A method and device for precisely controlling the temperature of a battery electrolyte

Abstract

The present application provides a method and device for precisely controlling the temperature of a battery electrolyte, relating to the field of optimization control technology, including: dynamically monitoring to obtain the real-time temperature, and judging whether the real-time stack temperature of the battery electrolyte in the real-time temperature conforms to the predetermined stack operating temperature constraint; if the real-time stack temperature conforms to the predetermined stack operating temperature constraint, reading the predetermined future moment; performing predictive analysis on the stack temperature time series established based on the real-time stack temperature to obtain the predicted stack temperature at the predetermined future moment; when the predicted stack temperature does not conform to the predetermined stack operating temperature constraint, activating the precise temperature control mechanism in real time; and performing precise temperature control processing on the battery electrolyte through the precise temperature control mechanism. Through the present application, the technical problem in the prior art that the stability of battery performance and the service life are affected due to the low efficiency of the traditional cooling method and the lack of real-time dynamic adjustment ability can be solved, and the technical effect of improving battery performance and extending the service life can be achieved.

Description

Technical Field

[0001] The present application relates to the field of optimization control technology, and in particular to a method and device for precise temperature control of battery electrolyte. Background Art

[0002] With the rapid development of technology, particularly in the fields of new energy and electric vehicles, lithium batteries, as key energy storage devices, have been widely used in electric vehicles, smartphones, and other portable electronic devices. However, due to the complexity of their internal chemical reactions and the variability of their operating environment, lithium batteries are prone to overheating and excessive discharge over long periods of use and high loads. These problems can lead to decreased battery performance, shortened lifespan, and even safety accidents. Therefore, effectively managing battery temperature to ensure operation within a stable and ideal temperature range has become a key technology for improving battery performance and safety.

[0003] Currently, existing battery temperature control technologies mainly focus on regulating battery temperature through cooling systems, such as air cooling and liquid cooling. However, these traditional temperature control technologies have certain defects. For example, although the air cooling system has a simple structure, its efficiency is relatively low and cannot meet the heat dissipation requirements of high-power batteries; the liquid cooling system requires more complex piping and radiator designs, which is costly and prone to efficiency degradation in low-temperature environments. In addition, existing battery temperature control solutions are usually based on a fixed temperature range and lack the ability to monitor and adjust in real time. They are unable to cope with temperature fluctuations of the battery under different operating conditions. This results in the battery management system being unable to accurately control the battery temperature, resulting in energy waste and performance degradation.

[0004] In summary, the existing technology has technical problems such as the low efficiency of traditional cooling methods and the lack of real-time dynamic adjustment capabilities, which make it impossible to meet the temperature control requirements of high-power batteries under different working conditions, further affecting the stability of battery performance and service life. Summary of the Invention

[0005] The purpose of this application is to provide a precise temperature control method and device for battery electrolyte, so as to solve the technical problem in the prior art that the traditional cooling method has low efficiency and lacks real-time dynamic adjustment capability, resulting in the inability to meet the temperature control requirements of high-power batteries under different working conditions, further affecting the stability of battery performance and service life.

[0006] In view of the above problems, the present application provides a method and device for precise temperature control of battery electrolyte.

[0007] In a first aspect, the present application provides a method for precisely controlling the temperature of a battery electrolyte, which is implemented by a device for precisely controlling the temperature of a battery electrolyte, and includes: dynamically monitoring to obtain a real-time temperature, and determining whether the real-time stack temperature of the battery electrolyte in the real-time temperature meets a predetermined stack operating temperature constraint; if the real-time stack temperature meets the predetermined stack operating temperature constraint, reading a predetermined future time; performing a predictive analysis on the stack temperature time series established based on the real-time stack temperature to obtain the predicted stack temperature at the predetermined future time; when the predicted stack temperature does not meet the predetermined stack operating temperature constraint, activating a precise temperature control mechanism in real time; and performing a precise temperature control process on the battery electrolyte through the precise temperature control mechanism.

[0008] In a second aspect, the present application further provides a device for precisely controlling the temperature of a battery electrolyte, which is used to execute the method for precisely controlling the temperature of a battery electrolyte as described in the first aspect, and includes: a judgment module, which is used to dynamically monitor to obtain a real-time temperature and determine whether the real-time stack temperature of the battery electrolyte in the real-time temperature meets a predetermined stack operating temperature constraint; a reading module, which is used to read a predetermined future time if the real-time stack temperature meets the predetermined stack operating temperature constraint; a prediction module, which is used to perform a predictive analysis on the stack temperature time series established based on the real-time stack temperature to obtain the predicted stack temperature at the predetermined future time; an activation module, which is used to activate a precise temperature control mechanism in real time when the predicted stack temperature does not meet the predetermined stack operating temperature constraint; and a temperature control module, which is used to perform a precise temperature control process on the battery electrolyte through the precise temperature control mechanism.

[0009] The technical solution provided in the present application has at least the following technical effects or advantages: by dynamically monitoring to obtain a real-time temperature and determining whether the real-time stack temperature of the battery electrolyte in the real-time temperature meets a predetermined stack operating temperature constraint; if the real-time stack temperature meets the predetermined stack operating temperature constraint, reading a predetermined future time; performing a predictive analysis on the stack temperature time series established based on the real-time stack temperature to obtain the predicted stack temperature at the predetermined future time; when the predicted stack temperature does not meet the predetermined stack operating temperature constraint, activating a precise temperature control mechanism in real time; and performing a precise temperature control process on the battery electrolyte through the precise temperature control mechanism. That is to say, by achieving the technical goal of precisely controlling the battery temperature, the technical effects of improving the battery performance and extending the service life are achieved.

[0010] The above description is only an overview of the technical solution of the present application. In order to better understand the technical means of the present application, it can be implemented according to the content of the specification. In order to make the above and other purposes, features, and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically described below. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understood through the following description of the specification. Brief Description of the Drawings

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only exemplary. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0012] Figure 1 It is a schematic flowchart of a precise temperature control method for a battery electrolyte of the present application;

[0013] Figure 2 It is a schematic structural diagram of a precise temperature control device for a battery electrolyte of the present application.

[0014] Description of the reference numerals: judgment module 11, reading module 12, prediction module 13, activation module 14, temperature control module 15. Detailed Embodiments

[0015] By providing a precise temperature control method and device for a battery electrolyte, the present application solves the technical problem in the prior art that due to the low efficiency of traditional cooling methods and the lack of real-time dynamic adjustment capabilities, the temperature control requirements of high-power batteries in different working states cannot be met, further affecting the stability of battery performance and service life. The technical goal of precisely controlling the battery temperature is achieved, and the technical effect of improving battery performance and extending service life is achieved.

[0016] Next, the technical solutions in the present application will be clearly and completely described with reference to the drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the example embodiments described here. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application. Additionally, it should be noted that for the sake of convenience of description, only the parts related to the present application are shown in the drawings rather than all of them.

[0017] Embodiment 1, please refer to the attached Figure 1, this application provides a precise temperature control method for battery electrolyte, which is applied to a precise temperature control device for battery electrolyte, and specifically includes the following steps:

[0018] Step 1: Dynamically monitor the real-time temperature and determine whether the real-time stack temperature of the battery electrolyte in the real-time temperature meets the predetermined stack operating temperature constraint.

[0019] Specifically, dynamic monitoring means observing the changes of a certain device during operation by collecting data in real time. For example, in a battery management system, dynamic monitoring can obtain the temperature information of the battery electrolyte in real time. This information is transmitted to the monitoring system through sensors or temperature probes, and corresponding judgments are made based on this data. The real-time temperature refers to the instantaneous temperature of the current battery electrolyte, which can change over time. For example, during the charging and discharging of the battery, the internal temperature of the battery may increase or decrease with the change of current. The real-time stack temperature of the battery electrolyte refers to the temperature of the electrolyte in the battery stack, which is used to evaluate the operating state of the battery. The real-time stack temperature affects the safety and efficiency of the battery because too high or too low temperature may cause the battery performance to decline or be damaged. By setting a safe operating temperature range as the predetermined stack operating temperature constraint. By monitoring the real-time temperature and comparing it with the predetermined stack operating temperature constraint, it is possible to timely detect whether the battery is in a normal operating state. If the temperature of the battery electrolyte is too high or too low, corresponding measures can be taken, such as adjusting the cooling system or reminding the operator to check, to ensure the safe operation of the battery.

[0020] Step 2: If the real-time stack temperature meets the predetermined stack operating temperature constraint, read the predetermined future time.

[0021] Specifically, the predetermined stack operating temperature constraint refers to a temperature range set to ensure the safe and efficient operation of the battery. When the currently measured battery stack temperature meets the set safe operating temperature range, read the predetermined future time. The predetermined future time refers to the temperature state or the time for the next operation to be performed after a period of time calculated based on the current temperature control and time difference parameters. By setting this future time in advance, precise temperature control adjustment can be carried out to ensure that the battery always remains within an appropriate temperature range, thereby avoiding the problems of overheating or overcooling of the battery and ensuring the stability and service life of the battery.

[0022] Step 3: Perform predictive analysis on the stack temperature time series established based on the real-time stack temperature to obtain the predicted stack temperature at the predetermined future time.

[0023] Specifically, through real-time acquisition by sensors, it is used to reflect the thermal state of the battery pack during operation. The temperature data is arranged in chronological order to establish a time series of the stack temperature, reflecting the law of the stack temperature changing over time. By predicting and analyzing this time series of the stack temperature, the temperature change trend of the stack at a future moment is predicted. Based on the existing real-time temperature data, the temperature of the stack at a certain future moment is calculated to obtain the predicted stack temperature at the predetermined future moment.

[0024] Step Four: When the predicted stack temperature does not meet the predetermined stack operating temperature constraint, the precise temperature control mechanism is activated in real time.

[0025] Specifically, when the predicted stack temperature does not meet the predetermined stack operating temperature constraint, it means that the temperature of the stack may deviate from the temperature range required by the design, thus affecting the working efficiency and safety of the battery. Then, the precise temperature control mechanism is activated in real time. The precise temperature control mechanism is an automated temperature control system used to adjust the temperature of the stack to ensure that it is maintained within a predetermined range. The temperature control mechanism can lower the battery temperature through a cooling system (such as liquid cooling or air cooling), or raise the temperature through devices such as heaters. Furthermore, by controlling the temperature, it ensures that the stack operates within an ideal temperature range, thereby enhancing the safety and performance of the battery.

[0026] Step Five: Perform precise temperature control on the battery electrolyte through the precise temperature control mechanism.

[0027] Specifically, perform precise temperature control on the battery electrolyte through the precise temperature control mechanism to ensure its operation in the best working state. The precise temperature control mechanism maintains the stability of the battery electrolyte by precisely controlling different parameters such as temperature, pressure, and flow rate. For example, if the temperature of the battery is greater than its designed operating temperature, the precise temperature control mechanism may lower its temperature by increasing the cooling air flow or reducing the flow rate of the electrolyte until it reaches the preset temperature value. Through the temperature control mechanism, it can ensure that the battery operates within a safe and efficient temperature range, thereby increasing the service life of the battery, reducing energy waste, and preventing failures or damages caused by overheating.

[0028] The method for precise temperature control of a battery electrolyte is applied to a device for precise temperature control of a battery electrolyte, which can achieve the technical goal of precisely controlling the battery temperature and achieve the technical effect of improving battery performance and extending service life.

[0029] Furthermore, this application also includes: obtaining the tube length parameter of the vortex tube, where the vortex tube refers to the connecting tube connecting the precise temperature control mechanism and the battery electrolyte; obtaining the predetermined flow rate of compressed air, and obtaining the temperature control time difference in combination with the tube length parameter; based on the temperature control time difference and the real-time moment when the real-time stack temperature is obtained, determining the predetermined future moment.

[0030] Specifically, the length information of the vortex tube is obtained through measurement or calculation to acquire the tube length parameter of the vortex tube. Here, the vortex tube refers to a pipeline for transferring gas or liquid, which is used to regulate the temperature of the fluid flowing through the pipeline. The vortex tube is connected to the precise temperature control mechanism and the battery electrolyte to ensure the stability of the internal temperature of the battery. The tube length parameter refers to the physical length of the vortex tube, which plays an important role in the temperature control effect and the response speed of the system. For example, a longer tube length may lead to an extended gas flow time, thereby affecting the efficiency of temperature regulation.

[0031] Next, the predetermined flow rate of the compressed air is obtained. The compressed air is set to flow through the vortex tube at a certain speed to assist in temperature control. The predetermined flow rate refers to the set flow rate value, which is optimized according to actual requirements to ensure that the compressed air can effectively carry away excess heat or maintain temperature stability. By controlling the flow rate of the compressed air, the temperature of the battery electrolyte can be adjusted more precisely. Too low flow rate may result in untimely temperature regulation, while too high flow rate may waste energy or cause excessive temperature fluctuations in the system.

[0032] Then, based on the length of the vortex tube and the flow rate of the compressed air, the time difference required for temperature regulation is calculated. The temperature control time difference reflects the response speed of the temperature control system. The longer the tube length, the longer the air flow time, and thus it may take longer to complete the predetermined temperature regulation. Therefore, by combining the tube length and the flow rate, the time required for temperature change can be predicted and adjusted in advance to avoid too high or too low temperature.

[0033] Finally, based on the temperature control time difference and the real-time moment of the acquired real-time stack temperature, a predetermined future moment is determined. By real-time monitoring the battery stack temperature and combining with the temperature control time difference, the temperature state at a future moment is calculated. The real-time moment refers to the current time point of the system. By combining this time point with the temperature control time difference, it can be predicted when the temperature control effect will reach the expected target. For example, if it is preset to reach a certain temperature after five minutes, the flow rate of the compressed air and other control parameters are adjusted according to the temperature control time difference to ensure that the temperature of the battery electrolyte reaches the predetermined range at the future moment.

[0034] Furthermore, this application also includes: establishing the stack temperature time series according to the mapping relationship between the real-time stack temperature and the real-time moment; drawing a stack temperature scatter plot based on the stack temperature time series and obtaining the stack temperature trend line of the stack temperature scatter plot; obtaining the stack temperature at the predetermined future moment according to the stack temperature trend line and denoting it as the predicted stack temperature.

[0035] Specifically, according to the mapping relationship between the real-time stack temperature and the real-time moment, a stack temperature time series is established. The real-time stack temperature refers to the temperature of the battery stack at any moment, and the real-time moment refers to the current time point, and each temperature value corresponds to a specific time. By corresponding each temperature data point with the corresponding time point one by one, a sequence of temperature changes is gradually formed, which is the stack temperature time series.

[0036] By plotting each temperature value in the stack temperature time series against its corresponding time point on the coordinate axis, a stack temperature scatter plot is obtained. In the scatter plot, the horizontal axis represents time and the vertical axis represents temperature, and each point represents the temperature at a specific time point. The fluctuation of the battery temperature at different times can be visually obtained through the scatter plot. Further, based on the scatter points, a stack temperature trend line is calculated and plotted to reflect the overall direction of temperature change, such as rising, falling or remaining stable.

[0037] Based on the stack temperature trend line, the stack temperature at a specific future moment is predicted. For example, if the trend line indicates that the temperature rises at a certain rate every minute, then it can be inferred according to this trend that if five minutes later is the predetermined future moment, the stack temperature will be higher than the current temperature. The temperature value calculated from the trend line is recorded as the predicted value to estimate the change of the future stack temperature. The predicted stack temperature is not the real-time temperature, but an estimated value calculated based on the trend line and historical temperature data, which provides a reference basis for subsequent temperature control and battery management.

[0038] Further, this application also includes: performing spline fitting on the stack temperature scatter plot based on the principle of spline curves to obtain a stack temperature fitting curve; obtaining the stack temperature fitting polynomial of the stack temperature fitting curve; inputting the predetermined future moment into the stack temperature fitting polynomial to obtain a second predicted stack temperature; and performing calibration and adjustment on the predicted stack temperature with the second predicted stack temperature.

[0039] Specifically, the spline curve is a smooth curve fitting method that constructs a smooth and continuous curve by connecting the data points. In the stack temperature scatter plot, each scatter point represents a time point and the corresponding temperature value. By spline fitting, the scatter points are constructed into a smooth curve to more accurately represent the change trend of the stack temperature over time. The stack temperature fitting curve obtained by fitting can reflect the fluctuation of the actual data and also eliminate the noise in the data, making the temperature change trend clearer and more stable.

[0040] Obtain the stack temperature fitting polynomial of the stack temperature fitting curve. The stack temperature fitting polynomial can describe the relationship between the stack temperature and time. The stack temperature fitting polynomial is a set of coefficients representing the law of temperature change with time. For example, if the fitted polynomial is a quadratic polynomial, it may be that the temperature is equal to a constant plus a linear change in time plus a term of the square of time.

[0041] Input the predetermined future time into the stack temperature fitting polynomial to obtain the second predicted stack temperature at that time. The second predicted stack temperature is a predicted value deduced from the trend of historical temperature data. Through prediction, the temperature change of the battery in the future period can be predicted, which helps to judge whether further temperature control measures need to be taken.

[0042] There may be errors in predicting the stack temperature. Therefore, compare the second predicted stack temperature obtained based on the stack temperature fitting curve with the actual predicted temperature to judge whether they are consistent. If there is a deviation, the prediction result needs to be adjusted, such as recalculating the polynomial coefficients or correcting the future prediction according to the actual temperature situation. Through verification, the accuracy of the prediction can be improved, ensuring the reliability of the battery temperature control system.

[0043] Furthermore, this application also includes: extracting the real-time ambient temperature from the real-time temperature; establishing the ambient temperature time series according to the mapping relationship between the real-time ambient temperature and the real-time moment; analyzing the ambient temperature time series to obtain the predicted ambient temperature; using the predicted stack temperature and the predicted ambient temperature as the precise temperature control constraints, and optimizing to obtain the optimal temperature control strategy; the precise temperature control mechanism performs precise temperature control processing on the battery electrolyte based on the optimal temperature control strategy.

[0044] Specifically, extract the real-time ambient temperature from the real-time temperature to identify the temperature information related to the environment. The ambient temperature refers to the temperature change in the battery working environment, such as the temperature of the surrounding air, which may affect the working state and efficiency of the battery.

[0045] Next, associate each real-time collected ambient temperature with its corresponding specific time (i.e., the real-time moment), thereby forming a time series of temperature changes, and further obtaining the change trend of the ambient temperature at different time points.

[0046] Analyze the ambient temperature time series to obtain the predicted ambient temperature, that is, through time series analysis or prediction models (such as regression analysis or machine learning methods), by analyzing the known ambient temperature time series, infer the ambient temperature at a future moment.

[0047] Furthermore, the predicted stack temperature and the predicted ambient temperature respectively represent the expected values of the temperature of the battery stack and the external ambient temperature. Using the predicted stack temperature and the predicted ambient temperature as the precise temperature control constraints, the optimal temperature control strategy is obtained through optimization. The precise temperature control constraints refer to the temperature control measures that need to be taken based on these temperature data to maintain the best working state of the battery. The most suitable temperature control strategy is found through an optimization algorithm, such as adjusting the flow rate or temperature of the cooling system, to ensure that the temperature of the battery electrolyte remains within the ideal range.

[0048] Finally, the precise temperature control mechanism performs precise temperature control on the battery electrolyte based on the optimal temperature control strategy. The precise temperature control mechanism is an automated control system that controls the temperature of the electrolyte inside the battery according to the optimal temperature control strategy, ensuring that the temperature of the battery always remains within a safe and efficient range. For example, if the battery temperature is too high, the temperature control mechanism will reduce the battery temperature by accelerating the coolant circulation or starting other cooling devices, thus avoiding damage caused by overheating of the battery.

[0049] Furthermore, this application also includes: constructing a temperature control index set for the precise temperature control mechanism, where the temperature control index set refers to a set of control indexes for the precise temperature control mechanism to control the compressed air entering the battery electrolyte; extracting the first temperature control index from the temperature control index set, where the first temperature control index has an identifier of the first temperature control parameter threshold; under the precise temperature control constraints, constructing a temperature control optimization space based on the first temperature control parameter threshold, and using the temperature control fitness evaluation function as the temperature control optimization evaluation strategy to obtain the optimal temperature control strategy.

[0050] Specifically, constructing the temperature control index set of the precise temperature control mechanism refers to a set of parameters used to precisely adjust the temperature. The temperature control index set is the key index for the precise temperature control mechanism to adjust and control the compressed air entering the battery electrolyte. By controlling these indexes, the precise temperature control mechanism can ensure that the temperature of the battery electrolyte is maintained within a predetermined range, preventing the temperature from being too high or too low from affecting the performance or safety of the battery. For example, controlling parameters such as the temperature, flow rate, and pressure of the compressed air can directly affect the temperature change of the electrolyte.

[0051] Then, a temperature control parameter is randomly selected from the temperature control index set as the first temperature control index. The first temperature control index has an identifier of the first temperature control parameter threshold, and exceeding the first temperature control parameter threshold may lead to temperature control failure or a decrease in the performance of the battery. The first temperature control parameter threshold is obtained by a person skilled in the art through custom setting according to the actual situation.

[0052] Under the precise temperature control constraint, the temperature of the battery electrolyte is controlled to keep it within the predetermined operating range, thereby improving the efficiency and life of the system. Precise temperature control constraints include restrictions on temperature fluctuations, as well as requirements on energy consumption and other related factors. Based on the precise temperature control constraint, the first temperature control parameter threshold is set. The first temperature control parameter threshold defines the upper and lower limits of parameters such as temperature, energy consumption, and efficiency under different working conditions. According to the method for obtaining the first temperature control parameter threshold, multiple groups of temperature control parameter thresholds are obtained, and a temperature control optimization space is constructed, including all possible temperature control strategies. Then, by changing the values of different parameters, the optimal solution that can meet the precise temperature control constraint is found.

[0053] Next, the effectiveness of each temperature control strategy is quantitatively evaluated using a temperature control fitness evaluation function as a temperature optimization strategy. This function integrates multiple evaluation metrics, such as energy consumption, efficiency, and noise, and calculates the fitness of each strategy to determine which performs best under given constraints. Ultimately, this fitness evaluation of the temperature control strategies yields an optimal temperature control strategy that optimizes battery performance while ensuring precise temperature control constraints.

[0054] Furthermore, the present application also includes: the temperature control index set includes pressure, flow rate, temperature and humidity for controlling the compressed air.

[0055] Specifically, the temperature control index set refers to a collection of multiple parameters used to regulate and control temperature, including pressure, flow rate, temperature, and humidity. Pressure refers to the force exerted by compressed air in a pipe, directly affecting the efficiency of air flow and the density of the gas. For example, in a compressed air system, higher pressure may accelerate air flow, improving cooling effectiveness; lower pressure may slow air flow and reduce cooling capacity. Flow rate refers to the speed at which compressed air flows through a pipe or system. Regulating flow rate plays a critical role in temperature control, as excessively high flow rates can lead to uneven cooling, while excessively low flow rates may prevent the air's temperature from being effectively transferred to the object being cooled. For example, properly adjusting flow rate ensures that air flowing over battery surfaces effectively removes heat, thereby maintaining the battery within a safe operating temperature range. Temperature refers to the temperature of the compressed air itself and is related to its flow rate and pressure. Excessively high compressed air temperature exacerbates battery temperature increases, affecting battery performance and safety; excessively low temperature may result in ineffective cooling. Therefore, controlling compressed air temperature is a crucial factor in maintaining a stable battery operating temperature. Humidity refers to the water vapor content in the air. Excessive humidity can cause condensation of moisture in the air, adversely affecting battery safety and system stability, especially in electronic devices. Therefore, controlling humidity levels can prevent moisture from damaging devices and thus improve system reliability.

[0056] Furthermore, this application also includes: The expression of the temperature control fitness evaluation function is as follows: ; where represents the temperature control fitness, represents the temperature control stability coefficient, refers to the temperature control evaluation index parameter of the th temperature control evaluation index, refers to the weight coefficient of the th temperature control evaluation index, and = 1, represents the number of temperature control evaluation indexes, and , where the temperature control evaluation indexes at least include energy consumption, efficiency, and noise.

[0057] Specifically, the temperature control fitness evaluation function is used to measure the quality of the temperature control strategy, evaluate the performance of the temperature control strategy in actual operation through a series of parameters, and help determine the optimal temperature control strategy. The temperature control fitness represents the overall effect of the temperature control strategy. The higher the fitness, the better the temperature control effect, and vice versa.

[0058] The temperature control stability coefficient is a parameter that measures whether the temperature control process is stable. Temperature stability is crucial for the battery system. Excessive temperature fluctuations will affect the life and efficiency of the battery. Therefore, the larger the value of the temperature control stability coefficient, the better the performance of the temperature control strategy in maintaining temperature stability.

[0059] The th temperature control evaluation index parameter refers to the parameter set for each specific evaluation index when evaluating the temperature control strategy, which is used to measure the performance of the temperature control strategy in multiple dimensions, such as energy efficiency, efficiency, and noise. Each evaluation index has a corresponding parameter to reflect the degree of influence of the index on the temperature control effect.

[0060] The th temperature control evaluation index weight coefficient refers to the relative importance of each temperature control evaluation index in the entire evaluation. In the evaluation process, a weight coefficient is set for each evaluation index. The larger the value of the weight coefficient, the greater the influence of the evaluation index on the temperature control fitness, and vice versa.

[0061] = 1 means that the sum of the weight coefficients is 1, ensuring that the sum of the weights of all indexes does not exceed 100% and avoiding the excessive influence of a certain index on the entire evaluation result.

[0062] The number of temperature control evaluation indexes Refers to the number of evaluation criteria considered when evaluating the temperature control strategy. Since the performance of the temperature control strategy involves multiple aspects, multiple evaluation indicators are required to comprehensively judge its effectiveness. According to requirements, the number of temperature control evaluation indicators can vary, but at least includes three aspects: energy consumption, efficiency, and noise. Among them, energy consumption represents the amount of energy consumed during the temperature control process, efficiency is the ratio of the energy and time invested in achieving the required goal by the temperature control strategy, and noise takes into account the possible noise pollution during the temperature control process.

[0063] Furthermore, this application also includes: extracting the first temperature control strategy in the temperature control optimization space, and simulating the first temperature control strategy to obtain the first temperature control simulation record; performing optimization evaluation on the first temperature control simulation record according to the temperature control optimization evaluation strategy to obtain the first temperature control fitness; extracting the second temperature control strategy in the temperature control optimization space, and simulating the second temperature control strategy to obtain the second temperature control simulation record; performing optimization evaluation on the second temperature control simulation record according to the temperature control optimization evaluation strategy to obtain the second temperature control fitness; determining the optimal temperature control strategy according to the comparison result of comparing the first temperature control fitness with the second temperature control fitness.

[0064] Specifically, randomly extract the first temperature control strategy from the temperature control optimization space. The temperature control optimization space refers to the set of all possible temperature control strategies. By selecting different strategies within this space, the most suitable solution can be found. According to the first temperature control strategy, simulate the actual operating environment through simulation testing to evaluate the performance of this temperature control strategy, thereby obtaining the first temperature control simulation record, including the changes of various parameters during the temperature control process, such as the rate of temperature change, adjustment accuracy, etc.

[0065] Then, perform optimization evaluation on the first temperature control simulation record based on the temperature control fitness evaluation function in the temperature control optimization evaluation strategy, and analyze the simulation record, including factors such as the stability of temperature control, energy consumption efficiency, response speed, etc. Through evaluation, the first temperature control fitness can be obtained, which is used to measure the standard of whether this strategy can meet the expected control requirements. The higher the first temperature control fitness, the better the strategy may perform in actual operation, and vice versa.

[0066] Randomly extract the second temperature control strategy in the temperature control optimization space, select another temperature control solution for simulation, and obtain the second temperature control simulation record. By evaluating the performance of the second temperature control strategy under the same conditions, the second temperature control simulation record is obtained.

[0067] Then, based on the temperature control fitness evaluation function in the temperature control optimization evaluation strategy, an optimization evaluation is performed on the second temperature control simulation record, and the simulation record is analyzed, including factors such as the stability of temperature control, energy consumption efficiency, response speed, etc. Through the evaluation, the second temperature control fitness can be obtained, which is used to measure the standard for whether the strategy can meet the expected control requirements. The higher the second temperature control fitness, the better the strategy may perform in actual operation, and vice versa.

[0068] Finally, by comparing the first temperature control fitness and the second temperature control fitness, a comparison result is obtained to determine which strategy has a higher fitness, thereby selecting the optimal temperature control strategy. The optimal temperature control strategy refers to a solution that can better meet the battery temperature control requirements among all tested strategies and can effectively maintain the battery electrolyte within a safe and efficient temperature range.

[0069] In summary, the precise temperature control method for a battery electrolyte provided by this application has the following technical effects: obtaining the real-time temperature through dynamic monitoring, and judging whether the real-time stack temperature of the battery electrolyte in the real-time temperature conforms to the predetermined stack working temperature constraint; if the real-time stack temperature conforms to the predetermined stack working temperature constraint, reading the predetermined future moment; performing predictive analysis on the stack temperature time series established based on the real-time stack temperature to obtain the predicted stack temperature at the predetermined future moment; when the predicted stack temperature does not conform to the predetermined stack working temperature constraint, activating the precise temperature control mechanism in real time; performing precise temperature control processing on the battery electrolyte through the precise temperature control mechanism, that is, by achieving the technical goal of precisely controlling the battery temperature, achieving the technical effects of improving battery performance and extending service life.

[0070] Embodiment 2, based on the precise temperature control method for a battery electrolyte in the foregoing embodiment and with the same inventive concept, this application also provides a precise temperature control device for a battery electrolyte. Please refer to the appendix Figure 2 , including: a judgment module 11, which is used to dynamically monitor and obtain the real-time temperature, and judge whether the real-time stack temperature of the battery electrolyte in the real-time temperature conforms to the predetermined stack working temperature constraint; a reading module 12, which is used to read the predetermined future moment if the real-time stack temperature conforms to the predetermined stack working temperature constraint; a prediction module 13, which is used to perform predictive analysis on the stack temperature time series established based on the real-time stack temperature to obtain the predicted stack temperature at the predetermined future moment; an activation module 14, which is used to activate the precise temperature control mechanism in real time when the predicted stack temperature does not conform to the predetermined stack working temperature constraint; a temperature control module 15, which is used to perform precise temperature control processing on the battery electrolyte through the precise temperature control mechanism.

[0071] Further, the precise temperature control device for the battery electrolyte is further configured to: obtain the pipe length parameter of the vortex tube, where the vortex tube refers to the connecting pipe connecting the precise temperature control mechanism and the battery electrolyte; obtain the predetermined flow rate of the compressed air, and obtain the temperature control time difference in combination with the pipe length parameter; based on the temperature control time difference and the real-time moment when the real-time stack temperature is obtained, determine the predetermined future moment.

[0072] Further, the precise temperature control device for the battery electrolyte is further configured to: establish the stack temperature time series according to the mapping relationship between the real-time stack temperature and the real-time moment; draw a stack temperature scatter plot based on the stack temperature time series, and obtain the stack temperature trend line of the stack temperature scatter plot; obtain the stack temperature at the predetermined future moment according to the stack temperature trend line, and record it as the predicted stack temperature.

[0073] Further, the precise temperature control device for the battery electrolyte is further configured to: perform spline fitting on the stack temperature scatter plot based on the spline curve principle to obtain a stack temperature fitting curve; obtain the stack temperature fitting polynomial of the stack temperature fitting curve; input the predetermined future moment into the stack temperature fitting polynomial to obtain a second predicted stack temperature; use the second predicted stack temperature to calibrate and adjust the predicted stack temperature.

[0074] Further, the precise temperature control device for the battery electrolyte is further configured to: extract the real-time ambient temperature from the real-time temperature; establish the ambient temperature time series according to the mapping relationship between the real-time ambient temperature and the real-time moment; analyze the ambient temperature time series to obtain the predicted ambient temperature; use the predicted stack temperature and the predicted ambient temperature as precise temperature control constraints, and optimize to obtain the optimal temperature control strategy; the precise temperature control mechanism performs precise temperature control processing on the battery electrolyte based on the optimal temperature control strategy.

[0075] Further, the precise temperature control device for the battery electrolyte is further configured to: form a temperature control index set of the precise temperature control mechanism, where the temperature control index set refers to the set of control indexes for the precise temperature control mechanism to control the compressed air to enter the battery electrolyte; extract the first temperature control index from the temperature control index set, and the first temperature control index has the identification of the first temperature control parameter threshold; under the precise temperature control constraint, form a temperature control optimization space based on the first temperature control parameter threshold, and use the temperature control fitness evaluation function as the temperature control optimization evaluation strategy to obtain the optimal temperature control strategy.

[0076] Further, the precise temperature control device for the battery electrolyte is further configured to: the temperature control index set includes the pressure, flow rate, temperature and humidity for controlling the compressed air.

[0077] Further, the precise temperature control device for a battery electrolyte is also used for: The expression of the temperature control fitness evaluation function is as follows: ; where refers to the temperature control fitness refers to the temperature control stability coefficient refers to the temperature control evaluation index parameter of the th temperature control evaluation index refers to the weight coefficient of the th temperature control evaluation index, and = 1 refers to the number of temperature control evaluation indexes, and , where the temperature control evaluation indexes at least include energy consumption, efficiency, and noise

[0078] [[ID= 23]]Further, the precise temperature control device for a battery electrolyte is also used for: Extracting the first temperature control strategy in the temperature control optimization space, and performing simulation on the first temperature control strategy to obtain the first temperature control simulation record; Performing optimization evaluation on the first temperature control simulation record according to the temperature control optimization evaluation strategy to obtain the first temperature control fitness; Extracting the second temperature control strategy in the temperature control optimization space, and performing simulation on the second temperature control strategy to obtain the second temperature control simulation record; Performing optimization evaluation on the second temperature control simulation record according to the temperature control optimization evaluation strategy to obtain the second temperature control fitness; Determining the optimal temperature control strategy according to the comparison result obtained by comparing the first temperature control fitness with the second temperature control fitness

[0079] In the present specification, each embodiment is described in a progressive manner, and the key point of each embodiment is the difference from other embodiments. The precise temperature control method and specific examples in the foregoing Embodiment 1 are equally applicable to the precise temperature control device in this embodiment. Through the foregoing detailed description of the precise temperature control method for a battery electrolyte, those skilled in the art can clearly know the precise temperature control device in this embodiment. Therefore, for the sake of brevity of the specification, it will not be elaborated herein

[0080] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein

[0081] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of this application and its equivalent technologies, this application also intends to include these changes and modifications.

Claims

1. A precise temperature control method for battery electrolyte, characterized in that: include: Dynamically monitoring and obtaining a real-time temperature, and determining whether a real-time stack temperature of the battery electrolyte in the real-time temperature complies with a predetermined stack operating temperature constraint; If the real-time stack temperature meets the predetermined stack operating temperature constraint, reading the predetermined future time includes: Obtaining a tube length parameter of a vortex tube, wherein the vortex tube refers to a connecting tube connecting a precise temperature control mechanism and the battery electrolyte; Obtaining a predetermined flow rate of compressed air and obtaining a temperature control time difference in combination with the pipe length parameter; Determining the predetermined future time based on the temperature control time difference and the real time of obtaining the real-time stack temperature; Performing a forecast analysis on the stack temperature time series established based on the real-time stack temperature to obtain the forecasted stack temperature at the predetermined future time, including: Establishing the stack temperature time series according to the mapping relationship between the real-time stack temperature and the real-time moment; Obtaining a stack temperature scatter plot based on the stack temperature time series, and obtaining a stack temperature trend line of the stack temperature scatter plot; Obtaining the stack temperature at the predetermined future time according to the stack temperature trend line, and recording it as the predicted stack temperature; When the predicted stack temperature does not meet the predetermined stack operating temperature constraint, activating the precise temperature control mechanism in real time; The battery electrolyte is subjected to precise temperature control by the precise temperature control mechanism.

2. The precise temperature control method for battery electrolyte according to claim 1, characterized in that: After obtaining the stack temperature at the predetermined future time according to the stack temperature trend line and recording it as the predicted stack temperature, the method further includes: Performing spline fitting on the stack temperature scatter plot based on the spline curve principle to obtain a stack temperature fitting curve; Obtaining a stack temperature fitting polynomial of the stack temperature fitting curve; Inputting the predetermined future time into the stack temperature fitting polynomial to obtain a second predicted stack temperature; The predicted stack temperature is verified and adjusted using the second predicted stack temperature.

3. The precise temperature control method for battery electrolyte according to claim 1, characterized in that: The precise temperature control mechanism is used to precisely control the temperature of the battery electrolyte, including: Extracting the real-time ambient temperature from the real-time temperature; Establishing an ambient temperature time series according to a mapping relationship between the real-time ambient temperature and the real-time moment; Analyzing the ambient temperature time series to obtain a predicted ambient temperature; Using the predicted stack temperature and the predicted ambient temperature as precise temperature control constraints, an optimal temperature control strategy is obtained through optimization; The precise temperature control mechanism performs precise temperature control on the battery electrolyte based on the optimal temperature control strategy.

4. The precise temperature control method for battery electrolyte according to claim 3, characterized in that: Using the predicted stack temperature and the predicted ambient temperature as precise temperature control constraints, an optimal temperature control strategy is obtained by searching for the optimal temperature control strategy, including: Establishing a temperature control index set for the precise temperature control mechanism, wherein the temperature control index set refers to a set of control indexes for the precise temperature control mechanism to control the compressed air to enter the battery electrolyte; Extracting a first temperature control indicator from the temperature control indicator set, where the first temperature control indicator has an identifier of a first temperature control parameter threshold; Under the precise temperature control constraint, a temperature control optimization space is established based on the first temperature control parameter threshold, and a temperature control fitness evaluation function is used as a temperature control optimization evaluation strategy to obtain the optimal temperature control strategy.

5. The precise temperature control method for battery electrolyte according to claim 4, characterized in that: The temperature control index set includes the pressure, flow rate, temperature and humidity for controlling the compressed air.

6. The precise temperature control method for battery electrolyte according to claim 5, characterized in that: The expression of the temperature control adaptability evaluation function is as follows: ； in, It refers to temperature adaptation. is the temperature stability coefficient, It refers to the The temperature control evaluation index parameters of the temperature control evaluation index, It refers to the The weight coefficient of the temperature control evaluation index, and =1, is the number of temperature evaluation indicators, and , wherein the temperature control evaluation indicators include at least energy consumption, efficiency and noise.

7. The precise temperature control method for battery electrolyte according to claim 4, characterized in that: Under the precise temperature control constraint, a temperature control optimization space is established based on the first temperature control parameter threshold, and a temperature control fitness evaluation function is used as a temperature control optimization evaluation strategy to obtain the optimal temperature control strategy, including: Extracting a first temperature control strategy from the temperature control optimization space, and simulating the first temperature control strategy to obtain a first temperature control simulation record; Performing optimization evaluation on the first temperature control simulation record according to the temperature control optimization evaluation strategy to obtain a first temperature control adaptability; Extracting a second temperature control strategy from the temperature control optimization space, and simulating the second temperature control strategy to obtain a second temperature control simulation record; Performing optimization evaluation on the second temperature control simulation record according to the temperature control optimization evaluation strategy to obtain a second temperature control adaptability; The optimal temperature control strategy is determined according to a comparison result obtained by comparing the first temperature control adaptability with the second temperature control adaptability.

8. A precise temperature control device for battery electrolyte, characterized in that: The steps for implementing the precise temperature control method for a battery electrolyte according to any one of claims 1 to 7 include: A judgment module, the judgment module is used to dynamically monitor and obtain real-time temperature, and judge whether the real-time stack temperature of the battery electrolyte in the real-time temperature meets the predetermined stack operating temperature constraint; A reading module, configured to read a predetermined future time if the real-time stack temperature meets the predetermined stack operating temperature constraint; A prediction module, configured to perform prediction analysis on a stack temperature time series established based on the real-time stack temperature to obtain a predicted stack temperature at the predetermined future moment; an activation module, configured to activate a precise temperature control mechanism in real time when the predicted stack temperature does not meet the predetermined stack operating temperature constraint; A temperature control module is used to perform precise temperature control on the battery electrolyte through the precise temperature control mechanism.

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