CN115292823A - Method and equipment for optimizing structure of automobile power battery pack - Google Patents
Method and equipment for optimizing structure of automobile power battery pack Download PDFInfo
- Publication number
- CN115292823A CN115292823A CN202211223786.4A CN202211223786A CN115292823A CN 115292823 A CN115292823 A CN 115292823A CN 202211223786 A CN202211223786 A CN 202211223786A CN 115292823 A CN115292823 A CN 115292823A
- Authority
- CN
- China
- Prior art keywords
- sensitivity
- analysis
- structure model
- parts
- battery pack
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
-
- G—PHYSICS
- 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]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Geometry (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Optimization (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Aviation & Aerospace Engineering (AREA)
- Pure & Applied Mathematics (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Secondary Cells (AREA)
- Battery Mounting, Suspending (AREA)
Abstract
The application discloses method and equipment for optimizing structure of automobile power battery pack, comprising the following steps: a rough structure model establishing step: establishing a rough structure model based on parts of the automobile power battery pack; a first sensitivity analysis step: performing sensitivity analysis on the rough structure model based on a first sensitivity analysis method to determine one or more first sensitivity parts; establishing a fine structure model: establishing a fine structure model based on one or more first sensitivity parts; a second sensitivity analysis step: performing sensitivity analysis on the fine structure model based on a second sensitivity analysis method to determine one or more second sensitivity parts; and (3) optimizing: and one or more second sensitivity parts are structurally optimized, so that the optimization efficiency and accuracy of the automobile power battery pack are improved.
Description
Technical Field
The present application relates to the field of automotive power battery packs, and in particular, to a method, apparatus, and computer-readable storage medium for optimizing the structure of an automotive power battery pack.
Background
For new energy vehicles, the power battery pack is a key core part, and the performance of the power battery pack affects the driving safety and the driving mileage. At present, the volume and the weight of the power battery are generally large, and on the premise that the battery module is difficult to change, the lightweight optimization design of the structure of the power battery is particularly important.
The method is characterized in that the structure of the power battery pack of the automobile is optimally designed, all the optimized parts are used as design parameters or several optimized parts are selected as the design parameters manually and blindly in the existing method, so that the optimized design parameters or the number is large or useless design parameters exist, and the efficiency and the accuracy of the overall optimized design are greatly reduced.
Disclosure of Invention
The technical problem that this application mainly solved is how to improve optimization efficiency and the rate of accuracy of car power battery package.
According to a first aspect, there is provided in one embodiment an automotive power pack method comprising: a rough structure model establishing step: establishing a rough structure model based on parts of the automobile power battery pack; a first sensitivity analysis step: performing sensitivity analysis on the rough structure model based on a first sensitivity analysis method to determine one or more first sensitivity parts; establishing a fine structure model: establishing a fine structure model based on one or more first sensitivity parts; a second sensitivity analysis step: performing sensitivity analysis on the fine structure model based on a second sensitivity analysis method to determine one or more second sensitivity parts; and (3) optimizing: one or more second sensitivity components are structurally optimized.
In some embodiments, the first sensitivity analyzing step comprises: NVH and mechanical performance analysis is carried out on the rough structure model to obtain a first performance analysis result; determining a first performance analysis target with the largest influence on the automobile working condition from NVH and mechanical performance analysis based on the first performance analysis result; analyzing a first performance analysis target of the coarse structure model based on a first sensitivity analysis method to determine the sensitivity of one or more parts of the coarse structure model; and determining one or more parts of the rough structure model with the sensitivity higher than the first threshold value as one or more first sensitivity parts.
In some embodiments, the second sensitivity analyzing step comprises: NVH and mechanical performance analysis is carried out on the fine structure model to obtain a second performance analysis result; determining a second performance analysis target with the largest influence on the automobile working condition from NVH and mechanical performance analysis based on a second performance analysis result; analyzing a second performance analysis target of the fine structure model based on a second sensitivity analysis method to determine the sensitivity of one or more parts of the fine structure model; determining parts of the fine structure model having sensitivity higher than a second threshold as one or more second sensitive parts;
in some embodiments, the step of modeling the coarse structure comprises: the grid size of the rough structure model is increased, non-optimized parts are reduced, and the battery module is changed into a counterweight unit.
In some embodiments, the optimizing step comprises: and carrying out DOE (design of experiments) on the basis of the fine structure model, and determining the structural parameters of one or more second sensitivity parts.
In some embodiments, after the optimizing step, a checking step is further included; the checking step comprises the following steps: adjusting the fine structure model according to the structure parameters of one or more second sensitivity parts; and carrying out NVH and mechanical performance analysis on the adjusted fine structure model, completing structure optimization if the performance analysis result meets the requirement, adding part of parts in the coarse structure model into the fine structure model if the performance analysis result does not meet the requirement, and then carrying out a second sensitivity analysis step, an optimization step and a check step again based on the added fine structure model.
In some embodiments, the NVH and mechanical property analysis includes one or more of modal analysis, static strength analysis, stiffness analysis, crush analysis, drop analysis, mechanical impact analysis, and floor ball impact analysis.
In some embodiments, the first sensitivity analysis method comprises a Sobol analysis method, a Morris method, an EFAST method, a GSE method, or a USM method; the second sensitivity analysis method includes a Sobol analysis method, a Morris method, an EFAST method, a GSE method, or a USM method.
According to a second aspect, there is provided in an embodiment an electronic device comprising: a memory; a processor; and a computer program; wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method as described above in the first aspect.
According to a third aspect, an embodiment provides a computer readable storage medium having a program stored thereon, the program being executable by a processor to implement the method of any of the first aspects as described above.
According to the method, the device and the computer readable storage medium for optimizing the structure of the automobile power battery pack, the optimized parts are determined by analyzing the sensitivity of the parts in the structural model, so that the optimized parts are structurally optimized, and the optimization efficiency and the accuracy of the automobile power battery pack are improved.
Drawings
Fig. 1 is a schematic flowchart of a method for optimizing a structure of an automotive power battery pack according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an external view of a rough texture model according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an internal view of a rough texture model according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a component for determining one or more first sensitivity levels provided in an embodiment of the present application;
FIG. 5 is a schematic diagram of an external view of a fine structure model provided in an embodiment of the present application;
FIG. 6 is a schematic diagram of an internal view of a fine structure model provided in an embodiment of the present application;
FIG. 7 is a schematic diagram of a component for determining one or more second sensitivity levels provided by an embodiment of the present application;
FIG. 8 is a schematic diagram of a checking step according to an embodiment of the present application;
fig. 9 is a schematic view of an electronic device according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail below with reference to the accompanying drawings by way of specific embodiments. Wherein like elements in different embodiments have been given like element numbers associated therewith. In the following description, numerous specific details are set forth in order to provide a better understanding of the present application. However, those skilled in the art will readily recognize that some of the features may be omitted or replaced with other elements, materials, methods in different instances. In some instances, certain operations related to the present application have not been shown or described in detail in order to avoid obscuring the core of the present application from excessive description, and it is not necessary for those skilled in the art to describe these operations in detail, so that they may be fully understood from the description in the specification and the general knowledge in the art.
Furthermore, the features, operations, or characteristics described in the specification may be combined in any suitable manner to form various embodiments. Also, the various steps or actions in the description of the methods may be transposed or transposed in order, as will be apparent to a person skilled in the art. Thus, the various sequences in the specification and drawings are for the purpose of describing certain embodiments only and are not intended to imply a required sequence unless otherwise indicated where such sequence must be followed.
The numbering of the components as such, e.g., "first", "second", etc., is used herein only to distinguish the objects as described, and does not have any sequential or technical meaning. The term "connected" and "coupled" as used herein includes both direct and indirect connections (couplings), unless otherwise specified.
The structure optimization is carried out on the power battery pack, and mainly aims to carry out structure optimization design on certain parts so as to improve the NVH and mechanical properties of the power battery pack, reduce the thickness of the parts, reduce the weight of the power battery pack, optimize topology and appearance and change the layout of reinforcing ribs.
In a power battery pack optimal design process, the method comprises the following steps: firstly, establishing a power battery pack model; secondly, performing CAE simulation analysis on the power battery pack model to determine an optimized design working condition; thirdly, the thickness sizes of all the optimizable parts or the thickness sizes of a plurality of parts are selected as design parameters in a man-made blind mode, and the optimization design is carried out on the design parameters; checking the optimization design result, if the optimization design result meets the requirement, finishing the optimization, and if the optimization design result does not meet the requirement, reselecting design parameters of the parts to carry out optimization design;
when the parts are determined as the optimized design parameters, the sensitivity of each part in the whole model is not analyzed, all parts with high sensitivity cannot be ensured to be used as the design parameters, and parts with low sensitivity can also be used as the design parameters, so that the number of optimized samples is excessive in the optimized design process, useless sample schemes are easy to appear, the analysis calculation amount is increased, and the optimized analysis efficiency and accuracy are reduced; the precision of the optimization design result is low, the obtained design scheme is not necessarily the optimal design scheme, and when the performance check is not satisfied, the optimization analysis is repeatedly performed due to the fact that the sensitivity of parts is unknown, such as the aim of increasing and decreasing the design parameters, and finally the efficiency of the whole optimization design is greatly reduced.
The sensitivity represents the effect of reducing or increasing the size of an automobile part when the design is optimized on the performance of the part. For example, the reduced size of the high-sensitivity component has a greater impact on the performance of the component. For another example, a low-sensitivity component has a small influence on the performance of the component when the component is reduced in size. So if the high sensitivity components are optimized to meet the requirements, the low sensitivity components will essentially meet the requirements.
In the embodiment of the application, a method for optimizing the structure of an automobile power battery pack as shown in fig. 1 is provided, and the method comprises the following steps of S101-S104:
step S101, a coarse structure model establishing step: establishing a rough structure model based on parts of the automobile power battery pack;
the power battery pack is a component in an automobile, and the power battery pack includes a plurality of parts, such as an upper case, a lower case, a lifting lug, a battery, a wire harness, a battery management system, a heat dissipation cold plate, a cooling duct, and the like.
In some embodiments, when building the rough structure model, the model may be simplified appropriately to improve the computational efficiency, for example, increasing the grid size of the rough structure model, reducing the non-optimized components and changing the battery module into the counterweight unit. In some embodiments, increasing the mesh size of the rough structure model means expanding the mesh size in the model, and in some embodiments, reducing the non-optimized components may be reducing the non-optimized components such as wiring harnesses, battery management systems, heat sink cold plates, cooling ducts, and the like. In some embodiments, changing the battery module into the counterweight unit means combining a plurality of optimized parts, and adding the weights of the plurality of optimized parts, combining the parts into one part, and then performing optimization.
In some embodiments, an external view of the created roughness model is shown in FIG. 2 and an internal view of the created roughness model is shown in FIG. 3.
Step S102, a first sensitivity analysis step: performing sensitivity analysis on the rough structure model based on a first sensitivity analysis method, and determining one or more first sensitivity parts;
the first sensitivity analysis method includes a Sobol analysis method, a Morris method, an EFAST method, a GSE method, or a USM method.
In some embodiments, step S102 may be performed by the steps shown in fig. 4, where fig. 4 is a schematic diagram of determining one or more first sensitivity components provided in the embodiments of the present application, and the method includes steps S401 to S404:
s401, carrying out NVH and mechanical performance analysis on the rough structure model to obtain a first performance analysis result;
NVH analysis is the analysis of noise, vibration and harshness of sound and vibration in the automobile. NVH and mechanical property analysis includes one or more of modal analysis, static strength analysis, stiffness analysis, crush analysis, drop analysis, mechanical impact analysis, crash analysis, and floor ball impact analysis.
The first performance analysis result represents an analysis result of the coarse structure model in NVH and mechanical performance analysis. As an example, the first performance analysis results are that the first order natural frequency in the modal analysis is higher than 40% of the standard requirement, the maximum stress in the static strength analysis is higher than 15% of the standard requirement, the maximum stress in the stiffness analysis is higher than 25% of the standard requirement, the crush distance in the crush analysis is higher than 50% of the maximum crush distance, the maximum strain in the drop analysis is higher than 50% of the standard requirement, the maximum stress in the mechanical impact analysis is higher than 10% of the standard requirement, the maximum strain in the crash analysis is higher than 50% of the standard requirement, and the maximum strain in the floor ball impact analysis is higher than 50% of the standard requirement.
S402, determining a first performance analysis target with the largest influence on the working condition of the automobile from NVH and mechanical performance analysis based on a first performance analysis result;
the first performance analysis target represents a performance analysis target which has the largest influence on the working condition of the automobile, namely is closest to the standard requirement when the structure of the power battery pack is optimized. As an example, as can be seen from the example of step S401, the maximum stress in the mechanical shock analysis is higher than 10% of the standard requirement, the performance analysis result is closest to the standard requirement, and thus the mechanical shock analysis is the first performance analysis target.
Step S403, analyzing a first performance analysis target of the rough structure model based on a first sensitivity analysis method to determine the sensitivity of one or more parts of the rough structure model;
as an example, the mechanical impact is simulated and analyzed by a Sobol sensitivity analysis method with 20 parts in the rough structure model as input.
In the Sobol sensitivity analysis method, a user only needs to take thickness information of a plurality of analyzed parts as input, and through black box analysis, a medium influence index and a global influence index of each part can be obtained, wherein the medium influence index represents the influence of an independent variable, the global influence index represents the influence of the independent variable relative to the whole, and the larger the medium influence index is, the larger the global influence index is. The sensitivity of the component may be expressed by a single influence index or a global influence index.
Step S404, determining one or more parts of the rough structure model with the sensitivity higher than a first threshold value as one or more first sensitivity parts.
As an example, the output yields the sensitivity of 20 parts in the coarse structure model, taking 20 parts in the coarse structure model as input. The first threshold value represents a threshold value of sensitivity for distinguishing a high-sensitivity component from a low-sensitivity component. Since the component lower than the first threshold value has a smaller influence on the performance than the whole component when the component is optimized, the component lower than the first threshold value is eliminated, and the component higher than the first threshold value is used as the first sensitive component.
Step S103, fine structure model building step: a fine structure model is established based on the one or more first sensitivity components.
In some embodiments, an external view of the built fine structure model is shown in FIG. 5, and an internal view of the built fine structure model is shown in FIG. 6.
Step S104, a second sensitivity analysis step: and performing sensitivity analysis on the fine structure model based on a second sensitivity analysis method to determine one or more second sensitivity parts.
The second sensitivity analysis method includes a Sobol analysis method, a Morris method, an EFAST method, a GSE method, or a USM method.
In some embodiments, step S103 may be performed by the steps shown in fig. 7, and fig. 7 is a schematic diagram for determining one or more second sensitivity components provided in the embodiments of the present application, which includes steps S701 to S704, and some descriptions may refer to fig. 7 and its related descriptions, which are not repeated herein.
S701, carrying out NVH and mechanical performance analysis on the fine structure model to obtain a second performance analysis result;
the second performance analysis result represents the analysis result of the coarse structure model in the NVH and mechanical performance analysis.
S702, determining a second performance analysis target with the largest influence on the automobile working condition from NVH and mechanical performance analysis based on a second performance analysis result;
and the second performance analysis target represents the performance analysis target which has the largest influence on the working condition of the automobile, namely is closest to the standard requirement when the structure of the power battery pack is optimized.
Step S703, analyzing a second performance analysis target of the fine structure model based on a second sensitivity analysis method to determine the sensitivity of one or more parts of the fine structure model;
step S704, the parts of the fine structure model whose sensitivity is higher than the second threshold are determined as one or more second sensitivity parts.
Step S105, an optimization step: one or more second sensitivity components are structurally optimized.
In some embodiments, DOE design experiments may be performed to determine structural parameters of one or more second sensitive components based on the fine structure model.
The DOE test design is a relatively mature optimization design method, an optimal Latin hypercube test design method is adopted, the number of test design samples is set to be at least more than 100, namely, a thickness dimension combination sample scheme of at least 100 optimized parts is needed, the influence of the thickness dimension change of the parts of the fine structure model on the NVH and mechanical performance of the power battery pack is researched through the DOE analysis result, and after the analysis is finished, some analysis charts and result data (such as linear correlation curves and sensitivity charts of design variables) related to sensitivity can be automatically generated for subsequent judgment and analysis. By way of example, design variables, design constraints, and design goals are determined by DOE trial design. The design variable is that the casing can bodiness 1mm at most, can attenuate 3mm at minimum, casing can bodiness 1.5mm at most down, can attenuate 1mm at minimum, the lug can bodiness 1.5mm at most, can attenuate 1mm at minimum, the horizontal installing support of battery module can bodiness 1mm at most, can attenuate 1.5mm at minimum. The design constraint is that the maximum stress result of the structure under the mechanical impact analysis working condition does not exceed the standard required value. The design goal is to minimize the total mass of the power cell pack. Finally, the optimized thickness dimensions of 4 parts meeting the requirements of the power battery pack on the lightest weight, NVH (noise vibration harshness) and mechanical performance meeting the evaluation standard are determined as that the upper shell is reduced by 2.5mm, the lower shell is increased by 0.5mm, the lifting lug is increased by 0.5mm, and the transverse mounting bracket of the battery module is reduced by 1mm.
In some embodiments, after the optimizing step, a checking step is further included to check the optimization result. Fig. 8 is a schematic diagram of a checking step provided in an embodiment of the present application, where the checking step includes steps S801 to S804:
step S801, adjusting a fine structure model according to the structure parameters of one or more second sensitivity parts;
and substituting the optimized structural parameters of the second sensitivity parts into the fine structure model to determine whether the optimized structural parameters meet the performance requirements.
And S802, carrying out NVH and mechanical performance analysis on the adjusted fine structure model, finishing structure optimization if the performance analysis result meets the requirement, adding part of parts in the coarse structure model into the fine structure model if the performance analysis result does not meet the requirement, and carrying out a second sensitivity analysis step, an optimization step and a check step again based on the added fine structure model.
And carrying out NVH and mechanical performance analysis on the adjusted fine structure model, and if the performance analysis result meets the requirement, completing structure optimization.
And if the performance analysis result does not meet the requirement, indicating that the performance of the optimized parts does not meet the standard, adding part of the parts in the rough structure model into the fine structure model, and then performing the second sensitivity analysis step, the optimization step and the checking step again based on the added fine structure model.
Based on the same inventive concept, an embodiment of the present application provides an electronic device, as shown in fig. 9, including: a processor 91 and a memory 92 for storing instructions executable by the processor 91; wherein the processor 91 is configured to execute to implement an automotive power battery pack structure optimization method as provided in the foregoing, the method comprising: a rough structure model establishing step: establishing a rough structure model based on parts of the automobile power battery pack; a first sensitivity analysis step: performing sensitivity analysis on the rough structure model based on a first sensitivity analysis method, and determining one or more first sensitivity parts; establishing a fine structure model: establishing a fine structure model based on one or more first sensitivity parts; a second sensitivity analysis step: performing sensitivity analysis on the fine structure model based on a second sensitivity analysis method to determine one or more second sensitivity parts; and (3) optimizing: one or more second sensitivity components are structurally optimized.
Based on the same inventive concept, the present embodiment provides a non-transitory computer-readable storage medium, which when instructions in the storage medium are executed by the processor 91 of the electronic device, enables the electronic device to perform a display method that implements a restocking list as provided above.
Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, though not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.
Also, the description uses specific words to describe embodiments of the specification. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.
Additionally, the order in which the elements and sequences are processed, the use of alphanumeric characters, or the use of other designations in this specification is not intended to limit the order of the processes and methods in this specification, unless otherwise specified in the claims. While certain presently contemplated useful embodiments of the invention have been discussed in the foregoing disclosure by way of various examples, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein described. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.
Similarly, it should be noted that in the preceding description of embodiments of the present specification, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features are required than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.
Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.
For each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited in this specification, the entire contents of each are hereby incorporated by reference into this specification. Except where the application history document does not conform to or conflict with the contents of the present specification, it is to be understood that the application history document, as used herein in the present specification or appended claims, is intended to define the broadest scope of the present specification (whether presently or later in the specification) rather than the broadest scope of the present specification. It is to be understood that the descriptions, definitions and/or uses of terms in the accompanying materials of the present specification shall control if they are inconsistent or inconsistent with the contents of the present specification.
Finally, it should be understood that the examples in this specification are only intended to illustrate the principles of the examples in this specification. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.
Claims (10)
1. A method for optimizing the structure of an automobile power battery pack is characterized by comprising the following steps:
establishing a rough structure model based on parts of the automobile power battery pack;
performing sensitivity analysis on the rough structure model based on a sensitivity analysis method to determine a plurality of first sensitivity parts;
establishing a fine structure model based on a plurality of first sensitivity parts;
performing sensitivity analysis on the fine structure model based on a sensitivity analysis method, and determining a plurality of second sensitivity parts;
and carrying out structural optimization on the plurality of second sensitivity parts.
2. The method for optimizing a vehicle power battery pack structure according to claim 1, wherein the sensitivity analysis of the rough structure model based on the sensitivity analysis method to determine a plurality of first sensitivity components comprises:
carrying out NVH and mechanical performance analysis on the rough structure model to obtain a first performance analysis result;
determining a first performance analysis mode which has the largest influence on the working condition of the automobile from NVH and mechanical performance analysis based on the first performance analysis result;
determining a first sensitivity of the part of the rough structure model based on a first performance analysis mode, the rough structure model and a sensitivity analysis method;
a plurality of first sensitivity components having a sensitivity above a first threshold are determined based on the first sensitivity.
3. The method for optimizing a vehicle power battery pack structure according to claim 2, wherein the sensitivity analysis of the fine structure model based on the sensitivity analysis method to determine a plurality of second sensitivity components comprises:
NVH and mechanical performance analysis is carried out on the fine structure model to obtain a second performance analysis result;
determining a second performance analysis mode which has the largest influence on the working condition of the automobile from NVH and mechanical performance analysis based on a second performance analysis result;
determining a second sensitivity of the part of the fine structure model based on a second performance analysis mode, the fine structure model and the sensitivity analysis method;
a plurality of second sensitivity components having a sensitivity above a second threshold are determined based on the second sensitivity.
4. The method for optimizing the structure of the vehicle power battery pack according to claim 1, wherein the step of establishing a rough structure model based on the parts of the vehicle power battery pack comprises the steps of:
the grid size of the rough structure model is increased, the number of non-optimized parts is reduced, and the battery module is changed into a counterweight unit.
5. The method for optimizing the structure of the vehicle power battery pack according to claim 3, wherein the optimizing the structure of the plurality of second sensitive parts includes: and carrying out DOE (design of experiments) test design based on the fine structure model, and determining the structural parameters of the second sensitivity parts.
6. The method for optimizing a vehicle power pack structure according to claim 5, further comprising, after the determining the parameters of the plurality of second sensitivity components:
adjusting the fine structure model according to the structural parameters of the plurality of second sensitivity parts;
and carrying out NVH and mechanical performance analysis on the adjusted fine structure model, finishing structure optimization if the performance analysis result meets the requirement, adding part of parts in the coarse structure model into the fine structure model if the performance analysis result does not meet the requirement, and re-determining a plurality of second sensitivity parts based on the added fine structure model.
7. The method for optimizing the structure of the automotive power battery pack according to any one of claims 2 to 3, wherein the NVH and mechanical property analysis includes a modal analysis, a static strength analysis, a stiffness analysis, a crush analysis, a drop analysis, a mechanical impact analysis, a collision analysis, and a floor ball impact analysis.
8. The method for optimizing the pack structure of automotive power batteries according to any one of claims 1 to 6, characterized in that the sensitivity analysis method comprises a Sobol analysis method, a Morris method, an EFAST method, a GSE method and a USM method.
9. An electronic device, comprising: a memory; a processor; and a computer program; wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method according to any one of claims 1 to 8.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out steps corresponding to the method according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211223786.4A CN115292823B (en) | 2022-10-09 | 2022-10-09 | Method and equipment for optimizing structure of automobile power battery pack |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211223786.4A CN115292823B (en) | 2022-10-09 | 2022-10-09 | Method and equipment for optimizing structure of automobile power battery pack |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115292823A true CN115292823A (en) | 2022-11-04 |
| CN115292823B CN115292823B (en) | 2023-02-17 |
Family
ID=83833420
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211223786.4A Active CN115292823B (en) | 2022-10-09 | 2022-10-09 | Method and equipment for optimizing structure of automobile power battery pack |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115292823B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117648731A (en) * | 2024-01-29 | 2024-03-05 | 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) | Design method and system of explosion-proof power battery pack |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105320784A (en) * | 2014-07-01 | 2016-02-10 | 上汽通用五菱汽车股份有限公司 | Optimization design method for sensitivities of regions of automobile body |
| CN107887669A (en) * | 2017-11-07 | 2018-04-06 | 大连理工大学 | A kind of heat dissipation metal electrokinetic cell pack arrangement design method and battery bag |
| CN111753430A (en) * | 2020-06-29 | 2020-10-09 | 重庆大学 | Multi-objective optimization method for arrangement of single batteries of power battery pack of electric automobile considering heat dissipation |
| CN111969265A (en) * | 2020-08-12 | 2020-11-20 | 芜湖奇达动力电池系统有限公司 | Power battery pack safety monitoring system and monitoring method for new energy automobile |
| CN112937571A (en) * | 2021-03-12 | 2021-06-11 | 北京理工大学 | Intelligent automobile track tracking control method and system |
-
2022
- 2022-10-09 CN CN202211223786.4A patent/CN115292823B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105320784A (en) * | 2014-07-01 | 2016-02-10 | 上汽通用五菱汽车股份有限公司 | Optimization design method for sensitivities of regions of automobile body |
| CN107887669A (en) * | 2017-11-07 | 2018-04-06 | 大连理工大学 | A kind of heat dissipation metal electrokinetic cell pack arrangement design method and battery bag |
| CN111753430A (en) * | 2020-06-29 | 2020-10-09 | 重庆大学 | Multi-objective optimization method for arrangement of single batteries of power battery pack of electric automobile considering heat dissipation |
| CN111969265A (en) * | 2020-08-12 | 2020-11-20 | 芜湖奇达动力电池系统有限公司 | Power battery pack safety monitoring system and monitoring method for new energy automobile |
| CN112937571A (en) * | 2021-03-12 | 2021-06-11 | 北京理工大学 | Intelligent automobile track tracking control method and system |
Non-Patent Citations (4)
| Title |
|---|
| RUOYANG YUAN等: "Modelling and Co-simulation of hybrid vehicles: A thermal management perspective", 《JOURNALAPPLIED THERMAL ENGINEERING》 * |
| 李日步等: "纯电动汽车动力电池包轻量化技术综述", 《汽车零部件》 * |
| 王文伟等: "电动汽车电池箱结构随机振动疲劳分析", 《汽车工程学报》 * |
| 罗朝晖等: "混合动力旅游客车整车轻量化设计", 《客车技术与研究》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117648731A (en) * | 2024-01-29 | 2024-03-05 | 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) | Design method and system of explosion-proof power battery pack |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115292823B (en) | 2023-02-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102867075B (en) | Acceleration frequency response analysis-based body floor optimal design method | |
| Xie et al. | Crashworthiness optimisation of a composite energy-absorbing structure for subway vehicles based on hybrid particle swarm optimisation | |
| Pan et al. | Crush and crash analysis of an automotive battery-pack enclosure for lightweight design | |
| CN115292823B (en) | Method and equipment for optimizing structure of automobile power battery pack | |
| CN112685946B (en) | New energy automobile battery pack shell weight reduction design method based on second-order response surface model | |
| CN116595649A (en) | Vehicle lightweight design method, system, electronic equipment and storage medium | |
| Wang et al. | Multi-objective optimization of crashworthiness of vehicle front longitudinal beam | |
| Navale et al. | Crashworthiness aspects of electric vehicle design | |
| CN116090092A (en) | Safety design method of new energy vehicle battery pack and battery pack thereof | |
| CN115186547A (en) | Method, device and equipment for analyzing and optimizing performance of whole vehicle and storage medium | |
| CN113449376B (en) | Method, system and equipment for selecting shock absorber of suspension equipment under train | |
| Tomar et al. | Modelling and analysis of a chassis frame by using carbon fiber and E-glass epoxy as composite material: a comparative study | |
| Liang et al. | Bus rollover crashworthiness under European standard: an optimal analysis of superstructure strength using successive response surface method | |
| Lin et al. | Structural design optimization of the body section using the finite element method | |
| Kalsi et al. | Optimization of compressor mounting bracket of a passenger car | |
| Ofochebe et al. | Absorbable energy monitoring scheme: new design protocol to test vehicle structural crashworthiness | |
| Mei et al. | [Retracted] Key Technologies of Lightweight Materials for New Energy Vehicles Based on Ant Colony Algorithm | |
| Singh et al. | Dynamic Analysis of Condenser Assembly of Automobile Air Conditioning System Using CAE Tools | |
| Wang et al. | Research on the optimization of automobile plastic front frame structure | |
| Sreenivas et al. | Investigating the crashworthiness of kenaf/kevlar hybrid composite frontal car fascia for low-velocity impact using LS-DYNA | |
| CN111625902A (en) | Equivalent simulation method for electric automobile column collision | |
| CN115270584B (en) | Lightweight method suitable for new energy electric vehicle battery bracket | |
| Long et al. | Lightweight Investigation of Extended‐Range Electric Vehicle Based on Collision Failure Using Numerical Simulation | |
| Gao et al. | A Design Optimization Process of Improving the Automotive Subframe Dynamic Stiffness Using Tuned Rubber Mass Damper | |
| Zhang et al. | Optimization design on dynamic characteristics and fatigue life of automotive suspension system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |