A method and device for online detection of battery temperature of new energy ship

Abstract

The present invention relates to the technical field of battery temperature detection, and in particular to a method and device for online detection of battery temperature of a new energy ship. The present invention first obtains the temperature distribution on the surface of a single new energy ship battery, and evaluates the abnormal state of the new energy ship battery according to a surface temperature distribution thermal imaging diagram; then monitors the internal temperature according to a temperature detector inside the new energy ship battery, and compares the temperature of other batteries in a new energy ship battery group to obtain the temperature prominence of the detected battery, and then further detects the state of the battery in combination with the comparison of the power consumption of the battery group, and finally obtains a relatively accurate detection result of the temperature of the new energy ship battery, thereby improving the credibility of the online detection result of the temperature of the new energy ship battery; makes corresponding battery state judgment and management decisions according to the detection result, thereby improving the safe operation of the system and the long-term performance of the battery.

Description

Technical Field

[0001] The present invention relates to the technical field of battery temperature detection, and in particular to a method and device for online detection of battery temperature of a new energy ship. Background Art

[0002] With the development and application of new energy ships, batteries, as important energy storage devices, are particularly critical in terms of safety and performance stability. Batteries mainly provide electrical energy for the power system. These batteries need to have high energy density, long life, safety and environmental adaptability to meet the needs of ships under long-term navigation and various operating conditions. Therefore, online monitoring of battery temperature has become one of the important means to ensure the safety of battery operation.

[0003] In new energy ships, battery packs are often composed of multiple battery cells or modules. In order to ensure the long-term stable operation of the battery pack, comprehensive temperature monitoring must be carried out. Excessive temperature may shorten the life of the battery, reduce performance, and even cause safety hazards. In the process of temperature detection of new energy ship batteries, factors such as poor sensor contact or environmental interference (such as electromagnetic interference) may cause distortion of temperature detection data; and rapid temperature changes and insufficient sensor sampling frequency may cause the measurement results to be not real-time and accurate; changes in ambient temperature inside and outside the battery compartment, humidity, air pressure and other factors, as well as possible chemical gas emissions (such as when the battery is abnormal) may have a negative impact on the accuracy and stability of the sensor, leading to misunderstanding or incorrect analysis of temperature data, affecting the judgment of battery status and management decisions.

[0004] Therefore, there is an urgent need for a battery temperature detection method to improve the accuracy and stability of battery temperature detection. Summary of the invention

[0005] In order to solve the above technical problems, the purpose of the present invention is to provide a method and device for online detection of battery temperature of new energy ships.

[0006] According to the first aspect of the embodiment of the present application, a method for online detection of battery temperature of a new energy ship is provided, and the technical solution adopted specifically includes:

[0007] Using sensors, obtain multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different positions on the battery surface, multiple internal temperature monitoring values ​​and internal temperature monitoring curves at different positions inside the battery, ambient temperature monitoring data, output voltage monitoring curves of each battery, and output current monitoring curves of the battery pack;

[0008] Analyze the surface temperature monitoring value and the surface temperature distribution thermal imaging diagram of the battery, and obtain the abnormality of the battery state in combination with the predetermined temperature range;

[0009] Analyzing the difference between the output voltage monitoring curve of the battery and other batteries in the battery pack and the difference between the internal temperature monitoring values ​​to obtain a state authenticity verification factor of the battery;

[0010] According to the abnormality degree of the state of the battery and the state authenticity verification factor, combined with the output current monitoring curve of the battery pack, a temperature health factor of the battery is obtained;

[0011] According to the temperature health factor of the battery, a battery status warning is performed to complete the online detection of the battery temperature.

[0012] In some embodiments of the present invention, analyzing the surface temperature monitoring value and the surface temperature distribution thermal imaging image of the battery, and combining with a predetermined temperature range to obtain the abnormality of the battery state includes:

[0013] Analyze the surface temperature monitoring value of the battery and the surface temperature distribution thermal imaging diagram to obtain the temperature distribution uniformity of the battery;

[0014] Analyze the surface temperature monitoring value and the surface temperature distribution thermal imaging diagram of the battery, and obtain the temperature safety risk of the battery in combination with the predetermined temperature range;

[0015] The abnormality degree of the battery state is obtained by combining the temperature distribution uniformity and the temperature safety risk.

[0016] In some embodiments of the present invention, analyzing the surface temperature monitoring value and the surface temperature distribution thermal imaging image of the battery to obtain the temperature distribution uniformity of the battery includes:

[0017] Using a superpixel segmentation algorithm to divide the surface temperature distribution thermal imaging image into a plurality of temperature distribution regions, and obtaining the number of temperature distribution regions;

[0018] Analyzing the differences between the surface temperature monitoring values ​​at all positions of the battery to obtain the surface temperature difference of the battery;

[0019] The temperature distribution uniformity of the battery is obtained by combining the number of temperature distribution areas and the surface temperature difference.

[0020] In some embodiments of the present invention, analyzing the surface temperature monitoring value and the surface temperature distribution thermal imaging image of the battery, combined with a predetermined temperature range, to obtain the temperature safety risk of the battery includes:

[0021] The surface temperature distribution thermal imaging image is divided into a plurality of temperature distribution regions by using a superpixel segmentation algorithm, and the highest temperature region and the lowest temperature region in the temperature distribution region are obtained;

[0022] Calculating the average temperature in the highest temperature area and the average temperature in the lowest temperature area according to the surface temperature monitoring value;

[0023] A first difference between the average temperature in the highest temperature area and the highest temperature in the predetermined temperature range is calculated, and a second difference between the average temperature in the lowest temperature area and the lowest temperature in the predetermined temperature range is calculated. The temperature safety risk of the battery is obtained by combining the first difference and the second difference.

[0024] In some embodiments of the present invention, analyzing the difference between the output voltage monitoring curve of the battery and other batteries in the battery pack and the difference between the internal temperature monitoring values ​​to obtain the state authenticity verification factor of the battery includes:

[0025] Analyze the difference between the output voltage monitoring curves of the battery and other batteries in the battery pack to obtain the linkage between the battery and other batteries in the battery pack;

[0026] Analyzing the difference between the internal temperature monitoring curves of the battery and other batteries in the battery pack to obtain the internal temperature prominence of the battery;

[0027] Combining the linkage of the battery and the internal temperature prominence degree, a battery status authenticity verification factor is obtained.

[0028] In some embodiments of the present invention, the difference in the degree of fluctuation of the internal temperature monitoring curve of the battery and other batteries in the battery pack is analyzed, and the internal temperature prominence of the battery is obtained by combining the internal temperature monitoring value of the battery and the ambient temperature monitoring data.

[0029] In some embodiments of the present invention, the temperature health factor of the battery is obtained according to the state abnormality degree and the state authenticity verification factor of the battery, combined with the output current monitoring curve of the battery pack, including:

[0030] All the time points in the output current monitoring curve of the battery pack are combined into a time series set, and the current monitoring values ​​corresponding to all the time series points are combined into a current data set;

[0031] Analyzing the correlation between the time series set and the current data set to obtain a correlation coefficient of an output current monitoring curve of the battery pack;

[0032] The temperature health factor of the battery is obtained according to the state abnormality degree and the state authenticity verification factor of the battery in combination with the correlation coefficient of the output current monitoring curve of the battery pack.

[0033] In some embodiments of the present invention, an infrared sensor is used to obtain multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different locations on the battery surface; a temperature sensor is used to obtain multiple internal temperature monitoring values ​​and internal temperature monitoring curves at different locations inside the battery, and a temperature sensor is used to obtain ambient temperature monitoring data; a pressure sensor is used to obtain an output voltage monitoring curve of each battery; and a current sensor is used to obtain an output current monitoring curve of the battery pack.

[0034] According to the second aspect of the embodiment of the present application, a new energy ship battery temperature online detection device is provided, and the technical solution adopted is specifically: the device includes: a memory and a processor, wherein:

[0035] The memory is used to store program code;

[0036] The processor is used to read the program code stored in the memory and execute the online detection method of the battery temperature of a new energy ship as described in any one of the first aspects of the present application.

[0037] In some embodiments of the present invention, the processor comprises:

[0038] A data acquisition module, used to obtain, by using sensors, multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different positions on the battery surface, multiple internal temperature monitoring values ​​at different positions inside the battery, an output voltage monitoring curve of each battery, and an output current monitoring curve of the battery pack;

[0039] A state abnormality analysis module, used for analyzing the surface temperature monitoring value and the surface temperature distribution thermal imaging diagram of the battery, and obtaining the state abnormality of the battery in combination with a predetermined temperature range;

[0040] A state authenticity verification factor analysis module, used for analyzing the difference between the output voltage monitoring curve of the storage battery and other storage batteries in the storage battery group and the difference between the internal temperature monitoring values, to obtain the state authenticity verification factor of the storage battery;

[0041] A temperature health factor analysis module, used to obtain a temperature health factor of the battery according to the state abnormality degree of the battery and the state authenticity verification factor, combined with an output current monitoring curve of the battery pack;

[0042] The battery status warning module is used to provide a battery status warning based on the temperature health factor of the battery and complete online battery temperature detection.

[0043] Compared with the prior art, the method and device for online detection of battery temperature of new energy ships provided by the present invention have the following beneficial effects:

[0044] The present invention first obtains the temperature distribution on the surface of a single new energy ship battery, and evaluates the abnormal state of the new energy ship battery according to the surface temperature distribution thermal imaging diagram. The evaluation result has a certain degree of unreality, so the present invention verifies it according to the temperature distribution inside the battery. Then, the internal temperature is monitored according to the temperature detector inside the new energy ship battery, and the temperature of other batteries in the new energy ship battery group is compared to obtain the temperature prominence of the detected battery; then the battery status is further detected in combination with the comparison of the power consumption of the battery group; finally, a more accurate detection result of the temperature of the new energy ship battery is obtained, and the credibility of the online detection result of the temperature of the new energy ship battery is improved; according to the detection result, the corresponding battery status judgment and management decision are made; through effective detection and management of the temperature of the new energy ship battery, necessary measures are taken in time to ensure the safe operation of the system and the long-term performance of the battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 A basic flow chart of a method for online temperature detection of a battery in a new energy ship provided by an embodiment of the present invention;

[0047] Figure 2 A basic flow chart of a method for analyzing abnormality of a battery state provided by one embodiment of the present invention;

[0048] Figure 3 A basic flow chart of a method for analyzing factors of battery status authenticity verification provided by one embodiment of the present invention;

[0049] Figure 4 A schematic diagram of the basic composition of an online temperature detection device for a new energy ship battery provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the online detection method and device of the temperature of a new energy ship battery proposed by the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. Terms such as "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such article or device. In the absence of further restrictions, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the article or device including the element.

[0052] The battery system of a new energy ship is usually composed of multiple battery cells or batteries, which are assembled into modules and further combined into a whole battery pack. In order to ensure the safety and stable performance of the battery pack, in addition to selecting the appropriate battery type, it is also necessary to implement an effective battery management system (BMS). BMS is responsible for monitoring the status of the battery (such as voltage, temperature and current), controlling the charging and discharging process, and implementing protection strategies (such as overcharge, over-discharge, and over-temperature protection) to ensure that the battery operates within a safe operating range and maximizes its service life. The present invention proposes a method and device for online detection of battery temperature in new energy ships. The main purpose is to accurately detect the temperature of batteries in new energy ships and improve the effectiveness of management decisions on battery status.

[0053] The specific scheme of the online detection method of the battery temperature of a new energy ship provided by the present invention is described in detail below with reference to the accompanying drawings.

[0054] See also Figure 1 , which shows the basic process of a new energy ship battery temperature online detection method provided by an embodiment of the present invention.

[0055] like Figure 1 As shown, an embodiment of the present invention provides a method for online detection of battery temperature of a new energy ship, comprising:

[0056] S100: Using sensors, obtain multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different positions on the battery surface, multiple internal temperature monitoring values ​​at different positions inside the battery, an output voltage monitoring curve of each battery, and an output current monitoring curve of the battery pack.

[0057] By using sensors, multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different positions on the battery surface, multiple internal temperature monitoring values ​​and internal temperature monitoring curves at different positions inside the battery, and ambient temperature monitoring data are obtained. Specifically, according to the characteristics of the battery pack (such as size, voltage, temperature range, etc.), a suitable temperature sensor is selected. Common temperature sensor types include thermistors, thermocouples, infrared sensors, etc. The temperature sensors are installed inside and outside the battery pack to ensure that the temperature data at key positions can be accurately measured. In this embodiment, infrared sensors are used to obtain multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different positions on the battery surface; thermistor temperature sensors or thermocouple temperature sensors are used to obtain multiple internal temperature monitoring values ​​and internal temperature monitoring curves at different positions inside the battery; and thermistor temperature sensors or thermocouple temperature sensors are used to obtain ambient temperature monitoring data. In addition, sensors are also used to collect the output voltage monitoring curve of each battery and the output current monitoring curve of the battery pack. In this embodiment, a pressure sensor is used to obtain the output voltage monitoring curve of each battery. The duration of the voltage sensor collecting data can be set to 10 minutes to obtain the output voltage monitoring curve of all batteries in the battery pack during the monitoring period; and a current sensor is used to obtain the output current monitoring data of the battery pack. The duration of the current sensor collecting data can be set to 10 minutes to obtain the output current monitoring curve of the battery pack during the monitoring period. The sensor collects battery temperature, voltage, and current data in real time, and usually converts the analog signal into a digital signal through an analog-to-digital converter (ADC) for subsequent processing and storage. The collected temperature, voltage, and current data are then transmitted to the data processing unit via wired or wireless transmission. The wireless transmission method can use Bluetooth, WiFi and other technologies, and the wired transmission can be achieved through CAN bus, Ethernet and other methods.

[0058] S200: Analyze the surface temperature monitoring value and the surface temperature distribution thermal imaging image of the battery, and obtain the abnormality of the battery state in combination with the predetermined temperature range.

[0059] In step S100, the surface temperature monitoring value of a single battery is obtained according to the infrared sensor, and the surface temperature distribution thermal imaging image of the single battery is obtained. Under normal circumstances, the surface temperature of a single battery should be relatively evenly distributed, and no obvious hot spots or cold spots should appear. Therefore, this embodiment obtains the abnormality of the battery state by analyzing the surface temperature monitoring value and the surface temperature distribution thermal imaging image of the battery in combination with the predetermined temperature range.

[0060] See also Figure 2 , which shows the basic process of a battery state abnormality analysis method provided by an embodiment of the present invention.

[0061] like Figure 2 As shown, the surface temperature monitoring value and the surface temperature distribution thermal imaging diagram of the battery are analyzed, and the state abnormality of the battery is obtained in combination with a predetermined temperature range, including steps S201 to S203.

[0062] S201: Analyze the surface temperature monitoring value and the surface temperature distribution thermal imaging image of the battery to obtain the temperature distribution uniformity of the battery.

[0063] The surface temperature monitoring values ​​and surface temperature distribution thermal imaging images of the battery are analyzed to obtain the temperature distribution uniformity of the battery. The specific analysis method is as follows: First, the surface temperature distribution thermal imaging image is divided into multiple temperature distribution areas using a superpixel segmentation algorithm to obtain the number of temperature distribution areas. Then, the differences between the surface temperature monitoring values ​​at all positions of the battery are analyzed to obtain the surface temperature difference of the battery. Finally, the temperature distribution uniformity of the battery is obtained by combining the number of temperature distribution areas and the surface temperature difference. The calculation formula for the temperature distribution uniformity of the battery is:

[0064]

[0065] In the formula, Indicates The uniformity of temperature distribution of each battery; Indicates Battery surface Surface temperature monitoring values ​​at each location; Indicates Battery surface Surface temperature monitoring values ​​at each location; Indicates the number of temperature distribution areas; Indicates the difference between the surface temperature monitoring values ​​at any two positions on the surface of the battery; represents one of the sets of differences; Indicates co-existence Group difference.

[0066] It indicates the average difference of the surface temperature monitoring values ​​at various positions in the temperature distribution on the surface of the new energy battery. The larger the average difference, the greater the difference between the surface temperature monitoring values ​​of the battery, that is, the greater the surface temperature difference; represents the number of temperature distribution areas obtained after superpixel segmentation, The larger the value is, the more fragmented the segmentation is, and the more uneven the temperature distribution of the corresponding battery is; therefore, The larger the product of , the worse the uniformity of the battery temperature distribution is, and the more likely the battery temperature is not in normal condition.

[0067] S202: Analyze the surface temperature monitoring value and the surface temperature distribution thermal imaging image of the battery, and obtain the temperature safety risk of the battery in combination with the predetermined temperature range.

[0068] The temperature of the battery is usually designed to be within a safe operating range, that is, the battery has a predetermined temperature range. Under normal circumstances, the temperature should be maintained within this predetermined temperature range and will not be too high or too low. Too high or too low temperatures indicate that there is a safety risk in the battery temperature. Therefore, by analyzing the surface temperature monitoring value of the battery and the surface temperature distribution thermal imaging map, combined with the predetermined temperature range, the temperature safety risk of the battery is obtained. The specific analysis method is: first, the surface temperature distribution thermal imaging map is divided into multiple temperature distribution areas using a superpixel segmentation algorithm to obtain the highest temperature area and the lowest temperature area in the temperature distribution area, and the highest temperature area and the lowest temperature area are marked. Then, according to the surface temperature monitoring value, the average temperature in the highest temperature area and the average temperature in the lowest temperature area are calculated. Finally, the first difference between the average temperature in the highest temperature area and the highest temperature in the predetermined temperature range is calculated, and the second difference between the average temperature in the lowest temperature area and the lowest temperature in the predetermined temperature range is calculated. The temperature safety risk of the battery is obtained by combining the first difference and the second difference. The calculation formula for the temperature safety risk of the battery is:

[0069]

[0070] In the formula, Indicates Temperature safety risk of each battery; Indicates The average temperature of all surface temperature monitoring values ​​in the highest temperature area in the surface temperature distribution thermal imaging diagram of each battery; Indicates The average temperature of all surface temperature monitoring values ​​in the lowest temperature area in the surface temperature distribution thermal imaging diagram of each battery; Indicates the lowest temperature in a predetermined temperature range of a battery; Indicates The highest temperature in a predetermined temperature range for each battery.

[0071] Indicates the absolute value of the difference between the average temperature of all surface temperature monitoring values ​​in the lowest temperature area of ​​the surface temperature distribution thermal imaging diagram and the lowest temperature in the predetermined temperature range of the battery. The smaller the value, the closer the lowest temperature of the battery is to the lower limit of the predetermined temperature range, and the temperature may be too low. Indicates the absolute value of the difference between the average temperature of all surface temperature monitoring values ​​in the highest temperature area of ​​the surface temperature distribution thermal imaging diagram and the highest temperature in the predetermined temperature range of the battery. The smaller the value, the closer the highest temperature of the battery is to the upper limit of the predetermined temperature range, and the temperature may be too high; It represents the product of the difference between the temperature of the highest temperature area and the temperature of the lowest temperature area in the surface temperature distribution thermal imaging diagram and the predetermined temperature range. The smaller the product is, the closer the temperature of the battery is to the upper and lower limits of the predetermined temperature range, and the temperature may be too high or too low, that is, the higher the temperature safety risk of the battery.

[0072] S203: Combining the temperature distribution uniformity and the temperature safety risk, the abnormality of the battery state is obtained.

[0073] Combining the temperature distribution uniformity and temperature safety risk, the abnormality of the battery state is obtained. The calculation formula for the abnormality of the battery state is:

[0074]

[0075] In the formula, Indicates The abnormality of the battery status; Indicates The uniformity of temperature distribution of each battery; Indicates Temperature safety risk of each battery; represents the hyperbolic tangent function; Indicates a constant. To prevent the denominator from being 0, the value can be 0.01.

[0076] The larger the value is, the worse the uniformity of the battery temperature distribution is. The battery temperature is more likely to be abnormal, indicating that the battery is more abnormal. The smaller it is, the more likely the battery is to have an over-high or under-low temperature, that is, the higher the temperature safety risk of the battery, the higher the abnormality of the battery state; therefore, It indicates the abnormality of the battery state of the new energy ship evaluated based on the thermal imaging diagram of the surface temperature distribution. The larger the product is, the uneven temperature distribution on the battery surface and the higher the safety risk. That is, the higher the abnormality of the battery state of the new energy ship, the lower the health level.

[0077] S300: Analyze the difference between the output voltage monitoring curve of the battery and other batteries in the battery pack and the difference between the internal temperature monitoring values ​​to obtain the battery status authenticity verification factor.

[0078] Step S200 evaluates the abnormality of the battery state through the surface temperature distribution thermal imaging image of a single battery, but evaluating only a single battery is too one-sided, and the state evaluation result needs to be verified to obtain the true battery state. Therefore, this embodiment obtains the battery state authenticity verification factor by analyzing the difference between the output voltage monitoring curve of the battery and other batteries in the battery pack and the difference between the internal temperature monitoring values.

[0079] See also Figure 3 , which shows the basic process of a battery status authenticity verification factor analysis method provided by an embodiment of the present invention.

[0080] like Figure 3 As shown, the difference between the internal temperature monitoring value and the internal temperature monitoring value is used to obtain the battery status authenticity verification factor, including:

[0081] S301: Analyze the difference between the output voltage monitoring curves of the battery and other batteries in the battery group to obtain the linkage between the battery and other batteries in the battery group.

[0082] In practical applications, especially on new energy ships, multiple batteries are usually used to form a battery pack to provide sufficient power. If the output voltage of each battery is highly correlated, it means that the stability of the battery pack system is high, that is, the battery status may be normal.

[0083] Therefore, this embodiment obtains the linkage between the battery and other batteries in the battery pack by analyzing the difference between the output voltage monitoring curves of the battery and other batteries in the battery pack. The calculation formula for the linkage between the battery and other batteries in the battery pack is:

[0084]

[0085] In the formula, Indicates The linkage between each battery and other batteries in the battery pack; Indicates The output voltage monitoring curve of each battery in the battery pack The mean square error of the output voltage monitoring curves of other batteries; Indicates the number of battery cells in a battery pack.

[0086] It indicates the average mean square error between the output voltage monitoring curve of a single battery in the new energy ship battery system and the output voltage monitoring curves of the remaining batteries. The larger the average value, the poorer the linkage between the battery and other batteries in the battery pack, that is, the battery may be in an abnormal operating state; if the output voltage working state of the battery is different from the working state of other batteries, then the battery may have some abnormal conditions.

[0087] S302: Analyze the difference between the internal temperature monitoring curves of the battery and other batteries in the battery pack to obtain the internal temperature prominence of the battery.

[0088] Infrared sensors can measure the temperature of the battery shell surface, but cannot directly observe or measure the specific conditions inside the battery, and the health status of the battery may be more affected by internal factors. Therefore, this embodiment obtains the internal temperature prominence of the battery by analyzing the difference between the internal temperature monitoring curves of the battery and other batteries in the battery pack. Further, in order to analyze the difference in the degree of fluctuation of the internal temperature monitoring curves of the battery and other batteries in the battery pack, the internal temperature prominence of the battery is obtained by combining the internal temperature monitoring value of the battery and the ambient temperature monitoring data. The calculation formula for the internal temperature prominence of the battery is:

[0089]

[0090] In the formula, Indicates The internal temperature of each battery is high; Indicates The fluctuation variance of the internal temperature monitoring curve of each battery cell; Indicates the battery pack The fluctuation variance of the internal temperature monitoring curves of other battery cells; Indicates The average value of all internal temperature monitoring values ​​of the battery; Indicates the average value of the ambient temperature monitoring data during the data monitoring period; Indicates the number of battery cells in a battery pack.

[0091] Indicates the difference between the internal temperature change of the detected battery and the internal temperature change of other batteries in the battery pack during the online detection of the new energy battery temperature. The larger the value, the greater the difference between the internal temperature monitoring value of the battery and the internal temperature monitoring values ​​of other batteries in the battery pack, that is, the battery may have some abnormal conditions; It means that when the ambient temperature monitoring data is small, the internal temperature of the battery is high, indicating that there may be some abnormal conditions in the battery; It indicates the prominence of the internal temperature detection result of the battery of the new energy ship. The larger the product is, the different the change of the internal monitoring temperature of the battery is from other batteries, that is, the more prominent the internal temperature detection result of the battery is.

[0092] S303: Combining the linkage of the battery and the degree of internal temperature prominence, obtain a battery status authenticity verification factor.

[0093] Combining the linkage of the battery and the degree of internal temperature prominence, the battery status authenticity verification factor is obtained. The calculation formula of the battery status authenticity verification factor is:

[0094]

[0095] In the formula, Indicates A battery status authenticity verification factor; Indicates the The linkage between each battery and other batteries in the battery pack; Indicates The internal temperature of each battery is high; represents the hyperbolic tangent function.

[0096] The larger the value, the poorer the linkage between the battery and other batteries in the battery pack, that is, the battery may be in an abnormal operating state, indicating that the authenticity verification of the battery state is stronger; The larger the value, the greater the difference between the internal temperature monitoring value of the battery and the internal temperature monitoring values ​​of other batteries in the battery pack, that is, the battery may have some abnormal conditions, indicating that the authenticity verification of the battery status is stronger; The Euclidean norm represents the linkage between the new energy ship battery and other batteries and the prominence of the internal temperature of the battery. The main purpose of the Euclidean norm is to comprehensively output a relatively stable value in two states. The larger the value, the more obvious the abnormal behavior of the battery, that is, the stronger the verification of the authenticity of the battery status, and the more credible the battery status assessment is.

[0097] S400: Obtaining a temperature health factor of the battery according to the abnormality degree of the battery state and the state authenticity verification factor in combination with an output current monitoring curve of the battery pack.

[0098] According to the abnormality of the battery state and the state authenticity verification factor, combined with the output current monitoring curve of the battery pack, the temperature health factor of the battery is obtained. Specifically, first, all the time points in the output current monitoring curve of the battery pack are combined into a time series set, and the current monitoring values ​​corresponding to all the time series points are combined into a current data set. Then, the correlation between the time series set and the current data set is analyzed to obtain the correlation coefficient of the output current monitoring curve of the battery pack. Finally, according to the abnormality of the battery state and the state authenticity verification factor, combined with the correlation coefficient of the output current monitoring curve of the battery pack, the temperature health factor of the battery is obtained. The calculation formula for the temperature health factor of the battery is:

[0099]

[0100] In the formula, Indicates The temperature health factor of each battery; Indicates The abnormality of the battery status; Indicates A battery status authenticity verification factor; Represents the covariance of the time series set and the current data set in the current detection curve; Represents the standard deviation of the timing set in the current detection curve; Represents the standard deviation of the current data set in the current detection curve; Expressed as a natural constant An exponential function with base ; Indicates a constant. To prevent the denominator from being 0, the value can be 0.01.

[0101] It indicates the change of output current of the battery pack of new energy ship during the data collection period. The closer the correlation coefficient is to 1, the higher the current is during this period. A higher charging current or discharging current will increase the temperature of the battery, which may affect the accuracy of battery status detection. The larger the value, the uneven temperature distribution on the battery surface and the higher the safety risk. That is, the higher the abnormality of the battery state of the new energy ship, the lower the health level. The larger the value, the more obvious the abnormal behavior of the battery. It represents the temperature health factor of the battery of the new energy ship. The larger the product is, the worse the battery health status evaluated by thermal imaging is in the online temperature detection method of the battery of the new energy ship. The stronger the authenticity of the evaluation result is and the smaller the influence of the charging current or the discharging current on the temperature detection result is, the smaller the temperature health factor of the battery of the new energy ship is.

[0102] S500: Perform battery status warning according to the battery temperature health factor and complete battery temperature online detection.

[0103] According to the new energy ship battery temperature health factor obtained in step S400, the health factor threshold is set to ; When the temperature health factor of the new energy ship battery When the online detection result is lower than the threshold, that is, When the temperature is abnormal, it is considered that the battery may have obvious abnormal behavior. The temperature abnormality warning device on the new energy ship can warn the battery status at this time. Later, consider replacing the battery or formulate an effective preventive maintenance plan based on the actual test results to extend the life of the battery pack and improve the reliability of the online temperature detection system.

[0104] Based on the same inventive concept as the above method, this embodiment also provides an online temperature detection device for batteries of new energy ships. Figure 4 A schematic diagram of the basic composition of an online temperature detection device for a new energy ship battery provided by an embodiment of the present invention is shown in FIG. Figure 4 As shown, the device includes: a memory 10 and a processor 20, wherein: the memory 10 is used to store program codes; the processor 20 is used to read the program codes stored in the memory 10, and execute the use of sensors to obtain multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different positions on the battery surface, multiple internal temperature monitoring values ​​and internal temperature monitoring curves at different positions inside the battery, environmental temperature monitoring data, the output voltage monitoring curve of each battery, and the output current monitoring curve of the battery group; the surface temperature monitoring values ​​and the surface temperature distribution thermal imaging images of the battery are analyzed, and the state abnormality of the battery is obtained in combination with a predetermined temperature range; the difference between the output voltage monitoring curve of the battery and other batteries in the battery group and the difference between the internal temperature monitoring values ​​are analyzed to obtain the state authenticity verification factor of the battery; according to the state abnormality of the battery and the state authenticity verification factor, combined with the output current monitoring curve of the battery group, the temperature health factor of the battery is obtained; according to the temperature health factor of the battery, a battery state warning is performed to complete the online detection of the battery temperature.

[0105] Furthermore, the processor 20 includes a data acquisition module 21 , a state abnormality analysis module 22 , a state authenticity verification factor analysis module 23 , a temperature health factor analysis module 24 , and a battery state early warning module 25 . The data acquisition module 21 is configured to use sensors to obtain multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different positions on the battery surface, multiple internal temperature monitoring values ​​at different positions inside the battery, the output voltage monitoring curve of each battery, and the output current monitoring curve of the battery group; the state abnormality analysis module 22 is configured to analyze the surface temperature monitoring values ​​and surface temperature distribution thermal imaging images of the battery, and obtain the state abnormality of the battery in combination with a predetermined temperature range; the state authenticity verification factor analysis module 23 is configured to analyze the difference between the output voltage monitoring curve of the battery and the difference between the internal temperature monitoring values ​​of the battery and other batteries in the battery group, and obtain the state authenticity verification factor of the battery; the temperature health factor analysis module 24 is configured to obtain the temperature health factor of the battery according to the state abnormality and state authenticity verification factor of the battery, in combination with the output current monitoring curve of the battery group; the battery state warning module 25 is configured to perform a battery state warning according to the temperature health factor of the battery and complete the online detection of the battery temperature.

[0106] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0107] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for online detection of battery temperature of new energy ships, characterized in that: The method comprises: Using sensors, obtain multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different positions on the battery surface, multiple internal temperature monitoring values ​​and internal temperature monitoring curves at different positions inside the battery, ambient temperature monitoring data, output voltage monitoring curves of each battery, and output current monitoring curves of the battery pack; Analyze the surface temperature monitoring value and the surface temperature distribution thermal imaging diagram of the battery, and obtain the abnormality of the battery state in combination with a predetermined temperature range; Analyzing the difference between the output voltage monitoring curve of the battery and other batteries in the battery pack and the difference between the internal temperature monitoring values ​​to obtain a state authenticity verification factor of the battery; According to the abnormality degree of the state of the battery and the state authenticity verification factor, combined with the output current monitoring curve of the battery pack, a temperature health factor of the battery is obtained; According to the temperature health factor of the battery, a battery status warning is performed to complete online battery temperature detection; Analyzing the surface temperature monitoring value and the surface temperature distribution thermal imaging diagram of the battery, and combining with a predetermined temperature range to obtain the abnormality of the battery state, includes: Analyze the surface temperature monitoring value of the battery and the surface temperature distribution thermal imaging diagram to obtain the temperature distribution uniformity of the battery; Analyze the surface temperature monitoring value and the surface temperature distribution thermal imaging diagram of the battery, and obtain the temperature safety risk of the battery in combination with the predetermined temperature range; Combining the temperature distribution uniformity and the temperature safety risk, obtaining the abnormality of the battery state; Analyzing the surface temperature monitoring value and the surface temperature distribution thermal imaging image of the battery to obtain the temperature distribution uniformity of the battery includes: Using a superpixel segmentation algorithm to divide the surface temperature distribution thermal imaging image into a plurality of temperature distribution regions, and obtaining the number of temperature distribution regions; Analyzing the differences between the surface temperature monitoring values ​​at all positions of the battery to obtain the surface temperature difference of the battery; Combining the number of temperature distribution areas and the surface temperature difference, obtaining the temperature distribution uniformity of the battery; Analyzing the surface temperature monitoring value and the surface temperature distribution thermal imaging diagram of the battery, and combining with a predetermined temperature range, obtaining the temperature safety risk of the battery, including: The surface temperature distribution thermal imaging image is divided into a plurality of temperature distribution regions by using a superpixel segmentation algorithm, and the highest temperature region and the lowest temperature region in the temperature distribution region are obtained; Calculating the average temperature in the highest temperature area and the average temperature in the lowest temperature area according to the surface temperature monitoring value; Calculating a first difference between the average temperature in the highest temperature area and the highest temperature in a predetermined temperature range, and calculating a second difference between the average temperature in the lowest temperature area and the lowest temperature in the predetermined temperature range, and combining the first difference and the second difference to obtain a temperature safety risk of the battery; Analyzing the difference between the output voltage monitoring curve of the battery and other batteries in the battery pack and the difference between the internal temperature monitoring values ​​to obtain the battery status authenticity verification factor includes: Analyze the difference between the output voltage monitoring curves of the battery and other batteries in the battery pack to obtain the linkage between the battery and other batteries in the battery pack; Analyzing the difference between the internal temperature monitoring curves of the battery and other batteries in the battery pack to obtain the internal temperature prominence of the battery; Combining the linkage of the battery and the internal temperature protrusion degree of the battery, obtaining a state authenticity verification factor of the battery; Analyze the difference in fluctuation degree of the internal temperature monitoring curve of the battery and other batteries in the battery pack, and obtain the internal temperature prominence degree of the battery by combining the internal temperature monitoring value of the battery and the ambient temperature monitoring data; According to the state abnormality degree of the battery and the state authenticity verification factor, combined with the output current monitoring curve of the battery pack, the temperature health factor of the battery is obtained, including: All the time points in the output current monitoring curve of the battery pack are combined into a time series set, and the current monitoring values ​​corresponding to all the time series points are combined into a current data set; Analyzing the correlation between the time series set and the current data set to obtain a correlation coefficient of an output current monitoring curve of the battery pack; The temperature health factor of the battery is obtained according to the state abnormality degree and the state authenticity verification factor of the battery in combination with the correlation coefficient of the output current monitoring curve of the battery pack.

2. The online detection method for battery temperature of new energy ships according to claim 1 is characterized in that: Use infrared sensors to obtain multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different locations on the battery surface; use temperature sensors to obtain multiple internal temperature monitoring values ​​and internal temperature monitoring curves at different locations inside the battery, and use temperature sensors to obtain ambient temperature monitoring data; use pressure sensors to obtain output voltage monitoring curves for each battery; And use the current sensor to obtain the output current monitoring curve of the battery pack.

3. A new energy ship battery temperature online detection device, characterized in that: The device comprises: a memory and a processor, wherein: The memory is used to store program codes; The processor is used to read the program code stored in the memory and execute the online detection method for the temperature of the new energy ship battery according to any one of claims 1 to 2.

4. The online temperature detection device for the battery of a new energy ship according to claim 3 is characterized in that: The processor comprises: A data acquisition module, used to obtain, by using sensors, multiple surface temperature monitoring values ​​and surface temperature distribution thermal imaging images at different positions on the battery surface, multiple internal temperature monitoring values ​​at different positions inside the battery, an output voltage monitoring curve of each battery, and an output current monitoring curve of the battery pack; A state abnormality analysis module, used for analyzing the surface temperature monitoring value and the surface temperature distribution thermal imaging diagram of the battery, and obtaining the state abnormality of the battery in combination with a predetermined temperature range; A state authenticity verification factor analysis module, used for analyzing the difference between the output voltage monitoring curve of the storage battery and other storage batteries in the storage battery group and the difference between the internal temperature monitoring values, to obtain the state authenticity verification factor of the storage battery; A temperature health factor analysis module, used to obtain a temperature health factor of the battery according to the state abnormality degree of the battery and the state authenticity verification factor, combined with an output current monitoring curve of the battery pack; The battery status warning module is used to perform battery status warning according to the temperature health factor of the battery and complete online detection of the battery temperature.

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