Gas-heat combined safety monitoring method and device for energy storage battery cabinet with air cooling system

Abstract

The invention provides a gas-heat combined safety monitoring method and device for an energy storage battery cabinet with an air cooling system. The method comprises the following steps: constructing a finite element model of the energy storage battery cabinet with the air cooling system; establishing a temperature field control model, an airflow field control model and an airflow field heat transfer model; boundary setting is carried out on the built energy storage battery cabinet finite element model with the air cooling system, and grids on fluid and solid interfaces are in butt joint to form a common-node grid structure; according to the temperature field control model, the airflow field control model and the airflow field heat transfer model, airflow and temperature field joint simulation is carried out on the energy storage battery cabinet model with the air cooling system, a hot spot with the maximum temperature and a position where gas circulation is most concentrated are obtained, and sensors are arranged at the corresponding positions. The system has the advantages of being high in safety performance, low in cost and the like, comprehensive and real-time monitoring of the energy storage battery pack can be achieved, the thermal safety performance of the energy storage battery pack is effectively improved, and the service life of the energy storage battery pack is prolonged.

Description

Technical Field

[0001] The present invention relates to the field of safety of new energy storage systems, and in particular to a method and device for combined air-heat safety monitoring of an energy storage battery cabinet with an air cooling system. Background Art

[0002] In the context of the current booming development of new energy technologies, the role of energy storage systems has become increasingly prominent, especially in promoting the effective use of renewable energy and the flexible regulation of power grids. Lithium batteries have the advantages of environmental protection, high energy density and long cycle life. However, as the capacity and power density of lithium battery systems become higher and higher, the thermal stability of lithium batteries when running at high temperatures and the reduction of thermal life of battery packs in long-term use are becoming more and more prominent, which has become a key technical problem restricting the further development of energy storage systems. Therefore, the development of efficient and accurate thermal monitoring technology and the improvement of the thermal safety of battery systems are crucial to ensure the long-term reliable operation of energy storage systems.

[0003] In order to achieve safe monitoring of new energy storage systems, it is necessary to monitor battery charging and discharging and battery status, monitor energy storage charging and discharging parameters, and then calculate performance evaluation indicators to determine the status of energy storage batteries. However, due to the complexity of the structure of energy storage battery packs and the number of large-scale batteries inside, traditional thermal management methods, such as thermocouples and infrared thermal imaging, are costly to implement and difficult to achieve comprehensive and real-time temperature monitoring when facing the complex structure of large-scale battery packs and a large number of battery cells. For the monitoring of battery temperature and gas, the prior art usually adopts a direct control method, that is, one or more sensors are directly arranged at any position in the battery for monitoring. However, the location of the sensor arrangement will directly affect the accuracy of monitoring, and the detection accuracy and range of a single sensor are limited, and it is difficult to cover all batteries in a large-scale battery pack for accurate detection. Although the detection accuracy and range can be improved to a certain extent by arranging multiple sensors, it will greatly increase the detection cost. If the sensor is not arranged in a good position, the best monitoring effect cannot be achieved.

[0004] Some practitioners have proposed to build a multi-point temperature data set by arranging sensors at multiple points to reflect the heat generation power of a single battery in the battery module under different working conditions, and further apply genetic algorithms for cross-validation to determine the most ideal monitoring point location. However, this type of method is usually only for static conditions, and does not fully consider the impact of the air cooling system on the gas diffusion path in actual operation. It is not suitable for actual dynamic airflow environments. For large-scale battery packs, it is still impossible to accurately determine the location suitable for gas sensor layout in a dynamic airflow environment, so the monitoring effect is still poor. Summary of the invention

[0005] The technical problem to be solved by the present invention is as follows: In view of the above-mentioned problems in the prior art, a method and device for combined gas-heat safety monitoring of an energy storage battery cabinet with an air cooling system is provided, which is simple to implement, has monitoring accuracy, high safety performance and low cost, so as to realize comprehensive and real-time monitoring of the energy storage battery pack, effectively improve the thermal safety performance of the energy storage battery pack and extend its service life.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A combined air-heat safety monitoring method for an energy storage battery cabinet with an air cooling system comprises the following steps:

[0008] According to the structure of the battery components in the controlled energy storage battery cabinet with an air cooling system, the structure of the air cooling system and the layout of the air cooling system, a finite element model of the energy storage battery cabinet with an air cooling system is constructed;

[0009] Establish a temperature field control model to simulate the time-varying state of the heat source inside the battery, establish an airflow field control model to simulate the flow characteristics of the fluid inside the energy storage battery cabinet, and establish an airflow field heat transfer model to simulate the heat transfer state of the fluid inside the energy storage battery cabinet under the influence of temperature gradient and internal heat source;

[0010] The boundaries of the constructed finite element model of the energy storage battery cabinet with an air cooling system are set, and the meshes on the fluid and solid interfaces are connected to form a mesh structure with common nodes, so as to obtain the energy storage battery cabinet model with an air cooling system;

[0011] According to the temperature field control model, the airflow field control model and the airflow field heat transfer model, the energy storage battery cabinet model with the air cooling system is jointly simulated with the airflow and temperature field to obtain the hot spot with the highest temperature and the position where the gas flow is most concentrated, so as to control the arrangement of temperature sensors at the hot spot with the highest temperature obtained by simulation, and to arrange gas sensors at the position where the airflow is most concentrated.

[0012] Furthermore, in the finite element model of the energy storage battery cabinet with an air cooling system, the entire battery is regarded as a black box to construct a physical model of a single battery, and the heat convection and heat radiation inside the battery are ignored. The thermal conductivity inside the battery is configured to be constant in all directions, and a grille is opened on the side of the battery cabinet, and a unit heat dissipation device is configured in front of the battery cabinet to dissipate heat for the battery module. The battery modules are stacked on each other in the cabinet, and a heat dissipation channel is configured for each battery module so that air can flow evenly through each battery unit through the heat dissipation channel.

[0013] Furthermore, the temperature field control model established uses the average density ρ and specific heat capacity C of the battery p , Kelvin temperature scale T for temperature measurement, rate of change of temperature over time The heat transfer control equation formed by the thermal conductivity k in each direction and the volume heat generation rate S of the side reaction is:

[0014]

[0015]

[0016] Where ρ represents the density of the material, C p is the specific heat capacity at constant pressure, u is the fluid velocity, represents the temperature gradient inside the solid over time, represents the divergence of the heat flux density vector, describing how heat flows out from a point, Q represents the rate of internal heat generation per unit volume, Q ted represents the form of heat generation from the thermoelectric effect, q represents the heat flux vector, and k represents the thermal conductivity.

[0017] Furthermore, the Reynolds number is used in the established airflow field control model to predict the state of fluid flow, wherein when the Reynolds number is less than a first preset threshold, the flow is judged to be in a laminar state, and when the Reynolds number is greater than a second preset threshold, the flow is judged to be in a turbulent state, and when the Reynolds number is within the range between the first preset threshold and the second preset threshold, the flow is judged to be in a transitional state from laminar flow to turbulent flow.

[0018] Furthermore, the calculation formula of the Reynolds number is:

[0019]

[0020] Wherein, Re represents the Reynolds number, ρ represents the density of the fluid, v represents the flow velocity of the fluid, L represents the characteristic length, μ represents the dynamic viscosity of the fluid, and ν represents the kinematic viscosity of the fluid ν=μ / ρ.

[0021] Furthermore, the heat transfer control equation under the flow field of the established airflow field heat transfer model is:

[0022]

[0023]

[0024] Among them, C p represents the specific heat capacity at constant pressure, u represents the fluid velocity vector, represents the change of temperature with time, q represents the heat flux density vector, Q represents the internal heat source term per unit volume, Q p and Q vd represents the heat of chemical reaction, k represents thermal conductivity, and ρ represents fluid density P A Indicates absolute pressure, R srepresents the specific gas constant and T represents the absolute humidity.

[0025] Furthermore, in the boundary setting of the finite element model of the energy storage battery cabinet with an air cooling system, the air inlet of the box is set as a velocity inlet, the exhaust port is set as a standard pressure outlet, and the static pressure of the exhaust port is set to a standard atmospheric pressure value.

[0026] Furthermore, the boundary setting of the finite element model of the energy storage battery cabinet with an air cooling system also includes configuring the following turbulent boundary control equations:

[0027]

[0028]

[0029]

[0030]

[0031] Where n represents the normal vector, (-pI+K) is the stress tensor, where p is the pressure, I is the identity matrix, and K is the turbulent kinetic energy. represents the correction term for pressure, p input Indicates input pressure, c μ represents the turbulence model constant, η represents the turbulence correction coefficient, k represents the turbulence viscosity coefficient, ∈ represents the turbulence dissipation rate, u represents the fluid velocity vector, u n Represents the component of the velocity vector in a certain direction, U ref Indicates the reference flow rate, L T represents the characteristic length of turbulence, Δp pc represents the pressure correction term, Represents the gradient operator.

[0032] Furthermore, it also includes monitoring the concentrations of multiple gases in the controlled energy storage battery cabinet respectively, and judging whether the concentrations of various gases in the controlled energy storage battery cabinet reach the warning threshold and the warning level when the warning threshold is reached according to the monitoring results and pre-configured warning thresholds corresponding to multiple warning levels.

[0033] A gas-heat combined safety monitoring device for an energy storage battery cabinet with an air cooling system comprises a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to execute a gas-heat combined safety monitoring method for an energy storage battery cabinet with an air cooling system.

[0034] Compared with the prior art, the advantages of the present invention are:

[0035] 1. The present invention constructs a temperature field control model, an airflow field control model and an airflow field heat transfer model to perform gas-heat coupling modeling, and performs joint simulation of airflow and temperature field on the finite element model of the energy storage battery cabinet with an air cooling system, so as to obtain the hot spots with the highest temperature and the positions where the gas circulation is most concentrated, and then accurately arranges sensors according to the hot spots with the highest temperature and the positions where the gas circulation is most concentrated, so as to achieve the optimal arrangement of sensors. Compared with the direct monitoring of battery temperature and gas emissions in the prior art, the accuracy and efficiency of monitoring can be significantly improved, and the problem of inaccurate sensor arrangement in traditional monitoring methods under complex air cooling systems can be overcome.

[0036] 2. The present invention further uses simulation calculations to comprehensively consider the impact of airflow on the diffusion pattern of faulty gas under the wind cooling effect, more effectively captures early thermal fault signals and signs of faulty gas leakage, and takes preventive measures in time, thereby significantly enhancing the safety management level and fault warning capability of the energy storage battery cabinet. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a flow chart of the combined gas-heat safety monitoring method for an energy storage battery cabinet with an air cooling system according to an embodiment of the present invention.

[0038] Figure 2 Schematic diagram of a typical battery cabinet with an air cooling system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] Traditional temperature field control models are usually suitable for scenarios that consider temperature changes during battery operation alone, but are not suitable for battery cabinets with air cooling systems. The present invention is aimed at the safety monitoring of battery cabinets with air cooling systems. On the basis of constructing a temperature field control model, the airflow field control model and the heat transfer model are introduced to achieve gas-heat coupling modeling. Since the airflow field is introduced, it can not only affect the heat dissipation and hot spot distribution, but also the distribution of the airflow field. Therefore, through the joint simulation of the airflow and temperature field, the temperature poles and airflow concentration areas can be accurately obtained, and then the optimal locations for the layout of temperature and gas sensors can be determined based on the simulation results, so that accurate joint safety monitoring of energy storage gas and heat can be achieved.

[0041] like Figure 1 As shown, the gas-heat combined safety monitoring method of the energy storage battery cabinet with an air cooling system in this embodiment includes the following steps:

[0042] Step 1: construct a finite element model of the energy storage battery cabinet with an air cooling system according to the structure of the battery assembly in the energy storage battery cabinet with an air cooling system, the structure of the air cooling system, and the layout position of the air cooling system.

[0043] The finite element method is to approximate the solution of partial differential equations or integral equations by dividing a large problem domain into smaller, simple, finite elements, usually triangles or quadrilaterals (in two-dimensional problems) or other higher-dimensional shapes. Each small element can be described by a relatively simple equation, and then these small elements are combined according to certain rules to form a global equation system, which approximates the entire problem domain. Discretization is to divide the continuous problem domain into a finite number of small elements to form a discrete model. Finite element modeling specifically includes: selecting element type, establishing equations, assembly, applying boundary conditions, solving, post-processing and other steps.

[0044] In this embodiment, the battery pack model is constructed according to the following principles:

[0045] (1) When constructing the physical model of a single battery, the entire battery is treated as a “black box” and the actual material composition inside the battery is ignored.

[0046] (2) Ignore the heat convection and heat radiation inside the battery and only focus on the convective heat transfer between the battery surface and the surrounding air.

[0047] (3) It is assumed that the thermal conductivity inside the battery is constant in all directions and does not change with changes in ambient temperature.

[0048] like Figure 2 As shown, in this embodiment, the battery cabinet has a grille with holes on the side, and a unit fan is arranged in the front, which drives the airflow to enter from the grille and flow out from the fan for heat dissipation of the battery module. The battery modules are stacked on top of each other in the cabinet, which can not only save space, but also leave appropriate gaps between the modules to promote air flow. Each battery module is designed with a heat dissipation channel, which is coordinated with the airflow path in the entire cabinet to ensure that cold air can flow evenly through each battery cell. In addition, the stacking structure design also allows battery modules to be easily added or replaced. It is understandable that the fan can also use other types of heat dissipation devices.

[0049] Step 2: Establish a temperature field control model to simulate the time-varying state of the heat source inside the battery, establish an airflow field control model to simulate the flow characteristics of the fluid inside the energy storage battery cabinet, and establish an airflow field heat transfer model to simulate the heat transfer state of the fluid inside the energy storage battery cabinet under the influence of temperature gradient and internal heat source.

[0050] In the overcharged battery thermal runaway model, two types of heat, Joule heat and side reaction heat, need to be considered. This embodiment specifically utilizes the partial differential equation module and heat transfer module of COMSOL to construct a temperature field control model.

[0051] The governing equations for heat transfer include the average density and specific heat capacity of the battery, ρ and C p , Kelvin temperature scale T for temperature measurement, rate of change of temperature over time The thermal conductivity k in each direction and the volume heat generation rate S of the side reaction are expressed as:

[0052]

[0053]

[0054] in, represents the divergence of the heat flux density vector, and q represents the heat flux density vector.

[0055] During the charging and discharging process of lithium batteries, the internal heat source is not constant, but changes with time, and its change is not a simple linear change. Therefore, in order to simulate the time-varying behavior of the internal heat source of lithium iron phosphate batteries, the internal heat source can be modeled using a custom function in the simulation software, thereby realizing a method including loading and compiling custom functions. The temperature field control model established in this embodiment uses the average density ρ and specific heat capacity C of the battery p , Kelvin temperature scale T for temperature measurement, rate of change of temperature over time The heat transfer control equation formed by the thermal conductivity k in each direction and the volume heat generation rate S of the side reaction is specifically the solid heat transfer control equation as follows:

[0056]

[0057]

[0058] Wherein, formula (3) is the expression of energy conservation, ρ represents the density of the battery, C p is the specific heat capacity at constant pressure, u is the fluid velocity, represents the rate of change of temperature with time, represents the divergence of the heat flux density vector, describing how heat flows out from a point, Q represents the rate of internal heat generation per unit volume, Q ted represents the form of heat generation from the thermoelectric effect, equation (4) is Fourier's law of heat conduction, q represents the heat flux density vector, and k represents thermal conductivity.

[0059] This embodiment uses the above method to construct a temperature field control model, allowing dynamic adaptation of the behavior of the heat source. The heat source can be loaded using a custom function through the simulation software to respond to the charge and discharge cycles, thereby improving the accuracy of the thermal model.

[0060] In this embodiment, the battery pack is cooled by forced convection. Specifically, air is introduced into the battery case through the air supply port, then flows along the outer shell surface of the battery, and is finally discharged from the exhaust port through the convection heat exchange with the battery module. According to the knowledge of fluid mechanics, the flow state of the fluid inside the battery pack case can be divided into turbulent and laminar flow. The specific fluid flow state is determined by the Reynolds number. Among them, the Reynolds number is a dimensionless number used to describe the characteristics of fluid flow, especially the laminar and turbulent states of flow. The calculation formula of the Reynolds number is:

[0061]

[0062] Wherein, Re represents the Reynolds number, ρ represents the density of the fluid, v represents the flow velocity of the fluid, L represents the characteristic length, μ represents the dynamic viscosity of the fluid, and ν represents the kinematic viscosity of the fluid ν=μ / ρ.

[0063] The flow state of the fluid inside the battery pack box can be divided into turbulent flow and laminar flow, and the turbulence model can be determined according to the Reynolds number. In this embodiment, the Reynolds number is used to predict the state of fluid flow in the airflow field control model, wherein when the Reynolds number is less than the first preset threshold, the flow is determined to maintain a laminar state, when the Reynolds number is greater than the second preset threshold, the flow is determined to be a turbulent state, and when the Reynolds number is within the range between the first preset threshold and the second preset threshold, the flow is determined to be a transition state from laminar flow to turbulent flow.

[0064] Specifically, when the Reynolds number is low (for example, less than 2000), the flow tends to maintain a laminar state, that is, the flow is smooth and orderly; when the Reynolds number is high (for example, greater than 4000), the flow tends to become a turbulent state, that is, the flow is chaotic and disordered; at intermediate Reynolds numbers (approximately between 2000 and 4000), the flow may be in a transitional state, transitioning from laminar flow to turbulent flow.

[0065] Fluent software has built-in multiple turbulence models to adapt to different types of fluid flows and engineering application requirements. These turbulence models are mainly used to predict and analyze turbulent flow characteristics that are difficult to measure directly in practical applications, such as k-ε, ko, DES, LES and other models. This embodiment preferably uses the k-ε model as the airflow field control model, and can further construct the heat transfer control equation under the flow field. The k-ε model has the advantages of high stability, strong adaptability and good calculation accuracy. In the k-ε turbulence model, k represents turbulent kinetic energy, ε represents dissipation rate, and ignores the viscosity between molecules. The k-ε model can be divided into the standard k-ε turbulence model, the RNG k-ε turbulence model and the Realizable k-ε turbulence model.

[0066] In this embodiment, the heat transfer control equation under the flow field of the established air flow field heat transfer model is:

[0067]

[0068]

[0069] Wherein, formula (6) is the energy equation in fluid dynamics, which contains convection terms and heat conduction terms, C p represents the specific heat capacity at constant pressure, u represents the fluid velocity vector, represents the change of temperature with time, q represents the heat flux density vector, Q represents the internal heat source term per unit volume, Q p and Q vd represents the heat of chemical reaction, equation (7) is Fourier's law of heat conduction, k represents thermal conductivity, and ρ represents fluid density P A Indicates absolute pressure, R s represents the specific gas constant and T represents the absolute humidity.

[0070] Step 3: Set the boundaries of the constructed finite element model of the energy storage battery cabinet with an air cooling system, and connect the meshes on the fluid and solid interfaces to form a mesh structure with common nodes.

[0071] Considering the heat exchange problem between fluid and solid, that is, the fluid-solid coupled heat exchange problem, this embodiment processes the boundary surface between fluid and solid when performing meshing. Specifically, in the constructed model, by performing shared topology operations in the SCDM software, the perfect docking of the grids on the interface between fluid and solid is achieved to form a grid structure with common nodes. This processing method can significantly improve the efficiency and accuracy of boundary surface information transmission. Furthermore, the type of interface is defined as a coupled type. In the boundary condition setting of the model, the air inlet of the box is also set as a velocity inlet, and the exhaust port is set as a standard pressure outlet, and its static pressure is set to a standard atmospheric pressure value.

[0072] In this embodiment, the boundary setting of the finite element model of the energy storage battery cabinet with an air cooling system also includes configuring the following turbulence boundary control equation to control the turbulence at the grid boundary of the battery cabinet:

[0073]

[0074] Where n represents the normal vector, (-pI+K) is the stress tensor, where p is the pressure, I is the identity matrix, and K is the turbulent kinetic energy. represents the correction term for pressure, p input Indicates input pressure, c μ represents the turbulence model constant, η represents the turbulence correction coefficient, k represents the turbulence viscosity coefficient, ∈ represents the turbulence dissipation rate, u represents the fluid velocity vector, u n Represents the component of the velocity vector in a certain direction, U ref Indicates the reference flow rate, L T represents the characteristic length of turbulence, Δp pc represents the pressure correction term, Represents the gradient operator.

[0075] This embodiment couples fluid dynamics with heat conduction when constructing a finite element model of an energy storage battery cabinet with an air cooling system, and can simultaneously consider the mutual influence of flow and heat transfer, and set boundary conditions accordingly. The k-∈ turbulence model and turbulence correction coefficient η are used to improve the calculation efficiency while ensuring accuracy. Further, by introducing the normal vector n and the pressure correction term Δp pc It can also handle complex boundary conditions.

[0076] Step 4: Perform a joint simulation of the airflow and temperature field of the energy storage battery cabinet model with an air cooling system according to the temperature field control model, the airflow field control model, and the airflow field heat transfer model to obtain the hotspot with the highest temperature and the position where the gas flow is most concentrated, so as to control the placement of temperature sensors at the hotspot with the highest temperature obtained by simulation, and to place gas sensors at the position where the airflow is most concentrated.

[0077] This embodiment constructs a temperature field control model and an airflow field control model for coupled calculation, which can not only introduce a new turbulent heat transfer process, but also guide the arrangement of gas sensors through airflow distribution. After simulation calculation, the temperature field and airflow field simulation result images and data can be output to determine the hot spot with the highest temperature and the position where the gas circulation is most concentrated, that is, the hot spot with the highest temperature and the position where the airflow is most concentrated. According to the simulation result, the temperature sensor is arranged in the area with the highest temperature, so that the temperature of the energy storage battery can be accurately monitored and the abnormal increase of the battery temperature can be discovered in time; the energy storage battery fault characteristic gas sensor, such as CO, H2 sensor, etc., is arranged in the area with the most concentrated gas circulation, and combined with the temperature sensor, so that the fault of the battery can be discovered in time, which is convenient for subsequent safety protection measures.

[0078] Due to the accelerated diffusion of gas under air cooling, the gas concentration in the local area is reduced, resulting in the difficulty of forming high-concentration areas. In addition, turbulence is formed under air cooling, which enhances the mixing of gas and surrounding air, making the faulty gas more evenly distributed in the space, increasing the difficulty of gas sensor monitoring and fault judgment. This embodiment uses sophisticated simulation calculations to comprehensively consider the impact of airflow on the diffusion pattern of faulty gas under the air cooling effect, more effectively captures early thermal fault signals and signs of faulty gas leakage, and takes preventive measures in a timely manner, thereby significantly enhancing the safety management level and fault warning capability of the energy storage battery cabinet.

[0079] Since the airflow in high temperature areas is weak, the temperature in concentrated airflow areas is generally low. Therefore, temperature sensors and characteristic gas sensors are generally arranged in different positions of the battery cabinet, which can reasonably utilize the internal space of the battery cabinet. Further combined with the monitoring of the battery cell temperature, it can be combined with the hot spot ambient temperature collected by the battery cabinet sensor for analysis to determine whether the energy storage battery has failed.

[0080] When the energy storage system is operating normally, the temperature of the battery cabinet should be similar to the ambient temperature, and the temperature of the battery cell should be slightly higher than the ambient temperature. However, when a thermal runaway fault occurs in the battery, the temperature of the battery cabinet and the temperature of the battery cell both rise rapidly, much higher than the ambient temperature. In this embodiment, the concentrations of various gases in the controlled energy storage battery cabinet are monitored separately, and based on the monitoring results and the pre-configured warning thresholds corresponding to multiple warning levels, it is determined whether the concentrations of various gases in the controlled energy storage battery cabinet have reached the warning threshold and the warning level if the warning threshold is reached. This can achieve graded warnings for the energy storage battery cabinet, further ensuring the safety and reliability of the energy storage battery cabinet. When it is determined that the corresponding warning threshold is reached, the control triggers the warning signal. For example, if the concentration of any gas exceeds its set primary warning threshold, a warning signal will be triggered; if it exceeds the advanced alarm threshold, an alarm signal will be triggered.

[0081] In a specific application embodiment, corresponding primary (level 1) warning and advanced (level 2) alarm thresholds are set for each gas concentration, as shown in Table 1. When the concentrations of any two gases reach the primary warning level at the same time, or when the concentration of any one gas reaches the advanced alarm level, it can be determined that the battery in the energy storage battery pack may have multiple potential faults including thermal runaway.

[0082] Table 1 Fault gas warning threshold

[0083] Gas Type Level 1 warning threshold Second level warning threshold CO 100ppm 200ppm <![CDATA[H2]]> 30ppm 100ppm <![CDATA[CH4]]> 1000ppm 3000ppm

[0084] This embodiment also provides a gas-heat combined safety monitoring device for an energy storage battery cabinet with an air cooling system, including a processor and a memory, the memory is used to store computer programs, and the processor is used to execute a gas-heat combined safety monitoring method for an energy storage battery cabinet with an air cooling system.

[0085] It is understandable that the above method of this embodiment can be executed by a single device, such as a computer or server, etc., and can also be applied to a distributed scenario and completed by multiple devices in cooperation with each other. In the case of a distributed scenario, one of the multiple devices can only execute one or more steps in the above method of this embodiment, and multiple devices interact to complete the above method. The processor can be implemented in the form of a general-purpose CPU, a microprocessor, an application-specific integrated circuit, or one or more integrated circuits, etc., for executing related programs to implement the above method of this embodiment. The memory can be implemented in the form of a read-only memory ROM, a random access memory RAM, a static storage device, and a dynamic storage device. The memory can store an operating system and other applications. When the above method of this embodiment is implemented by software or firmware, the relevant program code is stored in the memory and called and executed by the processor.

[0086] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A combined air-heat safety monitoring method for an energy storage battery cabinet with an air cooling system, characterized in that: The following steps are involved: According to the structure of the battery components in the energy storage battery cabinet with air cooling system, the structure of the air cooling system and the layout of the air cooling system, a finite element model of the energy storage battery cabinet with air cooling system is constructed; Establish a temperature field control model to simulate the time-varying state of the heat source inside the battery, establish an airflow field control model to simulate the flow characteristics of the fluid inside the energy storage battery cabinet, and establish an airflow field heat transfer model to simulate the heat transfer state of the fluid inside the energy storage battery cabinet under the influence of temperature gradient and internal heat source; The boundaries of the constructed finite element model of the energy storage battery cabinet with an air cooling system are set, and the meshes on the fluid and solid interfaces are connected to form a mesh structure with common nodes, so as to obtain the energy storage battery cabinet model with an air cooling system; According to the temperature field control model, the airflow field control model and the airflow field heat transfer model, the energy storage battery cabinet model with the air cooling system is jointly simulated with the airflow and temperature field to obtain the hot spot with the highest temperature and the position where the gas flow is most concentrated, so as to control the arrangement of temperature sensors at the hot spot with the highest temperature obtained by simulation, and to arrange gas sensors at the position where the airflow is most concentrated.

2. The method for combined air-heat safety monitoring of an energy storage battery cabinet with an air cooling system according to claim 1 is characterized in that: In the finite element model of the energy storage battery cabinet with an air cooling system, the entire battery is regarded as a black box to construct a physical model of a single battery, and the heat convection and heat radiation inside the battery are ignored. The thermal conductivity inside the battery is configured to be constant in all directions, and a grille is opened on the side of the battery cabinet, and a unit heat dissipation device is configured in front of the battery cabinet to dissipate heat for the battery module. The battery modules are stacked on each other in the cabinet, and a heat dissipation channel is configured for each battery module so that air can flow evenly through each battery unit through the heat dissipation channel.

3. The method for combined air-heat safety monitoring of an energy storage battery cabinet with an air cooling system according to claim 1 is characterized in that: The temperature field control model established uses the average density ρ and specific heat capacity C of the battery p , Kelvin temperature scale T for temperature measurement, rate of change of temperature over time The heat transfer control equation formed by the thermal conductivity k in each direction and the volume heat generation rate S of the side reaction is: The first equation is the expression of energy conservation, ρ represents the density of the battery, C p is the specific heat capacity at constant pressure, u is the fluid velocity, represents the rate of change of temperature with time, represents the divergence of the heat flux density vector, describing how heat flows out from a point, Q represents the rate of internal heat generation per unit volume, Q ted represents the form of heat generation from the thermoelectric effect, the second equation is Fourier's law of heat conduction, q represents the heat flux density vector, and k represents the thermal conductivity.

4. The method for combined air-heat safety monitoring of an energy storage battery cabinet with an air cooling system according to claim 1 is characterized in that: The Reynolds number is used in the established airflow field control model to predict the state of fluid flow, wherein when the Reynolds number is less than a first preset threshold, the flow is judged to be in a laminar state, and when the Reynolds number is greater than a second preset threshold, the flow is judged to be in a turbulent state, and when the Reynolds number is within the range between the first preset threshold and the second preset threshold, the flow is judged to be in a transitional state from laminar flow to turbulent flow.

5. The method for combined air-heat safety monitoring of an energy storage battery cabinet with an air cooling system according to claim 4 is characterized in that: The calculation formula of the Reynolds number is: Wherein, Re represents the Reynolds number, ρ represents the density of the fluid, v represents the flow velocity of the fluid, L represents the characteristic length, μ represents the dynamic viscosity of the fluid, and ν represents the kinematic viscosity of the fluid ν=μ / ρ.

6. The method for combined air-heat safety monitoring of an energy storage battery cabinet with an air cooling system according to claim 1 is characterized in that: The heat transfer control equation under the flow field of the established airflow field heat transfer model is: Among them, C p represents the specific heat capacity at constant pressure, u represents the fluid velocity vector, represents the change of temperature with time, q represents the heat flux density vector, Q represents the internal heat source term per unit volume, Q p and Q vd represents the heat of chemical reaction, k represents thermal conductivity, and ρ represents fluid density P A Indicates absolute pressure, R s represents the specific gas constant and T represents the absolute humidity.

7. The method for combined air-heat safety monitoring of an energy storage battery cabinet with an air cooling system according to claim 1 is characterized in that: In the boundary setting of the finite element model of the energy storage battery cabinet with an air cooling system, the air inlet of the box is set as the velocity inlet, the exhaust port is set as the standard pressure outlet, and the static pressure of the exhaust port is set to a standard atmospheric pressure value.

8. The method for combined air-heat safety monitoring of an energy storage battery cabinet with an air cooling system according to claim 7 is characterized in that: The boundary setting of the finite element model of the energy storage battery cabinet with air cooling system also includes the configuration of the following turbulent boundary control equations: Δp pc =0.5Kρ(u·n) 2 , Where n represents the normal vector, (-pI+K) is the stress tensor, where p is the pressure, I is the identity matrix, and K is the turbulent kinetic energy. represents the correction term for pressure, p input Indicates input pressure, c μ represents the turbulence model constant, η represents the turbulence correction coefficient, k represents the turbulence viscosity coefficient, ∈ represents the turbulence dissipation rate, u represents the fluid velocity vector, u n Represents the component of the velocity vector in a certain direction, U ref Indicates the reference flow rate, L T represents the characteristic length of turbulence, Δp pc represents the pressure correction term, Represents the gradient operator.

9. The method for combined air-heat safety monitoring of an energy storage battery cabinet with an air cooling system according to any one of claims 1 to 8, characterized in that: It also includes monitoring the concentrations of various gases in the controlled energy storage battery cabinet separately, and judging whether the concentrations of various gases in the controlled energy storage battery cabinet have reached the warning threshold and the warning level if the warning threshold is reached based on the monitoring results and pre-configured warning thresholds corresponding to multiple warning levels.

10. A gas-heat combined safety monitoring device for an energy storage battery cabinet with an air cooling system, comprising a processor and a memory, wherein the memory is used to store a computer program, characterized in that: The processor is configured to execute the computer program to perform the method according to any one of claims 1 to 9.

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