A battery internal temperature testing device under power environment

Abstract

The present invention relates to a battery internal temperature testing device under a power environment, comprising a temperature sensor array, arranged inside the battery, for real-time monitoring of temperature data of various areas inside the battery, and preprocessing the temperature data to obtain preprocessed data; a data acquisition module, connected to the temperature sensor array, for collecting preprocessed data of various temperature sensors; a data processing module, connected to the data acquisition module, initializing a group of particles according to the number of temperature monitoring points inside the battery, each particle representing the temperature state of various areas inside the battery; and determining an evaluation function for evaluating the degree of agreement between the temperature state represented by each particle and the actually monitored temperature data. The present invention can improve the safety of a battery management system.

Description

Technical Field

[0001] The present invention relates to the technical field of power battery management, and in particular to a battery internal temperature testing device under a power environment. Background Art

[0002] In a power environment, changes in the internal temperature of the battery directly affect the working efficiency and safety of the battery. Therefore, real-time monitoring of the internal temperature of the battery and accurate testing of it are of great significance to ensure the normal operation of the battery system and prevent potential safety hazards.

[0003] Traditional battery temperature monitoring methods often use single-point or a few-point temperature measurements, which is difficult to fully reflect the temperature distribution inside the battery, especially in complex and changing power environments. In addition, traditional temperature measurement methods also have problems such as slow response speed and low accuracy, which cannot meet the accuracy and real-time requirements of modern high-performance battery systems for temperature monitoring. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a battery internal temperature testing device under a power environment to meet the demand for comprehensive and real-time monitoring of the battery internal temperature, thereby improving the safety of the battery management system.

[0005] In order to solve the above technical problems, the basic concept of the technical solution adopted by the present invention is:

[0006] In a first aspect, a battery internal temperature testing device in a power environment comprises:

[0007] A temperature sensor array is arranged inside the battery, and is used to monitor the temperature data of various areas inside the battery in real time, and pre-process the temperature data to obtain pre-processed data;

[0008] A data acquisition module, connected to the temperature sensor array, for collecting pre-processed data from each temperature sensor;

[0009] The data processing module is connected to the data acquisition module, and initializes a group of particles according to the number of temperature monitoring points inside the battery, each particle representing the temperature state of each area inside the battery; determines an evaluation function for evaluating the degree of agreement between the temperature state represented by each particle and the actual monitored temperature data; updates the position and speed of the particle according to the evaluation function; and obtains the final temperature data through multiple iterations when the preset number of iterations is reached;

[0010] A display module, connected to the data processing module, for displaying the temperature data of each area inside the battery and the temperature change trend in real time;

[0011] The early warning module is connected to the data processing module and sends out an early warning signal when the internal temperature of the battery exceeds a preset safety range.

[0012] In a preferred embodiment of any of the above schemes, preprocessing the temperature data to obtain preprocessed data includes:

[0013] Temperature data is passed Filtering is performed to obtain filtered data, where i is the index, T is the original temperature signal, N is the size of the filter window, and μ k is the center point of the Gaussian kernel function, σ k is the standard deviation of the Gaussian kernel function, ti means that this is the temperature value i time units before time t, and the exp function is used to calculate the temperature according to the data point i and the kernel function center point μ k The distance is used to calculate a weight value between 0 and 1, and T(t) is the filtered temperature value;

[0014] For the filtered data, Processing is performed to obtain preprocessed data, where T(t) is the actual temperature value at time t, μ(t) is the average temperature value at time t, σ(t) is the standard deviation of the temperature at time t, and T n (t) Normalized temperature value at time t.

[0015] In a preferred embodiment of any of the above schemes, the calculation formula for the temperature average value μ(t) at time t is:

[0016]

[0017] Wherein, M is the size of the sliding window, T(tj) is the temperature value from T(t) (ie, j=0) to T(t-M+1), and j is the index.

[0018] In a preferred embodiment of any of the above schemes, the calculation formula of the temperature standard deviation σ(t) at time t is:

[0019]

[0020] Wherein, M is the size of the sliding window, T(tj) is taken from T(t) (ie, j=0) to T(t-M+1), j is the index, and μ(t) is the average temperature.

[0021] In a preferred embodiment of any of the above schemes, the evaluation function calculation formula is:

[0022]

[0023] in, represents the state of the ith particle at time t; Ns is the number of temperature monitoring points inside the battery; is the temperature value actually measured at the kth monitoring point at time t; is the temperature value of the kth monitoring point estimated based on the state of the i-th particle at time t; σ k is the standard deviation of the temperature measurement at the kth monitoring point.

[0024] In a preferred embodiment of any of the above schemes, the speed formula for updating particles is:

[0025]

[0026] in, is the velocity of the jth particle at the next time step t+1, is the velocity of the particle at the current time step t, is the acceleration of the particle at the current time step t, Δt is the time step, and β is a decay factor between 0 and 1.

[0027] In a preferred embodiment of any of the above schemes, the formula for updating the position of the particle is:

[0028]

[0029] in, is the position of the jth particle at the next time step t+1, is the position of the particle at the current time step t, is the velocity of the particle at the current time step t, is the acceleration of the particle at the current time step t; Δt is the time step, F ext Represents a constant.

[0030] In a second aspect, a method for testing the internal temperature of a battery under a power environment is provided, the method comprising:

[0031] Obtain temperature data of various areas inside the battery;

[0032] Performing data processing on the temperature data to obtain preprocessed data;

[0033] According to the preprocessed data, the number of temperature monitoring points inside the battery is obtained, and the number of temperature monitoring points is processed to obtain the temperature state of a specific area;

[0034] According to the temperature state of a specific area, an evaluation function is defined, and the initial position and velocity of the particle are set to obtain the updated position and velocity of the particle;

[0035] Iterate the updated particle position and velocity multiple times to optimize the particle state to obtain the final temperature data;

[0036] The final temperature data is visualized to realize temperature display and monitoring.

[0037] After adopting the above technical solution, the present invention has the following beneficial effects compared with the prior art:

[0038] Through the setting of the temperature sensor array, the system can monitor the temperature data of each area inside the battery in real time to ensure a comprehensive grasp of the battery status. The system uses a particle swarm optimization algorithm to process the temperature data. By initializing the particle swarm, defining the evaluation function, updating the particle position and speed, etc., it can more accurately estimate the temperature state inside the battery. The temperature sensor array can cover various key areas inside the battery and provide more comprehensive temperature monitoring data. The display module can visualize the final temperature data and display the temperature data of each area inside the battery and the temperature change trend in real time. Through precise temperature monitoring and early warning mechanisms, it helps to avoid extreme situations such as battery overheating or overcooling, thereby protecting the battery from damage and extending the battery life. The existence of the early warning module enables the system to issue an alarm in time when the temperature is abnormal, reducing the risks caused by safety issues such as battery thermal runaway.

[0039] The specific implementation modes of the present invention are further described in detail below in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. Some specific embodiments of the present application will be described in detail in an illustrative and non-restrictive manner with reference to the drawings. The same reference numerals in the drawings indicate the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the drawings:

[0041] Figure 1 It is a schematic diagram of a battery internal temperature testing device under a power environment of the present invention.

[0042] Figure 2 It is a flow chart of a method for testing the internal temperature of a battery under a power environment of the present invention.

[0043] It should be noted that these drawings and text descriptions are not intended to limit the conceptual scope of the present invention in any way, but to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. The elements in the drawings are schematic and not drawn to scale. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0045] The following embodiment of the present application takes a battery internal temperature testing device and method under a power environment as an example to explain the scheme of the present application in detail, but this embodiment cannot limit the protection scope of the present application.

[0046] like Figure 1 As shown, the present invention provides a battery internal temperature testing device under a power environment, comprising:

[0047] A temperature sensor array is arranged inside the battery, and is used to monitor the temperature data of various areas inside the battery in real time, and pre-process the temperature data to obtain pre-processed data;

[0048] A data acquisition module, connected to the temperature sensor array, for collecting pre-processed data from each temperature sensor;

[0049] The data processing module is connected to the data acquisition module, and initializes a group of particles according to the number of temperature monitoring points inside the battery, each particle representing the temperature state of each area inside the battery; determines an evaluation function for evaluating the degree of agreement between the temperature state represented by each particle and the actual monitored temperature data; updates the position and speed of the particle according to the evaluation function; and obtains the final temperature data through multiple iterations when the preset number of iterations is reached;

[0050] A display module, connected to the data processing module, for displaying the temperature data of each area inside the battery and the temperature change trend in real time;

[0051] The early warning module is connected to the data processing module and sends out an early warning signal when the internal temperature of the battery exceeds a preset safety range.

[0052] In a specific embodiment, temperature sensors are arranged in different areas inside the battery, and the data acquisition module obtains pre-processed temperature data from the temperature sensor array periodically or in real time. The data processing module first initializes a group of particles according to the number of temperature monitoring points inside the battery, defines an evaluation function, and uses particle filtering or similar algorithms to update the position and speed of the particles according to the evaluation function. The state of the particles is optimized through multiple iterations. When the preset number of iterations is reached, the algorithm converges. At this time, the state of the particles represents the final temperature data. The display module receives the temperature data from the data processing module, and the early warning module continuously monitors the temperature data inside the battery. In the present invention, the system can monitor the temperature inside the battery in real time, detect abnormal conditions in time, and warn in advance through the early warning module, thereby effectively preventing safety problems caused by battery overheating. The temperature data is optimized and processed by algorithms such as particle filtering to improve the accuracy and reliability of the data. The real-time temperature data and trend chart provided by the display module enable operators to intuitively understand the working status of the battery, which is convenient for management and maintenance.

[0053] The present invention provides a battery internal temperature testing device under a power environment, which preprocesses temperature data to obtain preprocessed data, including:

[0054] Temperature data is passed Filtering is performed to obtain filtered data, where i is the index, T is the original temperature signal, N is the size of the filter window, and μ k is the center point of the Gaussian kernel function, σ k is the standard deviation of the Gaussian kernel function, ti means that this is the temperature value i time units before time t, and the exp function is used to calculate the temperature according to the data point i and the kernel function center point μ k The distance is used to calculate a weight value between 0 and 1, and T(t) is the filtered temperature value;

[0055] For the filtered data, Processing is performed to obtain preprocessed data, where T(t) is the actual temperature value at time t, μ(t) is the average temperature value at time t, σ(t) is the standard deviation of the temperature at time t, and T n (t) Normalized temperature value at time t.

[0056] In a specific embodiment, the collected original temperature data is recorded as T, and a filtering window size N is selected. For each data point, a Gaussian kernel function is set with it as the center. For each data point in the window, an exp function is used to calculate a weight value between 0 and 1 according to its distance from the center point of the Gaussian kernel. All data points in the window are weighted averaged according to their weights to obtain a filtered temperature value. After filtering, the filtered data is normalized, and the difference between the actual temperature value T(t) at time t and the average temperature at that time point is calculated. The temperature standard deviation at time t is calculated, and the actual temperature is converted into the average temperature value T(t). The difference between the temperature value and the average value is divided by the standard deviation to obtain the normalized temperature value at time t; in the present invention, through Gaussian filtering, the noise and outliers in the original temperature data can be effectively removed, the data can be made smoother, and the data quality can be improved. The normalization processing makes the temperature data at different time points comparable, eliminates the influence of the dimension, and the preprocessed data more accurately reflects the real temperature state inside the battery, which is helpful to more accurately evaluate the working performance and safety of the battery. The preprocessed data can be more easily used to set the temperature threshold, so as to realize the timely monitoring and early warning of abnormal conditions such as battery overheating.

[0057] The present invention provides a battery internal temperature testing device in a power environment, and the calculation formula of the temperature average value μ(t) at time t is:

[0058]

[0059] Among them, M is the size of the sliding window, T(tj) is the temperature value from t to tj, and j is the index.

[0060] In a specific embodiment, a sliding window size M is set, temperature values ​​from t to tj are collected, all temperature values ​​in the window are added and divided by the window size M to obtain the temperature average value at time t; in the present invention, by calculating the average temperature in the sliding window, the original temperature data can be effectively smoothed, and the impact of noise and instantaneous fluctuations on temperature monitoring can be reduced. Using a sliding window to calculate the average value can take into account more data points, thereby improving the reliability and stability of the temperature data. By observing the changes in the average temperature in the sliding window, the changing trend of the internal temperature of the battery can be more easily identified, which helps to predict future temperature behavior.

[0061] The present invention provides a battery internal temperature testing device under a power environment, and the calculation formula of the temperature standard deviation σ(t) at time t is:

[0062]

[0063] Where M is the size of the sliding window, T(tj) is the temperature value from t to tj, j is the index, and μ(t) is the average temperature.

[0064] In a specific embodiment, first, the sliding window size is determined, and for time t, the temperature values ​​from t to tj are collected, and the temperature standard deviation is calculated; in the present invention, the temperature standard deviation provides a quantitative indicator of the discreteness of the temperature data in the window, so as to understand the range and stability of the temperature inside the battery. By monitoring the changes in the temperature standard deviation, abnormal fluctuations in the temperature inside the battery can be more easily detected. The calculation of the temperature standard deviation helps to more accurately evaluate the working status of the battery, so as to take safety measures in time and avoid potential safety risks.

[0065] The present invention provides a battery internal temperature testing device under a power environment, and the evaluation function calculation formula is:

[0066]

[0067] in, represents the state of the ith particle at time t; N is the number of temperature monitoring points inside the battery; is the temperature value actually measured at the kth monitoring point at time t; is the temperature value of the kth monitoring point estimated based on the state of the i-th particle at time t; σ k is the standard deviation of the temperature measurement at the kth monitoring point.

[0068] In a specific embodiment, the number N of data points used to evaluate the model is determined, and for each monitoring point i, the difference between the predicted temperature value and the actual observed temperature value is calculated, and the square value of the difference of each monitoring point is used as input, and the Gaussian function is applied for calculation, and the weighted square difference of all monitoring points is summed to obtain the value of the evaluation function. In the present invention, the evaluation function provides a quantitative indicator for evaluating the performance of the temperature prediction model. This makes the comparison between different models easy and objective. By using the square difference, the evaluation function emphasizes large prediction errors more. The application of the Gaussian function gives different weights to differences of different sizes, which helps to balance the impact of different monitoring points on the overall evaluation. The calculation method of the evaluation function makes it easy to minimize through the optimization algorithm, so as to find the best model parameters.

[0069] The present invention provides a battery internal temperature testing device under a power environment, and the speed formula of the updated particles is:

[0070]

[0071] in, is the velocity of the jth particle at the next time step t+1, is the velocity of the particle at the current time step t, is the acceleration of the particle at the current time step t, Δt is the time step, and β is a decay factor between 0 and 1.

[0072] In a specific embodiment, the particle velocity is initialized, the acceleration of each particle at the current time step t is calculated according to the dynamic model of the battery internal temperature testing device, an appropriate time step is set, a decay factor between 0 and 1 is selected, and the velocity, acceleration, time step and decay factor of the current time step are combined to calculate the velocity of each particle at the next time step t+1; in the present invention, by considering the current velocity and acceleration, and introducing the time step and decay factor, the velocity of the particle can be controlled more accurately, and the introduction of the decay factor makes the updating of the particle velocity have a certain flexibility, and the decay degree of the velocity can be adjusted according to the actual situation. By properly selecting the time step and the decay factor, the stability of the particle velocity update can be ensured, and the simulation distortion caused by too fast or too slow speed can be avoided. By reasonably updating the particle velocity, the change of the internal temperature of the battery can be simulated more efficiently, and the calculation time and resource consumption can be reduced.

[0073] The present invention provides a battery internal temperature testing device under a power environment, and the particle position updating formula is:

[0074]

[0075] in, is the position of the jth particle at the next time step t+1, is the position of the particle at the current time step t, is the velocity of the particle at the current time step t, is the acceleration of the particle at the current time step t; Δt is the time step, F ext Represents a constant.

[0076] In a specific embodiment, at the start time, an initial position is assigned to each particle, the speed and acceleration are calculated, the speed and acceleration of each particle at the current time step t are calculated, an appropriate constant is set, and the position, speed, acceleration and constant of the current time step are combined to calculate the position of each particle at the next time step t+1; in the present invention, by considering the current position, speed and acceleration, and introducing constants, the position of the particle can be more accurately controlled, and the change in the internal temperature of the battery can be accurately simulated. The introduction of constants makes the update of the particle position flexible, and the amplitude of the position change can be adjusted according to actual conditions to better adapt to different power environments. By appropriately selecting constants, the stability of the particle position update can be ensured. By reasonably updating the particle position, the change in the internal temperature of the battery can be more efficiently simulated, reducing computing time and resource consumption.

[0077] like Figure 2 As shown, a method for testing the internal temperature of a battery under a power environment comprises the following steps:

[0078] Step 11, obtaining temperature data of various areas inside the battery;

[0079] Step 12, performing data processing on the temperature data to obtain pre-processed data;

[0080] Step 13, obtaining the number of temperature monitoring points inside the battery according to the preprocessed data, and processing the number of temperature monitoring points to obtain the temperature state of a specific area;

[0081] Step 14, defining an evaluation function according to the temperature state of a specific area, setting the initial position and velocity of the particle, so as to obtain the updated position and velocity of the particle;

[0082] Step 15, iterating the updated particle position and velocity multiple times to optimize the particle state to obtain the final temperature data;

[0083] Step 16, visualize the final temperature data to display and monitor the temperature.

[0084] In a specific embodiment, a temperature sensor is used to collect temperature data of different areas inside the battery in real time, the temperature data is preprocessed, the number of temperature monitoring points inside the battery is determined, the temperature data of each monitoring point is analyzed, temperature anomalies or key areas are identified, the temperature monitoring points are divided into different areas by clustering or other statistical methods, and the temperature state of each area is determined, an evaluation function is defined according to the temperature state of a specific area, a particle swarm optimization algorithm is used, the position and speed of the particles are iteratively updated multiple times, and the final temperature data obtained after optimization is visualized; in the present invention, by processing and optimizing the original temperature data, noise and outliers can be removed to obtain more accurate temperature data, by processing the number of temperature monitoring points, the key areas and abnormal areas inside the battery can be identified, and more refined temperature monitoring can be achieved, by defining an evaluation function and setting the initial state of the particles, resources can be allocated more reasonably, the efficiency and accuracy of temperature monitoring can be improved, by iteratively optimizing the state of the particles and visualizing the final temperature data, the temperature state inside the battery can be monitored in real time, potential safety hazards can be discovered and handled in a timely manner, and the safe operation of the battery can be ensured.

[0085] It should be noted that the system is a system corresponding to the above method, and all implementation methods in the above method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0086] The embodiment of the present invention further provides a computing device, comprising: a processor, a memory storing a computer program, wherein when the computer program is executed by the processor, the method described above is executed. All implementations in the above method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0087] The embodiment of the present invention also provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute the method described above. All implementations in the above method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0088] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0089] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0090] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0091] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual conditions to achieve the purpose of the solution of this embodiment.

[0092] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0093] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0094] In addition, it is pointed out that in the apparatus and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. Moreover, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but not necessarily in chronological order, and some steps can be performed in parallel or independently of each other. For those of ordinary skill in the art, it is understood that all or any steps or components of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or a network of computing devices in hardware, firmware, software or a combination thereof, which can be achieved by those of ordinary skill in the art using basic programming skills after reading the description of the present invention.

[0095] Therefore, the purpose of the present invention can also be achieved by running a program or a group of programs on any computing device. The computing device can be a well-known general device. Therefore, the purpose of the present invention can also be achieved by simply providing a program product containing a program code that implements the method or device. That is to say, such a program product also constitutes the present invention, and the storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any well-known storage medium or any storage medium developed in the future. It is also pointed out that in the device and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. In addition, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but not necessarily in chronological order. Some steps can be performed in parallel or independently of each other.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A battery internal temperature testing device under a power environment, characterized in that: include: A temperature sensor array is arranged inside the battery, and is used to monitor the temperature data of various areas inside the battery in real time, and pre-process the temperature data to obtain pre-processed data; A data acquisition module, connected to the temperature sensor array, for collecting pre-processed data from each temperature sensor; The data processing module is connected to the data acquisition module. According to the number of temperature monitoring points inside the battery, a group of particles is initialized, each particle represents the temperature state of each area inside the battery; an evaluation function is determined to evaluate the degree of agreement between the temperature state represented by each particle and the actual monitored temperature data; according to the evaluation function, the position and speed of the particle are updated; through multiple iterations, when the preset number of iterations is reached, the final temperature data is obtained; the evaluation function calculation formula is: in, represents the state of the ith particle at time t; N s is the number of temperature monitoring points inside the battery; is the temperature value actually measured at the kth monitoring point at time t; is the temperature value of the kth monitoring point estimated based on the state of the i-th particle at time t; σ k is the standard deviation of the temperature measurement at the kth monitoring point; A display module, connected to the data processing module, for displaying the temperature data of each area inside the battery and the temperature change trend in real time; The early warning module is connected to the data processing module and sends out an early warning signal when the internal temperature of the battery exceeds a preset safety range.

2. The battery internal temperature testing device under power environment according to claim 1, characterized in that: The temperature data is preprocessed to obtain preprocessed data, including: Temperature data is passed Filtering is performed to obtain filtered data, where i is the index, T is the original temperature signal, N is the size of the filter window, and μ k is the center point of the Gaussian kernel function, σ k is the standard deviation of the Gaussian kernel function, ti represents the temperature value i time units before time t, and the exp function is used to calculate the temperature according to the data point i and the kernel function center point μ k The distance is used to calculate a weight value between 0 and 1, and T(t) is the filtered temperature value; For the filtered data, Processing is performed to obtain preprocessed data, where μ(t) is the average temperature at time t, σ(t) is the standard deviation of temperature at time t, T n (t) Normalized temperature value at time t.

3. The battery internal temperature testing device under power environment according to claim 2, characterized in that: The calculation formula for the average temperature μ(t) at time t is: Where M is the size of the sliding window, T(tj) represents the temperature value j time units before time t, and j is the index.

4. The battery internal temperature testing device under power environment according to claim 3, characterized in that: The calculation formula for the temperature standard deviation σ(t) at time t is:

5. The battery internal temperature testing device under power environment according to claim 4, characterized in that: The formula for updating particle velocity is: in, is the velocity of the jth particle at the next time step t+1, is the velocity of the particle at the current time step t, is the acceleration of the particle at the current time step t, Δt is the time step, and β is a decay factor between 0 and 1.

6. The battery internal temperature testing device under power environment according to claim 5, characterized in that: The formula for updating the particle position is: in, is the position of the jth particle at the next time step t+1, is the position of the particle at the current time step t, is the velocity of the particle at the current time step t, is the acceleration of the particle at the current time step t; Δt is the time step, F ext Represents a constant.

7. A method for testing the internal temperature of a battery under a power environment, characterized in that: The method comprises: Obtain temperature data of various areas inside the battery; Performing data processing on the temperature data to obtain preprocessed data; According to the preprocessed data, the number of temperature monitoring points inside the battery is obtained, and the number of temperature monitoring points is processed to obtain the temperature state of a specific area; According to the temperature state of a specific area, an evaluation function is defined, and the initial position and velocity of the particle are set to obtain the updated position and velocity of the particle; the evaluation function calculation formula is: in, represents the state of the ith particle at time t; N s is the number of temperature monitoring points inside the battery; is the temperature value actually measured at the kth monitoring point at time t; is the temperature value of the kth monitoring point estimated based on the state of the i-th particle at time t; σ k is the standard deviation of the temperature measurement at the kth monitoring point; Iterate the updated particle position and velocity multiple times to optimize the particle state to obtain the final temperature data; The final temperature data is visualized to realize temperature display and monitoring.

8. A computing device, characterized in that include: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the method according to claim 7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program, which implements the method according to claim 7 when executed by a processor.

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