A liquid cooling circulation control method for a power battery box of an electric vehicle

Abstract

This application relates to the field of battery box thermal management technology, specifically to a liquid cooling circulation control method for an electric vehicle power battery box. The method includes: real-time acquisition of the temperature at each temperature observation point of each individual battery cell within the battery box; constructing a thermal field non-uniformity factor based on the instantaneous temperature difference, high-temperature duration, and temperature dispersion of each individual battery cell; constructing a thermal equilibrium failure risk value based on the differences in thermal field non-uniformity factors among all individual batteries within the battery box; constructing a phase change margin coefficient based on the cooling capacity of the composite phase change material within the battery box at the current temperature; obtaining a label at each time point; and combining the thermal equilibrium failure risk value, phase change margin coefficient, and average temperature change rate at all times to obtain a classification model, thereby obtaining the label of the battery box at the current time point, and determining whether the liquid cooling circulation system needs to be activated. This application achieves a balance between thermal management efficiency and energy consumption by controlling the activation time of the liquid cooling circulation system.

Description

Technical Field

[0001] This application relates to the field of battery box thermal management technology, specifically to a liquid cooling cycle control method for an electric vehicle power battery box. Background Technology

[0002] Electric vehicle battery packs typically consist of multiple lithium-ion batteries connected in series and parallel to form integrated battery modules. The small spacing between individual cells within the battery pack leads to poor heat dissipation, causing heat accumulation in the central area. Currently, there are two main types of thermal management for electric vehicle battery packs: air-cooled and liquid-cooled. Air-cooled thermal management is simple in structure and low in cost, but its heat dissipation effect is limited and it struggles to cope with high-temperature environments outside the vehicle. Liquid-cooled thermal management uses a liquid cooling medium with a higher convective heat transfer coefficient, providing precise temperature control and good temperature uniformity, but it consumes more energy.

[0003] Passive thermal management of phase change materials (PCMs) is a novel thermal management method for electric vehicle battery packs, offering advantages such as simple structure, convenient maintenance, and no energy consumption. However, it suffers from low heat exchange efficiency, difficulty in dissipating stored latent heat, and limited heat capacity. To overcome these shortcomings, a combination of two thermal management methods is often employed, such as phase change-liquid cooling coupling technology. This technology introduces active liquid cooling circulation into the passively thermally managed PCM, utilizing both the latent heat storage of the PCM and the efficient heat dissipation capabilities of liquid cooling. However, continuous operation of the liquid cooling circulation system leads to significant energy consumption, reducing vehicle range. To further reduce energy consumption, the liquid cooling circulation system needs to be activated when the cooling effect of the PCM is insufficient. However, determining the optimal timing for liquid cooling system intervention is challenging; premature intervention increases energy consumption, while delayed intervention causes overheating of the battery pack, impacting battery life and safety. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides a liquid cooling cycle control method for an electric vehicle power battery box, thereby resolving the existing issues.

[0005] The liquid cooling cycle control method for an electric vehicle power battery box of this application adopts the following technical solution: One embodiment of this application provides a liquid cooling cycle control method for an electric vehicle power battery pack, the method comprising the following steps: Several temperature observation points are set on the surface of each individual battery cell inside the battery box, and the temperature of each temperature observation point is acquired in real time. Based on the temperature difference of all temperature observation points of each individual cell at the current moment, as well as the duration of high temperature and the degree of temperature dispersion of each individual cell during the observation period at the current moment, a thermal field non-uniformity factor of each individual cell at the current moment is constructed; based on the difference between the thermal field non-uniformity factors of all individual cells in the battery box at the current moment, a thermal equilibrium failure risk value is constructed to characterize the possibility of thermal imbalance risk in the battery box at the current moment. The peak phase change temperature and the termination phase change temperature of the composite phase change material are obtained based on the pre-acquired DSC curve of the composite phase change material; the phase change margin coefficient is constructed based on the temperature range of the average temperature of all temperature observation points in the battery box at the current moment, and the difference between it and the peak phase change temperature and the termination phase change temperature. Based on the actual state of the liquid cooling circulation system of the battery box at each moment within a preset historical period, the label of each moment is obtained. Combined with the thermal equilibrium failure risk value, phase transition margin coefficient, and average temperature change rate at all moments, a classification model is obtained to obtain the label of the battery box at the current moment, and then it is determined whether the liquid cooling circulation system needs to be turned on at the current moment.

[0006] Preferably, the specific process of setting several temperature observation points on the surface of each individual battery cell inside the battery box is as follows: Obtain the temperature cloud map of the battery box at the end of discharge without opening the liquid cooling pipes, and take the positions corresponding to the maximum and minimum surface temperatures of each individual cell in the obtained temperature cloud map as the first type of observation points; Obtain the temperature cloud map of the battery box with the liquid cooling pipes turned on at the end of discharge, and take the positions corresponding to the maximum and minimum surface temperatures of each individual cell in the obtained temperature cloud map as the second type of observation points. The locations of the nearest individual battery cells on both sides of each liquid cooling pipe are used as the third type of observation points; All observation points in the union of the first, second, and third types of observation points are used as the temperature observation points of the battery box.

[0007] Preferably, the process for constructing the thermal field non-uniformity factor of each individual cell at the current moment is as follows: Calculate the difference between the highest and lowest temperature values ​​of each individual cell at all temperature observation points at the current moment; The temperatures of all temperature observation points of each individual cell at each time point within the current observation period are counted. The temperature observation points corresponding to the highest temperature at each time point are selected. The number of times each temperature observation point of each individual cell reaches the highest temperature within the current observation period is recorded as the high temperature indicator value of each temperature observation point. Calculate the variance of the temperature values ​​of each individual cell at all temperature observation points at each time, and calculate the mean of the variance of each individual cell at all times within the observation period at the current time. The thermal field non-uniformity factor is positively correlated with the difference, the mean, and the maximum value among the high temperature identification values ​​of all temperature observation points.

[0008] Preferably, the thermal equilibrium failure risk value is positively correlated with the range of the thermal field non-uniformity factor of all individual cells in the battery box at the current moment.

[0009] Preferably, the phase transition peak temperature refers to the temperature of the highest peak point of the endothermic peak in the DSC curve; the phase transition termination temperature refers to the temperature at the intersection of the trailing tangent of the endothermic peak in the DSC curve and the baseline; wherein, the trailing tangent of the endothermic peak refers to the tangent at the point where the absolute value of the slope is the largest in the descending edge of the endothermic peak of the DSC curve.

[0010] Preferably, the formula for calculating the phase transition margin coefficient is: In the formula, This represents the phase transition margin coefficient of the battery pack at the current moment. It is the average temperature of all temperature observation points inside the battery box at the current moment; It is the peak phase transition temperature of the composite phase change material; is the phase transition termination temperature of the composite phase change material; exp() is an exponential function with the natural constant e as the base.

[0011] Preferably, the method for obtaining the tags at each moment is as follows: when the liquid cooling circulation system of the battery box is not turned on at any moment within a preset historical period, the tag for that moment is set to "not turned on"; otherwise, the tag for that moment is set to "turned on".

[0012] Preferably, the process of obtaining the classification model is as follows: the thermal equilibrium failure risk value, phase transition margin coefficient, and average temperature change rate at each time point are used to form the feature vector at each time point; the feature vectors of all times within a preset historical period and their corresponding labels are used as the input of the classification model to train the model and obtain the trained classification model.

[0013] Preferably, the method for obtaining the label of the battery box at the current moment is as follows: the feature vector of the battery box at the current moment is used as the input of the trained classification model, and the label at the current moment is output.

[0014] Preferably, the specific process of determining whether the liquid cooling circulation system needs to be activated at the current moment is as follows: If the battery box is currently labeled "not open", then there is no need to turn on the liquid cooling circulation system; If the battery compartment is currently labeled "on", then the liquid cooling circulation system needs to be turned on.

[0015] This application has at least the following beneficial effects: This application addresses the difficulty in determining the intervention timing of the liquid cooling circulation system in phase change-liquid cooling coupling technology. By analyzing the temperature distribution differences of individual cells, the duration of high temperatures, and the degree of temperature non-uniformity at different times, a thermal field non-uniformity factor is constructed, overcoming the limitations of traditional methods that rely solely on instantaneous temperature difference criteria. A thermal equilibrium failure risk value is constructed to dynamically assess the probability of thermal imbalance, identifying battery degradation risks caused by uneven heat dissipation and providing a basis for subsequent decisions on whether to activate the liquid cooling circulation system. By analyzing the cooling capacity of the composite phase change material within the battery pack at the current temperature, a phase change margin coefficient is constructed, providing a basis for determining whether to activate the liquid cooling circulation system at the current moment. Furthermore, a classification model is trained using the thermal equilibrium failure risk value, phase change margin coefficient, and average temperature change rate to determine whether the liquid cooling circulation system needs to be activated at the current moment. This method can promptly activate the liquid cooling circulation system when the cooling capacity of the composite phase change material weakens or fails, dissipating heat and achieving an optimized balance between thermal management efficiency and energy consumption, thus improving the safety of the battery pack. Attached Figure Description

[0016] To more clearly illustrate the technical solutions and advantages 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 some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating the steps of a liquid cooling cycle control method for an electric vehicle power battery box provided in this application; Figure 2 This is a schematic diagram of the internal structure of the electric vehicle power battery box provided in this application; wherein, 1 is the battery box shell, 2 is the lithium iron phosphate battery, 3 is the paraffin / expanded graphite composite phase change material, and 4 is the liquid cooling pipe. Figure 3 The location distribution map of the third type of observation points provided in this application; where "×" indicates the location of the third type of observation points. Detailed Implementation

[0018] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a liquid cooling cycle control method for an electric vehicle power battery box proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0020] The following description, in conjunction with the accompanying drawings, details a specific scheme for a liquid cooling cycle control method for an electric vehicle power battery box provided in this application.

[0021] This application provides a liquid cooling cycle control method for an electric vehicle power battery box in one embodiment. Specifically, it provides the following liquid cooling cycle control method for an electric vehicle power battery box. Please refer to [link to relevant documentation]. Figure 1 The method includes the following steps: Step 1: Set up several temperature observation points on the surface of each individual battery cell inside the battery box, and obtain the temperature of each temperature observation point in real time.

[0022] Phase change materials (PCMs) are materials that can change their physical state within a certain temperature range. When the battery temperature reaches the PCM temperature, the PCM undergoes a solid-liquid or gas-liquid transition, absorbing the heat dissipated during battery charging and discharging. Paraffin wax, due to its wide PCM temperature range, low cost, and non-corrosiveness, is often used as a PCM for battery cooling. However, pure paraffin wax has low thermal conductivity, making it difficult to rapidly cycle under the complex operating conditions of electric vehicles. Adding expanded graphite helps improve the heat transfer rate of the PCM. This application uses a paraffin / expanded graphite composite PCM for the electric vehicle power battery box, where the proportion of expanded graphite is 3%-15%, and in this embodiment, it is 6%.

[0023] Electric vehicle power battery boxes typically employ a battery module structure where multiple lithium-ion batteries are connected in series and parallel. A large number of batteries are compactly connected within the power battery box. This application uses N identical square lithium iron phosphate batteries connected in series to form an electric vehicle battery module. The spacing between each lithium iron phosphate battery is set to 8mm. A composite phase change material composed of paraffin / expanded graphite is filled into the battery box, and liquid cooling pipes are embedded in the gaps between adjacent lithium iron phosphate batteries. The liquid cooling pipes are made of aluminum tubing with an inner diameter of 4mm, and the cooling medium is pure water. A schematic diagram of the internal structure of the electric vehicle power battery box is shown below. Figure 2As shown. For ease of description, the electric vehicle power battery box will be referred to as the battery box from now on.

[0024] This application simplifies the lithium iron phosphate battery model, assuming that the lithium iron phosphate battery surface is flat without bulges and the internal material is uniformly distributed. The resistance at the electrode connection is not considered. It is assumed that the spacing of the lithium iron phosphate batteries is completely consistent and that the composite phase change material is uniformly distributed. Fluent is used to perform the first thermal simulation analysis on the battery box without opening the liquid cooling pipe. The ambient temperature is 25℃, the initial SOC of the battery box is 100%, and the discharge rate is 3C. The temperature cloud map of the battery box at the end of the discharge is obtained and recorded as the first temperature cloud map.

[0025] A second thermal simulation analysis was performed on the battery box with the liquid cooling pipes open using Fluent. In this simulation, the influence of the liquid cooling pipe wall thickness and the embedded pipe on the total amount of composite phase change material was ignored. The flow velocity of the fluid in the pipe was set to 0.2 m / s, the coolant inlet temperature was set to 25℃, and the other parameters were the same as those in the first thermal simulation. The battery box temperature cloud map at the end of the discharge was obtained and recorded as the second temperature cloud map.

[0026] Within the first temperature cloud map, the locations corresponding to the maximum and minimum surface temperatures of each individual battery cell are selected as first-type observation points. Within the second temperature cloud map, the battery surface locations corresponding to the maximum and minimum surface temperatures of each individual battery cell are selected as second-type observation points. It should be noted that if multiple maximum and minimum temperature values ​​exist on the surface of each individual battery cell, the locations corresponding to all maximum and minimum temperatures are used as observation points. Furthermore, this application uses the closest individual battery cell surface locations on both sides of each liquid cooling pipe as third-type observation points. The distribution map of the third-type observation points is shown below. Figure 3 As shown in the figure, "×" indicates the location of the third type of observation point.

[0027] All observation points in the union of the first, second, and third types of observation points are used as temperature observation points for the battery box. Temperature sensors are placed at all these observation points to monitor the surface temperature of each observation point inside the battery box. In this embodiment, the data acquisition time interval for the temperature sensors is set to 1 second.

[0028] Step 2: Based on the temperature difference of all temperature observation points of each individual cell at the current moment, as well as the duration of high temperature and the degree of temperature dispersion of each individual cell during the observation period at the current moment, construct the thermal field non-uniformity factor of each individual cell at the current moment; based on the difference between the thermal field non-uniformity factors of all individual cells in the battery box at the current moment, construct the thermal equilibrium failure risk value to characterize the possibility of thermal imbalance risk in the battery box at the current moment.

[0029] Since the lithium-ion batteries used in electric vehicles are generally stacked into a single cell using a lamination or winding process, the thermal conductivity of square lithium-ion batteries is significantly lower in the thickness direction than in the length and width direction. When the battery pack is working, especially under high-rate charging and discharging conditions, the heat generated inside the battery is uneven, and there are certain temperature differences in different positions of the single square cell.

[0030] For any single cell in the battery box, there are multiple temperature observation points. Taking the i-th cell at the current moment as an example, we obtain the highest temperature value among all temperature observation points of the i-th cell at the current moment. and minimum temperature Calculate the temperature difference of the i-th individual cell at the current moment. : In the formula, Let i be the temperature difference of the i-th individual cell at the current moment. This represents the highest temperature value among all temperature observation points for the i-th individual cell at the current time. It represents the lowest temperature among all temperature observation points of the i-th individual cell at the current moment.

[0031] income It directly reflects the degree of imbalance in the thermal field of the battery. The larger the value, the more unbalanced the thermal field of the i-th cell at the current moment.

[0032] Furthermore, uneven thermal distribution within a single cell is a key indicator affecting battery lifespan. In the internal regions of a single cell that are consistently exposed to higher temperatures, the SEI film thickens continuously and rapidly, consuming active lithium and increasing internal resistance. Conversely, the cooler regions age more slowly, directly leading to capacity decay and uneven internal resistance in the single cell, thus reducing battery lifespan.

[0033] Based on the above characteristics, this application uses the current moment and a preset number of sampling moments prior to it as the observation period for the current moment. In this embodiment, the preset number is 120. The temperatures of all temperature observation points for the i-th individual cell at each moment within the observation period are counted. The temperature observation point corresponding to the highest temperature at each moment is selected. The number of times each temperature observation point of the i-th individual cell reaches the highest temperature within the observation period is counted and recorded as the high-temperature identifier value for each temperature observation point, used to characterize the duration of high temperature at each temperature observation point.

[0034] Calculate the variance of the temperature values ​​at all temperature observation points for the i-th cell at each time step, using this variance as the discrete value of the temperature distribution of the i-th cell at each time step. Then, denot the mean of the discrete values ​​of the temperature distribution of the i-th cell at the current time step within the observation period as follows: This reflects the degree of difference in surface temperature distribution of the i-th individual cell under short-term operating conditions.

[0035] As a preferred implementation, a thermal field non-uniformity factor for each individual battery cell is constructed based on the temperature difference at all temperature observation points of each individual battery cell at the current moment, the duration of high temperature in the observation period of each individual battery cell at the current moment, and the degree of temperature dispersion at all moments. This factor is used to characterize the degree of harm caused by the temperature non-uniformity of each individual battery cell to the battery at the current moment. The construction process of the thermal field non-uniformity factor for each individual battery cell at the current moment is as follows: calculate the difference between the highest and lowest temperature values ​​among all temperature observation points of each individual battery cell at the current moment; statistically analyze the high temperature indicator values ​​of each temperature observation point of each individual battery cell within the observation period of the current moment; calculate the variance of the temperature values ​​of all temperature observation points of each individual battery cell at each moment, and calculate the mean of the variance of each individual battery cell at all moments within the observation period of the current moment; the thermal field non-uniformity factor is positively correlated with the difference, the mean, and the maximum value among the high temperature indicator values ​​of all temperature observation points. The positive correlation means that the dependent variable increases (decreases) as the independent variable increases (decreases).

[0036] In this embodiment, the thermal field non-uniformity factor of the i-th single cell at the current moment is denoted as . Its specific expression is: In the formula, Let be the thermal field non-uniformity factor of the i-th single cell at the current moment; It is the temperature difference of the i-th individual cell at the current moment. It is the maximum value of the high temperature indicator value among all temperature observation points of the i-th single cell within the observation period at the current time, and n is the total number of sampling times within the current time and its preset historical period; It is the mean of the discrete values ​​of the temperature distribution of the i-th individual cell at all times within the observation period at the current time. This is a normalization function used to ensure that the value range of the fused objects is consistent. In this embodiment, the minimum-maximum normalization method is used for normalization.

[0037] The calculation logic of the above formula is as follows: Since the lifespan degradation of individual batteries in an electric vehicle battery pack depends not only on the temperature difference at a certain instant, but also on the temperature distribution pattern and sustained high temperatures, Used to characterize the instantaneous temperature difference of the i-th individual cell at the current moment; Used to capture the dynamic non-uniformity of the thermal field of the i-th individual cell during the observation period at the current moment; As a high-temperature duration weight, it measures the duration of the high-temperature location on the surface of the i-th cell. A larger value indicates a longer duration of the high-temperature region and a greater degree of harm to the uniformity of the battery's thermal field. The obtained... The larger the value, the greater the degree of damage caused to the battery by the uneven temperature distribution of the i-th individual cell at the current moment.

[0038] Furthermore, the small spacing between individual cells within the battery box leads to different heat transfer rates even when each cell generates the same amount of heat. Cells located in the central area have relatively poor heat dissipation conditions, which can easily cause heat accumulation and result in higher temperatures than the outer cells. This exacerbates the uneven operating temperature of the entire battery box, especially when the battery is discharging at a high rate, which increases the likelihood of thermal imbalance in the battery box.

[0039] As a preferred implementation, a thermal equilibrium failure risk value for the battery pack is constructed based on the degree of difference in thermal field non-uniformity factors among all individual cells in the battery pack at the current moment. This value characterizes the likelihood of thermal imbalance occurring in the battery pack at the current moment. The thermal equilibrium failure risk value is positively correlated with the range of thermal field non-uniformity factors among all individual cells in the battery pack at the current moment.

[0040] In this embodiment, the thermal equilibrium failure risk value of the battery box at the current moment is denoted as: Its specific expression is: In the formula, This represents the risk value of thermal equilibrium failure of the battery pack at the current moment. It is the maximum value of the thermal non-uniformity factor of all individual cells in the battery box at the current moment. It is the minimum value of the thermal non-uniformity factor of all individual cells in the battery box at the current moment. This is a preset minimum constant used to prevent the expression from being meaningless due to a zero denominator. Its value range is [0.001, 0.01], and in this embodiment, it is 0.001.

[0041] in, The larger the value, the greater the difference in thermal field uniformity between different individual cells within the battery box, and the greater the likelihood of thermal imbalance occurring within the battery box at that moment; the denominator term... Used to normalize the thermal equilibrium failure risk value. The resulting... By analyzing the differences in thermal field non-uniformity factors among all individual cells in the battery box at the current moment, the risk level of thermal imbalance in the battery box can be quantified. The larger the value, the more uneven the operating temperature of all individual cells in the battery box, the more likely the thermal balance characteristics of the battery box are to fail, resulting in inconsistent aging rates among individual cells and thus affecting the service life of the battery box.

[0042] Step 3: Based on the pre-acquired DSC curve of the composite phase change material, obtain the phase change peak temperature and phase change termination temperature of the composite phase change material; based on the temperature range of the average temperature of all temperature observation points in the battery box at the current moment, and the difference between it and the phase change peak temperature and the phase change termination temperature, construct the phase change margin coefficient.

[0043] Furthermore, adding a certain amount of expanded graphite to paraffin helps improve the heat transfer rate of the phase change material, and the phase change range will also change for composite phase change materials with different proportions of expanded graphite. Therefore, this application uses differential scanning calorimetry (DSC) to obtain the DSC curve of the composite phase change material. Specifically, 3-5 mg of paraffin / expanded graphite composite phase change material is taken, and the precisely weighed sample is placed in the DSC sample pan. The test environment is set to N2, the heating rate is set to 2℃ / min, and the test temperature range is [20℃, 60℃]. The composite phase change material will melt and absorb some heat within the test temperature range during the experiment, forming the DSC curve. The horizontal axis of the DSC curve represents temperature, and the vertical axis represents thermal power (i.e., the heat released or absorbed per unit time).

[0044] The endothermic peaks in the DSC curve correspond to the solid-liquid phase transition (melting) process of the composite phase change material. The temperature of the highest peak of the endothermic peak in the DSC curve is taken as the phase transition peak temperature of the composite phase change material. The temperature at the intersection of the leading edge tangent of the endothermic peak in the DSC curve and the baseline is taken as the phase transition initiation temperature of the composite phase change material. The temperature at the intersection of the trailing edge tangent of the endothermic peak in the DSC curve and the baseline is taken as the phase transition termination temperature of the composite phase change material. The leading edge tangent of the endothermic peak refers to the tangent at the point where the absolute value of the slope is the largest along the rising edge of the endothermic peak in the DSC curve, and the trailing edge tangent refers to the tangent at the point where the absolute value of the slope is the largest along the falling edge of the endothermic peak in the DSC curve.

[0045] If the operating temperature of the battery charging and discharging inside the battery box reaches the phase change initiation temperature of the composite phase change material, the composite phase change material just begins to absorb heat and melt, undergoing a solid-liquid phase change. If the operating temperature of the battery charging and discharging inside the battery box reaches the phase change peak temperature of the composite phase change material, the battery in the battery box has the largest heat absorption rate and the fastest phase change rate. If the operating temperature of the battery charging and discharging inside the battery box reaches the phase change termination temperature of the composite phase change material, the composite phase change material ends the heat absorption and melting process of the solid-liquid phase change, the cooling margin of the composite phase change material has been fully utilized, and it is difficult to provide phase change cooling for the battery box in the future.

[0046] As a preferred embodiment, a phase change margin coefficient is constructed based on the temperature range of the average temperature of all temperature observation points in the battery box at the current moment, and the difference between it and the phase change peak temperature and the phase change termination temperature. This coefficient is used to characterize the possibility that the composite phase change material in the battery box does not have cooling capacity at the current moment.

[0047] In this embodiment, the phase transition margin coefficient of the battery box at the current moment is denoted as... Its specific expression is: In the formula, This represents the phase transition margin coefficient of the battery pack at the current moment. It is the average temperature of all temperature observation points inside the battery box at the current moment; It is the peak phase transition temperature of the composite phase change material; is the phase transition termination temperature of the composite phase change material; exp() is an exponential function with the natural constant e as the base.

[0048] like When the overall temperature of the battery pack is below the peak phase change temperature (phase change margin limit), most of the composite phase change material is in a solid state or just beginning to melt, and the latent heat energy storage is not fully activated. At this point, the closer the average temperature inside the battery pack is to the peak phase change temperature, the stronger the heat absorption capacity of the composite phase change material. Therefore, the cooling margin of the composite phase change material can better meet the battery temperature cooling requirements, and there is less need to activate the liquid cooling cycle. The smaller the value, the stronger the cooling ability of the composite phase change material.

[0049] like The overall temperature of the battery pack is higher than the peak phase change temperature (phase change margin limit), which is within the temperature range where the latent heat of the composite phase change material is fully utilized. The composite phase change material continuously undergoes solid-liquid phase transition, which is the main operating range desired in the design. The numerical transformation shows a linear trend. Tend to At that time, that is A value approaching 2 indicates that the phase change process is nearing its end, latent heat is about to be exhausted, and the cooling margin of the composite phase change material is decreasing. Therefore, liquid cooling circulation should be activated as an auxiliary cooling method to reduce the temperature inside the battery pack. The higher the value, the weaker the ability of the composite phase change material to cool down.

[0050] like When the battery box temperature exceeds the phase change termination temperature, the composite phase change material is in a temperature range where its latent heat is completely consumed and its latent heat energy storage is fully utilized. However, the cooling margin of the composite phase change material is extremely low, resulting in the loss of the battery box's cooling capacity. At this point, the calculated phase change margin coefficient is nonlinearly amplified using an exponential function to prevent thermal runaway and safety issues caused by the battery box. Therefore, it is crucial to activate the liquid cooling circulation system as the primary cooling method to increase the heat exchange rate of the battery box and ensure that heat is removed promptly. The higher the value, the weaker the ability of the composite phase change material to cool down, and the more necessary it is to activate the liquid cooling cycle to cool the battery box.

[0051] In summary, the results are as follows: The larger the value, the weaker the ability of the composite phase change material in the battery box to provide auxiliary cooling at the current moment, and the more necessary it is to activate the liquid cooling cycle to cool the battery box.

[0052] Step 4: Based on the actual state of the liquid cooling circulation system of the battery box at each moment within a preset historical period, obtain the tag for each moment, and combine the thermal equilibrium failure risk value, the phase transition margin coefficient, and the average temperature change rate at all moments to obtain a classification model, thereby obtaining the tag of the battery box at the current moment, and then determining whether the liquid cooling circulation system needs to be turned on at the current moment.

[0053] Furthermore, this application collects operational data of the battery box under diverse operating conditions (different ambient temperatures, different charge / discharge rates) within a preset historical period. In this embodiment, the preset historical period is 10 hours. The thermal equilibrium failure risk value, phase transition margin coefficient, and average temperature change rate of the battery box at each moment within the preset historical period are calculated to form the feature vector for each moment. The average temperature change rate of the battery box at each moment refers to the average of the temperature change rates at all temperature observation points at each moment. Based on the actual operating state of the liquid cooling circulation system at each moment within the preset historical period, corresponding labels are assigned to each moment: when the liquid cooling circulation system of the battery box is not turned on at any moment within the preset historical period, the label for that moment is "not turned on"; otherwise, the label for that moment is "on". The feature vectors and their corresponding labels for all moments within the preset historical period are used as input to the classification model to train the model, resulting in a trained classification model. In this embodiment, the classification model uses a Support Vector Machine (SVM) model with a Gaussian kernel and a penalty coefficient of 1.0. The model training process is a well-known technique, and the specific process will not be described in detail.

[0054] Furthermore, the feature vector composed of the battery box's thermal equilibrium failure risk value, phase transition margin coefficient, and average temperature change rate at the current moment is used as the input to the trained classification model, and the label at the current moment is output.

[0055] The liquid cooling circulation system for the battery box is controlled based on the current label: if the label for the battery box is "not on" at the current moment, it means that the cooling margin of the composite phase change material can meet the battery temperature regulation requirements at the current moment, and there is no need to turn on the liquid cooling circulation system; if the label for the battery box is "on" at the current moment, it means that the cooling margin of the composite phase change material cannot meet the battery temperature regulation requirements at the current moment, and the liquid cooling circulation system needs to be turned on to assist the composite phase change material in cooling and regulating the battery box, so that the battery box is in the best working state.

[0056] When the battery box is in operation, the composite phase change material can effectively control the battery temperature rise in a short period of time. However, once the heat absorbed exceeds its capacity, it will lose its cooling capacity, causing the temperature inside the battery box to rise and even leading to a safety accident. The method described in this application enables the liquid cooling circulation system to be activated promptly when the cooling capacity of the composite phase change material weakens or fails, dissipating heat and ensuring that the battery box maintains effective temperature regulation capabilities regardless of whether it is used cyclically or under high load.

[0057] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0058] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0059] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them; modifications to the technical solutions described in the foregoing embodiments, or equivalent substitutions of some of the technical features, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A liquid cooling cycle control method for an electric vehicle power battery pack, characterized in that, The method includes the following steps: Several temperature observation points are set on the surface of each individual battery cell inside the battery box, and the temperature of each temperature observation point is acquired in real time. Based on the temperature difference of all temperature observation points of each individual cell at the current moment, as well as the duration of high temperature and the degree of temperature dispersion of each individual cell during the observation period at the current moment, a thermal field non-uniformity factor of each individual cell at the current moment is constructed; based on the difference between the thermal field non-uniformity factors of all individual cells in the battery box at the current moment, a thermal equilibrium failure risk value is constructed to characterize the possibility of thermal imbalance risk in the battery box at the current moment. The peak phase change temperature and the termination phase change temperature of the composite phase change material are obtained based on the pre-acquired DSC curve of the composite phase change material; the phase change margin coefficient is constructed based on the temperature range of the average temperature of all temperature observation points in the battery box at the current moment, and the difference between it and the peak phase change temperature and the termination phase change temperature. Based on the actual state of the liquid cooling circulation system of the battery box at each moment within a preset historical period, the label of each moment is obtained. Combined with the thermal equilibrium failure risk value, phase transition margin coefficient, and average temperature change rate at all moments, a classification model is obtained to obtain the label of the battery box at the current moment, and then it is determined whether the liquid cooling circulation system needs to be turned on at the current moment.

2. The liquid cooling cycle control method for an electric vehicle power battery box as described in claim 1, characterized in that, The specific process of setting several temperature observation points on the surface of each individual battery cell inside the battery box is as follows: Obtain the temperature cloud map of the battery box at the end of discharge without opening the liquid cooling pipes, and take the positions corresponding to the maximum and minimum surface temperatures of each individual cell in the obtained temperature cloud map as the first type of observation points; Obtain the temperature cloud map of the battery box with the liquid cooling pipes turned on at the end of discharge, and take the positions corresponding to the maximum and minimum surface temperatures of each individual cell in the obtained temperature cloud map as the second type of observation points. The locations of the nearest individual battery cells on both sides of each liquid cooling pipe are used as the third type of observation points; All observation points in the union of the first, second, and third types of observation points are used as the temperature observation points of the battery box.

3. The liquid cooling cycle control method for an electric vehicle power battery box as described in claim 1, characterized in that, The process of constructing the thermal field non-uniformity factor of each individual cell at the current moment is as follows: Calculate the difference between the highest and lowest temperature values ​​of each individual cell at all temperature observation points at the current moment; The temperatures of all temperature observation points of each individual cell at each time point within the current observation period are counted. The temperature observation points corresponding to the highest temperature at each time point are selected. The number of times each temperature observation point of each individual cell reaches the highest temperature within the current observation period is recorded as the high temperature indicator value of each temperature observation point. Calculate the variance of the temperature values ​​of each individual cell at all temperature observation points at each time, and calculate the mean of the variance of each individual cell at all times within the observation period at the current time. The thermal field non-uniformity factor is positively correlated with the difference, the mean, and the maximum value among the high temperature identification values ​​of all temperature observation points.

4. The liquid cooling cycle control method for an electric vehicle power battery box as described in claim 1, characterized in that, The thermal equilibrium failure risk value is positively correlated with the range of thermal field non-uniformity factors of all individual cells in the battery box at the current moment.

5. The liquid cooling cycle control method for an electric vehicle power battery box as described in claim 1, characterized in that, The phase transition peak temperature refers to the temperature of the highest peak point of the endothermic peak in the DSC curve; the phase transition termination temperature refers to the temperature at the intersection of the trailing tangent of the endothermic peak in the DSC curve and the baseline; wherein, the trailing tangent of the endothermic peak refers to the tangent at the point where the absolute value of the slope is the largest in the descending edge of the endothermic peak of the DSC curve.

6. The liquid cooling cycle control method for an electric vehicle power battery box as described in claim 1, characterized in that, The formula for calculating the phase transition margin coefficient is as follows: In the formula, This represents the phase transition margin coefficient of the battery pack at the current moment. It is the average temperature of all temperature observation points inside the battery box at the current moment; It is the peak phase transition temperature of the composite phase change material; is the phase transition termination temperature of the composite phase change material; exp() is an exponential function with the natural constant e as the base.

7. The liquid cooling cycle control method for an electric vehicle power battery box as described in claim 1, characterized in that, The method for obtaining the tags at each moment is as follows: when the liquid cooling circulation system of the battery box is not turned on at any moment within a preset historical period, the tag for that moment is set to "not turned on"; otherwise, the tag for that moment is set to "turned on".

8. The liquid cooling cycle control method for an electric vehicle power battery box as described in claim 1, characterized in that, The process of obtaining the classification model is as follows: the thermal equilibrium failure risk value, phase transition margin coefficient, and average temperature change rate at each time point are used to form the feature vector at each time point; the feature vectors of all times within a preset historical period and their corresponding labels are used as the input of the classification model to train the model and obtain the trained classification model.

9. The liquid cooling cycle control method for an electric vehicle power battery box as described in claim 8, characterized in that, The method for obtaining the label of the battery box at the current moment is as follows: use the feature vector of the battery box at the current moment as the input of the trained classification model, and output the label at the current moment.

10. The liquid cooling cycle control method for an electric vehicle power battery box as described in claim 7, characterized in that, The specific process for determining whether the liquid cooling circulation system needs to be activated at the current moment is as follows: If the battery compartment is currently labeled "Not Open", then there is no need to turn on the liquid cooling circulation system. If the battery compartment is currently labeled "On", then the liquid cooling circulation system needs to be turned on.

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