CN111753430A - Multi-objective optimization method for arrangement of single batteries of power battery pack of electric automobile considering heat dissipation - Google Patents
Multi-objective optimization method for arrangement of single batteries of power battery pack of electric automobile considering heat dissipation Download PDFInfo
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- CN111753430A CN111753430A CN202010604071.8A CN202010604071A CN111753430A CN 111753430 A CN111753430 A CN 111753430A CN 202010604071 A CN202010604071 A CN 202010604071A CN 111753430 A CN111753430 A CN 111753430A
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- 238000005457 optimization Methods 0.000 title claims abstract description 43
- 230000017525 heat dissipation Effects 0.000 title claims abstract description 31
- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000002474 experimental method Methods 0.000 claims description 4
- 238000001816 cooling Methods 0.000 claims description 3
- 238000000611 regression analysis Methods 0.000 claims description 3
- 238000010206 sensitivity analysis Methods 0.000 claims description 3
- 238000012938 design process Methods 0.000 claims description 2
- 238000012360 testing method Methods 0.000 abstract description 14
- 238000013461 design Methods 0.000 abstract description 8
- 230000004075 alteration Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000000110 cooling liquid Substances 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 239000000178 monomer Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/04—Constraint-based CAD
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/06—Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
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Abstract
According to the method, the maximum temperature of the battery pack and the maximum temperature difference of the single batteries are used as design indexes, the influence relation between the variable of the distance between the single batteries and the design indexes is explored on the basis of uniform test data, the functional relation between the distance between the single batteries and the maximum temperature difference of the single batteries is fitted by adopting a nonlinear regression method, a multi-objective optimization model of the arrangement of the single batteries of the power battery pack of the electric automobile based on heat dissipation is constructed, and a new thought is provided for the heat dissipation optimization design of the battery pack.
Description
Technical Field
The invention relates to the field of heat dissipation of power battery packs of electric vehicles, in particular to a multi-objective optimization method for single battery arrangement of a power battery pack of an electric vehicle, which considers heat dissipation.
Technical Field
The running performance and the safety performance of the pure electric vehicle are directly influenced by the heat dissipation performance of the power battery pack. Optimization of the heat dissipation performance of the power battery pack has become an important research content of electric vehicle heat management. In the existing heat dissipation optimization method for the power battery pack, parameters such as the diameter and the shape of a cooling pipeline in the battery pack, the flow rate of a cooling liquid, the ventilation speed and the like are optimized to occupy the mainstream, and the optimization design on the arrangement distance of single batteries in the battery pack is less involved.
Disclosure of Invention
The invention aims to establish a multi-target optimization method for the arrangement of single batteries of a power battery pack of an electric automobile, which takes the highest temperature index of the battery pack into consideration and the maximum temperature difference index of different single batteries into consideration, in the heat dissipation optimization design of the power battery pack of the electric automobile.
The technical scheme adopted for achieving the purpose of the invention is that the method for optimizing the arrangement of the single batteries of the power battery pack of the electric automobile in view of heat dissipation is a multi-objective method. It comprises the following contents:
on the basis of analyzing the influence of the arrangement distance of the single batteries of the battery pack on the maximum temperature of the battery pack and the maximum temperature difference of the single batteries, the maximum temperature of the battery pack and the maximum temperature difference of the single batteries are taken as targets, experimental data are obtained by adopting a uniform experimental method and a sensitivity analysis method, a nonlinear regression analysis method is adopted according to the experimental data, a multi-target optimization model for the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation is fitted, and an optimization algorithm is adopted for optimization solution.
Preferably, the multi-objective optimization method for the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation is to adjust the distance between the single batteries by considering the arrangement distance of the single batteries in the design process of the battery pack so as to enable the maximum temperature of the battery pack and the maximum temperature difference of the single batteries to be within a reasonable temperature range.
Preferably, the electric vehicle power battery pack single battery arrangement multi-objective optimization model considering heat dissipation is characterized in that: the method for establishing the multi-target optimization model for the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation by taking the minimum highest temperature of the battery pack and the minimum maximum temperature difference of the single batteries as multiple targets comprises the following steps:
establishing a battery pack in which 11 single batteries are sequentially arranged, wherein the battery pack takes air cooling as a heat dissipation mode;
(1) decision variables
The method comprises the following steps: considering the heat dissipation condition of the battery pack, the distances d1 and d2 … … d10 of the single batteries are used as optimization variables;
(2) objective function
1) The maximum temperature of the battery pack;
2) the maximum temperature difference of the single battery of the battery pack;
(3) constraint conditions
dimin<di<dimax(i＝1,2……10)。
Preferably, the multi-objective optimization method for the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation is characterized in that: and performing optimization solution by using an optimization algorithm, including but not limited to an evolutionary algorithm, and designing the battery pack by using the optimized interval parameters.
Compared with the prior power battery pack heat dissipation optimization, the invention has the beneficial effects that:
the method takes the highest temperature of the battery pack and the maximum temperature difference of the single batteries as design indexes, simplifies decision variables, namely the distance between the single batteries of the power battery pack, by adopting sensitivity analysis based on uniform test data, constructs a multi-target optimization model for the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation according to a re-designed uniform test, solves the optimization model by adopting an optimization algorithm to obtain an optimal arrangement scheme of the single batteries of the power battery pack, and provides a new idea for the heat dissipation optimization of the battery pack.
Drawings
FIG. 1 shows a model establishment process of a multi-objective optimization method for single battery arrangement of an electric vehicle power battery pack considering heat dissipation
FIG. 2 shows a power battery pack of a pure electric vehicle
FIG. 3 shows the arrangement spacing of the single cells in the battery pack
Detailed Description
The present invention will be further described with reference to the accompanying drawings and examples, but it should not be construed that the scope of the above-described subject matter is limited to the examples. Various substitutions and alterations can be made without departing from the technical idea of the invention and the scope of the invention is covered by the present invention according to the common technical knowledge and the conventional means in the field.
In this embodiment, a battery pack of a pure electric vehicle is taken as an example, and the battery pack is composed of 11 single batteries, and the appearance of the battery pack is shown in fig. 2.
The cell spacings d1, d2, … … d10 were initially determined as test variables, as shown in fig. 3. Initially 10 influencing factors were selected according to the number of experimental variables, and 11 levels were selected for each influencing factor, as shown in table 1.
TABLE 1 factors and levels
In order to obtain test data as reliably as possible, the test data in the homogeneous test design is selected for use in this context
The number of tests is 11 in the design table of (1), as shown in Table 2.
Table 2 uniformity test table
According to the uniform experiment table designed in table 2, table 1 is filled in according to the selection rule of table 2 to obtain a new uniform experiment table, as shown in table 3.
TABLE 3 homogeneous test Table
Each set of test parameters was simulated using hydrodynamic simulation software Fluent to obtain the maximum temperature of the battery pack and the maximum temperature difference of the individual batteries, with the results shown in table 4.
TABLE 4 test results
The sensitivity value of each influencing factor to the index is calculated by MATLAB, and the distances among the monomers which have larger influence on the index are d1, d2, d3, d5 and d9 which are selected as optimization variables. And redesigning the uniform test table according to the reselected optimization variables to obtain the index value of each test point. Then, a nonlinear regression analysis method was used to perform function fitting on the index values, and the fitting results are shown in Table 5.
Table 5 fitting coefficient of each index
In summary, the multi-objective optimization model is as follows:
finally, the model is solved based on an optimization algorithm, and the result is as follows:
TABLE 6 results of solution
And taking the optimized data result as the distance between the single batteries of the battery pack, and analyzing each index by using a fluid dynamics analysis software Fluent. The maximum temperature of the single battery of the battery pack is 315.3K and the maximum temperature difference is 5.6K under the original arrangement interval, and after the interval optimization, the maximum temperature and the maximum temperature difference of the single battery of the battery pack are 309.1K and 3.5K respectively, which are respectively reduced by 1.96 percent and 37.5 percent. Analysis results show that the method is effective and feasible, and can obviously improve the performance of the battery pack.
Claims (4)
1. The multi-objective optimization method for the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation is characterized by comprising the following steps of:
on the basis of analyzing the influence of the arrangement distance of the single batteries of the battery pack on the maximum temperature of the battery pack and the maximum temperature difference of the single batteries, the maximum temperature of the battery pack and the maximum temperature difference of the single batteries are taken as targets, experimental data are obtained by adopting a uniform experimental method and a sensitivity analysis method, a nonlinear regression analysis method is adopted according to the experimental data, a multi-objective function of the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation is fitted, an optimization model is constructed, and optimization solution is carried out by adopting an optimization algorithm.
2. The multi-objective optimization method for the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation according to claim 1, is characterized in that: the method for multi-target optimization of the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation is characterized in that the arrangement distance of the single batteries is considered in the design process of the battery pack so as to adjust the distance between the single batteries and achieve the purpose that the maximum temperature of the battery pack and the maximum temperature difference of the single batteries are within a reasonable temperature range.
3. The multi-objective optimization model for single battery arrangement of the electric automobile power battery pack considering heat dissipation according to claim 1, is characterized in that: the method comprises the following steps of establishing a multi-objective optimization model for the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation by taking the minimum maximum temperature of the battery pack and the minimum maximum temperature difference of the single batteries as a multi-objective in claim 1:
establishing a battery pack in which 11 single batteries are sequentially arranged, wherein the battery pack takes air cooling as a heat dissipation mode;
(1) decision variables
The method comprises the following steps: considering the heat dissipation condition of the battery pack, the distances d1 and d2 … … d10 of the single batteries are used as optimization variables;
(2) objective function
1) The maximum temperature of the battery pack;
2) the maximum temperature difference of the single battery of the battery pack;
(3) constraint conditions
dimin<di<dimax(i＝1,2……10)。
4. The multi-objective optimization method for the arrangement of the single batteries of the power battery pack of the electric automobile considering heat dissipation according to claim 1, is characterized in that: and performing optimization solution by using an optimization algorithm, including but not limited to an evolutionary algorithm, and designing the battery pack by using the optimized interval parameters.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113158461A (en) * | 2021-04-20 | 2021-07-23 | 同济大学 | Multi-objective optimization design method for vehicle-mounted lithium ion power battery pack thermal management system |
| CN115292823A (en) * | 2022-10-09 | 2022-11-04 | 北京理工大学深圳汽车研究院(电动车辆国家工程实验室深圳研究院) | Method and equipment for optimizing structure of automobile power battery pack |
-
2020
- 2020-06-29 CN CN202010604071.8A patent/CN111753430A/en active Pending
Non-Patent Citations (2)
| Title |
|---|
| JINHONG XIE等: "Optimization investigation on the liquid cooling heat dissipation structure for the lithium-ion battery package in electric vehicles", PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS, PART D: JOURNAL OF AUTOMOBILE ENGINEERING, pages 1735 - 1750 * |
| KAI CHEN等: "Design of the cell spacings of battery pack in parallel air-cooled battery thermal management system", INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, pages 393 - 401 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113158461A (en) * | 2021-04-20 | 2021-07-23 | 同济大学 | Multi-objective optimization design method for vehicle-mounted lithium ion power battery pack thermal management system |
| CN113158461B (en) * | 2021-04-20 | 2023-02-10 | 同济大学 | Multi-objective optimization design method for vehicle-mounted lithium ion power battery pack thermal management system |
| CN115292823A (en) * | 2022-10-09 | 2022-11-04 | 北京理工大学深圳汽车研究院(电动车辆国家工程实验室深圳研究院) | Method and equipment for optimizing structure of automobile power battery pack |
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