Energy storage liquid cooling system for new energy vehicle battery module

Abstract

The application provides a new energy automobile battery module energy storage liquid cooling system, relates to the battery energy storage temperature control technical field, determines the temperature balance inflection point according to all heat distribution state information, determines the flow limit amplitude cycle of the cooling medium between the cold plates according to the temperature balance inflection point, and dynamically adjusts the temperature change hysteresis deviation between the cold plates in the energy storage liquid cooling assembly by all flow limit amplitude cycles; the cooling lag trend of the new energy automobile battery module during liquid cooling circulation is determined according to the temperature control slow change attribute, the phase change cooling strategy of the cooling medium during stratified tolerance circulation is adaptively adjusted according to the cooling lag trend, and the cooling medium in the energy storage liquid cooling assembly is quota corrected according to the temperature change hysteresis deviation after dynamic proportion adjustment and the phase change cooling strategy after adaptive adjustment. The application can adjust the cooling medium regulation and control strategy of the energy storage liquid cooling assembly in the whole process under the dynamic change of the battery module multi-working condition, so as to improve the accuracy of the battery module temperature control.

Description

Technical Field

[0001] This application relates to the field of battery energy storage and temperature control technology, and more specifically, to an energy storage liquid cooling system for new energy vehicle battery modules. Background Technology

[0002] Battery energy storage temperature control refers to the process of dynamically adjusting the control strategy of the temperature control system by sensing various thermal characteristics of the new energy vehicle battery module in real time, including charging and discharging power, operating conditions, ambient temperature, and cold plate heat load, and combining this with the core parameters of the battery module, such as the temperature distribution of individual cells, the temperature difference between cold plates, and the state of the cooling medium. This achieves precise control of the battery temperature, ensuring battery operation safety, improving charging and discharging efficiency, and extending battery life.

[0003] However, existing liquid cooling processes used in new energy vehicle battery modules suffer from the problem of not integrating temperature change hysteresis bias and phase change strategies into the cooling medium quota correction. This makes it difficult for the liquid cooling system to achieve coordinated heat dissipation between cold plates and precise temperature control under intermittent charging and discharging and gradually changing operating conditions. Consequently, battery modules are prone to localized overheating, poor temperature synchronization, or cooling lag, thereby reducing battery safety and lifespan and limiting the practical application of high-energy-density battery modules. Therefore, how to adjust the cooling medium regulation strategy of energy storage liquid cooling components throughout the entire process under dynamic changes in multiple operating conditions of battery modules to improve the accuracy of battery module temperature control is a key challenge facing the industry. Summary of the Invention

[0004] This application provides an energy storage liquid cooling system for new energy vehicle battery modules, which can adjust the cooling medium regulation strategy of the energy storage liquid cooling components throughout the entire process under the dynamic changes of multiple operating conditions of the battery module, so as to improve the accuracy of battery module temperature control.

[0005] In a first aspect, this application provides an energy storage liquid cooling system for a new energy vehicle battery module, the energy storage liquid cooling system comprising: The information acquisition module is used to acquire information on the heat distribution status of each cold plate component when the new energy vehicle battery module works together during operation. The proportion adjustment module is used to determine the temperature equilibrium inflection point of the battery module in the intermittent charge and discharge state based on all heat distribution state information, determine the flow limiting period of the cooling medium between each cold plate based on the temperature equilibrium inflection point, and then dynamically adjust the proportion of the temperature change hysteresis deviation between the cold plates in the energy storage liquid cooling component by all flow limiting periods. The temperature control determination module is used to determine the temperature control gradual change attribute of the new energy vehicle battery module when the operating conditions change gradually, and to determine the cooling hysteresis trend of the new energy vehicle battery module during liquid cooling cycle based on the temperature control gradual change attribute. Then, the phase change cooling strategy of the cooling medium during stratified tolerance circulation is adapted and determined based on the cooling hysteresis trend. The quota correction module is used to correct the quota of the cooling medium in the energy storage liquid cooling component based on the temperature change hysteresis deviation after dynamic ratio adjustment and the phase change cooling strategy after temperature adjustment determination.

[0006] In this embodiment, determining the inflection point of the battery module's temperature equilibrium during intermittent charging and discharging based on all thermal distribution state information specifically includes: The temperature change properties of the battery module are determined based on real-time heat distribution data during intermittent charging and discharging. The gradual temperature gradient within the charge / discharge cycle is determined by the aforementioned temperature change attribute. The gradual temperature gradient determines the inflection point of the stationary temperature equilibrium of the battery module in the intermittent charge and discharge state.

[0007] In this embodiment, the inflection point of the standing temperature equilibrium refers to the key node at which the heat generation rate and heat dissipation rate of the marked battery module reach a dynamic balance during intermittent charging and discharging.

[0008] In this embodiment, the flow rate limiting period refers to the time interval during which the flow rate of the cooling medium is controlled to vary within a set range.

[0009] In this embodiment, the dynamic proportion adjustment of the temperature hysteresis deviation between cold plates in the energy storage liquid cooling component by all flow limiting cycles specifically includes: The elastic pulsation amplitude of the cooling medium flow between each cold plate was analyzed by all flow limiting cycles. The dynamic adjustment weight of the temperature change hysteresis deviation is determined based on the elastic pulsation amplitude and the real-time collected temperature difference compensation sequence of the cold plate inlet and outlet. The dynamic adjustment weights are allocated to the hysteresis control loop according to the heat load distribution ratio between the cold plates, so as to realize the dynamic proportion adjustment of the temperature change hysteresis deviation.

[0010] In this embodiment, the dynamic proportion adjustment refers to adjusting the weight proportion of temperature change hysteresis deviation adjustment of each cold plate according to real-time operating conditions, so as to adapt to the temperature control method of heat load changes.

[0011] In this embodiment, determining the temperature control properties of the new energy vehicle battery module under gradually changing operating conditions specifically includes: Collect the real-time temperature change sequence of the battery module within the gradually changing operating range and the historical thermal management response delay index; The thermal inertia smoothness of the new energy vehicle battery module is determined based on the real-time temperature change sequence and the response delay index. The temperature control properties of the new energy vehicle battery module under gradually changing operating conditions are determined based on the thermal inertia smoothness.

[0012] In this embodiment, the temperature control gradual change attribute refers to the battery module's ability to smoothly adapt to temperature regulation when operating conditions change gradually.

[0013] In this embodiment, the cooling hysteresis trend refers to the direction and degree of lag of the liquid cooling system in response to changes in the thermal load of the battery module.

[0014] In this embodiment, the determination of temperature adjustment based on the cooling hysteresis trend to adapt the phase change cooling strategy of the cooling medium in stratified tolerance circulation specifically includes: Based on the cooling hysteresis trend, the temperature rheological tolerance of the cooling component during cooling is analyzed. Determine the amplitude adjustment correction rules for the cooling medium during stratified tolerance circulation; Based on the amplitude adjustment correction rule and the temperature rheological tolerance, the feasibility of phase change action in the stratified tolerance circulation process is determined, and the adaptation temperature adjustment determination result is obtained.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: By acquiring the thermal distribution information of each cold plate component of the new energy vehicle battery module during operation; determining the stationary temperature equilibrium inflection point of the battery module in intermittent charging and discharging state based on all thermal distribution information; determining the flow limiting period of the cooling medium between each cold plate based on the stationary temperature equilibrium inflection point; and then dynamically adjusting the proportion of temperature change hysteresis deviation between cold plates in the energy storage liquid cooling component based on all flow limiting periods; determining the temperature control slow change attribute of the new energy vehicle battery module under slow operating conditions; determining the cooling hysteresis trend of the new energy vehicle battery module during liquid cooling circulation based on the temperature control slow change attribute; and then using the cooling hysteresis trend to adapt and adjust the phase change cooling strategy of the cooling medium in stratified tolerance circulation; and adjusting the quota of the cooling medium in the energy storage liquid cooling component based on the temperature change hysteresis deviation after dynamic proportion adjustment and the phase change cooling strategy after adaptation and adjustment.

[0016] Therefore, this application demonstrates that it can precisely regulate the temperature control requirements of multiple operating conditions in the liquid cooling scenario of new energy vehicle battery modules. Specifically, by acquiring the thermal distribution information of each cold plate component during the collaborative operation of the battery module, it can overcome the shortcomings of existing technologies that do not cover the details of cold plate collaboration in thermal distribution acquisition. It comprehensively captures key data such as the cold plate temperature field, medium flow rate, and heat exchange power, constructing a complete thermal characteristic input foundation, thereby improving the liquid cooling system's perception accuracy and collaborative analysis capabilities of the battery module's thermal state. Furthermore, by determining the stationary temperature equilibrium inflection point in intermittent charge-discharge states based on all thermal distribution information, and then determining the cooling medium flow rate limiting period and dynamically adjusting the temperature change hysteresis deviation between cold plates accordingly, it can solve the problems of disconnect between stationary temperature inflection point determination and flow regulation, and the lack of correction for temperature change hysteresis in existing technologies. This ensures precise matching between flow regulation and thermal equilibrium nodes, eliminates temperature control asynchrony between cold plates, and effectively improves the temperature control performance under intermittent charge-discharge conditions. This technology improves the synchronization and efficiency of cooling medium utilization. By determining the temperature change attributes under gradually changing operating conditions, and then determining the cooling hysteresis trend of the liquid cooling cycle accordingly, and adapting it to the phase change cooling strategy based on the stratified tolerance circulation, it can overcome the shortcomings of existing technologies where the temperature change attributes are disconnected from the cooling hysteresis and the phase change strategy is not well adapted. This makes the temperature control strategy fit the characteristics of gradually changing operating conditions, avoids cooling lag, dynamically optimizes the activation timing and parameters of phase change cooling, and enhances the adaptability and heat dissipation efficiency of the liquid cooling system to gradually changing operating conditions. By adjusting the cooling medium quota based on the temperature change hysteresis deviation after dynamic ratio adjustment and the phase change cooling strategy after temperature adjustment judgment, it can solve the problem of existing quota correction not integrating multiple factors, achieve multi-dimensional precise allocation of flow rate, pressure, and phase change ratio, and construct a closed-loop control of "sensing-judgment-adjustment-correction", thereby improving the temperature control accuracy of the liquid cooling system under multiple operating conditions, the battery operation safety, and the application adaptability of high energy density battery modules.

[0017] In summary, the technical solution adopted in this application can adjust the cooling medium regulation strategy of the energy storage liquid cooling component throughout the entire process under the dynamic changes of multiple operating conditions of the battery module, so as to improve the accuracy of battery module temperature control. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this embodiment of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a module structure diagram of an energy storage liquid cooling system for a new energy vehicle battery module provided in this application; Figure 2This is a flowchart illustrating the process for determining the traffic limiting period provided in this application; Figure 3 This is a flowchart illustrating the process for determining the cooling hysteresis trend provided in this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0021] This application provides an energy storage liquid cooling system for new energy vehicle battery modules. Its core is to acquire the thermal distribution information of each cold plate component of the new energy vehicle battery module during operation; determine the stationary temperature equilibrium inflection point of the battery module in intermittent charge-discharge states based on all thermal distribution information; determine the flow limiting period of the cooling medium between each cold plate based on the stationary temperature equilibrium inflection point; and then dynamically adjust the proportion of the temperature change hysteresis deviation between the cold plates in the energy storage liquid cooling component based on all flow limiting periods; determine the temperature control slow change attribute of the new energy vehicle battery module under slow operating conditions; determine the cooling hysteresis trend of the new energy vehicle battery module during liquid cooling circulation based on the temperature control slow change attribute; and then use the cooling hysteresis trend to adapt and adjust the phase change cooling strategy of the cooling medium during stratified tolerance circulation; and perform quota correction of the cooling medium in the energy storage liquid cooling component based on the temperature change hysteresis deviation after dynamic proportion adjustment and the phase change cooling strategy after adaptation and temperature adjustment.

[0022] To better understand the above technical solutions, a detailed description of the technical solutions will be provided below in conjunction with the accompanying drawings and specific embodiments. (Refer to...) Figure 1 As shown in the figure, this is a modular structure diagram of an energy storage liquid cooling system for a new energy vehicle battery module according to this embodiment of the present application. The energy storage liquid cooling system includes: an information acquisition module 100, a proportion adjustment module 200, a temperature adjustment determination module 300, and a quota correction module 400, which are described below: The information acquisition module 100 is used to acquire the heat distribution status information of each cold plate component working together during the operation of the new energy vehicle battery module.

[0023] In practical implementation, firstly, hardware is installed in key areas of each cold plate assembly: NTC thermistors are attached to the cold plate inlet, outlet, middle, and battery contact area; electromagnetic flow meters and pressure sensors are installed in the medium pipeline, all connected to the BMS. The sampling frequency can be set to once per second as needed. Then, the BMS processes the data: a Kalman filter is used to build a prediction model, and the collected data is compared with the predicted values ​​to remove noise; linear interpolation is used to supplement missing data due to sensor faults. Finally, a set of data on the temperature field curves, medium flow velocity curves, and heat exchange power of each cold plate is generated. This generated set of data serves as information on the thermal distribution state of the cold plate assemblies working collaboratively during the operation of the new energy vehicle battery module, which will not be elaborated further here.

[0024] It should be noted that, in this application, the thermal distribution status information refers to the data set of temperature, heat exchange efficiency and thermal characteristic distribution of each cold plate and corresponding battery cell during battery module operation.

[0025] The proportion adjustment module 200 is used to determine the temperature equilibrium inflection point of the battery module in the intermittent charge and discharge state based on all heat distribution state information, determine the flow limiting period of the cooling medium between each cold plate based on the temperature equilibrium inflection point, and then dynamically adjust the proportion of the temperature change hysteresis deviation between the cold plates in the energy storage liquid cooling component by all flow limiting periods.

[0026] In this embodiment, the inflection point of the battery module's temperature equilibrium during intermittent charging and discharging can be determined based on all thermal distribution state information in the following manner: The temperature change properties of the battery module are determined based on real-time heat distribution data during intermittent charging and discharging. The gradual temperature gradient within the charge / discharge cycle is determined by the aforementioned temperature change attribute. The gradual temperature gradient determines the inflection point of the stationary temperature equilibrium of the battery module in the intermittent charge and discharge state.

[0027] In practice, firstly, real-time temperature data for the entire intermittent charge-discharge process is extracted from the stored thermal distribution information, including the temperature value of each battery cell corresponding to each cold plate and the acquisition time. The data is imported into data analysis software, and a temperature-time curve is plotted with time on the horizontal axis and the average temperature of each battery cell on the vertical axis. The charge-discharge cycle is divided into stages: the temperature rises during the charging stage, rises slowly or remains stable during the discharging stage, and decreases during the resting stage. The temperature change range of each stage is statistically analyzed, such as the temperature rising from 25℃ to 32℃ during the charging stage and falling from 32℃ to 30℃ during the resting stage. The duration of each stage is also recorded. By combining the stage trends, temperature ranges, and durations, the temperature change attributes of the battery module are determined, such as "rapid temperature rise during charging and slow temperature drop during resting." Then, based on the temperature change attributes, the intermittent charge-discharge cycle is divided into three sub-stages: charging, discharging, and resting. For each sub-stage, temperature data points at equal time intervals are selected, for example, a temperature value is taken every 10 seconds. The temperature change rate of each sub-stage is calculated using linear regression: a linear equation is established with time as the independent variable and temperature as the dependent variable, and the slope of the equation represents the gradual temperature gradient for that stage. For example, during the charging stage, 20 sets of data are collected, and the calculated slope is 0.07℃ / s, meaning the gradual temperature gradient during the charging stage is 0.07℃ / s; during the resting stage, the calculated slope is -0.02℃ / s, meaning the gradual temperature gradient during the resting stage is -0.02℃ / s. By recording the gradient values ​​for each stage, the gradual temperature gradient within the charge-discharge cycle is obtained. Finally, the criteria for determining the inflection point of the stationary temperature equilibrium can be set based on expert experience or experiments: when the absolute value of the gradual temperature gradient is ≤0.005℃ / s, and the duration of this gradient state is ≥20 seconds, the starting time of the corresponding time period is the stationary temperature equilibrium inflection point. The gradual temperature gradient of each sub-stage is analyzed: the gradient is relatively large during the charging stage, usually not meeting the conditions; in the later stage of the discharging stage, the gradient gradually decreases, and when the gradient drops to 0.004℃ / s and lasts for 22 seconds, the start time of this 22 seconds is recorded; the gradient is negative during the resting stage, and if the absolute value of the gradient does not meet the standard, it is not considered an inflection point. Considering all the times that meet the conditions, if only the discharging stage has a time that meets the requirements, that time is the inflection point of the battery module's temperature equilibrium; if multiple times exist, the earliest time is taken as the final inflection point, thus obtaining the inflection point of the battery module's temperature equilibrium in the intermittent charging and discharging state.

[0028] It should be noted that, in this application, real-time thermal distribution data refers to the data collected in real time on the distribution of thermal characteristics of each cold plate and corresponding battery in the battery module; temperature change attribute refers to the temperature change characteristics of the battery module over time during intermittent charging and discharging; gradual temperature gradient refers to the rate of temperature change of the battery module within the intermittent charging and discharging cycle; the standing temperature equilibrium inflection point refers to the key node that marks the dynamic balance between the heat generation rate and the heat dissipation rate of the battery module during intermittent charging and discharging; and intermittent charging and discharging state refers to the non-continuous charging and discharging working state in which the battery module alternately charges and discharges, and there is a static period between charging and discharging.

[0029] Preferably, in this embodiment, the flow rate limiting period of the cooling medium between each cold plate is determined based on the temperature equilibrium inflection point, with reference to... Figure 2 As shown in the figure, this is a flowchart illustrating the process of determining the traffic limiting period in some embodiments of this application. In this embodiment, the determination of the traffic limiting period can be achieved using the following steps: In step S21, the thermal relaxation information of the battery module in intermittent working mode is analyzed through the standing temperature equilibrium inflection point; In step S22, the initial amplitude gap during cooling medium flow rate adjustment is extracted based on the thermal relaxation information; In step S23, the dynamic demand rules for the cooling medium between each cold plate are determined based on the initial amplitude gap; In step S24, the flow rate limiting period of the cooling medium between each cold plate is determined by the dynamic demand rule.

[0030] In practice, firstly, real-time thermal distribution data for one hour before and after the thermal equilibrium inflection point is retrieved from the battery management system, including the temperature of each cold plate, the flow rate of the cooling medium, and the heat exchange power. Using the thermal equilibrium inflection point as the midpoint, the data is divided into two stages: "before the inflection point (insufficient heating / heat dissipation)" and "after the inflection point (thermal equilibrium)". The temperature change rate of each cold plate in both stages is calculated: the temperature value is selected every 5 minutes within the 30 minutes before the inflection point, and the ratio of the temperature difference to the time difference between adjacent time points is calculated to obtain the heating rate; similarly, the temperature change rate within the 30 minutes after the inflection point (approaching 0) is calculated. Simultaneously, the heat dissipation power change of the cooling medium in each stage is statistically analyzed. The temperature change rate, heat dissipation power change, and duration are integrated, and the integrated result is used as the thermal relaxation information of the battery module in intermittent operation mode. Then, based on the heat dissipation power change in the thermal relaxation information, the target heat dissipation power of each cold plate in the "non-equilibrium stage" and the "thermal equilibrium stage" is determined. Based on the relationship between heat dissipation power and cooling medium flow rate, the formula is: Flow rate = Heat dissipation power / (Specific heat capacity of medium × Inlet and outlet temperature difference), where the specific heat capacity of the medium is a known constant, and the inlet and outlet temperature difference is calibrated to 5℃ through previous experiments. The target flow rate for the cooling medium in each of the two stages is calculated. For example, in the non-equilibrium stage, the heat dissipation power of a cold plate is 100W, and the calculated target flow rate is 4L / min; in the thermal equilibrium stage, the heat dissipation power is 50W, and the target flow rate is 2L / min. The difference between the target flow rates in the two stages is used as the flow rate adjustment amplitude for that cold plate. The average flow rate adjustment amplitude for all cold plates is then taken, and standardized according to industry temperature control stability standards (flow rate variation should not exceed 30% of the benchmark value). The standardized result is used as the initial amplitude gap for cooling medium flow rate adjustment. Then, the temperature and heat exchange power of each cold plate are monitored in real time, and heat load judgment thresholds are set: when the temperature of a cold plate is higher than the target temperature (e.g., 35℃) or the heat exchange power exceeds the benchmark value by 120%, it is judged as a "high demand state"; when the temperature is lower than 25℃ or the heat exchange power is lower than the benchmark value by 80%, it is judged as a "low demand state"; the rest are "normal demand states". For different states, rules are formulated in conjunction with the initial amplitude gap: under high demand state, the cooling medium flow rate must be maintained at the upper limit of the initial amplitude gap (e.g., 4L / min); under normal demand state, the flow rate is adjusted to the middle value of the gap (e.g., 3L / min); under low demand state, the flow rate is reduced to the lower limit of the gap (e.g., 2L / min). At the same time, state switching conditions are set, such as switching to high demand state only when the temperature is higher than 35℃ for 5 consecutive minutes, to avoid frequent adjustments caused by short-term fluctuations, thus forming dynamic demand rules for the cooling medium between each cold plate.Finally, a flow regulation monitoring module is set up in the battery management system to record the flow regulation response time of each cold plate under different demand conditions: when a flow regulation command is issued (e.g., from 3L / min to 4L / min), the flow meter data is collected in real time, and the time it takes for the flow rate to reach the target value from the current value is recorded. The test is repeated 10 times and the average value is taken to obtain the flow response delay under each demand condition (e.g., a response delay of 3 seconds under high demand condition). According to the duration requirements of each state in the dynamic demand rules (e.g., the high demand condition must be maintained for at least 10 minutes), the flow limiting period is set to "shortest duration of state - response delay", thus obtaining the flow limiting period of the cooling medium between each cold plate.

[0031] It should be noted that, in this application, thermal relaxation information refers to the rate and process data of the temperature transition from a non-equilibrium state to an equilibrium state in the intermittent working mode of the battery module; intermittent working mode refers to the working mode of the new energy vehicle battery module in which charging and discharging operations are alternated and there are pause intervals, rather than continuous charging and discharging; initial amplitude gap refers to the reference difference range of the cooling medium flow rate before and after adjustment; dynamic demand rule refers to the flow rate adjustment adaptation criterion formulated according to the actual heat load change of the cold plate; flow rate limiting cycle refers to the time interval for controlling the change of cooling medium flow rate within a set amplitude.

[0032] In this embodiment, the dynamic proportion adjustment of the temperature hysteresis deviation between cold plates in the energy storage liquid cooling component based on all flow limiting cycles can be achieved through the following steps: The elastic pulsation amplitude of the cooling medium flow between each cold plate was analyzed by all flow limiting cycles. The dynamic adjustment weight of the temperature change hysteresis deviation is determined based on the elastic pulsation amplitude and the real-time collected temperature difference compensation sequence of the cold plate inlet and outlet. The dynamic adjustment weights are allocated to the hysteresis control loop according to the heat load distribution ratio between the cold plates, so as to realize the dynamic proportion adjustment of the temperature change hysteresis deviation.

[0033] In practice, firstly, the flow limiting cycle data of all cold plates and the real-time monitoring data of the cooling medium flow rate within the corresponding cycle are retrieved from the battery management system. Using a single flow limiting cycle as the analysis unit, for example, if the flow limiting cycle of a cold plate is 597 seconds, flow data is extracted every second within this cycle, resulting in 597 sets of data. The maximum and minimum values ​​of the flow data within this cycle are calculated, and the difference between the two is the flow pulsation value within that cycle. The flow pulsation value is calculated for each of the 10 consecutive flow limiting cycles of the cold plate, and the average value is taken as the elastic pulsation amplitude of the cold plate. Then, the inlet and outlet temperature difference data of each cold plate is collected in real time, recorded once every 10 seconds, while ambient temperature data is also collected. The compensated temperature difference is calculated using the formula: Temperature Difference = Measured Temperature Difference + 0.02 × (Ambient Temperature - 25℃), where 25℃ is the standard ambient temperature. Each set of measured temperature differences is corrected, and 10 consecutive sets of corrected temperature difference data are arranged chronologically to form a temperature difference compensation sequence. Weighting rules are then established: a larger elastic pulsation amplitude indicates more unstable medium flow and potentially larger temperature hysteresis deviation, corresponding to a higher adjustment weight; a larger average value in the temperature difference compensation sequence indicates a higher heat load on the cold plate, also resulting in a higher adjustment weight. The elastic pulsation amplitude (normalized to 0-0.5) is added to the average value of the temperature difference compensation sequence (normalized to 0-0.5), and the result is used as the dynamic adjustment weight for the temperature hysteresis deviation. Finally, the heat load distribution ratio of each cold plate is calculated: based on the heat load calculation formula (Heat Load = Cooling Medium Flow Rate × Medium Specific Heat Capacity × Average Value of Temperature Difference Compensation Sequence), the heat load of each cold plate is calculated, and then the heat load of a single cold plate is divided by the sum of the heat loads of all cold plates to obtain the heat load distribution ratio of that cold plate. The dynamic adjustment weights are then redistributed to the hysteresis control loop: Each cold plate corresponds to an independent hysteresis control loop. The dynamic adjustment weight of the cold plate is multiplied by the heat load distribution ratio to obtain the loop adjustment coefficient. The loop adjustment coefficient is input into the adjustment command generation module of the hysteresis control loop. The larger the coefficient, the larger the amplitude of the flow adjustment command output by the loop. The control loop adjusts the flow adjustment frequency and amplitude according to the coefficient to achieve targeted correction of temperature-induced hysteresis deviation.

[0034] It should be noted that, in this application, temperature hysteresis deviation refers to the hysteresis deviation between the actual temperature change response and the ideal control target when the temperature of the cold plate in the energy storage liquid cooling component changes; elastic pulsation amplitude refers to the magnitude of the flow rate fluctuation over time when the cooling medium flows between the cold plates; temperature difference compensation sequence refers to a continuous data set for correcting the real-time temperature difference between the inlet and outlet of the cold plate; hysteresis control loop represents the control unit used to monitor and correct the temperature hysteresis of the cold plate; dynamic adjustment weight refers to the adjustment priority coefficient allocated according to the actual thermal state of the cold plate; heat load distribution ratio refers to the proportion of heat that each cold plate in the energy storage system needs to bear to the total heat dissipation demand; dynamic proportion adjustment refers to adjusting the adjustment weight ratio of the temperature hysteresis deviation of each cold plate according to the real-time operating conditions to adapt to the temperature control method of heat load changes.

[0035] The temperature control determination module 300 is used to determine the temperature control gradual change attribute of the new energy vehicle battery module when the operating conditions change gradually, and to determine the cooling hysteresis trend of the new energy vehicle battery module during liquid cooling circulation based on the temperature control gradual change attribute. Then, the phase change cooling strategy of the cooling medium during stratified tolerance circulation is adapted and determined based on the cooling hysteresis trend.

[0036] In this embodiment, determining the temperature control properties of a new energy vehicle battery module under gradually changing operating conditions can be achieved through the following steps: Collect the real-time temperature change sequence of the battery module within the gradually changing operating range and the historical thermal management response delay index; The thermal inertia smoothness of the new energy vehicle battery module is determined based on the real-time temperature change sequence and the response delay index. The temperature control properties of the new energy vehicle battery module under gradually changing operating conditions are determined based on the thermal inertia smoothness.

[0037] In practice, firstly, the battery management system monitors operating parameters such as battery charging and discharging power and vehicle speed. Based on expert experience and battery cell charging and discharging change standards, a gradual change in operating conditions is defined as the period when the power or vehicle speed changes by ≤10% within 10 minutes. The start and end times of this period are recorded. Within this gradual change period, the average temperature of each cell in the battery module is collected every 5 seconds and organized into a real-time temperature change sequence according to the collection time. Simultaneously, historical thermal management data is retrieved from the energy storage system's storage unit: records within the past 3 months that are consistent with the current gradual change type (e.g., all are power gradual increase) are selected, and the difference between the time when the liquid cooling system's flow rate begins to adjust and the start time of the heat load change after each heat load change is extracted and averaged as the response delay index. Then, for the temperature values ​​of two adjacent time points in the sequence, the ratio of the temperature difference to the time difference is calculated to obtain the temperature change slope for each time interval. The average absolute value of all slopes is then taken as the average temperature change slope. If the response delay index is greater than 3s, it indicates that the system response is slow and the average temperature change slope needs to be multiplied by a correction factor of 1.2; if it is less than or equal to 3s, it should be multiplied by a factor of 1.0. The corrected value is the thermal inertia smoothness of the new energy vehicle battery module. Finally, a threshold for judging thermal inertia smoothness is set: referring to the industry standard for temperature control of new energy vehicle batteries, when the thermal inertia smoothness is ≤0.02℃ / s, the temperature control gradual change attribute is judged as "strong"; when the thermal inertia smoothness is between 0.02-0.04℃ / s, it is judged as "medium"; when the thermal inertia smoothness is >0.04℃ / s, it is judged as "weak". The thermal inertia smoothness is then compared with the threshold: if the thermal inertia smoothness of a battery module is 0.024℃ / s, which is in the range of 0.02-0.04℃ / s, its temperature control gradual change attribute is judged as "medium"; if the thermal inertia smoothness is 0.018℃ / s, it is judged as "strong"; if it is 0.045℃ / s, it is judged as "weak". All the results of the judgment are taken as the temperature control gradual change attribute of the new energy vehicle battery module under gradual change of operating conditions.

[0038] It should be noted that, in this application, "gradual change in operating conditions" refers to the state in which the charging and discharging power, vehicle speed, and other operating condition parameters of the new energy vehicle battery module change smoothly within a unit of time; "real-time temperature change sequence" refers to the set of battery module temperature change data recorded in chronological order within the gradual change range of operating conditions; "response delay index" refers to the response time parameter of the liquid cooling system to changes in heat load during historical thermal management; "thermal inertia smoothness" refers to the degree of smoothness of the battery module temperature change with heat load; and "gradual change in temperature control attribute" refers to the battery module's ability to smoothly adapt to temperature regulation during gradual changes in operating conditions.

[0039] Preferably, in this embodiment, the cooling hysteresis trend of the new energy vehicle battery module during liquid cooling cycle is determined based on the temperature control gradual change attribute, with reference to... Figure 3As shown in the figure, this is a flowchart illustrating the process of determining the cooling hysteresis trend in some embodiments of this application. In this embodiment, the determination of the cooling hysteresis trend can be achieved by the following steps: In step S31, the cyclic response constraints of the new energy vehicle battery module during liquid cooling are determined based on the temperature control gradual change attribute. In step S32, the hysteresis configuration index for liquid cooling cycle is determined based on the cyclic response constraint; In step S33, the linkage cooling trajectory of the new energy vehicle battery module during cooling response is determined; In step S34, the cooling hysteresis trend of the new energy vehicle battery module during liquid cooling cycle is determined based on the hysteresis configuration index and the linkage cooling trajectory.

[0040] In practice, firstly, the determined temperature control gradual change attribute (strong, medium, weak) is retrieved, and the corresponding cyclic response constraint dimensions are set according to the attribute: including the upper limit of the cooling medium flow rate adjustment rate, the temperature adjustment target deviation range, and the pressure stability threshold. If the temperature control gradual change attribute is "strong," it indicates that the temperature change is gradual, so the upper limit of the flow rate adjustment rate is set to 0.5 L / min·s (to avoid fluctuations caused by excessively rapid adjustment), the temperature adjustment target deviation range is ±0.5℃ (high-precision control), and the pressure stability threshold is ±0.02MPa; if the attribute is "medium," the upper limit of the flow rate adjustment rate is set to 0.8 L / min·s, the temperature deviation range is ±1℃, and the pressure threshold is ±0.03MPa; if the attribute is "weak," the temperature change is relatively rapid, so the upper limit of the flow rate adjustment rate is set to 1.2 L / min·s, the temperature deviation range is ±1.5℃, and the pressure threshold is ±0.05MPa. These parameters are then entered into the constraint configuration module of the battery management system to form the cyclic response constraints of the new energy vehicle battery module during liquid cooling circulation. Next, the flow hysteresis time, temperature response hysteresis, and pressure balance hysteresis duration were set, with each indicator calculated based on cyclic response constraints. Specifically, the flow hysteresis time was calculated based on the upper limit of the flow regulation rate in the cyclic response constraints, determining the time required from "triggering the flow regulation command" to "the actual flow reaching 80% of the constraint upper limit"; the temperature response hysteresis was set to 50% of the temperature regulation target deviation range in the cyclic response constraints; and the pressure balance hysteresis duration was set as the longest allowable time for pressure to stabilize within the constraint threshold after fluctuation. These three indicators were used as the hysteresis configuration indicators during liquid cooling circulation. Then, during liquid cooling circulation operation, linked data acquisition was initiated: three data points were synchronously collected every 2 seconds—average battery module temperature (T), real-time cooling medium flow rate (Q), and actual pipeline pressure (P), continuously for 30 minutes, resulting in 30 × 30 = 900 sets of synchronous data. Using time as the horizontal axis and temperature (left, unit: °C), flow rate (upper right, unit: L / min), and pressure (lower right, unit: MPa) as the vertical axes, three curves are plotted in data analysis software to form a "temperature-flow-pressure" linkage cooling trajectory diagram, which represents the linkage cooling trajectory of the new energy vehicle battery module during cooling response. Finally, key node data are extracted from the linkage cooling trajectory diagram: the time when the temperature first exceeds the target value (T0), the time when the flow rate begins to adjust (Q0), and the time when the pressure stabilizes (P0). Lag is determined by comparing the hysteresis configuration indicators: Q0-T0 is calculated; if it is greater than the flow rate hysteresis time (e.g., 4s), "flow rate adjustment hysteresis" is identified; the maximum extent by which the temperature exceeds the target value is calculated; if it is greater than the temperature response hysteresis (e.g., 0.25°C), "temperature response hysteresis" is identified; P0-Q0 is calculated; if it is greater than the pressure balance hysteresis time (e.g., 5s), "pressure balance hysteresis" is identified.Statistical lag type and degree: If only the flow regulation is lagging and Q0-T0=5s (exceeding the indicator by 1s), the cooling lag trend is judged as "slight flow lag"; if there is both temperature response lag (exceeding 0.3℃) and pressure balance lag (P0-Q0=7s), it is judged as "moderate comprehensive lag"; if all indicators are seriously exceeded (such as Q0-T0=8s), it is judged as "severe comprehensive lag", forming a cooling lag trend of new energy vehicle battery modules in liquid cooling cycle.

[0041] It should be noted that, in this application, the cyclic response constraint refers to the boundary that limits the adjustment range and speed of the liquid cooling cycle; the hysteresis configuration index refers to the parameter that quantifies the degree of hysteresis of the liquid cooling system in the cyclic adjustment; the linkage cooling trajectory refers to the curve that reflects the synchronous change of the battery module temperature and the adjustment action of the liquid cooling system; and the cooling hysteresis trend refers to the direction and degree of hysteresis of the liquid cooling system in response to changes in the thermal load of the battery module.

[0042] In this embodiment, the determination of temperature adjustment based on the cooling hysteresis trend to adapt the phase change cooling strategy of the cooling medium in stratified tolerance circulation can be achieved in the following way: Based on the cooling hysteresis trend, the temperature rheological tolerance of the cooling component during cooling is analyzed. Determine the amplitude adjustment correction rules for the cooling medium during stratified tolerance circulation; Based on the amplitude adjustment correction rule and the temperature rheological tolerance, the feasibility of phase change action in the stratified tolerance circulation process is determined, and the adaptation temperature adjustment determination result is obtained.

[0043] In practice, firstly, the cooling hysteresis trend (slight flow hysteresis, moderate overall hysteresis, severe overall hysteresis) is retrieved, and the analytical dimensions of the temperature rheological tolerance are set according to the trend type: including the maximum allowable temperature fluctuation value, the upper limit of the temperature change rate, and the tolerance maintenance duration. If the cooling hysteresis trend is "slight flow hysteresis", it indicates a low degree of hysteresis, and the maximum allowable temperature fluctuation value is set to ±1℃ (strictly controlling fluctuations), the upper limit of the temperature change rate is 0.03℃ / s, and the tolerance maintenance duration is 10 minutes (requiring long-term stability); if it is "moderate overall hysteresis", the fluctuation value is relaxed to ±1.5℃, the upper limit of the rate is 0.05℃ / s, and the maintenance duration is 8 minutes; if it is "severe overall hysteresis", the fluctuation value is set to ±2℃, the upper limit of the rate is 0.08℃ / s, and the maintenance duration is 5 minutes (prioritizing timely cooling). Then, historical temperature control data is used for verification: Temperature fluctuation records under the same trend are extracted. If over 90% of the data meets the set tolerance, the temperature rheological tolerance is determined; if not, the fluctuation value is increased by 0.2℃ and re-verified until the requirement is met, thus obtaining the temperature rheological tolerance when the cooling component is cooling. Next, the cooling medium is layered: based on the battery module cold plate installation position, it is divided into upper, middle, and lower cold plates, labeled L1, L2, and L3, respectively, with each layer corresponding to an independent flow control valve. The core parameters for amplitude correction are then defined: including the basic adjustment amplitude (set according to the average heat load of each layer) and the layer correction coefficient (calculated based on the difference in heat load between layers). Basic adjustment amplitude: L1 layer average heat load 120W, basic amplitude set to 1.2L / min; L2 layer 100W, set to 1.0L / min; L3 layer 80W, set to 0.8L / min. Layered correction coefficient calculation: Divide the real-time heat load of each layer by the average heat load. For example, if the real-time heat load of layer L1 is 132W, the correction coefficient = 132W ÷ 120W = 1.1. This will not be elaborated further. Finally, simulate layered tolerance circulation adjustment: In the simulation module of the battery management system, input the real-time temperature and heat load data of each layer of cold plates, calculate the actual adjustment range of the cooling medium of each layer according to the amplitude correction rule, and simulate the temperature change curve after adjustment. Then compare the temperature rheological tolerance: If in the simulation curve, the temperature fluctuation value of each layer is ≤ the set tolerance (e.g., ±1.5℃), the temperature change rate is ≤ the upper limit (e.g., 0.05℃ / s), and the duration reaches the tolerance maintenance time (e.g., 8 minutes), then it is determined that "no phase change cooling strategy needs to be enabled", and the current liquid cooling amplitude adjustment can be maintained; if the temperature fluctuation value of any layer exceeds the tolerance, or the rate exceeds the upper limit, and the duration exceeds 3 minutes, then it is determined that "the phase change cooling strategy needs to be enabled". Parameter settings upon activation: Phase change trigger temperature = upper limit of temperature rheological tolerance - 0.3℃ (e.g., if tolerance ±1.5℃, trigger temperature = target temperature + 1.2℃), phase change medium filling ratio = basic ratio (30%) + 0.05 × hysteresis level (medium hysteresis level 2, ratio = 30% + 10% = 40%). Compile the judgment results and parameters into an adaptation temperature adjustment judgment report.Final amplitude correction rule: The actual adjustment amplitude of a certain layer = the basic adjustment amplitude × the layer correction coefficient, and the actual amplitude must be within the "flow range corresponding to the temperature rheological tolerance" (e.g., when the tolerance is ±1℃, the flow range is 1.0-1.4L / min). If it exceeds the range, the boundary value of the range shall be taken as the actual amplitude.

[0044] It should be noted that, in this application, stratified tolerance circulation refers to a circulation mode in which the cooling medium flows in layers according to the cold plate, and the flow rate and pressure of each layer are allowed to have certain deviations; phase change cooling strategy refers to a temperature control scheme that absorbs a large amount of heat through phase change of the cooling medium to adapt to changes in the heat load of the battery module; temperature rheological tolerance refers to the maximum range of temperature fluctuation allowed over time during the temperature control process of the cooling component; amplitude correction rule refers to the criteria for correcting the adjustment amplitude of the cooling medium in stratified tolerance circulation; and adaptation temperature control judgment result refers to the conclusion that clarifies whether the phase change cooling strategy is enabled and how the enabling parameters are set.

[0045] The quota correction module 400 is used to correct the quota of the cooling medium in the energy storage liquid cooling component based on the temperature change hysteresis deviation after dynamic ratio adjustment and the phase change cooling strategy after temperature adjustment determination.

[0046] In this embodiment, the quota correction of the cooling medium in the energy storage liquid cooling component based on the temperature change hysteresis deviation after dynamic ratio adjustment and the phase change cooling strategy after adaptive temperature adjustment determination can be specifically carried out in the following manner: The intensity of conflict feedback during the thermal control process is determined based on the temperature change hysteresis deviation after dynamic proportion adjustment and the phase change cooling strategy after adaptive temperature adjustment judgment. A quota correction sequence for cooling medium is generated based on the conflict feedback intensity and the real-time cooling medium flow requirement. The flow distribution of the cooling medium among the cold plates is rebalanced using the quota correction sequence, and the quota-corrected cooling medium allocation index is output.

[0047] In practice, firstly, the temperature hysteresis deviation value of each cold plate is obtained from the dynamic proportion adjustment results (e.g., cold plate 1: 0.8℃, cold plate 2: 1.2℃), and the phase change cooling strategy parameters (e.g., phase change trigger temperature 32℃, medium filling ratio 40%) are obtained from the adaptation temperature adjustment judgment results. Then, conflict scenarios are defined: if the temperature hysteresis deviation is >1℃ (requiring increased flow correction), but the phase change strategy requires reduced flow to avoid overcooling (e.g., flow rate ≤3L / min at a filling ratio of 40%), then a conflict is determined to exist; if the deviation is ≤1℃ and consistent with the flow rate requirement of the phase change strategy, then there is no conflict. Conflict feedback intensity calculation: the intensity is set to 0 for no conflict, 0.3 for mild conflict (1 cold plate conflict), 0.6 for moderate conflict (2-3 cold plate conflicts), and 0.9 for severe conflict (≥4 cold plate conflicts). For example, if there is a conflict between two cold plates, the conflict feedback intensity is determined to be 0.6; if there is only one conflict and the deviation is small (0.9℃), the intensity is adjusted to 0.2. Finally, the intensity values ​​of each conflict area are recorded, and the conflict feedback intensity in the thermal control process is obtained by summarizing them. Then, calculate the real-time flow requirement: Based on the heat load of each cold plate (heat load = specific heat capacity of medium × flow rate × temperature difference), calculate the current required cooling medium flow rate. For example, if the heat load of cold plate 1 is 120W, the specific heat capacity of the medium is 4.2kJ / (kg·℃), and the temperature difference is 5℃, then the real-time required flow rate = 120W ÷ 4.2 × 10³J / (kg·℃) × 5℃ × 1kg / L) ≈ 5.7L / min. Then, combine the conflict feedback intensity correction: If the conflict feedback intensity is 0.6 (moderate conflict), the real-time required flow rate is 5.7L / min, and the phase change strategy allows a maximum flow rate of 3L / min, then the corrected flow rate = 3L / min + 0.6 × (5.7L / min - 3L / min) = 3L / min + 1.62L / min = 4.62L / min; if the intensity is 0 (no conflict), the corrected flow rate = real-time required flow rate. Generate quota correction sequence: Generate correction instructions at 10-second intervals, and divide the correction flow rate into gradients of "increase by 0.2L / min every 10 seconds" to obtain the quota correction sequence for the cooling medium.

[0048] It should be noted that in this application, the quota correction sequence refers to the set of cooling medium quota adjustment instructions arranged in chronological order; the conflict feedback intensity refers to the degree of contradiction between the temperature change hysteresis deviation after quantification of dynamic proportion adjustment and the phase change cooling strategy in terms of thermal control requirements; the cooling medium allocation index refers to the standard parameters such as cooling medium flow rate, pressure, and phase change ratio of each cold plate after correction; and the flow distribution rebalancing refers to adjusting the cooling medium flow rate ratio of each cold plate according to the quota correction sequence.

[0049] Therefore, this application demonstrates that it can precisely regulate the temperature control requirements of multiple operating conditions in the liquid cooling scenario of new energy vehicle battery modules. Specifically, by acquiring the thermal distribution information of each cold plate component during the collaborative operation of the battery module, it can overcome the shortcomings of existing technologies that do not cover the details of cold plate collaboration in thermal distribution acquisition. It comprehensively captures key data such as the cold plate temperature field, medium flow rate, and heat exchange power, constructing a complete thermal characteristic input foundation, thereby improving the liquid cooling system's perception accuracy and collaborative analysis capabilities of the battery module's thermal state. Furthermore, by determining the stationary temperature equilibrium inflection point in intermittent charge-discharge states based on all thermal distribution information, and then determining the cooling medium flow rate limiting period and dynamically adjusting the temperature change hysteresis deviation between cold plates accordingly, it can solve the problems of disconnect between stationary temperature inflection point determination and flow regulation, and the lack of correction for temperature change hysteresis in existing technologies. This ensures precise matching between flow regulation and thermal equilibrium nodes, eliminates temperature control asynchrony between cold plates, and effectively improves the temperature control performance under intermittent charge-discharge conditions. This technology improves the synchronization and efficiency of cooling medium utilization. By determining the temperature change attributes under gradually changing operating conditions, and then determining the cooling hysteresis trend of the liquid cooling cycle accordingly, and adapting it to the phase change cooling strategy based on the stratified tolerance circulation, it can overcome the shortcomings of existing technologies where the temperature change attributes are disconnected from the cooling hysteresis and the phase change strategy is not well adapted. This makes the temperature control strategy fit the characteristics of gradually changing operating conditions, avoids cooling lag, dynamically optimizes the activation timing and parameters of phase change cooling, and enhances the adaptability and heat dissipation efficiency of the liquid cooling system to gradually changing operating conditions. By adjusting the cooling medium quota based on the temperature change hysteresis deviation after dynamic ratio adjustment and the phase change cooling strategy after temperature adjustment judgment, it can solve the problem of existing quota correction not integrating multiple factors, achieve multi-dimensional precise allocation of flow rate, pressure, and phase change ratio, and construct a closed-loop control of "sensing-judgment-adjustment-correction", thereby improving the temperature control accuracy of the liquid cooling system under multiple operating conditions, the battery operation safety, and the application adaptability of high energy density battery modules.

[0050] In summary, the technical solution adopted in this application can adjust the cooling medium regulation strategy of the energy storage liquid cooling component throughout the entire process under the dynamic changes of multiple operating conditions of the battery module, so as to improve the accuracy of battery module temperature control.

[0051] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0052] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compactdisc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0053] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

Claims

1. A liquid cooling system for energy storage in a battery module for a new energy vehicle, characterized in that, The energy storage liquid cooling system includes: The information acquisition module is used to acquire information on the heat distribution status of each cold plate component when the new energy vehicle battery module works together during operation. The proportion adjustment module is used to determine the stationary temperature equilibrium inflection point of the battery module in intermittent charge and discharge state based on all heat distribution state information, determine the flow limiting period of the cooling medium between each cold plate based on the stationary temperature equilibrium inflection point, and then dynamically adjust the proportion of temperature change hysteresis deviation between cold plates in the energy storage liquid cooling component based on all flow limiting periods. The stationary temperature equilibrium inflection point refers to the key node marking the dynamic balance between the heat generation rate and the heat dissipation rate of the battery module in intermittent charge and discharge. The flow limiting period refers to the time interval for controlling the change of cooling medium flow rate within a set range. The dynamic proportion adjustment refers to adjusting the adjustment weight proportion of temperature change hysteresis deviation of each cold plate according to real-time operating conditions to adapt to the temperature control method of changing heat load. The temperature control determination module is used to determine the temperature control properties of the new energy vehicle battery module under gradually changing operating conditions. Based on the temperature control properties, it determines the cooling hysteresis trend of the new energy vehicle battery module during liquid cooling circulation. Then, based on the cooling hysteresis trend, it determines the appropriate temperature control for the phase change cooling strategy of the cooling medium under stratified tolerance circulation. The temperature control properties refer to the stable adaptation capability of the battery module's temperature regulation under gradually changing operating conditions. The cooling hysteresis trend refers to the direction and degree of lag of the liquid cooling system in response to changes in the thermal load of the battery module. The quota correction module is used to correct the quota of the cooling medium in the energy storage liquid cooling component based on the temperature change hysteresis deviation after dynamic ratio adjustment and the phase change cooling strategy after temperature adjustment determination.

2. The energy storage liquid cooling system for a new energy vehicle battery module as described in claim 1, characterized in that, The specific steps to determine the inflection point of the battery module's temperature equilibrium during intermittent charging and discharging, based on all thermal distribution information, include: The temperature change properties of the battery module are determined based on real-time heat distribution data during intermittent charging and discharging. The gradual temperature gradient within the charge / discharge cycle is determined by the aforementioned temperature change attribute. The gradual temperature gradient determines the inflection point of the stationary temperature equilibrium of the battery module in the intermittent charge and discharge state.

3. The energy storage liquid cooling system for a new energy vehicle battery module as described in claim 1, characterized in that, The dynamic proportion adjustment of the temperature hysteresis deviation between cold plates in the energy storage liquid cooling module by all flow limiting cycles specifically includes: The elastic pulsation amplitude of the cooling medium flow between each cold plate was analyzed by all flow limiting cycles. The dynamic adjustment weight of the temperature change hysteresis deviation is determined based on the elastic pulsation amplitude and the real-time collected temperature difference compensation sequence of the cold plate inlet and outlet. The dynamic adjustment weights are allocated to the hysteresis control loop according to the heat load distribution ratio between the cold plates, so as to realize the dynamic proportion adjustment of the temperature change hysteresis deviation.

4. The energy storage liquid cooling system for a new energy vehicle battery module as described in claim 1, characterized in that, The specific characteristics of temperature control and gradual change attributes of new energy vehicle battery modules under gradual changes in operating conditions include: Collect the real-time temperature change sequence of the battery module within the gradually changing operating range and the historical thermal management response delay index; The thermal inertia smoothness of the new energy vehicle battery module is determined based on the real-time temperature change sequence and the response delay index. The temperature control properties of the new energy vehicle battery module under gradually changing operating conditions are determined based on the thermal inertia smoothness.

5. The energy storage liquid cooling system for a new energy vehicle battery module as described in claim 1, characterized in that, The determination of temperature adjustment based on the cooling hysteresis trend to adapt the phase change cooling strategy of the cooling medium in stratified tolerance circulation specifically includes: Based on the cooling hysteresis trend, the temperature rheological tolerance of the cooling component during cooling is analyzed. Determine the amplitude adjustment correction rules for the cooling medium during stratified tolerance circulation; Based on the amplitude adjustment correction rule and the temperature rheological tolerance, the feasibility of phase change action in the stratified tolerance circulation process is determined, and the adaptation temperature adjustment determination result is obtained.

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