Thermal Management Method, System and Storage Medium of Energy Storage System

Abstract

The present invention relates to the field of energy storage technologies, specifically to a thermal management method, system, and storage medium for an energy storage system. The thermal management method for the energy storage system includes: predicting the operating state of the management device, obtaining the operating state data of the management device within a preset period, and constructing a charging operating state number axis table and a discharging operating state number axis table. Constructing the temperature operating curve of the energy storage system. Performing correction to obtain a corrected curve. Judging whether the corrected curve exceeds a preset warning threshold. Judging whether the difference time period is less than a preset time length and dissipating heat with the most energy-saving cooling device. Through this method, the heat dissipation of the energy storage system can be budgeted, so that heat management can be carried out in advance, which provides preparation and cooling time for heat management, and can dissipate heat through the best cooling device, maximizing the saving of cooling energy, improving the energy utilization rate, avoiding energy waste, and reducing management costs.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage, and particularly to a thermal management method, system and storage medium for an energy storage system. Background Art

[0002] An energy storage system is a technology and device that stores energy for future use. Such a system usually consists of an energy storage unit, a controller and an energy management system, and can store and release electrical energy in different ways, such as batteries, compressed air, liquid fuels, flywheels, supercapacitors, etc.

[0003] The advantages of an energy storage system are that it can provide functions such as quick start, peak shaving, smooth output, and reduction of the volatility of renewable energy. These functions make the energy storage system an important solution, which can help power companies manage the power grid, reduce dependence on fossil fuels, lower carbon emissions, and improve energy efficiency.

[0004] Currently, there are many types of energy storage systems on the market, each with its own advantages and disadvantages. The specific choice of which system depends on the specific application scenario and requirements. Some common energy storage systems include lead-acid batteries, lithium-ion batteries, flow batteries, fuel cells, etc.

[0005] The thermal management of an energy storage system is one of the key factors to ensure the safe and reliable operation of the energy storage system. If the heat accumulated in the energy storage system cannot be effectively dissipated, it may lead to battery damage, performance degradation and even serious consequences such as fire. The following are several common thermal management technologies: 1. Natural cooling: Using the ambient temperature to naturally cool the energy storage system. This is the simplest and most economical method, but it is only applicable to low power density batteries. 2. Forced air cooling: Cooling by forcing the circulation of air flow. This method is applicable to high power density batteries. 3. Water cooling: A system that uses water as a coolant to dissipate heat. This method can provide higher heat dissipation efficiency, but it requires additional energy to heat the water. 4. Phase change materials: Using phase change materials (such as organic compounds) to achieve thermal management. This method can provide efficient heat dissipation effect, but the cost is high. 5. Thermal runaway monitoring: Monitoring the heat accumulation in the energy storage system and taking measures to prevent overheating when necessary. In summary, different energy storage systems have different thermal management requirements, and appropriate thermal management technologies need to be selected according to the actual situation. At the same time, effective thermal management can also extend the life of the energy storage system and improve its reliability and safety.

[0006] The existing thermal management of the energy storage system directly controls the cooling and heat dissipation through temperature detection. At this time, the development trend of the temperature is not evaluated, which is likely to cause damage to the energy storage system and energy waste. Summary of the Invention

[0007] To solve the above technical problems, the present invention provides a thermal management method for an energy storage system, which is used to predict the heat of the energy storage system and perform planned management. The thermal management method of the energy storage system may include:

[0008] S1. Predict the operating state of the management device, obtain the operating state data of the management device within a preset period, and construct a charging operating state number axis table and a discharging operating state number axis table according to the operating state data. The management device here is an electrical device connected to the energy storage system and capable of affecting the working state of the energy storage system. It also includes a charging module connected to the energy storage system. Generally, according to the operating rules of the electrical devices connected to the energy storage system, we can predict the operating states of each device within a short time. A preset period needs to be determined according to the specific time, specifically based on the heat release delay time of the energy storage system. Of course, other numerical settings are not excluded. The operating state data includes the operating time points of each management device, the operating states at each time point, the operating electric power, and the end time point, etc. That is, starting from the current time point, the operating states of each management device corresponding to each time point are obtained. The operating state here not only includes power consumption but also includes state data that can affect heat dissipation, which will not be elaborated here specifically. The operating state number axis table can be a time number axis, the length of the number axis is the preset period, the unit of the operating state number axis table is the unit time point within the preset period, and the operating states within the preset period need to be implanted into the number axis according to the corresponding time points, so as to obtain the operating state number axis table.

[0009] S2. Construct a temperature operating curve of the energy storage system according to the charging operating state number axis table and the discharging operating state number axis table. The operating state data includes the operating time points of each management device, the operating states at each time point, the operating electric power, and the end time point, etc. The operating state includes the names of each management device and their corresponding operating parameters. According to the various operating parameters corresponding to each different management device, the usage state of the energy storage system can be obtained.

[0010] S3. Correct the temperature operating curve of the energy storage system and obtain a corrected curve. As time goes by, the absolute time point where the abscissa origin of the temperature operating curve of the energy storage system is located is constantly changing. The ordinate corresponding to the temperature operating curve of the energy storage system is obtained through prediction and calculation. However, the endpoint values of the temperature operating curve of the energy storage system can be obtained through detection, which provides the possibility and convenience for correction. The predicted charging and discharging operating state number axis table may change, and the parameters of the energy storage system may also change with temperature and some operating conditions. The change of the predicted charging and discharging operating state number axis table can be corrected through real-time calculation. However, some parameter changes of the energy storage system cannot be reflected by the predicted operating state number axis table. Therefore, double-error correction of the operating curve is required.

[0011] S4. Determine whether the correction curve exceeds a preset warning threshold T 标 . If so, issue a first-level alarm and execute S5; if not, do not issue a first-level alarm. The preset warning threshold T here 标 can be set according to the actual situation. In the coordinate system, it is a horizontal line. If the correction curve exceeds the warning threshold, it means the intersection of two lines.

[0012] S5. Calibrate the abscissa of the intersection point as i, and then determine whether i is less than a preset time length i 标 . If so, issue a second-level alarm and execute S6; if not, do not issue a second-level alarm, where i is the time period between the intersection point and the current time point, and the preset time length i 标 can be determined according to the heat dissipation capacity of the heat dissipation equipment of the energy storage system.

[0013] S6. Determine whether the fitting curve of the correction curve to the cooling equipment numbered h exceeds the preset warning threshold T 标 , where h is the number of the cooling equipment of the energy storage system, h = 1, 2,..., H; if so, select the cooling equipment numbered h for cooling; if not, execute S7;

[0014] S7. Determine whether the fitting curve of the correction curve to the cooling equipment numbered h + 1 exceeds the preset warning threshold T 标 , and calculate by analogy in turn. If the fitting curve of the correction curve to the cooling equipment numbered H still exceeds the preset warning threshold T 标 , then cool down according to the cooling equipment numbered H.

[0015] Preferably, the method for constructing the temperature operation curve of the energy storage system may include: constructing a plane coordinate system, where the abscissa of the plane coordinate system is a preset period and the ordinate is a temperature value. Then, calculate the heat dissipation temperature value T of the energy storage system corresponding to each time point within the preset period through the operation state number axis table, and then implant the heat dissipation temperature value T of the energy storage system into the plane coordinate system according to the time point to obtain each heat dissipation temperature value point, and connect each heat dissipation temperature value point in sequence, so as to obtain the temperature operation curve of the energy storage system.

[0016] Preferably, the heat dissipation temperature value T of the energy storage system is the predicted temperature value within the energy storage system, and its value can be calculated according to the charge operation state number axis table and the discharge operation state number axis table. The heat dissipation temperature value of the energy storage system , where R is the discharge internal resistance of the energy storage system, and R’ is the charge internal resistance of the energy storage system. Their specific values can be obtained by testing according to the charge-discharge state of the energy storage system or obtained from the energy storage system. j is the number of each management device in the discharge operation state number axis table at the predicted time point, and J is the total number of discharge management devices at this predicted time point, j = 1, 2, …, J; I j is the operating current of the discharge management device numbered j, I J 0 is the additional current when J discharge management devices are operating. k is the number of each charge management device in the charge operation state number axis table at the predicted time point, and K is the total number of charge management devices at this predicted time point, k = 1, 2, …, K; I k is the operating current of the charge management device numbered k, I K 1 is the additional current of K charge management devices, I K 1 can be obtained through experimental detection. ε is the heat dissipation proportionality factor, and its value is related to the heat dissipation performance and temperature difference of the energy storage system. Its value is generally between 0.1 - 0.8, and it can be obtained by looking up the information table prepared in advance according to experiments. Of course, it can also be obtained through calculation. C is the average specific heat capacity of the energy storage system, and M is the effective mass of the energy storage system, which can be obtained through a heating experiment on the energy storage system. S is the effective heat dissipation area of the energy storage system, and its value can be obtained from the device parameters of the energy storage system, and will not be elaborated here specifically. The heat dissipation temperature value calculated by this method can fully consider the heat dissipation state when charging and discharging are operating simultaneously, consider the heat generation of each current and the influence of the additional current at the same time, and through the influence of the heat dissipation efficiency, the evaluation is more comprehensive, conforms to the actual heat dissipation of the energy storage system, and the calculation is accurate.

[0017] Preferably: The method for obtaining the additional current I J 0 can include: obtaining the detection current I 总 by detecting the energy storage system. At this time, the additional current of each discharge management device numbered j, and then making a compatibility information table of device - additional current for each discharge management device. The compatibility information table includes each cooperating management device, parameter information, and the corresponding additional current. By looking up the compatibility information table through the name and parameter information of each management device, the additional current can be obtained.

[0018] Preferably, the method for obtaining the heat dissipation ratio factor ε may include: conducting experiments on the energy storage system in advance, calculating to obtain the heat dissipation ratio factor values according to different heat dissipation temperature differences ΔT, so as to obtain the heat dissipation ratio factor values corresponding to different heat dissipation temperature differences ΔT, then constructing a heat dissipation ratio curve, and looking up the heat dissipation ratio curve through the heat dissipation temperature difference ΔT, thereby obtaining the heat dissipation ratio factor.

[0019] Preferably: the heat dissipation ratio factor value , where Q is the theoretical heat generation of the energy storage system, and ΔT is the heat dissipation temperature difference, which can be the difference between the internal temperature and the ambient temperature of the energy storage system and can be obtained by detection.

[0020] Preferably: the specific theoretical heat generation , where Q’ is the power consumption of the energy storage system and U is the operating voltage of the energy storage system.

[0021] Preferably: the method for constructing the heat dissipation ratio curve may include: constructing a plane coordinate system with the abscissa being the heat dissipation temperature difference and the ordinate being the heat dissipation ratio factor, then implanting the calculated heat dissipation ratio factors into the plane coordinate system according to the corresponding heat dissipation temperature differences to obtain heat dissipation ratio points, and then connecting the heat dissipation ratio points in sequence to obtain the heat dissipation ratio curve.

[0022] Preferably: the method for correcting the temperature operation curve of the energy storage system may include: detecting the internal temperature value T’ of the energy storage system, calculating the heat dissipation temperature value T’’ of the energy storage system according to the operation state data at the current time point, translating the ordinate of the endpoint of the temperature operation curve of the energy storage system from the heat dissipation temperature value T to T’, and scaling and correcting the ordinate point values of the temperature operation curve of the energy storage system according to the ratio, thereby obtaining the corrected curve. By correcting in this way, not only can the errors of the current operation state parameters be corrected, but also the errors due to calculation can be corrected, so that the two errors can be corrected in all directions and the corrected curve can be made more accurate.

[0023] Preferably: the warning threshold , where is the buffer factor, T 1 is the tolerance temperature or upper limit temperature of the energy storage system, and its value is generally 0.8 - 0.95. Of course, other value settings are not excluded. The smaller the value setting of the buffer factor, the better the protection of the energy storage system, and the larger its buffer space, but its alarm frequency will increase and the cooling cost will be relatively high, increasing the management cost. This setting method is the fixed value method and cannot be adjusted according to the actual situation.

[0024] Preferably: the preset warning threshold T 标The calculation method may further include: calculating the tolerance temperature t of each electrical component in the energy storage system m , where m is the number of each electrical component or electrical material in the energy storage system, and the tolerance temperature t m can be obtained according to the upper limit of the operating temperature of each electrical component or electrical material, and the specific details are not elaborated here. The preset warning threshold , where M is the total number of each electrical component or electrical material in the energy storage system, m = 1, 2,..., M; t m is the tolerance temperature of each electrical component or electrical material in the energy storage system, and δ m is the weight ratio of the electrical component or electrical material with the number m. ɑ m is the heat dissipation ratio coefficient of the electrical component or electrical material with the number m, and its value can be obtained according to the structure of the energy storage system and the materials of its peripheral structure, and can be specifically obtained through calculation or experiment, and the process of the experiment is not elaborated here. The preset warning threshold calculated by this method can take into account the tolerance temperature, its weight ratio and its heat dissipation ratio coefficient of each electrical component or material. This calculation method is comprehensive and the calculation result is accurate.

[0025] Preferably: the heat dissipation ratio coefficient , where n is the number of the material outside the electrical component or electrical material with the number m, and its numbering can be carried out from the inside to the outside, and the specific details are not elaborated here. b n is the thickness of the peripheral material with the number n, is the thermal conductivity of the peripheral material with the number n, and S n is the effective surface area of the peripheral material with the number n, which can be obtained through the structure of the energy storage system, and the specific details are not elaborated here. is an adjustment coefficient, and its specific value can be obtained through the structure of the energy storage system. Its value is generally 0.5 - 1, and the specific details are not elaborated here. The preset warning threshold calculated by this method takes into account the structure of the energy storage system and the materials of its peripheral structure, and the evaluation is comprehensive and the calculation is accurate.

[0026] Preferably: the preset time length , where T 0 is the target temperature for cooling the energy storage system, which can be the standard operating temperature of the energy storage system, generally 20 - 50 degrees Celsius, and the specific details are not elaborated here. h is the number of the cooling equipment of the energy storage system, h = 1, 2,..., H; the cooling equipment of the energy storage system can include air-cooled heat dissipation, air-conditioning heat dissipation, etc., and its sorting method can be carried out from the lowest cooling capacity to the highest. Basically, its cooling capacity and cooling cost are positively correlated, and the specific details are not elaborated here. θ his the heat dissipation capacity factor of the cooling device numbered h, which can be obtained by conducting experiments on the cooling capacities of various cooling devices. These data are all dimensionless data. Max[] is used to take the maximum value, and the specific details are not elaborated here. This method processes the temperature difference through logarithms, taking into account the trend of temperature dissipation. The higher the temperature, the stronger the heat dissipation ability. This calculation method can fully consider the heat dissipation characteristics, with strong calculation accuracy and better conforming to the actual heat dissipation situation.

[0027] Preferably, the method for obtaining the fitting curve of the correction curve for the cooling device numbered h may include: performing cooling fitting on each cooling device to obtain a cooling fitting curve. The cooling fitting curve is a curve constructed with the cooling time as the abscissa and the temperature drop as the ordinate. Different cooling fitting curves can be constructed for different starting temperatures and ambient temperatures, and the specific details are not elaborated here. Then, implant the cooling fitting curve into the correction curve coordinate system, and subtract the cooling fitting curve from the correction curve to obtain the cooling device fitting curve. The specific numerical operations are not elaborated here.

[0028] The present invention also proposes a thermal management system for an energy storage system, which is used to predict the heat of the energy storage system and perform planned management. The thermal management system of the energy storage system may include:

[0029] An equipment operation statistics module, which is used to predict the operation status of the management equipment, obtain the operation status data of the management equipment within a preset period, and construct a charging operation status number axis table and a discharging operation status number axis table based on the operation status data.

[0030] An energy storage system statistics module, which is used to construct an energy storage system temperature operation curve based on the charging operation status number axis table and the discharging operation status number axis table.

[0031] An operation curve correction module, which is used to correct the energy storage system temperature operation curve and obtain a correction curve.

[0032] A judgment and analysis module, which is used to judge whether the correction curve exceeds a preset warning threshold T 标 , if so, a first-level alarm is triggered; if not, no first-level alarm is issued. After receiving the first-level alarm, the abscissa of the calibration intersection point is marked as i, and then it is judged whether i is less than a preset time length i 标 , if so, a second-level alarm is triggered; if not, no second-level alarm is issued. It is judged whether the fitting curve of the correction curve for the cooling device numbered h exceeds the preset warning threshold T 标 , if so, select the cooling device numbered h for cooling; if not, judge whether the fitting curve of the correction curve for the cooling device numbered h + 1 exceeds the preset warning threshold T 标, and so on for sequential calculations. If the correction curve still exceeds the preset warning threshold T for the cooling device numbered H 标 , then cooling is performed according to the cooling device numbered H.

[0033] As a preferred embodiment of the present invention, a computer-readable storage medium stores a computer program thereon. When the program is executed by a processor, the steps of the thermal management method of the energy storage system are implemented. When the thermal management method of the energy storage system is applied, it can be applied in the form of software. For example, it can be designed as a program that can run independently on the computer-readable storage medium. The computer-readable storage medium can be a USB flash drive, designed as a USB key, and designed through the USB flash drive to start the entire method through external triggering.

[0034] The technical effects and advantages of the present invention: Through this method, the heat dissipation of the energy storage system can be budgeted, so that heat management can be carried out in advance, which provides preparation and cooling time for heat management. Cooling is performed through the best cooling device, which can save cooling energy to the greatest extent, improve energy utilization efficiency, avoid energy waste, and reduce management costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a schematic flow chart of the thermal management method of the energy storage system proposed by the present invention.

[0036] Figure 2 is a schematic structural diagram of the thermal management system of the energy storage system proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] The embodiments of the present disclosure are described in detail below. Examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary only for explaining the present disclosure and should not be construed as limiting the present disclosure. On the contrary, the embodiments of the present disclosure include all changes, modifications, and equivalents falling within the spirit and scope of the appended claims.

[0038] Embodiment 1

[0039] Reference Figure 1 , in this embodiment, a thermal management method of the energy storage system is proposed for predicting the heat of the energy storage system and performing planned management. The thermal management method of the energy storage system may include:

[0040] S1. Predict the operating state of the management device, obtain the operating state data of the management device within a preset period, and construct a charging operating state number axis table and a discharging operating state number axis table based on the operating state data. Here, the management device is an electrical device connected to the energy storage system and capable of affecting the working state of the energy storage system, including electrical appliances connected to the energy storage system, such as lighting devices, refrigeration devices, motor units, etc., and also includes a charging module connected to the energy storage system. The charging module can be a charging device, a photovoltaic system, or other power generation modules, which will not be elaborated here specifically. Generally, according to the operating rules of the electrical devices connected to the energy storage system, we can predict the operating states of each device within a short period. For example, if the energy storage system is an energy storage device for photovoltaic and wind power generation of street lamps, we can obtain the power generation amount of photovoltaic power generation based on the light intensity and light angle of the current day, and then obtain the power generation power of the photovoltaic after conversion. Then, based on the current wind power generation device, we can obtain the wind power generation power and the heat dissipation efficiency caused by the wind in the future period of time. The sum of the two and the conversion can obtain the charging power of the energy storage system. Street lamps do not discharge during the day. According to the usage rules of street lamps, we can obtain that the street lamp is turned on for lighting at 5 pm, and the power of the street lamp is 50w, so that we can obtain its discharging power. Of course, this is just a simple example and is not universal. Other situations will not be elaborated here specifically. A preset period needs to be determined according to the specific time. Specifically, it can be 0.1min - 60min, and it is preferably 1 - 10min. Specifically, it needs to be based on the heat dissipation delay time of the energy storage system. Of course, other numerical settings are not excluded. Generally, the length of the predicted period is not large, and it is completely possible to predict each management device, which will not be elaborated here specifically. The operating state data includes the operating time points of each management device, the operating states at each time point, the operating electric power, and the end time point, etc. Thus, starting from the current time point, the operating states of each management device corresponding to each time point are obtained. Here, the operating state not only includes power consumption but also includes state data that can affect heat dissipation, which will not be elaborated here specifically. The operating state number axis table can be a time number axis. The length of the number axis is the preset period. The unit of the operating state number axis table is the unit time point within the preset period. The operating states within the preset period need to be implanted into the number axis according to the corresponding time points, so that the operating state number axis table can be obtained.

[0041] S2. Construct the temperature operation curve of the energy storage system based on the charging operation status number axis table and the discharging operation status number axis table. The operation status data includes the time points when each management device operates, the operation status at each time point, the operating electric power, the end time point, etc. The operation status includes the names of each management device and their corresponding operation parameters. The usage status of the energy storage system can be obtained according to various operation parameters corresponding to different management devices. For example, a management device is a fan. The fan is in the on state at 11 o'clock and is in the first gear of heat dissipation. The operation parameter of the first gear of heat dissipation is a power of 20W, and it is planned to be turned off at 11:10. Of course, this is just a simple example and is not universal. Other situations are not elaborated here. The method for constructing the temperature operation curve of the energy storage system may include: constructing a plane coordinate system, where the abscissa of the plane coordinate system is the preset period and the ordinate is the temperature value. Then, calculate the heat dissipation temperature value T of the energy storage system corresponding to each time point within the preset period through the operation status number axis table. Then, implant the heat dissipation temperature value T of the energy storage system into the plane coordinate system according to the time points to obtain each heat dissipation temperature value point, and connect each heat dissipation temperature value point in sequence to obtain the temperature operation curve of the energy storage system. The heat dissipation temperature value T of the energy storage system is the predicted temperature value within the energy storage system, and its value can be calculated according to the charging operation status number axis table and the discharging operation status number axis table. The heat dissipation temperature value , where R is the discharging internal resistance of the energy storage system, and R' is the charging internal resistance of the energy storage system. Its specific value can be obtained through testing according to the charge-discharge status of the energy storage system or obtained according to the energy storage system. The specific testing process is prior art and is not elaborated here. j is the number of each management device in the discharging operation status number axis table at the predicted time point, and J is the total number of discharging management devices at this predicted time point, j = 1, 2,..., J; I j is the operating current of the discharging management device numbered j, I J 0 is the additional current during the operation of J discharging management devices. Its specific value can be obtained through experiments. In its ideal state, its value is zero. However, in actual situations, the superposition of multiple currents during operation will increase the current load of the circuit. Therefore, by setting the additional current, the impact of the current on the energy storage system can be better evaluated, avoiding calculation errors caused by changes in the current value due to circuit load, and improving the accuracy of prediction. The additional current I J 0 can be obtained by conducting an experiment on the energy storage system for discharging with corresponding management devices and parameters. By detecting the energy storage system, the detected current I 总 is obtained. At this time, the additional current of each discharging management device numbered j , and then make a compatibility information table of device - additional current for each discharge management device. The compatibility information table includes each cooperating management device, parameter information, and the corresponding additional current. When calculating, search the compatibility information table through the names and parameter information of each management device, so that the additional current can be obtained. k is the number of each charging management device in the charging operation status number axis table at the predicted time point, K is the total number of charging management devices at this predicted time point, k = 1, 2, …, K; I k is the operating current of the charging management device numbered k, I K 1 is the additional current of K charging management devices. At this time, each charging management device can be multiple solar panels, wind power generation modules, etc., and its prediction can be carried out through the power generation law, I K 1 can be obtained through experimental detection, and the details are not described here. ε is the heat dissipation proportion factor, and its value is related to the heat dissipation performance and temperature difference of the energy storage system. Its value is generally between 0.1 - 0.8, and it can be obtained by looking up the information table prepared in advance according to experiments. Of course, it can also be obtained through calculation. When obtained through calculation, the heat dissipation proportion factor , where Q is the theoretical heat generation of the energy storage system, and its value can be obtained through experiments on the energy storage system. Of course, it can also be obtained through calculation. The specific theoretical heat generation , where Q’ is the power consumption of the energy storage system, U is the working voltage of the energy storage system, and their specific values are not described here. ΔT is the heat dissipation temperature difference, which can be the difference between the internal temperature and the ambient temperature of the energy storage system and can be obtained through detection. C is the average specific heat capacity of the energy storage system, M is the effective mass of the energy storage system, and it can be obtained through a heating experiment on the energy storage system. Specifically, it is the prior art and is not described here in detail. Specifically, experiments on the energy storage system can be carried out in advance, and calculations can be made according to different heat dissipation temperature differences ΔT, so that the heat dissipation proportion factors corresponding to different heat dissipation temperature differences ΔT can be obtained, and then a heat dissipation proportion curve can be constructed. The method for constructing the heat dissipation proportion curve can include: constructing a plane coordinate system, with the abscissa being the heat dissipation temperature difference and the ordinate being the heat dissipation proportion factor, and then implanting the calculated heat dissipation proportion factors into the plane coordinate system according to the corresponding heat dissipation temperature differences to obtain heat dissipation proportion points, and then connecting each heat dissipation proportion point in sequence to obtain the heat dissipation proportion curve. Search the heat dissipation proportion curve through the heat dissipation temperature difference to obtain the heat dissipation proportion factor. S is the effective heat dissipation area of the energy storage system, and its value can be obtained from the device parameters of the energy storage system, and the details are not described here. The heat dissipation temperature value calculated by this method can fully consider the heat dissipation state when charging and discharging are operating simultaneously, consider the influence of each current heat generation and additional current at the same time, and at the same time, through the influence of heat dissipation efficiency, the evaluation is more comprehensive, conforms to the actual heat dissipation of the energy storage system, and the calculation is accurate.

[0042] S3. Modify the temperature operation curve of the energy storage system and obtain the modified curve. As time goes by, the absolute time point of the origin of the abscissa where the temperature operation curve of the energy storage system is located is constantly changing. The ordinate corresponding to the temperature operation curve of the energy storage system is obtained through predictive calculation. However, the endpoint values of the temperature operation curve of the energy storage system can be obtained through detection, which provides the possibility and convenience for modification. The predicted charge-discharge operation state number axis table may change, and the parameters of the energy storage system may also change with temperature and some operating conditions. The change of the predicted charge-discharge operation state number axis table can be corrected through real-time calculation. However, the change of some parameters of the energy storage system cannot be reflected by the predicted operation state number axis table. Therefore, it is necessary to correct the operation curve with double errors. The correction method of the temperature operation curve of the energy storage system may include: detecting the internal temperature value T' of the energy storage system, calculating the heat dissipation temperature value T'' of the energy storage system according to the operation state data at the current time point, translating the endpoint ordinate of the temperature operation curve of the energy storage system from the heat dissipation temperature value T to T', and scaling and correcting the ordinate point values of the temperature operation curve of the energy storage system according to the ratio, so as to obtain the modified curve. By correcting through this method, not only can the current operation state parameter error be corrected, but also the error due to calculation can be corrected, so that the two errors can be corrected in all directions, making the modified curve more accurate.

[0043] S4. Determine whether the modified curve exceeds a preset warning threshold T 标 , if so, perform a first-level alarm and execute S5, if not, do not perform a first-level alarm. The preset warning threshold T 标 can be set according to the actual situation. In the coordinate system, it is a horizontal straight line. When the modified curve exceeds the warning threshold, it is the intersection of the two lines. Generally, the tolerance temperature or upper limit temperature T 1 of the energy storage system needs to be considered, etc. Generally, the warning threshold , where is a buffer factor, and its value is generally 0.8 - 0.95. Of course, other value settings are not excluded. The smaller the value setting of the buffer factor, the better the protection of the energy storage system, and the larger its buffer space, but its alarm frequency will increase, and the cooling cost will be relatively high, increasing the management cost. This setting method is the fixed value method and cannot be adjusted according to the actual situation. The calculation method of the preset warning threshold T 标 can also include: calculating the tolerance temperature t m of each electrical component in the energy storage system, where m is the number of each electrical component or electrical material in the energy storage system, and the tolerance temperature t mcan be obtained according to the upper limit of the operating temperature of each electrical component or electrical material, and will not be elaborated here. The preset warning threshold , where M is the total number of electrical components or electrical materials in the energy storage system, m = 1, 2, …, M; t m is the tolerance temperature of each electrical component or electrical material in the energy storage system, δ m is the weight ratio of the electrical component or electrical material with the number m, which can be preset according to the importance of the electrical component or electrical material in the energy storage system, and will not be elaborated here. ɑ m is the heat dissipation ratio coefficient of the electrical component or electrical material with the number m, and its value can be obtained according to the structure of the energy storage system and the materials of its peripheral structure, and can be specifically obtained through calculation or experiment, and the process of the experiment will not be elaborated here. The preset warning threshold calculated by this method can take into account the tolerance temperature, its weight ratio and its heat dissipation ratio coefficient of each electrical component or material. This calculation method is comprehensive and the calculation result is accurate. Heat dissipation ratio factor , where n is the number of the material outside the electrical component or electrical material with the number m, and its numbering can be carried out from the inside to the outside, and will not be elaborated here. b n is the thickness of the peripheral material with the number n, is the thermal conductivity of the peripheral material with the number n, S n is the effective surface area of the peripheral material with the number n, which can be obtained through the structure of the energy storage system, and will not be elaborated here. is an adjustment coefficient, and its specific value can be obtained through the structure of the energy storage system, and its value is generally 0.5 - 1, and will not be elaborated here. The preset warning threshold calculated by this method takes into account the structure of the energy storage system and the materials of its peripheral structure, and the evaluation is comprehensive and the calculation is accurate.

[0044] S5. The abscissa of the calibration intersection point is i, and then it is judged whether i is less than a preset time length i 标 , if so, secondary alarm is carried out and S6 is executed, if not, secondary alarm is not carried out, where i is the time period between the intersection point and the current time point, and the preset time length i 标 can be determined according to the heat dissipation capacity of the heat dissipation device of the energy storage system, and the specific value is generally 0.5 min - 5 min. This fixed time limit is relatively mechanical and cannot be adjusted organically according to the specific situation, and it is easy to waste energy. The preset time length , where T 0The cooling target temperature for the energy storage system can be the standard operating temperature of the energy storage system, generally 20 - 50 degrees Celsius, which will not be elaborated here. h is the number of the cooling device of the energy storage system, h = 1, 2, … H; the energy storage system cooling device can include air-cooled heat dissipation, air-conditioning heat dissipation, etc., and its sorting method can be sorted from low to high cooling capacity. Basically, its cooling capacity and cooling cost are positively correlated, which will not be elaborated here. θ h is the heat dissipation capacity factor of the cooling device numbered h, which can be obtained through experiments on the cooling capacity of each cooling device. These data are all dimensionless data. Max[] is used to take the maximum value, which will not be elaborated here. This method processes the temperature difference through logarithms, can consider the trend of temperature dissipation, and the higher the temperature, the stronger the heat dissipation capacity. This calculation method can fully consider the heat dissipation characteristics, has strong calculation accuracy, and is more in line with the actual heat dissipation situation.

[0045] S6. Determine whether the fitting curve of the correction curve to the cooling device numbered h exceeds the preset warning threshold T 标 If not, select the cooling device numbered h for cooling. If so, execute S7;

[0046] S7. Determine whether the fitting curve of the correction curve to the cooling device numbered h + 1 exceeds the preset warning threshold T 标 And so on for calculation in sequence. If the fitting curve of the correction curve to the cooling device numbered H still exceeds the preset warning threshold T 标 Then cool down according to the cooling device numbered H. The method for obtaining the fitting curve of the correction curve to the cooling device numbered h can include performing cooling fitting on each cooling device to obtain a cooling fitting curve. The cooling fitting curve is a curve constructed with the cooling time as the abscissa and the reduced temperature as the ordinate. Different cooling fitting curves can be constructed for different starting temperatures and ambient temperatures, which will not be elaborated here. Then implant the cooling fitting curve into the correction curve coordinate system, and subtract the cooling fitting curve from the correction curve, so as to obtain the cooling device fitting curve. The specific numerical operations will not be elaborated here. Through this method, the heat dissipation of the energy storage system can be budgeted, so that heat management can be carried out in advance, which provides preparation and cooling time for heat management, and can cool down with the best cooling device, saving cooling energy to the greatest extent, improving the energy utilization rate, avoiding energy waste, and reducing management costs.

[0047] Embodiment 2

[0048] The present invention also proposes a thermal management system for an energy storage system, which is used to predict the heat of the energy storage system and perform planned management. The thermal management system of the energy storage system can include:

[0049] The device operation statistics module is used to predict the operation status of the management device, obtain the operation status data of the management device within a preset period, and construct a charging operation status number axis table and a discharging operation status number axis table based on the operation status data.

[0050] The energy storage system statistics module is used to construct the temperature operation curve of the energy storage system according to the charging operation status number axis table and the discharging operation status number axis table.

[0051] The operation curve correction module is used to correct the temperature operation curve of the energy storage system and obtain the corrected curve.

[0052] The judgment and analysis module is used to judge whether the corrected curve exceeds a preset warning threshold T 标 , if so, a first-level alarm is issued; if not, the first-level alarm is not issued. After receiving the first-level alarm, the abscissa of the calibration intersection is set as i, and then it is judged whether i is less than a preset time length i 标 , if so, a second-level alarm is issued; if not, the second-level alarm is not issued. It is judged whether the fitting curve of the corrected curve to the temperature reduction device numbered h exceeds the preset warning threshold T 标 , if not, the temperature reduction device numbered h is selected for temperature reduction; if so, it is judged whether the fitting curve of the corrected curve to the temperature reduction device numbered h + 1 exceeds the preset warning threshold T 标 , and so on. If the fitting curve of the corrected curve to the temperature reduction device numbered H still exceeds the preset warning threshold T 标 , then the temperature reduction is carried out according to the temperature reduction device numbered H.

[0053] Embodiment 3

[0054] As a preferred embodiment of the present invention, a computer-readable storage medium stores a computer program thereon. When the program is executed by a processor, the steps of the thermal management method of the energy storage system are implemented. When the thermal management method of the energy storage system is applied, it can be applied in the form of software, such as designed as a program that can run independently on the computer-readable storage medium. The computer-readable storage medium can be a USB flash drive, designed as a USB key, and designed through the USB flash drive as a program to start the entire method by external trigger.

[0055] It should be understood that various forms of the processes shown above can be used, reordering, adding or deleting steps. For example, the steps recorded in the present disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present application can be achieved, and no limitations are imposed herein.

[0056] The above specific embodiments do not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub - combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present disclosure should be included within the protection scope of the present disclosure.

Claims

1. A thermal management method for an energy storage system, characterized in that: The thermal management method of the energy storage system comprises: S1. Predict the operating status of the management device, obtain the operating status data of the management device within a preset cycle, and construct a charging operating status axis table and a discharging operating status axis table according to the operating status data. The management device is an electrical device connected to the energy storage system and capable of affecting the working status of the energy storage system; S2. Constructing a temperature operation curve of the energy storage system according to the charging operation state axis table and the discharging operation state axis table; the method for constructing the temperature operation curve of the energy storage system includes: constructing a plane coordinate system, the horizontal axis of the plane coordinate system is a preset period, and the vertical axis is a temperature value, and then calculating the heat dissipation temperature value T of the energy storage system corresponding to each time point in the preset period through the operation state axis table, and then implanting the heat dissipation temperature value T of the energy storage system into the plane coordinate system according to the time point to obtain each heat dissipation temperature value point, and connecting each heat dissipation temperature value point in sequence to obtain the temperature operation curve of the energy storage system; the heat dissipation temperature value of the energy storage system , where R is the discharge internal resistance of the energy storage system, R' is the charging internal resistance of the energy storage system, j is the number of each management device in the discharge operation state axis table at the predicted time point, and J is the total number of discharge management devices at the predicted time point, j=1, 2, ..., J; I j is the operating current of the discharge management device numbered j, I J 0 is the additional current when J discharge management devices are running, k is the number of each charge management device in the charging operation state axis table at the prediction time point, K is the total number of charge management devices at the prediction time point, k=1, 2, ..., K; I k is the operating current of the charging management device numbered k, I K 1 is the additional current of K charging management devices, I K 1 It can be obtained through experimental detection, ε is the heat dissipation proportional factor, C is the average specific heat capacity of the energy storage system, M is the effective mass of the energy storage system, and S is the effective heat dissipation area of ​​the energy storage system; S3, correcting the temperature operation curve of the energy storage system and obtaining a corrected curve; the correction method of the temperature operation curve of the energy storage system includes: detecting the internal temperature value T' of the energy storage system, and calculating the heat dissipation temperature value T'' of the energy storage system according to the operation status data at the current time point, and translating the endpoint ordinate of the temperature operation curve of the energy storage system from the heat dissipation temperature value T to T', and scaling and correcting the ordinate point value of the temperature operation curve of the energy storage system according to a preset ratio to obtain a corrected curve; S4. Determine whether the correction curve exceeds a preset warning threshold T 标 If yes, a first-level alarm is issued and S5 is executed; if no, a first-level alarm is not issued; S5, mark the horizontal coordinate of the intersection point as i, and then determine whether i is less than a preset time length i 标 If yes, a second-level alarm is issued and S6 is executed; if no, no second-level alarm is issued; S6. Determine whether the correction curve for the cooling device fitting curve numbered h exceeds the preset warning threshold value T 标 , h is the cooling device number of the energy storage system, h=1, 2, ..., H; the sorting method is to sort the cooling capacity from low to high, if not, select the cooling device numbered h for cooling, if yes, execute S7; the correction curve obtains the fitting curve of the cooling device numbered h, including: performing cooling fitting on each cooling device to obtain a cooling fitting curve, the cooling fitting curve is a curve constructed with the cooling time as the horizontal coordinate and the lowering temperature as the vertical coordinate; then implanting the cooling fitting curve into the correction curve coordinate system, and subtracting the cooling fitting curve from the correction curve to obtain the cooling device fitting curve; S7, determine whether the correction curve fits the cooling device numbered h+1 to a curve exceeding a preset warning threshold value T 标 , and then perform analogy calculations. If the correction curve still exceeds the preset warning threshold T for the cooling device numbered H, 标 , then cool down according to the cooling device or combination numbered H.

2. The thermal management method of the energy storage system according to claim 1, characterized in that: The preset ratio is .

3. The thermal management method of the energy storage system according to claim 1, characterized in that: The warning threshold ,in is the buffer factor, and T1 is the tolerance temperature or upper limit temperature of the energy storage system.

4. The thermal management method of the energy storage system according to claim 1, characterized in that: The preset warning threshold T 标 The calculation method includes: preset warning threshold , where m is the serial number of each electrical component or electrical material in the energy storage system, M is the total number of each electrical component or electrical material in the energy storage system, m=1, 2, ..., M; t m is the tolerable temperature of each electrical component or electrical material in the energy storage system; m It is the weight ratio of the electrical component or electrical material electrical component numbered m; m It is the heat dissipation proportional coefficient of the electrical component numbered m or the electrical material electrical component.

5. The thermal management method of the energy storage system according to claim 4, characterized in that: Heat dissipation ratio coefficient , where n is the number of the electrical component or electrical material, the number of the material surrounding the electrical component; b n is the thickness of the peripheral material numbered n, is the thermal conductivity of the peripheral material numbered n, S n is the effective surface area of ​​the peripheral material numbered n; is the adjustment factor.

6. The thermal management method of the energy storage system according to claim 1, characterized in that: The preset time length , where T0 is the cooling target temperature of the energy storage system; h=1, 2, …H; θ h It is the heat dissipation capacity factor of the cooling device numbered h; Max[] is the maximum value.

7. A thermal management system for an energy storage system, characterized in that: The thermal management system of the energy storage system comprises: The equipment operation statistics module is used to predict the operation status of the management equipment, obtain the operation status data of the management equipment within a preset period, and construct a charging operation status axis table and a discharging operation status axis table according to the operation status data. The management equipment is an electrical device connected to the energy storage system and can affect the working status of the energy storage system; The energy storage system statistics module is used to construct the temperature operation curve of the energy storage system according to the charging operation state axis table and the discharging operation state axis table; the energy storage system temperature operation curve construction method includes: constructing a plane coordinate system, the horizontal axis of the plane coordinate system is a preset period, and the vertical axis is a temperature value, and then calculating the energy storage system heat dissipation temperature value T corresponding to each time point in the preset period through the operation state axis table, and then implanting the energy storage system heat dissipation temperature value T into the plane coordinate system according to the time point to obtain each heat dissipation temperature value point, and connecting each heat dissipation temperature value point in sequence to obtain the energy storage system temperature operation curve; the energy storage system heat dissipation temperature value , where R is the discharge internal resistance of the energy storage system, R' is the charging internal resistance of the energy storage system, j is the number of each management device in the discharge operation state axis table at the predicted time point, and J is the total number of discharge management devices at the predicted time point, j=1, 2, ..., J; I j is the operating current of the discharge management device numbered j, I J 0 is the additional current when J discharge management devices are running, k is the number of each charge management device in the charging operation state axis table at the prediction time point, K is the total number of charge management devices at the prediction time point, k=1, 2, ..., K; I k is the operating current of the charging management device numbered k, I K 1 is the additional current of K charging management devices, I K 1 It can be obtained through experimental detection, ε is the heat dissipation proportional factor, C is the average specific heat capacity of the energy storage system, M is the effective mass of the energy storage system, and S is the effective heat dissipation area of ​​the energy storage system; An operating curve correction module is used to correct the temperature operating curve of the energy storage system and obtain a corrected curve; the correction method of the temperature operating curve of the energy storage system includes: detecting the internal temperature value T' of the energy storage system, and calculating the heat dissipation temperature value T'' of the energy storage system according to the operating status data at the current time point, and translating the endpoint ordinate of the temperature operating curve of the energy storage system from the heat dissipation temperature value T to T', and scaling and correcting the ordinate point value of the temperature operating curve of the energy storage system according to a preset ratio to obtain a corrected curve; The judgment analysis module is used to judge whether the correction curve exceeds a preset warning threshold T 标 If yes, a first-level alarm is issued, if no, no first-level alarm is issued; the horizontal coordinate of the intersection is calibrated as i, and then it is determined whether i is less than a preset time length i 标 If yes, a second-level alarm is issued, if no, no second-level alarm is issued; determine whether the correction curve for the cooling device fitting curve numbered h exceeds the preset warning threshold T 标 If not, select the cooling device numbered h for cooling. If yes, determine whether the correction curve fits the cooling device numbered h+1 to a curve that exceeds the preset warning threshold T. 标 , and then perform analogy calculations. If the correction curve still exceeds the preset warning threshold T for the cooling device numbered H, 标 , the temperature is cooled according to the cooling device numbered H or the combination mode, and the method for obtaining the fitting curve of the cooling device numbered h by the correction curve includes: performing cooling fitting on each cooling device to obtain the cooling fitting curve, the cooling fitting curve is a curve constructed with the cooling time as the horizontal coordinate and the lowering temperature as the vertical coordinate; then the cooling fitting curve is implanted into the correction curve coordinate system, and the cooling fitting curve is subtracted from the correction curve to obtain the cooling device fitting curve.

8. A computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the steps of the thermal management method for an energy storage system according to any one of claims 1 to 6 are implemented.

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