Model equivalent processing method in energy storage container system simulation calculation

Abstract

The invention discloses a model equivalent processing method in simulation calculation of an energy storage container system, the energy storage container system comprises a battery bin, a water machine bin and a hydrogen pumping chamber, and the model equivalent processing method comprises equivalent simplification processing of the battery bin, the water machine bin and the hydrogen pumping chamber; when equivalent simplification processing is carried out on the battery compartment, the energy source type of a battery pack and a high-voltage box in the battery compartment is selected as a total heat source, a heat power value is input, and heat generated by solar radiation is given to a container shell as heating power; carrying out equivalent simplification treatment on the water machine cabin, namely carrying out equivalent simplification treatment on a fan, filter cotton and a shutter; carrying out equivalent simplification treatment on the hydrogen pumping chamber, namely carrying out equivalent simplification treatment on a fan, filter cotton and a metal mesh pore plate; the complex model is equivalently processed by applying a theoretical modeling mode, so that the calculation precision is not influenced, the number of equivalent model grids is relatively small, the model grids are easy to converge, and the accuracy of a simulation calculation result is greatly ensured.

Description

Technical Field

[0001] The invention relates to the technical field of energy storage containers, and in particular to a model equivalent processing method in simulation calculation of an energy storage container system. Background Art

[0002] With the rapid development of the energy storage industry, the energy storage container system is constantly developing towards a more integrated "container +" direction. The design requirements for its internal liquid cooling system, air cooling system, and hydrogen extraction system are also increasing. It is difficult to complete the complete design based on experience alone. Therefore, it is necessary to use professional CFD simulation software to provide certain data references for the design of the container system.

[0003] Since the internal structure of the energy storage container system is relatively complex and the overall model is relatively large, there are two extreme forms of simulation processing methods for the energy storage container system in the prior art:

[0004] ① During simulation, the model is not simplified, and the entire model is directly divided into grids for calculation. On the one hand, due to the large number of grids, the configuration requirements for the workstation are extremely high, and the calculation is also very time-consuming. On the other hand, the internal structure of the container is relatively complex, the results are not easy to converge, and the correct results cannot be obtained.

[0005] ② The model processing is too simplified during simulation, such as ignoring the influence of louvers, filter cotton pressure drop and the mutual influence of each chamber, which leads to insufficient accuracy of the results and directly affects the selection of key components. Summary of the invention

[0006] In order to solve the above problems, the present invention provides a model equivalent processing method in the simulation calculation of an energy storage container system with a reasonable structure, which not only does not affect the simulation calculation accuracy, but also has a relatively small number of model grids after equivalent and is easy to converge, thereby greatly ensuring the accuracy of the simulation calculation results.

[0007] The technical solution adopted by the present invention is as follows:

[0008] A model equivalent processing method in a simulation calculation of an energy storage container system, wherein the energy storage container system includes a battery compartment, a water machine compartment, and a hydrogen extraction chamber, and the model equivalent processing method includes equivalent simplified processing of the battery compartment, the water machine compartment, and the hydrogen extraction chamber;

[0009] When performing equivalent simplification processing on the battery compartment, the energy source type of the battery pack and high-voltage box in the battery compartment is selected as the total heat source and the thermal power value is input, and the heat generated by solar radiation is given to the container shell as heating power;

[0010] Equivalent simplified treatment of the water machine room, including equivalent simplified treatment of fans, filter cotton and shutters;

[0011] Equivalent simplified treatment of the hydrogen extraction chamber, including equivalent simplified treatment of the fan, filter cotton and metal mesh plate.

[0012] As a further improvement of the above technical solution:

[0013] The air space inside the container is regarded as a heat source, and thermal power is assigned to the heat source to be equivalent to the heat entering the container through the seal.

[0014] The battery pack and high-voltage box in the battery compartment are simplified into a rectangular structure to ensure that the surface area and volume of the model before and after simplification are equivalent.

[0015] Calculate the thermal power value released by the battery pack into the container. The steps are:

[0016] Step 1: Measure the curve of the heating power of the single cell over time by HPPC method;

[0017] Step 2: Establish a battery pack model, perform charge and discharge simulation calculations on a single battery pack model, and obtain a curve of the heat power dissipated into the air by a single battery pack over time at a specific ambient temperature;

[0018] Step 3: Compare the simulation results in step 2 with the battery pack charge and discharge test data to complete parameter calibration;

[0019] Step 4: Calibrate the battery pack model in the second step, and obtain the curve of the change of heat power dissipated into the air over time during the charge and discharge process of a single battery pack at different temperatures through simulation calculation, and finally obtain the curve of the change of average heat power dissipated into the air with temperature;

[0020] Step 5: Combine the number of battery packs to obtain the thermal power value released by the battery pack into the container.

[0021] The heat generated by solar radiation is the heat absorbed by the container under solar radiation. The heat calculation formula is:

[0022]

[0023] Where Q is the heat generated by the outer wall of the container; ε is the emissivity coefficient; σ is the Stefan-Boltzmann coefficient 5.67×10 -8 W / m 2 K 4 ; T H is the absolute temperature of the external environment, in K; T L is the average temperature of the container as a whole, in K; A H is the surface area of ​​the container; t is the time, when t=1s, Q is the heating power.

[0024] A fan interface with zero thickness is used as a simplified model of the fan, and a pressure jump across the fan interface is applied. Planes parallel to the interface are intercepted on both sides of the fan interface, and the static pressure on both sides of the fan is monitored at the plane.

[0025] Since the dimension of the filter cotton in the thickness direction is much smaller than that in other directions, the filter cotton is simplified into a porous baffle with one-dimensional flow resistance. The parameter fitting is performed based on the filter cotton flow rate-pressure drop data set to obtain the inertial resistance coefficient and the viscous resistance coefficient. The interface of the filter cotton is set as the mesh baffle interface, and the inertial resistance coefficient and the viscous resistance coefficient are set.

[0026] Considering the internal structure of the shutter, a three-dimensional model of the shutter entity is established, and the air volume passing through the shutter, the flow field trace diagram of the air inside the shutter, and the pressure drop on both sides of the shutter are obtained by simulation at the system level.

[0027] The resistance coefficient of the metal mesh plate is calculated from the porosity of the metal mesh plate as follows:

[0028]

[0029] Where F is the porosity of the metal mesh plate, l c is the resistance coefficient of the mesh plate;

[0030] The interface of the metal mesh plate is selected as the mesh baffle interface, and the resistance coefficient is set.

[0031] The inlet type of the battery compartment is selected as mass flow inlet, and the outlet type is selected as mass flow outlet; the inlet type of the water machine compartment is selected as pressure inlet, and the outlet type is selected as pressure outlet; the inlet type of the hydrogen extraction chamber is selected as pressure inlet, and the outlet type is selected as pressure outlet.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The idea of ​​the present invention is compact, reasonable, and easy to operate. By using theoretical modeling methods, the energy storage container system with a relatively complex model is equivalently processed, including the battery compartment, the water machine compartment, the fan, the filter cotton, the shutter, and the metal mesh plate in the hydrogen extraction room. Not only does it not affect the calculation accuracy, but the number of model grids after the equivalent is relatively small, and it is easy to converge, which greatly ensures the accuracy of the simulation calculation results.

[0034] The present invention also includes the following advantages:

[0035] In the present invention, the fan entity model is equivalent to the fan interface model, the filter cotton and the metal mesh plate are treated as porous baffles, and the solar radiation is equivalent to the heating of the outer iron sheet of the container. The shutters that affect the selection and calculation results after simplification are not simplified. The calculation process and the calculation results are effectively taken into account, the precision and accuracy of the calculation results are guaranteed, and reliable data reference can be provided for the physical design. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a front view of the energy storage container system of the present invention.

[0037] Figure 2 It is a three-dimensional diagram of the energy storage container system of the present invention.

[0038] Figure 3 This is a simulation flow chart of the energy storage container system of the present invention.

[0039] Figure 4 This is a curve diagram showing the thermal power of a single battery pack of the present invention changing with temperature.

[0040] Figure 5 This is a resistance-wind speed fitting relationship diagram of the filter cotton in a certain embodiment of the present invention.

[0041] Figure 6 A flow chart for performing concomitant shape optimization on the water machine room shutter of the present invention.

[0042] Figure 7 This is a temperature cloud diagram of the energy storage container of the present invention.

[0043] Figure 8 This is a diagram of the internal air velocity trajectory during the flow field simulation of the hydrogen extraction chamber of the present invention.

[0044] Fig. 9 This is the optimized deformation cloud diagram of the shutter surface of the present invention.

[0045] Fig.10 It is a velocity trace diagram in the water machine chamber of the present invention.

[0046] Fig.11 It is a comparison diagram of the pressure drop before and after the optimization of the shutters above the water machine room of the present invention.

[0047] Among them: 10. Hydrogen extraction chamber; 20. Battery compartment; 30. Water machine compartment; 21. Battery pack; 22. High-voltage box. DETAILED DESCRIPTION

[0048] The specific implementation of the present invention will be described below in conjunction with the accompanying drawings.

[0049] like Figure 1 and Figure 2As shown, the model equivalent processing method in the simulation calculation of the energy storage container system of this embodiment, the energy storage container system includes a battery compartment 20, a water machine compartment 30, and a hydrogen extraction chamber 10, and the model equivalent processing method includes equivalent simplified processing of the battery compartment 20, the water machine compartment 30, and the hydrogen extraction chamber 10.

[0050] like Figure 3 As shown in the figure, it is a simulation flow chart of the energy storage container system. After importing the energy storage container model, meshing is performed, including establishing fluid and solid mesh models, physical models, setting parameters and other steps; then boundary conditions and initial conditions are set for each region, and finally simulation calculations are performed to view the results.

[0051] In this embodiment, boundary conditions and initial conditions are set for the battery compartment, water machine compartment, and hydrogen extraction chamber, and equivalent simplified processing is performed at the same time.

[0052] When performing equivalent simplified processing on the battery compartment 20, the energy source type of the battery pack 21 and the high-voltage box 22 in the battery compartment 20 is selected as the total heat source and the thermal power value is input, and the heat generated by solar radiation is given to the container shell in the form of heating power.

[0053] The equivalent simplified processing of the water machine compartment 30 includes the equivalent simplified processing of the fan, the filter cotton, and the shutter.

[0054] The equivalent simplified processing of the hydrogen extraction chamber 10 includes the equivalent simplified processing of the fan, the filter cotton, and the metal mesh plate.

[0055] In this embodiment, the relatively complex energy storage container system is equivalently processed by using theoretical modeling, including the battery compartment 20, the water machine compartment 30, the fan, filter cotton, shutters, and metal mesh plates in the hydrogen extraction chamber 10. This not only does not affect the calculation accuracy, but also the number of model grids after the equivalent is relatively small, and it is easy to converge.

[0056] The inlet type of the battery compartment 20 is selected as a mass flow inlet, and the outlet type is selected as a mass flow outlet; the inlet type of the water machine compartment 30 is selected as a pressure inlet, and the outlet type is selected as a pressure outlet; the inlet type of the hydrogen extraction chamber 10 is selected as a pressure inlet, and the outlet type is selected as a pressure outlet.

[0057] When performing equivalent simplification processing on the battery compartment 20 , the battery pack 21 and the high-voltage box 22 in the battery compartment 20 are equivalently simplified into a rectangular parallelepiped structure to ensure that the surface area and volume of the model before and after simplification are equivalent.

[0058] The steps for calculating the thermal power value released by the battery pack 21 into the container are:

[0059] Step 1: Measure the curve of the heating power of the single cell over time by HPPC method (hybrid pulse power performance test);

[0060] Step 2: Establish a battery pack model, perform charge and discharge simulation calculations on a single battery pack model, and obtain a curve of the heat power dissipated into the air by a single battery pack over time at a specific ambient temperature;

[0061] Step 3: Compare the simulation results in step 2 with the battery pack charge and discharge test data to complete parameter calibration;

[0062] Step 4: Calibrate the battery pack model in the second step. Through simulation calculation, obtain the curve of the heat power lost to the air over time during the charge and discharge process of a single battery pack at different temperatures, and finally obtain the curve of the average heat power lost to the air over temperature, such as Figure 4 As shown, the change curve can be input as the thermal power value of the battery pack 21 according to actual operation;

[0063] Step 5: Combine the number of battery packs to obtain the thermal power value released by the battery pack into the container.

[0064] The thermal power value obtained in the fifth step is used as the thermal power of the battery pack and high-voltage box as the total heat source in the equivalent processing of the battery compartment.

[0065] In actual operation, after the thermal power value of the battery pack 21 is calculated, the heating power can also be directly assigned to the high voltage box.

[0066] In this embodiment, the battery pack 21 and the high voltage box are both heat sources.

[0067] In a high temperature environment with direct sunlight, the heat generated by solar radiation cannot be ignored. Since the container is not a black body, it will radiate some heat when receiving solar thermal radiation, and it will also absorb some heat. In the process of model simplification, the thermal insulation cotton and container shell are retained. In the process of thermal simulation, the heat radiation absorbed by the container system under solar radiation is assigned to the container shell.

[0068] The heat generated by solar radiation is the heat absorbed by the container under solar radiation. The calculation formula is:

[0069]

[0070] Where Q is the heat generated by the outer wall of the container; ε is the emissivity coefficient; σ is the Stefan-Boltzmann coefficient 5.67×10 -8 W / m 2 K 4 ; T H is the absolute temperature of the external environment, in K; T L is the average temperature of the container as a whole, in K; A His the surface area of ​​the container; t is the time, when t=1s, Q is the heating power.

[0071] For example, when the external environment is 318K (45°C), the overall average temperature of the container is 308K (35°C) and the surface area is 39m 2 , when the time is 1s, the radiation heat Q absorbed by the container is:

[0072] Q = 0.5 × 5.67 × 10 -8 ×(318 4 -308 4 )×39×1=1357J

[0073] Therefore, in the process of equivalent simplified processing of the energy storage container, the thermal power generated by solar radiation, that is, the heating power given to the container shell, is 1357W.

[0074] In the actual use of energy storage containers, some heat will enter the interior of the container through seals and other components, and this part of heat cannot be ignored. In the equivalent simplified processing of thermal simulation, the air domain inside the container is used as a heat source, and thermal power is assigned to the heat source to be equivalent to the heat entering the interior of the container through the seals.

[0075] In actual operation, the amount of heat that enters the container through the seal is related to the size of the container and the insulation effect, and can be calculated based on the specific container.

[0076] In this embodiment, the heat source of the energy storage container mainly comes from three parts, namely, 1) the heat generated by the battery pack and high-voltage box in the battery compartment, which is the total heat source; 2) the heat generated by the outer wall of the container under solar radiation; 3) the heat that enters the interior of the container through components such as seals; while the total heat source of the battery compartment is equivalently simplified, the other two heat sources are also equivalently treated.

[0077] In the CFD simulation process, the fan model is complex and difficult to converge, so the fan is simplified. A fan interface with zero thickness is used as a simplified model of the fan, and a pressure jump across the fan interface is applied; planes parallel to the interface are intercepted on both sides of the fan interface, and the static pressure on both sides of the fan is monitored at the plane.

[0078] Since the pressure difference value of the fan is equal to the resistance value of the entire system, the size of the resistance value directly determines the size of the system flow rate, so in this embodiment, the static pressure on both sides of the fan is monitored.

[0079] During the simulation operation, extract the data of the existing fan PQ curve, obtain the fan PQ curve Excel table, import the fan PQ curve table, select the fan interface type as fan interface, the PQ curve input type as table, select the pressure drop and flow units, and select to open the fan redundancy detailed instructions.

[0080] The pressure difference of the fan corresponds to P in the fan PQ curve, and Q is the system flow rate. By importing the fan PQ curve table, this embodiment does not need to establish a complete fan model, but can fully reflect the function of the fan.

[0081] To prevent dust from entering the interior with the air, filter cotton will be installed at the openings of the water machine room and the hydrogen extraction room.

[0082] Since the dimension of the filter cotton in the thickness direction is much smaller than that in other directions, the filter cotton is simplified into a porous baffle with one-dimensional flow resistance. The parameter fitting is performed based on the filter cotton flow rate-pressure drop data set to obtain the inertial resistance coefficient and the viscous resistance coefficient. The interface of the filter cotton is set as the mesh baffle interface, and the inertial resistance coefficient and the viscous resistance coefficient are set.

[0083] The calculation of inertial drag coefficient and viscous drag coefficient can be carried out as follows:

[0084] For a porous baffle, the pressure drop Δp is:

[0085] Δp=-ρ(P i |v s,n |+P v )v s,n

[0086] Among them, v s,n is the surface normal velocity; P i is the porous inertial resistance coefficient; P v is the porous viscous drag coefficient and ρ is the air density; the inertial drag coefficient and the viscous drag coefficient effectively define the baffle permeability for one-dimensional flow.

[0087] The filter cotton resistance-wind speed data set is fitted, and the fitting expression is:

[0088] Δp=av 2 +bv

[0089] Among them, a and b are constants obtained by fitting the formula.

[0090] Since, Δp=-ρ(P i |v s,n |+P v )v s,n =av 2 +bv.

[0091] Then: Inertial resistance coefficient P i =a / ρ, viscous resistance coefficient P v =b / ρ.

[0092] In one embodiment, the resistance-wind speed data set of the filter cotton is shown in Table 1 below:

[0093] Table 1: Filter resistance-wind speed data

[0094]

[0095]

[0096] The data in the table are converted into Δp=av 2 +bv for fitting, such as Figure 5 As shown, the expression is obtained:

[0097] Δp=1.5607x 2 +1.6335x

[0098] The air density ρ is 1.175 kg / m 3 , and obtain the inertial resistance coefficient P i =a / ρ=1.33, viscous resistance coefficient P v =b / ρ=1.39.

[0099] During the simulation of the hydrogen extraction chamber, the metal mesh plate will produce a certain resistance to the air. The interface of the metal mesh plate is selected as the mesh baffle interface, and the resistance coefficient is set.

[0100] The resistance coefficient of the metal mesh plate is calculated from the porosity of the metal mesh plate as follows:

[0101]

[0102] Where F is the porosity of the metal mesh plate, l c is the resistance coefficient of the mesh plate.

[0103] For a metal mesh plate with a porosity of 79%, its resistance coefficient is 0.5841; the specific value of the resistance coefficient will directly affect the flow resistance of the system. The resistance coefficient is taken into consideration in this embodiment. Compared with the method of only inputting the porosity without clarifying the resistance coefficient in the existing simulation, this embodiment is closer to the real flow field near the metal mesh plate in actual use.

[0104] In the process of flow field simulation of the water machine chamber, the internal structure of the shutter is considered, and a three-dimensional model of the shutter entity is established. The air volume passing through the shutter at the system level, the flow field trajectory diagram of the air inside the shutter, and the pressure drop on both sides of the shutter are obtained by simulation, which is helpful for the design and selection of the shutter.

[0105] In the existing simulation, the physical structure of the shutter is ignored, the fluid domain inside the shutter is not extracted, only the cross-sectional shape of the shutter is selected, and then the depth and width values ​​are input. The software automatically generates a calculation model of the shutter for simulation calculation. No physical model of the shutter is established during the simulation process, and there is a large error between the calculation result and the actual result. In this embodiment, the flow field simulation is performed based on the physical three-dimensional model of the shutter, which is more helpful for the design and selection of the shutter.

[0106] At the same time, a shape optimization model of the blinds can also be established to optimize the blinds model structure at the system level to reduce the wind resistance of the blinds.

[0107] In actual operation, Figure 6 As shown in the figure, the steps for adjoint shape optimization of the blinds are:

[0108] 1) Import the 3D model of the water machine, select the mesh model, and divide the mesh.

[0109] 2) Select the physical model, which includes the coupled solver and the adjoint solver.

[0110] 3) Set the water machine fan interface, porous baffle parameters, and inlet and outlet boundary conditions, etc.

[0111] 4) Since the optimization goal is to reduce the total pressure drop on both sides of the water machine louver, a new pressure drop report on both sides of the louver is created, and the pressure drop on both sides of the louver is set as the accompanying cost function.

[0112] 5) Establish the maximum deflection angle and minimum surface validity report of the blinds mesh (for later determination of whether to continue optimization).

[0113] 6) Establish the automatic operation steps of the adjoint shape optimization. First, calculate the initial water machine model flow field, then calculate the adjoint function and the surface sensitivity of the shutter, and finally deform the mesh according to the surface sensitivity and check the mesh quality. If the mesh quality meets the requirements of the maximum deflection angle and the minimum surface, use the optimized geometry to solve the original fluid, otherwise end the simulation process.

[0114] 7) Set the solver parameters (set the CFL control method to automatic and the expert initialization method to the grid sequence method), and set a fixed number of steps as the stopping criterion.

[0115] CFL is named after the initials of Courant, Friedrichs, and Lewy. The CFL number is the basis for judging convergence and stability in numerical simulation of fluid mechanics, which means that the dependent domain of the difference equation must contain the dependent domain of the corresponding differential equation.

[0116] The CFL condition is a necessary condition for stability and convergence in numerical simulation of flow fields.

[0117] 8) Define a deformation displacement field to optimize the louver surface. The deformation displacement field is calculated using the cumulative deformation displacement, the adjoining surface sensitivity field, and the steepest descent constant. The steepest descent constant controls the deformation amplitude of the surface during the optimization cycle and is set to -1.0E-3. Define the deformation field as: $${cumulative deformation displacement}+${steepest descent constant}*$${adjoining surface sensitivity field}, and assign the field function to the louver boundary to be optimized.

[0118] 9) Create a blinds shape optimization scenario and run the calculation.

[0119] like Figure 7 As shown, it is a temperature cloud map of the energy storage container in this embodiment, which can intuitively display the temperature of each component of the entire energy storage container system, so as to optimize the distribution position of each component.

[0120] like Figure 8 As shown, when simulating the flow field of the hydrogen extraction chamber in this embodiment, the air velocity trajectory diagram inside the energy storage container can be intuitively displayed, and the parts inside the container system where the gas is not flowing can be clearly seen so as to optimize the parts.

[0121] like Fig. 9 As shown, it is the deformation cloud diagram of the optimized surface of the shutter of this embodiment, which can intuitively show the structural changes of the optimized model of the shutter relative to the original model.

[0122] like Fig.10 As shown, it is a velocity trace diagram in the water machine compartment of this embodiment, which can intuitively display the air velocity and flow field distribution inside the water machine so as to optimize the water machine system.

[0123] like Fig.11 As shown, it is a comparison diagram of the pressure drop before and after the optimization of the shutters above the water machine compartment of this embodiment, which intuitively displays the velocity cloud map and pressure drop changes before and after the optimization of the shutters, and can better show the optimization effect. The pressure drop before optimization is 52.4Pa, and the pressure drop after optimization is 19.3Pa.

[0124] In this embodiment, the fan entity model is equivalent to the fan interface model, the filter cotton and metal mesh plate are treated as porous baffles, and the solar radiation is equivalent to the heating of the outer iron sheet of the container. The shutters that affect the selection and calculation results after simplification are not simplified. This effectively takes into account the calculation process and the calculation results, ensures the precision and accuracy of the calculation results, and can provide reliable data reference for physical design.

[0125] The present invention is simple to operate and performs equivalent processing on the fan, filter cotton, shutter and metal mesh plate in the battery compartment, the water machine compartment and the hydrogen extraction chamber. Not only does it not affect the calculation accuracy, but the number of model grids after the equivalent is relatively small and easy to converge, which greatly ensures the accuracy of the simulation calculation results.

[0126] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0127] The above description is an explanation of the present invention, not a limitation of the present invention. The scope of the present invention is defined in the claims. Any form of modification may be made within the scope of protection of the present invention.

Claims

1. A model equivalent processing method in the simulation calculation of an energy storage container system, characterized in that: The energy storage container system includes a battery compartment, a water machine compartment, and a hydrogen extraction chamber, and the model equivalent processing method includes equivalent simplified processing of the battery compartment, the water machine compartment, and the hydrogen extraction chamber; When performing equivalent simplification processing on the battery compartment, the energy source type of the battery pack and high-voltage box in the battery compartment is selected as the total heat source and the thermal power value is input, and the heat generated by solar radiation is given to the container shell as heating power; The equivalent simplified treatment of the water machine room includes the equivalent simplified treatment of the fan, filter cotton, and shutters; the equivalent simplified treatment of the hydrogen extraction room includes the equivalent simplified treatment of the fan, filter cotton, and metal mesh plate.

2. The model equivalent processing method in the energy storage container system simulation calculation according to claim 1, characterized in that: The air space inside the container is regarded as a heat source, and thermal power is assigned to the heat source to be equivalent to the heat entering the container through the seal.

3. The model equivalent processing method in the energy storage container system simulation calculation according to claim 1, characterized in that: The battery pack and high-voltage box in the battery compartment are simplified into a rectangular structure to ensure that the surface area and volume of the model before and after simplification are equivalent.

4. The model equivalent processing method in the energy storage container system simulation calculation according to claim 1, characterized in that: Calculate the thermal power value released by the battery pack into the container. The steps are: Step 1: Measure the curve of the heating power of the single cell over time by HPPC method; Step 2: Establish a battery pack model, perform charge and discharge simulation calculations on a single battery pack model, and obtain a curve of the heat power dissipated into the air by a single battery pack over time at a specific ambient temperature; Step 3: Compare the simulation results in step 2 with the battery pack charge and discharge test data to complete parameter calibration; Step 4: Calibrate the battery pack model in the second step, and obtain the curve of the change of heat power dissipated into the air over time during the charge and discharge process of a single battery pack at different temperatures through simulation calculation, and finally obtain the curve of the change of average heat power dissipated into the air with temperature; Step 5: Combine the number of battery packs to obtain the thermal power value released by the battery pack into the container.

5. The model equivalent processing method in the energy storage container system simulation calculation according to claim 1, characterized in that: The heat generated by solar radiation is the heat absorbed by the container under solar radiation. The heat calculation formula is: Where Q is the heat generated by the outer wall of the container; ε is the emissivity coefficient; σ is the Stefan-Boltzmann coefficient 5.67×10 - 8 W / m 2 K 4 ; T H is the absolute temperature of the external environment, in K; T L is the average temperature of the container as a whole, in K; A H is the surface area of ​​the container; t is the time, when t=1s, Q is the heating power.

6. The model equivalent processing method in the energy storage container system simulation calculation according to claim 1, characterized in that: A fan interface with zero thickness is used as a simplified model of the fan, and a pressure jump across the fan interface is applied. Planes parallel to the interface are intercepted on both sides of the fan interface, and the static pressure on both sides of the fan is monitored at the plane.

7. The model equivalent processing method in the energy storage container system simulation calculation according to claim 1, characterized in that: Since the dimension of the filter cotton in the thickness direction is much smaller than that in other directions, the filter cotton is simplified into a porous baffle with one-dimensional flow resistance. The parameter fitting is performed based on the filter cotton flow rate-pressure drop data set to obtain the inertial resistance coefficient and the viscous resistance coefficient. The interface of the filter cotton is set as the mesh baffle interface, and the inertial resistance coefficient and the viscous resistance coefficient are set.

8. The model equivalent processing method in the energy storage container system simulation calculation according to claim 1, characterized in that: Considering the internal structure of the shutter, a three-dimensional model of the shutter entity is established, and the air volume passing through the shutter, the flow field trace diagram of the air inside the shutter, and the pressure drop on both sides of the shutter are obtained by simulation at the system level.

9. The model equivalent processing method in the energy storage container system simulation calculation according to claim 1, characterized in that: The resistance coefficient of the metal mesh plate is calculated from the porosity of the metal mesh plate as follows: Where F is the porosity of the metal mesh plate, l c is the resistance coefficient of the mesh plate; The interface of the metal mesh plate is selected as the mesh baffle interface, and the resistance coefficient is set.

10. The model equivalent processing method in the energy storage container system simulation calculation according to claim 1, characterized in that: The inlet type of the battery compartment is selected as mass flow inlet, and the outlet type is selected as mass flow outlet; the inlet type of the water machine compartment is selected as pressure inlet, and the outlet type is selected as pressure outlet; the inlet type of the hydrogen extraction chamber is selected as pressure inlet, and the outlet type is selected as pressure outlet.

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