CN111767625A - Thermal simulation method for lithium ion battery pack - Google Patents
Thermal simulation method for lithium ion battery pack Download PDFInfo
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- CN111767625A CN111767625A CN201910238645.1A CN201910238645A CN111767625A CN 111767625 A CN111767625 A CN 111767625A CN 201910238645 A CN201910238645 A CN 201910238645A CN 111767625 A CN111767625 A CN 111767625A
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Abstract
The invention discloses a thermal simulation method of a lithium ion battery pack, which comprises the following steps: importing a three-dimensional geometric model of the lithium ion battery pack; preprocessing the imported three-dimensional geometric model; inputting thermal material physical parameters of each component, wherein the thermal material physical parameters comprise density, thermal conductivity and specific heat capacity; calculating the heat generation rate of the heat source component and giving the heat generation rate to the heat source component; setting a convection heat transfer coefficient on a convection heat transfer surface in the three-dimensional geometric model; generating a heat transfer contact pair; dividing grids of all components in the three-dimensional geometric model, and carrying out numerical value dispersion on the three-dimensional geometric model; and carrying out simulation solution on the temperature field data and the temperature rise data of the lithium ion battery pack. The thermal simulation method of the lithium ion battery pack can be used for predicting the temperature distribution and temperature rise condition of the battery pack after the battery pack is loaded and the whole vehicle runs under the working condition, so that reference and basis are provided for the structural optimization of the battery pack thermal management system.
Description
Technical Field
The invention relates to the technical field of lithium ion batteries, in particular to a thermal simulation method of a lithium ion battery pack.
Background
With the social development and progress, the automobile holding amount is rapidly increased, and the problems of non-renewable resource consumption and environmental pollution are aggravated. In order to relieve the current resource and environmental pressures, the development of new energy vehicles has been pursued as a national strategy. As a key component of a new energy automobile, the technical progress of a power battery is important.
In the existing battery products, the lithium ion battery is widely applied to the field of new energy automobiles due to the advantages of high energy density, large output power, quick charging, long service life and the like.
Lithium ion battery has different operation effects under the temperature of difference, and low temperature can seriously influence the discharge performance of battery, and too high temperature can accelerate the ageing of battery, reduces the life-span of battery, can appear the danger of burning explosion even. The temperature change of the battery is influenced by the external environment and is caused by the operation condition of the battery. Therefore, predicting battery temperature distribution and variation through thermal simulation is very important for a battery thermal management system. Further, the results of the thermal simulation may be used to guide the optimization of the hardware configuration of the battery pack heating system and heat dissipation system.
In the process of designing and manufacturing the battery pack, a plurality of existing battery or battery pack manufacturers lack a complete temperature prediction mechanism of a battery pack thermal management system aiming at the running condition of a whole vehicle, and design is carried out only by depending on the experience of a design engineer, so that the risk of over-temperature, insufficient output power or shorter service life than expected exists in the actual loading and running of a large number of products.
Therefore, a new thermal simulation method for lithium ion battery pack is needed.
Disclosure of Invention
The invention aims to overcome the defects that the battery product has the risks of over-temperature, insufficient output power or short service life lower than expected in practical application due to the lack of an accurate temperature prediction mechanism in the design of the conventional lithium ion battery pack, and provides a novel thermal simulation method for the lithium ion battery pack.
The invention solves the technical problems by adopting the following technical scheme:
the invention provides a thermal simulation method of a lithium ion battery pack, which is characterized by comprising the following steps of:
step 1, importing a three-dimensional geometric model of the lithium ion battery pack, wherein the three-dimensional geometric model comprises a plurality of components, and the components comprise a heat source component, a heat dissipation component and a heat transfer component;
step 2, preprocessing the imported three-dimensional geometric model;
step 3, inputting the physical parameters of the thermal material of each component, wherein the physical parameters of the thermal material comprise density, thermal conductivity and specific heat capacity;
step 4, calculating the heat generation rate of the heat source component, and giving the calculated heat generation rate to the heat source component, wherein the heat generation rate is the single heat generation rate or the total heat generation rate;
step 5, setting a convection heat transfer coefficient on a convection heat transfer surface in the three-dimensional geometric model;
step 6, generating heat transfer contact pairs, wherein each heat transfer contact pair comprises a pair of the components;
7, dividing grids of all components in the three-dimensional geometric model, and performing numerical value dispersion on the three-dimensional geometric model;
and 8, carrying out simulation solving on the temperature field data and the temperature rise data of the lithium ion battery pack.
Preferably, the preprocessing in step 2 includes deleting the components in the three-dimensional geometric model, whose influence factors on heat generation, heat transfer and heat dissipation of the lithium ion battery pack are smaller than preset influence factor thresholds, and retaining other components.
Preferably, the preprocessing in step 2 includes deleting local features of the three-dimensional geometric model, the size of which is smaller than a preset size threshold, where the local features include some or all of pinholes, small bosses, small fillets, small chamfers, and edges.
Preferably, the preprocessing in step 2 includes eliminating curved surface data defects existing in the three-dimensional geometric model, where the curved surface data defects include gaps, dislocations, and overlaps.
Preferably, the heat source component comprises a cell, and the step 4 estimates the heat generation rate of the cell by using a Bernardi-based thermal model.
Preferably, the convective heat transfer coefficient includes a natural convective heat transfer coefficient, an air-cooled convective heat transfer coefficient, and a liquid-cooled convective heat transfer coefficient.
Preferably, the step 5 further includes calculating the natural convection heat transfer coefficient, the air-cooled convection heat transfer coefficient, and the liquid-cooled convection heat transfer coefficient by using an empirical formula.
Preferably, the step 5 further comprises calculating the convective heat transfer coefficient by using a CFD (computational fluid dynamics) method.
Preferably, the thermal simulation method further comprises the following steps:
and 9, extracting the temperature field data and the temperature rise data of the lithium ion battery pack to form a simulation report.
On the basis of the common knowledge in the field, the above preferred conditions can be combined randomly to obtain the preferred embodiments of the invention.
The positive progress effects of the invention are as follows:
the thermal simulation method of the lithium ion battery pack can be used for predicting the temperature distribution and temperature rise condition of the battery pack after the battery pack is loaded and the whole vehicle runs under the working condition, so that reference and basis are provided for the structural optimization of the battery pack thermal management system, and the required computing resources are relatively less, the computing speed is higher, and the universality is higher.
Drawings
Fig. 1 is a flowchart of a thermal simulation method of a lithium ion battery pack according to a preferred embodiment of the present invention.
Fig. 2 is a schematic flow chart of a calculation process for calculating the heat generation rate of the heat source in step 4 in the thermal simulation method for the lithium ion battery pack according to the preferred embodiment of the present invention.
Fig. 3 is a schematic flow chart of a specific implementation step of calculating the convective heat transfer coefficient by using a CFD method in step 5 in the thermal simulation method for a lithium ion battery pack according to the preferred embodiment of the present invention.
Detailed Description
The following detailed description of the preferred embodiments of the present invention, taken in conjunction with the accompanying drawings, is intended to be illustrative, and not restrictive, and any other similar items may be considered within the scope of the present invention.
In the following detailed description, directional terms, such as "left", "right", "upper", "lower", "front", "rear", and the like, are used with reference to the orientation as illustrated in the drawings. The components of various embodiments of the present invention can be positioned in a number of different orientations and the directional terminology is used for purposes of illustration and is in no way limiting.
Referring to fig. 1, a thermal simulation method of a lithium ion battery pack according to a preferred embodiment of the present invention includes the following steps:
step 1, importing a three-dimensional geometric model of the lithium ion battery pack, wherein the three-dimensional geometric model comprises a plurality of components, and the components comprise a heat source component, a heat dissipation component and a heat transfer component;
step 2, preprocessing the imported three-dimensional geometric model;
step 3, inputting the physical parameters of the thermal material of each component, wherein the physical parameters of the thermal material comprise density, thermal conductivity and specific heat capacity;
step 4, calculating the heat generation rate of the heat source component, and giving the calculated heat generation rate to the heat source component, wherein the heat generation rate is the single heat generation rate or the total heat generation rate;
step 5, setting a convection heat transfer coefficient on a convection heat transfer surface in the three-dimensional geometric model;
step 6, generating heat transfer contact pairs, wherein each heat transfer contact pair comprises a pair of the components;
7, dividing grids of all components in the three-dimensional geometric model, and performing numerical value dispersion on the three-dimensional geometric model;
step 8, carrying out simulation solving on the temperature field data and the temperature rise data of the lithium ion battery pack;
and 9, extracting the temperature field data and the temperature rise data of the lithium ion battery pack to form a simulation report.
Among them, step 9 is a preferable step, which mainly consists in outputting the result of the simulation calculation.
According to some preferred embodiments of the present invention, the preprocessing in the step 2 includes deleting the components of the three-dimensional geometric model having the influence factors on heat generation, heat transfer and heat dissipation of the lithium ion battery pack smaller than the preset influence factor threshold, and retaining other components. Thus, some components of the three-dimensional geometric model that are not critical to thermal simulation calculations may be removed.
According to some preferred embodiments of the present invention, the preprocessing in step 2 includes deleting local features of the three-dimensional geometric model, the size of which is smaller than a preset size threshold, where the local features include some or all of pinholes, small bosses, small rounded corners, small chamfers and folded edges. In addition, the welding seam can be filled, the gap is eliminated, and the interference is checked.
According to some preferred embodiments of the present invention, the preprocessing in the step 2 includes eliminating surface data defects existing in the three-dimensional geometric model, and the surface data defects include gaps, misalignment and overlapping.
It should be understood that the original three-dimensional geometric model may include many parts, and the influence of the parts on heat generation, heat transfer and heat dissipation is very little, but a large amount of calculation workload is brought, so that according to the above preferred embodiment, these parts which are not critical may be deleted, and key parts, such as the electric core, the heat-conducting aluminum plate, the cold plate, the box body, etc., are retained, thereby significantly improving the calculation efficiency of the simulation calculation, reducing the required calculation resources, and simultaneously ensuring the calculation accuracy.
According to some preferred embodiments of the present invention, the heat source component includes a cell, and the step 4 estimates the heat generation rate of the cell using a Bernardi-based thermal model. Because the internal structure of the lithium ion battery is complex, the factors influencing the heat production power are more, the heat production power test is relatively difficult, the cost is higher, and the mechanisms capable of testing the heat production rate of the battery cell are fewer. Therefore, the method for estimating the heat production rate of the single battery cell by adopting the Bernardi-based thermal model is a convenient, rapid and effective method.
According to some preferred embodiments of the present invention, referring to fig. 2, the calculating the heat generation rate of the heat source in step 4 may specifically adopt the following sub-steps:
substep 4.1, carrying out HPPC test on the battery cell to obtain voltage and current parameters of battery cell charging/discharging at different temperatures and different SOC;
substep 4.2, calculating a charge/discharge DR-SOC curve of the battery cell at different temperatures according to the test data in substep 4.1, and taking a direct current internal resistance mean value of an effective SOC interval for simple and convenient calculation;
substep 4.3, obtaining the direct current internal resistance of the battery cell according to the substep 4.2, and calculating the heat generation rate of the battery cell under 1C charging/discharging;
substep 4.4, converting the power-time data of the working condition of the whole vehicle into a multiplying power-time relation, and calculating the heat generation rate of the battery cell of the working condition of the whole vehicle according to the charge-discharge heat generation rate of the battery cell 1C obtained in substep 4.3;
and a substep 4.5 of importing the finished automobile working condition electric core heat generation rate obtained in the substep 4.4 into three-dimensional thermal simulation software, and endowing a corresponding heat source model.
According to some embodiments of the present invention, for example, in the sub-step 4.3, the heat generation rate Q of the battery cell under charging and discharging at 1C can be calculated by using formula (1) or formula (2).
Wherein, I is charging and discharging current (A), E is battery monomer voltage (V), E0Is the battery open circuit voltage (V), T is the temperature,
is temperature coefficient (V/K), R is direct current internal resistance, (E-E)0) Which represents a portion of the heat of joule,
representing the portion of the heat of reversible reaction. For power type batteryIn general, large-rate charge and discharge are performed, joule heat is a main part, and the following formula (2) can be used for calculation in engineering in consideration of calculation conservation.
Q＝1.15I2R (2)
In view of the fact that the time step is usually smaller, such as 0.1s, in the working condition of the whole vehicle, the calculated time step of the heat generation rate of the working condition of the whole vehicle is correspondingly smaller, and the simulation calculation amount is overlarge. For this reason, in sub-step 4.4, the heat generation rate can be equivalently converted by averaging over 1s, 2s, 5s, or 10s time steps, thereby greatly simplifying the operation and reducing the amount of computation.
According to some preferred embodiments of the present invention, the convective heat transfer coefficient includes a natural convective heat transfer coefficient, an air-cooled convective heat transfer coefficient, and a liquid-cooled convective heat transfer coefficient.
According to some preferred embodiments of the present invention, the step 5 further includes calculating the natural convection heat transfer coefficient, the air-cooled convection heat transfer coefficient, and the liquid-cooled convection heat transfer coefficient by using empirical formulas.
According to some preferred embodiments of the present invention, the convective heat transfer coefficient in step 5 can be calculated by using empirical formula (3), or can be calculated by CFD software. The natural convection heat transfer coefficient is calculated by formula (3)
Wherein m and n are empirical coefficients and take the values shown in Table 1, L is characteristic length, and kpThe thermal conductivity of air, g is the acceleration of gravity, α is the coefficient of volume expansion, v is the viscosity of the fluid, △ T is the temperature difference between the wall and the fluid, μpIs hydrodynamic viscosity, cpIs the specific heat of the fluid.
TABLE 1
The air-cooled convection heat transfer coefficient can be calculated by adopting a formula (4)
Wherein L is a characteristic length, kpIs the thermal conductivity of air and is,
is Reynolds number (u is incoming flow velocity, v is kinematic viscosity of air),
is the prandtl number (c)pIs the specific heat capacity of air, mupIs aerodynamic viscosity), the application range Re≤5×105。
The liquid cooling convection heat transfer coefficient is calculated by adopting a formula (5) or (6) according to the structural form,
wherein d isinIs the inner diameter of the pipe, kpIs the thermal conductivity of air and is,
is Reynolds number (u is incoming flow velocity, v is kinematic viscosity of air),
is the prandtl number (c)pIs the specific heat capacity of air, mupIs an aerodynamic viscosity).
Wherein C and n are empirical coefficients,mthe values for the row number correction factor are shown in Table 2-3, where D is the outer diameter of the cylinder and k ispIs the thermal conductivity of air and is,
is Reynolds number (u is incoming flow velocity, v is kinematic viscosity of air),
is the prandtl number (c)pIs the specific heat capacity of air, mupIs aerodynamic viscosity), PrwIs the prandtl number calculated using the tube wall temperature.
TABLE 2
TABLE 3
| Number of rows | 1 | 2 | 3 | 4 | 5 | 6 | 8 | 12 | 16 | 20 |
| Fork row | 0.62 | 0.76 | 0.84 | 0.88 | 0.92 | 0.95 | 0.96 | 0.98 | 0.99 | 1.0 |
According to some preferred embodiments of the present invention, the step 5 further comprises calculating the convective heat transfer coefficient by using a CFD method.
Specifically, for example, the specific implementation steps of calculating the convective heat transfer coefficient by using the CFD method in step 5 may be as follows:
substep 5.1, establishing a three-dimensional heat exchange model on the basis of the original three-dimensional geometric model, replacing the original module with an equivalent module, extracting a flow channel, simplifying the model and then leading the model into a CFD calculation program;
substep 5.2, inputting material thermophysical parameters including the density, specific heat capacity, thermal conductivity and the like of the module, the heat-conducting filling material, the box body, the cooling equipment, the cooling medium and the like;
substep 5.3, assigning the heat generation rate (average value) of the heat source to the heat source;
substep 5.4, connecting the thermal contact surfaces, including the interfaces between the solid and between the solid and the fluid, to confirm that the connection is error-free;
substep 5.5, setting boundary conditions such as an inlet-outlet boundary, a wall boundary, fluid temperature and the like, solving and setting main convergence criteria, monitor options and the like;
substep 5.6, dividing grids and checking the quality of the grids;
substep 5.7, after the substep is finished, begin to operate and calculate;
and 5.8, after the solution is completed, extracting the convection heat transfer coefficient of each main convection heat transfer surface.
Preferably, the cell quality, the continuity of the model and the repeated cells can be checked at any time in the process of dividing the grid, so that the problem of the cell quality cannot cause solving difficulty in the subsequent analysis. The quality of the inspection unit is mainly the warpage, the aspect ratio, the included angle, the length, the Jacobian, the repeating unit and the like of the inspection unit.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that these are by way of example only, and that the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the spirit and scope of the invention, and these changes and modifications are within the scope of the invention.
Claims (9)
1. A thermal simulation method of a lithium ion battery pack is characterized by comprising the following steps:
step 1, importing a three-dimensional geometric model of the lithium ion battery pack, wherein the three-dimensional geometric model comprises a plurality of components, and the components comprise a heat source component, a heat dissipation component and a heat transfer component;
step 2, preprocessing the imported three-dimensional geometric model;
step 3, inputting the physical parameters of the thermal material of each component, wherein the physical parameters of the thermal material comprise density, thermal conductivity and specific heat capacity;
step 4, calculating the heat generation rate of the heat source component, and giving the calculated heat generation rate to the heat source component, wherein the heat generation rate is the single heat generation rate or the total heat generation rate;
step 5, setting a convection heat transfer coefficient on a convection heat transfer surface in the three-dimensional geometric model;
step 6, generating heat transfer contact pairs, wherein each heat transfer contact pair comprises a pair of the components;
7, dividing grids of all components in the three-dimensional geometric model, and performing numerical value dispersion on the three-dimensional geometric model;
and 8, carrying out simulation solving on the temperature field data and the temperature rise data of the lithium ion battery pack.
2. The thermal simulation method of claim 1, wherein the preprocessing in the step 2 comprises deleting components of the three-dimensional geometric model having an influence factor on heat generation, heat transfer, and heat dissipation of the lithium ion battery pack that is smaller than a preset influence factor threshold, and retaining other components.
3. The thermal simulation method of claim 1, wherein the preprocessing in the step 2 comprises deleting local features with a size smaller than a preset size threshold in the three-dimensional geometric model, wherein the local features comprise parts or all of small holes, small bosses, small round corners, small chamfers and folded edges.
4. The thermal simulation method of claim 1, wherein the preprocessing of step 2 comprises eliminating surface data defects existing in the three-dimensional geometric model, wherein the surface data defects comprise gaps, dislocations and overlaps.
5. The thermal simulation method of claim 1, wherein the heat source component comprises a cell, and the step 4 estimates the heat generation rate of the cell using a Bernardi-based thermal model.
6. The thermal simulation method of claim 1, wherein the convective heat transfer coefficient comprises a natural convective heat transfer coefficient, an air-cooled convective heat transfer coefficient, a liquid-cooled convective heat transfer coefficient.
7. The thermal simulation method of claim 6, wherein said step 5 further comprises calculating said natural convective heat transfer coefficient, said air-cooled convective heat transfer coefficient, said liquid-cooled convective heat transfer coefficient using empirical formulas.
8. The thermal simulation method of claim 1, wherein the step 5 further comprises calculating the convective heat transfer coefficient using a CFD method.
9. The thermal simulation method of any one of claims 1-8, further comprising the steps of:
and 9, extracting the temperature field data and the temperature rise data of the lithium ion battery pack to form a simulation report.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112464539A (en) * | 2020-12-16 | 2021-03-09 | 北方特种能源集团有限公司西安庆华公司 | ANSYS-based simulation analysis method for thermal battery support lug impact resistance |
| CN112729611A (en) * | 2020-12-23 | 2021-04-30 | 江苏省电力试验研究院有限公司 | Estimation method for internal temperature of energy storage system of lithium ion battery |
| CN113312856A (en) * | 2021-05-14 | 2021-08-27 | 湘潭大学 | Numerical calculation combined thermal management control simulation method for battery pack of electric vehicle |
| CN113359038A (en) * | 2021-02-23 | 2021-09-07 | 万向一二三股份公司 | Lithium ion battery discharge and connecting piece heat production verification method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112464539A (en) * | 2020-12-16 | 2021-03-09 | 北方特种能源集团有限公司西安庆华公司 | ANSYS-based simulation analysis method for thermal battery support lug impact resistance |
| CN112464539B (en) * | 2020-12-16 | 2024-05-14 | 北方特种能源集团有限公司西安庆华公司 | Simulation analysis method for thermal battery lug impact resistance based on ANSYS |
| CN112729611A (en) * | 2020-12-23 | 2021-04-30 | 江苏省电力试验研究院有限公司 | Estimation method for internal temperature of energy storage system of lithium ion battery |
| CN113359038A (en) * | 2021-02-23 | 2021-09-07 | 万向一二三股份公司 | Lithium ion battery discharge and connecting piece heat production verification method |
| CN113312856A (en) * | 2021-05-14 | 2021-08-27 | 湘潭大学 | Numerical calculation combined thermal management control simulation method for battery pack of electric vehicle |
| CN113312856B (en) * | 2021-05-14 | 2022-04-26 | 湘潭大学 | Numerical calculation combined thermal management control simulation method for battery pack of electric vehicle |
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