CN116432426A - Vehicle-mounted power battery evaluation method, readable storage medium and computer equipment - Google Patents
Vehicle-mounted power battery evaluation method, readable storage medium and computer equipment Download PDFInfo
- Publication number
- CN116432426A CN116432426A CN202310291676.XA CN202310291676A CN116432426A CN 116432426 A CN116432426 A CN 116432426A CN 202310291676 A CN202310291676 A CN 202310291676A CN 116432426 A CN116432426 A CN 116432426A
- Authority
- CN
- China
- Prior art keywords
- simulation model
- battery pack
- evaluation
- model
- stress
- 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.)
- Pending
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 122
- 238000004088 simulation Methods 0.000 claims abstract description 213
- 230000004044 response Effects 0.000 claims abstract description 74
- 238000004458 analytical method Methods 0.000 claims abstract description 60
- 238000001228 spectrum Methods 0.000 claims abstract description 14
- 230000008859 change Effects 0.000 claims abstract description 5
- 238000000034 method Methods 0.000 claims description 30
- 230000001133 acceleration Effects 0.000 claims description 22
- 238000013142 basic testing Methods 0.000 claims description 19
- 230000001052 transient effect Effects 0.000 claims description 18
- 239000000463 material Substances 0.000 claims description 14
- 230000006870 function Effects 0.000 claims description 13
- 230000005284 excitation Effects 0.000 claims description 9
- 238000012546 transfer Methods 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 8
- 230000006835 compression Effects 0.000 claims description 7
- 238000007906 compression Methods 0.000 claims description 7
- 230000003938 response to stress Effects 0.000 claims description 6
- 238000010606 normalization Methods 0.000 claims description 3
- 238000013461 design Methods 0.000 description 6
- 238000001125 extrusion Methods 0.000 description 5
- 238000012360 testing method Methods 0.000 description 4
- 238000003491 array Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000005315 distribution function Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 239000011248 coating agent Substances 0.000 description 1
- 238000000576 coating method Methods 0.000 description 1
- 238000013016 damping Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 239000003792 electrolyte Substances 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009863 impact test Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012067 mathematical method Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 239000003381 stabilizer Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
-
- 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
- G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
-
- 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
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Development Economics (AREA)
- Geometry (AREA)
- Educational Administration (AREA)
- Evolutionary Computation (AREA)
- Game Theory and Decision Science (AREA)
- Computer Hardware Design (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Secondary Cells (AREA)
Abstract
The invention provides a vehicle-mounted power battery evaluation method, a readable storage medium and computer equipment, which comprise the following steps: constructing a battery pack simulation model, and analyzing to obtain dynamics evaluation parameters of the battery pack simulation model; obtaining road spectrum information, wherein the road spectrum information contains response signals of each hard point of the vehicle, which change along with time when running on different road surfaces; constructing a whole vehicle simulation model according to the battery pack simulation model and the vehicle body model, and determining mechanical property evaluation parameters of the battery pack simulation model according to the response signals; constructing a collision model, performing collision simulation analysis, and acquiring safety reliability evaluation parameters of the battery pack simulation model; and constructing a parameter index evaluation system according to the evaluation parameters, and determining weight information of each evaluation parameter to complete the evaluation of the power battery. The evaluation method provided by the invention evaluates and analyzes the vehicle-mounted power battery from the single battery, the module, the shell and the battery pack to the whole vehicle from the part to the whole vehicle, and has the structure and the layering property.
Description
Technical Field
The present invention relates to the field of battery technologies, and in particular, to a power battery evaluation method, a readable storage medium, and a computer device.
Background
In recent years, a plurality of safety accident reports appear on the new energy electric vehicle, so that the concern of society on the safety performance of the new energy electric vehicle is raised, the confidence of the new energy electric vehicle is reduced, and the following is also carried out! With the development of the age, more and more new energy automobiles enter our lives, and many scholars continuously and systematically study the way of improving the safety of the new energy electric automobiles.
The safety of the new energy electric automobile is basically the safety of the vehicle-mounted power battery, and is a complex accident probability problem. The safety factor needs to be controlled to reduce the probability of dangerous accidents. Therefore, the safety analysis and evaluation of the vehicle-mounted power battery are developed in the research, development, popularization and application stages of the new energy electric automobile, and the vehicle-mounted power battery has important practical value and application value.
At present, in the design stage of the power battery, the power battery can be simulated by adopting a simulation method to evaluate the safety, service life and other performances of the battery, but the existing evaluation method is often more general, the simulation result actual application scene has larger phase difference and the simulation result precision is poorer mainly through multiple simulations of the integral model of the power battery under different working conditions.
Disclosure of Invention
In view of the above, it is necessary to provide a power battery evaluation method, a readable storage medium, and a computer device, which address the problems of the prior art that simulation methods are more general and have poor accuracy as a result.
The first aspect of the invention provides a vehicle-mounted power battery evaluation method, which comprises the following steps:
constructing a battery pack simulation model, and carrying out dynamic response analysis on the battery pack simulation model to obtain dynamic evaluation parameters of the battery pack simulation model;
obtaining road spectrum information, wherein the road spectrum information contains response signals of each hard point of the vehicle, which change along with time when running on different road surfaces;
constructing a whole vehicle simulation model according to the battery pack simulation model and the vehicle body model, and determining mechanical property evaluation parameters of the battery pack simulation model in the whole vehicle simulation model according to the response signals;
constructing a collision model, and performing collision analysis on the whole vehicle simulation model according to the collision model to obtain a safety reliability evaluation parameter of the battery pack simulation model in the collision analysis;
and constructing a parameter index evaluation system according to the dynamics evaluation parameters, the mechanical property evaluation parameters and the safety reliability evaluation parameters, and determining weight information of each evaluation parameter to complete evaluation of the power battery.
Preferably, the constructing the battery pack simulation model includes:
constructing a plurality of single battery simulation models, and respectively endowing material properties to each component part in the single battery simulation models according to a preset material constitutive model;
assembling a plurality of single battery simulation models to form a battery module model;
constructing a shell simulation model, and assembling the shell simulation model and the battery module model to obtain an initial battery pack simulation model;
performing modal analysis on the initial battery pack simulation model, and judging whether the shell simulation model in the initial battery pack simulation model meets preset requirements or not;
and if the shell simulation model meets the preset requirement, taking the initial battery pack simulation model as a battery pack simulation model.
Preferably, the dynamics evaluation parameters include a random vibration stress evaluation parameter and an impact stress evaluation parameter, and the performing a dynamics response analysis on the battery pack simulation model to obtain the dynamics evaluation parameters of the battery pack simulation model includes:
carrying out random vibration analysis on the battery pack simulation model to obtain dynamic stress amplitude response of the battery pack simulation model meeting Gaussian distribution;
determining an absolute dynamic stress amplitude corresponding to 99.73% of the confidence interval according to the dynamic stress amplitude response to obtain the random vibration stress evaluation parameter;
performing impact power analysis on the battery pack simulation model to obtain a transient impact time domain history curve of the battery pack simulation model;
and determining the transient stress of each connecting point of the battery pack simulation model and the vehicle body model according to the transient impact time domain history curve, and selecting the largest transient stress in each connecting point as an impact stress evaluation parameter.
Preferably, the obtaining road spectrum information, where the road spectrum information includes response signals that change with time when each hard spot of the vehicle travels on different roads, includes:
acquiring response acceleration signals acquired by a basic test vehicle when the basic test vehicle runs under different road conditions, wherein the response acceleration signals reflect specific road conditions when the basic test vehicle runs;
acquiring a road condition transfer function of a simulation system;
respectively iterating the response acceleration signals acquired on different road surfaces according to the road condition transfer function to acquire vibration response excitation signals of each hard point in the basic test vehicle under different road conditions;
dividing the vibration response excitation signals according to a preset time period, and obtaining time domain vibration response signals of each hard point changing along with time when the basic test vehicle runs on different roads.
Preferably, the mechanical performance evaluation parameters include a fatigue damage evaluation parameter and a bolt strength evaluation parameter, and the determining the mechanical performance evaluation parameters of the battery pack simulation model in the whole vehicle simulation model according to the response signal includes:
searching hard points corresponding to the basic test vehicle in the whole vehicle simulation model, and inputting the time domain response signals to the hard points corresponding to the whole vehicle simulation model;
carrying out structural stress response analysis on the whole vehicle simulation model under different road conditions according to the time domain vibration response signals;
calculating a first fatigue damage value of the battery pack simulation model and a second fatigue damage value of each connecting point connecting bolt of the battery pack simulation model and the vehicle body model under the structural stress response analysis through a fatigue accumulated damage theory;
determining the fatigue damage assessment parameter according to the first fatigue damage value and the second fatigue damage value;
obtaining the maximum stress of each hard point of the whole vehicle simulation model when a time domain vibration response signal is input;
and calculating the stress of the connecting bolt according to the maximum stress of each hard point, and determining the bolt strength evaluation parameter according to the stress of the connecting bolt.
Preferably, the obtaining the safety reliability evaluation parameter of the battery pack simulation model in the collision analysis includes:
acquiring an intrusion curve of the shell simulation model into the battery pack simulation model during collision, and determining stress changes of compression bolts among a plurality of single battery simulation models according to the intrusion curve;
acquiring a response acceleration course curve of the single battery simulation model during collision;
determining a connection lifting lug, a connection bolt and stress changes of the single battery simulation model, wherein the connection lifting lug, the connection bolt and the single battery simulation model are connected with the vehicle body model according to the response acceleration process curve;
and determining the safety reliability evaluation parameters according to the stress changes of the compression bolt, the connecting lifting lug, the connecting bolt and the single battery simulation model.
Preferably, the determining the weight information of each evaluation parameter to complete the evaluation of the power battery includes:
carrying out dimensionless and normalization treatment on each evaluation parameter in the parameter index evaluation system;
constructing an AHP hierarchical model, quantitatively analyzing the dimensionless and normalized evaluation parameters through the AHP hierarchical model, and determining weight information of the evaluation parameters;
and evaluating the power battery according to the weight information of each evaluation parameter.
Preferably, before assembling the plurality of unit cell simulation models to form a battery module model, the evaluation method further includes:
carrying out single mechanical simulation analysis on the single battery simulation model, and obtaining a stress-strain history curve of the single battery simulation model according to the single mechanical simulation analysis;
and determining the maximum tensile stress value or the maximum strain value allowed by the single battery simulation model according to the stress-strain history curve.
A second aspect of the present invention provides a readable storage medium having stored thereon a program which when executed by a processor implements any of the methods described above.
A third aspect of the invention provides a computer device comprising a memory, a processor and a program stored on the memory and executable on the processor, the processor implementing the method of any one of the preceding claims when executing the program.
The vehicle-mounted power battery assessment method provided by the invention comprises the steps of carrying out structural and hierarchical assessment analysis on a vehicle-mounted power battery from a single battery, a module, a shell and a battery pack to a whole vehicle from a part to a whole vehicle, carrying out analysis on random vibration, impact and the like of the battery pack, verifying the rationality of the shell, collecting specific road conditions of a road surface, carrying out fatigue analysis according to road condition information, verifying and assessing the strength and durability influence of vehicle-mounted excitation of the battery pack on the whole vehicle on the battery pack, carrying out analysis on the strength of a bolt, verifying whether the shape of a connecting bolt meets the requirement or not, carrying out collision test on the battery pack loaded into the whole vehicle by constructing a collision model, and verifying the safety reliability of the components such as the bolt; and finally, calculating weight information of each evaluation parameter through an AHP method, comprehensively evaluating, comprehensively, qualitatively and quantitatively evaluating the safety performance of the power battery, optimizing structural design according to an evaluation result, and being suitable for being popularized and used in a large range.
Drawings
Fig. 1 is a flowchart of a power battery evaluation method according to a first embodiment of the present invention;
FIG. 2 is a detailed flow chart of the construction of the battery pack simulation model of FIG. 1;
FIG. 3 is a detailed flow chart of the dynamic response analysis of the battery pack simulation model of FIG. 1;
FIG. 4 is a detailed flowchart of step S20 in FIG. 1;
FIG. 5 is a detailed flowchart of step S30 in FIG. 1;
FIG. 6 is a detailed flowchart of step S40 in FIG. 1;
fig. 7 is a detailed flowchart of step S50 in fig. 1.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
These and other aspects of embodiments of the invention will be apparent from and elucidated with reference to the description and drawings described hereinafter. In the description and drawings, particular implementations of embodiments of the invention are disclosed in detail as being indicative of some of the ways in which the principles of embodiments of the invention may be employed, but it is understood that the scope of the embodiments of the invention is not limited correspondingly. On the contrary, the embodiments of the invention include all alternatives, modifications and equivalents as may be included within the spirit and scope of the appended claims.
Referring to fig. 1, a vehicle-mounted power battery evaluation method according to a first embodiment of the present invention includes steps S10 to S50.
Step S10, a battery pack simulation model is constructed, and dynamic response analysis is carried out on the battery pack simulation model to obtain dynamic evaluation parameters of the battery pack simulation model;
before simulation analysis, three-dimensional drawing software can be used for constructing a three-dimensional simulation model, and in the implementation, CAD data of a Catia design is used for constructing a battery pack simulation model.
Referring to fig. 2, in this embodiment, the construction of the battery pack simulation model specifically includes the following steps:
step S101, constructing a plurality of single cell simulation models, and respectively endowing material properties to all component parts in the single cell simulation models according to a preset material constitutive model;
the single battery comprises parts such as an inner core, a current collector, a coating and the like, three-dimensional simulation models of all parts are firstly constructed by adopting three-dimensional drawing software, the three-dimensional simulation models of all parts are assembled into a single battery simulation model, and a constitutive model of a material is built according to the actual material composition of all parts; the built constitutive model comprises characteristic information such as density, strength, strain ratio and the like of various materials, and the materials in the constitutive model are respectively endowed to each component part in the single battery simulation model for simulation of the power battery.
Step S102, assembling a plurality of single battery simulation models to form a battery module model;
after a plurality of single battery simulation models are established and materials are respectively endowed, the plurality of single battery simulation models are assembled to form a battery module model, and specifically, the number of the single battery simulation models in a single battery module model can be determined according to actual needs.
Step S103, constructing a shell simulation model, and assembling the shell simulation model and a battery module model to obtain an initial battery pack simulation model;
besides the battery module, the vehicle-mounted power battery is also provided with a shell for protection, so that before the power battery is simulated, a shell simulation model is also required to be built according to the actual power battery, and the shell simulation model in the framework is assembled with the battery module model to obtain an initial battery pack simulation model.
Step S104, carrying out modal analysis on the initial battery pack simulation model, and judging whether a shell simulation model in the initial battery pack simulation model meets preset requirements or not;
after the shell simulation model and the battery module model are assembled, the effectiveness of the shell simulation model needs to be further verified, and specifically, the mode analysis can be performed after the assembled initial battery pack simulation model is endowed with material properties; modes refer to the natural vibration characteristics of a mechanical structure, each mode having a particular natural frequency, damping ratio, and mode shape. The natural frequency, the vibration mode and other results of the structure can be obtained through modal analysis, the characteristics of the main modes of each stage of the structure in a certain easily affected frequency range are known through modal analysis, and the actual vibration response of the structure under the action of various vibration sources outside or inside the frequency range can be predicted; thus, modal analysis is an important method for dynamic design of structures and device fault diagnosis.
Step S105, if the shell simulation model meets the preset requirement, the initial battery pack simulation model is used as a battery pack simulation model.
Determining the natural frequency of the battery pack simulation model according to the modal analysis in the step S104, judging whether the determined natural frequency is the same as or close to the response frequency of the actual power battery when being knocked by the force hammer, and if the natural frequency of the power battery is close to the response frequency when being knocked by the force hammer in operation, the power battery is easy to generate resonance, so that the situation is avoided as much as possible; therefore, if the natural frequency of the battery pack simulation model is the same as or close to the response frequency when the battery pack simulation model is knocked by the force hammer, the structure of the simulation model of the shell should be modified, and then the battery pack simulation model is subjected to modal simulation again until the requirements are met; taking the modified battery pack simulation model as a battery pack simulation model for subsequent simulation analysis; the modeling method is high in accuracy and comprises the steps of modeling single batteries and determining an effective external shell structure model to assemble a battery pack simulation model.
After the battery pack simulation model is determined, further, dynamic response analysis is carried out on the battery pack simulation model, and dynamic evaluation parameters of the battery pack simulation model are obtained, wherein the dynamic evaluation parameters comprise random vibration stress evaluation parameters and impact stress evaluation parameters.
Referring to fig. 3, in this embodiment, the dynamic response analysis of the battery pack simulation model specifically includes the following steps:
step S111, carrying out random vibration analysis on the battery pack simulation model to obtain dynamic stress amplitude response of the battery pack simulation model meeting Gaussian distribution;
the random vibration analysis can be performed according to the international common random vibration test standard, the random vibration is a collection of a large number of phenomena, but generally meets a certain statistical rule, in the embodiment, in the random vibration analysis process of the battery pack simulation model, the dynamic stress of the battery pack simulation model meets gaussian distribution, and the expression of the dynamic stress probability density distribution function is as follows:
wherein x is a dynamic stress variable of the battery pack simulation model in random vibration, mu is a mathematical expectation of dynamic stress, and sigma is a standard deviation of the dynamic stress.
Step S112, determining an absolute dynamic stress amplitude corresponding to 99.73% of the confidence interval according to the dynamic stress amplitude response to obtain a random vibration stress evaluation parameter;
in the present embodiment, since the battery pack simulation model performs random vibration analysis, external force is not provided thereto, and thus the mathematical expectation μ of dynamic stress has a value of 0; the dynamic stress value of the probability density distribution function is only related to the standard deviation sigma, and the absolute value of the dynamic stress of 3 times is selected, namely the absolute value of the dynamic stress of 3 sigma is taken as a confidence interval, and the probability of the dynamic stress value in the confidence interval is 99.73%. The 3 sigma absolute value was taken as a random vibration stress evaluation parameter.
Step S113, performing impact power analysis on the battery pack simulation model to obtain a transient impact time domain history curve of the battery pack simulation model;
and performing impact power response analysis on the battery pack simulation model according to the conventional impact test standard to obtain a transient impact time domain history curve of the battery pack simulation model.
Step S114, determining the transient stress of each connection point of the battery pack simulation model and the vehicle body model according to the transient impact time domain history curve, and selecting the largest transient stress in each connection point as an impact stress evaluation parameter.
Specifically, the interval division may be performed according to a preset duration in the transient impact time domain history curve setting in step S113, the transient impact time domain history curve is set to be divided into a plurality of periods, the transient stress of each connection point of the battery pack simulation model and the vehicle body model is determined according to the transient impact time domain history curve divided into the plurality of periods, and the transient stress with the largest contact point is selected as the impact stress evaluation parameter.
S20, road spectrum information is obtained, wherein the road spectrum information contains response signals which change along with time when each hard point of the vehicle runs on different road surfaces;
the road spectrum refers to a road surface spectrum of a road, can reflect the specific road condition of the road, and can acquire the reliability such as the flatness of the road and obtain corresponding response in the running process of a vehicle on the road.
Referring to fig. 4, in the present embodiment, step S20 specifically includes the following steps:
step S21, acquiring response acceleration signals acquired by the basic test vehicle when running under different road conditions, wherein the response acceleration signals reflect specific road conditions when the basic test vehicle runs;
in order to acquire the information of flatness, pavement pits, curvature and the like of the acquired pavement, a sensor can be arranged on a basic test vehicle to acquire vibration of the vehicle in the running process, and the acquired vibration information is used for acquiring signals of corresponding response acceleration or response strain and the like of the vehicle, so that specific road conditions are reflected through the signals.
Step S22, obtaining a road condition transfer function of a simulation system;
step S23, respectively iterating response acceleration signals acquired on different road surfaces according to the road condition transfer function to acquire vibration response excitation signals of each hard point in the basic test vehicle under different road conditions;
and inputting the collected response acceleration signals under different road conditions into a road condition transfer function of the system to iterate for a plurality of times, and obtaining information such as force, torque and the like of each hard point of the vehicle under the response acceleration, wherein vibration response excitation signals of the vehicle running on different road surfaces are reflected. Specifically, in this embodiment, the specific road condition includes an uphill road section and a turning road section, the response acceleration of the uphill road section and the response acceleration of the turning road section are respectively input into the road condition transfer function for multiple iterations, the road condition transfer function is converged and stabilized, and then the iterations are stopped, so as to obtain information such as force and torque of each hard point of the vehicle of the uphill road section under the response acceleration and information such as force and torque of each hard point of the vehicle of the turning road section under the response acceleration, wherein the hard points include mark points on the auxiliary frame, the transverse stabilizer bar, the wheel hubs and the like.
And step S24, dividing the vibration response excitation signals according to a preset time period, and obtaining time domain vibration response signals of each hard point changing along with time when the basic test vehicle runs on different roads.
Step S30, constructing a whole vehicle simulation model according to the battery pack simulation model and the vehicle body model, and determining mechanical property evaluation parameters of the battery pack simulation model in the whole vehicle simulation model according to the response signals;
assembling the battery pack into a vehicle body model to obtain a simulation model of the whole vehicle so as to simulate the actual application scene of the power battery, wherein the mechanical property evaluation parameters mainly comprise fatigue damage evaluation parameters and bolt strength evaluation parameters;
referring to fig. 5, in the present embodiment, step S30 specifically includes the following steps:
step S31, searching hard points corresponding to the basic test vehicle in the whole vehicle simulation model, and inputting time domain response signals to the hard points corresponding to the whole vehicle simulation model;
specifically, in this embodiment, the force, torque, and other information of each hard point of the basic test vehicle obtained in step S20 when running on different road conditions are respectively input to each hard point corresponding to the whole vehicle simulation model, so as to simulate the whole vehicle simulation model to run on an actual road surface.
S32, carrying out structural stress response analysis on the whole vehicle simulation model under different road conditions according to the time domain vibration response signals;
step S33, calculating a first fatigue damage value of a battery pack simulation model and a second fatigue damage value of each connecting bolt of the battery pack simulation model and a vehicle body model under structural stress response analysis through a fatigue accumulated damage theory;
the fatigue damage value is related to the distance or time that the vehicle travels on the road, and each part of the vehicle may be damaged after each travel, and when the fatigue damage value reaches 1, the part is damaged, and maintenance or replacement is required.
Step S34, determining fatigue damage evaluation parameters according to the first fatigue damage value and the second fatigue damage value;
step S35, obtaining the maximum stress of each hard point of the whole vehicle simulation model when a time domain vibration response signal is input;
and S36, calculating the stress of the connecting bolt according to the maximum stress of each hard point, and determining a bolt strength evaluation parameter according to the stress of the connecting bolt.
And calculating the stress of the connecting bolt according to the maximum stress of each hard point through virtual iteration of Admas, and calculating the evaluation parameters such as the strength, the slip loosening coefficient, the probability and the like of the connecting bolt at the joint of the battery pack simulation model and the vehicle body model according to the VDI2230 specification.
Step S40, constructing a collision model, and performing collision analysis on the whole vehicle simulation model according to the collision model to obtain the safety reliability evaluation parameters of the battery pack simulation model in the collision analysis;
in particular, the collision model may be a barrier model for a frontal or side collision; and carrying out whole car collision simulation on the whole car simulation model according to the conventional collision specification, and verifying the safety and reliability of the power battery under the collision working condition.
Referring to fig. 6, in the present embodiment, step S40 specifically includes the following steps:
s41, obtaining an intrusion curve of an outer shell simulation model into a battery pack simulation model during collision, and determining stress changes of compression bolts among a plurality of single battery simulation models according to the intrusion curve;
step S42, obtaining a response acceleration course curve of the single battery simulation model during collision;
step S43, determining stress changes of a connecting lifting lug, a connecting bolt and a single battery simulation model which are connected with the battery pack simulation model and the vehicle body model according to the response acceleration process curve;
and S44, determining safe reliability evaluation parameters according to the stress changes of the compression bolt, the connecting lifting lug, the connecting bolt and the single battery simulation model.
And if the stress of the compression bolt, the connecting lifting lug, the connecting bolt and the single battery simulation model in collision is larger than the maximum tensile stress, the component is invalid.
And S50, constructing a parameter index evaluation system according to the dynamics evaluation parameters, the mechanical property evaluation parameters and the safety reliability evaluation parameters, and determining weight information of each evaluation parameter so as to complete the evaluation of the power battery.
Referring to fig. 7, in the present embodiment, step S50 specifically includes the following steps:
step S51, carrying out dimensionless and normalization processing on each evaluation parameter in the parameter index evaluation system;
and performing unquantized and normalized processing on each evaluation parameter, completely eliminating units of each related evaluation parameter through preset variable substitution, and converting a dimensionless expression into a dimensionless expression to form a scalar.
Step S52, constructing an AHP hierarchical model, quantitatively analyzing the dimensionless and normalized evaluation parameters through the AHP hierarchical model, and determining weight information of the evaluation parameters;
AHP (analytic hierarchy process) is a simple, flexible and practical multi-criterion decision method for quantitatively analyzing qualitative problems, various factors in complex problems can be divided into mutually connected ordered layers, and weights reflecting the relative importance sequence of elements of each layer are calculated through mathematical methods such as function matrixes, judgment matrixes and the like;
and step S53, the power battery is evaluated according to the weight information of each evaluation parameter.
The weight information of each evaluation parameter is calculated by using an AHP method, so that the weight vector of the corresponding evaluation parameter is obtained, the safety performance of the power battery is evaluated comprehensively, qualitatively and quantitatively, and the corresponding measure scheme can be determined according to the sensitivity of the weight vector of each evaluation parameter and used for structural optimization, and the research and development design is fed back.
Further, in this embodiment, the vehicle-mounted power battery evaluation method further includes:
carrying out single mechanical simulation analysis on the single battery simulation model, and obtaining a stress-strain history curve of the single battery simulation model according to the single mechanical simulation analysis;
specifically, the single mechanical simulation analysis mainly includes positive pressure, lateral pressure and ball extrusion simulation analysis, and specifically, in this embodiment, the single mechanical simulation analysis is ball extrusion simulation analysis, and parameters of electrolyte leakage and voltage drop in the power battery are represented according to extrusion displacement in the extrusion process.
And determining the maximum tensile stress value or the maximum strain value allowed by the single cell simulation model according to the stress-strain history curve.
And according to the maximum stress value or the maximum strain value, representing the failure parameter of the internal short circuit of the power battery, namely predicting the extrusion stress of the internal short circuit of the battery through the maximum stress value or the maximum strain value. It will be appreciated that it is also possible to verify by the maximum stress value whether a short circuit has occurred inside the battery in the crash test.
The vehicle-mounted power battery assessment method provided by the embodiment of the invention comprises the steps of carrying out assessment analysis on the vehicle-mounted power battery from part to whole from the single battery, the module, the shell and the battery pack to the whole vehicle, and has structural property and layering property; the method comprises the steps of analyzing random vibration, impact and the like of a battery pack, verifying the rationality of a shell, collecting specific road conditions of a road surface, performing fatigue analysis according to road condition information, verifying and evaluating the strength and durability influence of vehicle-mounted excitation on the battery pack on the whole vehicle, analyzing the strength of a bolt, verifying whether the selection of a connecting bolt meets the requirement, constructing a collision model, performing collision test on the battery pack loaded into the whole vehicle, and verifying the safety and reliability of the bolt and other components; and finally, calculating weight information of each evaluation parameter through an AHP method, comprehensively evaluating, comprehensively, qualitatively and quantitatively evaluating the safety performance of the power battery, optimizing structural design according to an evaluation result, and being suitable for being popularized and used in a large range.
A second embodiment of the present invention provides a readable storage medium having stored thereon a program which, when executed by a processor, implements any of the methods described above.
A third embodiment of the present invention provides a computer device including a memory, a processor, and a program stored on the memory and executable on the processor, the processor implementing the method of any one of the above when executing the program.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
1. The vehicle-mounted power battery evaluation method is characterized by comprising the following steps of:
constructing a battery pack simulation model, and carrying out dynamic response analysis on the battery pack simulation model to obtain dynamic evaluation parameters of the battery pack simulation model;
obtaining road spectrum information, wherein the road spectrum information contains response signals of each hard point of the vehicle, which change along with time when running on different road surfaces;
constructing a whole vehicle simulation model according to the battery pack simulation model and the vehicle body model, and determining mechanical property evaluation parameters of the battery pack simulation model in the whole vehicle simulation model according to the response signals;
constructing a collision model, and performing collision analysis on the whole vehicle simulation model according to the collision model to obtain a safety reliability evaluation parameter of the battery pack simulation model in the collision analysis;
and constructing a parameter index evaluation system according to the dynamics evaluation parameters, the mechanical property evaluation parameters and the safety reliability evaluation parameters, and determining weight information of each evaluation parameter to complete evaluation of the power battery.
2. The method of evaluating according to claim 1, wherein the constructing a battery pack simulation model comprises:
constructing a plurality of single battery simulation models, and respectively endowing material properties to each component part in the single battery simulation models according to a preset material constitutive model;
assembling a plurality of single battery simulation models to form a battery module model;
constructing a shell simulation model, and assembling the shell simulation model and the battery module model to obtain an initial battery pack simulation model;
performing modal analysis on the initial battery pack simulation model, and judging whether the shell simulation model in the initial battery pack simulation model meets preset requirements or not;
and if the shell simulation model meets the preset requirement, taking the initial battery pack simulation model as a battery pack simulation model.
3. The evaluation method according to claim 1, wherein the dynamics evaluation parameters include a random vibration stress evaluation parameter and an impact stress evaluation parameter, and the performing a dynamics response analysis on the battery pack simulation model to obtain the dynamics evaluation parameters of the battery pack simulation model includes:
carrying out random vibration analysis on the battery pack simulation model to obtain dynamic stress amplitude response of the battery pack simulation model meeting Gaussian distribution;
determining an absolute dynamic stress amplitude corresponding to 99.73% of the confidence interval according to the dynamic stress amplitude response to obtain the random vibration stress evaluation parameter;
performing impact power analysis on the battery pack simulation model to obtain a transient impact time domain history curve of the battery pack simulation model;
and determining the transient stress of each connecting point of the battery pack simulation model and the vehicle body model according to the transient impact time domain history curve, and selecting the largest transient stress in each connecting point as an impact stress evaluation parameter.
4. The method according to claim 1, wherein the obtaining road spectrum information, the road spectrum information including response signals of each hard spot of the vehicle changing with time when running on different road surfaces, includes:
acquiring response acceleration signals acquired by a basic test vehicle when the basic test vehicle runs under different road conditions, wherein the response acceleration signals reflect specific road conditions when the basic test vehicle runs;
acquiring a road condition transfer function of a simulation system;
respectively iterating the response acceleration signals acquired on different road surfaces according to the road condition transfer function to acquire vibration response excitation signals of each hard point in the basic test vehicle under different road conditions;
dividing the vibration response excitation signals according to a preset time period, and obtaining time domain vibration response signals of each hard point changing along with time when the basic test vehicle runs on different roads.
5. The evaluation method according to claim 4, wherein the mechanical property evaluation parameters include a fatigue damage evaluation parameter and a bolt strength evaluation parameter, and the determining the mechanical property evaluation parameter of the battery pack simulation model in the whole vehicle simulation model from the response signal includes:
searching hard points corresponding to the basic test vehicle in the whole vehicle simulation model, and inputting the time domain response signals to the hard points corresponding to the whole vehicle simulation model;
carrying out structural stress response analysis on the whole vehicle simulation model under different road conditions according to the time domain vibration response signals;
calculating a first fatigue damage value of the battery pack simulation model and a second fatigue damage value of each connecting point connecting bolt of the battery pack simulation model and the vehicle body model under the structural stress response analysis through a fatigue accumulated damage theory;
determining the fatigue damage assessment parameter according to the first fatigue damage value and the second fatigue damage value;
obtaining the maximum stress of each hard point of the whole vehicle simulation model when a time domain vibration response signal is input;
and calculating the stress of the connecting bolt according to the maximum stress of each hard point, and determining the bolt strength evaluation parameter according to the stress of the connecting bolt.
6. The evaluation method according to claim 2, wherein the obtaining the safety reliability evaluation parameters of the battery pack simulation model in the collision analysis includes:
acquiring an intrusion curve of the shell simulation model into the battery pack simulation model during collision, and determining stress changes of compression bolts among a plurality of single battery simulation models according to the intrusion curve;
acquiring a response acceleration course curve of the single battery simulation model during collision;
determining a connection lifting lug, a connection bolt and stress changes of the single battery simulation model, wherein the connection lifting lug, the connection bolt and the single battery simulation model are connected with the vehicle body model according to the response acceleration process curve;
and determining the safety reliability evaluation parameters according to the stress changes of the compression bolt, the connecting lifting lug, the connecting bolt and the single battery simulation model.
7. The method of claim 1, wherein determining the weight information for each evaluation parameter to complete the evaluation of the power cell comprises:
carrying out dimensionless and normalization treatment on each evaluation parameter in the parameter index evaluation system;
constructing an AHP hierarchical model, quantitatively analyzing the dimensionless and normalized evaluation parameters through the AHP hierarchical model, and determining weight information of the evaluation parameters;
and evaluating the power battery according to the weight information of each evaluation parameter.
8. The evaluation method according to claim 2, characterized in that before assembling a plurality of the cell simulation models to form a battery module model, the evaluation method further comprises:
carrying out single mechanical simulation analysis on the single battery simulation model, and obtaining a stress-strain history curve of the single battery simulation model according to the single mechanical simulation analysis;
and determining the maximum tensile stress value or the maximum strain value allowed by the single battery simulation model according to the stress-strain history curve.
9. A readable storage medium having stored thereon a program, which when executed by a processor, implements the method according to any of claims 1-8.
10. A computer device comprising a memory, a processor and a program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1-8 when the program is executed by the processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310291676.XA CN116432426A (en) | 2023-03-23 | 2023-03-23 | Vehicle-mounted power battery evaluation method, readable storage medium and computer equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310291676.XA CN116432426A (en) | 2023-03-23 | 2023-03-23 | Vehicle-mounted power battery evaluation method, readable storage medium and computer equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116432426A true CN116432426A (en) | 2023-07-14 |
Family
ID=87091816
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310291676.XA Pending CN116432426A (en) | 2023-03-23 | 2023-03-23 | Vehicle-mounted power battery evaluation method, readable storage medium and computer equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116432426A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116952751A (en) * | 2023-09-20 | 2023-10-27 | 中国汽车技术研究中心有限公司 | Battery pack damage assessment method, system and equipment |
-
2023
- 2023-03-23 CN CN202310291676.XA patent/CN116432426A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116952751A (en) * | 2023-09-20 | 2023-10-27 | 中国汽车技术研究中心有限公司 | Battery pack damage assessment method, system and equipment |
| CN116952751B (en) * | 2023-09-20 | 2023-12-15 | 中国汽车技术研究中心有限公司 | Battery pack damage assessment method, system and equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113591228B (en) | Noise transmission path analysis and optimization method | |
| CN116432426A (en) | Vehicle-mounted power battery evaluation method, readable storage medium and computer equipment | |
| CN117824756A (en) | Building structure monitoring method, equipment and storage medium | |
| Karpenko et al. | Methodology for the composite tire numerical simulation based on the frequency response analysis | |
| Zhang et al. | Deep learning-based vibration stress and fatigue-life prediction of a battery-pack system | |
| CN116629078B (en) | Method and system for predicting fatigue life durability of automobile | |
| CN110889248A (en) | Air spring fatigue life prediction platform and prediction method thereof | |
| CN117473620B (en) | Bridge reconstruction construction method integrating BIM technology and algorithm model | |
| CN111709160B (en) | Driving dynamic performance analysis optimization method and system based on truck chassis | |
| CN115204020B (en) | Method and system for analyzing strength of electrically-driven bridge system, storage medium and test equipment | |
| CN110955933B (en) | Mechanical structure fuzzy fatigue reliability calculation method based on response surface method | |
| CN114624015B (en) | Method, device, equipment and storage medium for testing strength of vehicle part | |
| CN117928982A (en) | Experimental platform testing method, operation and maintenance method and storage medium based on road condition information | |
| CN117350115A (en) | Simulation analysis and evaluation method for fastening and sealing assembly working conditions of vehicle-mounted shark fin structure | |
| CN114254533B (en) | Method for examining influence and prediction of fatigue vibration on fixed angle of product group component | |
| Veltri | FEM techniques for high stress detection in accelerated fatigue simulation | |
| CN115544746A (en) | Multi-attribute target-driven aluminum auxiliary frame optimization design method and system | |
| CN113919189A (en) | Physical tire model-based whole vehicle road noise analysis method | |
| Saleem et al. | Health monitoring of ultra high fiber performance reinforced concrete communication tower using machine learning algorithms | |
| CN118313070B (en) | Deep learning-based automobile structure stress anomaly analysis method and system | |
| CN114936485B (en) | Vibration stress and fatigue life prediction method for battery pack system | |
| CN117763709A (en) | Modularized design optimization method for cast triangular beam structure | |
| Zhang et al. | Multi-objective optimization design of assembled wheel lightweight based on implicit parametric method and modified NSGA-II | |
| Ding et al. | Research on Data Analysis and Safety Assessment of Traditional Automobile Operation Based on Neural Network | |
| CN118313070A (en) | Deep learning-based automobile structure stress anomaly analysis method and 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 |