation peak at the same time, it means that the battery has no sodium precipitation phenomenon; if there is a stress mutation peak but no temperature mutation peak, there is sodium precipitation, because the thermal change may have a certain hysteresis; if there is a temperature mutation but no stress mutation, it means that the solid interface film of the battery is ruptured and reorganized, and the actual sodium precipitation still needs to be determined by the stress change at 100% SOC in the cycle.

[0107] The present invention uses an optical fiber temperature sensor and an optical fiber pressure sensor to perform real-time detection of battery data, thereby realizing sodium ion battery formation condition analysis and in-situ detection of the actual internal condition during circulation, and ultimately realizing sodium ion battery health status assessment and safety improvement. Especially under the conditions of Example 1, without the application of external stress, the optical fiber temperature sensor and the optical fiber pressure sensor have the highest accuracy, which effectively improves the accuracy of battery health status monitoring. Compared with the current mainstream ultrasonic detection, ultrasonic detection cannot be applied to processes with a large amount of gas production, and its signal will be seriously distorted, while the optical fiber is not affected by internal gas production and can still continuously collect data, showing the superiority of optical fiber detection.

[0108] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for monitoring the health status of a sodium battery based on an optical fiber sensor, characterized in that: include, An optical fiber temperature sensor and an optical fiber pressure sensor are embedded and fixed in situ in the middle empty layer of the wound sodium ion battery cell, and the first liquid injection packaging is performed after assembly to obtain a built-in optical fiber sodium ion battery; The built-in fiber-optic sodium-ion battery was placed for 18 to 32 hours and then closed-cup formation was performed at high temperature to obtain a formed battery. After two weeks of circulation, stress and temperature difference data were collected to obtain the first set of data. After the secondary liquid injection, the formed battery was placed aside for 18 to 32 hours and then subjected to constant current and constant voltage charge and discharge test. The charging current was set to 0.2C, the discharging current was set to 0.5C, and the placement time after a single charge / discharge was 10 minutes. Stress and temperature difference data were collected to obtain the second set of data. The electrochemical data of the wound sodium-ion battery body is the third set of data; By comparing the error levels between each set of data, the health status of the sodium battery can be monitored; The monitoring of the health status of the sodium battery includes: Two groups of data were analyzed separately: the first group, stress mutation and temperature mutation comparison, if the stress mutation is abnormal, the formation effect is not good; the second group, theoretically there is no stress and temperature mutation peak, if there is, there is a problem with the formation; When the error between the stress, strain, and temperature difference of the second set of data and the first set of data is greater than 5%, it indicates that the battery health is impaired; The monitoring also includes, During the formation process, the stress and strain of the battery under 100% charge state are collected. If there is no mutation site in the heat generation data, it means that there is no sodium precipitation during the formation period and the solid interface film is intact.

2. The method for monitoring the health status of a sodium battery based on an optical fiber sensor according to claim 1, characterized in that: The structure of the built-in optical fiber sodium ion battery comprises a battery body (1), a positive electrode sheet (2) and a negative electrode sheet (5) arranged on the battery body (1), a polyethylene diaphragm (6) arranged on the surface of the battery body (1), and an optical fiber temperature sensor (3) and an optical fiber pressure sensor (4) wrapped inside the battery body (1).

3. The method for monitoring the health status of a sodium battery based on an optical fiber sensor according to claim 1, characterized in that: The first injection packaging is sodium ion electrolyte, and the injection volume is 1.0Ah g -1 .

4. The method for monitoring the health status of a sodium battery based on an optical fiber sensor according to claim 1, characterized in that: The temperature of the high temperature closed-mouth forming is 45° C., and the forming current is 0.1C.

5. The method for monitoring the health status of a sodium battery based on an optical fiber sensor as claimed in claim 3, characterized in that: The high temperature closed-end forming cycle number is 2 weeks.

6. The method for monitoring the health status of a sodium battery based on an optical fiber sensor according to claim 1, characterized in that: The injection volume of the secondary injection is 0.5Ah g -1 .

7. The method for monitoring the health status of a sodium battery based on an optical fiber sensor according to claim 1, characterized in that: The test temperature of the constant current and constant voltage charge and discharge test is 25°C.

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