JP6610330B2 - Battery module temperature trend prediction method, prediction device, and prediction program - Google Patents

Description

  The present invention relates to a method, an apparatus, and a program for simply predicting temperature trends of a plurality of battery modules arranged in a battery pack.

  Conventionally, in the vehicle design and development stage, fluid flow (air) and temperature fields in battery packs are predicted by computer simulation using computational fluid dynamics (CFD) analysis software. Yes. For example, Patent Document 1 calculates the influencing factors of the heat dissipation performance of the single battery (battery cell) in the battery pack, the flow rate of the cooling air for the assembled battery (battery module), and the calorific value of the single battery. A method for evaluating the heat dissipation of an assembled battery by obtaining the temperature rise amount of the unit cell from the value is disclosed.

JP 2001-297801 A

  In general, an in-vehicle battery pack is configured by arranging a plurality of battery modules including a plurality of battery cells in a case. If an air-cooled battery pack is used, there is a gap between battery cells or between battery modules. Is provided. A duct for supplying cold air from the blower to the battery cell is disposed in the battery pack. When this duct has a plurality of air distribution ports, it is possible to improve the efficiency of cooling the battery cells by designing the cool air from each air distribution port to flow toward the gap. It is known that the change in the temperature of the battery cell has a high contribution ratio of the flow rate of the cold air flowing out from each air outlet (hereinafter referred to as “air distribution rate”) to the total flow rate of the cold air flowing in the duct. Therefore, in the past, three-dimensional CFD analysis (three-dimensional calculation) was performed for various air distribution rates while changing the configuration and shape of the duct, and the temperature of the battery cell was predicted by simulation to obtain an appropriate air distribution. A design study was conducted to select the rate.

  However, in this examination method, even if the shape of the duct is slightly changed, a final (appropriate) duct shape is performed in order to perform a three-dimensional calculation modeling the detailed structure in the battery pack each time. It took a long time to get In addition, there is a concern that the duct shape obtained by the three-dimensional calculation performed within a limited time is away from the appropriate shape. That is, there is a problem that it is difficult to achieve both reduction in calculation time and acquisition of an appropriate duct shape. In order to solve this problem, a method of reducing the calculation load by converting the three-dimensional calculation into one dimension can be considered. However, this method is known to break down the calculation because the heat transfer path changes greatly under a situation where the flow field changes greatly. Therefore, it is desired to propose a method capable of calculating even when the flow field in the battery pack changes greatly.

  This case has been devised in view of such a problem, and it shortens the calculation time until an appropriate duct shape is obtained, and also shows a temperature trend even when the flow field in the battery pack changes greatly. One object is to provide a battery module temperature trend prediction method, a prediction device, and a prediction program that can be predicted. The present invention is not limited to this purpose, and is a function and effect derived from each configuration shown in the embodiment for carrying out the invention described later, and has another function and effect that cannot be obtained by conventional techniques. is there.

  (1) In the battery module temperature trend prediction method disclosed herein, a plurality of battery modules including a plurality of battery cells are disposed in the case, and a cooling duct having a plurality of air distribution ports is disposed in the case. In the provided battery pack, a prediction method for causing a computer to execute a process of predicting a temperature trend of the battery module, wherein the reference state in which all the plurality of air distribution ports of the duct are opened and the plurality of air distribution ports are integrated. For each of a plurality of different closed states closed one by one in sequence, an analysis step of calculating each cold heat amount from each of the plurality of air distribution ports and each cell temperature of the plurality of battery cells by CFD analysis; The amount of change in each cold heat amount in each closed state with respect to each cold heat amount is calculated as each cold heat difference, and before the cell temperature in the reference state with respect to each cell temperature A calculation step for calculating a change amount of each cell temperature in each closed state as each cell temperature difference and a theoretical formula relating the correspondence between each cold heat difference and each cell temperature difference in each closed state are constructed. A construction step and a prediction step of predicting a temperature trend of the battery module with respect to each cooling amount of a new shape duct having the same basic configuration as the duct, using a coefficient obtained from the theoretical formula.

(2) It is preferable to use an air distribution rate indicating a ratio of an outflow amount of the fluid from the air distribution port to an inflow amount of the fluid into the duct as the cold heat amount.
(3) When the plurality of battery cells are disposed in plane symmetry with respect to a predetermined plane of symmetry, and the plurality of air distribution ports are provided in plane symmetry with respect to the plane of symmetry In the construction step, it is preferable to use the respective cooling / heating differences of the air distribution ports located on the same side as the battery cell with respect to the symmetry plane in the construction of the theoretical formula.

(4) In the calculation step, for each closed state in which the air distribution port located on the same side as the battery cell with respect to the symmetry plane is closed, the cooling difference on the same side and the respective on the same side. It is preferable to calculate the cell temperature difference.
(5) In the prediction step, it is preferable to predict the temperature tendency with respect to the air distribution rate for each air distribution port of the new shape duct acquired by CFD analysis performed on the new shape duct.
(6) In the prediction step, it is preferable to predict the temperature tendency with respect to each target air distribution rate of the new shape duct set based on a predetermined condition.

  (7) In the battery module temperature trend prediction apparatus disclosed herein, a plurality of battery modules including a plurality of battery cells are disposed in the case, and a cooling duct having a plurality of air distribution ports is disposed in the case. In the provided battery pack, a prediction device that performs a process of predicting a temperature trend of the battery module, wherein the reference state in which the plurality of air distribution ports of the duct are all opened and the plurality of air distribution ports one by one For each of a plurality of different closed states blocked in order, an analysis unit for calculating each cold heat amount from each of the plurality of air distribution ports and each cell temperature of the plurality of battery cells by CFD analysis, and each of the reference states The amount of change in the amount of each cold in the closed state relative to the amount of heat is calculated as a difference in each heat, and the amount of change in the closed state relative to the cell temperature in the reference state A calculation unit that calculates a change amount of the cell temperature as each cell temperature difference, a construction unit that constructs a theoretical formula that correlates the correspondence between each cold temperature difference and each cell temperature difference in each closed state, and the theory A predicting unit that predicts a temperature trend of the battery module with respect to each cooling amount of a new-shaped duct having the same basic configuration as the duct, using a coefficient obtained from an equation.

  (8) According to the battery module temperature trend prediction program disclosed herein, a plurality of battery modules including a plurality of battery cells are disposed in the case, and a cooling duct having a plurality of air distribution ports is disposed in the case. In the provided battery pack, a prediction program for executing a process for predicting a temperature trend of the battery module, wherein the reference state in which the plurality of air distribution ports of the duct are all opened and the plurality of air distribution ports one by one For each of a plurality of different closed states blocked in order, an analysis step of calculating each cold heat amount from each of the plurality of air distribution ports and each cell temperature of the plurality of battery cells by CFD analysis, and each of the reference states While calculating the amount of change of each cold quantity of each closed state with respect to the quantity of cold as each cold difference, each of the cell temperature of the reference state Construction that builds a theoretical formula that relates the correspondence between each cooling temperature difference and each cell temperature difference in each closed state, and a calculation step that calculates the amount of change in each cell temperature in the chain state as each cell temperature difference The computer is caused to execute a process and a predicting process of predicting a temperature trend of the battery module with respect to each cooling amount of a new shape duct having the same basic configuration as the duct, using a coefficient obtained from the theoretical formula.

  For the new shape duct that has the same basic configuration as the duct used to construct the theoretical formula, the temperature trend can be predicted without performing CFD analysis. It can be greatly shortened. In other words, it is possible to easily and quickly grasp the temperature trend for each module, so that it is possible to shorten the time (design time) until an appropriate duct shape can be designed and acquired, thereby reducing calculation cost and design cost. be able to.

  Also, in the construction of the theoretical formula, in order to calculate each cold heat amount and each cell temperature by creating a plurality of patterns in which the flow field in the battery pack is intentionally changed by closing a plurality of air distribution ports one by one in order, It is possible to construct a theoretical formula that captures the maximum change in the flow field in the battery pack. Thereby, even if it is a case where the flow field in a battery pack changes a lot, the temperature tendency with respect to each cold energy of a new shape duct can be predicted.

It is a typical whole block diagram of a battery pack. (A) is the top view which modeled the blower of FIG. 1, (b) is the top view which modeled the battery module of FIG. It is a block diagram which illustrates the composition of the temperature trend prediction device of a battery module. It is a flowchart which illustrates the procedure of the temperature tendency prediction method of a battery module.

  With reference to the drawings, a battery module temperature trend prediction method, a prediction device, and a prediction program will be described. Each embodiment shown below is only an example, and there is no intention of excluding various modifications and application of technology that are not clearly shown in each of the following embodiments. Each configuration of the present embodiment can be implemented with various modifications without departing from the spirit thereof. Further, they can be selected as necessary, or can be appropriately combined.

[1. Overview]
The battery module temperature trend prediction method, prediction apparatus, and prediction program according to this embodiment include a battery pack in which a plurality of battery modules are disposed in a case and a cooling duct having a plurality of air distribution ports is provided. 1 predicts temperature trends of a plurality of battery modules. “Temperature trend” here refers to the direction and amount of change in module temperature, how much it rises or falls with respect to the temperature of the battery module in the reference flow field (hereinafter referred to as “module temperature”). To do.

  The battery module is a module in which a plurality of battery cells are connected in series. The temperature of the battery cell (hereinafter referred to as “cell temperature”) varies depending on the influence of the calorific value of the battery cell itself and the amount of heat for cooling the battery cell (hereinafter referred to as “cold heat amount”). Therefore, when the heat generation amount of the battery cell is considered to be constant, the cell temperature changes depending on the amount of cold received from each air outlet. This amount of cold heat is the flow rate of cold air flowing out from each air outlet of the duct (hereinafter referred to as “air flow rate”) or the ratio of each air flow rate to the amount of cold air flowing into the duct (total flow rate in the duct) (hereinafter referred to as “air flow rate”). It has a positive correlation with the “air distribution rate” and can be replaced with the air distribution amount or the air distribution rate. In the present embodiment, the air distribution rate is used as the amount of cold heat. The air distribution rate of each air distribution port is determined by the configuration and shape of the duct, and is a major factor in determining the cooling performance of the battery cell.

  Conventionally, each time the duct configuration or shape is changed, a three-dimensional CFD analysis (three-dimensional calculation) is performed on the air distribution rate, and the cell distribution temperature is predicted to appropriately adjust the air distribution rate of each air distribution port. The design study of setting to a proper value was underway. However, in this method, even if the basic structure of the duct (for example, the size of the entire duct and the number and position of the air distribution ports) is the same, the air distribution rate changes if the shape is changed a little. Each time, three-dimensional calculation is performed, which requires considerable calculation time, and the calculation cost has increased accordingly.

  For this reason, in the prediction method of this embodiment, first, the temperature trend is calculated simply and at high speed for each module, and the time (design time) until an appropriate duct shape (each air distribution rate) can be designed and acquired can be shortened. Plan. Specifically, when the duct shape is changed without changing the basic structure (basic structure) of the duct, three-dimensional CFD analysis is performed for each cell temperature for each air distribution rate of the new shape duct. By calculating without doing, the temperature tendency of the battery module at each air distribution rate is predicted. Then, based on the predicted temperature trend, each air distribution rate within which all module temperatures fall within a predetermined temperature range (the temperature difference between all module temperatures becomes small) and the module temperature does not become too high. Ask for.

  The “basic structure of the duct” here refers to the size of the entire duct (width, length, height), the number of intakes and air distribution ports of the duct, and their positions. means. That is, changing the basic configuration of the duct means changing to a completely different duct. On the other hand, the “new shape duct” means a duct in which the shape and size of the air distribution port and the angle of the surface where the air distribution port is provided (direction of the air distribution port) are changed while maintaining the basic configuration of the duct. That is, changing the design of the duct shape means changing the detailed configuration of the duct. Even when the duct shape is changed in design, the air distribution rate of each air distribution port changes.

  In this prediction method, after determining the basic configuration of the duct, a theoretical formula for predicting each cell temperature from each air distribution rate of this duct is constructed. And about the duct of new shape whose basic composition is the same as this duct, a temperature tendency is predicted using a theoretical formula. Thereby, compared with the conventional design examination method described above, the three-dimensional calculation when the duct shape is changed can be omitted, so that the module temperature tendency can be calculated at high speed. In addition, in this prediction method, a theoretical formula that can be calculated even when the flow field in the battery pack changes greatly is constructed.

  The construction of the above theoretical formula will be described. When the duct shape is changed, the flow field in the duct changes. Further, if the flow field in the duct changes, the flow rate of the cold air discharged from each air distribution port (that is, each air distribution rate) changes, so that the way of changing the cell temperature changes. Therefore, the theoretical formula is constructed by changing the flow field in the duct into a plurality of patterns and associating the air distribution rate of each air distribution port with each cell temperature in each flow field.

  At this time, the flow field in the duct is deliberately changed drastically in order to obtain a theoretical formula that maximizes the change in the flow field in the battery pack. Specifically, a reference state in which all the air distribution openings are opened is created, and a plurality of different closed states in which the plurality of air distribution openings are closed one by one are created. For example, if the number of ducts is six, seven patterns of flow fields (models) are created. Then, a three-dimensional CFD analysis is performed on each flow field, and the air distribution rate and each cell temperature of each air distribution port are calculated. That is, in this prediction method, three-dimensional calculation is performed at the stage of constructing the theoretical formula, but it is not necessary to perform three-dimensional calculation after constructing the theoretical formula.

  Here, the calorific value of each battery cell does not change even if the design of the duct shape is changed. Therefore, when paying attention to the “heat source” in the battery pack, only the influence (cold heat amount) of the cold air distributed by the duct changes due to the design change of the duct shape. That is, for the battery cell, only the degree of cold input changes due to the design change of the duct shape (each air distribution rate). Therefore, in order to exclude only the amount of heat generated by the battery cells and focus only on the influence of cooling, the amount of change from each air distribution rate and each cell temperature in the reference state is calculated in a plurality of closed states. Then, by associating these change amounts (the change rate of the air distribution rate, the change amount of the cell temperature), a superposition equation (theoretical equation) relating to the change of the cooling energy is constructed.

  In this prediction method, a pre-calculation for constructing the above theoretical formula is performed before the main calculation for predicting the temperature trend of the battery module. That is, in the pre-calculation, the above-mentioned reference state and a plurality of closed state models are created for the battery pack, a three-dimensional CFD analysis is performed, and the air distribution rate and the cell temperature of each air distribution port in each state are calculated. calculate. For a plurality of closed states, the change amount of each air distribution rate from the reference state (cooling difference, hereinafter referred to as “air distribution rate difference”) and the change amount of each cell temperature (hereinafter referred to as “cell temperature difference”) Calculate and build a theoretical formula that correlates these correspondences.

  On the other hand, in this calculation, using the above theoretical formula, the temperature of each cell is calculated with respect to the air distribution rate of the duct with the same basic configuration as the duct that constructed the theoretical formula. To do. In addition, each air distribution rate of the new shape duct may be acquired by, for example, calculating each air distribution rate when the shape of the duct is changed by CFD analysis of the duct alone or by actually measuring it. May be. Alternatively, each target air distribution rate may be determined from a predetermined condition, and each target air distribution rate may be set as each air distribution rate of the new duct. Therefore, as described above, since the three-dimensional CFD analysis is not performed (in this calculation) after constructing the theoretical formula, the trend of the module temperature can be predicted at high speed, and the calculation cost and the design cost can be reduced. .

[2. Analysis model]
In this embodiment, an air-cooled battery pack that is mounted on a vehicle and used as a power source is taken as an example, and the temperature trend of the battery module in the battery pack is predicted. First, the configuration of the battery pack 1 that is a prediction target (analysis target) will be described. FIG. 1 is a schematic overall configuration diagram of the battery pack 1. In FIG. 1, the case 6 of the battery pack 1 is indicated by a two-dot chain line, and an electric system such as a control unit and wiring, and a fixing structure of the battery module 2 are not shown. 2A is a top view modeling the blower 5 in the battery pack 1 of FIG. 1, and FIG. 2B is a top view modeling the battery module 2 in the battery pack 1 of FIG. .

  As shown in FIG. 1, the battery pack 1 includes a plurality of battery modules 2 disposed in a case 6 and a cooling device similarly provided in the case 6. The plurality of battery modules 2 are juxtaposed in the longitudinal direction of the battery pack 1 with a gap 7 therebetween. As shown in FIG. 2B, each battery module 2 is a module in which a plurality of battery cells 3 are connected in series. A gap (not shown) is also provided between adjacent battery cells 3. In the battery pack 1 of the present embodiment, a plurality of battery cells 3 are arranged in plane symmetry with respect to a symmetry plane extending in the longitudinal direction and the vertical direction of the battery pack 1. In addition, in this embodiment, although the battery pack 1 provided with the five battery modules 2 which consist of the eight battery cells 3 is illustrated, the number of the battery cells 3 and the battery modules 2 is not restricted to these.

  The battery pack 1 of the present embodiment is a hermetic type, and the battery cell 3 is cooled by a cooling device provided in the case 6. As shown in FIG. 1, the cooling device includes a duct 4 disposed above the battery module 2, a blower 5 connected to one end of the duct 4, and a cooling system (not shown) that cools the air in the case 6. Is provided. The duct 4 has an intake port (not shown) connected to the blower 5 and a plurality of air distribution ports for discharging cool air (air) sent by the blower 5. As shown in FIGS. 1 and 2A, the duct 4 of the present embodiment includes two air distribution ports 4E provided on an end surface opposite to the blower 5 (the other end of the duct 4), and a lower surface (battery). There are a total of six air distribution openings of four air distribution openings 4B provided on the surface on the module 2 side. In the present embodiment, the air distribution ports 4B and 4E are provided so as to be plane-symmetric with respect to the above-described symmetry plane.

  The end surface air distribution port 4 </ b> E is an opening that is positioned on the straight line of the intake port and discharges the cool air in the duct 4 toward the side surface 61 of the case 6. The cool air that has flowed out of the air distribution port 4E hits the side surface 61, and then is dispersed in all directions and flows toward the blower 5 side. On the other hand, the air distribution port 4 </ b> B on the lower surface is an opening that is positioned substantially above the gap 7 between the battery modules 2 and discharges the cool air in the duct 4 toward the gap 7. The cool air that has flowed out of the air distribution port 4B flows through the gap 7 and hits the bottom surface of the case 6, and then flows into the blower 5 side by joining the flow that has made a U-turn by hitting the side surface 61. The cool air flowing out from the air distribution ports 4B and 4E cools the battery cell 3 and is then cooled in the cooling system and is absorbed by the blower 5 again. Thus, an air flow (circulation) is formed in the battery pack 1.

  In the pre-calculation before the three-dimensional CFD analysis is performed, an analysis model (CAD model) that reproduces the shape of the battery pack 1 to be analyzed is created in order to construct a theoretical formula. In the present embodiment, an analysis model of a reference state (hereinafter also referred to as “reference model”) in which all the air distribution openings 4B and 4E are opened, and an analysis of six different closed states in which the air distribution openings 4B and 4E are sequentially closed one by one. A model (hereinafter also referred to as “closed model”) is created.

  Next, for each analysis model, a modeled object (duct, battery cell 3, etc.) shape and a mesh (computation grid, cell) of the internal space (air) of the case 6 are created. Is discretized. The shape, size, number (number of divisions), division position, and the like of the mesh are appropriately set according to the analysis processing capability of the computer, desired analysis accuracy, and the like. Various numerical data are set for each of the plurality of meshes. For example, for the mesh corresponding to the shape of the object, parameters for defining the size and shape of the mesh are set. In addition to the parameters defining the size and shape of the mesh, the speed and direction of air flow are set for the mesh corresponding to the internal space. Then, CFD analysis is performed for each analysis model, and the air distribution rate of each air distribution port, each cell temperature, and the like are calculated.

[3. Device configuration]
The prediction device of this embodiment is realized by a general-purpose computer capable of executing a computer program 17 (prediction program) for temperature trend prediction. FIG. 3 is a schematic configuration diagram in the case where the prediction apparatus is configured using the computer 10.

  As shown in FIG. 3, the computer 10 (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, flash memory, reader / writer, etc.], input device 14 (keyboard, mouse, etc.), output device 15 (display, printer device, etc.) and communication device 16 (wireless or wired) Transmission / reception device). These are connected to be communicable with each other via a bus 18 (control bus, data bus, etc.) provided in the computer 10. The computer program 17 is installed in the external storage device 13.

  The computer program 17 may be recorded in a recording medium 19 that can be read by an optical drive, a flash memory, a reader / writer, or the like. Alternatively, the computer program 17 may be recorded in an online storage on a network to which the computer 10 can be connected. In any case, it can be executed by downloading the computer program 17 to the HDD, SSD or the like of the computer 10 or by reading it into the CPU 11 or the memory 12.

  The CPU 11 of this embodiment reads a program installed in the external storage device 13 on the memory 12 and executes it, and outputs a calculation result to the output device 15. The configuration and shape of the battery pack 1 and the duct 4 serving as an analysis model can be input, for example, by diverting data created by general-purpose three-dimensional CAD (Computer Aided Design) software to the computer program 17 or from the input device 14 Set by Data necessary for predicting the temperature trend is set based on an input from the input device 14 or as a value given in advance.

The data necessary for predicting the temperature trend includes the shape data of the battery pack 1 (battery module 2, battery cell 3, duct 4 etc.), the total flow rate of the cool air sent from the blower 5 to the duct 4, the temperature of the cool air, etc. included. The shape data includes the number of battery cells 3, the number of air distribution ports 4B and 4E of the duct 4, and the like. In this embodiment, as shown in FIG. 2A, numbers k = 1 to 6 are assigned to the six air distribution ports 4B and 4E, respectively. This number k represents the position of the air distribution ports 4B and 4E. For example, k = 1 represents one of the air distribution ports 4E on the end face (upper side in the figure). This air distribution port 4E (k = 1) is also referred to as “first air distribution port 41”, and the kth air distribution port is represented by reference numeral 4k. Further, the air distribution rate of the air distribution port 4k is expressed as m _k .

Further, as shown in FIG. 2 (b), for the plurality of battery cells 3, numbers i = 1 to 8 are assigned in the short direction of the battery pack 1 and numbers j = 1 to 5 are assigned in the longitudinal direction. The numbers i and j represent the positions of the battery cells 3. For example, i = 1 and j = 1 represent the battery cells 3 located at the upper left corner in the drawing. Further, the temperature of the battery cell 3 at the position indicated by the numbers i and j is expressed as a cell temperature T _ij . For example, the cell temperature of the battery cell 3 (i = 1, j = 1) located in the upper left corner is T ₁₁ .
In the present embodiment, the amount of inflow from the blower 5 and the temperature of the cold air are both set in advance as constant values.

  The function of the computer program 17 that performs the prediction of the temperature trend is schematically shown in FIG. The computer program 17 includes an analysis unit 17a, a calculation unit 17b, a construction unit 17c, and a prediction unit 17d. 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 analysis part 17a calculates each air distribution rate _mk and each cell temperature _Tij by creating the analysis model mentioned above and performing a three-dimensional CFD analysis. Specifically, the analysis unit 17a creates a reference model, then sets various numerical data for each of the plurality of meshes, and performs a three-dimensional CFD analysis, whereby each wind distribution in the reference state is set. The rate m _k0 and each cell temperature T _ij0 are calculated. In addition, the analysis unit 17a creates six different closed models in which the air distribution ports 41 to 46 are closed one by one, and similarly performs CFD analysis, so that each air distribution rate m _{k1 to} m _{k6 of} each closed model. And each cell temperature _{Tij1- Tij6} is calculated.

In this embodiment, each air distribution rate and each cell temperature of the closed model in which the p-th air distribution port 4p is closed are expressed as m _kp and T _ijp , respectively. For example, “air distribution rate m ₁₂ ” represents the air distribution rate of the first air distribution port 41 (k = 1) in the closed state in which the second air distribution port 42 (p = 2) is closed. For example, “cell temperature T ₁₂₃ ” represents the cell temperature of the battery cell 3 (i = 1, j = 2) in the closed state in which the third air distribution port 43 (p = 3) is closed. The analysis unit 17a transmits the calculated air distribution rates m _kp (m _{k0 to} m _k6 ) and the cell temperatures T _ijp (T _{ij0 to} T _ij6 ) to the calculation unit 17b. The analysis unit 17a transmits the calculated air distribution rate m _k0 and the cell temperature T _ij0 in the reference state to the prediction unit 17d.

The calculation unit 17b calculates how much each air distribution rate m _kp and each cell temperature T _{ijp in the} closed state in which the p-th air distribution port 4p is closed change from each air distribution rate m _k0 and each cell temperature T _{ij0 in} the reference state. This is calculated using the following Equation 1 and Equation 2. The calculation unit 17b according to the present embodiment calculates the amount of change in each air distribution rate m _{k1 to} m _k6 in each closed state with respect to each air distribution rate m _k0 in the reference state as each air distribution rate difference δm _{k1 to} δm _k6. , and calculates the amount of change in the cell temperature _{T ij1} ~T ij6 in each of the closed state of each cell temperature T _Ij0 in the reference state as the cell temperature difference δT _ij1 ~δT _ij6.

Δm _kp (Each wind distribution rate difference) in Equation 1 is a change from the reference state (m _k0 ) of the air distribution rate m _kp of the kth air distribution port 4k in the closed state where the pth air distribution port 4p is closed. Amount. Similarly, δT _ijp (each cell temperature difference) in Equation 2 is the reference state (T _ij0 ) of the cell temperature T _ijp of the battery cell 3 (i, j) in the closed state where the p-th air distribution port 4p is closed. The amount of change from The calculation unit 17b transmits the calculated air distribution rate differences δm _kp and the cell temperature differences δT _ijp to the construction unit 17c.

The construction unit 17c associates each air distribution rate difference δm _kp with each cell temperature difference δT _ijp in each closed state, and constructs a theoretical formula shown by the following formula 3. The theoretical formula is an expression that expresses a change in cell temperature (cell temperature difference δT _ijp ) as a sum of products of a change in air distribution rate (air distribution rate difference δm _kp ) and a coefficient. In addition, a in a formula | equation is the number of the ventilation openings 41-46 which the duct 4 has, and is a = 6 in this embodiment. C _ij ^k in Equation 3 is a coefficient that correlates the correspondence between each air distribution rate difference δm _kp and each cell temperature difference δT _ijp, and is expressed by Equation 4.

The coefficient C _ij ^k is used to obtain a change amount of the cell temperature T _ij when the air distribution rate m _{k of the kth} air distribution port 4k is changed in accordance with the design change of the duct shape. In other words, the coefficient C _ij ^k is a value that represents how much the cell temperature T _ij changes from the reference state as a result of the change of the cooling heat that has been changed by changing the air distribution rate m _k . Since the coefficient C _ij ^k is different for each position of the battery cell 3, the number (i, j) indicating the position of the battery cell 3 is attached. In addition, the coefficient C _ij ^k is also numbered k because the influence of the cooling heat given to the battery cell 3 (i, j) differs depending on the air distribution opening 4k.

Here, in the battery pack 1 of the present embodiment, the plurality of battery cells 3 are arranged in plane symmetry with respect to the symmetry plane, and the plurality of air distribution ports 41 to 46 are plane symmetry with respect to the same symmetry plane. It is provided as follows. For this reason, the construction unit 17c of the present embodiment imposes left-right symmetry when constructing the theoretical formula to reduce the calculation load. Specifically, for the battery cell 3 with the number i of i = 1 to 4, a theoretical formula is constructed using the air distribution rate m _k of the air distribution port 4k with the number k of k = 1 to 3, and the number For the battery cell 3 in which i is i = 5 to 8, the construction of the theoretical formula using the air distribution rate m _{k in} which the number k is k = 1 to 3 is omitted. Similarly, for the battery cell 3 with the number i of i = 5 to 8, a theoretical formula is constructed using the air distribution rate m _k of the air distribution port 4k with the number k of k = 4 to 6, and the number i is For the battery cell 3 with i = 1 to 4, the construction of the theoretical formula using the air distribution rate m _k with the number k of k = 4 to 6 is omitted. That is, the coefficient C _ij ^k is calculated from Equation 4 using the air distribution rate difference δm _kp of the air distribution port 4k located on the same side as the battery cell 3 with respect to the symmetry plane.

In addition, when imposing the left-right symmetry in the construction of the theoretical formula, the left-right symmetry may be similarly imposed in the calculation unit 17b. Specifically, for the battery cell 3 with the number i of i = 1 to 4, the calculation unit 17b calculates each air distribution rate difference in the closed state in which the air distribution port 4p with the number p of p = 1 to 3 is closed. δm _{k1 to} δm _k3 and cell temperature differences δT _{ij1 to} δT _ij3 are calculated, and these calculations are omitted for the battery cell 3 whose number i is i = 5 to 8, and similarly, the number i is i = 5 to 5 for cells 3 of 8, calculates the distribution respective air distribution index difference at the closed state closes the air outlet 4p δm _k4 ~δm _k6 and the cell temperature difference _δT ij4 ~δT ij6 the number p p = 4 to 6 However, these calculations may be omitted for the battery cell 3 whose number i is i = 1 to 4. That is, in every closed state closes the air distribution ports 4p located cell 3 on the same side with respect to the symmetry plane, the air-distribution index difference of the same side δm _k1 ~δm _k3 and the cell temperature difference _{δT ij1} ~δT ij3 May be calculated.

The processes by the analysis unit 17a, the calculation unit 17b, and the construction unit 17c correspond to the “pre-calculation” described above. The processing by the next prediction unit 17d corresponds to the “main calculation” described above. The construction unit 17c transmits the coefficient C _ij ^k obtained from the theoretical formula to the prediction unit 17d. The constructing unit 17c uses external data as data that can be used in this calculation (coefficient C _ij ^k is “a parameter relating each air distribution rate difference δm _{k of the} duct 4 and each cell temperature difference δT _ij ”). It may be recorded in the storage device 13. The coefficient C _ij ^k can be used in the prediction unit 17d described below when the design of the duct 4 is changed. When the arrangement and number of the battery modules 2 and the battery cells 3 are changed, even if the basic configuration of the duct 4 is the same, processing from the analysis unit 17a is performed again, and a new coefficient C _ij ^k Is calculated.

The predicting unit 17d uses the coefficient C _ij ^k to predict the temperature trend of the battery module 2 with respect to each air distribution rate n _k of the new shape duct. As a method for predicting the temperature trend, for example, the following equation 5 is used to calculate each cell temperature difference δX _ij (the amount of change from the reference state of each cell temperature X _ij ) for each air distribution rate n _k . Is a method of grasping the cell temperature distribution (temperature trend in module units) by graphing. Incidentally, .DELTA.n _k in Equation 5 is the difference Haifuritsu n _k for air distribution ratio m _k0 in the reference state of the k-th air distribution ports 4k (see Equation 6). _Further, by adding each cell temperature T _ij0 in the reference state calculated by the analysis unit 17a to each calculated cell temperature difference δX _ij , each cell temperature X _ij at each air distribution rate n _k is calculated. A temperature trend may be predicted.

The prediction unit 17d of the present embodiment sets each air distribution rate _nk of the new shape duct by two methods. The first method calculates the air distribution rate m _k ′ for each air distribution port of the new shape duct by performing CFD analysis of the duct itself for the new shape duct having the same basic configuration as the duct 4 described above. Value m _k ′ is set to each of the above-mentioned air distribution rates n _k (set to n _k = m _k ′). This CFD analysis is different from the three-dimensional CFD analysis performed in the analysis unit 17a described above, and models only the new-shaped duct, and uses each of the air flow rate from the blower 5 and the cold air temperature as input values. n _k is calculated. That is, the CFD analysis performed by the prediction unit 17d has a smaller calculation load than the CFD analysis performed by the analysis unit 17a.

The second method sets a target Haifuritsu nt _k for each air distribution mouth of the new shape duct based on a predetermined condition, the respective target Haifuritsu nt _k and the air distribution ratio n _k of the ( n _k = nt _k ). Examples of the predetermined condition include temperature conditions such as an allowable temperature range of the battery cell 3 and an allowable temperature range of the battery module 2. Specifically, the air distribution ratios nt _k for keeping all module temperatures within a predetermined allowable range and preventing the module temperature and the cell temperature from becoming too high are set as target values.

An appropriate duct shape (air distribution rate) can be designed by using the above-mentioned prediction result of the temperature tendency (that is, repeatedly performing this prediction method) for setting the target air distribution rate nt _k . For example, the prediction unit 17d first sets the air distribution rate n _k by the first method to predict the temperature trend, and then sets the target air distribution rate nt _k from the prediction result to predict the temperature trend, Furthermore, the calculation of updating the target air distribution rate nt _k based on the result may be performed.

[4. flowchart]
FIG. 4 is a flowchart showing a procedure (temperature tendency prediction method) when the computer 10 executes the computer program 17.
Step A1 is an initial setting step. That is, in step A1, original data of the battery pack 1 serving as an analysis model and data necessary for trend prediction are prepared, or input from the external storage device 13, the input device 14, or the like. In this initial setting, the number p is set to p = 0.

Steps A2, A3 and A5 are processes (analysis process) performed in the analysis unit 17a. In step A2, based on the data prepared in the previous step, a plurality of analysis models (reference model and a plurality of closed models) simulating the battery pack 1 are created. In subsequent step A3, CFD analysis is performed on the reference model, and each air distribution rate m _k0 and each cell temperature T _ij0 in the reference state are calculated. In step A4, a value obtained by adding 1 to the number p is set as a new number p. In step A5, CFD analysis is performed on the closed model in which the p-th air distribution port 4p is closed, and each air distribution rate m _kp and each cell temperature T _{ijp in the} closed state in which the air distribution port 4p is closed are calculated. The For example, when the process first proceeds to step A5, each air distribution rate m _k1 and each cell temperature T _{ij1 in the} closed state in which the first air distribution port 41 is closed are calculated.

In step A6, each air distribution rate difference δm _{kp in the} closed state in which the air distribution port 4p is closed is calculated by the above equation 1, and in the subsequent step A7, each cell temperature difference in the same closed state is calculated by the above equation 2. δT _ijp is calculated. These steps A6 and A7 are processing (calculation process) performed in the calculation unit 17b. In step A8, it is determined whether or not the current number p is equal to the number a of the air distribution openings 4k. If p = a is not satisfied, the process returns to step A4. Then, each air distribution rate difference δm _kp and each cell temperature difference δT _ijp in the closed state in which the next air distribution port 4p is closed are calculated in the same manner, and when all the patterns have been calculated, the process proceeds to step A9.

In step A9, the construction unit 17c associates each air distribution rate difference δm _kp and each cell temperature difference δT _ijp calculated in the calculation step, and a superposition formula (theoretical formula, the above formula regarding the change in cold energy). 3) is constructed, and the coefficient C _ij ^k is obtained by the above equation 4 (construction step).
The processes in steps A1 to A9 described above correspond to pre-calculation. The next steps A10 to A12 are processing (prediction process) performed in the prediction unit 17d.

In Step A10, each air distribution rate _nk of the new shape duct is set by one of the two methods described above. In step A11, the cell temperature difference δX _{ij at} each air distribution rate n _k is calculated using the above equations 5 and 6, and the temperature trend of the battery module 2 is predicted based on this result (step S11). A12). In addition, the process of step A10-12 is repeatedly implemented until the final (appropriate) duct shape is obtained. In these processes, since the three-dimensional CFD analysis is not performed, the calculation cycle can be shortened (the number of cycles is increased).

[5. effect]
(1) In the prediction method, the prediction device 10, and the prediction program 17 described above, a theoretical formula is established that relates the correspondence between each air distribution rate difference (variation in cold energy) and each cell temperature difference in each closed state, The coefficient C _ij ^k is obtained from this theoretical formula. And about the new shape duct whose basic composition is the same as the duct 4 used for construction of a theoretical formula, the temperature tendency of the battery module 2 with respect to each air distribution rate n _k (cooling heat amount) is predicted using this coefficient C _ij ^k. Is done.

That is, according to the prediction method, the prediction device 10, and the prediction program 17 described above, it is possible to predict a temperature tendency with respect to each air distribution rate n _k (cooling amount) of the new shape duct without performing CFD analysis. The time (calculation time) for calculating the temperature tendency can be greatly shortened. As a result, temperature trends can be easily and quickly grasped on a module-by-module basis, and it is possible to reduce the time required to design and acquire an appropriate duct shape (design time) as well as to reduce calculation costs and design costs. can do.

Moreover, in the construction of the theoretical formula, a plurality of closed states in which the flow field in the battery pack 1 is intentionally changed by closing the plurality of air distribution ports 4k one by one in order are created, and each air distribution rate m _kp and each cell temperature In order to calculate T _ijp , it is possible to construct a theoretical formula that captures the change in the flow field in the battery pack 1 to the maximum. Thereby, even if the flow field in the battery pack 1 changes greatly, the temperature tendency with respect to each amount of cold heat of the new shape duct can be predicted. In this method, since the amount of change from each air distribution rate m _k0 and each cell temperature T _ij0 in the reference state is calculated in a plurality of closed states, the influence of heat generation of the battery cell 3 itself is removed, and the duct is A theoretical formula focusing on only the change in the amount of heat from 4 can be constructed. That is, the theoretical formula can be simplified and the design time can be shortened.

(2) In addition, since the air distribution rate m _k of each air distribution port 4k is used as the amount of heat received from each air distribution port 4k, it is possible to accurately grasp the change in cold energy and reduce the calculation load. Thereby, calculation cost can further be suppressed.
(3) When the battery cells 3 are arranged in plane symmetry and the air distribution ports 4k are also arranged in plane symmetry as in the battery pack 1 described above, the construction process and the prediction process By imposing left-right symmetry in, the calculation load can be further reduced.

(4) As a first method, the prediction unit 17d described above performs a CFD analysis of a single duct on a new shape duct having the same basic configuration as the duct 4, thereby performing an air distribution rate for each air distribution port of the new shape duct. m _k ′ is calculated, and these values m _k ′ are set as the respective air distribution rates n _k . Then, the trend of the module temperature at the air distribution rate n _k is predicted using the coefficient C _ij ^k . That is, the design of the duct 4 in the battery pack 1 is changed to the new shape duct by using the coefficient C _ij ^k without performing the three-dimensional CFD analysis when the new shape duct is arranged in the battery pack 1. In this case, the temperature tendency of the battery module 2 can be easily predicted. Thereby, the calculation time can be shortened and the calculation cost can be reduced.

(5) In addition, the prediction unit 17d described above, as the second method, and the target Haifuritsu nt _k each air distribution index n _k that is set based on a predetermined condition. Then, the trend of the module temperature at the air distribution rate n _k is predicted using the coefficient C _ij ^k . As a result, temperature trends can be easily and quickly grasped on a module-by-module basis, so the time required to design and acquire an appropriate duct shape (design time) can be shortened, and calculation costs and design costs can be reduced. can do.

[6. 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 embodiment described above has exemplified the case of using the air distribution ratio m _k as cold calorie the battery cell 3 receives from the respective air distribution ports 4k, may be used air distribution amount instead of Haifuritsu m _k. It is also possible to use a parameter which takes into account the temperature information of the cold air in Haifuritsu m _k or air distribution amount as the cold calorie.

  In the above-described embodiment, the in-vehicle battery pack 1 is exemplified as an analysis target. However, the analysis target is a cooling module having a plurality of battery modules including a plurality of battery cells and a plurality of air distribution ports. The duct may be a battery pack provided in the case, and is not limited to the configuration described above. For example, the battery pack 1 may not be for vehicle use, and the battery cells 3 may not be arranged in plane symmetry. Further, the air distribution opening of the duct 4 may not be arranged so as to be plane symmetric, and the position thereof is not limited to the end face or the lower face.

DESCRIPTION OF SYMBOLS 1 Battery pack 2 Battery module 3 Battery cell 4 Duct 4B Bottom air distribution port 4E End surface air distribution port 4k kth air distribution port 4p pth air distribution port 41-46 Air distribution port 5 Blower 6 Case 7 Crevice 10 Computer (prediction device)
17 Computer program (prediction program)
T _ij cell temperature T _ij0 reference state cell temperature T _ijp distribution port 4p closed cell temperature m _k air distribution rate (cooling amount)
m _k0 air distribution rate in the standard state m _kp air distribution rate in the closed state with the air distribution port 4p closed δT _ijp cell temperature difference δm _kp air distribution difference (cooling difference)
n _k predetermined air distribution rate nt _k target air distribution rate m _k ′

Claims (8)

In a battery pack in which a plurality of battery modules including a plurality of battery cells are arranged in a case and a cooling duct having a plurality of air distribution openings is provided in the case, a temperature trend of the battery module is predicted. A prediction method for causing a computer to execute processing,
For each of a reference state in which all of the plurality of air distribution openings of the duct are opened and a plurality of different closed states in which the plurality of air distribution openings are sequentially closed one by one, the amount of cold heat from the plurality of air distribution openings is determined by CFD analysis. And an analysis step of calculating each cell temperature of the plurality of battery cells,
The amount of change in each amount of cold in each closed state with respect to each amount of cold in the reference state is calculated as a difference in each heat, and the change in each cell temperature in each closed state with respect to each cell temperature in the reference state A calculation step of calculating the amount as the temperature difference of each cell;
A construction step of constructing a theoretical formula relating the correspondence between each of the cooling and heating differences and each of the cell temperature differences in each of the closed states;
A prediction step of predicting a temperature trend of the battery module with respect to each cooling amount of a new shape duct having the same basic configuration as the duct, using a coefficient obtained from the theoretical formula;
A temperature trend prediction method for a battery module, comprising: The temperature trend of the battery module according to claim 1, wherein an air distribution rate indicating a ratio of an outflow amount of the fluid from the air distribution port to an inflow amount of the fluid into the duct is used as the cold heat amount. Prediction method. When the plurality of battery cells are arranged in plane symmetry with respect to a predetermined symmetry plane, and the plurality of air distribution ports are provided to be plane symmetrical with respect to the symmetry plane,
3. The battery according to claim 1, wherein, in the construction step, each of the cooling and heating differences of the air distribution ports located on the same side as the battery cell with respect to the symmetry plane is used for construction of the theoretical formula. Method for predicting module temperature trends. In the calculation step, the cold temperature difference on the same side and the cell temperature difference on the same side in each closed state in which the air distribution port located on the same side as the battery cell is closed with respect to the symmetry plane. The temperature trend prediction method for battery modules according to claim 3, wherein: The said prediction process predicts the said temperature tendency with respect to the air distribution rate for every air distribution port of the said new shape duct acquired by the CFD analysis implemented about the said new shape duct, The any one of Claims 1-4 characterized by the above-mentioned. The temperature trend prediction method for a battery module according to claim 1. The said prediction process predicts the said temperature tendency with respect to each target air distribution rate of the said new shape duct set based on predetermined conditions, The any one of Claims 1-5 characterized by the above-mentioned. Battery module temperature trend prediction method. In a battery pack in which a plurality of battery modules including a plurality of battery cells are arranged in a case and a cooling duct having a plurality of air distribution openings is provided in the case, a temperature trend of the battery module is predicted. A prediction device that executes processing,
For each of a reference state in which all of the plurality of air distribution openings of the duct are opened and a plurality of different closed states in which the plurality of air distribution openings are sequentially closed one by one, the amount of cold heat from the plurality of air distribution openings is determined by CFD analysis. And an analysis unit for calculating each cell temperature of the plurality of battery cells,
The amount of change in each amount of cold in each closed state with respect to each amount of cold in the reference state is calculated as a difference in each heat, and the change in each cell temperature in each closed state with respect to each cell temperature in the reference state A calculation unit for calculating the amount as the temperature difference of each cell;
In each closed state, a construction unit that constructs a theoretical formula that relates the correspondence between each of the cooling and heating differences and each of the cell temperature differences;
Using a coefficient obtained from the theoretical formula, a prediction unit that predicts a temperature trend of the battery module with respect to each cooling amount of a new-shaped duct having the same basic configuration as the duct;
A temperature trend predicting device for a battery module, comprising: In a battery pack in which a plurality of battery modules including a plurality of battery cells are arranged in a case and a cooling duct having a plurality of air distribution openings is provided in the case, a temperature trend of the battery module is predicted. A prediction program for executing processing,
For each of a reference state in which all of the plurality of air distribution openings of the duct are opened and a plurality of different closed states in which the plurality of air distribution openings are sequentially closed one by one, the amount of cold heat from the plurality of air distribution openings is determined by CFD analysis. And an analysis step of calculating each cell temperature of the plurality of battery cells,
The amount of change in each amount of cold in each closed state with respect to each amount of cold in the reference state is calculated as a difference in each heat, and the change in each cell temperature in each closed state with respect to each cell temperature in the reference state A calculation step of calculating the amount as the temperature difference of each cell;
A construction step of constructing a theoretical formula relating the correspondence between each of the cooling and heating differences and each of the cell temperature differences in each of the closed states;
A prediction step of predicting a temperature trend of the battery module with respect to each cooling amount of a new shape duct having the same basic configuration as the duct, using a coefficient obtained from the theoretical formula;
A computer-executable program for predicting the temperature trend of a battery module.

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