Battery analysis system based on magnetic field reflection detection technology of quantum magnetic sensor

Abstract

The invention provides a battery analysis system based on a magnetic field reflection detection technology of a quantum magnetic sensor, and the system comprises a magnetic field generation part which is opposite to a detected battery, and is used for generating a controllable magnetic field which is horizontal to the plane of the detected battery, so as to detect different layers in the detected battery; the quantum magnetic induction part and the magnetic field generation part are arranged on the same side, and the induction surface of the quantum magnetic induction part is opposite to the tested battery to collect the magnetic induction intensity of the reflected magnetic field reflected from different levels in the tested battery; the processing module controls the magnetic field generation component to generate different magnetic field characteristics; the working condition of the quantum magnetic induction part is controlled; receiving the magnetic induction intensity acquired by the quantum magnetic induction component, and performing signal processing on the magnetic induction intensity; and the analysis module analyzes internal defects and an aging mechanism of the tested battery based on the magnetic induction intensity processed by the processing module. According to the invention, the detected battery does not need to be in a charge-discharge state, interference of an environmental magnetic field does not need to be shielded, and internal defects and an aging mechanism of the battery can be nondestructively detected and analyzed.

Description

Technical Field

[0001] The present invention relates to the technical field of battery detection, and particularly to a battery analysis system based on a magnetic field reflection detection technology using a quantum magnetic sensor. Background Art

[0002] For the internal defect detection of batteries, especially lithium batteries, existing technical means include using X-rays, ultrasonic waves, thermal imaging, magnetic resonance, etc. for detection, as well as detecting by analyzing the electrochemical impedance spectrum of the battery, and weak magnetic detection, magnetic field gradient detection, and so on. However, these detection means all have some problems more or less, as follows:

[0003] 1. X-rays: The cost of detection equipment is high, and there is a radiation hazard.

[0004] 2. Ultrasonic waves: The detection results for batteries with complex shapes and uneven surfaces may be affected, and good coupling with the battery surface is required, and the detection operation is relatively complex.

[0005] 3. Thermal imaging: It can only detect surface temperature changes, has limited ability to detect defects in deeper positions inside the battery, and is greatly affected by the ambient temperature and heat dissipation conditions.

[0006] 4. Electrochemical impedance spectrum: The test results are greatly affected by factors such as the charge and discharge state and temperature of the battery, and professional equipment and data analysis capabilities are required.

[0007] 5. Magnetic resonance: The equipment is expensive, and the operation and maintenance costs are also high.

[0008] 6. Weak magnetic detection: The battery needs to be in a charge and discharge state, and it needs to be carried out in a strict electromagnetic shielding environment.

[0009] 7. Magnetic field gradient detection: Similar to weak magnetic detection, the battery needs to be in a charge and discharge state, and it needs to be carried out in a strict electromagnetic shielding environment.

[0010] In summary, the current non-destructive testing technologies are either expensive in equipment, limited in detection ability, or require contact. And the magnetic field-based detection technologies require the battery to be in a charge and discharge state and strict electromagnetic shielding to measure its weak magnetic field. Summary of the Invention

[0011] In order to overcome the defects existing in the above-mentioned prior art, the purpose of the present invention is to provide a battery analysis system based on a magnetic field reflection detection technology using a quantum magnetic sensor.

[0012] To achieve the above object of the present invention, the present invention provides a battery analysis system based on a magnetic field reflection detection technology using a quantum magnetic sensor, including:

[0013] A magnetic field generating component, which is arranged opposite to the battery under test, is used to generate a controllable magnetic field parallel to the plane of the battery under test, and the controllable magnetic field is used to detect different layers in the battery under test;

[0014] A quantum magnetic induction component, which is arranged on the same side as the magnetic field generating component, and the induction surface of the quantum magnetic induction component faces the battery under test, is used to collect the magnetic induction intensity of the reflected magnetic field reflected from different layers in the battery under test;

[0015] A processing module, its first output terminal is controllably connected to the input terminal of the magnetic field generating component. When detecting different layers in the battery under test, the processing module controls the magnetic field generating component to generate different magnetic field characteristics; the second output terminal of the processing module is connected to the control terminal of the quantum magnetic induction component to control the working conditions of the quantum magnetic induction component; the input terminal of the processing module is electrically connected to the output terminal of the quantum magnetic induction component, receives the magnetic induction intensity collected by the quantum magnetic induction component, and performs signal processing on it;

[0016] An analysis module, its input terminal is electrically connected to the output terminal of the processing module, and analyzes the internal defects and aging mechanism of the battery under test based on the magnetic induction intensity processed by the processing module.

[0017] Optionally, the magnetic field generating component is one of the following structures:

[0018] Structure 1: The magnetic field generating component includes two coils, the winding directions of the two coils are opposite, and the quantum magnetic induction component is located between the two coils;

[0019] Structure 2: The magnetic field generating component is a U-shaped coil or a C-shaped coil, and the quantum magnetic induction component is arranged inside the opening of the U-shaped coil or C-shaped coil.

[0020] Optionally, it further includes a sliding table, and the quantum magnetic induction component and the magnetic field generating component are arranged on the moving surface of the sliding table, and detect different layers in the battery under test point by point in a point-scanning manner, and obtain the magnetic induction intensity of the reflected magnetic field reflected from different layers in the battery under test point by point, or detect different layers in the battery under test row by row in a line-scanning manner, and obtain the magnetic induction intensity of the reflected magnetic field reflected from different layers in the battery under test row by row and layer by layer.

[0021] Optionally, the sliding table includes an X-axis slide rail and a Y-axis slide rail, and the quantum magnetic induction component and the magnetic field generating component move on the X-axis slide rail and the Y-axis slide rail synchronously and without priority, and detect different layers in the battery under test point by point in a point-scanning manner, and obtain the magnetic induction intensity of the reflected magnetic field reflected from different layers in the battery under test point by point.

[0022] Optionally, the sliding table includes an X-axis slide rail or a Y-axis slide rail, and the quantum magnetic induction component includes a sensor array composed of a plurality of quantum magnetic sensors;

[0023] The quantum magnetic induction component and the magnetic field generating component move synchronously along the X-axis or Y-axis on the X-axis slide rail or Y-axis slide rail, and detect different layers in the battery under test row by row along the length or width direction of the battery under test, and obtain the magnetic induction intensity of the reflected magnetic field reflected from different layers in the battery under test row by row.

[0024] Optionally, the sliding table includes a Z-axis slide rail, and the quantum magnetic induction component and the magnetic field generating component move synchronously along the Z-axis to adjust the vertical distance between the quantum magnetic induction component, the magnetic field generating component and the battery under test.

[0025] Optionally, the analysis module performs one or any combination of the following analyses:

[0026] Combining the magnetic induction intensities of the reflected magnetic fields reflected from different layers in the battery under test to generate a magnetic field image of the battery under test, and displaying the magnetic induction intensity of the reflected magnetic field of a certain layer inside the entire battery under test in a two-dimensional form, and / or displaying the magnetic induction intensity of the reflected magnetic field inside the entire battery under test in a three-dimensional form;

[0027] Using deep learning technology to automatically identify, label and measure the internal defects and aging of the battery;

[0028] The generated magnetic field image is manually identified, labeled and measured by professionals for the internal defects and aging mechanism of the battery.

[0029] Optionally, a database is stored in the analysis module, and the database includes various internal defects of various batteries and the corresponding magnetic induction intensity distribution data reflected from the battery under test collected by the battery analysis system; and various aging mechanisms of various batteries and the corresponding magnetic induction intensity distribution data reflected from the battery under test collected by the battery analysis system.

[0030] Optionally, the processing module includes:

[0031] An acquisition circuit, whose input end is electrically connected to the output end of the quantum magnetic induction component, and is used to receive the magnetic induction intensity collected by the quantum magnetic induction component;

[0032] A processor, whose input end is electrically connected to the output end of the acquisition circuit, and performs signal processing on the magnetic induction intensity received from the acquisition circuit; its output end is connected to the input end of the drive circuit, generates an electrical signal for controlling the working conditions of the quantum magnetic induction component and an electrical signal for controlling the magnetic field generating component to generate different magnetic field characteristics, and sends them to the drive circuit;

[0033] A drive circuit, whose input end is electrically connected to the output end of a processor, and whose first output end is electrically connected to the input end of a magnetic field generating component, provides drive current for the magnetic field generating component according to an electrical signal for controlling the magnetic field generating component to generate different magnetic field characteristics; its second output end is connected to the control end of a quantum magnetic induction component, and provides bias current for the quantum magnetic induction component according to an electrical signal for controlling the operating conditions of the quantum magnetic induction component.

[0034] Optionally, the processing module further includes an analog front-end circuit;

[0035] The input end of the analog front-end circuit is electrically connected to the output end of the quantum magnetic induction component, and is used to capture and process the voltage signal output by the quantum magnetic induction component, and extract an effective voltage signal reflecting the change in magnetic field induction intensity as a magnetic induction intensity signal; the output end of the analog front-end circuit is electrically connected to the input end of the acquisition circuit, and the acquisition circuit receives the magnetic induction intensity signal and converts it from an analog signal to a digital signal.

[0036] The beneficial effects of the present invention are as follows:

[0037] The present invention uses a quantum magnetic sensor to detect a weak magnetic field with a magnetic induction intensity as low as the nanotesla level (10 -9 T), and the cost is low.

[0038] The magnetic field detected by the present invention is an externally built magnetic field of the magnetic field generating component, and the magnetic field intensity, direction and frequency are controlled. It is not necessary for the battery under test to be in a charging or discharging state, and it is not sensitive to environmental magnetic fields and noise, and there is no need to shield the interference of environmental magnetic fields.

[0039] The present invention can present the magnetic field induction intensity after reflection of a certain layer of the battery under test in the form of a two-dimensional image, intuitively displaying defects.

[0040] The present invention can present the magnetic field induction intensity after reflection of each layer inside the battery under test in the form of a three-dimensional image, intuitively displaying defects.

[0041] The present invention adopts a reflection detection technology, which can quickly locate all defects at different levels inside the battery.

[0042] The magnetic field characteristics generated by the magnetic field generating component of the present invention can be changed according to the battery under test to achieve the best detection effect.

[0043] The present invention can be applied to the battery industry for non-destructively detecting and analyzing the internal defects and aging mechanisms of batteries.

[0044] The present invention can automatically identify, label and measure the internal defects and aging mechanisms of batteries by means of artificial intelligence such as deep learning; it also supports the identification, label and measurement of the internal defects and aging mechanisms of batteries by industry experts.

[0045] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present invention. Brief Description of the Drawings

[0046] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0047] Figure 1 is a schematic structural diagram of the first embodiment, where the solid lines in the figure represent the direct circuit connections of the components, and the dashed lines represent the magnetic force lines of the magnetic field. Detailed Description of the Embodiments

[0048] Embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described by referring to the drawings below are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0049] In the description of the present invention, unless otherwise specified and defined, it should be noted that the terms "mounted", "connected", and "coupled" should be understood in a broad sense. For example, it may be a mechanical connection or an electrical connection, or may be the internal communication of two elements. It may be directly connected or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0050] The First Embodiment

[0051] As Figure 1 shown, the present invention provides a battery analysis system based on the magnetic field reflection detection technology of a quantum magnetic sensor, including: a magnetic field generating component, a quantum magnetic induction component, a processing module, and an analysis module.

[0052] Among them, the magnetic field generating component is disposed opposite to the battery under test, and is used to generate a controllable magnetic field parallel to the plane of the battery under test. The controllable magnetic field is used to detect different layers inside the battery under test, and a fixed distance needs to be maintained between the magnetic field generating component and the battery under test; the quantum magnetic induction component is disposed on the same side as the magnetic field generating component, and the induction surface of the quantum magnetic induction component faces the battery under test, and is used to collect the magnetic induction intensity of the reflected magnetic field reflected from different layers inside the battery under test. The relative positions among the magnetic field generating component, the battery under test, and the quantum magnetic induction component are set such that the magnetic field generated by the magnetic field generating component is in the tangential direction of the quantum magnetic induction component. The quantum magnetic induction component cannot sense the magnetic field emitted by the magnetic field generating component, and can only sense the reflected magnetic field reflected by the battery under test. The first output end of the processing module is controllably connected to the input end of the magnetic field generating component. When detecting different layers inside the battery under test, the processing module controls the magnetic field generating component to generate different magnetic field characteristics; the second output end of the processing module is connected to the control end of the quantum magnetic induction component to control the working conditions of the quantum magnetic induction component; the input end of the processing module is electrically connected to the output end of the quantum magnetic induction component to receive the magnetic induction intensity collected by the quantum magnetic induction component and perform signal processing on it; the input end of the analysis module is electrically connected to the output end of the processing module, and analyzes the internal defects and aging mechanism of the battery under test based on the magnetic induction intensity processed by the processing module.

[0053] In this embodiment, the magnetic field generating component includes two coils, the winding directions of the two coils are opposite, the quantum magnetic induction component is located between the two coils, and the three are closely arranged to form an integral body. The processing module controls the two coils to generate a controllable magnetic field.

[0054] Of course, the magnetic field generating component can also be a U-shaped coil or a C-shaped coil, and the quantum magnetic induction component is disposed inside the opening of the U-shaped coil or C-shaped coil, and the two are closely arranged to form an integral body.

[0055] In this embodiment, the working conditions of the quantum magnetic induction component, such as the magnitude and frequency of the bias current, can be changed according to the model, parameters, etc. of the battery under test to achieve the optimal detection effect. The magnetic field characteristics generated by the magnetic field generating component are changed according to different layers inside the battery under test. The magnetic field frequencies and / or magnetic induction intensities required to detect different layers inside the battery under test are different to achieve the optimal detection effect. The magnetic field characteristics include: the magnetic induction intensity or frequency of the magnetic field, and the magnetic field characteristics are determined by the magnitude and frequency of the current on the coil. The magnetic field generating component and the quantum magnetic induction component are disposed on the detection table. Specifically, a three-axis sliding table is disposed on the detection table, including an X-axis slide rail, a Y-axis slide rail, and a Z-axis slide rail. The quantum magnetic induction component and the magnetic field generating component are disposed on the three-axis sliding table, and the quantum magnetic induction component and the magnetic field generating component move synchronously on the X-axis slide rail, Y-axis slide rail, and Z-axis slide rail of the three-axis sliding table.

[0056] When detecting different batteries, the quantum magnetic induction component and the magnetic field generating component can be synchronously moved along the Z-axis to adjust the vertical distance between the quantum magnetic induction component, the magnetic field generating component and the battery to be measured.

[0057] During detection, the quantum magnetic induction component and the magnetic field generating component are synchronously moved on the X-axis slide rail and the Y-axis slide rail without priority. That is, they can move along the X-axis direction first and then along the Y-axis direction, or they can move along the Y-axis direction first and then along the X-axis direction. The different layers inside the battery under test are detected point by point in a point scanning manner, and the magnetic induction intensity of the reflected magnetic field reflected from the different layers inside the battery under test is obtained point by point. The number of scanning points determines the detection accuracy. The three-axis slide table is connected to the processing module in a controlled manner, and the processing module controls the movement of the active surface of the three-axis slide table on the plane of the battery under test. The specific structure of the three-axis slide table can adopt the existing conventional structure, and the positional relationship between the quantum magnetic induction component, the magnetic field generating component and the three-axis slide table also adopts the conventional method, as long as it is ensured that the quantum magnetic induction component and the magnetic field generating component can move synchronously on the X-axis slide rail, the Y-axis slide rail and the Z-axis slide rail, which will not be elaborated here.

[0058] This embodiment is applicable to the situation where the quantum magnetic induction component can only obtain the magnetic induction intensity reflected from one point or a small number of points of the battery under test at a time. For example, the quantum magnetic induction component has only one quantum magnetic sensor.

[0059] Applying current to the coil can generate a magnetic field, and the magnetic induction intensity of the magnetic field is proportional to the coil current. In order to detect various inner layer battery defects and failure mechanisms, the processing module applies an alternating current with a frequency of 0 Hz to 10 MHz to the coil of the magnetic field generating component to form an alternating magnetic field of 0 Hz to 10 MHz, which can be specifically determined according to the model, parameters, etc. of the battery under test. The distance between the magnetic field generating component and the battery under test is not greater than 1 centimeter. In order to achieve nano-Tesla (10 -9For the magnetic field response of the quantum magnetic sensor (T), the processing module controls the bias current / voltage frequency of the quantum magnetic sensor to be from 0 Hz to 100 kHz to improve the signal-to-noise ratio of the effective signal output by the quantum magnetic sensor. This is achieved through the processor and the drive circuit in the processing module. Specifically, the processor can be a single-chip microcomputer, a microprocessor, an FPGA, or a DSP, etc. Its output terminal is connected to the input terminal of the drive circuit, generating an electrical signal for controlling the working conditions of the quantum magnetic induction component and an electrical signal for controlling the magnetic field generating component to generate different magnetic field characteristics, and sending them to the drive circuit; the drive circuit is composed of operational amplifiers. Here, a conventional application circuit can be used. Its input terminal is electrically connected to the output terminal of the processor. Its first output terminal is electrically connected to the input terminal of the magnetic field generating component, providing a drive current for the magnetic field generating component according to the electrical signal for controlling the magnetic field generating component to generate different magnetic field characteristics; its second output terminal is connected to the control terminal of the quantum magnetic induction component, providing a bias current for the quantum magnetic induction component according to the electrical signal for controlling the working conditions of the quantum magnetic induction component.

[0060] The processor is controllably connected to the control terminal of the three-axis sliding table, controlling the quantum magnetic induction component and the magnetic field generating component to move synchronously and without precedence on the X-axis slide rail and the Y-axis slide rail, so that the magnetic field generating component detects different levels inside the battery to be measured in a point-scanning manner, and the quantum magnetic induction component obtains the magnetic field signals of the reflected magnetic fields reflected from different levels inside the battery to be measured point by point. Here, the number of scanning points determines the detection accuracy. In this embodiment, the different levels inside the battery to be measured refer to the different levels of the battery to be measured in the Z-axis direction. When detecting point by point, each point position of the battery to be measured is detected for the different levels in the Z-axis direction at that point position. Specifically, it is detected by controlling the magnetic field generating component to generate different magnetic field characteristics through the processing module.

[0061] After the quantum magnetic induction component collects the magnetic induction intensity of the reflected magnetic field reflected from the battery to be measured, it is obtained and processed by the analog front-end circuit in the processing module. Specifically, the analog front-end circuit is composed of an instrumentation amplifier, an operational amplifier, a phase-sensitive detector, and a low-pass filter. The input terminal of the analog front-end circuit is electrically connected to the output terminal of the quantum magnetic induction component, successively capturing and processing the voltage signal output by the quantum magnetic induction component through the instrumentation amplifier, the operational amplifier, the phase-sensitive detector, and the low-pass filter, filtering out the noise interference therein, and extracting the effective voltage signal reflecting the change in the magnetic induction intensity of the magnetic field as the magnetic induction intensity signal. The instrumentation amplifier, the operational amplifier, the phase-sensitive detector, and the low-pass filter all adopt conventional application circuits.

[0062] The output end of the analog front-end circuit is electrically connected to the input end of the acquisition circuit in the processing module. The acquisition circuit is composed of an analog-to-digital converter. The acquisition circuit receives the magnetic induction intensity signal and converts it from an analog voltage quantity to a digital voltage quantity. The input end of the processor is electrically connected to the output end of the acquisition circuit, receives the digital voltage quantity signal sent by the acquisition circuit as the magnetic induction intensity, and performs signal processing. In this embodiment, fast Fourier transform, digital filtering, digital detection, etc. are adopted to further improve the signal-to-noise ratio of the effective signal.

[0063] The analysis module includes a host computer. The host computer acquires the magnetic induction intensity output by the front-end processing module, and combines the magnetic induction intensities of the reflected magnetic fields reflected by different layers inside the battery under test detected at each scanning point to generate the magnetic field image data of the battery under test, and uses a display component to display the magnetic induction intensity of the reflected magnetic field inside the entire battery under test. Since different magnetic field characteristics correspond to different internal layers of the battery, the magnetic field image data of a certain layer inside the battery under test can be combined to display the magnetic induction intensity of the reflected magnetic field of a certain layer inside the entire battery under test in a two-dimensional form; or the magnetic field image data of all internal layers of the battery under test can be combined to be displayed in the form of a three-dimensional image.

[0064] The analysis module stores a database, which includes various internal defects of various batteries and the magnetic induction intensity distribution data of the reflected magnetic fields reflected from the battery under test collected by using this battery analysis system corresponding thereto; and various aging mechanisms of various batteries and the magnetic induction intensity distribution data of the reflected magnetic fields reflected from the battery under test collected by using this battery analysis system corresponding thereto.

[0065] The host computer can be built-in with various common defect models of various batteries after deep learning using the above database, and can automatically identify, label, and measure the internal defects and aging mechanisms of the battery.

[0066] The host computer can also send the generated magnetic field image to a third party for professionals to identify, label, and measure the internal defects and aging mechanisms of the battery.

[0067] Here, the identification, labeling, and measurement can be for the two-dimensional magnetic field image of a certain layer inside the battery under test, or for the three-dimensional magnetic field image of the whole inside the battery under test.

[0068] Embodiment 2

[0069] This application also provides another battery analysis system based on the magnetic field reflection detection technology of quantum magnetic sensors. This embodiment is roughly the same as Embodiment 1, and the difference is that: the quantum magnetic induction component is a sensor array composed of multiple quantum magnetic sensors.

[0070] The length and width of the plane of the battery under test are correspondingly arranged with the X-axis slide rail and the Y-axis slide rail. During the detection, the quantum magnetic induction component and the magnetic field generating component move synchronously along the X-axis or Y-axis on the X-axis slide rail or the Y-axis slide rail, and scan and detect different layers inside the battery under test row by row along the length or width direction of the plane of the battery under test. The magnetic induction intensity of the reflected magnetic field of a certain layer of the battery under test detected is displayed in the form of an image. Each layer corresponding to each row of the battery under test is traversed and detected, and the magnetic induction intensity of its reflected magnetic field is collected.

[0071] The magnetic field image data of a certain layer inside the battery under test are combined and the magnetic induction intensity of the reflected magnetic field of a certain layer inside the entire battery under test is displayed in a two-dimensional form; alternatively, the magnetic field image data of all the internal layers of the battery under test can be combined and displayed in the form of a three-dimensional image.

[0072] When the analysis module conducts analysis, the host computer obtains the magnetic induction intensity collected by each group of sensor arrays output by the front-end processing module, combines the magnetic induction intensity collected by each group of sensor arrays to generate magnetic field image data, and uses the display component to display the magnetic induction intensity of the reflected magnetic field of a certain layer inside the battery under test in a two-dimensional form, or display the magnetic induction intensity of the reflected magnetic field inside the entire battery under test in a three-dimensional image form.

[0073] The identification, marking and measurement of the internal defects and aging mechanisms of the battery by the host computer are the same as those in the first embodiment, and will not be elaborated here.

[0074] In the description of this specification, the descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0075] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and purposes of the present invention, and the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A battery analysis system based on magnetic field reflection detection technology of quantum magnetic sensor, characterized in that: include: A magnetic field generating component is arranged opposite to the battery under test and is used to generate a controllable magnetic field horizontal to the plane of the battery under test, and the controllable magnetic field is used to detect different layers in the battery under test; A quantum magnetic induction component is arranged on the same side as the magnetic field generating component, the induction surface of the quantum magnetic induction component faces the battery under test, and is used to collect the magnetic induction intensity of the reflected magnetic field reflected from different levels in the battery under test; A processing module, wherein a first output end thereof is controlled and connected to an input end of a magnetic field generating component, and when different layers in the tested battery are detected, the processing module controls the magnetic field generating component to generate different magnetic field characteristics; a second output end of the processing module is connected to a control end of a quantum magnetic induction component to control the working conditions of the quantum magnetic induction component; an input end of the processing module is electrically connected to an output end of the quantum magnetic induction component to receive the magnetic induction intensity collected by the quantum magnetic induction component and perform signal processing on the magnetic induction intensity; The analysis module has an input end electrically connected to the output end of the processing module, and analyzes the internal defects and aging mechanism of the tested battery based on the magnetic induction intensity processed by the processing module.

2. The battery analysis system based on the magnetic field reflection detection technology of quantum magnetic sensor according to claim 1 is characterized in that: The magnetic field generating component is one of the following structures: Structure 1: The magnetic field generating component includes two coils, the winding directions of the two coils are opposite, and the quantum magnetic induction component is located between the two coils; Structure 2: The magnetic field generating component is a U-shaped coil or a C-shaped coil, and the quantum magnetic induction component is arranged in the opening of the U-shaped coil or the C-shaped coil.

3. The battery analysis system based on the magnetic field reflection detection technology of quantum magnetic sensor according to claim 1 is characterized in that: It also includes a slide, and the quantum magnetic induction component and the magnetic field generating component are arranged on the active surface of the slide. Different layers in the battery under test are detected point by point in a point scanning manner, and the magnetic induction intensity of the reflected magnetic field reflected from the different layers in the battery under test is obtained point by point, or different layers in the battery under test are detected line by line in a line scanning manner, and the magnetic induction intensity of the reflected magnetic field reflected from the different layers in the battery under test is obtained line by line.

4. The battery analysis system based on the magnetic field reflection detection technology of quantum magnetic sensor according to claim 3 is characterized in that: The slide table includes an X-axis slide rail and a Y-axis slide rail. The quantum magnetic induction component and the magnetic field generating component move on the X-axis slide rail and the Y-axis slide rail synchronously and in no particular order, and detect different layers in the battery under test point by point in a point scanning manner, and obtain the magnetic induction intensity of the reflected magnetic field reflected from different layers in the battery under test point by point.

5. The battery analysis system based on the magnetic field reflection detection technology of quantum magnetic sensor according to claim 3 is characterized in that: The slide table includes an X-axis slide rail or a Y-axis slide rail, and the quantum magnetic induction component includes a sensor array composed of a plurality of quantum magnetic sensors; The quantum magnetic induction component and the magnetic field generating component move synchronously along the X-axis or Y-axis on the X-axis slide rail or the Y-axis slide rail, detect different layers in the battery under test line by line along the length or width direction of the battery under test in a line scanning manner, and obtain the magnetic induction intensity of the reflected magnetic field reflected from different layers in the battery under test line by line.

6. The battery analysis system based on the magnetic field reflection detection technology of quantum magnetic sensor according to claim 3 is characterized in that: The slide table includes a Z-axis slide rail, and the quantum magnetic induction component and the magnetic field generating component move synchronously along the Z-axis to adjust the vertical distance between the quantum magnetic induction component, the magnetic field generating component and the battery to be tested.

7. The battery analysis system based on the magnetic field reflection detection technology of quantum magnetic sensor according to claim 1 or 3, characterized in that: The analysis module performs one or any combination of the following analyses: Combining the magnetic induction intensities of the reflected magnetic fields reflected at different levels in the tested battery to generate a magnetic field image of the tested battery, displaying the magnetic induction intensity of the reflected magnetic field of a certain layer inside the entire tested battery in a two-dimensional form, and / or displaying the magnetic induction intensity of the reflected magnetic field inside the entire tested battery in a three-dimensional form; Use deep learning technology to automatically identify, mark and measure internal defects and aging of batteries; The generated magnetic field images are used by professionals to identify, mark and measure the internal defects and aging mechanisms of the battery.

8. The battery analysis system based on the magnetic field reflection detection technology of quantum magnetic sensor according to claim 1 is characterized in that: The analysis module stores a database, which includes various internal defects of various batteries and the corresponding magnetic induction intensity distribution data reflected from the tested batteries collected by the battery analysis system; and various aging mechanisms of various batteries and the corresponding magnetic induction intensity distribution data reflected from the tested batteries collected by the battery analysis system.

9. The battery analysis system based on the magnetic field reflection detection technology of quantum magnetic sensor according to claim 1 is characterized in that: The processing module comprises: A collection circuit, whose input end is electrically connected to the output end of the quantum magnetic induction component, and is used to receive the magnetic induction intensity collected by the quantum magnetic induction component; A processor, whose input end is electrically connected to the output end of the acquisition circuit, performs signal processing on the magnetic induction intensity received from the acquisition circuit; whose output end is connected to the input end of the drive circuit, generates an electrical signal for controlling the working condition of the quantum magnetic induction component and an electrical signal for controlling the magnetic field generating component to generate different magnetic field characteristics, and sends them to the drive circuit; A driving circuit, wherein the input end thereof is electrically connected to the output end of the processor, the first output end thereof is electrically connected to the input end of the magnetic field generating component, and the driving current is provided to the magnetic field generating component according to the electrical signal for controlling the magnetic field generating component to generate different magnetic field characteristics; the second output end thereof is connected to the control end of the quantum magnetic induction component, and the bias current is provided to the quantum magnetic induction component according to the electrical signal for controlling the working condition of the quantum magnetic induction component.

10. The battery analysis system based on the magnetic field reflection detection technology of quantum magnetic sensor according to claim 9 is characterized in that: The processing module also includes an analog front-end circuit; The input end of the analog front-end circuit is electrically connected to the output end of the quantum magnetic induction component, and is used to capture and process the voltage signal output by the quantum magnetic induction component, and extract the effective voltage signal reflecting the change in the magnetic field magnetic induction intensity as the magnetic induction intensity signal; the output end of the analog front-end circuit is electrically connected to the input end of the acquisition circuit, and the acquisition circuit receives the magnetic induction intensity signal and converts it from an analog signal to a digital signal.

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