Battery thermal management system and method

Abstract

The invention discloses a battery thermal management system and method, which relates to the technical field of battery management, including: analyzing thermal imaging images of a battery and its surroundings to obtain thermal energy analysis points; dividing the environment where the battery is located to obtain detection areas and set preferred detection points; obtaining the thermal energy threshold of each detection area; performing real-time temperature detection on the battery in use, and issuing early warnings and processing based on the thermal energy threshold of each detection area; the invention is used to solve the problem that in the improvement of battery detection by temperature sensors in the prior art, there is a lack of a method for optimizing the placement position of the temperature sensor, resulting in the detection result of the temperature sensor being unable to accurately reflect the temperature condition of the battery when it is working, thereby being unable to accurately obtain the temperature data of the battery when it is working.

Description

Technical Field

[0001] The present invention relates to the technical field of battery management, and in particular to a battery thermal management system and method. Background Art

[0002] Battery thermal management is a new technology that is based on the influence of temperature on battery performance, combined with the electrochemical characteristics and heat generation mechanism of the battery, based on the optimal charging and discharging temperature range of the specific battery. It is established through reasonable design on the basis of multiple disciplines and fields such as materials science, electrochemistry, heat transfer and molecular dynamics. It is designed to solve the problem of thermal dissipation or thermal runaway caused by batteries working at too high or too low temperatures, so as to improve the overall performance of the battery.

[0003] Existing improvements in battery thermal management usually control the temperature of the battery by obtaining the temperature of the battery body. For example, in the Chinese patent with publication number CN117080630A, a battery thermal management method is disclosed. The scheme is to collect the temperature of the battery tab and calculate the battery body temperature based on the tab temperature, and judge the startup logic of the battery thermal management system according to the body temperature T2, so that the battery thermal management system is started to heat up, cool down or maintain the current temperature of the battery, so as to accurately control the temperature of the battery. Other improvements in battery thermal management usually use temperature sensors to detect the temperature of the battery for further management. However, in the existing improvements of detecting the battery by temperature sensors, there is a lack of a method for optimizing the placement position of the temperature sensor. When the temperature sensor is used to detect the temperature of the battery, the detection result of the temperature sensor cannot accurately reflect the temperature of the battery during operation due to the problem of selecting the detection position, so that the temperature data of the battery during operation cannot be accurately obtained, and the use of the battery cannot be effectively managed. In view of this, it is necessary to improve the existing battery thermal management method. Summary of the invention

[0004] The present invention aims to solve one of the technical problems in the prior art to at least a certain extent. By proposing a battery thermal management system and method, it is used to solve the problem that in the improvement of battery detection through temperature sensors in the prior art, there is a lack of a method for optimizing the selection of the placement position of the temperature sensor. When the temperature sensor is used to detect the temperature of the battery, the detection result of the temperature sensor cannot accurately reflect the temperature condition of the battery during operation due to the problem of selecting the detection position, thereby failing to accurately obtain the temperature data of the battery during operation, and further failing to effectively manage the battery usage.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a battery thermal management system, including a thermal energy detection module, a thermal energy division module, a thermal energy analysis module and a real-time thermal processing module:

[0006] The thermal energy detection module is used to analyze the thermal imaging images of the battery and the surrounding environment to obtain thermal energy analysis points, where the thermal energy analysis points include strong analysis points, medium analysis points and weak analysis points;

[0007] The thermal energy division module is used to divide the environment where the battery is located based on the thermal energy analysis point to obtain multiple detection areas, and set a preferred detection point in each detection area based on the division result;

[0008] The thermal energy analysis module is used to detect the thermal energy of the battery at the preferred detection points in all detection areas and obtain the thermal energy threshold of each detection area;

[0009] The real-time thermal processing module is used to perform real-time temperature detection on the battery in use, and to issue early warnings and perform processing based on the thermal energy threshold of each detection area.

[0010] Furthermore, the thermal energy detection module is configured with a thermal energy monitoring strategy, which includes:

[0011] Before using the battery, use an infrared thermal imager to photograph the battery and the device powered by the battery, and record the thermal infrared image obtained as the initial thermal image, and record the position where the infrared thermal imager is used to photograph as the thermal imaging position;

[0012] After the battery is used and the standard battery time has passed, an infrared thermal imager is used to photograph the battery and the device powered by the battery at a thermal imaging position, and the thermal infrared image obtained is recorded as a fever thermal image.

[0013] Furthermore, the thermal energy detection module is also configured with an imaging processing strategy, which includes:

[0014] grayscale the initial thermal image, and record the grayscale-processed initial thermal image as an initial grayscale image;

[0015] grayscale processing is performed on the heating thermal image, and the heating thermal image after the grayscale processing is recorded as a heating grayscale image;

[0016] For any pixel point K in the initial grayscale image, obtain the position coordinates (x1, y1) of the pixel point K, where x1 is the row where the pixel point K is located in the initial grayscale image, and y1 is the column where the pixel point K is located in the initial grayscale image;

[0017] Based on the position coordinates of pixel point K, a pixel point with the same position coordinates is obtained in the fever grayscale image, recorded as pixel point K~, the grayscale value of pixel point K is recorded as K1, and the grayscale value of pixel point K~ is recorded as K~1; when K1 is equal to K~1, pixel point K is recorded as an unaffected pixel point;

[0018] When K1 is not equal to K~1 and the difference between K1 and K~1 is greater than the first gray value, the pixel point K is recorded as a strong analysis point;

[0019] When K1 is not equal to K~1, and the difference between K1 and K~1 is greater than the second gray value and less than or equal to the first gray value, the pixel point K is recorded as the middle analysis point;

[0020] When K1 is not equal to K~1 and the difference between K1 and K~1 is less than or equal to the second grayscale value, the pixel point K is recorded as a weak analysis point.

[0021] Furthermore, the thermal energy detection module is also configured with a scale determination strategy, which includes:

[0022] Before using the battery, use an infrared thermal imager to photograph the battery, and convert the image obtained after the photographing into grayscale, which is recorded as a grayscale battery image. The average grayscale value of all pixels in the area where the battery is located in the grayscale battery image is recorded as the initial grayscale value;

[0023] Using a battery and operating the battery at low power, photographing the battery using an infrared thermal imager, graying the image obtained after the photographing, and recording it as a low-power battery image, and recording the average grayscale value of all pixels in the area where the battery is located in the low-power battery image as the low-power grayscale value;

[0024] Use a battery and operate the battery at rated power, use an infrared thermal imager to photograph the battery, convert the photographed image into grayscale and record it as a rated battery image, and record the average grayscale value of all pixels in the area where the battery is located in the rated battery image as the rated grayscale value;

[0025] Record the difference between the low-power gray value and the initial gray value as the second gray value;

[0026] The difference between the rated grayscale value and the initial grayscale value is recorded as the first grayscale value.

[0027] Furthermore, the thermal energy division module is configured with a regional division strategy, which includes:

[0028] All independent regions formed by all thermal energy analysis points in the initial grayscale image are sequentially recorded as thermal energy analysis region 1 to thermal energy analysis region N, and based on the actual environments corresponding to the thermal energy analysis regions in the initial grayscale image, the actual environments corresponding to all thermal energy analysis regions are sequentially recorded as detection regions 1 to detection regions N;

[0029] For any detection area N1, the thermal energy analysis area corresponding to the detection area N1 is recorded as the thermal energy area M1, the number of all pixel points in the thermal energy area M1 is obtained, recorded as L, the number of all strong analysis points in the thermal energy area M1 is obtained, recorded as L1, the number of all medium analysis points in the thermal energy area M1 is obtained, recorded as L2, the number of all weak analysis points in the thermal energy area M1 is obtained, recorded as L3, the value of L1 divided by L is recorded as the strong proportion, the value of L2 divided by L is recorded as the medium proportion, and the value of L3 divided by L is recorded as the weak proportion;

[0030] Obtain the maximum value among the strong proportion, the medium proportion and the weak proportion. When the maximum value is the strong proportion, the detection area N1 is recorded as the strong detection area; when the maximum value is the medium proportion, the detection area N1 is recorded as the medium detection area; when the maximum value is the weak proportion, the detection area N1 is recorded as the weak detection area;

[0031] Mark all detection areas as strong, medium, or weak.

[0032] Furthermore, the thermal energy division module is also configured with a detection point positioning strategy, which includes:

[0033] For any detection area N1, when the detection area N1 is recorded as a strong detection area, the area formed by all strong analysis points in the thermal energy area M1 corresponding to the detection area N1 is recorded as a preferred area;

[0034] Obtaining the outer contour of the preferred area, and obtaining the geometric center of the outer contour of the preferred area, which is recorded as a preferred positioning point, wherein the preferred positioning point is a pixel point;

[0035] When the preferred positioning point coincides with any strong analysis point J, the strong analysis point J is recorded as the preferred detection point of the detection area N1; when the preferred positioning point does not coincide with any strong analysis point, the strong analysis point with the shortest straight-line distance to the preferred positioning point is recorded as the preferred detection point of the detection area N1;

[0036] Based on the method of obtaining the preferred detection points in the strong detection area, the preferred detection points in the medium detection area and the weak detection area are obtained.

[0037] Furthermore, the thermal energy analysis module is configured with a thermal energy detection strategy, which includes:

[0038] For any detection area N1, a thermal energy detection point is set based on the position of the preferred detection point in the thermal energy area M1 corresponding to the detection area N1 in the actual battery environment;

[0039] A temperature sensor is placed at the heat energy detection point, and the temperature obtained by the temperature sensor is recorded as the heat energy value N1;

[0040] The battery is operated at rated power, and the maximum value of the thermal energy value N1 during the battery operation is obtained, which is recorded as the thermal energy threshold value of the thermal energy value N1;

[0041] Get the thermal energy threshold of the thermal energy value of all detection areas;

[0042] The real-time thermal processing module is used to perform real-time temperature detection on the battery in use, and to issue early warnings and perform processing based on the thermal energy threshold of each detection area.

[0043] Furthermore, the real-time heat treatment module is configured with an overheating warning strategy, which includes:

[0044] When the battery is in operation, when the thermal energy value of the temperature sensor in any detection area is greater than the thermal energy threshold of the detection area, a battery overheating warning is sent to the staff.

[0045] Furthermore, the real-time heat treatment module is also configured with an overheating treatment strategy, which includes:

[0046] When the battery overheat warning is sent for a period of time after the heat danger time, the battery is still running and there are still temperature sensors in the detection area whose thermal energy values ​​are greater than the thermal energy threshold of the detection area, the line connected to the battery is cut off to stop the battery from running.

[0047] In a second aspect, the present invention also provides a battery thermal management method, comprising:

[0048] Step S1, analyzing the thermal imaging image of the battery and the surrounding environment to obtain thermal energy analysis points, wherein the thermal energy analysis points include strong analysis points, medium analysis points and weak analysis points;

[0049] Step S2, dividing the environment where the battery is located based on the thermal energy analysis point to obtain multiple detection areas, and setting a preferred detection point in each detection area based on the division result;

[0050] Step S3, detecting the thermal energy of the battery at the preferred detection points in all detection areas, and obtaining the thermal energy threshold of each detection area;

[0051] Step S4, real-time temperature detection of the battery in use is performed, and early warning and processing are performed based on the thermal energy threshold of each detection area.

[0052] Beneficial effects of the present invention: The present invention first analyzes the thermal imaging images of the battery and the surrounding environment to obtain thermal energy analysis points; then divides the environment where the battery is located based on the thermal energy analysis points to obtain multiple detection areas, and sets preferred detection points in each detection area based on the division results. The advantage of this is that by performing thermal energy detection on the battery and obtaining thermal energy analysis points, the area affected by the battery temperature in the surrounding environment when the battery is running can be obtained, so that the preferred detection point that can accurately reflect the temperature change of the battery can be found in the detection area obtained in the subsequent process, so that the temperature data of the battery when working can be accurately obtained by detecting and analyzing the preferred detection points;

[0053] The present invention also detects the thermal energy of the battery at the preferred detection points in all detection areas, and obtains the thermal energy threshold of each detection area. Finally, real-time temperature detection is performed on the battery in use, and early warning and processing are performed based on the thermal energy threshold of each detection area. The advantage of this is that by obtaining the thermal energy threshold of each detection area based on the preferred detection point, the temperature change in the battery surrounding environment can be obtained based on the thermal energy threshold when the battery is actually operating, thereby extracting the temperature change data of the battery when it is working, and making the obtained data more accurate.

[0054] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 is a flow chart of the steps of the method of the present invention;

[0056] Figure 2 is a functional block diagram of the system of the present invention;

[0057] Figure 3 A schematic diagram of obtaining the preferred detection points of the present invention;

[0058] Figure 4 It is a connection block diagram of the electronic device of the present invention.

[0059] In the figure, 50 is an electronic device; 501 is a processor; and 502 is a memory. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] Example 1, please refer to Figure 1 As shown, in a first aspect, the present application provides a battery thermal management method, comprising:

[0062] Step S1, analyzing the thermal imaging image of the battery and the surrounding environment to obtain thermal energy analysis points, wherein the thermal energy analysis points include strong analysis points, medium analysis points and weak analysis points;

[0063] Step S1 includes the following steps: Step S101, before using the battery, use an infrared thermal imager to photograph the battery and the device powered by the battery, and record the thermal infrared image obtained by the photographing as an initial thermal image, and record the position where the infrared thermal imager is used to photograph as a thermal imaging position;

[0064] In the specific implementation process, by taking the initial thermal image and the heat generation thermal image of the battery before and after use at the thermal imaging position, the temperature change in the battery surrounding environment caused by the temperature change of the battery during the operation of the battery can be obtained, which is conducive to obtaining the detection area that can reflect the temperature change of the battery in the subsequent analysis;

[0065] Step S102, after the battery is used and a standard battery time has passed, an infrared thermal imager is used to photograph the battery and the device powered by the battery at a thermal imaging position, and the thermal infrared image obtained by the photographing is recorded as a heat generation thermal image;

[0066] In the specific implementation process, the standard battery time is adjusted according to the type of battery and the operating state of the battery. When taking a thermal image, the operating state of the battery should be stable and the battery's own temperature tends to be stable. For example, in a test, the battery's own temperature continues to rise within 10 minutes of the start of operation. After 10 minutes, the battery's own temperature no longer rises and remains at 40°C. In this case, the standard battery time should be greater than 10 minutes, for example, set to 11 minutes;

[0067] Step S103, graying the initial thermal image, and recording the grayed initial thermal image as an initial gray image;

[0068] grayscale processing is performed on the heating thermal image, and the heating thermal image after the grayscale processing is recorded as a heating grayscale image;

[0069] In the specific implementation process, due to the influence of the battery temperature, the grayscale values ​​of some pixels in the initial grayscale image will change in the heating grayscale image. Therefore, the area affected by the battery temperature in the environment can be extracted through the pixels whose grayscale values ​​have changed, thereby obtaining the detection area;

[0070] Step S104, for any pixel point K in the initial grayscale image, obtain the position coordinates (x1, y1) of the pixel point K, where x1 is the row where the pixel point K is located in the initial grayscale image, and y1 is the column where the pixel point K is located in the initial grayscale image;

[0071] Step S105, based on the position coordinates of pixel point K, obtain the pixel point with the same position coordinates in the fever grayscale image, record it as pixel point K~, record the grayscale value of pixel point K as K1, and record the grayscale value of pixel point K~ as K~1; when K1 is equal to K~1, record pixel point K as an unaffected pixel point;

[0072] In a specific implementation process, in one detection, the first gray value is 75, the position coordinates of the pixel point K are (20, 20), the gray value of the pixel point K is 200, and the gray value of the pixel point K~ obtained in the fever gray image by the position coordinates of the pixel point K is 100, then the pixel point K is recorded as a strong analysis point;

[0073] Step S106, when K1 is not equal to K~1 and the difference between K1 and K~1 is greater than the first gray value, the pixel point K is recorded as a strong analysis point;

[0074] When K1 is not equal to K~1, and the difference between K1 and K~1 is greater than the second gray value and less than or equal to the first gray value, the pixel point K is recorded as the middle analysis point;

[0075] When K1 is not equal to K~1 and the difference between K1 and K~1 is less than or equal to the second grayscale value, the pixel point K is recorded as a weak analysis point;

[0076] In the specific implementation process, by setting strong analysis points, medium analysis points and weak analysis points, the areas affected by the battery temperature in the initial grayscale image and the degree of influence in each area can be obtained, among which the strong analysis points are most affected by the battery temperature.

[0077] Step S101 includes the following sub-steps: Step S1011, before using the battery, use an infrared thermal imager to photograph the battery, and grayscale the image obtained after the photographing, record it as a grayscale battery image, and record the average grayscale value of all pixels in the area where the battery is located in the grayscale battery image as the initial grayscale value;

[0078] Step S1012, using the battery and operating the battery at low power, photographing the battery using an infrared thermal imager, and graying the image obtained after the photographing to record it as a low-power battery image, and recording the average grayscale value of all pixels in the area where the battery is located in the low-power battery image as the low-power grayscale value;

[0079] Step S1013, using the battery and operating the battery at rated power, photographing the battery using an infrared thermal imager, and graying the image obtained after the photographing to record it as a rated battery image, and recording the average grayscale value of all pixels in the area where the battery is located in the rated battery image as the rated grayscale value;

[0080] Step S1014, recording the difference between the low-power grayscale value and the initial grayscale value as a second grayscale value;

[0081] Recording the difference between the rated gray value and the initial gray value as the first gray value;

[0082] In a specific implementation process, for example, in a data extraction process, the initial grayscale value extracted is 123, the low-power grayscale value is 150, and the rated grayscale value is 170. Then, by calculation, it can be obtained that the first grayscale value is 47 and the second grayscale value is 27.

[0083] Step S2, dividing the environment where the battery is located based on the thermal energy analysis point to obtain multiple detection areas, and setting a preferred detection point in each detection area based on the division result;

[0084] Step S201, all independent areas formed by all thermal energy analysis points in the initial grayscale image are sequentially recorded as thermal energy analysis area 1 to thermal energy analysis area N, and based on the actual environment corresponding to the thermal energy analysis area in the initial grayscale image, the actual environment corresponding to all thermal energy analysis areas is sequentially recorded as detection area 1 to detection area N;

[0085] Step S202, for any detection area N1, record the thermal energy analysis area corresponding to the detection area N1 as the thermal energy area M1, obtain the number of all pixel points in the thermal energy area M1, record it as L, obtain the number of all strong analysis points in the thermal energy area M1, record it as L1, obtain the number of all medium analysis points in the thermal energy area M1, record it as L2, obtain the number of all weak analysis points in the thermal energy area M1, record it as L3, and record the value of L1 divided by L as the strong proportion, the value of L2 divided by L as the medium proportion, and the value of L3 divided by L as the weak proportion;

[0086] Step S203, obtaining the maximum value among the strong proportion, the medium proportion and the weak proportion. When the maximum value is the strong proportion, the detection area N1 is recorded as the strong detection area; when the maximum value is the medium proportion, the detection area N1 is recorded as the medium detection area; when the maximum value is the weak proportion, the detection area N1 is recorded as the weak detection area;

[0087] In the specific implementation process, by obtaining the maximum value of the strong proportion, the medium proportion and the weak proportion, the temperature influence in each detection area can be reflected. When the strong proportion is large, it means that there are more areas in the detection area that are greatly affected by temperature.

[0088] Mark all detection areas as strong, medium, or weak.

[0089] Step S204, for any detection area N1, when the detection area N1 is recorded as a strong detection area, the area formed by all strong analysis points in the thermal energy area M1 corresponding to the detection area N1 is recorded as a preferred area;

[0090] Obtaining the outer contour of the preferred area, and obtaining the geometric center of the outer contour of the preferred area, which is recorded as a preferred positioning point, wherein the preferred positioning point is a pixel point;

[0091] In a specific implementation process, when the set center of the outer contour of the preferred area is located within a pixel point, the pixel point is recorded as the preferred positioning point;

[0092] Step S205, see Figure 3 As shown, the area formed by □ is the pixel point corresponding to the thermal energy area, D1 to D13 are the areas formed by all the strong analysis points in the thermal energy area, ● is the preferred positioning point, and the preferred positioning point does not coincide with any strong analysis point. Through analysis, it can be obtained that D4 should be recorded as the preferred detection point of the detection area; when the preferred positioning point coincides with any strong analysis point J, the strong analysis point J is recorded as the preferred detection point of the detection area N1; when the preferred positioning point does not coincide with any strong analysis point, the strong analysis point with the shortest straight-line distance to the preferred positioning point is recorded as the preferred detection point of the detection area N1;

[0093] Step S206, based on the method for obtaining the preferred detection points in the strong detection area, obtaining the preferred detection points in the medium detection area and the weak detection area.

[0094] Step S3, detecting the thermal energy of the battery at the preferred detection points in all detection areas, and obtaining the thermal energy threshold of each detection area;

[0095] Step S301, for any detection area N1, a thermal energy detection point is set based on the position of the preferred detection point in the thermal energy area M1 corresponding to the detection area N1 in the actual battery environment;

[0096] In the specific implementation process, the selected location of the thermal energy detection point can be adjusted according to the actual situation. For example, when the thermal energy detection point is located on the device, the temperature sensor can be placed on the device; when the thermal energy detection point is located on the wall, it can be selected according to the distance between the wall and the battery. When the wall is close to the battery, the temperature sensor can be placed on the battery, and when the wall is far from the battery, the thermal energy detection point can be deleted;

[0097] Step S302, placing a temperature sensor at the heat energy detection point, and recording the temperature obtained by the temperature sensor as the heat energy value N1;

[0098] Step S303, operating the battery at rated power, obtaining the maximum value of the thermal energy value N1 during the battery operation process, and recording it as the thermal energy threshold of the thermal energy value N1;

[0099] Step S304, obtaining the thermal energy thresholds of the thermal energy values ​​of all detection areas.

[0100] Step S4, performing real-time temperature detection on the battery in use, and issuing warnings and processing based on the thermal energy threshold of each detection area;

[0101] Step S401, when the battery is in operation, when the thermal energy value of the temperature sensor in any detection area is greater than the thermal energy threshold of the detection area, a battery overheating warning is sent to the staff;

[0102] Step S402, when the battery overheat warning is sent for a period of time after the heat danger time, the battery is still running and there is still a temperature sensor in the detection area whose thermal energy value is greater than the thermal energy threshold of the detection area, the line connected to the battery is cut off to stop the battery from running;

[0103] In the specific implementation process, the thermal hazard time can be set according to the actual allowable high-temperature operation of the battery. For example, in a test, the actual allowable high-temperature operation time of the battery is 30 minutes. When the high-temperature operation time of the battery is greater than 30 minutes, it will cause irreversible damage to the battery and surrounding components. The thermal hazard time is set to 30 minutes, and the thermal energy threshold of detection area A is 50°C. When the battery is operating once, the thermal energy value of the temperature sensor in detection area A is 55°C, then a battery overheating warning is sent to the staff. After 30 minutes, the battery is still running and the thermal energy value of the temperature sensor in detection area A is still 55°C, then the line connected to the battery is cut off to stop the battery from running.

[0104] Example 2, please refer to Figure 2 As shown, in a second aspect, the present invention provides a battery thermal management system, including a thermal energy detection module, a thermal energy division module, a thermal energy analysis module and a real-time thermal processing module:

[0105] The thermal energy detection module is used to analyze the thermal imaging images of the battery and the surrounding environment to obtain thermal energy analysis points, where the thermal energy analysis points include strong analysis points, medium analysis points and weak analysis points;

[0106] The thermal energy detection module is equipped with a thermal energy monitoring strategy, which includes:

[0107] Before using the battery, use an infrared thermal imager to photograph the battery and the device powered by the battery, and record the thermal infrared image obtained as the initial thermal image, and record the position where the infrared thermal imager is used to photograph as the thermal imaging position;

[0108] After the battery is used and the standard battery time has passed, the battery and the device powered by the battery are photographed at the thermal imaging position using an infrared thermal imager, and the thermal infrared image obtained is recorded as a heat generation thermal image;

[0109] The thermal energy detection module is also equipped with an imaging processing strategy, which includes:

[0110] grayscale the initial thermal image, and record the grayscale-processed initial thermal image as an initial grayscale image;

[0111] grayscale processing is performed on the heating thermal image, and the heating thermal image after the grayscale processing is recorded as a heating grayscale image;

[0112] For any pixel point K in the initial grayscale image, obtain the position coordinates (x1, y1) of the pixel point K, where x1 is the row where the pixel point K is located in the initial grayscale image, and y1 is the column where the pixel point K is located in the initial grayscale image;

[0113] Based on the position coordinates of pixel point K, a pixel point with the same position coordinates is obtained in the fever grayscale image, recorded as pixel point K~, the grayscale value of pixel point K is recorded as K1, and the grayscale value of pixel point K~ is recorded as K~1; when K1 is equal to K~1, pixel point K is recorded as an unaffected pixel point;

[0114] When K1 is not equal to K~1 and the difference between K1 and K~1 is greater than the first gray value, the pixel point K is recorded as a strong analysis point;

[0115] When K1 is not equal to K~1, and the difference between K1 and K~1 is greater than the second gray value and less than or equal to the first gray value, the pixel point K is recorded as the middle analysis point;

[0116] When K1 is not equal to K~1 and the difference between K1 and K~1 is less than or equal to the second grayscale value, the pixel point K is recorded as a weak analysis point.

[0117] The thermal energy detection module is also configured with a scale determination strategy, which includes:

[0118] Before using the battery, use an infrared thermal imager to photograph the battery, and convert the image obtained after the photographing into grayscale, which is recorded as a grayscale battery image. The average grayscale value of all pixels in the area where the battery is located in the grayscale battery image is recorded as the initial grayscale value;

[0119] Using a battery and operating the battery at low power, photographing the battery using an infrared thermal imager, graying the image obtained after the photographing, and recording it as a low-power battery image, and recording the average grayscale value of all pixels in the area where the battery is located in the low-power battery image as the low-power grayscale value;

[0120] Use a battery and operate the battery at rated power, use an infrared thermal imager to photograph the battery, convert the photographed image into grayscale and record it as a rated battery image, and record the average grayscale value of all pixels in the area where the battery is located in the rated battery image as the rated grayscale value;

[0121] Record the difference between the low-power gray value and the initial gray value as the second gray value;

[0122] The difference between the rated grayscale value and the initial grayscale value is recorded as the first grayscale value.

[0123] The thermal energy division module is used to divide the environment where the battery is located based on the thermal energy analysis point to obtain multiple detection areas, and set a preferred detection point in each detection area based on the division result;

[0124] The thermal energy partitioning module is configured with a regional partitioning strategy, which includes:

[0125] All independent regions formed by all thermal energy analysis points in the initial grayscale image are sequentially recorded as thermal energy analysis region 1 to thermal energy analysis region N, and based on the actual environments corresponding to the thermal energy analysis regions in the initial grayscale image, the actual environments corresponding to all thermal energy analysis regions are sequentially recorded as detection regions 1 to detection regions N;

[0126] For any detection area N1, the thermal energy analysis area corresponding to the detection area N1 is recorded as the thermal energy area M1, the number of all pixel points in the thermal energy area M1 is obtained, recorded as L, the number of all strong analysis points in the thermal energy area M1 is obtained, recorded as L1, the number of all medium analysis points in the thermal energy area M1 is obtained, recorded as L2, the number of all weak analysis points in the thermal energy area M1 is obtained, recorded as L3, the value of L1 divided by L is recorded as the strong proportion, the value of L2 divided by L is recorded as the medium proportion, and the value of L3 divided by L is recorded as the weak proportion;

[0127] Obtain the maximum value among the strong proportion, the medium proportion and the weak proportion. When the maximum value is the strong proportion, the detection area N1 is recorded as the strong detection area; when the maximum value is the medium proportion, the detection area N1 is recorded as the medium detection area; when the maximum value is the weak proportion, the detection area N1 is recorded as the weak detection area;

[0128] Mark all detection areas as strong, medium, or weak.

[0129] The thermal energy partitioning module is also equipped with a detection point positioning strategy, which includes:

[0130] For any detection area N1, when the detection area N1 is recorded as a strong detection area, the area formed by all strong analysis points in the thermal energy area M1 corresponding to the detection area N1 is recorded as a preferred area;

[0131] Obtaining the outer contour of the preferred area, and obtaining the geometric center of the outer contour of the preferred area, which is recorded as a preferred positioning point, wherein the preferred positioning point is a pixel point;

[0132] When the preferred positioning point coincides with any strong analysis point J, the strong analysis point J is recorded as the preferred detection point of the detection area N1; when the preferred positioning point does not coincide with any strong analysis point, the strong analysis point with the shortest straight-line distance to the preferred positioning point is recorded as the preferred detection point of the detection area N1;

[0133] Based on the method of obtaining the preferred detection points in the strong detection area, the preferred detection points in the medium detection area and the weak detection area are obtained.

[0134] The thermal energy analysis module is used to detect the thermal energy of the battery at the preferred detection points in all detection areas and obtain the thermal energy threshold of each detection area;

[0135] The thermal analysis module is equipped with a thermal detection strategy, which includes:

[0136] For any detection area N1, a thermal energy detection point is set based on the position of the preferred detection point in the thermal energy area M1 corresponding to the detection area N1 in the actual battery environment;

[0137] A temperature sensor is placed at the heat energy detection point, and the temperature obtained by the temperature sensor is recorded as the heat energy value N1;

[0138] The battery is operated at rated power, and the maximum value of the thermal energy value N1 during the battery operation is obtained, which is recorded as the thermal energy threshold value of the thermal energy value N1;

[0139] Get the thermal energy threshold of the thermal energy values ​​of all detection areas.

[0140] The real-time thermal processing module is used to perform real-time temperature detection on the battery in use, and to issue early warnings and perform processing based on the thermal energy threshold of each detection area.

[0141] The real-time heat treatment module is configured with an overheating warning strategy, which includes:

[0142] When the battery is in operation, when the thermal energy value of the temperature sensor in any detection area is greater than the thermal energy threshold of the detection area, a battery overheating warning is sent to the staff.

[0143] The real-time heat treatment module is also equipped with an overheating treatment strategy, which includes:

[0144] When the battery overheat warning is sent for a period of time after the heat danger time, the battery is still running and there are still temperature sensors in the detection area whose thermal energy values ​​are greater than the thermal energy threshold of the detection area, the line connected to the battery is cut off to stop the battery from running.

[0145] Example 3, third aspect, please refer to Figure 4 As shown, the present application provides an electronic device, including a processor 501 and a memory 502, the memory 502 stores computer-readable instructions, and when the computer-readable instructions are executed by the processor 501, the steps in the above method are executed. Through the above technical solution, the processor 501 and the memory 502 are interconnected and communicate with each other through a communication bus and / or other forms of connection mechanisms, and the memory 502 stores a computer program executable by the processor 501. When the electronic device 50 is running, the processor 501 executes the computer program to execute the method in any optional implementation of the above embodiment to achieve the following functions: by analyzing the thermal imaging image of the battery and the surrounding environment, a thermal energy analysis point is obtained; then, based on the thermal energy analysis point, the environment where the battery is located is divided to obtain multiple detection areas, and based on the division result, a preferred detection point is set in each detection area, and the thermal energy of the battery is detected in the preferred detection points of all detection areas, and the thermal energy threshold of each detection area is obtained, and finally, the battery in use is detected in real time, and an early warning and processing are performed based on the thermal energy threshold of each detection area.

[0146] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0147] It should be understood by those skilled in the art that embodiments of the present invention may provide methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Among them, the storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0148] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, 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 communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

Claims

1. A battery thermal management system, characterized in that: Including thermal energy detection module, thermal energy division module, thermal energy analysis module and real-time thermal processing module: The thermal energy detection module is used to analyze the thermal imaging image of the battery and the surrounding environment to obtain thermal energy analysis points, where the thermal energy analysis points include strong analysis points, medium analysis points and weak analysis points; grayscale the initial thermal image, and record the initial thermal image after grayscale processing as the initial grayscale image; grayscale processing is performed on the heating thermal image, and the heating thermal image after the grayscale processing is recorded as a heating grayscale image; By taking the initial thermal image and the exothermic thermal image of the battery before and after use at the thermal imaging position, the initial thermal image and the exothermic thermal image can reflect the temperature change in the battery surrounding environment caused by the battery temperature change, and can reflect the detection area of ​​the battery temperature change; by setting the strong analysis point, the medium analysis point and the weak analysis point, the area affected by the battery temperature in the initial grayscale image and the degree of influence in each area can be obtained, among which the strong analysis point is most affected by the battery temperature; The thermal energy division module is used to divide the environment where the battery is located based on the thermal energy analysis point to obtain multiple detection areas, and set a preferred detection point in each detection area based on the division result; The thermal energy division module is configured with a regional division strategy, which includes: All independent regions formed by all thermal energy analysis points in the initial grayscale image are sequentially recorded as thermal energy analysis region 1 to thermal energy analysis region N, and based on the actual environments corresponding to the thermal energy analysis regions in the initial grayscale image, the actual environments corresponding to all thermal energy analysis regions are sequentially recorded as detection regions 1 to detection regions N; For any detection area N1, the thermal energy analysis area corresponding to the detection area N1 is recorded as the thermal energy area M1, the number of all pixel points in the thermal energy area M1 is obtained, recorded as L, the number of all strong analysis points in the thermal energy area M1 is obtained, recorded as L1, the number of all medium analysis points in the thermal energy area M1 is obtained, recorded as L2, the number of all weak analysis points in the thermal energy area M1 is obtained, recorded as L3, the value of L1 divided by L is recorded as the strong proportion, the value of L2 divided by L is recorded as the medium proportion, and the value of L3 divided by L is recorded as the weak proportion; Obtain the maximum value among the strong proportion, the medium proportion and the weak proportion. When the maximum value is the strong proportion, the detection area N1 is recorded as the strong detection area; when the maximum value is the medium proportion, the detection area N1 is recorded as the medium detection area; when the maximum value is the weak proportion, the detection area N1 is recorded as the weak detection area; Mark all detection areas as strong detection areas, medium detection areas, or weak detection areas; The thermal energy division module is also configured with a detection point positioning strategy, which includes: For any detection area N1, when the detection area N1 is recorded as a strong detection area, the area formed by all strong analysis points in the thermal energy area M1 corresponding to the detection area N1 is recorded as a preferred area; Obtaining the outer contour of the preferred area, and obtaining the geometric center of the outer contour of the preferred area, which is recorded as a preferred positioning point, wherein the preferred positioning point is a pixel point; When the preferred positioning point coincides with any strong analysis point J, the strong analysis point J is recorded as the preferred detection point of the detection area N1; when the preferred positioning point does not coincide with any strong analysis point, the strong analysis point with the shortest straight-line distance to the preferred positioning point is recorded as the preferred detection point of the detection area N1; Based on the method of obtaining the preferred detection points in the strong detection area, obtaining the preferred detection points in the medium detection area and the weak detection area; The thermal energy analysis module is used to detect the thermal energy of the battery at the preferred detection points in all detection areas and obtain the thermal energy threshold of each detection area; The real-time thermal processing module is used to perform real-time temperature detection on the battery in use, and to issue early warnings and perform processing based on the thermal energy threshold of each detection area.

2. The battery thermal management system according to claim 1, characterized in that: The thermal energy detection module is configured with a thermal energy monitoring strategy, which includes: Before using the battery, use an infrared thermal imager to photograph the battery and the device powered by the battery, and record the thermal infrared image obtained as the initial thermal image, and record the position where the infrared thermal imager is used to photograph as the thermal imaging position; After the battery is used and the standard battery time has passed, an infrared thermal imager is used to photograph the battery and the device powered by the battery at a thermal imaging position, and the thermal infrared image obtained is recorded as a fever thermal image.

3. The battery thermal management system according to claim 2, characterized in that: The thermal energy detection module is also configured with an imaging processing strategy, which includes: For any pixel point K in the initial grayscale image, obtain the position coordinates (x1, y1) of the pixel point K, where x1 is the row where the pixel point K is located in the initial grayscale image, and y1 is the column where the pixel point K is located in the initial grayscale image; Based on the position coordinates of pixel point K, a pixel point with the same position coordinates is obtained in the fever grayscale image, recorded as pixel point K~, the grayscale value of pixel point K is recorded as K1, and the grayscale value of pixel point K~ is recorded as K~1; when K1 is equal to K~1, pixel point K is recorded as an unaffected pixel point; When K1 is not equal to K~1 and the difference between K1 and K~1 is greater than the first gray value, the pixel point K is recorded as a strong analysis point; When K1 is not equal to K~1, and the difference between K1 and K~1 is greater than the second gray value and less than or equal to the first gray value, the pixel point K is recorded as the middle analysis point; When K1 is not equal to K~1 and the difference between K1 and K~1 is less than or equal to the second grayscale value, the pixel point K is recorded as a weak analysis point.

4. The battery thermal management system according to claim 3, characterized in that: The thermal energy detection module is also configured with a scale determination strategy, which includes: Before using the battery, use an infrared thermal imager to photograph the battery, and convert the image obtained after the photographing into grayscale, which is recorded as a grayscale battery image. The average grayscale value of all pixels in the area where the battery is located in the grayscale battery image is recorded as the initial grayscale value; Using a battery and operating the battery at low power, photographing the battery using an infrared thermal imager, graying the image obtained after the photographing, and recording it as a low-power battery image, and recording the average grayscale value of all pixels in the area where the battery is located in the low-power battery image as the low-power grayscale value; Use a battery and operate the battery at rated power, use an infrared thermal imager to photograph the battery, convert the photographed image into grayscale and record it as a rated battery image, and record the average grayscale value of all pixels in the area where the battery is located in the rated battery image as the rated grayscale value; Record the difference between the low-power gray value and the initial gray value as the second gray value; The difference between the rated grayscale value and the initial grayscale value is recorded as the first grayscale value.

5. The battery thermal management system according to claim 4, characterized in that: The thermal energy analysis module is configured with a thermal energy detection strategy, which includes: For any detection area N1, a thermal energy detection point is set based on the position of the preferred detection point in the thermal energy area M1 corresponding to the detection area N1 in the actual battery environment; A temperature sensor is placed at the heat energy detection point, and the temperature obtained by the temperature sensor is recorded as the heat energy value N1; The battery is operated at rated power, and the maximum value of the thermal energy value N1 during the battery operation is obtained, which is recorded as the thermal energy threshold value of the thermal energy value N1; Get the thermal energy threshold of the thermal energy value of all detection areas; The real-time thermal processing module is used to perform real-time temperature detection on the battery in use, and to issue early warnings and perform processing based on the thermal energy threshold of each detection area.

6. The battery thermal management system according to claim 5, characterized in that: The real-time heat treatment module is configured with an overheating warning strategy, which includes: When the battery is in operation, when the thermal energy value of the temperature sensor in any detection area is greater than the thermal energy threshold of the detection area, a battery overheating warning is sent to the staff.

7. The battery thermal management system according to claim 6, characterized in that: The real-time heat treatment module is also configured with an overheating treatment strategy, which includes: When the battery overheat warning is sent for a period of time after the heat danger time, the battery is still running and there are still temperature sensors in the detection area whose thermal energy values ​​are greater than the thermal energy threshold of the detection area, the line connected to the battery is cut off to stop the battery from running.

8. A method for a battery thermal management system according to any one of claims 1 to 7, characterized in that: include: Step S1, analyzing the thermal imaging image of the battery and the surrounding environment to obtain thermal energy analysis points, wherein the thermal energy analysis points include strong analysis points, medium analysis points and weak analysis points; Step S2, dividing the environment where the battery is located based on the thermal energy analysis point to obtain multiple detection areas, and setting a preferred detection point in each detection area based on the division result; Step S3, detecting the thermal energy of the battery at the preferred detection points in all detection areas, and obtaining the thermal energy threshold of each detection area; Step S4, real-time temperature detection of the battery in use is performed, and early warning and processing are performed based on the thermal energy threshold of each detection area.

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