Temperature control method for battery pack of electric ship

Abstract

The invention discloses an electric ship battery pack temperature control method, and relates to the technical field of ship battery pack temperature control, and the method comprises the following steps: arranging a plurality of temperature sensors in a battery pack, monitoring the temperature data of each single battery in real time, and transmitting the temperature information of each single battery to a central processing unit in real time; through multi-sensor arrangement, heat conduction model calculation and intelligent cooling system scheduling, accurate temperature monitoring and dynamic adjustment of the electric ship battery pack are realized, real-time abnormal detection is ensured, and thermal runaway is prevented. The intelligent cooling system accurately adjusts cooling force according to temperature changes, and safety accidents are avoided. Meanwhile, a cooling strategy is optimized, energy consumption is reduced, system efficiency is improved, battery life is prolonged, sailing mileage is increased, maintenance cost is reduced, and long-term stable and efficient operation of the battery pack is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of ship battery pack temperature control, and in particular to a method for controlling the temperature of an electric ship battery pack. Background Art

[0002] Temperature control of electric ship battery packs refers to ensuring that they operate within a safe and efficient working range by accurately monitoring and adjusting the temperature of lithium battery packs. With the gradual popularization of the application of new energy technologies, lithium batteries have become the main power source for ships, and their safety is particularly important. Battery packs tend to generate a lot of heat under high power loads. If the temperature cannot be controlled in a timely and effective manner, thermal runaway of the battery may occur, which may cause fire or explosion, threatening the safety of the ship and crew. At the same time, if the temperature is not properly controlled, high-power equipment such as the liquid cooling system may run for a long time, thereby wasting a lot of electricity, further affecting the efficiency of battery use and reducing the ship's mileage. Therefore, temperature control of battery packs is not only the key to ensuring ship safety, but is also closely related to the efficiency of power utilization and navigation capabilities.

[0003] The prior art has the following deficiencies: In the temperature control process of electric ship battery packs in the prior art, the thermal runaway chain reaction caused by local overheating is a potential serious risk. When a cell in the battery pack is locally overheated due to an internal short circuit or extreme charging and discharging conditions, if it is not detected in time and effectively dissipated, the heat may be quickly transferred to the adjacent cells, triggering thermal runaway of the entire battery pack. This will not only cause a sharp drop in battery performance, but may also cause fires or explosions, especially in a closed cabin environment, posing a great threat to the safety of ships and personnel. However, traditional temperature control systems mostly rely on average temperature data, which makes it difficult to accurately capture the rapid heating of local hot spots, increasing the risk of problems not being discovered in time, which may delay emergency response at critical moments.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The purpose of the present invention is to provide a temperature control method for an electric ship battery pack. Through the combination of multi-sensor arrangement, heat conduction model calculation and intelligent cooling system scheduling, the electric ship battery pack can achieve accurate temperature monitoring and dynamic adjustment, ensure the temperature of each single cell is monitored in real time, detect and report abnormalities in time, and avoid thermal runaway events. The intelligent cooling system accurately adjusts the cooling intensity according to the severity of the temperature anomaly to avoid safety accidents. At the same time, by dynamically optimizing the cooling strategy, energy waste is avoided, system efficiency is improved, battery pack life is extended, mileage is increased, maintenance costs are reduced, and long-term stable and efficient operation of the battery pack is ensured to solve the problems in the above-mentioned background technology.

[0006] In order to achieve the above object, the present invention provides the following technical solution: a method for controlling the temperature of an electric ship battery pack, comprising the following steps: By setting up multiple temperature sensors in the battery pack, the temperature data of each single battery is monitored in real time, and the temperature information of each single battery is transmitted to the central processing unit in real time, ensuring that the temperature data of each single battery is accurately acquired and transmitted; When the temperature of a single cell in the battery pack exceeds the preset safety threshold, the alarm system is immediately triggered and the single cell is marked as an abnormal cell. The location, temperature information and related timestamp of the abnormal cell are recorded for subsequent processing and trend analysis. Based on the temperature data of each single cell in the battery pack and the temperature relationship between the adjacent single cells, the expansion trend of abnormal temperature is calculated in real time, and the speed and range of heat conduction to the adjacent cells are evaluated. Through calculation and prediction, the expansion range of the heat source is accurately evaluated; Based on the heat source expansion assessment results, the cooling system is automatically scheduled to perform priority cooling, focusing on cooling the abnormal area and its adjacent areas to prevent heat from spreading to the rest of the battery pack, ensuring that local cooling is prioritized; Combining real-time monitored temperature data with historical temperature control data, the cooling strategy is optimized through data analysis and artificial intelligence algorithms, and the cooling intensity and response time of the cooling system are dynamically adjusted. Based on the temperature change trend of the battery pack, the risk of thermal runaway is predicted in advance and optimized in real time to ensure the temperature control efficiency of the battery pack and battery performance.

[0007] Preferably, by setting multiple batteries in the battery pack to monitor the temperature of each single battery and transmit the data to the central processing unit, the specific steps of ensuring accurate acquisition of temperature data are as follows: In the battery pack of an electric ship, multiple temperature sensors are reasonably arranged according to the structural characteristics of the battery pack; The temperature sensor will transmit the collected temperature data of each battery cell to the central processing unit in real time through the built-in communication module; After receiving the temperature data transmitted by each single battery, the central processing unit integrates and processes the acquired data in real time; When the central processing unit confirms that the temperature of a single battery exceeds the safety threshold, the corresponding cooling mechanism is immediately activated and the cooling system is scheduled through the feedback mechanism.

[0008] Preferably, when the temperature of a single cell of the battery pack exceeds a preset safety threshold, the alarm system is immediately triggered, and the single cell is marked as an abnormal cell, and the location, temperature information and related timestamp of the abnormal cell are recorded for subsequent processing and trend analysis. The specific steps are as follows: When the temperature of a single cell in the battery pack exceeds the preset safety threshold, the central processing unit immediately detects the abnormal temperature data; When the central processing unit confirms that the temperature of a single battery exceeds the standard, the alarm mechanism is immediately triggered; After confirming that the battery temperature is abnormal and triggering an alarm, mark the single battery as an abnormal battery and immediately record the specific information of the battery; After recording abnormal battery information, subsequent processing and analysis are carried out, including trend analysis and prediction of abnormal events.

[0009] Preferably, according to the temperature data of each single cell in the battery pack and the temperature relationship between the adjacent single cells, the expansion trend of the abnormal temperature is calculated in real time, the speed and range of heat conduction to the adjacent cells are evaluated, and the expansion range of the heat source is accurately evaluated through calculation and prediction. The specific steps are as follows: When an abnormal temperature event triggers the alarm system and marks a single battery as abnormal, first, the temperature data of all battery cells are collected, and the temperature information of adjacent single batteries is obtained in real time; When it is determined that the temperature of a single battery exceeds the safety threshold, the central processing unit will calculate the expansion trend of the temperature anomaly through the heat conduction model based on the temperature data of the battery and the temperature information of the surrounding batteries; After obtaining the expansion trend of temperature anomaly, the next step is to accurately evaluate the heat conduction speed and range; Combining real-time data and prediction results, it is evaluated which battery cells and their adjacent areas have reached critical temperatures, thereby triggering the next preventive measures.

[0010] Preferably, based on the heat source expansion assessment result, the cooling system is automatically scheduled to perform priority cooling processing, focusing on cooling the abnormal area and its adjacent areas to prevent heat from spreading to the rest of the battery pack and ensure that local cooling is prioritized. The specific steps are as follows: After completing the evaluation of the heat source expansion, the heat conduction range is accurately predicted to determine the priority areas for cooling, that is, to locate the areas with the most severe temperature anomalies and their adjacent areas. The calculation expression is as follows: , where and Battery monomer and battery cells The temperature value, is the temperature difference, through the temperature difference To evaluate the heat from abnormal battery Conducted to adjacent cells speed, so as to determine which adjacent areas need to be cooled first; According to the heat source expansion assessment results, the cooling intensity of each area is determined. The calculation expression is as follows: , where is the amount of heat that the cooling system needs to transfer. is the flow rate of cooling medium, is the specific heat capacity of the cooling medium, is the temperature difference in the target area; After confirming the cooling demand, the working priority of the cooling system will be adjusted according to the evaluation results of the heat source, and the cooling priority will be scheduled by the following formula: , where is the maximum safe temperature of the battery pack, Cooling priority refers to the degree and order in which the cooling system prioritizes cooling of areas in the battery pack temperature control system based on the temperature status of the battery cells and the risk of heat source expansion; Once the cooling priority is determined, the working state of the cooling system is adjusted in real time. The cooling strategy is optimized to prevent the heat source from spreading to the rest of the battery pack. The temperature changes of each battery area are monitored in real time, and the cooling effect is dynamically adjusted as needed. The calculation expression is as follows: , where It is the cooling power, which indicates the heat absorbed and removed from the battery cell area by the cooling system per unit time.

[0011] Preferably, the real-time monitored temperature data and historical temperature control data are combined to optimize the cooling strategy through data analysis and artificial intelligence algorithms, dynamically adjust the cooling intensity and response time of the cooling system, and predict and optimize the response to thermal runaway risks in advance based on the temperature change trend of the battery pack to ensure the temperature control efficiency and battery performance of the battery pack. The specific steps are as follows: In the battery pack of electric ships, the integration of real-time monitoring temperature data and historical temperature control data is the basis for the optimization of the entire temperature control strategy. First, the temperature data of each single battery is obtained from each sensor in the battery pack in real time, and it is compared with the historical temperature control data. The integrated data provides a comprehensive temperature control status background. According to the input data, a dynamic temperature control model is established and calculated by the following formula: , where It's time point The temperature value at the moment, is the initial temperature, is the average temperature increment, is the natural base, It is the response speed factor of the cooling system, reflecting the efficiency of the cooling system; The data analysis stage involves deep learning of real-time temperature data and historical data to identify the temperature change trend of the battery pack and then predict the temperature trend of the battery pack in the future. In order to capture the trend of battery temperature changes, a regression analysis method based on machine learning is used to effectively identify the time series pattern in the historical temperature data and predict future temperature changes. The calculation expression is as follows: , where is the predicted temperature at the next moment, is the mapping function learned by the LSTM model, It's the past Temperature data at the moment; Based on data analysis and trend prediction, an optimization algorithm is used to adjust the cooling strategy. The core goal is to reduce the temperature of the battery cells by optimizing the behavior of the cooling system while avoiding energy waste caused by overcooling. The calculation expression is as follows: , where is the cooling capacity required by the cooling system, is the efficiency factor of the cooling system, is the power consumption of the cooling system, is the ambient temperature; Finally, based on the predicted temperature trend and the optimized cooling strategy, the risk of thermal runaway is predicted in real time, and the strategy is adjusted immediately when the actual temperature is about to exceed the safe range. The probability of thermal runaway under different temperature control measures is evaluated, and the calculation expression is as follows: , where is the thermal runaway risk value, i.e., the time point The thermal runaway risk value at the moment, is the maximum safe temperature of the battery pack, is the probability that the temperature exceeds the maximum safe temperature, is the risk function.

[0012] In the above technical solution, the technical effects and advantages provided by the present invention are: The present invention combines multi-sensor arrangement, heat conduction model calculation and intelligent cooling system scheduling, so that the battery pack of electric ships can achieve accurate temperature monitoring and dynamic adjustment. These measures ensure that the temperature of each single cell can be monitored in real time during the operation of the battery pack, and abnormal temperature will be detected and reported in time, which greatly improves the safety of the battery pack. When the temperature of a single cell exceeds the preset safety threshold, the system can immediately trigger an alarm and predict the expansion trend of heat through the heat conduction model, thereby preventing the heat source from further spreading to adjacent batteries and avoiding the occurrence of thermal runaway events. Through the scheduling of the intelligent cooling system, the system can accurately adjust the cooling intensity according to the severity of the temperature anomaly, ensure that the heat is effectively dispersed, and avoid serious safety accidents such as fire and explosion caused by temperature anomalies. Overall, this series of measures enables the temperature control system of the battery pack of electric ships to maintain the safe and stable operation of the battery pack when facing extreme environments and high-load work, greatly reducing the safety hazards caused by temperature problems.

[0013] The present invention dynamically optimizes the cooling strategy and intelligently schedules the cooling system, and the temperature control management of the battery pack not only ensures safety, but also improves the overall performance and service life of the battery pack. The intelligent cooling system can dynamically adjust the cooling mode according to the real-time temperature data of each single battery, the heat conduction expansion trend, and the working status of the battery pack to ensure the accurate use of cooling resources and avoid waste of cooling energy. For example, when the temperature in the core area of ​​the battery pack is high, the cooling system will give priority to strengthening the heat dissipation of this area, while the temperature control of the peripheral area can appropriately reduce the cooling intensity. This precise cooling strategy reduces unnecessary energy consumption and improves the efficiency of system operation. In addition, by optimizing the cooling effect, the temperature of the battery monomer is always kept within a safe range, thereby avoiding battery aging, performance degradation or damage caused by high temperature. This not only extends the service life of the battery pack, but also improves the mileage and efficiency of the electric ship, reduces the cost of maintenance and replacement, and ensures that the battery pack works efficiently and stably for a long time. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0015] Figure 1 The present invention is a method flow chart of a method for controlling the temperature of an electric ship battery pack. DETAILED DESCRIPTION

[0016] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0017] The present invention provides Figure 1 A method for controlling the temperature of an electric ship battery pack is shown, comprising the following steps: By setting up multiple temperature sensors in the battery pack, the temperature data of each single battery is monitored in real time, and the temperature information of each single battery is transmitted to the central processing unit in real time, ensuring that the temperature data of each single battery is accurately acquired and transmitted; By setting up multiple sensors in the battery pack to monitor the temperature of each single battery and transmit the data to the central processing unit, the specific steps to ensure accurate acquisition of temperature data are as follows: In the battery pack of an electric ship, multiple temperature sensors are reasonably arranged according to the structural characteristics of the battery pack; The positive and negative poles, connection areas and temperatures of each single battery may be different, so sensors should be installed in these key locations to ensure the comprehensiveness and accuracy of temperature data. The selection of sensors needs to have high precision, high response speed and a wide temperature range to ensure that small changes in temperature can be captured during the operation of the entire battery pack. At the same time, the layout of sensors should avoid electromagnetic interference to ensure stable signal transmission and reduce errors. The structural changes of the battery pack and the arrangement of the batteries should also be taken into account during the design to ensure that the temperature of each battery cell can be monitored in real time without missing or creating blind spots.

[0018] The temperature sensor will transmit the collected temperature data of each battery cell to the central processing unit in real time through the built-in communication module; The communication module should choose a stable and low-latency wireless or wired transmission method to ensure the real-time and accuracy of the data. During the data transmission process, the system must be able to handle the different frequencies and real-time nature of the temperature data between battery cells to ensure that the data of each sensor is not lost or delayed. For example, a timed sampling method can be used to collect data once every second or every millisecond, and the data is sent to the central processing unit through an efficient transmission protocol. In addition, the temperature data also needs to be pre-processed, including denoising, filtering and other operations, to improve the quality of the data and avoid data errors caused by interference signals. This step ensures that the temperature information of each single battery in the battery pack can be accurately transmitted to the central control system in real time.

[0019] After receiving the temperature data transmitted by each single battery, the central processing unit integrates and processes the acquired data in real time; Through data fusion technology, the system can perform weighted averaging on sensor data at different locations, eliminate deviations that may be caused by sensor errors, and ensure that the true temperature value of each single cell is finally obtained. At this time, the central processing unit will not only monitor the temperature of each single cell in real time, but also compare these temperature data with the preset safety temperature threshold. Once the temperature of a single cell exceeds the safety threshold, the system will immediately issue an alarm. To further ensure the accuracy of monitoring, the central processing unit can also set up redundant sensors. When the main sensor fails, the redundant sensor can continue to provide stable temperature data to ensure uninterrupted temperature monitoring.

[0020] When the central processing unit confirms that the temperature of a single battery exceeds the safety threshold, the corresponding cooling mechanism is immediately activated and the cooling system is scheduled through the feedback mechanism; Specifically, the cooling system may include a liquid cooling system, an air cooling system, or a heat pipe cooling system. Through the temperature control algorithm, the system will give priority to centralized cooling of battery areas with abnormal temperatures and their adjacent battery areas to prevent heat from spreading to other battery cells. The operation mode of the cooling system will be dynamically adjusted according to the real-time monitored temperature data, such as increasing the flow rate of the coolant, increasing the speed of the cooling fan, or adjusting the working mode of the heat sink. In addition, real-time feedback on the cooling effect will also be returned to the central processing unit to help it adjust the cooling strategy to ensure that the temperature control of the battery pack is always kept within a safe range to avoid thermal runaway.

[0021] When the temperature of a single cell in the battery pack exceeds the preset safety threshold, the alarm system is immediately triggered and the single cell is marked as an abnormal cell. The location, temperature information and related timestamp of the abnormal cell are recorded for subsequent processing and trend analysis. When the temperature of a single cell in the battery pack exceeds the preset safety threshold, the alarm system is immediately triggered and the single cell is marked as an abnormal cell. The location, temperature information and related timestamp of the abnormal cell are recorded for subsequent processing and trend analysis. The specific steps are as follows: When the temperature of a single cell in the battery pack exceeds the preset safety threshold, the central processing unit immediately detects the abnormal temperature data; This threshold is usually set based on the battery's operating temperature range and safety standards to ensure that the battery operates within a safe range. Once the temperature of a battery cell exceeds the safe range, the central processing unit will mark the cell through real-time temperature data monitoring and determine whether the abnormal temperature is an emergency. The system will use a variety of algorithms (such as temperature anomaly detection algorithm, threshold determination algorithm) for secondary confirmation to reduce the risk of false alarms and missed alarms. Ensure that temperature anomalies are discovered as soon as possible to prevent potential safety risks such as thermal runaway.

[0022] When the central processing unit confirms that the temperature of a single battery exceeds the standard, the alarm mechanism is immediately triggered; The alarm system usually includes multiple levels of alarm methods, such as sound alarms, visual warnings (LED indicator lights or display alarms), and remote notifications to the ship's control center or operators. At this time, the alarm content will include information such as the temperature of the relevant single battery, the time and location of the abnormality, and the battery number, so that it can be quickly located and appropriate disposal measures can be taken. In addition, the system will determine the alarm level and determine the urgency of the alarm based on the severity of the temperature exceeding the standard. For example, if the temperature exceeds the standard by a large margin or exceeds the critical threshold, the system will issue an emergency alarm and immediately start emergency measures such as the cooling system.

[0023] After confirming that the battery temperature is abnormal and triggering an alarm, mark the single battery as an abnormal battery and immediately record the specific information of the battery; These records include important data such as the battery number, location, current temperature value, timestamp of the abnormality, alarm triggering conditions (such as how many degrees the temperature exceeded), etc. This information is not only used for timely response and processing, but also provides data support for subsequent trend analysis and fault tracking. The recorded data can help engineers analyze the causes of battery abnormalities and check whether the battery has aging, damage or design defects during subsequent maintenance. Accurate records can improve the transparency of battery pack management and effectively avoid possible future failures.

[0024] After recording abnormal battery information, conduct subsequent processing and analysis, including trend analysis and prediction of abnormal events; By collecting and analyzing all relevant data (such as temperature change trends, historical temperature control data, temperature conditions of adjacent batteries, etc.), the system can further evaluate the temperature anomaly of the single battery and predict the risk of heat source expansion. If temperature anomalies are recorded at the same battery location multiple times, the system will issue a warning signal, indicating that the battery may have potential problems and requires further inspection or replacement. In addition, data analysis can also identify the regularity of battery temperature anomalies and provide reference to technicians to help them optimize the temperature control strategy or system design of the battery pack, thereby reducing the occurrence of similar problems. Combined with real-time monitoring data, the system can dynamically adjust the cooling strategy based on factors such as the severity and duration of the temperature anomaly to ensure the temperature control safety of the battery pack in future operation.

[0025] Based on the temperature data of each single cell in the battery pack and the temperature relationship between the adjacent single cells, the expansion trend of abnormal temperature is calculated in real time, and the speed and range of heat conduction to the adjacent cells are evaluated. Through calculation and prediction, the expansion range of the heat source is accurately evaluated; According to the temperature data of each single cell in the battery pack and the temperature relationship between the adjacent single cells, the expansion trend of abnormal temperature is calculated in real time, and the speed and range of heat conduction to the adjacent cells are evaluated. Through calculation and prediction, the expansion range of the heat source is accurately evaluated. The specific steps are as follows: When an abnormal temperature event triggers the alarm system and marks a single battery as abnormal, first, the temperature data of all battery cells are collected, and the temperature information of adjacent single batteries is obtained in real time; These temperature data include the current temperature of each single cell, the magnitude of abnormal temperature, and the spatial position relationship of each single cell. There is usually a certain temperature difference between the battery cells in the battery pack, so the temperature relationship between adjacent batteries is crucial for the conduction and expansion of heat. The system needs to determine the temperature gradient in the local area through the data of the temperature sensor and the heat conduction path between adjacent batteries. These data will provide a basis for subsequent heat transfer calculations to ensure that the expansion trend of temperature anomalies can be accurately evaluated.

[0026] When it is determined that the temperature of a single battery exceeds the safety threshold, the central processing unit will calculate the expansion trend of the temperature anomaly through the heat conduction model based on the temperature data of the battery and the temperature information of the surrounding batteries; Heat conduction in a battery pack usually follows the physical principle of heat transfer, and heat is conducted from high-temperature areas to low-temperature areas. The system needs to simulate and calculate the conduction rate of temperature anomalies from a single battery to the surrounding adjacent batteries, taking into account factors such as the thermal capacity and thermal conductivity of the battery and the distance between batteries, and evaluate the potential for heat source expansion. Through this process, the system can predict in advance whether the temperature anomaly area will spread to other battery cells, and take preventive measures before the abnormal temperature expands to a level that endangers the entire battery pack.

[0027] After obtaining the expansion trend of temperature anomaly, the next step is to accurately evaluate the heat conduction speed and range; The speed at which heat is conducted between battery cells depends on the thermal conductivity inside the battery and the distance between adjacent batteries. The system uses mathematical models (such as finite element analysis, heat conduction equations, etc.) to accurately calculate the speed and range of heat propagation by combining temperature data, physical properties (such as the thermal conductivity of the battery) and the layout structure of the battery. For example, the batteries in the battery pack may form a strong heat conduction channel through metal connectors or conductive plates, while the gaps or insulating materials between battery cells may slow down the speed of heat transfer. Based on these physical properties, the system can accurately determine whether the heat source will quickly expand to adjacent areas, thereby affecting the overall temperature distribution of the battery pack.

[0028] Combine real-time data and prediction results to assess which battery cells and their adjacent areas have reached critical temperatures, thereby triggering the next preventive measures; During the prediction process, the system also needs to comprehensively consider factors such as the temperature difference between batteries, heat capacity, and the reaction speed of the cooling system. If the heat spreads to the key areas of the battery pack, the system will immediately dispatch cooling equipment (such as liquid cooling system, air cooling system, etc.) to accelerate cooling of these areas first, and avoid further temperature out of control due to insufficient cooling measures. In addition, the system can also predict the duration of temperature anomalies, and determine whether long-term cooling treatment is required through data models to ensure the stability of temperature control of the battery pack during the treatment process.

[0029] Based on the heat source expansion assessment results, the cooling system is automatically scheduled for priority cooling, and the cooling effect is enhanced centrally or locally, focusing on cooling the abnormal area and its adjacent areas to prevent heat from spreading to the rest of the battery pack, ensuring that local cooling is prioritized; Based on the heat source expansion assessment results, the cooling system is automatically scheduled for priority cooling, and the cooling effect is enhanced centrally or locally, focusing on cooling the abnormal area and its adjacent areas to prevent heat from spreading to the rest of the battery pack and ensuring that local cooling is prioritized. The specific steps are as follows: After completing the evaluation of the heat source expansion, the heat conduction range is accurately predicted to determine the priority areas for cooling, that is, to locate the areas with the most severe temperature anomalies and their adjacent areas. The calculation expression is as follows: , where and Battery monomer and battery cells The temperature value, is the temperature difference, through the temperature difference To evaluate the heat from abnormal battery Conducted to adjacent cells speed, so as to determine which adjacent areas need to be cooled first; After completing the heat source expansion assessment, accurately predict the heat conduction range and determine the priority cooling areas, mainly to effectively prevent the heat in the temperature abnormality area from spreading further and ensure that the most severely overheated area and its adjacent areas are cooled first. The purpose of this process is to identify and locate the area with the most severe local overheating, as well as the adjacent areas with higher temperatures, to ensure that the cooling system can concentrate resources to cool the key areas in the shortest time, thereby avoiding the overheating phenomenon from spreading to the entire battery pack and preventing possible thermal runaway or other safety hazards. Through this precise cooling strategy, the safety and stability of the battery pack can be significantly improved, ensuring its efficient performance and long life during operation.

[0030] According to the heat source expansion assessment results, the cooling intensity of each area is determined. The calculation expression is as follows: , where is the amount of heat that the cooling system needs to transfer. is the flow rate of cooling medium, is the specific heat capacity of the cooling medium, is the temperature difference in the target area; Based on the local heat conduction assessment within the battery pack, the system will The size of the cooling system determines the amount of cooling required for each zone. By adjusting the coolant flow and the working mode of the cooling system, the system can optimize the cooling efficiency and ensure that the temperature in key areas can be reduced to a safe range in the shortest time.

[0031] Cooling medium refers to a substance used to absorb, transfer and dissipate heat. In the temperature control system of electric ship battery packs, the flow rate of cooling medium is an important parameter that determines the cooling efficiency. According to the type and design requirements of the cooling system, the common cooling media are as follows: Common cooling media: Water (liquid cooling system) Water is one of the most common cooling media and is widely used in liquid cooling systems. Water has a high specific heat capacity and thermal conductivity, can effectively transfer heat, and is suitable for large-scale cooling.

[0032] Advantages: efficient heat exchange capacity, abundant resources and low cost.

[0033] Disadvantages: prone to corrosion, requires antifreeze and anti-corrosion treatment.

[0034] Coolant (liquid cooling system) Coolant is usually composed of water and additives (such as antifreeze, preservatives) to improve the low temperature performance and corrosion resistance of water. Common coolants include ethylene glycol solutions or other specially formulated liquids.

[0035] Advantages: Can be used in low temperature environment and has better corrosion resistance.

[0036] Disadvantages: higher price, requires regular replacement and maintenance.

[0037] Air (air cooling system) Air cooling systems use fans or air flow to remove heat and are typically used for smaller systems or systems that do not require liquid cooling. Air cooling is often used to dissipate heat externally on devices such as battery packs and motors.

[0038] Advantages: simple structure, no need for liquid medium, low maintenance cost.

[0039] Disadvantages: Limited cooling effect, especially at high power output, the cooling capacity of air is poor.

[0040] Oil (oil cooling system) Oil cooling usually uses mineral oil or synthetic oil as the cooling medium and is widely used in some high-performance, high-power equipment, such as battery pack or motor cooling in electric vehicles.

[0041] Advantages: Oil has good thermal conductivity and lubrication, which can reduce friction and wear between components.

[0042] Disadvantages: Oil requires good sealing and leak-proof design, and the maintenance and replacement cycle is short.

[0043] Fluorinated liquid (two-phase cooling system) Fluorinated liquid cooling media, such as 3M™ Novec™ fluids, are often used in special high-efficiency cooling systems, especially for applications that require high thermal management capabilities, such as efficient liquid cooling of battery packs, electronic components, etc.

[0044] Advantages: high heat conduction efficiency, good insulation performance, suitable for cooling precision electronic equipment.

[0045] Disadvantages: high price, need to be replaced regularly, improper handling may have an impact on the environment.

[0046] Carbon dioxide (CO2) Carbon dioxide (CO2) cooling systems are used for cooling in some special cases, such as certain high-voltage batteries or cooling systems. CO2 can achieve extremely high heat transfer efficiency in the supercritical state.

[0047] Advantages: As a natural coolant, it is non-toxic, environmentally friendly, and has high heat transfer efficiency.

[0048] Disadvantages: Requires high-voltage environment and complex system design.

[0049] In the temperature control system of the battery pack, the choice of cooling medium is crucial, which directly affects the cooling effect, cost, maintenance cycle and system complexity. Water and coolant are widely used in liquid cooling systems, while air is usually suitable for smaller systems. Oil and fluorinated fluid are used in high-efficiency cooling situations. Choosing the right cooling medium can be optimized according to actual cooling needs, environmental conditions and cost-effectiveness.

[0050] Specific heat capacity of cooling medium It refers to the amount of heat that a unit mass of cooling medium needs to absorb or release when the temperature rises or drops by 1 degree Celsius. It is an important physical parameter to measure the heat capacity of the cooling medium, usually in joules / kilogram·degree Celsius (J / kg·°C). The larger the specific heat capacity, the more heat can be absorbed or released per unit mass of cooling medium, showing a stronger heat storage capacity. In the temperature control system of the battery pack, the specific heat capacity of the cooling medium determines the efficiency of the cooling system-the cooling medium with a larger specific heat capacity can effectively absorb the heat generated by the battery at a smaller flow rate, thereby improving the cooling efficiency and reducing the demand for cooling medium flow. Therefore, specific heat capacity is a key factor affecting cooling effect, cooling capacity and energy consumption. Common cooling media such as water have a higher specific heat capacity, so water is widely used in many cooling systems and can provide effective heat exchange effects at lower flow rates.

[0051] After confirming the cooling demand, the working priority of the cooling system will be adjusted according to the evaluation results of the heat source, and the cooling priority will be scheduled by the following formula: , where is the maximum safe temperature of the battery pack, Cooling priority refers to the degree and order in which the cooling system prioritizes cooling of areas in the battery pack temperature control system based on the temperature status of the battery cells and the risk of heat source expansion; Once the cooling priority is determined, the working state of the cooling system is adjusted in real time. The cooling strategy is optimized to prevent the heat source from spreading to the rest of the battery pack. The temperature changes of each battery area are monitored in real time, and the cooling effect is dynamically adjusted as needed. The calculation expression is as follows: , where is the cooling power, which indicates the amount of heat absorbed and removed from the battery cell area by the cooling system per unit time; Through real-time monitoring and dynamic adjustment of cooling power, the system can quickly respond to changes in battery temperature. Helps the system evaluate the efficiency of the cooling system and adjust it according to the temperature requirements of different areas. Ensure that the cooling system can play a role in time during the expansion of the heat source, prevent the heat from spreading to other battery areas, and ensure the safety and stability of the entire battery pack.

[0052] Combining real-time monitored temperature data with historical temperature control data, the cooling strategy is optimized through data analysis and artificial intelligence algorithms, and the cooling intensity and response time of the cooling system are dynamically adjusted. Based on the temperature change trend of the battery pack, the thermal runaway risk is predicted in advance and optimized in real time to ensure the temperature control efficiency and battery performance of the battery pack; Combining real-time monitored temperature data with historical temperature control data, the cooling strategy is optimized through data analysis and artificial intelligence algorithms, and the cooling intensity and response time of the cooling system are dynamically adjusted. Based on the temperature change trend of the battery pack, the thermal runaway risk is predicted in advance and optimized in real time to ensure the temperature control efficiency and battery performance of the battery pack. The specific steps are as follows: In the battery pack of electric ships, the integration of real-time monitoring temperature data and historical temperature control data is the basis for the optimization of the entire temperature control strategy. First, the temperature data of each single battery is obtained from each sensor in the battery pack in real time, and compared with the historical temperature control data. In order to better analyze the data, the historical data not only includes the temperature history of the battery pack, but also involves the response time, cooling intensity, temperature fluctuation of the cooling system, etc. The integrated data provides a comprehensive temperature control status background. According to the input data, a dynamic temperature control model is established and calculated by the following formula: , where It's time point The temperature value at the moment, is the initial temperature, is the average temperature increment, is the natural base, It is the response speed factor of the cooling system, reflecting the efficiency of the cooling system; By acquiring temperature changes in real time and comparing them with patterns in historical data, the system can more accurately identify the current temperature control status of the battery pack and provide a data basis for the optimization of subsequent cooling strategies.

[0053] The data analysis stage involves deep learning of real-time temperature data and historical data, identifying the trend of battery pack temperature changes, and then predicting the temperature trend of the battery pack in the future. In order to capture the trend of battery temperature changes, a regression analysis method based on machine learning is used, especially a deep learning algorithm based on time series data (such as long short-term memory network, LSTM), which effectively identifies the time series pattern in the historical temperature data and predicts future temperature changes. The calculation expression is as follows: , where is the predicted temperature at the next moment, is the mapping function learned by the LSTM model, It's the past Temperature data at the moment; Through this step, the system can predict the trend of temperature increase and identify potential thermal runaway risks in advance. The predicted temperature trend will help the system dynamically adjust the cooling strategy and take action in advance to avoid the dangers caused by excessive temperature.

[0054] Based on data analysis and trend prediction, optimization algorithms (such as particle swarm optimization, genetic algorithm or reinforcement learning) are used to adjust the cooling strategy. The optimization algorithm dynamically adjusts the cooling intensity and response time of the cooling system according to the temperature prediction data of the battery pack, the current state of the cooling system, and the preset temperature threshold. The core goal is to reduce the temperature of the battery cell by optimizing the behavior of the cooling system while avoiding energy waste caused by overcooling. The calculation expression is as follows: , where is the cooling capacity required by the cooling system, is the efficiency factor of the cooling system, is the power consumption of the cooling system, is the ambient temperature; By adjusting the power consumption and response time of the cooling system, the cooling system can achieve energy saving and efficient operation while meeting temperature control requirements. Dynamically optimized cooling strategies also need to adapt to real-time temperature changes to avoid excessive or insufficient cooling due to prediction errors.

[0055] Finally, based on the predicted temperature trend and the optimized cooling strategy, the risk of thermal runaway is predicted in real time, and the strategy is adjusted immediately when the actual temperature is about to exceed the safe range. To this end, the system will combine the current temperature data, cooling response and historical temperature fluctuations to calculate whether the battery pack has the potential risk of thermal runaway. Mathematical modeling and risk assessment algorithms (such as Monte Carlo simulation, Bayesian network, etc.) are used to evaluate the probability of thermal runaway under different temperature control measures. The calculation expression is as follows: , where is the thermal runaway risk value, i.e., the time point The thermal runaway risk value at the moment, is the maximum safe temperature of the battery pack, is the probability that the temperature exceeds the maximum safe temperature, is the risk function, describing the temperature of the battery pack , average temperature increment and response time How it affects thermal runaway risk.

[0056] Specific implementation 1: In the temperature control system of the battery pack of an electric ship, ensuring that the temperature information of each battery cell is transmitted to the central processing unit in real time and accurately is the most basic and critical part. By arranging multiple high-precision temperature sensors inside the battery pack, the temperature of each single battery in the battery pack can be detected in real time and transmitted to the central processing unit. These sensors usually use high-precision temperature sensing elements such as thermocouples, RTDs (platinum resistance temperature sensors) or thermistors, which have high sensitivity and reliability and can ensure the accuracy of the data.

[0057] The specific arrangement of sensors needs to be reasonably planned according to the shape and size of the battery pack and the heat conduction path between the batteries. A common practice is to arrange sensors in the positive and negative poles, central areas, contact surfaces and other areas of concentrated heat conduction of each single battery in the battery pack to ensure that temperature changes can be detected in a timely manner. In addition, in order to avoid temperature monitoring blind spots in local areas of the battery pack, the number of sensors should be appropriately increased, especially in the core and edge areas of the battery pack, and the distance between sensors should not be too large.

[0058] In terms of data transmission, the sensor transmits temperature data to the system's processing unit by connecting to the wireless or wired communication module of the central processing unit. Specifically, a low-power, high-speed communication protocol is used to ensure data accuracy and real-time performance during transmission. Wireless transmission technology (such as Wi-Fi, Bluetooth, Zigbee, etc.) is suitable for occasions where the battery pack space is large and wiring is difficult, while wired transmission (such as RS485, CAN bus, etc.) is more common when the internal wiring of the battery pack is relatively simple. The system should select an appropriate communication method to ensure that the temperature data can be transmitted to the central processing unit stably and accurately.

[0059] In order to ensure the reliability of temperature data transmission, the system needs to have a certain redundancy design. For example, when a sensor fails, the redundant sensor can automatically take over to ensure that the temperature data is not affected. In addition, the data must be encrypted during the transmission process to prevent external interference or data tampering. The data transmitted by each sensor will be labeled, including information such as timestamp, sensor number and location, which can provide detailed records for subsequent fault analysis, maintenance and trend analysis.

[0060] After receiving all the temperature data, the central processing unit in the system will analyze the temperature of each single battery in real time to determine whether there is a risk of overheating. Once the temperature of a single battery exceeds the preset safety threshold, the system will immediately trigger the alarm mechanism, mark the abnormal battery and record relevant information. At this time, the temperature monitoring system can not only accurately locate the battery cell with abnormal temperature, but also further evaluate the temperature status of other batteries in the battery pack, providing data support for the next cooling strategy.

[0061] Through the multi-sensor arrangement and the implementation of real-time data transmission system, the battery pack of electric ships can ensure that the temperature information of each single battery is monitored in a timely and accurate manner, providing stable and reliable data support for subsequent temperature control management. The real-time collection and transmission of temperature data not only enhances the accuracy of battery pack temperature control, but also significantly reduces the risk of safety accidents caused by excessive temperature, ensuring the safe and efficient operation of the battery pack.

[0062] Specific implementation 2: Once the temperature of a single cell in a battery pack exceeds the set safety threshold, simply relying on the alarm system to start and mark the abnormal cell is not enough to effectively prevent the problem from getting worse. In order to avoid the chain reaction caused by the overheating of a single cell in the battery pack, it is particularly important to use a temperature expansion trend calculation and early warning system based on a heat conduction model.

[0063] The heat conduction model can accurately describe the heat transfer law between battery cells and predict whether abnormal temperature will spread to adjacent battery cells, thereby affecting the safety of the entire battery pack. Heat is transferred from areas with higher temperatures to areas with lower temperatures. The heat conduction characteristics inside the battery pack directly affect the speed and range of heat source expansion. In this case, the system must first collect the temperature data of each single battery in the battery pack in real time, and combine it with the temperature data of the surrounding batteries to analyze its temperature gradient. The greater the temperature gradient between battery cells, the faster the heat transfer speed and the higher the risk of expansion. In order to more accurately assess the possibility of heat expansion, the system needs to evaluate the speed and range of heat propagation by calculating the heat conduction path and considering the thermal conductivity, heat capacity and other characteristics of the internal battery materials.

[0064] To achieve this calculation, the central processing unit in the system runs a heat conduction model, which usually uses finite element analysis (FEA) or other numerical simulation methods to model the temperature distribution of the battery pack based on factors such as the battery's geometry, material thermal properties, and ambient temperature. Through this model, the system can predict how heat will spread to adjacent batteries after a battery cell has a temperature anomaly, and predict the maximum range of the expansion. The system also adjusts the model parameters in real time and dynamically optimizes it based on the actual temperature data of each battery.

[0065] In this way, the system can timely and accurately evaluate the trend of heat source expansion when local temperature anomalies occur inside the battery pack, and predict which areas may be affected by heat conduction. For example, a battery in the battery pack may increase the temperature of batteries in its neighboring areas at high temperatures, causing these batteries to reach critical temperatures, thereby triggering a chain reaction. Therefore, the system can take preventive measures in time through simulation calculations before the heat is further transferred. By real-time monitoring of the heat expansion range, the system can accurately evaluate whether it is necessary to start the cooling system to prevent temperature runaway and avoid safety hazards such as overheating of the entire battery pack.

[0066] The advantage of this system is that it can predict and prevent potential thermal runaway problems before abnormal battery pack temperature occurs, thus providing additional safety for the battery pack. The system can dynamically adjust the cooling strategy according to actual conditions to avoid excessive or insufficient cooling, ensuring that the battery pack achieves the best balance between high efficiency and safety.

[0067] Specific implementation 3: In a battery pack, the design and scheduling of the cooling system is crucial to the control of battery temperature. Once the temperature monitoring system detects that the temperature of a single battery exceeds the standard and predicts through the heat conduction model that the heat may spread to adjacent areas, effective countermeasures must be taken quickly through the cooling system. In order to ensure that the temperature of the battery pack is always kept within a safe range, the intelligent scheduling and dynamic optimization of the cooling system become the key.

[0068] The cooling system of the battery pack of an electric ship usually includes a liquid cooling system, an air cooling system or a heat pipe cooling system. During implementation, the cooling system should be able to accurately dispatch different types of cooling equipment according to the severity of the temperature anomaly. When the temperature of a battery cell is too high, the system will immediately start the cooling mechanism and give priority to cooling the single cell and its adjacent areas. The liquid cooling system can achieve efficient heat dissipation by increasing the coolant flow rate or adjusting the coolant temperature, while the air cooling system accelerates the heat dissipation process by adjusting the fan speed and air volume.

[0069] The scheduling of the cooling system must not only respond to the temperature anomalies of individual battery cells, but also consider the overall temperature distribution of the battery pack. In order to avoid the waste of cooling resources and insufficient cooling effect, the system uses intelligent algorithms to optimize the cooling strategy. By collecting and analyzing the temperature data of each single battery in real time, the cooling system can dynamically adjust the cooling intensity and response time of the cooling system according to the temperature distribution of the battery pack. For example, when the temperature in the core area of ​​the battery pack is high, the cooling system will give priority to strengthening the cooling intensity of this area; when the temperature in the peripheral area is low, the system can reduce the cooling power to avoid unnecessary energy consumption.

[0070] In addition, the optimization of the cooling system must also take into account the operating status of the battery pack, the external ambient temperature, and the operating mode of the ship. For example, the battery pack may generate a lot of heat during charging or discharging, and when the ship is traveling at high speed, the ambient temperature is high, and the heat dissipation pressure of the battery pack will also increase. Therefore, the system must dynamically adjust the operating mode of the cooling system according to different working conditions to ensure that the battery pack can always be in the best temperature control state.

[0071] This intelligent, dynamically optimized cooling system scheduling mechanism can not only respond in a timely manner when the temperature is abnormal, but also reduce energy waste and improve the efficiency of the cooling system. Ultimately, this cooling strategy can effectively ensure the safety of the battery pack under high load, avoid safety accidents caused by excessive temperature, and extend the service life of the battery.

[0072] The present invention combines multi-sensor arrangement, heat conduction model calculation and intelligent cooling system scheduling, so that the battery pack of electric ships can achieve accurate temperature monitoring and dynamic adjustment. These measures ensure that the temperature of each single cell can be monitored in real time during the operation of the battery pack, and abnormal temperature will be detected and reported in time, which greatly improves the safety of the battery pack. When the temperature of a single cell exceeds the preset safety threshold, the system can immediately trigger an alarm and predict the expansion trend of heat through the heat conduction model, thereby preventing the heat source from further spreading to adjacent batteries and avoiding the occurrence of thermal runaway events. Through the scheduling of the intelligent cooling system, the system can accurately adjust the cooling intensity according to the severity of the temperature anomaly, ensure that the heat is effectively dispersed, and avoid serious safety accidents such as fire and explosion caused by temperature anomalies. Overall, this series of measures enables the temperature control system of the battery pack of electric ships to maintain the safe and stable operation of the battery pack when facing extreme environments and high-load work, greatly reducing the safety hazards caused by temperature problems.

[0073] The present invention dynamically optimizes the cooling strategy and intelligently schedules the cooling system, and the temperature control management of the battery pack not only ensures safety, but also improves the overall performance and service life of the battery pack. The intelligent cooling system can dynamically adjust the cooling mode according to the real-time temperature data of each single battery, the heat conduction expansion trend, and the working status of the battery pack to ensure the accurate use of cooling resources and avoid waste of cooling energy. For example, when the temperature in the core area of ​​the battery pack is high, the cooling system will give priority to strengthening the heat dissipation of this area, while the temperature control of the peripheral area can appropriately reduce the cooling intensity. This precise cooling strategy reduces unnecessary energy consumption and improves the efficiency of system operation. In addition, by optimizing the cooling effect, the temperature of the battery monomer is always kept within a safe range, thereby avoiding battery aging, performance degradation or damage caused by high temperature. This not only extends the service life of the battery pack, but also improves the mileage and efficiency of the electric ship, reduces the cost of maintenance and replacement, and ensures that the battery pack works efficiently and stably for a long time.

[0074] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for controlling the temperature of an electric ship battery pack, characterized in that: The following steps are involved: By setting multiple temperature sensors in the battery pack, the temperature data of each single battery is monitored in real time, and the temperature information of each single battery is transmitted to the central processing unit in real time; When the temperature of a single cell in the battery pack exceeds the preset safety threshold, the alarm system is immediately triggered, and the single cell is marked as an abnormal battery, and the location, temperature information and related timestamp of the abnormal battery are recorded; Based on the temperature data of each single cell in the battery pack and the temperature relationship between the adjacent single cells, the expansion trend of abnormal temperature is calculated in real time, and the speed and range of heat transfer to adjacent cells are evaluated; Based on the heat source expansion assessment results, the cooling system is automatically scheduled to perform priority cooling, focusing on cooling the abnormal area and its adjacent areas; Combining real-time monitored temperature data with historical temperature control data, the cooling strategy is optimized through data analysis and artificial intelligence algorithms, and the cooling intensity and response time of the cooling system are dynamically adjusted. Based on the temperature change trend of the battery pack, the risk of thermal runaway is predicted in advance and optimized in real time to ensure the temperature control efficiency of the battery pack and battery performance.

2. The method for controlling the temperature of an electric ship battery pack according to claim 1, characterized in that: By setting up multiple sensors in the battery pack to monitor the temperature of each single battery and transmit the data to the central processing unit, the specific steps to ensure accurate acquisition of temperature data are as follows: In the battery pack of an electric ship, multiple temperature sensors are reasonably arranged according to the structural characteristics of the battery pack; The temperature sensor will transmit the collected temperature data of each battery cell to the central processing unit in real time through the built-in communication module; After receiving the temperature data transmitted by each single battery, the central processing unit integrates and processes the acquired data in real time; When the central processing unit confirms that the temperature of a single battery exceeds the safety threshold, the corresponding cooling mechanism is immediately activated and the cooling system is scheduled through the feedback mechanism.

3. The method for controlling the temperature of an electric ship battery pack according to claim 1, characterized in that: When the temperature of a single cell in the battery pack exceeds the preset safety threshold, the alarm system is immediately triggered and the single cell is marked as an abnormal cell. The location, temperature information and related timestamp of the abnormal cell are recorded for subsequent processing and trend analysis. The specific steps are as follows: When the temperature of a single cell in the battery pack exceeds the preset safety threshold, the central processing unit immediately detects the abnormal temperature data; When the central processing unit confirms that the temperature of a single battery exceeds the standard, the alarm mechanism is immediately triggered; After confirming that the battery temperature is abnormal and triggering an alarm, mark the single battery as an abnormal battery and immediately record the specific information of the battery; After recording the abnormal battery information, subsequent processing and analysis are carried out, including trend analysis and prediction of abnormal events.

4. The method for controlling the temperature of an electric ship battery pack according to claim 1, characterized in that: According to the temperature data of each single cell in the battery pack and the temperature relationship between the adjacent single cells, the expansion trend of abnormal temperature is calculated in real time, and the speed and range of heat conduction to the adjacent cells are evaluated. Through calculation and prediction, the expansion range of the heat source is accurately evaluated. The specific steps are as follows: When an abnormal temperature event triggers the alarm system and marks a single battery as abnormal, first, the temperature data of all battery cells are collected, and the temperature information of adjacent single batteries is obtained in real time; When it is determined that the temperature of a single battery exceeds the safety threshold, the central processing unit will calculate the expansion trend of the temperature anomaly through the heat conduction model based on the temperature data of the battery and the temperature information of the surrounding batteries; After obtaining the expansion trend of temperature anomaly, the next step is to accurately evaluate the heat conduction speed and range; Combining real-time data and prediction results, it is evaluated which battery cells and their adjacent areas have reached critical temperatures, thereby triggering the next preventive measures.

5. The method for controlling the temperature of an electric ship battery pack according to claim 1, characterized in that: Based on the heat source expansion assessment results, the cooling system is automatically scheduled to perform cooling priority processing, focusing on cooling the abnormal area and its adjacent areas to prevent heat from spreading to the rest of the battery pack and ensure that local cooling is prioritized. The specific steps are as follows: After completing the evaluation of the heat source expansion, the heat conduction range is accurately predicted to determine the priority areas for cooling, that is, to locate the areas with the most severe temperature anomalies and their adjacent areas. The calculation expression is as follows: , where and Battery monomer and battery cells The temperature value, is the temperature difference, through the temperature difference To evaluate the heat from abnormal battery Conducted to adjacent cells speed, so as to determine which adjacent areas need to be cooled first; According to the heat source expansion assessment results, the cooling intensity of each area is determined. The calculation expression is as follows: , where is the amount of heat that the cooling system needs to transfer. is the flow rate of cooling medium, is the specific heat capacity of the cooling medium, is the temperature difference in the target area; After confirming the cooling demand, the working priority of the cooling system will be adjusted according to the evaluation results of the heat source, and the cooling priority will be scheduled by the following formula: , where is the maximum safe temperature of the battery pack, Cooling priority refers to the degree and order in which the cooling system prioritizes cooling of areas in the battery pack temperature control system based on the temperature status of the battery cells and the risk of heat source expansion; Once the cooling priority is determined, the working state of the cooling system is adjusted in real time. The cooling strategy is optimized to prevent the heat source from spreading to the rest of the battery pack. The temperature changes of each battery area are monitored in real time, and the cooling effect is dynamically adjusted as needed. The calculation expression is as follows: , where It is the cooling power, which indicates the heat absorbed and removed from the battery cell area by the cooling system per unit time.

6. The method for controlling the temperature of an electric ship battery pack according to claim 1, characterized in that: Combining real-time monitored temperature data with historical temperature control data, the cooling strategy is optimized through data analysis and artificial intelligence algorithms, and the cooling intensity and response time of the cooling system are dynamically adjusted. Based on the temperature change trend of the battery pack, the thermal runaway risk is predicted in advance and optimized in real time to ensure the temperature control efficiency and battery performance of the battery pack. The specific steps are as follows: In the battery pack of electric ships, the integration of real-time monitoring temperature data and historical temperature control data is the basis for the optimization of the entire temperature control strategy. First, the temperature data of each single battery is obtained from each sensor in the battery pack in real time, and it is compared with the historical temperature control data. The integrated data provides a comprehensive temperature control status background. According to the input data, a dynamic temperature control model is established and calculated by the following formula: , where It's time point The temperature value at the moment, is the initial temperature, is the average temperature increment, is the natural base, It is the response speed factor of the cooling system, reflecting the efficiency of the cooling system; The data analysis stage involves deep learning of real-time temperature data and historical data to identify the temperature change trend of the battery pack and then predict the temperature trend of the battery pack in the future. In order to capture the trend of battery temperature changes, a regression analysis method based on machine learning is used to effectively identify the time series pattern in the historical temperature data and predict future temperature changes. The calculation expression is as follows: , where is the predicted temperature at the next moment, is the mapping function learned by the LSTM model, It's the past Temperature data at the moment; Based on data analysis and trend prediction, an optimization algorithm is used to adjust the cooling strategy. The core goal is to reduce the temperature of the battery cells by optimizing the behavior of the cooling system while avoiding energy waste caused by overcooling. The calculation expression is as follows: , where is the cooling capacity required by the cooling system, is the efficiency factor of the cooling system, is the power consumption of the cooling system, is the ambient temperature; Finally, based on the predicted temperature trend and the optimized cooling strategy, the risk of thermal runaway is predicted in real time, and the strategy is adjusted immediately when the actual temperature is about to exceed the safe range. The probability of thermal runaway under different temperature control measures is evaluated, and the calculation expression is as follows: , where is the thermal runaway risk value, i.e., the time point The thermal runaway risk value at the moment, is the maximum safe temperature of the battery pack, is the probability that the temperature exceeds the maximum safe temperature, is the risk function.

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