Monitoring method of battery thermal management system, battery management system and electric vehicle

Abstract

The present invention relates to a monitoring method for a battery thermal management system, a battery management system, and an electric vehicle. The monitoring method for the battery thermal management system comprises: obtaining a real-time heat transfer coefficient value between a power battery and a cooling device under predetermined operating conditions; obtaining a reference heat transfer coefficient value and a corresponding first heat transfer coefficient deviation threshold between the power battery and the cooling device under predetermined operating conditions; calculating the difference between the real-time heat transfer coefficient value and the reference heat transfer coefficient value; comparing the absolute value of the difference with the first heat transfer coefficient deviation threshold; and determining whether the battery thermal management system is in an abnormal state based on the comparison result. The monitoring method can not only monitor the state of the battery thermal management system in real time and detect abnormalities in the battery thermal management system in a timely manner, but also realize quantitative monitoring of the battery thermal management system to capture instantaneous or chronic changes in thermal management performance, thereby providing early warnings and effectively avoiding safety hazards and energy waste.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicles, and more particularly to a monitoring method for a battery thermal management system, a battery management system, and an electric vehicle. Background Art

[0002] Electric vehicles, with their energy-saving and environmentally friendly advantages, are an inevitable trend in future automotive development. Power batteries, as energy storage devices, primarily provide the driving power required for electric vehicles. They are the most critical core component of electric vehicles, and their performance directly determines the safety, reliability, and cost of electric vehicles.

[0003] Thermal issues with power batteries, such as heat accumulation during operation, temperature imbalances between individual battery cells during operation, and degradation or even malfunction of battery performance under harsh and complex operating conditions, can affect the performance and lifespan of electric vehicles. A battery thermal management system (BTMS) is used to manage thermal issues or thermal conditions in power batteries. Specifically, it is a complete system that optimizes the electrochemical performance of power batteries by analyzing the current operating conditions (including environmental conditions and vehicle power requirements) to ensure that the battery pack operates within the optimal temperature range. The main functions of the BTMS include: accurate measurement and monitoring of battery temperature, effective heat dissipation and ventilation when battery temperature is too high, rapid heating of batteries under low temperature conditions, effective ventilation of batteries when harmful gases are generated, and uniform distribution of the battery pack temperature field.

[0004] Currently, existing technologies are unable to promptly detect abnormalities in the BTMS status, nor provide early warning of transient or chronic thermal performance degradation. This can directly impact the safety, charge and discharge capacity, efficiency, cycle life, and other performance of the power battery, ultimately affecting the performance and safety of the entire vehicle.

[0005] Accordingly, this field requires a new technical solution to solve the above problems. Summary of the Invention

[0006] In order to solve the above-mentioned technical problems in the prior art, that is, to solve the technical problems in the prior art that the abnormality of the battery thermal management system cannot be detected in time and the instantaneous or chronic thermal performance degradation change thereof cannot be warned in advance, the present invention provides a monitoring method for the battery thermal management system, the monitoring method comprising:

[0007] Obtaining the real-time heat transfer coefficient value between the power battery and the cooling device under predetermined operating conditions;

[0008] Obtaining a reference heat transfer coefficient value and a corresponding first heat transfer coefficient deviation threshold between the power battery and the cooling device under the predetermined operating condition;

[0009] Calculating the difference between the real-time heat transfer coefficient value and the reference heat transfer coefficient value;

[0010] comparing the absolute value of the difference with the first heat transfer coefficient deviation threshold;

[0011] It is determined whether the battery thermal management system is in an abnormal state based on the comparison result.

[0012] The heat transfer coefficient of a battery thermal management system (BTM) can reflect the overall thermal performance of the BTM. For example, situations such as impacts on the bottom of the BTM, pipe blockage, dirt accumulation, or cold plate deformation can cause real-time changes in the heat transfer coefficient. Therefore, to monitor the status of the BTM in real time, the monitoring method first obtains the real-time heat transfer coefficient between the power battery and the cooling device under predetermined operating conditions, a reference heat transfer coefficient value under the same operating conditions, and a corresponding first heat transfer coefficient deviation threshold. The method then calculates the difference between the real-time heat transfer coefficient and the reference heat transfer coefficient value, compares the absolute value of this difference with the corresponding first heat transfer coefficient deviation threshold, and finally, based on the comparison result, determines whether the BTM is in an abnormal state. The real-time heat transfer coefficient between the battery and the cooling device under predetermined operating conditions can reflect the real-time thermal performance of the BTM under those conditions. The corresponding reference heat transfer coefficient value is the actual heat transfer coefficient value measured experimentally under those conditions, reflecting the ideal state of the BTM under those conditions. The difference between the real-time heat transfer coefficient under those conditions and the corresponding reference heat transfer coefficient value is the heat transfer coefficient deviation value for those conditions. By comparing the heat transfer coefficient deviation value with the corresponding first heat transfer coefficient deviation threshold, it is possible to determine whether the battery thermal management system is in an abnormal state. Abnormal conditions include but are not limited to the bottom of the battery thermal management system being bumped, the pipe being blocked, the dirt accumulation on the surface, or the cold plate being deformed. By continuously obtaining the real-time heat transfer coefficient and performing corresponding comparisons through the above method, the present invention realizes real-time quantitative monitoring of the battery thermal management system, which can not only promptly detect abnormal conditions of the battery thermal management system, but also monitor the changes in chronic or transient thermal performance degradation caused by the above abnormal conditions, so as to issue early warnings, thereby ensuring the safety and good performance of the power battery.

[0013] In the preferred technical solution of the above-mentioned method for monitoring the battery thermal management system, the step of determining whether the battery thermal management system is in an abnormal state based on the comparison result includes:

[0014] When the absolute value of the difference is less than or equal to the first heat transfer coefficient deviation threshold, determining that the battery thermal management system is in a normal state;

[0015] When the absolute value of the difference exceeds the first heat transfer coefficient deviation threshold, the battery thermal management system is determined to be in an abnormal state and an abnormality alert is issued. The first heat transfer coefficient deviation threshold represents the maximum value by which the battery thermal management system can deviate from the reference heat transfer coefficient value under normal conditions. Therefore, when the absolute value of the difference between the real-time heat transfer coefficient value and the reference heat transfer coefficient value exceeds the first heat transfer coefficient deviation threshold, it indicates that the battery thermal management system is in an abnormal state, and an abnormality alert may be issued.

[0016] In the preferred technical solution of the above-mentioned method for monitoring the battery thermal management system, when it is determined that the battery thermal management system is in an abnormal state, the monitoring method further includes:

[0017] Obtaining a second heat transfer coefficient deviation threshold corresponding to the predetermined operating condition, wherein the second heat transfer coefficient deviation threshold is greater than the first heat transfer coefficient deviation threshold;

[0018] comparing the absolute value of the difference with the second heat transfer coefficient deviation threshold;

[0019] When the absolute value of the difference is less than or equal to the second heat transfer coefficient deviation threshold, uploading the real-time parameters of the battery thermal management system corresponding to the predetermined operating condition to a cloud monitoring system;

[0020] When the absolute value of the difference is greater than the second heat transfer coefficient deviation threshold, an alarm is issued to the passengers. The second heat transfer coefficient deviation threshold is greater than the first heat transfer coefficient deviation threshold. When the absolute value of the above difference is greater than the second heat transfer coefficient deviation threshold, it means that the abnormal state of the battery thermal management system is relatively serious, so it is necessary to immediately remind the passengers in the vehicle to pay attention to this problem to avoid danger. When the absolute value of the above difference is less than or equal to the second heat transfer coefficient deviation threshold, it means that although the battery thermal management system is in an abnormal state, this abnormal state will not cause immediate danger, so it is only necessary to upload the abnormal state to the cloud monitoring system for further analysis and confirmation by the cloud monitoring system to provide accurate guidance for further response measures. Through a cloud monitoring system, such as a cloud monitoring system provided by a third party or a cloud monitoring system provided by a car manufacturer, it can help car manufacturers or other monitoring parties to scientifically capture battery packs with degraded thermal management performance.

[0021] In the preferred technical solution of the above-mentioned method for monitoring the battery thermal management system, uploading the real-time parameters of the battery thermal management system corresponding to the predetermined operating condition to the cloud monitoring system includes:

[0022] The battery pack temperature, coolant inlet and outlet temperatures, and coolant mass flow rate under the predetermined operating conditions are uploaded to the monitoring system. By uploading all of this parameter information to the cloud monitoring system, these parameters related to the battery thermal management system can help automakers or other monitoring parties scientifically identify battery packs with degraded thermal management performance.

[0023] In the preferred technical solution of the battery thermal management system monitoring method, the reference heat transfer coefficient value is obtained by looking up the pre-collected reference heat transfer coefficient table, so that the reference heat transfer coefficient value under the corresponding working condition can be obtained conveniently and quickly.

[0024] In the preferred technical solution of the battery thermal management system monitoring method, the lookup table is determined through experimental measurements. The lookup table is a table of normal heat transfer coefficient ranges, pre-determined through experimental measurements of corresponding batteries. It includes normal heat transfer coefficient values corresponding to different operating conditions and cooling states. This lookup table provides a more accurate reference heat transfer coefficient value.

[0025] In the preferred technical solution of the above-mentioned battery thermal management system monitoring method, the first and second heat transfer coefficient deviation thresholds are both selected based on variations in the reference heat transfer coefficient value across different regions and / or seasons. Variations in the reference heat transfer coefficient value across different regions and / or seasons can be obtained through big data analysis. Therefore, the first and second heat transfer coefficient deviation thresholds selected based on variations in the reference heat transfer coefficient value across different regions and / or seasons are more accurate.

[0026] In the preferred technical solution of the above-mentioned battery thermal management method, the step of obtaining the real-time heat transfer coefficient value between the power battery and the cooling device under predetermined operating conditions includes:

[0027] Collecting the battery pack temperature, the coolant inlet temperature and outlet temperature, and the coolant mass flow rate under the predetermined operating conditions;

[0028] The real-time heat transfer coefficient value is calculated based on the battery pack temperature, the inlet temperature, the outlet temperature, and the mass flow rate. These real-time parameters are all related to the heat transfer coefficient, and thus a real-time heat transfer coefficient value that conforms to reality can be calculated based on these real-time parameters.

[0029] In the preferred technical solution of the above-mentioned method for monitoring the battery thermal management system, the step of obtaining the real-time heat transfer coefficient value between the power battery and the cooling device under predetermined operating conditions further includes:

[0030] Collecting the battery pack temperature, the coolant inlet temperature and the coolant outlet temperature, and the coolant mass flow rate under the predetermined operating conditions multiple times at a predetermined frequency within a predetermined time period;

[0031] Calculate the corresponding real-time heat transfer coefficient value based on the battery pack temperature, the inlet temperature, the outlet temperature, and the mass flow rate collected each time; and

[0032] The average real-time heat transfer coefficient value of all the real-time heat transfer coefficient values is calculated. Calculating the average real-time heat transfer coefficient value over a predetermined time period effectively filters out abnormal real-time heat transfer coefficient values that are excessively large or small due to transient impacts. Based on this average real-time heat transfer coefficient value, the true state of the battery thermal management system over the predetermined time period can be more accurately determined, avoiding misjudgments and false alarms regarding the state of the battery thermal management system.

[0033] In the preferred technical solution of the above-mentioned monitoring method of the battery thermal management system, the real-time heat transfer coefficient value is calculated using the following formula:

[0034]

[0035] Among them, K is the real-time heat transfer coefficient value, T out is the outlet temperature of the coolant, T in is the inlet temperature of the coolant, T cell is the battery pack temperature, m is the coolant mass flow rate, c is the specific heat capacity of the coolant, and A is the contact area between the battery pack and the cooling device. Using the above formula, the real-time heat transfer coefficient value can be accurately obtained.

[0036] To address the aforementioned technical problems in the prior art, namely, the inability to promptly detect abnormalities in the battery thermal management system and provide early warnings for transient or chronic thermal performance degradation, the present invention further provides a battery management system that monitors the status of the battery thermal management system in real time by employing any of the above-described battery thermal management system monitoring methods. By employing any of the above-described battery thermal management system monitoring methods, the status of the battery thermal management system can be observed in real time, abnormalities in the status can be promptly detected, and early warnings for transient or chronic performance degradation can be provided, thereby effectively avoiding safety hazards and energy waste.

[0037] To address the existing issues of being unable to promptly detect battery thermal management system anomalies and provide early warning of transient or chronic thermal performance degradation, the present invention further provides an electric vehicle comprising: a battery management system as described above, configured to monitor the status of the battery thermal management system in real time. This battery management system not only ensures the safety, charge and discharge capacity, efficiency, and cycle life of the power battery, but also improves the performance and safety of the entire vehicle.

[0038] Solution 1. A method for monitoring a battery thermal management system, characterized in that the monitoring method comprises:

[0039] Obtaining the real-time heat transfer coefficient value between the power battery and the cooling device under predetermined operating conditions;

[0040] Obtaining a reference heat transfer coefficient value and a corresponding first heat transfer coefficient deviation threshold between the power battery and the cooling device under the predetermined operating condition;

[0041] Calculating the difference between the real-time heat transfer coefficient value and the reference heat transfer coefficient value;

[0042] comparing the absolute value of the difference with the first heat transfer coefficient deviation threshold;

[0043] It is determined whether the battery thermal management system is in an abnormal state based on the comparison result.

[0044] Solution 2. The method for monitoring a battery thermal management system according to Solution 1, wherein the step of determining whether the battery thermal management system is in an abnormal state based on the comparison result comprises:

[0045] When the absolute value of the difference is less than or equal to the first heat transfer coefficient deviation threshold, determining that the battery thermal management system is in a normal state;

[0046] When the absolute value of the difference is greater than the first heat transfer coefficient deviation threshold, it is determined that the battery thermal management system is in an abnormal state, and an abnormality reminder is issued.

[0047] Solution 3. The method for monitoring a battery thermal management system according to Solution 2, wherein when it is determined that the battery thermal management system is in an abnormal state, the monitoring method further comprises:

[0048] Obtaining a second heat transfer coefficient deviation threshold corresponding to the predetermined operating condition, wherein the second heat transfer coefficient deviation threshold is greater than the first heat transfer coefficient deviation threshold;

[0049] comparing the absolute value of the difference with the second heat transfer coefficient deviation threshold;

[0050] When the absolute value of the difference is less than or equal to the second heat transfer coefficient deviation threshold, uploading the real-time parameters of the battery thermal management system corresponding to the predetermined operating condition to a cloud monitoring system;

[0051] When the absolute value of the difference is greater than the second heat transfer coefficient deviation threshold, an alarm is issued to the passenger.

[0052] Solution 4. The method for monitoring a battery thermal management system according to Solution 3, wherein uploading the real-time parameters of the battery thermal management system corresponding to the predetermined operating condition to the cloud monitoring system comprises:

[0053] The battery pack temperature, the coolant inlet temperature and outlet temperature, and the coolant mass flow rate under the predetermined operating conditions are uploaded to the cloud monitoring system.

[0054] Solution 5. The method for monitoring a battery thermal management system according to Solution 3 is characterized in that the reference heat transfer coefficient value is obtained by a lookup table.

[0055] Solution 6. The method for monitoring a battery thermal management system according to Solution 5 is characterized in that the lookup table is determined through experimental measurements.

[0056] Option 7. The monitoring method for a battery thermal management system according to Option 3 is characterized in that the first heat transfer coefficient deviation threshold and the second heat transfer coefficient deviation threshold are both selected based on changes in the reference heat transfer coefficient value in different regions and / or different seasons.

[0057] Solution 8. The method for monitoring a battery thermal management system according to Solution 1, wherein the step of obtaining a real-time heat transfer coefficient value between the power battery and the cooling device under predetermined operating conditions comprises:

[0058] Collecting the battery pack temperature, the coolant inlet temperature and outlet temperature, and the coolant mass flow rate under the predetermined operating conditions;

[0059] The real-time heat transfer coefficient value is calculated based on the battery pack temperature, the inlet temperature, the outlet temperature, and the mass flow rate.

[0060] Solution 9. The method for monitoring a battery thermal management system according to Solution 1, wherein the step of obtaining a real-time heat transfer coefficient value between the power battery and the cooling device under predetermined operating conditions further comprises:

[0061] Collecting the battery pack temperature, the coolant inlet temperature and the coolant outlet temperature, and the coolant mass flow rate under the predetermined operating conditions multiple times at a predetermined frequency within a predetermined time period;

[0062] Calculate the corresponding real-time heat transfer coefficient value based on the battery pack temperature, the inlet temperature, the outlet temperature, and the mass flow rate collected each time; and

[0063] An average real-time heat transfer coefficient value of all said real-time heat transfer coefficient values is calculated.

[0064] Solution 10. The method for monitoring a battery thermal management system according to Solution 8 or 9, wherein the real-time heat transfer coefficient value is calculated using the following formula:

[0065]

[0066] Among them, K is the real-time heat transfer coefficient value, T out is the outlet temperature of the coolant, T in is the inlet temperature of the coolant, T cell is the battery pack temperature, m is the coolant mass flow rate, c is the specific heat capacity of the coolant, and A is the contact area between the battery pack and the cooling device.

[0067] Solution 11. A battery management system, characterized in that the battery management system adopts the monitoring method of the battery thermal management system according to any one of Solutions 1-10 to monitor the status of the battery thermal management system in real time.

[0068] Solution 12. An electric vehicle, characterized in that the electric vehicle comprises:

[0069] According to the battery management system described in Solution 11, the battery management system is used to monitor the status of the battery thermal management system in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The preferred embodiments of the present invention are described below with reference to the accompanying drawings, in which:

[0071] Figure 1 is a flow chart of a monitoring method for a battery thermal management system of the present invention;

[0072] Figure 2 is a flow chart of a first embodiment of a monitoring method for a battery thermal management system of the present invention;

[0073] Figure 3 This is a flow chart of an embodiment of a method for monitoring a battery thermal management system of the present invention to obtain a real-time heat transfer coefficient value;

[0074] Figure 4 4 is a flow chart of a second embodiment of a monitoring method for a battery thermal management system according to the present invention. DETAILED DESCRIPTION

[0075] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0076] In order to solve the technical problems in the prior art of being unable to timely detect abnormalities in the battery thermal management system and unable to provide early warning of its instantaneous or chronic thermal performance degradation changes, the present invention provides a monitoring method for the battery thermal management system, which includes:

[0077] Obtaining a real-time heat transfer coefficient value between the power battery and the cooling device under predetermined operating conditions (step S1);

[0078] Obtaining a reference heat transfer coefficient value and a corresponding first heat transfer coefficient deviation threshold between the power battery and the cooling device under the predetermined operating condition (step S2);

[0079] Calculating the difference between the real-time heat transfer coefficient value and the reference heat transfer coefficient value (step S3);

[0080] comparing the absolute value of the difference with the first heat transfer coefficient deviation threshold (step S4);

[0081] It is determined whether the battery thermal management system is in an abnormal state based on the comparison result (step S5).

[0082] The battery thermal management system is mainly used for heat dissipation, preheating, and temperature equalization of power batteries. Therefore, the normal operation of the battery thermal management system is crucial to ensuring the safety and performance of power batteries. The battery thermal management system includes but is not limited to a liquid cooling system or a direct cooling system. The coolant or refrigerant used in the battery thermal management system exchanges heat with the power battery through a cooling device. The coolant includes but is not limited to water, ethanol, mineral oil, or acetone. In one or more embodiments, the cooling device is a liquid cooling plate, such as a plate-shaped aluminum device. Alternatively, the cooling device may also be other suitable structures suitable for direct contact with the battery.

[0083] In this article, both the real-time heat transfer coefficient and the reference heat transfer coefficient refer to the amount of heat transferred per unit area per unit time when the temperature difference between the coolant and the battery is 1°C. In this article, power batteries include but are not limited to lithium-ion batteries, nickel-metal hydride batteries, fuel cells, lead-acid batteries, or sodium-sulfur batteries. In this article, predetermined operating conditions for power batteries include but are not limited to the charge and discharge power and coolant flow rate of the power battery.

[0084] Figure 1 FIG. 1 is a flow chart of a method for monitoring a battery thermal management system according to the present invention. Figure 1 As shown, after the battery thermal management system monitoring method is started, step S1 is first performed, that is, obtaining the real-time heat transfer coefficient value between the power battery and the cooling device under a predetermined working condition.

[0085] The power battery is generally equipped with a cell temperature sensor, a coolant liquid path temperature sensor, and a coolant level sensor, which can be used to collect the real-time battery pack temperature, the real-time coolant inlet temperature and outlet temperature, and the real-time coolant mass flow rate under the corresponding operating conditions. In one or more embodiments, the real-time battery pack temperature, the real-time coolant inlet temperature and outlet temperature, and the real-time coolant mass flow rate collected under the corresponding operating conditions of the power battery are used to calculate the real-time heat transfer coefficient value K. The real-time heat transfer coefficient value K can be calculated using the following formula:

[0086]

[0087] Among them, K is the real-time heat transfer coefficient value, T out is the outlet temperature of the coolant, T in is the inlet temperature of the coolant, T cell is the battery pack temperature, m is the mass flow rate of the coolant, c is the specific heat capacity of the coolant, and A is the contact area between the battery pack and the cooling device. The specific heat capacity of the coolant can be obtained by looking up the physical property table of the coolant. The physical property table of the coolant includes but is not limited to parameters such as heat capacity, dynamic viscosity, thermal conductivity, etc. These parameters will change accordingly with changes in temperature. In one or more embodiments, the real-time battery pack temperature T cell is the average battery pack temperature. out -T in )” is the heat taken away by the coolant per unit time, “T cell -(T out -T in ) / 2” is the temperature difference between the battery pack and the coolant.

[0088] like Figure 1 As shown, after executing step S1, the monitoring method of the battery thermal management system then executes step S2 to obtain a reference heat transfer coefficient value and a corresponding first heat transfer coefficient deviation threshold between the power battery and the cooling device under a predetermined operating condition.

[0089] In one or more embodiments, the reference heat transfer coefficient value K' is obtained by looking up the heat transfer coefficient corresponding to the predetermined operating condition from a pre-configured lookup table. The lookup table is imported or stored in the battery management system (BMS) of the power battery. The reference heat transfer coefficient values corresponding to different operating conditions in the lookup table (also called "normal heat transfer coefficient values") are all obtained through experimental measurements. Furthermore, based on all the previously collected heat transfer coefficient values, big data analysis can be performed to obtain the distribution or changes of the heat transfer coefficient in different regions and / or different seasons. The first heat transfer coefficient deviation threshold a1 is selected based on the changes in the obtained heat transfer coefficient in different regions and / or different seasons. Due to changes in seasons and / or geographical areas, under the same operating conditions, the normal heat transfer coefficient value will also change. Therefore, the first heat transfer coefficient deviation threshold a1 determined in the above manner is more accurate. The first heat transfer coefficient deviation threshold may be included in the lookup table of the reference heat transfer coefficient.

[0090] like Figure 1 As shown, after obtaining the real-time heat transfer coefficient value, the reference heat transfer coefficient value, and the corresponding first heat transfer coefficient deviation threshold a1, the monitoring method for the battery thermal management system proceeds to step S3, calculating the difference between the real-time heat transfer coefficient value K and the reference heat transfer coefficient value K' to obtain the heat transfer coefficient deviation value under predetermined operating conditions, namely, K-K'. The monitoring method then proceeds to step S4, comparing the absolute value of the difference K-K' with the first heat transfer coefficient deviation threshold a1. Finally, in step S5, based on the comparison of the absolute value of the difference K-K' with the first heat transfer coefficient deviation threshold a1, it is determined whether the battery thermal management system is in an abnormal state. For example, when the absolute value of the difference K-K' is less than or equal to the first heat transfer coefficient deviation threshold a1, the battery thermal management system is determined to be in a normal state; when the absolute value of the difference K-K' is greater than the first heat transfer coefficient deviation threshold a1, the battery thermal management system is determined to be in an abnormal state. After executing step S5, the monitoring method for the battery thermal management system terminates. After a predetermined time interval, the method can be re-implemented by repeating step S1.

[0091] By continuously implementing the above-mentioned battery thermal management system monitoring method and monitoring the battery thermal management system's status in real time, the operating status and efficiency changes of the battery thermal management system can be detected. For example, abnormal conditions such as the battery thermal management system's bottom being bumped, pipes being blocked, dirt accumulation on the surface, or cold plate deformation can be detected. This can avoid safety hazards and energy waste caused by undetected battery thermal management system failures. Furthermore, the heat transfer coefficient deviation calculated based on big data obtained by the big data monitoring device for the battery thermal management system status can provide data support for thermal management system fault diagnosis.

[0092] Figure 24 is a flow chart of a first embodiment of a monitoring method for a battery thermal management system according to the present invention. Figure 3 FIG. 1 is a flow chart of an embodiment of a method for monitoring a battery thermal management system of the present invention to obtain a real-time heat transfer coefficient value. Figure 2 As shown, after the battery thermal management system monitoring method is started, step S1 is first performed to obtain the real-time heat transfer coefficient value between the power battery and the cooling device under predetermined operating conditions. In this embodiment, the real-time heat transfer coefficient value is the average real-time heat transfer coefficient value and is obtained as follows.

[0093] like Figure 3 As shown, within a predetermined time period, the battery pack temperature, the inlet temperature and outlet temperature of the coolant, and the mass flow rate of the coolant under predetermined working conditions are collected multiple times at a predetermined frequency (step S11). In one or more embodiments, the predetermined time period is 3 minutes, and the predetermined frequency is 3 times / minute. Alternatively, the predetermined time period and the predetermined frequency may adopt other suitable values, for example, the predetermined time period is 2 minutes or 5 minutes, and the predetermined frequency is 4 times / minute or 2 times / minute. Based on the battery pack temperature (which may be the average battery pack temperature), the inlet temperature and outlet temperature of the coolant, and the mass flow rate of the coolant collected each time, the corresponding real-time heat transfer coefficient value is calculated (step S12). The above formula may be used to calculate the corresponding real-time heat transfer coefficient value. Finally, the average real-time heat transfer coefficient value of all real-time heat transfer coefficient values is calculated (S13). By calculating the average value of the real-time heat transfer coefficient, false alarms caused by instantaneous impacts on the battery thermal management system can be filtered out, the accuracy of the calculation results can be determined, and the accuracy of the judgment results can be improved.

[0094] Continue to refer Figure 2After obtaining the average real-time heat transfer coefficient value, the monitoring method proceeds to step S2 to obtain a reference heat transfer coefficient value and a corresponding first heat transfer coefficient deviation threshold between the power battery and the cooling device under predetermined operating conditions. The reference heat transfer coefficient value and the corresponding first heat transfer coefficient deviation threshold can be obtained in the same manner as described in step S2. The monitoring method then proceeds to step S3 to calculate the difference between the real-time heat transfer coefficient value and the reference heat transfer coefficient value, i.e., the difference between the average real-time heat transfer coefficient value and the reference heat transfer coefficient value. The monitoring method then proceeds to step S41 to compare the absolute value of this difference with the first heat transfer coefficient deviation threshold. If this absolute value is greater than the first heat transfer coefficient deviation threshold, it indicates that the deviation of the real-time heat transfer coefficient value from the reference heat transfer coefficient value under these operating conditions has exceeded the normal range. Therefore, the battery thermal management system monitoring method proceeds to step S51 to determine that the battery thermal management system is in an abnormal state and issue an abnormality alert, such as sending an abnormality alert message to the user, the vehicle manufacturer, or another agreed third party, indicating that the battery thermal management system has an abnormal condition. After step S51 is completed, the battery thermal management system monitoring method terminates. If the absolute value is less than or equal to the first heat transfer coefficient deviation threshold, indicating that the heat transfer coefficient deviation under the current operating condition is within the normal range, the monitoring method proceeds to step S52 to determine that the battery thermal management system is in a normal state. After step S52 is completed, the battery thermal management system monitoring method terminates. After a predetermined time interval, the method can be re-implemented by repeating step S1.

[0095] Figure 4 FIG. 1 is a flow chart of a second embodiment of a method for monitoring a battery thermal management system according to the present invention. Figure 4 As shown, after the battery thermal management system monitoring method is started, steps S1, S2, S3, S41, S51 and S52 are first executed. These steps are respectively the same as the corresponding steps S1, S2, S3, S41, S51 and S52 of the first embodiment described above, and are not repeated here. Alternatively, in this embodiment, in step S1, the real-time heat transfer coefficient value can be the real-time heat transfer coefficient value corresponding to a single moment, which is also obtained by the above calculation formula. When it is determined in step S51 that the battery management system is in an abnormal state, the monitoring method proceeds to step S6 to obtain a second heat transfer coefficient deviation threshold corresponding to a predetermined operating condition, wherein the second heat transfer coefficient deviation threshold is greater than the first heat transfer coefficient deviation threshold. In one or more embodiments, the second heat transfer coefficient deviation threshold is also selected based on the distribution of the obtained heat transfer coefficient in different regions and / or different seasons, and it can be included in the reference heat transfer coefficient lookup table.

[0096] like Figure 4As shown, after obtaining the second heat transfer coefficient deviation threshold, the battery thermal management system monitoring method proceeds to step S7, where the absolute value of the difference between the real-time heat transfer coefficient value and the reference heat transfer coefficient value is compared with the second heat transfer coefficient deviation threshold. When the absolute value of the difference is greater than the second heat transfer coefficient deviation threshold a2, it indicates that the real-time heat transfer coefficient deviation value deviates too significantly from the normal heat transfer coefficient under the corresponding operating conditions, and therefore the battery thermal management system is severely abnormal, potentially posing a danger to the vehicle's users or passengers. Therefore, the monitoring method proceeds to step S8, where an alarm is issued to the passengers, prompting them to immediately address the issue. When the absolute value of the difference is less than or equal to the second heat transfer coefficient deviation threshold, it indicates that the real-time heat transfer coefficient deviation value deviates only slightly from the normal heat transfer coefficient under the corresponding operating conditions, and the battery thermal management system is mildly abnormal, posing no immediate risk to the vehicle's users or passengers. In this case, the monitoring method of the battery thermal management system executes step S9, and uploads parameters such as the battery pack temperature, coolant inlet temperature and outlet temperature, and coolant mass flow rate under the working condition to the cloud monitoring system, which will be further analyzed and focused on by the car manufacturer or the agreed third party. This can help the car manufacturer or the third party to scientifically and timely capture battery packs with degraded thermal management performance.

[0097] Optionally, all parameters obtained in the above method process can be uploaded to the cloud monitoring system, including the normal state of the battery thermal management system, but not limited to the abnormal state of the battery thermal management system.

[0098] The present invention also relates to a battery management system. This battery management system uses any of the monitoring methods described above to monitor the status of a battery thermal management system in real time, enabling timely detection of thermal management system anomalies and providing early warning of transient or chronic thermal management state changes, thereby effectively avoiding safety hazards and energy waste.

[0099] The present invention also relates to an electric vehicle. This electric vehicle (not shown) can be a pure electric vehicle, a hybrid electric vehicle, or a fuel cell vehicle. This electric vehicle includes the battery management system described above. This battery management system can help automakers leverage big data to proactively identify battery packs that may be susceptible to thermal management failures. This can, in the long run, avoid safety hazards and reduce subsequent repair costs.

[0100] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A method for monitoring a battery thermal management system, characterized in that: The monitoring method comprises: Obtaining the real-time heat transfer coefficient value between the power battery and the cooling device under predetermined operating conditions; Obtaining a reference heat transfer coefficient value and a corresponding first heat transfer coefficient deviation threshold between the power battery and the cooling device under the predetermined operating condition; Calculating the difference between the real-time heat transfer coefficient value and the reference heat transfer coefficient value; comparing the absolute value of the difference with the first heat transfer coefficient deviation threshold; It is determined whether the battery thermal management system is in an abnormal state based on the comparison result.

2. The method for monitoring a battery thermal management system according to claim 1, wherein: The step of determining whether the battery thermal management system is in an abnormal state based on the comparison result includes: When the absolute value of the difference is less than or equal to the first heat transfer coefficient deviation threshold, determining that the battery thermal management system is in a normal state; When the absolute value of the difference is greater than the first heat transfer coefficient deviation threshold, it is determined that the battery thermal management system is in an abnormal state, and an abnormality reminder is issued.

3. The method for monitoring a battery thermal management system according to claim 2, wherein: When it is determined that the battery thermal management system is in an abnormal state, the monitoring method further includes: Obtaining a second heat transfer coefficient deviation threshold corresponding to the predetermined operating condition, wherein the second heat transfer coefficient deviation threshold is greater than the first heat transfer coefficient deviation threshold; comparing the absolute value of the difference with the second heat transfer coefficient deviation threshold; When the absolute value of the difference is less than or equal to the second heat transfer coefficient deviation threshold, uploading the real-time parameters of the battery thermal management system corresponding to the predetermined operating condition to a cloud monitoring system; When the absolute value of the difference is greater than the second heat transfer coefficient deviation threshold, an alarm is issued to the passenger.

4. The method for monitoring a battery thermal management system according to claim 3, wherein: Uploading the real-time parameters of the battery thermal management system corresponding to the predetermined operating condition to the cloud monitoring system includes: The battery pack temperature, the coolant inlet temperature and outlet temperature, and the coolant mass flow rate under the predetermined operating conditions are uploaded to the cloud monitoring system.

5. The method for monitoring a battery thermal management system according to claim 3, wherein: The reference heat transfer coefficient value is obtained by looking up a table.

6. The method for monitoring a battery thermal management system according to claim 5, wherein: The lookup table is determined through experimental measurement.

7. The method for monitoring a battery thermal management system according to claim 3, wherein: The first heat transfer coefficient deviation threshold and the second heat transfer coefficient deviation threshold are both selected according to changes in the reference heat transfer coefficient value in different regions and / or different seasons.

8. The method for monitoring a battery thermal management system according to claim 1, wherein: The step of obtaining a real-time heat transfer coefficient value between the power battery and the cooling device under a predetermined operating condition includes: Collecting the battery pack temperature, the coolant inlet temperature and outlet temperature, and the coolant mass flow rate under the predetermined operating conditions; The real-time heat transfer coefficient value is calculated based on the battery pack temperature, the inlet temperature, the outlet temperature, and the mass flow rate.

9. The method for monitoring a battery thermal management system according to claim 1, wherein: The step of obtaining a real-time heat transfer coefficient value between the power battery and the cooling device under a predetermined operating condition further includes: Collecting the battery pack temperature, the coolant inlet temperature and the coolant outlet temperature, and the coolant mass flow rate under the predetermined operating conditions multiple times at a predetermined frequency within a predetermined time period; Calculate the corresponding real-time heat transfer coefficient value based on the battery pack temperature, the inlet temperature, the outlet temperature, and the mass flow rate collected each time; and An average real-time heat transfer coefficient value of all said real-time heat transfer coefficient values is calculated.

10. The method for monitoring a battery thermal management system according to claim 8 or 9, characterized in that: The real-time heat transfer coefficient value is calculated using the following formula: Where K is the real-time heat transfer coefficient value, T out is the outlet temperature of the coolant, T in is the inlet temperature of the coolant, T cell is the battery pack temperature, m is the coolant mass flow rate, c is the specific heat capacity of the coolant, and A is the contact area between the battery pack and the cooling device.

11. A battery management system, characterized in that: The battery management system uses the battery thermal management system monitoring method according to any one of claims 1 to 10 to monitor the status of the battery thermal management system in real time.

12. An electric vehicle, characterized in that: The electric vehicle include: The battery management system according to claim 11, wherein the battery management system is used to monitor the status of the battery thermal management system in real time.

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