Power battery liquid cooling temperature judgment method and system

Abstract

The invention discloses a power battery liquid cooling temperature judgment method and system. The method comprises the following steps: collecting current data of a power battery, judging the charging and discharging state of the power battery, and calculating and outputting working state data; state data of the power battery and the cooling liquid are collected, and a state parameter set is obtained; analyzing the state parameter set and the working state data to obtain a temperature change trend parameter, and calculating and outputting a temperature state score; a historical temperature database is preset, the temperature state is compared with the historical temperature database, and a temperature judgment result is output. The method is used for solving the technical problems that in the prior art, temperature judgment is difficult to adapt to complex and changeable operation working conditions of a power battery, and the high-precision temperature management requirement cannot be met.

Description

Technical Field

[0001] This invention relates to the field of liquid cooling temperature determination, specifically to a method and system for determining the liquid cooling temperature of a power battery. Background Technology

[0002] Driven by the rapid development of the new energy vehicle and energy storage industries, power batteries have become core energy supply components, and their operating temperature has a decisive impact on safety performance, cycle life, and charge / discharge efficiency. When the power battery temperature is too high, it is prone to problems such as electrolyte decomposition, increasing the risk of thermal runaway; when the temperature is too low, it will lead to a decrease in lithium-ion diffusion rate, weakened charging acceptance, and even the formation of lithium dendrites. Liquid cooling systems, with their advantages of high heat dissipation efficiency and good temperature control uniformity, have become the mainstream technical solution for thermal management of medium and high power batteries. As the core decision-making link of the liquid cooling system, the power battery liquid cooling temperature judgment plays a crucial role in real-time monitoring of temperature status and guiding the action of thermal management actuators, and is the technical foundation for ensuring the long-term stable operation of the battery.

[0003] From a technical perspective, determining the liquid cooling temperature of a power battery requires coupled analysis of parameters from both the battery itself and the liquid cooling system. On one hand, the heat generated during battery charging and discharging directly determines the heat load of the liquid cooling system; on the other hand, the heat exchange efficiency of the liquid cooling system conversely affects battery temperature changes. If the coolant flow rate is insufficient or its thermal conductivity decreases, even if the initial temperature is normal, heat accumulation may lead to abnormal temperatures. Therefore, temperature determination must simultaneously cover both the battery's operating status and the liquid cooling system's operating conditions; coordinated analysis of both is a prerequisite for ensuring accurate judgment.

[0004] The current mainstream power battery liquid cooling temperature judgment process in the industry is based on basic data collection and static comparison with fixed thresholds as its core framework. The specific operation path is as follows: First, core data such as the real-time temperature of the battery cell and the inlet and outlet temperatures of the coolant are collected through thermistors placed on the surface of the battery cell and temperature sensors in the coolant circuit. Then, the collected real-time temperature data is directly compared with the preset fixed threshold. Finally, if the real-time temperature exceeds the threshold range, a temperature alarm message is output and the corresponding thermal management action is triggered. If the temperature is within the threshold range, it is determined that the temperature is normal, and the judgment result is fed back to the battery management system.

[0005] However, the existing judgment process has obvious technical limitations and is difficult to adapt to the complex and ever-changing operating conditions of power batteries, and cannot meet the requirements of high-precision temperature management: First, the adaptability to operating conditions is insufficient. The existing process does not deeply integrate the charging and discharging status with temperature judgment, which makes it impossible to distinguish the temperature risks of different operating conditions under the same temperature. The single judgment standard is prone to misjudgment or omission. Second, the dynamic prediction capability is lacking. The existing process only relies on the static comparison between real-time temperature and fixed threshold, without analyzing the trend and rate of temperature change. When the temperature rises or falls rapidly, the best control time is easily missed due to the judgment lag, which increases the risk of thermal runaway or low-temperature performance degradation. Summary of the Invention

[0006] This application provides a method and system for determining the liquid cooling temperature of a power battery, which addresses the technical problem that the temperature determination in the prior art is difficult to adapt to the complex and ever-changing operating conditions of power batteries and cannot meet the requirements for high-precision temperature management.

[0007] In view of the above problems, this application provides a method and system for determining the liquid cooling temperature of a power battery.

[0008] The first aspect of this application provides a method for determining the liquid cooling temperature of a power battery. The method is applied to a power battery liquid cooling temperature determination system. The method includes: collecting current data of the power battery, determining the charge / discharge state of the power battery, calculating and outputting operating state data; collecting state data of the power battery and coolant to obtain a set of state parameters; analyzing the set of state parameters and the operating state data to obtain temperature change trend parameters, calculating and outputting a temperature state score; pre-setting a historical temperature database, comparing the temperature state score with the historical temperature database, and outputting a temperature determination result.

[0009] A second aspect of this application provides a method and system for determining the liquid cooling temperature of a power battery. The system includes: a first processing unit for collecting current data of the power battery, determining the charge / discharge state of the power battery, calculating and outputting operating state data; a first obtaining unit for collecting state data of the power battery and coolant, and obtaining a set of state parameters; a second processing unit for analyzing the set of state parameters and the operating state data to obtain temperature change trend parameters, calculating and outputting a temperature state score; and a third processing unit for pre-setting a historical temperature database, comparing the temperature state score with the historical temperature database, and outputting a temperature determination result.

[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application embodiment collects current data from the power battery to determine its charge / discharge state, calculates and outputs operating state data; collects state data from the power battery and coolant to obtain a set of state parameters; analyzes the set of state parameters and operating state data to obtain temperature change trend parameters, calculates and outputs a temperature state score; and compares the temperature state score with a preset historical temperature database to output a temperature judgment result. This addresses the technical problem in existing technologies where temperature judgment is difficult to adapt to the complex and variable operating conditions of power batteries, thus failing to meet the requirements for high-precision temperature management.

[0011] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This application provides a method for determining the liquid cooling temperature of a power battery. Detailed Implementation

[0014] This application provides a method and system for determining the liquid cooling temperature of a power battery, which addresses the technical problem that existing technologies struggle to adapt temperature determination to the complex and variable operating conditions of power batteries, thus failing to meet the requirements for high-precision temperature management.

[0015] To address the aforementioned technical problems, the overall approach of the technical solution provided in this application is as follows: After introducing the basic principles of this application, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0016] Example 1 like Figure 1As shown, this application provides a method for determining the liquid cooling temperature of a power battery. The method is applied to a power battery liquid cooling temperature determination system, and the method includes: S100: Collects current data of the power battery, determines the charging and discharging state of the power battery, calculates and outputs working status data; This application provides a power battery operating state judgment scheme based on current data. By analyzing real-time collected current information, it achieves rapid identification of the battery's charging and discharging state and transforms current characteristics into intuitive operating state data, providing a simple and effective reference for the dynamic control of the battery management system. Specifically, the scheme first collects the power battery's current data in real time using a current sensor, and determines whether the battery is in a charging, discharging, or idle state based on the positive or negative attribute of the current value. Then, based on the actual magnitude of the current, it is mapped to a numerical range of 1-10 through standardization transformation to form directly applicable operating state data, where higher and lower values ​​correspond to differences in charging and discharging intensity. Finally, the state judgment result and the operating state data are output synchronously to complete the entire judgment process. For example, when the power battery is in the fast charging process, the current sensor collects a negative current, and the system determines it to be in a charging state. Combining the ratio of this charging current to the battery's maximum allowable charging current, the system calculates the operating state data in the range of 5-8, reflecting a medium to high intensity charging process. When the vehicle starts and accelerates, the current is positive, and the system determines it to be in a discharging state. The system calculates the operating state data in the range of 3-6 based on the magnitude of the discharging current, reflecting the current discharging intensity. The 1-10 range of the working status data is for the intuitive quantification of the status. 1 usually corresponds to a weak charging or resting state, and 10 corresponds to the maximum intensity of discharging or charging. The positive and negative definitions of the current data follow industry conventions. Positive current indicates that the battery outputs energy to the outside, and negative current indicates that the outside inputs energy to the battery. The current threshold for the resting state can be set according to the sensor accuracy.

[0017] Step S100 in the method provided in this application embodiment includes: S101: Collects the maximum discharge current, maximum charging current, and actual current data of the power battery as current data. S102: If the actual current data is 0, the charging and discharging state of the power battery is judged as the resting state; if the actual current data is positive, the charging and discharging state of the power battery is judged as the discharging state; if the actual current data is negative, the charging and discharging state of the power battery is judged as the charging state. S103: When the power battery is in a static state, the output operating status data is 1; when the power battery is in a discharging or charging state, the operating status data is calculated and output using the following formula:

[0018] in, For working status data, This is actual current data. The maximum discharge current, This is the maximum charging current.

[0019] The power battery operating state determination method provided in this application embodiment can achieve qualitative determination of charge / discharge state and quantitative characterization of operating intensity based on current data, providing accurate state reference for multi-dimensional management of battery systems. Specifically, firstly, the maximum discharge current, maximum charging current, and actual current data of the power battery are collected; secondly, the numerical type of the actual current data is determined. If I = 0, the power battery is determined to be in a static state, and operating state data 1 is directly output; if I > 0, the power battery is determined to be in a discharge state; if I < 0, the power battery is determined to be in a charging state. In both cases, operating state data is calculated and output using formulas; finally, based on the determination result of charge / discharge state, the corresponding operating state data is output. For example, consider the fast charging and high-speed acceleration processes of new energy vehicles: When a vehicle is connected to a fast charging station, the actual current is negative. By collecting the maximum discharge current and maximum charging current of the battery, and substituting them into a formula, we can obtain working state data reflecting the charging intensity. When the vehicle is accelerating rapidly at high speed, the actual current is positive. Similarly, by collecting the maximum discharge current and maximum charging current of the battery, and substituting them into a formula, we can obtain working state data reflecting the discharge intensity, thus demonstrating the differences in the battery's working state under different scenarios. The working state data is used to quantitatively describe the charging and discharging state and working intensity of the battery, with a value range of 1-10. The actual current data is the real-time input or output current value of the battery. The maximum discharge current refers to the maximum current value that the battery can output under safe and stable performance conditions. The maximum charging current refers to the maximum current value that the battery can receive from the outside under safe and stable performance conditions, usually expressed as a negative value to indicate the charging direction. Optionally, the operating status data can be corrected by combining other parameters such as the battery temperature and state of charge. For example, when the battery temperature exceeds the suitable range, the calculated operating status data can be weighted and adjusted to avoid the battery operating at high load for a long time under extreme conditions. Alternatively, the maximum discharge current and maximum charging current can be dynamically updated. Based on the battery's health status, cycle count, and other long-term performance degradation, the maximum current threshold can be adjusted in real time to make the operating status judgment more consistent with the performance changes throughout the battery's life cycle. S200: Collects state data of the power battery and coolant to obtain a set of state parameters; This application provides a method for collecting state data of the power battery and coolant to construct a state parameter set. By integrating multi-dimensional operational information of the battery and liquid cooling system, it provides a comprehensive data foundation for subsequent power battery thermal management and performance analysis, helping to achieve intelligent management and control of the battery system under complex operating conditions. Specifically, temperature and current sensors deployed in the power battery pack, and flow and temperature sensors in the liquid cooling circuit, are used to collect data related to the electrical performance and thermal state of the power battery, as well as data related to the thermal properties, flow state, and circuit structure of the coolant. These raw data are then preprocessed, including validity verification and time synchronization, and the processed power battery and coolant data are integrated to form a state parameter set that comprehensively reflects the collaborative working state of both. For example, when the power battery is in a high-speed, high-power discharge scenario, the sensors simultaneously collect high current data and rapidly rising temperature data of the battery, as well as real-time flow data and temperature difference data that changes with heat exchange of the coolant. This data is integrated into the state parameter set, which reflects the dynamic interaction process of battery heat generation and coolant heat dissipation under this operating condition.

[0020] Step S200 in the method provided in this application embodiment includes: S201: Collects state data of the power battery and coolant to obtain a set of state parameters, including: S202: Collect the operating time of the power battery and obtain the operating time parameter; S203: Collects temperature data of the power battery to obtain real-time temperature data and historical temperature data; S204: Collect coolant temperature data to obtain liquid cooling temperature difference data; S205: Collect the specific heat capacity of the coolant to obtain the specific heat capacity parameter of the coolant; S206: Collect the thermal resistance layer thickness of the coolant and obtain the thermal resistance layer thickness parameters; S207: Collect the real-time flow rate of the coolant and obtain the real-time flow rate parameters of the coolant; S208: The working duration parameter, real-time temperature data, past temperature data, liquid cooling temperature difference data, coolant specific heat capacity parameter, thermal resistance layer thickness parameter, and coolant real-time flow rate parameter are used as a set of state parameters.

[0021] This application provides a comprehensive evaluation method for a power battery liquid cooling system based on a multi-dimensional set of state parameters. By integrating multi-source information such as working time, temperature data, and liquid cooling characteristic parameters, a comprehensive state evaluation model is constructed to achieve accurate characterization and dynamic judgment of the battery thermal management state, providing complete data support and decision-making basis for the intelligent control of the liquid cooling system.

[0022] Specifically, firstly, working duration parameters are synchronously collected at a preset frequency, such as 100ms / time: cumulative working time and continuous working time, real-time temperature data of the power battery: cell maximum temperature, minimum temperature, average temperature, past temperature data: temperature sequence of the past 30 minutes, inlet and outlet temperature difference of coolant: liquid cooling temperature difference data, coolant specific heat capacity parameter, thermal resistance layer thickness parameter, and real-time flow parameter of coolant; secondly, the collected parameters are preprocessed, including outlier removal, time alignment, and unit standardization; then, the preprocessed parameters are integrated into a set of state parameters. Among them, the state parameter set refers to a multi-dimensional combination of parameters used to describe the operating state of the power battery and liquid cooling system, including time dimension, temperature dimension, and liquid cooling characteristic dimension; the working duration parameter is used to characterize the impact of continuous battery operation on temperature accumulation; real-time temperature data reflects the current thermal state of the battery, and past temperature data is used to analyze temperature change trends; liquid cooling temperature difference data reflects the heat exchange effect of the coolant; the specific heat capacity parameter of the coolant determines the heat absorption capacity per unit mass of coolant; the thermal resistance layer thickness parameter affects the heat transfer efficiency from the cell to the coolant; and the real-time flow rate parameter of the coolant reflects the amount of heat dissipation medium transported per unit time. For example, taking the application of power batteries in continuous high-power discharge scenarios as an example: the working time parameter reflects that the battery has been in a high-load operation state for a long time; the real-time temperature data shows that the battery temperature is rising; the past temperature data can trace the beginning and development of this temperature rise trend; the liquid cooling temperature difference data reflects the heat absorption of the coolant during the heat exchange process; the coolant specific heat capacity parameter determines the upper limit of heat that a unit volume of coolant can carry; the thermal resistance layer thickness parameter affects the efficiency of heat transfer from the battery to the coolant; and the real-time coolant flow rate parameter represents the scale of coolant participating in heat exchange per unit time. These parameters together constitute a set of state parameters that can comprehensively depict the complete thermal cycle process of the current battery heat generation, heat transfer to the coolant, and coolant carrying and dissipating heat. The evaluation model can use this to determine whether the thermal management system can match the current high-power discharge heat load.

[0023] S300: Analyzes the set of status parameters and working status data to obtain temperature change trend parameters, calculates and outputs temperature status score; This application provides a method for evaluating the temperature state of a power battery by fusing a set of state parameters with operating state data. This helps the thermal management system more accurately predict temperature trends and provides an intuitive and effective basis for subsequent adjustments to heat dissipation strategies and risk warnings, solving the problem that relying solely on single temperature data is insufficient to comprehensively reflect the thermal state. Specifically, a set of state parameters covering the electro-thermal characteristics of the power battery and the thermal-fluid characteristics of the coolant is first collected, while operating state data reflecting the battery's workload intensity is also acquired. Based on this multi-source data, a temperature change trend parameter reflecting the temperature change trend is obtained through correlation analysis of the battery temperature change pattern, coolant heat dissipation capacity, and workload. Subsequently, this trend parameter is combined with real-time temperature information to calculate a temperature state score. Finally, the temperature state score is output for subsequent decision-making by the battery management or thermal management system. For example, when the power battery is in a fast-charging scenario, the state parameter set includes data such as rapidly rising battery temperature, coolant flow rate, and temperature difference. The operating state data reflects a strong charging load. By analyzing this data, a temperature change trend parameter showing a rapid temperature increase can be obtained, and then a temperature state score reflecting the temperature risk in this fast-charging scenario can be calculated. In contrast, in scenarios where the vehicle is moving at low speed and the battery load is low, the analyzed temperature change trend parameter will show a relatively stable temperature characteristic, and the corresponding calculated temperature state score can reflect a safer thermal state. The state parameter set integrates multi-dimensional operating data of the power battery and coolant to comprehensively characterize the battery's thermal environment and cooling system status; the operating state data reflects the strength of the battery's current charging and discharging workload; the temperature change trend parameter is a quantitative description of the future trend of battery temperature change; and the temperature state score is a comprehensive quantitative result of the battery's thermal state after integrating the current temperature and the change trend.

[0024] Step S300 in the method provided in this application embodiment includes: S301: Calculate the temperature change trend parameter based on the set of state parameters and operating state data. The formula is as follows:

[0025] in, For temperature change trend parameters, For real-time temperature data, Based on past temperature data, for, For working duration parameters, This refers to the specific heat capacity parameter of the coolant. This refers to the real-time flow rate parameters of the coolant. The parameter is the thickness of the thermal resistance layer; S302: Calculate the temperature state score based on the temperature change trend parameter, using the following formula:

[0026] in, Classified by temperature state, For real-time temperature data, This is a parameter representing the temperature change trend. S303: Output temperature status.

[0027] This application provides a method for quantitatively assessing the temperature state of a power battery by integrating multiple parameters. Through a two-step calculation—first calculating temperature change trend parameters, then deriving the temperature state score—a comprehensive characterization of the current battery temperature level and its changing trend is achieved. This provides accurate and intuitive quantitative data for the dynamic control and risk warning of the thermal management system, solving the problem that relying solely on real-time temperature makes it difficult to predict temperature trends. Specifically, first, a set of state parameters is collected and acquired, including real-time temperature data, historical temperature data, operating status data, operating duration parameters, coolant specific heat capacity parameters, coolant real-time flow rate parameters, and thermal resistance layer thickness parameters. Second, the above parameters are substituted into a formula to calculate the temperature change trend parameters. The formula reflects the coupling effect of the battery's own temperature change with the workload and operating time, as well as the balancing effect of the coolant's heat dissipation capacity on the temperature trend. Next, the real-time temperature data and the temperature change trend parameters are substituted into the formula to obtain the temperature state score, which integrates the current temperature and trend weights. Finally, the temperature state score is output. For example, taking the application of power batteries in high-power discharge scenarios as an example: at this time, the working status data reflects a strong discharge load, the real-time temperature continues to rise with the discharge, the past temperature data records the lower temperature at the beginning of the discharge, the working time reflects the duration of high-power discharge, and the coolant-related parameters reflect the current heat dissipation configuration of the liquid cooling system; by substituting these parameters into the formula to calculate the temperature change trend parameter, if the battery temperature rises rapidly and the coolant heat dissipation capacity is relatively insufficient, the temperature change trend parameter will show a trend of temperature continuing to rise; then, the temperature state time-sharing will be calculated, and a higher state score will be assigned based on the current temperature and this trend, intuitively reflecting the dynamic evolution of temperature risk in high-power discharge scenarios. Among them, the temperature change trend parameter is used to quantify the trend of battery temperature change over time and system heat dissipation capacity. Its positive and negative signs and magnitudes reflect the trend and strength of temperature rise, fall, and stabilization; real-time temperature data refers to the actual temperature value of the power battery at the current moment; past temperature data refers to the battery temperature value at historical moments, used to reflect the amount of temperature change; operating status data characterizes the strength of the current working load of the power battery; operating duration parameter refers to the duration of the battery in the current operating state; coolant specific heat capacity parameter is a thermal property parameter of the coolant, reflecting its heat absorption capacity; coolant real-time flow rate parameter reflects the delivery rate of coolant per unit time, reflecting the flow intensity of the heat dissipation medium; thermal resistance layer thickness parameter refers to the thickness of the thermal resistance layer between the battery and the coolant, affecting the heat transfer resistance; temperature state score is a comprehensive quantitative result of the current level and trend of battery temperature, used to intuitively reflect the quality and risk level of the temperature state. Optionally, the weights of each parameter in the formula can be dynamically adjusted according to the season and ambient temperature to improve the assessment adaptability in different scenarios; the temperature status score can also be compared with the preset safety threshold to directly trigger thermal management actions such as strong cooling and power limiting, so that the assessment results can more directly serve the system control.

[0028] S400: Preset historical temperature database, compare the temperature status with the historical temperature database, and output the temperature judgment result; This application provides a scheme for assisting in judging the temperature state of a power battery by relying on a historical temperature database. By comparing the current temperature state score with the data in the historical temperature database, it is possible to assess whether the battery temperature is within the normal range from the perspective of historical patterns. This provides a more valuable reference for subsequent decisions of the thermal management system and solves the problem of lacking historical reference when relying solely on real-time data. Specifically, a historical temperature database is pre-set to store historical temperature data of the power battery under different typical operating conditions, such as fast charging, long-term high-power discharge, and low-temperature start-up. Then, the currently calculated temperature state score is obtained and compared with the historical temperature data of the corresponding operating conditions in the historical temperature database. Finally, based on the comparison result, a temperature judgment result containing information such as whether the temperature is normal is output. For example, when the power battery is in a high-speed, high-power discharge scenario, the temperature state score obtained at this time is compared with the historical data of high-speed, high-power discharge under the historical temperature database. If the current temperature state score is within the fluctuation range of historical normal data, a judgment result of healthy temperature is output; if the current temperature state score deviates significantly from the historical range, such as due to a temporary failure of the cooling system, a judgment result of temperature alarm is output. Among them, the historical temperature database refers to the collection of past temperature-related data of power batteries under various operating conditions and scenarios, which is used to provide historical reference standards for the current temperature status; the temperature status score is a comprehensive quantitative representation of the current temperature level and temperature change trend of the power battery; the temperature judgment result is a conclusive information output after comparison, used to reflect whether the current temperature is normal.

[0029] Step S400 in the method provided in this application embodiment includes: S401: Preset historical temperature database, receive historical temperature data from the historical temperature database, and obtain historical average temperature; S402: Preset temperature health tolerance value; S403: Compare the temperature status with the historical average temperature; S404: If the difference between the temperature status score and the historical average temperature is less than or equal to the allowable deviation value for temperature health, output real-time temperature data and temperature health indication information; if the difference between the temperature status score and the historical average temperature is greater than the allowable deviation value for temperature health, output real-time temperature data, temperature status score and temperature alarm information. S405: The real-time temperature data and temperature health indication information, together with the real-time temperature data, temperature status score and temperature alarm information, are used as the temperature judgment result.

[0030] In this embodiment of the application, a method for determining the temperature health of a power battery based on historical temperature data comparison is provided. By introducing a historical temperature benchmark and a preset deviation threshold, a graded judgment is made to identify the normal temperature state of the battery and issue an abnormal alarm. This method not only focuses on the absolute value of the real-time temperature, but also evaluates the rationality of the temperature state from the perspective of historical patterns, thereby improving the comprehensiveness and accuracy of the thermal management system in identifying temperature risks.

[0031] Specifically, firstly, based on the application scenario or operating condition type of the power battery, a corresponding historical temperature database is preset. This database stores historical temperature time-series data under similar scenarios / operating conditions. Secondly, historical temperature data is extracted from the historical temperature database, and the historical average temperature is obtained through statistical calculation to reflect the typical temperature level under similar scenarios / operating conditions. Simultaneously, based on battery thermal safety standards and the temperature stability requirements of the scenario, a temperature health allowable deviation value is preset. Next, the difference between the currently calculated temperature state and the historical average temperature is calculated. Then, based on the relationship between the difference and the temperature health allowable deviation value, different content is output: if the difference is ≤ temperature... The permissible deviation value indicates that the current temperature state is consistent with the normal level of similar historical conditions, and outputs real-time temperature data and temperature health indication information such as "temperature state is normal". If the difference is greater than the permissible deviation value, it indicates that the current temperature state deviates from the historical normal level, and there is an abnormal risk. Real-time temperature data, temperature status score (quantifying the degree of abnormality), and temperature alarm information such as "temperature state is abnormal, please pay attention to heat dissipation" are output. Finally, the real-time temperature data and temperature health indication information are combined with the real-time temperature data, temperature status score, and temperature alarm information as the temperature judgment result, which is then used by subsequent modules such as the thermal management strategy unit and vehicle alarm unit of the battery management system. For example, taking the summer fast charging scenario of new energy vehicles as an example: the historical temperature database stores a large amount of historical temperature data of the battery pack of this model under summer fast charging conditions. The statistically obtained historical average temperature can reflect the typical temperature level during summer fast charging; the preset permissible deviation value of temperature health defines the upper limit of the fluctuation of the temperature status score relative to the historical average temperature during normal fast charging. During a summer fast charge, if the difference between the temperature status score and the historical average temperature is within the deviation range, the system will output real-time temperature data and temperature health indication information. If the difference between the temperature status score and the historical average temperature exceeds the deviation value due to an abnormal increase in charging pile power or a coolant circulation failure, the system will output real-time temperature data, the abnormally high temperature status score, and a temperature alarm, and recommend reducing the charging power.

[0032] The historical temperature database is a collection of historical temperature data for power batteries under different application scenarios and operating conditions, providing a similar reference benchmark for the current temperature state. The historical average temperature is a value obtained by statistically averaging the data in the historical temperature database, reflecting the typical temperature level under similar scenarios / operating conditions. The temperature health allowable deviation value is a pre-set threshold used to determine whether the current temperature state deviates from the historical normal level; its value is related to the battery thermal stability requirements and scenario characteristics. The temperature state score is a comprehensive quantitative value that integrates the current temperature with the temperature change trend, calculated by the method mentioned above. The temperature health indication information is a prompt-type message output when the temperature state is normal. The temperature alarm information is a warning-type message output when the temperature state is abnormal. The temperature judgment result is the final output set including normal prompts or abnormal alarms plus quantitative data. Optionally, the historical temperature database can be dynamically updated, periodically incorporating new temperature data to make the historical average temperature more consistent with the thermal characteristics of the battery after aging.

[0033] Example 2 Based on the same inventive concept as the power battery liquid cooling temperature determination method in the foregoing embodiments, this application provides a power battery liquid cooling temperature determination system, including: The fourth processing unit is used to collect the maximum discharge current, maximum charging current, and actual current data of the power battery as current data. The first judgment unit is used to determine the charging and discharging state of the power battery as a static state if the actual current data is 0; to determine the charging and discharging state of the power battery as a discharging state if the actual current data is positive; and to determine the charging state of the power battery as a charging state if the actual current data is negative. The first calculation unit outputs operating status data of 1 when the power battery is in a static state; and calculates and outputs operating status data when the power battery is in a discharging or charging state, using the following formula:

[0034] in, For working status data, This is actual current data. The maximum discharge current, This is the maximum charging current; Preferred options also include: The first acquisition unit is used to acquire the working time of the power battery and obtain the working time parameter. The second acquisition unit is used to acquire temperature data of the power battery and obtain real-time temperature data and historical temperature data. The third acquisition unit is used to acquire the temperature data of the coolant and obtain the liquid cooling temperature difference data. The fourth acquisition unit is used to acquire the specific heat capacity of the coolant and obtain the specific heat capacity parameter of the coolant. The fifth acquisition unit is used to acquire the thermal resistance layer thickness of the coolant and obtain the thermal resistance layer thickness parameters. The sixth acquisition unit is used to acquire the real-time flow rate of the coolant and obtain the real-time flow rate parameters of the coolant. The fifth processing unit is used to collect working time parameters, real-time temperature data, past temperature data, liquid cooling temperature difference data, coolant specific heat capacity parameters, thermal resistance layer thickness parameters, and coolant real-time flow parameters as a set of state parameters. Preferred options also include: The second calculation unit is used to calculate the temperature change trend parameter based on the set of state parameters and the working state data. The formula is:

[0035] in, For temperature change trend parameters, For real-time temperature data, Based on past temperature data, for, For working duration parameters, This refers to the specific heat capacity parameter of the coolant. This refers to the real-time flow rate parameters of the coolant. The parameter is the thickness of the thermal resistance layer; The third calculation unit is used to calculate the temperature state score based on the temperature change trend parameter. The formula is:

[0036] in, Classified by temperature state, For real-time temperature data, This is a parameter representing the temperature change trend. The first output unit is used to output the temperature status. Preferred options also include: The first preset unit is used to preset the historical temperature database, receive historical temperature data from the historical temperature database, and obtain the historical average temperature. The second preset unit is used to preset the allowable deviation value for temperature health. The sixth processing unit is used to compare the temperature status with the historical average temperature. The seventh processing unit is used to output real-time temperature data and temperature health indication information if the difference between the temperature status score and the historical average temperature is less than or equal to the temperature health allowable deviation value; and to output real-time temperature data, temperature status score and temperature alarm information if the difference between the temperature status score and the historical average temperature is greater than the temperature health allowable deviation value. The eighth processing unit is used to use the real-time temperature data and temperature health indication information, along with the real-time temperature data, temperature status score, and temperature alarm information, as the temperature judgment result.

[0037] The steps of the methods or algorithms described in this application can be directly embedded in hardware, a software unit executed by a processor, or a combination of both. The software unit can be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other storage medium of any form in the art. Exemplarily, the storage medium can be connected to the processor so that the processor can read information from the storage medium and write information to the storage medium. Optionally, the storage medium can also be integrated into the processor. The processor and storage medium can be disposed in an ASIC, which can be disposed in a terminal. Optionally, the processor and storage medium can also be disposed in different components within the terminal. These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0038] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely illustrative examples of this application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Thus, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A method for judging a liquid cooling temperature of a power battery, characterized in that, The method is applied to a power battery liquid cooling temperature judgment system, and the method comprises the following steps: Current data of the power battery is collected, the charging and discharging state of the power battery is judged, working state data is calculated and outputted; State data of the power battery and the cooling liquid is collected to obtain a state parameter set; Temperature variation trend parameters are obtained by analyzing the state parameter set and the working state data, and temperature state scores are calculated and outputted; A historical temperature database is preset, the temperature state score is compared with the historical temperature database, and a temperature judgment result is outputted.

2. The method of claim 1, wherein, The current data of the power battery is collected, the charging and discharging state of the power battery is judged, and the working state data is calculated and outputted, which comprises the following steps: The maximum discharging current, the maximum charging current and the actual current data of the power battery are collected as the current data; If the actual current data is 0, the charging and discharging state of the power battery is judged as a static state; if the actual current data is positive, the charging and discharging state of the power battery is judged as a discharging state; if the actual current data is negative, the charging and discharging state of the power battery is judged as a charging state; When the charging and discharging state of the power battery is the static state, the working state data is outputted as 1; when the charging and discharging state of the power battery is the discharging state or the charging state, the working state data is calculated and outputted, and the formula is: ； wherein, is the operating state data, is the actual current data, is the maximum discharge current, is the maximum charge current.

3. The method of claim 1, wherein, The state data of the power battery and the cooling liquid is collected to obtain the state parameter set, which comprises the following steps: The working time length of the power battery is collected to obtain a working time length parameter; The temperature data of the power battery is collected to obtain real-time temperature data and past temperature data; The temperature data of the cooling liquid is collected to obtain liquid cooling temperature difference data; The specific heat capacity of the cooling liquid is collected to obtain a cooling liquid specific heat capacity parameter; The thickness of the thermal resistance layer of the cooling liquid is collected to obtain a thermal resistance layer thickness parameter; The real-time flow of the cooling liquid is collected to obtain a cooling liquid real-time flow parameter; The working time length parameter, the real-time temperature data, the past temperature data, the liquid cooling temperature difference data, the cooling liquid specific heat capacity parameter, the thermal resistance layer thickness parameter and the cooling liquid real-time flow parameter are taken as the state parameter set.

4. The method of claim 1, wherein, The temperature variation trend parameters are obtained by analyzing the state parameter set and the working state data, and the temperature state scores are calculated and outputted, which comprises the following steps: The temperature variation trend parameters are calculated according to the state parameter set and the working state data, and the formula is: ； wherein, is a temperature change trend parameter, is real-time temperature data, is past temperature data, is, is a working time parameter, is a coolant specific heat capacity parameter, is a coolant real-time flow parameter, is a thermal resistance layer thickness parameter; The temperature state scores are calculated according to the temperature variation trend parameters, and the formula is: ； wherein, is a temperature state, is real-time temperature data, is a temperature change trend parameter; The temperature state scores are outputted.

5. The method of claim 1, wherein, The historical temperature database is preset, the temperature state score is compared with the historical temperature database, and the temperature judgment result is outputted, which comprises the following steps: The historical temperature database is preset, historical temperature data in the historical temperature database is received to obtain a historical average temperature; A temperature health allowable deviation value is preset; The temperature state score is compared with the historical average temperature; If the difference between the temperature state score and the historical average temperature is less than or equal to the temperature health allowable deviation value, the real-time temperature data and temperature health indication information are outputted; if the difference between the temperature state score and the historical average temperature is greater than the temperature health allowable deviation value, the real-time temperature data, the temperature state score and temperature alarm information are outputted; The real-time temperature data and the temperature health indication information and the real-time temperature data, the temperature state score and the temperature alarm information are taken as the temperature judgment result.

6. A power battery liquid cooling temperature judgment system, characterized in that, The system comprises: The first processing unit is configured to collect current data of the power battery, determine the charging and discharging state of the power battery, calculate and output working state data; The first obtaining unit is configured to collect state data of the power battery and the coolant, and obtain a set of state parameters; The second processing unit is configured to analyze the set of state parameters and the working state data to obtain a temperature change trend parameter, calculate and output a temperature state score; The third processing unit is configured to preset a historical temperature database, compare the temperature state score with the historical temperature database, and output a temperature judgment result.

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