Battery eruption particulate matter deposition heat transfer calculation method based on CFD-DEM coupling

Abstract

The invention discloses a method for calculating deposition heat transfer of battery erupted particles based on CFD-DEM coupling, which simulates and evaluates the influence of deposition heat transfer of the battery erupted particles on thermal runaway safety of other batteries aiming at the multiphase flow behavior of lithium ion battery thermal runaway erupted high-temperature flue gas and particles. Firstly, information such as components, mass flow and temperature of battery eruption smoke and particles is measured through experiments, then diffusion of the smoke is simulated through a CFD method, the concentration and density of the smoke at all positions are obtained, collision and deposition behaviors between the particles and between the particles and a wall surface are simulated through a DEM discrete element method, particle information is transmitted to the CFD for calculation, and the concentration and density of the particles are obtained. Particle-wall surface contact judgment is introduced, finally, the coupling acting force and heat transfer capacity between particles and flue gas are calculated, and state information of a flow field and particulate matter is updated. According to the method, the thermal runaway accident risk of the battery system is evaluated after simulated particles are deposited, including temperature changes among particles, a flow field and a battery assembly.

Description

Technical Field

[0001] The present application relates to the technical field of physical field coupling simulation, and in particular to a method for calculating the deposition and heat transfer of battery eruption particles based on CFD-DEM coupling. Background Art

[0002] At present, power batteries represented by lithium-ion batteries are prone to battery thermal runaway accidents under the influence of external mechanical, thermal, and electrical abuse factors, which seriously endanger the safety of users' lives and property. When the battery is in thermal runaway, the process in which the smoke generated by various internal thermal runaway reactions breaks through the battery safety valve and brings out a large amount of particulate matter is a typical feature of battery thermal runaway. After a large amount of high-temperature particulate matter is deposited on the surface of the battery system, it transfers heat to the surface of the battery components, heats the battery, and accelerates the spread of battery thermal runaway and triggers thermal runaway of other batteries, causing cascade accidents.

[0003] Battery eruption particles are characterized by high speed, high temperature, and a high proportion of metal elements. Previous simulations of battery eruption products have focused on smoke diffusion, and have rarely considered the impact of particles on battery thermal runaway. And because particles are discrete media, they diffuse in the smoke after being ejected from the battery and are deposited as the smoke moves. Traditional CFD methods for simulating continuous media have difficulty accurately simulating the behavior of particles, and cannot consider collisions and contact heat transfer between particles and between particles and the walls of the battery system, resulting in the inability to assess the risk of battery thermal runaway accidents caused by particles. Summary of the invention

[0004] Based on the current technical problems raised in the background technology, the present invention provides a calculation method for the deposition and heat transfer of battery eruption particles based on CFD-DEM coupling. Aiming at the multiphase flow behavior of high-temperature flue gas and particles erupted by thermal runaway of lithium-ion batteries, the present invention simulates and evaluates the influence of the deposition and heat transfer of high-temperature particles erupted by thermal runaway of batteries on the safety of thermal runaway of other batteries, and helps to assist the safety design of battery systems. The specific technical scheme is as follows:

[0005] In the discrete element program, a particle model is constructed to set the shape, size, mechanical / thermal property parameters of the battery eruption particles, as well as the contact model describing the force between particles and the particle injection method. In the CFD program, the flow field geometry of the battery system is established, and the corresponding calculation grid is divided according to the battery eruption smoke domain, and the component type and mass fraction, mass flow rate, temperature and flue gas flow domain boundary pressure of the battery thermal runaway eruption smoke are set.

[0006] The overall control equation of CFD-DEM coupling of particulate matter and flue gas is as follows:

[0007] The mass continuity equation for smoke diffusion, assuming that there is no mass source in the smoke diffusion:

[0008]

[0009] where ρ f is the smoke density, ε f represents the smoke fraction of the fluid, is the velocity of the smoke.

[0010] Momentum conservation equation for smoke diffusion:

[0011]

[0012] Where P is the flue gas pressure, is the stress tensor of the flue gas, is the interaction force between smoke and particles, and g is the acceleration of gravity.

[0013] Energy equation for smoke diffusion:

[0014]

[0015] Among them, c f is the constant pressure specific heat capacity of flue gas, T f is the flue gas temperature, λ f is the thermal conductivity of flue gas, q P is the heat exchange between flue gas and particulate matter.

[0016] Construct the motion and force balance equations of a single particle based on Newton's laws:

[0017]

[0018] Among them, m p is the mass of the particles, is the velocity of the particle, is the contact and collision force between particles and between particles and the wall. is the force exerted by smoke on particulate matter.

[0019] The heat transfer equation for a single particle based on energy conservation is:

[0020]

[0021] Among them, Q c is the heat transfer due to contact and collision between particles and between particles and the wall, Q f It is the convection heat transfer between particles and flue gas.

[0022] In CFD-DEM coupling, the characteristics of the particle group are reflected by tracking the changes in the velocity, position, and temperature of a large number of particles. The coupling between smoke and particles is reflected through the phase interaction force and convective heat transfer.

[0023] Since the flue gas emitted by battery thermal runaway contains multiple components such as CO, CO2, H2, CH4, etc., the components and mass fractions of the flue gas can be measured by using a meteorological mass spectrometer after collecting the flue gas. In the coupled calculation, the physical properties of the flue gas in each fluid calculation grid are calculated based on the weighted mass fraction of each component:

[0024]

[0025] In the above formula, is the physical parameters of the flue gas at various locations in the flow field (specifically, the density, specific heat capacity, thermal conductivity, and viscosity of the flue gas), m i is the mass fraction of each component in the flue gas at each location, are the physical properties parameters of each component.

[0026] In the flow field, because the particles actually occupy a certain volume of space, each CFD fluid calculation grid does not only contain smoke, so it is necessary to update and calculate the smoke gas volume fraction in each grid according to the particle position:

[0027]

[0028] in, is the total volume of particles in the CFD calculation grid, V cell To calculate the volume of the grid.

[0029] The contact model in the discrete element DEM program is deeply developed, and the coordinates of the contact point between the particle and the wall and the normal force of the collision between the particle and the wall in the contact model are used as the inherent properties of the particle.

[0030] In the discrete element program, the data structure describing the particles is expanded to add custom attribute values ​​of the particles: the spatial coordinates of the contact point between the particle and the wall and the normal force between the particle and the battery wall;

[0031] On the basis of the original contact model (such as the Hertz Mindlin model), the coupling between the new custom attribute and the contact model is realized. In the particle collision detection step in the discrete element program, if a particle is found to collide with a wall, the spatial coordinates and normal force of the contact point where the particle collides with the wall are calculated through the geometric relationship between the contact model and the particle, and the custom attribute value is updated. If the particle does not collide with the wall at the current time step, the attribute value is not updated, and the attribute value updated at the last collision is maintained.

[0032] In the discrete element and computational fluid dynamics coupling program, the particle data structure class transmitted by the discrete element to the computational fluid dynamics program is expanded accordingly. The information in the particle data structure includes the particle center coordinates, particle radius, particle temperature, particle and wall collision contact point coordinates, and the normal force of particle and wall collision. The above values ​​of each particle are different, and the information of each particle is a specific object instance of the particle data structure class. The information of all particles is merged into a class array and written into the computer memory. The CFD program obtains the information of all particles in the flue gas flow domain in the CFD-DEM coupling time step by accessing the memory.

[0033] In the CFD program, a global coordinate index table is constructed. The function of the index table is to find the CFD calculation grid index containing the given coordinates of a certain point in space. The specific construction process is as follows:

[0034] In CFD calculations, after constructing the geometric model of the flue gas flow basin and battery area in the battery system and dividing the computational grids. Traverse all computational grids, extract the center coordinates of each computational grid, the spatial coordinates of each vertex of the computational grid, the properties of the computational grid (flue gas flow basin or battery solid area), and the computational grid index, and merge them into a global coordinate index table. Given any spatial coordinate position, traverse the global coordinate index table, calculate the distance between the spatial coordinate position and the grid center, filter out a series of computational grids with the closest distance, and then substitute the spatial coordinate position into the vertex coordinates of the computational grid to determine whether the spatial coordinate position is inside the computational grid. If it is inside a computational grid, it means that the particle is within the spatial range of the computational grid. According to the grid index value, find the grid in the CFD program.

[0035] From the DEM program, obtain the coordinates of the contact point between the particle and the wall and the coordinates of the particle center, and use the index table to find the computational grid containing the particle. Then traverse each mesh surface in the computational grid, find the wall surface that collides with the particle, and obtain the temperature of the collision surface grid. It should be noted that in the discrete element program, the simulation time step of the particle is inconsistent with the time step of the smoke simulation in CFD. The time step of the smoke simulation is about 10-50 times the time step of the particle simulation. Since the contact point attribute value of the particle is updated once the particle collides with the wall, in the current CFD calculation step, the coordinates of the particle and wall collision point are not necessarily the coordinates of the particle and wall collision point in the current smoke. It may be the coordinates of the particle and wall collision in the previous discrete element time step. Therefore, in the CFD program, the particle and the wall need to perform secondary collision detection. Calculate the distance between the coordinates of the particle center and the wall collision point. If the distance exceeds the particle radius, it means that the particle has not collided with the wall at the current moment. If it is less than or equal to the particle radius, it is judged that the particle is in contact with the wall.

[0036] In the CFD program, the calculation grid containing the particle is found using the index table according to the coordinates of the collision point between the particle and the wall and the coordinates of the center of the particle, and the temperature of the collision wall grid is obtained. Then the contact heat transfer coefficient of the particle hitting the wall is calculated by the physical parameters and mechanical parameters of the particle. The calculation of the contact heat transfer coefficient between particles and between particles and walls is carried out through contact models, experimental measurements and empirical models. There are many forms of contact heat transfer coefficient calculation model methods. In the present invention, the most widely used contact heat transfer coefficient calculation model is taken as an example:

[0037] Q c =h c ΔT p1p2 (8)

[0038]

[0039] Among them, h c To take into account the heat transfer coefficient of the contact heat transfer area, ΔT p1p2 is the temperature difference between particles and between particles and the wall, k p1 and k p2 are the thermal conductivity of the two particles or the particles and the wall, respectively. N is the normal force on the contact point, E * is the equivalent elastic modulus of the two particles or the particle and the wall in collision contact, r * is the geometric mean radius of the particles calculated by contact theory. All three can be derived from the contact model (Heartz Mindlin) model.

[0040] The heat transfer caused by particles hitting the wall is calculated by the convective heat transfer formula, and according to the principle of energy conservation, the heat transfer is converted into the volume heat source of the wall grid and loaded into the wall unit of the CFD calculation. The calculation equation of the volume heat source is:

[0041]

[0042] The heat transfer amount is then written into the particle data structure class object as the heat dissipation of the particle itself.

[0043] In the CFD program, the interphase force and convective heat transfer between the flue gas and the particles are converted into volume force source terms and volume heat source terms and loaded on the computational grid containing the particle. Then the flue gas force and convective heat transfer on the particle are written into the particle data structure of the particle and transmitted to the DEM calculation. The flow field CFD calculation is performed according to the preset time step t f , the discrete element calculation is based on the time step t p , update the state information of the flow field and particles, and perform two-phase coupling calculations according to preset steps.

[0044] Among them, the interaction between particles and smoke The force of smoke on particulate matter in equation (4) It is a pair of interacting forces, whose components include drag, buoyancy, lift, thermophoresis, etc. Among them, drag is the force with the highest proportion. Taking the drag of the flue gas on the particle as an example, the basic form of drag is shown in the following formula:

[0045]

[0046] In the above formula, C d is the drag coefficient, determined by experimental method and drag model, It is the difference between the particle velocity and the flue gas velocity at the location of the particle, that is, the relative velocity between the particle and the flue gas. p is the projected area of ​​the particle in the direction of relative velocity.

[0047] The selection of the drag model is related to the flow state of the smoke and the volume fraction of the smoke in the space. Taking the Gidaspow drag model as an example, the calculation of the drag coefficient depends on the characteristic parameter Reynolds number Re that characterizes the flow field state. p And volume share:

[0048]

[0049] For a single particle, the force of smoke on the particle represented by the drag force is directly loaded into the momentum conservation equation of the particle, while the reaction force of the drag force on the smoke needs to be converted into the volume momentum source term:

[0050]

[0051] The contact and collision forces between particles and between particles and walls are calculated based on the contact model of discrete elements. Through the contact model, the normal and tangential components of the force can be obtained. The normal force represents the depth of particle collision and contact, which is the key basis for calculating the contact heat transfer coefficient. In DEM, the corresponding contact model is selected based on the differences in particle properties, such as whether viscosity is considered, whether it is a spherical particle, and whether particle breakage is considered.

[0052] The calculation of the heat transfer between particles and smoke is related to the Reynolds number of smoke diffusion. For example, in the case of low Reynolds number, the Ranz model is used. The specific calculation method can also be measured experimentally. There are many forms. The present invention takes the Ranz model as an example:

[0053] Q f =h f (T p -T f ) (14)

[0054]

[0055] In the above formula, Nu i is the Nusselt number, d i is the characteristic length of smoke flow, k f is the thermal conductivity, Pr is the Prandtl number, Re i is the Reynolds number. f is the heat transfer coefficient.

[0056] Similarly, the coupled heat transfer between the flue gas and the particles is equal in value, but opposite in sign, which means that if the flue gas transfers heat to the particles, the particles are heated by the flue gas, and the flue gas itself introduces a negative energy source. For the update of the particle's own temperature, an iterative solution is performed based on formula (5). For CFD calculations, the particle heat transfer also needs to be converted into a body heat source:

[0057]

[0058] This process is repeated until the preset simulation time is met, and the thermal runaway safety of the battery system is evaluated based on the calculation results of the global temperature field of the battery system.

[0059] The present invention is based on the CFD-DEM coupling method to simulate the multiphase flow behavior of high-temperature particles dispersed in the flue gas during thermal runaway of the battery and diffused in the battery system with the flue gas. This makes up for the deficiency of existing CFD methods that it is difficult to directly simulate the safety hazards of high-temperature particle deposition to the battery system. Based on discrete element simulation, the present invention does not need to simplify the particles too much, select and calibrate different contact models, and can also consider the influence of particle shape and physical properties on particle deposition and heat transfer.

[0060] Another beneficial effect of the present invention is that it has certain scalability advantages. Under the framework of the method of the present invention, by adding more particle properties, other field forces such as electromagnetic force that particles are subjected to in the flow field can be considered. Specific particle deposition information can also be obtained, such as the average temperature, particle size, and deposition mass of the deposited particles to consider other battery thermal safety accident mechanisms induced by particles. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the figures required for use in the embodiments of the present application or related technical descriptions are briefly introduced below. Obviously, the figures described below are only some embodiments of the present application. For ordinary technicians in this field, other related figures can be obtained based on these figures without paying creative work.

[0062] Figure 1This is a calculation flow chart of a battery eruption particle deposition and heat transfer method based on CFD-DEM coupling according to the present invention;

[0063] Figure 2 This is a schematic diagram of the particle-wall contact collision detection principle of the present invention;

[0064] Figure 3 This is a schematic diagram of particle heat transfer and volume heat source conversion described in the present invention. DETAILED DESCRIPTION

[0065] In order to better illustrate the battery eruption particle deposition heat transfer method based on CFD-DEM coupling described in the present invention, an implementation example of the present invention is given below using the specific discrete element program DEM and the CFD program Fluent.

[0066] The specific calculation method flow chart of the present invention is as follows: Figure 1 As shown:

[0067] Initialize the flow field in Fluent, set the inlet boundary conditions according to the measured flue gas incident mass flow, composition, and temperature, set the initial pressure, temperature, and gas composition of the flow field in the battery system, establish a particle model in EDEM, and set the mass flow, temperature, incident position generation position, and speed of the inlet particles according to the measured results. Establish a grid index table in Fluent;

[0068] Start flow field calculation in Fluent, obtain particle information (particle temperature, particle center position, particle-wall contact point coordinates, particle radius, particle movement speed, and normal force between particles and walls) from EDEM, and prepare to calculate the coupled heat transfer between particles and battery walls and the heat transfer and coupled force between particles and flue gas;

[0069] Different from the conventional CFD-DEM coupling method, the present invention needs to calculate the coupled heat transfer between the particle and the battery wall to realize the conjugate heat transfer between the particle temperature and the battery surface. Through the particle center position and the contact point position, the CFD calculation grid where the particle is located is found according to the index table, the flue gas density, velocity, and temperature information of the grid are obtained, and contact judgment is performed to calculate the heat transfer between the particle and the wall, the coupled force and heat transfer between the particle and the flue gas, and load them into Fluent as heat source / momentum source items, update the flow field calculation results, and save the data at the same time, and pass them to EDEM as the basis for updating the particle temperature and stress state;

[0070] Start EDEM discrete element calculation. EDEM obtains the resultant force of the flow field acting on the particles and the total heat transferred by the particles from Fluent. It performs particle dynamics iterative calculation according to equations (4) and (5), calculates the collision force between particles and between particles, and updates the temperature, velocity, and spatial position of the particles. It then performs contact judgment and updates the center coordinates, velocity, temperature, and contact point coordinates of the particles.

[0071] EDEM updates the discrete element according to the time step tp, and the flow field is updated and iterated according to the time step tf. tf is 10 to 100 tp. After multiple EDEM calculations and multiple particle state updates, the particle state data is passed to Fluent, and the Fluent flow field calculation is restarted.

[0072] Repeat steps 2 to 5 above until the convergence condition and the preset simulation time scale are reached.

[0073] The overall control equation of CFD-DEM coupling of particulate matter and flue gas is as follows:

[0074] The mass continuity equation for smoke diffusion, assuming that there is no mass source in the smoke diffusion:

[0075]

[0076] where ρ f is the smoke density, ε f represents the smoke fraction of the fluid, is the velocity of the smoke.

[0077] Momentum conservation equation for smoke diffusion:

[0078]

[0079] Where P is the flue gas pressure, is the stress tensor of the flue gas, is the interaction force between smoke and particles, and g is the acceleration of gravity.

[0080] Energy equation for smoke diffusion:

[0081]

[0082] Among them, c f is the constant pressure specific heat capacity of flue gas, T f is the flue gas temperature, λ f is the thermal conductivity of flue gas, q P is the heat exchange between flue gas and particulate matter.

[0083] Construct the motion and force balance equations of a single particle based on Newton's laws:

[0084]

[0085] Among them, m p is the mass of the particles, is the velocity of the particle, is the contact and collision force between particles and between particles and the wall. is the force exerted by smoke on particulate matter.

[0086] The heat transfer equation for a single particle based on energy conservation is:

[0087]

[0088] Among them, Q c is the heat transfer due to contact and collision between particles and between particles and the wall, Q f It is the convection heat transfer between particles and flue gas.

[0089] In CFD-DEM coupling, the characteristics of the particle group are reflected by tracking the changes in the velocity, position, and temperature of a large number of particles. The coupling between smoke and particles is reflected through the phase interaction force and convective heat transfer.

[0090] Since the flue gas emitted by battery thermal runaway contains multiple components such as CO, CO2, H2, CH4, etc., the components and mass fractions of the flue gas can be measured by using a meteorological mass spectrometer after collecting the flue gas. In the coupled calculation, the physical properties of the flue gas in each fluid calculation grid are calculated based on the weighted mass fraction of each component:

[0091]

[0092] In the above formula, is the physical parameters of the flue gas at various locations in the flow field (specifically, the density, specific heat capacity, thermal conductivity, and viscosity of the flue gas), m i is the mass fraction of each component in the flue gas at each location, are the physical properties parameters of each component.

[0093] In the flow field, because the particles actually occupy a certain volume of space, each CFD fluid calculation grid does not only contain smoke, so it is necessary to update and calculate the smoke gas volume fraction in each grid according to the particle position:

[0094]

[0095] in, is the total volume of particles in the CFD calculation grid, V cell To calculate the volume of the grid.

[0096] The contact model in the discrete element DEM program is deeply developed, and the coordinates of the contact point between the particle and the wall and the normal force of the collision between the particle and the wall in the contact model are used as the inherent properties of the particle.

[0097] In the discrete element program, the data structure describing the particles is expanded to add custom attribute values ​​of the particles: the spatial coordinates of the contact point between the particle and the wall and the normal force between the particle and the battery wall;

[0098] On the basis of the original contact model (such as the Hertz Mindlin model), the coupling between the new custom attribute and the contact model is realized. In the particle collision detection step in the discrete element program, if a particle is found to collide with a wall, the spatial coordinates and normal force of the contact point where the particle collides with the wall are calculated through the geometric relationship between the contact model and the particle, and the custom attribute value is updated. If the particle does not collide with the wall at the current time step, the attribute value is not updated, and the attribute value updated at the last collision is maintained.

[0099] In the discrete element and computational fluid dynamics coupling program, the particle data structure class transmitted by the discrete element to the computational fluid dynamics program is expanded accordingly. The information in the particle data structure includes the particle center coordinates, particle radius, particle temperature, particle and wall collision contact point coordinates, and the normal force of particle and wall collision. The above values ​​of each particle are different, and the information of each particle is a specific object instance of the particle data structure class. The information of all particles is merged into a class array and written into the computer memory. The CFD program obtains the information of all particles in the flue gas flow domain in the CFD-DEM coupling time step by accessing the memory.

[0100] In the CFD program, a global coordinate index table is constructed. The function of the index table is to find the CFD calculation grid index containing the given coordinates of a certain point in space. The specific construction process is as follows:

[0101] In CFD calculations, after constructing the geometric model of the flue gas flow basin and battery area in the battery system and dividing the computational grids. Traverse all computational grids, extract the center coordinates of each computational grid, the spatial coordinates of each vertex of the computational grid, the properties of the computational grid (flue gas flow basin or battery solid area), and the computational grid index, and merge them into a global coordinate index table. Given any spatial coordinate position, traverse the global coordinate index table, calculate the distance between the spatial coordinate position and the grid center, filter out a series of computational grids with the closest distance, and then substitute the spatial coordinate position into the vertex coordinates of the computational grid to determine whether the spatial coordinate position is inside the computational grid. If it is inside a computational grid, it means that the particle is within the spatial range of the computational grid. According to the grid index value, find the grid in the CFD program.

[0102] From the DEM program, obtain the coordinates of the contact point between the particle and the wall and the coordinates of the center of the particle, and use the index table to find the computational grid containing the particle. Then traverse each mesh surface in the computational grid, find the wall surface that collides with the particle, and obtain the temperature of the collision surface mesh. It should be noted that in the discrete element program, the simulation time step of the particle is inconsistent with the time step of the flue gas simulation in CFD. The time step of the flue gas simulation is about 10-50 times the particle simulation time step. Because the contact point attribute value of the particle is updated once the particle collides with the wall. In the Fluent flow field calculation, the steps of the method for contact between the particle and the battery wall are as follows Figure 2 As shown in the figure, in the current CFD calculation step, the coordinates of the particle-wall collision point are not necessarily the coordinates of the particle-wall collision point in the current flue gas, but may be the coordinates of the particle-wall collision point in the previous discrete element time step. Therefore, in the CFD program, the particle and the wall need to be tested for secondary collision. Calculate the distance between the coordinates of the particle center and the wall collision point. If the distance exceeds the particle radius, it means that the particle has not collided with the wall at the current moment. If it is less than or equal to the particle radius, it is judged that the particle is in contact with the wall.

[0103] In the CFD program, the calculation grid containing the particle is found using the index table according to the coordinates of the collision point between the particle and the wall and the coordinates of the center of the particle, and the temperature of the collision wall grid is obtained. Then the contact heat transfer coefficient of the particle hitting the wall is calculated by the physical parameters and mechanical parameters of the particle. The calculation of the contact heat transfer coefficient between particles and between particles and walls is carried out through contact models, experimental measurements and empirical models. There are many forms of contact heat transfer coefficient calculation model methods. In the present invention, the most widely used contact heat transfer coefficient calculation model is taken as an example:

[0104] Q c =h c ΔT p1p2 (twenty four)

[0105]

[0106] Among them, h c To take into account the heat transfer coefficient of the contact heat transfer area, ΔT p1p2 is the temperature difference between particles and between particles and the wall, k p1 and k p2 are the thermal conductivity of the two particles or the particles and the wall, respectively. N is the normal force on the contact point, E * is the equivalent elastic modulus of the two particles or the particle and the wall in collision contact, r *is the geometric mean radius of the particles calculated by contact theory. All three can be derived from the contact model (Heartz Mindlin) model.

[0107] The heat transfer caused by particles hitting the wall is calculated by the convective heat transfer formula, and according to the principle of energy conservation, the heat transfer is converted into the volume heat source of the wall grid and loaded into the wall unit of the CFD calculation. The calculation equation of the volume heat source is:

[0108]

[0109] The heat transfer amount is then written into the particle data structure class object as the heat dissipation of the particle itself.

[0110] In the CFD program, the interphase force and convective heat transfer between the flue gas and the particles are converted into volume force source terms and volume heat source terms and loaded on the computational grid containing the particle. Then the flue gas force and convective heat transfer on the particle are written into the particle data structure of the particle and transmitted to the DEM calculation. The flow field CFD calculation is performed according to the preset time step t f , the discrete element calculation is based on the time step t p , update the state information of the flow field and particles, and perform two-phase coupling calculations according to preset steps.

[0111] Among them, the interaction between particles and smoke The force of smoke on particulate matter in equation (4) It is a pair of interacting forces, whose components include drag, buoyancy, lift, thermophoresis, etc. Among them, drag is the force with the highest proportion. Taking the drag of the flue gas on the particle as an example, the basic form of drag is shown in the following formula:

[0112]

[0113] In the above formula, C d is the drag coefficient, determined by experimental method and drag model, It is the difference between the particle velocity and the flue gas velocity at the location of the particle, that is, the relative velocity between the particle and the flue gas. p is the projected area of ​​the particle in the direction of relative velocity.

[0114] The selection of the drag model is related to the flow state of the smoke and the volume fraction of the smoke in the space. Taking the Gidaspow drag model as an example, the calculation of the drag coefficient depends on the characteristic parameter Reynolds number Re that characterizes the flow field state. p And volume share:

[0115]

[0116] For a single particle, the force of smoke on the particle represented by the drag force is directly loaded into the momentum conservation equation of the particle, while the reaction force of the drag force on the smoke needs to be converted into the volume momentum source term:

[0117]

[0118] The contact and collision forces between particles and between particles and walls are calculated based on the contact model of discrete elements. Through the contact model, the normal and tangential components of the force can be obtained. The normal force represents the depth of particle collision and contact, which is the key basis for calculating the contact heat transfer coefficient. In DEM, the corresponding contact model is selected based on the differences in particle properties, such as whether viscosity is considered, whether it is a spherical particle, and whether particle breakage is considered.

[0119] The calculation of the heat transfer between particles and smoke is related to the Reynolds number of smoke diffusion. For example, in the case of low Reynolds number, the Ranz model is used. The specific calculation method can also be measured experimentally. There are many forms. The present invention takes the Ranz model as an example:

[0120] Q f =h f (T p -T f ) (30)

[0121]

[0122] In the above formula, Nu i is the Nusselt number, d i is the characteristic length of smoke flow, k f is the thermal conductivity, Pr is the Prandtl number, Re i is the Reynolds number. f is the heat transfer coefficient.

[0123] Similarly, the coupled heat transfer between the flue gas and the particles is equal in value, but opposite in sign, which means that if the flue gas transfers heat to the particles, the particles are heated by the flue gas, and the flue gas itself introduces a negative energy source. For the update of the particle's own temperature, an iterative solution is performed based on formula (5). For CFD calculations, the particle heat transfer also needs to be converted into a body heat source:

[0124]

[0125] Since there are many forms of heat transfer in the flow field of the battery system, namely, convection heat transfer between the battery surface and the flue gas, contact heat transfer between the particles and the wall, and conjugate heat transfer between the particles and the flue gas, there are great differences in the heat transfer forms. Therefore, in the present invention, the heat transfer of the particles and the volume heat source of the battery system need to be specially processed, such as Figure 3As shown, follow these steps:

[0126] After the particles contact and collide with the battery surface according to the above content, for the case where the particles collide with the battery surface, first find the calculation unit where the contact point is located in the index table. Since the contact unit found in the index table is not necessarily a solid unit, if the unit is judged to be a non-solid unit, all neighboring units of the unit are traversed to determine whether it is a battery surface unit. If so, it is the solid unit of the battery surface contacted by the particle, and the battery wall temperature where the contact point is located is obtained.

[0127] Since there is convective heat exchange between the battery surface and the high-temperature flue gas, the present invention here needs to divide the heat transfer between the particles and the battery surface by the wall unit volume of the battery surface according to the principle of conservation of energy, and use it as the volume heat source in the battery wall unit, rather than destroying the original convective heat transfer conditions between the battery surface and the flue gas, or loading the heat source into the fluid unit of the flue gas.

[0128] According to the center position of the particle, use the index table to find the fluid calculation unit where the particle is located, calculate the coupled heat transfer between the particle and the flue gas, convert it into a volume heat source and add it to the fluid unit.

[0129] When particles are deposited, the more they are deposited, the greater the normal force between the particles in the lower layer and the battery surface, and the larger the contact area, which significantly increases the heat transfer. The forces on the particles are updated through the discrete element DEM program, and the temperature, pressure, and density information of the calculation domain is obtained through the CFD computational fluid dynamics method, so as to comprehensively judge the risk of particle deposition and heat transfer causing thermal runaway of the battery.

Claims

1. A calculation method for the deposition and heat transfer of battery eruption particles based on CFD-DEM coupling, targeting the multiphase flow behavior of high-temperature flue gas and particles erupted by thermal runaway of lithium-ion batteries, simulating and evaluating the influence of the deposition and heat transfer of high-temperature particles erupted by thermal runaway of batteries on the safety of thermal runaway of other batteries, characterized in that: The following steps are included: Step 1: In the discrete element program, a particle model is constructed to set the shape, size, mechanical / thermal property parameters of the battery eruption particles, as well as the contact model and particle injection method that describe the force between particles; in the computational fluid dynamics (CFD) program, the flow field geometry of the battery system is established, and the corresponding calculation grid is divided according to the battery eruption smoke domain, and the component type and mass fraction, mass flow rate, temperature and flue gas flow domain boundary pressure of the battery thermal runaway eruption smoke are set; Step 2: deeply develop the contact model in the discrete element DEM program, and use the coordinates of the contact point between the particle and the wall and the normal force of the particle and the wall in the contact model as the particle's own attributes; once the particle collides with the wall, update the attribute values ​​of the collision point and the normal contact force between the particle and the wall; then transmit the attribute value, the center coordinates of the particle, the particle radius, and the particle temperature to the CFD calculation program; Step 3, in the CFD program, a global coordinate index table is constructed, the function of the index table is to find the CFD calculation grid index containing the coordinate according to a given spatial coordinate of a certain point; in the CFD program, the calculation grid containing the particle is found according to the coordinates of the collision point between the particle and the wall and the coordinates of the center of the particle using the index table, and the temperature of the collision wall grid is obtained; then the contact heat transfer coefficient of the particle impacting the wall is calculated by the physical parameters and mechanical parameters of the particle, and the heat transfer of the particle impacting the wall is calculated by the convective heat transfer formula, and according to the principle of conservation of energy, the heat transfer is converted into a volume heat source of the wall grid and loaded into the wall unit of the CFD calculation; Step 4, obtain the flow velocity and temperature of the fluid calculation grid containing particles in the CFD program, calculate the phase interaction force and heat exchange between the flue gas and the particles with the velocity and temperature of the particles, load them on the CFD calculation grid and the resultant force of the discrete element, calculate and update the flow field motion state, and update the position, temperature and velocity information of the particles at the same time; Realize the coupling between CFD and DEM; Step 5: Flow field CFD calculation is performed according to the preset time step t f , the discrete element calculation is based on the time step t p , update the state information of the flow field and particles, and perform two-phase coupling calculations according to the preset steps. Repeat this process until the preset simulation time is met, and evaluate the thermal runaway safety of the battery system based on the calculation results.

2. The method according to claim 1, characterized in that: In step 2, the development steps of the particle contact model are: In the discrete element program, the data structure describing the particles is expanded to add custom attribute values ​​of the particles: the spatial coordinates of the contact point between the particle and the wall and the normal force between the particle and the battery wall; On the basis of the original contact model (such as the Hertz Mindlin model), the coupling between the custom attributes of the particle and the contact model is realized. In the particle collision detection step in the discrete element program, if it is found that the particle collides with the wall, the spatial coordinates and the normal force of the contact point where the particle collides with the wall are calculated through the geometric relationship between the contact model and the particle, and the custom attribute value is updated; if the particle does not collide with the wall at the current time step, the attribute value is not updated, and the attribute value updated at the last collision is maintained; In the discrete element and computational fluid dynamics coupling program, the particle data structure class transmitted by the discrete element to the computational fluid dynamics program is expanded accordingly, and the information in the particle data structure includes the particle center coordinates, particle radius, particle temperature, particle and wall collision contact point coordinates, and the normal force of the particle and wall collision; the value of each particle is different, and the information of each particle is a specific object instance of the particle data structure class; the information of all particulate matter is merged into a class array and written into the computer memory, and the CFD program obtains the information of all particles in the flue gas flow domain in the CFD-DEM coupling time step by accessing the memory.

3. The method according to claim 1, characterized in that In step 3, the steps of implementing heat transfer from particles to the battery wall by the CFD program are: In CFD calculation, after constructing the geometric model of the flue gas flow area and battery area in the battery system and dividing the calculation grids; traverse all the calculation grids, extract the center coordinates of each calculation grid, the spatial coordinates of each vertex of the calculation grid, the properties of the calculation grid (flue gas flow area or battery solid area), and the calculation grid index, and merge them into a global coordinate index table; Given any spatial coordinate position, traverse the global coordinate index table, calculate the distance between the spatial coordinate position and the grid center, select a series of computational grids with the closest distance, and then substitute the spatial coordinate position into the vertex coordinates of the computational grid to determine whether the spatial coordinate position is inside the computational grid. If it is inside a computational grid, it means that the particle is within the spatial range of the computational grid. According to the grid index value, find the grid in the CFD program. From the DEM program, obtain the coordinates of the contact point between the particle and the wall and the coordinates of the particle center, and use the index table to find the computational grid containing the particle; since the flow field calculation time step is longer than the particle discrete element calculation time step, and the custom properties of the particle-wall collision are only updated when the collision occurs, and the particle center position is updated in real time, at the beginning of the CFD calculation, the state information of the particle may not completely match the real-time particle state, and contact judgment is required; traverse each particle, calculate the distance between the coordinates of the particle center and the wall collision point, if the distance exceeds the particle radius, it means that the particle has not collided with the wall at the current moment, if it is less than or equal to the particle radius, it is judged that the particle is in contact with the wall; then traverse each mesh surface in the computational grid, find the wall that collides with the particle, and obtain the temperature of the collision surface mesh; Then, the contact heat transfer coefficient of the particles hitting the wall is calculated using the physical and mechanical parameters of the particles, and the heat transfer of the particles hitting the wall is calculated using the convective heat transfer formula. Based on the principle of conservation of energy, the heat transfer is converted into a volume heat source of the wall grid and loaded into the wall unit of the CFD calculation to complete the calculation of heat transfer from the particles to the wall. The heat transfer value is then written into the particle data structure class object as the heat dissipation of the particle itself.

4. The method according to claim 1, characterized in that: In step 4, in addition to the heat transfer of the particles to the wall, there is also convective heat transfer between the particles and the flue gas; according to the global coordinate index table, the flue gas flow rate and temperature of the calculation grid where the particles are located are found, and then the phase force and heat transfer between the flue gas and the particles are calculated in combination with the temperature and velocity of the particles; in the CFD program, the phase force and convective heat transfer between the flue gas and the particles are converted into volume force source terms and volume heat source terms and loaded on the calculation grid containing the particles; then the flue gas force and convective heat transfer on the particles are written into the particle data structure of the particles and transmitted to the DEM calculation; the flow field CFD calculation is performed according to the preset time step t f , the discrete element calculation is based on the time step t p , update the state information of the flow field and particles, and perform two-phase coupling calculation according to the preset steps; This process is repeated until the preset simulation time is met, and the thermal runaway safety of the battery system is evaluated based on the calculation results of the global temperature field.

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