JP6432192B2 - Temperature prediction device for battery packs - Google Patents

Description

The present invention, the surface temperature and internal temperature of the plurality of battery cells incorporated in the battery pack, such as the temperature of the temperature and the inner surface of the outer surface of the battery pack, to equipment that predict the temperature about the battery pack.

  Conventionally, in the design and development stage of industrial products, the temperature of parts constituting a finished product is predicted using computer simulation. For example, Patent Document 1 discloses that the temperature distribution of an exhaust pipe is steady using an exhaust system model that includes an exhaust pipe through which exhaust flows and a heat shield disposed around the exhaust pipe with a space therebetween. A method of predicting by analysis is disclosed.

Patent Document 2 discloses a method for estimating the temperature of an air-cooled battery, for example. In this method, a fluid model and a solid model are generated by dividing air (fluid) and battery (solid) into a plurality of cells, respectively, and the fluid model is analyzed by steady-state analysis. Based on the data obtained by this analysis, The solid model is analyzed by unsteady analysis and finally the temperature of the solid is estimated.
As described above, by estimating the temperature distribution of a part at the drawing stage, it is possible to perform design in consideration of the temperature of the part, and optimization of product dimensions, layout, material characteristics, and the like is facilitated.

Japanese Patent No. 5397634 Japanese Patent No. 5408185

  However, since the technique of the above-mentioned Patent Document 1 performs calculations based on the steady analysis method, only the stable temperature during steady running can be predicted, and it cannot be applied to the temperature prediction of parts that cause unsteady phenomena. Moreover, the technique of said patent document 2 estimates the temperature of the solid cooled with the fluid like air. For this reason, in order to predict the temperature of the solid inside the solid that has a solid and a fluid (for example, a battery pack incorporating a plurality of battery cells) inside the solid, Further improvements are needed.

  Here, a case where a plurality of battery cells built in the battery pack run out of heat will be considered. Thermal runaway is a phenomenon in which, for example, an internal short circuit occurs in a certain battery cell and heat is generated, and this heat generation further generates heat in other battery cells, and a plurality of battery cells generate abnormal heat one after another. When a battery cell runs out of heat, a rapid temperature rise occurs in the battery pack, and a high-speed gas jet from the battery cell is generated. Therefore, the temperature change of multiple battery cells and the temperature change of the entire battery pack are long. It becomes an unsteady state over time. As described above, the estimation method described in Patent Document 2 cannot be employed in a complicated situation where the temperature of a battery cell built in the battery pack is rapidly changed or a high-speed gas jet is generated.

This case, was conceived in view of the above problems, it is another object to provide a temperature pre HakaSo location that can be predicted accurately the temperature about the battery pack. The present invention is not limited to this purpose, and is a function and effect derived from each configuration shown in the embodiments for carrying out the invention described later, and other effects of the present invention are to obtain a function and effect that cannot be obtained by conventional techniques. Can be positioned.

( 1 ) The temperature predicting apparatus relating to the battery pack disclosed herein is an apparatus for predicting the temperature relating to the battery pack incorporating a plurality of battery cells using thermal fluid analysis software. The temperature prediction apparatus includes a model creating unit that creates a solid internal model in which a solid portion that contacts air inside the battery pack is divided into a plurality of cells, and an interior of the battery pack acquired in advance by actual measurement. Gas temperature acquisition unit that acquires, as the gas temperature, the temperature of the air adjacent to each cell of the solid internal model based on the measured data relating to the temperature change of the gas, and the gas temperature acquisition unit for each cell of the solid internal model And a temperature calculation unit that calculates a heat transfer amount by unsteady analysis using the gas temperature acquired in step S1 and calculates a temperature based on the heat transfer amount.

( 2 ) It is preferable that the gas temperature acquisition unit calculates the gas temperature by spatially interpolating measured temperatures at a plurality of positions in the battery pack that are actually measured in advance.
( 3 ) The model creation unit includes a plurality of solid external models obtained by dividing a contact portion with the surrounding air of the battery pack into a plurality of cells, and a plurality of contact portions of the surrounding air with the battery pack. It is preferable to create a fluid model divided into cells and modeled. In this case, the temperature calculation unit calculates, for each cell of the solid external model, a heat transfer amount by unsteady analysis using the fluid temperature of the cell of the fluid model adjacent to each cell, and based on the heat transfer amount It is preferable to calculate the temperature.

According to related that temperature predicting apparatus in the battery pack disclosed, for using the actual measurement data regarding internal temperature change of the battery pack obtained by measuring beforehand, to keep a measured data corresponding to the situation of temperature prediction in advance Therefore, regardless of the state of the battery cell (for example, even when a complicated phenomenon with strong non-stationarity such as when the battery cell has run out of heat), the temperature related to the battery pack is accurately predicted. Can do.

It is a schematic diagram for demonstrating the temperature prediction method regarding the battery pack which concerns on one Embodiment, (a) is a typical longitudinal cross-sectional view of a battery pack, (b) is the fluid model in the area | region R of Fig.1 (a). (C) shows the solid model (solid internal model and solid external model) in the region R of FIG. 1 (a). It is a block diagram which illustrates the composition of the temperature prediction device about the battery pack concerning one embodiment. It is a figure explaining the analysis process of the temperature prediction method regarding the battery pack which concerns on one Embodiment. It is a figure for demonstrating the acquisition method of gas temperature, (a) is a typical top view (those without a cover) which shows the measurement point in a battery pack, (b) and (c) are acquired by measurement. It is an example of the graph (a part of actual measurement data) which shows the temperature change in the measured measurement point. It is a figure for demonstrating the method of the space interpolation of gas temperature.

  Embodiments of the present invention will be described below with reference to the drawings. Note that the embodiment described below is merely an example, and there is no intention to exclude various modifications and technical applications that are not explicitly described in the following embodiment. Each configuration of the following embodiments can be implemented with various modifications without departing from the spirit thereof, and can be selected as necessary or can be appropriately combined.

[1. Analysis model]
A temperature prediction method and a temperature prediction apparatus related to a battery pack according to the present embodiment use thermal fluid analysis software, and each surface temperature and internal temperature of a plurality of battery cells built in the battery pack, the temperature of the battery module, the battery pack This is a method and apparatus for predicting all the temperatures related to the battery pack (hereinafter collectively referred to as “temperature related to the battery pack”) such as the temperature of the outer surface and the temperature of the inner surface. In this embodiment, by intentionally short-circuiting one battery cell among a plurality of battery cells built in the battery pack, a situation in which the battery cell has run out of heat is created, and the temperature change related to the battery pack in this situation And predict the distribution.

  As shown in FIG. 1A, the battery pack 1 to be analyzed is mounted, for example, under the floor of a vehicle (not shown) and used as a power source for the vehicle. The battery pack 1 is configured by incorporating a plurality of battery cells 3 in a case 7. In the present embodiment, eight battery cells 3 are connected in series to constitute one battery module 2. The battery pack 1 is configured by incorporating six battery modules 2 in a case 7. The case 7 has a tray 7a on which each battery module 2 is placed, and a cover 7b that covers the tray 7a from above. The battery pack 1 is hermetically sealed by fastening both flange portions with fastening members such as bolts in a state where a gasket is interposed between the flange portion of the tray 7a and the flange portion of the cover 7b.

  For example, when the battery pack 1 is charged or when the vehicle is traveling, the temperature of the battery pack 1 increases due to the heat generated by the battery cells accompanying charging / discharging, and is cooled by the air flowing outside the battery pack 1, so that the temperature is present. Kept in range. However, when a certain battery cell 3 is internally short-circuited for some reason, the battery cell 3 generates heat with a heat generation amount larger than the heat generation amount at the time of charging / discharging, and this heat is transmitted to the adjacent battery cell 3 to successively battery. The cell 3 is abnormally heated. Such a phenomenon is called thermal runaway, and in addition to a rapid temperature change, a high-speed gas jet is generated from the heated battery cell 3, and the battery pack 1 is in an unsteady state for a long time. become.

  Therefore, in order to accurately predict the temperature related to the battery pack 1, it is necessary to calculate the amounts of heat transfer by three heat transfer modes (that is, convection, heat conduction, and radiation) by unsteady analysis. In the present embodiment, a strongly coupled method is not used for this unsteady analysis, and a three-dimensional analysis model simulating the battery pack 1 is obtained by using a solid part (that is, the battery pack 1) and a fluid part around the battery pack 1 (that is, the battery pack 1). The calculation time is greatly shortened by performing unsteady analysis for the solid portion and steady analysis that does not calculate the state change for the fluid portion.

  An example of the analysis model is shown in FIGS. These drawings show the internal cross section of the model corresponding to the portion of the region R surrounded by the alternate long and short dash line in FIG. 1 (a). FIG. 1 (b) shows the fluid model 6 and FIG. It is a solid model. The fluid model 6 is set by dividing the air region around the battery pack 1 (outside the battery pack 1) into a plurality of cells 60 (calculation grids). Among the plurality of cells 60 of the fluid model 6, the cell 60 positioned at a contact portion with the battery pack 1 (that is, a boundary portion with the solid model) is particularly referred to as a fluid boundary cell 61.

  The solid model is obtained by modeling a solid part of the battery pack 1 and is classified into a solid internal model 4 and a solid external model 5. The solid internal model 4 is set by dividing a solid portion inside the battery pack 1 (for example, the battery cell 3 housed in the case 7) and the inner surface and thickness portion of the case 7 into a plurality of cells 40. It is a model. The solid external model 5 is a model that is set by dividing a portion of the battery pack 1 in contact with the air outside (that is, the outer surface portion of the case 7 of the battery pack 1) into a plurality of cells 50.

  Among the plurality of cells 40 of the solid internal model 4, the cell 40 located at a portion in contact with the air inside the battery pack 1 is particularly referred to as a solid internal boundary cell 41. On the other hand, the plurality of cells 50 of the solid external model 5 are all boundary cells located in a portion that is in contact with the air outside the battery pack 1 (that is, the boundary portion with the fluid model 6). 50. In FIGS. 1B and 1C, reference numerals are given to some of the cells 40, 41, 50, 60 and 61.

  Each of the plurality of cells 40, 50 and 60 includes various parameters such as parameters for defining the size and shape of the cells 40, 50 and 60, parameters indicating temperature, parameters such as mass, specific heat and thermal conductivity. Numeric data is set. Note that the shape, size, number of divisions, division position, etc. of each of the plurality of cells 40, 50 and 60 are not particularly limited. For example, as shown in FIG. 1B, cells 40 and 50 in which a rectangular shape and a triangular shape are mixed may be set, or all may be rectangular cells. Further, as shown in FIG. 1C, all the cells 60 may be set to substantially the same size, or only the fluid boundary cell 61 is set smaller than the other cells 60 to analyze the boundary portion. The accuracy may be increased.

[2. Device configuration]
The temperature prediction device for the battery pack 1 of the present embodiment is realized by a general-purpose computer capable of executing a computer program 17 for thermal fluid analysis, for example. FIG. 2 is a schematic configuration diagram in the case where the computer 10 is used to configure the temperature prediction device for the battery pack 1. FIG. 3 is a diagram showing an analysis process performed using the computer 10.

  As shown in FIG. 2, a computer 10 (temperature prediction device) includes a CPU 11 (Central Processing Unit), a memory 12 [Read Only Memory (ROM), Random Access Memory (RAM), etc.], an external storage device 13 [Hard Disk Drive (HDD), Solid State Drive (SSD), optical drive, etc.], input device 14 (keyboard, mouse, etc.) and output device 15 (display, printer device, etc.). These are connected to be communicable with each other via a bus 16 (control bus, data bus, etc.) provided in the computer 10. The computer program 17 for numerical fluid analysis is installed in the external storage device 13.

  The CPU 11 reads the program installed in the external storage device 13 on the memory 12 and executes it, and outputs the calculation result to the output device 15. The shape of the battery pack 1 serving as an analysis model is set, for example, by diverting data created by general-purpose three-dimensional CAD (Computer Aided Design) software to the computer program 17 or by input from the input device 14. Further, analysis conditions (for example, initial conditions and boundary conditions), specific parameter setting values, and the like are set based on input from the input device 14 or as values given in advance.

  The function of the computer program 17 for numerical fluid analysis is schematically shown in FIG. The computer program 17 includes a model creation unit 17a, a condition setting unit 17b, a map creation unit 17c, a gas temperature acquisition unit 17d, and a temperature calculation unit 17e. Each of these elements may be realized by an electronic circuit (hardware), or a part of these functions may be provided as hardware and the other part may be software.

  The model creation unit 17a creates the analysis model described above. As shown in FIGS. 1B and 1C, the model creation unit 17 a includes a fluid model 6 that is modeled by dividing an air region around the battery pack 1 into a plurality of cells 60, and the battery pack 1. A solid internal model 4 in which an internal solid portion is divided into a plurality of cells 40 and modeled; and a solid external model 5 in which a contact portion with air around the battery pack 1 is divided into a plurality of cells 50 and modeled; Create

  Further, the model creating unit 17a sets a cell located in a contact portion with the air inside the battery pack 1 among the plurality of cells 40 as the solid internal boundary cell 41, and out of the plurality of cells 60, A cell located at the boundary between the model 5 and the fluid model 6 is set as a fluid boundary cell 61. Further, all the plurality of cells 50 are set as the solid outer boundary cells 50.

The condition setting unit 17b sets conditions used for analysis. As shown in FIG. 3, the condition setting unit 17 b sets a plurality of boundary temperatures Tb ₁ , Tb ₂ ,..., Tb _K as boundary conditions used for steady analysis of the fluid model 6. The condition setting unit 17b sets, for example, a temperature lower than the room temperature of the battery pack 1 (for example, 35 [° C.]) as the boundary temperature Tb ₁ and a temperature higher than the temperature when the battery pack 1 abnormally generates heat (for example, 500). [° C.]) was set as a boundary temperature Tb _K, the boundary temperature Tb ₂ is divided between them in a predetermined temperature interval (e.g. 50~100 [℃]), ..., is set as Tb _K-1. Note that K is an integer of 3 or more, and corresponds to the number of times of steady analysis described later.

The condition setting unit 17b sets an initial temperature Ts as an initial condition used for unsteady analysis of the solid internal model 4 and the solid external model 5. The initial temperature Ts is, for example, the normal temperature of the battery pack 1 (for example, 40 [° C.]). The condition setting unit 17b transmits the set boundary temperatures Tb ₁ , Tb ₂ ,..., Tb _K to the map creation unit 17c, and transmits the set initial temperature Ts to the temperature calculation unit 17e. Note that the method of setting the plurality of boundary temperatures Tb ₁ , Tb ₂ ,..., Tb _K and the initial temperature Ts by the condition setting unit 17b is not particularly limited.

The map creation unit 17 c creates two maps Mp ₁ and Mp ₂ using the result of steady analysis of the fluid model 6. For all fluid boundary cells 61, _two maps Mp ₁ and Mp ₂ are provided for each fluid boundary cell 61. Maps Mp ₁ and Mp ₂ are created. The maps Mp ₁ and Mp ₂ created here are used for unsteady analysis of the solid external model 5 described later.

First, the map creation unit 17c uses a plurality of boundary temperatures Tb ₁ , Tb ₂ ,..., Tb _K set by the condition setting unit 17b for each of the fluid boundary cells 61 of the fluid model 6 to perform steady analysis. I do. Here, as shown in FIG. 3, for each fluid boundary cell 61, steady analysis 1, with boundary temperature Tb ₁ as input value, steady analysis 2, with boundary temperature Tb ₂ as input value, boundary temperature Tb _K A steady analysis K is performed with the input values.

The steady analysis here means, for example, when a boundary temperature Tb ₁ which is one boundary condition is given, to what steady temperature the temperature of each fluid boundary cell 61 of the fluid model 6 having the boundary condition is. It is a numerical analysis of whether it converges or what kind of distribution the steady-state temperature is. Each of the boundary temperatures Tb ₁ , Tb ₂ ,..., Tb _K gives a temperature distribution at the boundary between the fluid model 6 and the solid external model 5. Therefore, the amount of heat transfer between the fluid boundary cell 61 located at the outermost solid external model 5 side adjacent thereto of the fluid model 6, boundary temperature Tb _1, Tb _2, ..., respectively fluid Tb _K It can be calculated based on the temperature of the boundary cell 61.

By the above K times steady analysis, for each fluid boundary cell 61, the heat transfer coefficient h, the temperature Twe of the solid outer boundary cell 50 adjacent to each fluid boundary cell 61 (hereinafter referred to as the outer wall surface temperature Twe), The temperature Tf of the fluid boundary cell 61 (hereinafter referred to as fluid temperature Tf) and the amount of radiation input heat Hi (hereinafter referred to as radiation input heat amount Hi) are calculated K times. That is, as shown in FIG. 3, in the steady analysis 1, the heat transfer coefficient h ₁ , the outer wall temperature Twe ₁ , the fluid temperature Tf _1, and the radiation heat input Hi ₁ are calculated, and in the steady analysis 2 the heat transfer coefficient h ₂ Outer wall temperature Twe ₂ , fluid temperature Tf ₂ and radiant heat input Hi ₂ are calculated. In steady analysis K, heat transfer coefficient h _K , outer wall temperature Twe _K , fluid temperature Tf _K and radiant heat input Hi _K are calculated. Is done.

The map creating unit 17c displays a graph in which the horizontal axis represents the outer wall temperature Twe and the vertical axis represents the fluid temperature Tf, and the K sets of outer wall temperature Twe and fluid temperature Tf [ie, coordinates (Twe ₁ , Plot (Tf ₁ ), (Twe ₂ , Tf ₂ ), ..., (Twe _K , Tf _K )], and calculate approximate lines (regression lines, interpolation functions) using least squares, principal component analysis, etc. Thus, the first map Mp ₁ is created. That is, the first map Mp ₁ shows the relationship between the fluid temperature Tf and the outer wall surface temperature Twe in a certain fluid boundary cell 61 and is created for each fluid boundary cell 61. The approximate straight line calculated here is a fluid temperature Tf expressed as a function of the outer wall surface temperature Twe. As a result, for each fluid boundary cell 61, the ratio of the change amount of the fluid temperature Tf to the change amount of the outer wall surface temperature Twe (the change amount of the fluid temperature Tf / the change amount of the outer wall surface temperature Twe, that is, the slope of the approximate line) is grasped. can do.

Similarly, the map creating unit 17c uses a graph in which the horizontal axis represents the outer wall surface temperature Twe and the vertical axis represents the radiation input heat amount Hi. Plot the coordinates (Twe ₁ , Hi ₁ ), (Twe ₂ , Hi ₂ ), ..., (Twe _K , Hi _K )], and use the least squares method, principal component analysis method, etc. to calculate the interpolation function) to create a second map Mp _2. That is, the second map Mp ₂ shows the relationship between the radiation heat input Hi and the outer wall surface temperature Twe in a certain fluid boundary cell 61, and is created for each fluid boundary cell 61. The approximate straight line calculated here represents the amount of heat input Hi as a function of the outer wall surface temperature Twe. Thus, for each fluid boundary cell 61, the ratio of the change amount of the radiation input heat amount Hi to the change amount of the outer wall surface temperature Twe (the change amount of the radiation input heat amount Hi / the change amount of the outer wall surface temperature Twe, that is, the slope of the approximate straight line). Can be grasped.

The number K of steady analysis coincides with the plot points when the maps Mp ₁ and Mp ₂ are created, and is set to a value (for example, 4 to 6) in consideration of the balance between calculation accuracy and calculation load. However, since the K steady analysis by the map creation unit 17c can be calculated independently, parallel processing is possible if there are sufficient calculation resources, and the time required for the calculation processing is large because the number K of boundary temperatures Tb is large. It is thought that there is not much change. Therefore, for example, when there are sufficient calculation resources, it is possible to set the number K of the boundary temperatures Tb larger to further increase the calculation accuracy.

  The gas temperature acquisition unit 17d acquires the temperature of the air adjacent to each solid internal boundary cell 41 of the solid internal model 4 as the gas temperature Ta based on the actual measurement data 9 regarding the temperature change inside the battery pack 1 acquired in advance. Is. The gas temperature Ta acquired here is used for unsteady analysis of the solid internal model 4 described later.

  First, actual measurement data 9 will be described with reference to FIGS. 4A is a schematic top view showing the temperature measurement points in the battery pack 1 (with the cover 7b omitted), and FIGS. 4B and 4C show the battery pack 1 obtained by actual measurement. It is an example of the graph (a part of actual measurement data) which shows an internal temperature change. 4B is a graph of the measurement point A, and FIG. 4C is a graph of the measurement point M.

  As described above, since the temperature in the battery pack 1 changes abruptly when the battery cell 3 undergoes thermal runaway, the temperature in such an unsteady state cannot be predicted by the conventional estimation method. Therefore, in the present embodiment, a state in which the battery cell 3 is thermally runaway is created in advance, and temperature changes at a plurality of positions in the battery pack 1 when the thermal runaway is actually measured are measured. In the present embodiment, as shown in FIG. 4A, among the six battery modules 2 built in the battery pack 1, the uppermost battery cell 3 of the third battery module 2 from the left is internally short-circuited. (For example, a nail is stabbed at the position of the arrow in the figure), and a state in which the battery cell 3 is thermally runaway is created.

  When the battery cell 3 at the position indicated by the arrow in FIG. 4A is internally short-circuited, the battery cell 3 generates heat with a heat generation amount larger than the heat generation amount during charge / discharge. This heat is transmitted to the adjacent battery cell 3, and the adjacent battery cell 3 also generates heat with a large calorific value. In the present embodiment, since one battery module 2 is composed of eight battery cells 3, the eight battery cells 3 generate abnormal heat one after another. In addition, since the internal pressure rises in the battery cell 3 whose temperature has rapidly increased, the gas is released to the outside (that is, inside the battery pack 1).

  In addition, at 14 measurement points A to N indicated by white triangles in FIG. 4A, the temperature change from the moment when the internal short circuit is first performed is measured. Temperature sensors are arranged at the measurement points A to N, respectively. Each temperature sensor detects a temperature change at that point and outputs the detected information to the computer 10. The information output here is stored in the memory 12 of the computer 10 as the actual measurement data 9.

For example, the temperature sensor at the measurement point A measures the temperature change of the surface of the battery cell 3 that is caused to run out of heat. Further, the temperature sensor at the measurement point M measures the temperature change of the air (space in the battery pack 1) in the vicinity of the battery cell 3 to be thermally runaway. The graphs of these measurement results are shown in FIGS. 4B and 4C. Times t _{1 to} t ₈ in the graph are times when the battery cells 3 generate heat with a large amount of heat. It can be seen that the temperature at the measurement point increases as the calorific value of the battery cell 3 rapidly increases. The actual measurement data 9 includes information related to temperature changes measured at the measurement points A to N (for example, graphs as shown in FIGS. 4B and 4C).

  The gas temperature acquisition unit 17d calculates the gas temperature Ta adjacent to each solid internal boundary cell 41 of the solid internal model 4 by spatially interpolating measured temperatures at a plurality of positions in the battery pack 1 using the actual measurement data 9. To do. Spatial interpolation (also referred to as three-dimensional interpolation) estimates (calculates) values (temperatures) at points in the vicinity of these measurement points using data (in this case, temperature) from multiple measurement points that vary spatially The technique to do. In the present embodiment, the gas temperature Ta of air adjacent to the solid inner boundary cell 41 is calculated from the temperatures of three measurement points among the plurality of measurement points A to N.

Here, a spatial interpolation algorithm will be described with reference to FIG. First, the gas temperature acquisition unit 17d calculates the lengths of the center point (point 0) of the calculation grid and the surrounding measurement points, and the three measurement points (point 1) that are closest in length and are not collinear. Extract ~ 3). This point 0 corresponds to the air adjacent to the solid inner boundary cell 41. The peripheral measurement points correspond to a plurality of measurement points A to N. If the coordinates of these three points 1 to 3 are (x ₁ , y ₁ , z ₁ ), (x ₂ , y ₂ , z ₂ ) and (x ₃ , y ₃ , z ₃ ), respectively, these three points The plane equation passing through 1 to 3 is expressed by the following Equation 1. This plane is called a position plane. The coefficients a, b, and c are calculated from the determinant of Expression 2 below.

  The plane normal equation passing through the point 1 is expressed by the following formula 3.

The gas temperature acquisition unit 17d creates a point 4 on this normal. The length between the point 4 and point 1 is set to a value corresponding to the measured temperature T ₁ of the point 1 (e.g. a value equal to proportional to the measured temperatures T ₁ values and measured temperatures T _1). For example, when the point 1 is the measurement point A, the length between the point 4 and the point 1 (measurement point A) is set to a value corresponding to the measurement temperature at the measurement point A. In the present embodiment, the gas temperature acquisition unit 17d calculates the coordinates (x ₄ , y ₄ , z ₄ ) of the point 4 from the simultaneous equations of the following equations 4 and 5.

Similarly, the gas temperature acquisition unit 17d creates points 5 and 6 using the plane normal equation of points 2 and 3 and the measured temperatures T ₂ and T ₃ , and sets the coordinates of points 5 and 6 as coordinates. calculate. From these coordinates, the plane equation passing through the points 4 to 6 is expressed by the following equation 6. This plane is called a temperature plane. The coefficients a ₁ , b ₁ , and c ₁ are calculated from the determinant of Expression 7 below.

That is, in the present embodiment, the temperature at a certain point in the position plane is equal to the length between both planes of the normal passing through this point. Therefore, the gas temperature acquisition unit 17d projects the coordinates (x ₀ , y ₀ , z ₀ ) of the center point 0 of the calculation grid onto the position plane, and coordinates (x ₇ , y ₇ , z ₇ ) is calculated from the simultaneous equations of Equation 8 and Equation 9 below.

The gas temperature acquisition unit 17d determines the coordinates (x ₈ , y ₈ , z ₈ ) of the intersection (point 8) between the normal of the position plane that passes through the point 0 and the temperature plane, and the simultaneous equations of the following equations 10 and 11. Calculate from

  The positional relationship between point 0 and points 1 to 3 is substantially equal to the positional relationship between point 7 and points 1 to 3. Therefore, the gas temperature acquisition unit 17d calculates the temperature at the point 0 (that is, the gas temperature Ta) from the lengths of the points 7 and 8. In this way, the gas temperature acquisition unit 17d repeatedly calculates the gas temperature Ta of the air adjacent to the solid inner boundary cell 41 at a predetermined calculation cycle using the actual measurement data 9. This calculation cycle is the same as the calculation cycle of the unsteady analysis by the temperature calculation unit 17e described later. The gas temperature acquisition unit 17d transmits the calculated gas temperature Ta to the temperature calculation unit 17e.

  The temperature calculation unit 17e calculates the heat transfer amount of each cell 40 of the solid internal model 4 and the heat transfer amount of each cell 50 of the solid external model 5, and calculates the temperature of each cell 40, 50 from these heat transfer amounts. is there. For each cell 40, 50, the temperature calculation unit 17e predetermines a heat transfer amount in a heat transfer mode that affects the temperature of the cell among heat transfer amount qt by heat conduction, heat transfer amount qr by radiation, and heat transfer amount qc by convection. And the temperature of the cell is calculated based on the total heat transfer amount q obtained by adding the calculated heat transfer amounts. Thereby, the change and distribution of the temperature regarding the battery pack 1 are estimated. The calculation cycle is appropriately set in consideration of calculation accuracy and calculation load.

Here, the heat transfer amount qt due to heat conduction and the heat transfer amount qr due to radiation can be calculated only by calculation on the solid internal model 4 and solid external model 5 side, but the heat transfer amount qc (hereinafter referred to as convection heat transfer amount qc). Cannot be calculated without the temperature information of the fluid adjacent to the solid internal model 4 and the solid external model 5. Therefore, the temperature calculation unit 17e requires the condition setting unit 17b and the cell located at the boundary with the fluid (that is, the solid inner boundary cell 41 and the solid outer boundary cell 50) that require calculation of the convective heat transfer amount qc. The amount of convection heat transfer qc is calculated using the information transmitted from the gas temperature acquisition unit 17d and the maps Mp ₁ and Mp ₂ created by the map creation unit 17c.

  A specific calculation method of the convection heat transfer amount qc will be described. The temperature calculation unit 17e uses a different calculation method to calculate the convective heat transfer amount qci of each solid internal boundary cell 41 of the solid internal model 4 and the convective heat transfer amount qce of each solid external boundary cell 50 of the solid external model 5 using different calculation methods. Calculated by steady state analysis. The former calculation method is called a first calculation method, and the latter calculation method is called a second calculation method.

  The non-stationary analysis here refers to, for example, when an initial temperature Ts which is one initial condition is given, the temperature of each cell of the solid internal model 4 and the solid external model 5 having the initial condition is time. It is a numerical analysis of how the temperature changes over time or how the temperature distribution becomes.

  The temperature calculation unit 17e calculates the convection heat transfer amount qci for each solid inner boundary cell 41 by unsteady analysis using the first calculation method, and calculates the heat transfer amount qt by heat conduction and the heat transfer amount qr by radiation as necessary. The temperature of the cell 41 is calculated as the wall surface temperature Twi based on the total heat transfer amount q obtained by adding these. In the first calculation method, actual measurement data 9 acquired in advance by actual measurement is used as the temperature information of the fluid.

  That is, the temperature calculation unit 17e uses the gas temperature Ta of the air adjacent to each solid inner boundary cell 41 calculated by spatial interpolation from the actual measurement data 9 by the gas temperature acquisition unit 17d. The temperature calculation unit 17e substitutes this gas temperature Ta into the following equation 12 to calculate the convective heat transfer amount qci of the cell 41. Twi in Expression 12 is the wall surface temperature of the cell 41 calculated in the previous calculation cycle. In the first calculation cycle, the initial temperature Ts set by the condition setting unit 17b is substituted as the wall surface temperature Twi. The gas temperature Ta uses a value calculated in the same cycle as the calculation cycle for calculating the convection heat transfer amount qci.

The temperature calculation unit 17e calculates the convection heat transfer amount qce for each solid outer boundary cell 50 by unsteady analysis using the second calculation method, and also calculates the heat transfer amount qt by heat conduction and the heat transfer amount qr by radiation as necessary. And the temperature of the cell 50 is calculated as the outer wall surface temperature Twe based on the total heat transfer amount q. In the second calculation method, the maps Mp ₁ and Mp _{2 of} the fluid boundary cell 61 adjacent to each solid outer boundary cell 50 created by the map creating unit 17c are used.

That is, the temperature calculation unit 17e applies the outer wall surface temperature Twe of each solid outer boundary cell 50 calculated in the previous calculation cycle to the two maps Mp ₁ and Mp ₂ , respectively, and the fluid boundary adjacent to the cell 50 The fluid temperature Tf and the radiation heat input Hi of the cell 61 are acquired. Then, by substituting these values into the following formula 13, the convective heat transfer amount qce of the cell 50 is calculated. The outer wall surface temperature Twe applied to the maps Mp ₁ and Mp ₂ and Twe in the equation 13 are the outer wall surface temperature of the cell 50 calculated in the previous calculation cycle. In the first calculation cycle, the condition setting unit 17b The set initial temperature Ts is substituted as the outer wall surface temperature Twe.

In Expression 13, h is an average value of a plurality of heat transfer coefficients h ₁ , h ₂ ,..., H _K calculated by steady analysis by the map creating unit 17c. In Equation 13, σ is a Stefan-Boltzmann constant, and ε is an emissivity (constant).
That is, the temperatures of the boundary cells 41 and 50 of the solid internal model 4 and the solid external model 5 are given as the initial temperature Ts set by the condition setting unit 17b in the first calculation cycle, and in the second and subsequent calculation cycles. The wall surface temperature Twi and the outer wall surface temperature Twe calculated in the previous calculation cycle are given. On the other hand, these temperatures Ts, Twi, and Twe do not include information on the ambient temperature at which the solid internal model 4 and the solid external model 5 are surrounded, and the boundary conditions at the boundary between the fluid part and the solid part are Not determined.

On the other hand, the fluid temperature Tf given as a function of the outer wall surface temperature Twe is expressed in the first map Mp ₁ created by the map creating unit 17c. That is, if the initial temperature Ts or the outer wall temperature Twe calculated in the previous calculation cycle is substituted for the outer wall temperature Twe of this function, the fluid temperature Tf corresponding to the initial temperature Ts or the outer wall temperature Twe is calculated. Therefore, the amount of heat transfer between the solid outer boundary cell 50 of the solid outer model 5 and the fluid model 6 side adjacent thereto can be calculated. Further, the gas temperature Ta calculated by the gas temperature acquisition unit 17d is the temperature of the air adjacent to the solid internal boundary cell 41 located in the outermost shell of the solid internal model 4, and therefore, by using this gas temperature Ta, The amount of heat transfer between the solid inner boundary cell 41 and the air adjacent thereto can be calculated.

[3. flowchart]
A procedure (temperature prediction method) when the computer 10 executes the computer program 17 will be described using the analysis process of FIG.
In step S10, data of the battery pack 1 serving as an analysis model is prepared or input from the external storage device 13, the input device 14, or the like, and the above-described solid internal model 4, solid external model 5 and fluid model are input by the model creation unit 17a. 6 is created (model creation step). In addition, a plurality of boundary temperatures Tb ₁ , Tb ₂ ,..., Tb _K are set by the condition setting unit 17b, and an initial temperature Ts is set.

In step S20, steady analysis 1 using the plurality of boundary temperatures Tb ₁ , Tb ₂ ,..., Tb _K set in step S10 for each of the fluid boundary cells 61 of the fluid model 6 by the map creating unit 17c. , Steady analysis 2,..., Steady analysis K is performed. Then, for each fluid boundary cell 61, K pieces of heat transfer coefficient h, outer wall surface temperature Twe, fluid temperature Tf, and radiation heat input amount Hi are calculated (steady state analysis step).

In the subsequent step S30, the map creating unit 17c plots the outer wall surface temperature Twe and the fluid temperature Tf of the K sets obtained by steady analysis by taking the outer wall surface temperature Twe on the horizontal axis and the fluid temperature Tf on the vertical axis. An approximate straight line is calculated using a square method or the like, and a first map Mp ₁ is created for each fluid boundary cell 61 (map creation step). Similarly, taking the outer wall temperature Twe on the horizontal axis and the radiant heat input Hi on the vertical axis, the outer wall temperature Twe and the radiant heat input Hi of the K sets obtained by steady state analysis are plotted, using the least square method, etc. An approximate straight line is calculated, and a second map Mp ₂ is created for each fluid boundary cell 61 (map creation step).

In step S40, the temperature calculation unit 17e performs an unsteady analysis at a predetermined calculation cycle for each solid outer boundary cell 50 of the solid outer model 5, and calculates the outer wall surface temperature Twe of each solid outer boundary cell 50. A temperature change is obtained (temperature calculation step). In this calculation step, when calculating the convective heat transfer amount qce, the initial temperature Ts set in step S10 and the maps Mp ₁ and Mp ₂ created in step S30 are used. That is, the initial temperature Ts or the outer wall surface temperature Twe calculated in the previous calculation cycle is applied to the maps Mp ₁ and Mp ₂ , respectively, and the fluid temperature Tf and the radiant heat input Hi are acquired, and these are used for the convective heat transfer amount. qce is calculated.

  On the other hand, in step S35, the gas temperature Ta of the air adjacent to each of the solid internal boundary cells 41 of the solid internal model 4 is calculated by spatial interpolation based on the actual measurement data 9 acquired in advance by the gas temperature acquisition unit 17d. (Gas temperature acquisition step). In step S45, the temperature calculation unit 17e performs an unsteady analysis at a predetermined calculation cycle on each solid inner boundary cell 41 of the solid inner model 4, and calculates the wall surface temperature Twi of each solid inner boundary cell 41. Thus, a temperature change is obtained (temperature calculation step). In this calculation step, when calculating the convection heat transfer amount qci, the initial temperature Ts set in step S10 and the gas temperature Ta calculated in step S35 are used.

  The processes in steps S20 to S40 and the processes in steps S35 and S45 are executed in parallel. The unsteady analysis in step S40 and the unsteady analysis in step S45 are performed at the same timing in the same calculation cycle.

[4. effect]
(1) The above-described temperature prediction device 10 predicts the temperature related to the battery pack 1 by the above-described procedure (temperature prediction method). That is, since the above-described temperature prediction device 10 uses the actual measurement data 9 regarding the temperature change inside the battery pack 1 acquired in advance by actual measurement, the actual measurement data corresponding to the temperature prediction situation is prepared in advance. Regardless of the state of the cell 3 (for example, even when a complicated phenomenon with strong non-stationarity such as when the battery cell 3 has run out of heat), the temperature related to the battery pack 1 is accurately predicted. Can do. For example, a temperature change such as how the temperature of a certain battery module 2 in the battery pack 1 changes with the passage of time since a certain battery cell 3 started to abnormally heat due to an internal short circuit, or a plurality of times at a certain time The temperature distribution of the battery module 2 can be predicted.

  (2) In the temperature prediction apparatus 10 and the temperature prediction method described above, the gas temperature Ta is calculated by spatially interpolating the measurement temperatures at a plurality of positions (measurement points A to N) in the battery pack 1 acquired in advance. Even if all the temperatures in the pack 1 are not actually measured, the gas temperature Ta of the air adjacent to the cell 41 can be obtained for all the solid internal boundary cells 41 of the solid internal model 4. As a result, the number of temperature sensors for actual measurement can be reduced, leading to cost reduction, and the trouble of actual measurement and the capacity of the memory 12 can be reduced.

  (3) In the temperature prediction device 10 and the temperature prediction method described above, the solid external model 5 is created by modeling the contact portion with the air around the battery pack 1, and each cell 50 of the solid external model 5 is also unsteady. Since the heat transfer amount q is calculated by analysis and the temperature is calculated based on this, the temperature change and temperature distribution of the outer wall surface of the battery pack 1 can also be predicted.

(4) In the temperature prediction apparatus 10 and the temperature prediction method described above, steady analysis is performed for each fluid boundary cell 61 of the fluid model 6 in which the air around the battery pack 1 is modeled. Can be shortened.
(5) In the temperature prediction device 10 and the temperature prediction method described above, the temperature of the portion in contact with the air around the battery pack 1 is predicted in consideration of the influence of the radiation heat input Hi. Prediction accuracy can be further increased.

[5. Others]
Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the spirit of the present invention.
In the above-described embodiment, the case where the fluid temperature Tf and the radiation heat input amount Hi are each expressed as a linear function of the outer wall surface temperature Twe in the map creation process for creating the maps Mp ₁ and Mp ₂ is exemplified. The function is not limited to a linear function, and may be another function such as a quadratic function or an exponential function.

  Also, the solid internal model 4, the solid external model 5, and the fluid model 6 created by the model creation unit 17a in the above embodiment are merely examples, and are not limited to those described above. For example, the solid internal model 4 may be modeled by dividing a solid portion that contacts the air in the battery pack 1 into a plurality of cells, and the solid external model 5 The solid part (that is, the outer wall portion of the battery pack 1) in contact may be divided into a plurality of cells and modeled. Further, the fluid model 6 may be modeled by dividing the air region at the contact portion between the air and the battery pack 1 into a plurality of cells. That is, each of the solid internal model 4, the solid external model 5, and the fluid model 6 may have at least the solid internal boundary cell 41, the solid external boundary cell 50, and the fluid boundary cell 61, respectively.

Moreover, in order to predict the temperature change and temperature distribution of the battery module 2 or the battery cell 3, at least the solid internal model 4 may be set. In this case, the creation of the solid external model 5 and the fluid model 6 can be omitted, and the map creation unit 17c can also be omitted.
In the above embodiment, the gas temperature Ta of the air adjacent to the solid inner boundary cell 41 is calculated by spatially interpolating the measured temperatures at a plurality of positions, but the method for acquiring the gas temperature Ta is not limited to this. For example, the measurement temperature at the measurement point closest to the solid inner boundary cell 41 may be obtained as it is as the gas temperature Ta. In this case, the calculation load can be reduced.

Moreover, regarding the solid outer boundary cell 50 of the solid outer model 5, when calculating the convective heat transfer amount qce, the average value of the plurality of heat transfer coefficients h _{1 to} h _K calculated by the map creating unit 17c is used. The heat transfer coefficient h is not limited to an average value. For example, one may use the maximum value and the minimum value of the plurality of heat transfer coefficient h ₁ to h _K, or may be an intermediate value of the maximum value and the minimum value of the plurality of heat transfer coefficient h ₁ to h _K.

In the above embodiment, in the unsteady analysis, the outer wall surface temperature Twe and wall surface temperature Twi calculated in the previous calculation cycle are used in the current calculation cycle. However, the outer wall temperature Twe and wall surface temperature used in the current calculation cycle are used. Twi is not limited to the one calculated in the previous calculation cycle. For example, a value calculated in the previous calculation cycle may be used, or an average value of values calculated in the previous calculation cycle and the previous calculation cycle may be used.
In addition, when the battery pack 1 is mounted on a vehicle and an under cover that greatly affects heat transfer is provided, the heat transfer amount qt by heat conduction can be calculated by including the under cover in the solid external model 5. preferable.

In the above embodiment, the convection heat transfer amount qci of each solid inner boundary cell 41 is calculated using Equation 12. This formula 12 uses the formula for calculating the natural convection heat transfer coefficient of the horizontally upward heating flat plate. In order to further improve the calculation accuracy, the solid internal boundary cell 41 is divided into three, horizontal upward, horizontal downward and vertical. The heat transfer coefficients may be set separately.
In the above embodiment, the process of step S40 and the process of step S45 in FIG. 3 are both described as the temperature calculation process. These two steps are both performed by the temperature calculation unit 17e, and are steps for calculating the heat transfer amount by unsteady analysis and calculating the temperature based on the heat transfer amount. In any step, the initial temperature Ts is used as the initial value of the unsteady analysis. Since the two steps are common in these points, both have been described as the temperature calculation step.

  In the above embodiment, the case where the battery cell 3 is in a thermal runaway state has been described as an example of the assumed state of analysis. However, the assumed state of analysis is not limited to this, and actual measurement data corresponding to the state of analysis is acquired in advance. Thus, the temperature related to the battery pack 1 in various situations can be predicted. Furthermore, according to this method, even in the case of the battery pack 1 in which a sudden temperature change or a long-term unsteady phenomenon occurs, the temperature change and temperature distribution related to the battery pack 1 can be accurately calculated while reducing the calculation time. Can be predicted. Further, the battery pack 1 to be analyzed is not limited to a battery pack used as a power source of a vehicle or mounted under the floor of the vehicle. For example, the battery pack 1 is a battery pack built in an emergency power supply facility or an electronic device. Also good. The battery pack 1 is not limited to a battery module 2 including a plurality of battery cells 3, and may include a plurality of battery cells 3 that do not constitute a battery module.

DESCRIPTION OF SYMBOLS 1 Battery pack 2 Battery module 3 Battery cell 4 Solid internal model 5 Solid external model 6 Fluid model 9 Actual measurement data 10 Computer (temperature prediction apparatus)
17 computer program 17a model creation unit 17b condition setting unit 17c map creation unit 17d gas temperature acquisition unit 17e temperature calculation unit 40 solid internal model cell 41 solid internal boundary cell 50 solid external boundary cell (solid external model cell)
60 Fluid Model Cell 61 Fluid Boundary Cell
Ta gas temperature
Twi Wall temperature
Twe outer wall temperature
Tf Fluid temperature

Claims (3)

An apparatus for predicting a temperature related to a battery pack incorporating a plurality of battery cells using thermal fluid analysis software,
A model creation unit for creating a solid internal model that is obtained by dividing a solid part that contacts the air inside the battery pack into a plurality of cells;
A gas temperature acquisition unit that acquires, as a gas temperature, the temperature of the air adjacent to each cell of the solid internal model, based on actual measurement data related to a temperature change inside the battery pack acquired in advance by actual measurement;
For each cell of the solid internal model, a heat transfer amount is calculated by unsteady analysis using the gas temperature acquired by the gas temperature acquisition unit, and a temperature calculation unit that calculates a temperature based on the heat transfer amount; and A temperature prediction device for a battery pack, comprising: The gas temperature obtaining unit, and calculates the gas temperature measured temperature by spatial interpolation of a plurality of positions in advance actually measured the battery pack, the temperature predicting apparatus a battery pack according to claim 1, wherein. The model creation unit includes a solid external model that is modeled by dividing a contact portion of the battery pack with the surrounding air into a plurality of cells, and a contact portion of the surrounding air with the battery pack into a plurality of cells. Create a fluid model that is divided and modeled,
The temperature calculation unit calculates a heat transfer amount by unsteady analysis for each cell of the solid external model using a fluid temperature of a cell of the fluid model adjacent to each cell, and calculates a temperature based on the heat transfer amount. calculating characterized by a temperature predicting apparatus relates claim 1 or 2 battery pack according.

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