CN116070534A - Optimization method, device, equipment and medium for liquid cooling plate in lithium battery energy storage system - Google Patents
Optimization method, device, equipment and medium for liquid cooling plate in lithium battery energy storage system Download PDFInfo
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Abstract
The invention provides a method, a device, equipment and a medium for optimizing a liquid cooling plate in a lithium battery energy storage system, which belong to the field of lithium battery analysis, and the method comprises the steps of constructing a collaborative simulation optimizing platform and integrating a plurality of functional units; simplifying a geometric CAD model of the liquid cooling plate by adopting a geometric parameterization unit and outputting a parameterized geometric model; carrying out CFD modeling and analysis calculation on the parameterized geometric model by adopting a CFD modeling and analysis unit; determining a plurality of calculation points corresponding to the design variables by adopting a multi-parameter optimization unit; substituting a plurality of calculation points into a fitting algorithm to carry out fitting analysis to obtain a response surface and a sensitivity map of output parameters of each calculation point, and generating a fitting model; based on a multi-objective genetic algorithm, an optimal solution of the design variable is obtained, and an optimal value of the liquid cooling plate is output. Through the processing scheme of the application, the evaluation of the flow characteristics and the heat dissipation performance of the liquid cooling plate is realized, and the high-efficiency intelligent optimization of the cooling plate structure is realized.
Description
Technical Field
The invention relates to the field of lithium battery analysis, in particular to a method and a device for optimizing a liquid cooling plate in a lithium battery energy storage system, computer equipment and a computer readable storage medium.
Background
Along with the continuous development of the domestic energy storage market, the accumulated energy storage installation scale of China has been the first to jump around the world, and the application of lithium battery energy storage projects is more and more extensive. The main factors affecting the performance and life of the battery system of the lithium battery energy storage system at present are temperature control in the battery operation process: the overheat of the operating temperature may lead to thermal runaway of the battery, the low environment leads to reduced discharge efficiency, and the capacity of the battery cells is attenuated due to uneven temperature between the batteries. Therefore, how to control the battery operating temperature and temperature difference during the system operation is an important and difficult problem in the development of the heat management operation of the energy storage system.
For the novel lithium battery energy storage system based on the liquid cooling heat dissipation technology, the liquid cooling plate is a core part of the whole product heat management research and development. The design of the liquid cooling plate directly relates to core indexes such as control of the working temperature range of the whole battery pack, temperature difference, system flow resistance and the like. The liquid cooling plate is a heat dissipation device formed by a plurality of flow channels, redundant heat generated by the operation of the battery is transferred to the surface of the liquid cooling plate through the heat conduction pad and is finally taken away by cooling liquid in the flow channels inside the liquid cooling plate, and heat dissipation and operation temperature control of the energy storage battery are realized. The design of the internal flow channels firstly ensures that the flow field distribution in each heat dissipation flow channel is high in uniformity, thereby improving the consistency of the running temperature of the battery monomers in the whole battery pack; and secondly, the design of the liquid cooling plate flow channel is required to meet the requirements of small flow resistance and pressure reduction of the system under a certain flow rate, so that the additional energy consumption of the whole cooling system is reduced.
The prior liquid cooling plates are generally designed with equal width flow channels, but because the distance between each flow channel and the inlet and outlet, the length and the shape of the flow channel are different, the flow distribution in each flow channel is uneven due to the larger flow distribution in the flow channel, and the uneven heat dissipation among all areas in a battery system is further caused, so that the consistency of the temperatures in all the areas in the whole energy storage battery system is poor, the service life is influenced, and even the risk of thermal runaway can be caused. In addition, the structure of the liquid cooling plate at present mainly depends on experience of designers and a simple formula, and quantitative evaluation on internal flow characteristics of the liquid cooling plate is often lacking, especially parameters such as flow uniformity, flow resistance and the like. The cold plate designed often has the problems of poor flow uniformity, poor flow resistance and the like.
Therefore, the performance evaluation and optimization of the liquid cooling plate are very important for the heat design and heat management work of the energy storage system, but the flow path in the liquid cooling plate is complex, variable parameters are numerous, different values of the parameters have great influence on the heat dissipation of the battery, the method belongs to the multi-objective optimization problem, and a better multi-objective optimization application method of the liquid cooling plate does not exist at present. The optimization of the flow channel of the existing liquid cooling plate is usually carried out in a manual mode, calculation points are needed to be selected manually, calculation results of all calculation points are compared, the next calculation point is selected according to the comparison results, the above process is repeated in a circulating mode, and the whole process is often operated repeatedly. Because the calculation points are manually selected, the problems that an optimal solution cannot be found, the optimization process is long in time consumption, low in efficiency and the like often exist.
Disclosure of Invention
Therefore, in order to overcome the defects in the prior art, the invention realizes the evaluation of the heat dissipation performance of the liquid cooling plate by parameterizing the size of the liquid cooling plate and establishing a simulation model of the battery liquid cooling system through a CFD technology to form a parameterized CFD-based simulation model; and the intelligent optimization of the cold plate structure, the performance prediction and the optimization method, the device, the computer equipment and the computer readable storage medium of the cold plate in the lithium battery energy storage system with the optimal final output performance are realized by combining a multi-parameter intelligent optimization technology. CFD (Computational Fluid Dynamics) the fluid dynamics are calculated.
In order to achieve the above object, the present invention provides a method for optimizing a liquid cooling plate in a lithium battery energy storage system, comprising: constructing a collaborative simulation optimization platform of data interconnection, and integrating a geometric parameterization unit, a CFD modeling and analysis unit and a multi-parameter optimization unit; simplifying a geometric CAD model of the liquid cooling plate by adopting the geometric parameterization unit to obtain geometric dimension parameters of the liquid cooling plate after simplification, and outputting a parameterized geometric model; performing CFD mesh division on the parameterized geometric model by adopting the CFD modeling and analyzing unit, establishing a liquid cooling plate CFD mesh model, updating analysis parameters according to the actual flowing working condition of the liquid cooling plate, performing CFD analysis and calculation, and parameterizing an input variable and a result variable so as to output; defining an objective function, a design variable and a constraint space by adopting a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by the CFD modeling and analysis unit; substituting a plurality of calculation points into a fitting algorithm to carry out fitting analysis, obtaining a response surface and a sensitivity map of output parameters of each calculation point, and generating a fitting model; based on a multi-objective genetic algorithm, an optimal solution of the design variable is obtained, and the CFD modeling and analysis unit is adopted for verification, so that an optimal value of the liquid cooling plate is output.
In one embodiment, the simplifying the geometric CAD model of the liquid cooling plate by using the geometric parameterization unit to obtain the simplified geometric parameters of the liquid cooling plate includes: obtaining a geometric CAD model of a liquid cooling plate to be optimized; the geometric parameterization unit is adopted to parameterize the geometric dimension of the liquid cooling plate, so as to obtain an initial geometric dimension parameter consistent with the liquid cooling plate; analyzing the initial geometric dimension parameters, and identifying redundant parameters with the influence on the flow field smaller than a preset threshold value; and screening out the redundant parameters from the initial geometric parameters, and compensating the initial geometric parameters to obtain the simplified geometric parameters.
In one embodiment, the performing CFD modeling and analysis calculation according to the actual flow condition of the liquid cooling plate and updating analysis parameters, and parameterizing the input variable and the result variable for output includes: according to the actual flow condition, carrying out CFD grid division on the liquid cooling plate, and defining calculation parameters, wherein the calculation parameters comprise inlet and outlet speeds, temperature and turbulence models, and carrying out CFD flow field calculation analysis; and obtaining inlet and outlet pressure and section flow of each branch pipe flow passage in the CFD calculation result of the liquid cooling plate, and setting the result variables as output parameters for parameterization.
In one embodiment, the defining an objective function, a design variable and a constraint space by using a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by the CFD modeling and analysis unit includes: the multi-parameter optimization unit is adopted, the average difference of the section flow of each branch pipe of the liquid cooling plate and the total inlet and outlet pressure difference of the liquid cooling plate are taken as optimization targets, the geometric parameters of each flow passage section and the distance between the flow passage baffle and the end part are taken as design variables, and the variable constraint interval is taken as a boundary condition, wherein i is less than j, and i and j are positive numbers; determining the precision of the parameter data from the design requirement, and determining the number of settable calculation points in the parameter data according to the precision; and determining a plurality of calculation points corresponding to the design variable according to the number of calculation points and the parameter data.
In one embodiment, the inlet-outlet pressure drop Δp and the average difference Σ|x-x '|) of the flow rates of the various sub-pipelines are used as an objective function, wherein x is the section flow rate of each branch pipe in the sample, x' is the average value of the section flow rates of a plurality of branch pipes in the sample, and n is the number of branch pipes in the sample.
In one embodiment, the substituting the plurality of calculation points into a fitting algorithm to perform fitting analysis to obtain a response surface and a sensitivity map of output parameters of each calculation point, and generating a fitting model includes: and performing fitting analysis by adopting a Neural-Network algorithm to obtain a response surface and a sensitivity graph of each input parameter to the output parameter, and obtaining a fitting model.
An optimization device for a liquid cooling plate in a lithium battery energy storage system, the device comprising: the unit integration module is used for constructing a simulation collaborative optimization platform of data interconnection, integrating a geometric parameterization unit, a CFD modeling and analysis unit and a multi-parameter optimization unit which are connected in series; the simplifying module is used for simplifying the geometric CAD model of the liquid cooling plate by adopting the geometric parameterization unit, obtaining the geometric dimension parameters of the liquid cooling plate after being simplified, and outputting a parameterized geometric model; the CFD analysis calculation module is used for carrying out CFD mesh division on the parameterized geometric model by adopting the CFD modeling and analysis unit, establishing a liquid cooling plate CFD mesh model, carrying out CFD analysis calculation according to the actual flowing working condition of the liquid cooling plate and updating analysis parameters, and parameterizing an input variable and a result variable so as to output; the parameter definition module is used for defining an objective function, a design variable and a constraint space by adopting a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by the CFD modeling and analysis unit; the fitting module is used for substituting a plurality of calculation points into a fitting algorithm to carry out fitting analysis, so as to obtain a response surface and a sensitivity map of the output parameters of each calculation point, and generate a fitting model; and the verification module is used for acquiring an optimal solution of the design variable based on a multi-target genetic algorithm, adopting the CFD modeling and analysis unit to verify, and outputting an optimal value of the liquid cooling plate.
A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the above method when executing the computer program.
A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor realizes the steps of the above-mentioned method.
Compared with the prior art, the invention has the advantages that: establishing a simulation model of the battery liquid cooling system through a CFD technology, parameterizing the size of the liquid cooling plate structure to form a parameterized CFD simulation model, and realizing quantitative and accurate assessment of the heat dissipation performance of the liquid cooling plate; and the intelligent optimization of the cold plate structure, the performance prediction and the final output of the structural design scheme with optimal performance are realized by combining a multi-parameter intelligent optimization technology. The CFD simulation optimization mode is used for replacing simple theoretical formula calculation, so that quantitative evaluation is realized; the multi-parameter intelligent optimization is adopted to replace manual optimization, so that the effects of shortening the optimization period, improving the optimization efficiency and reducing the labor cost are achieved; in addition, the parameterized modeling geometric software, the CFD analysis software and the multi-parameter optimization are all tools under the same simulation platform, so that seamless transfer of geometric model, grid model, simulation model and optimization model parameters can be realized, cross-platform interface development work is reduced, modeling-simulation-optimization process integration is realized, and optimization efficiency is greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a cross section of a liquid cooling plate in an embodiment of the invention;
FIG. 2 is a flow chart of a method of optimizing a liquid cooling plate in a lithium battery energy storage system in accordance with an embodiment of the invention;
FIG. 3 is a graph showing the flow ratio distribution of each flow channel before and after optimization in the embodiment of the present invention;
FIG. 4 is a block diagram of an optimizing apparatus for a liquid cooling plate in a lithium battery energy storage system according to an embodiment of the present invention;
fig. 5 is an internal structural view of a computer device in an embodiment of the present invention.
Detailed Description
Embodiments of the present application are described in detail below with reference to the accompanying drawings.
Other advantages and effects of the present application will become apparent to those skilled in the art from the present disclosure, when the following description of the embodiments is taken in conjunction with the accompanying drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. The present application may be embodied or carried out in other specific embodiments, and the details of the present application may be modified or changed from various points of view and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
It is noted that various aspects of the embodiments are described below within the scope of the following claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the present application, one skilled in the art will appreciate that one aspect described herein may be implemented independently of any other aspect, and that two or more of these aspects may be combined in various ways. For example, apparatus may be implemented and/or methods practiced using any number and aspects set forth herein. In addition, such apparatus may be implemented and/or such methods practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
It should also be noted that the illustrations provided in the following embodiments merely illustrate the basic concepts of the application by way of illustration, and only the components related to the application are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
In addition, in the following description, specific details are provided in order to provide a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects may be practiced without these specific details.
As shown in FIG. 1, the inner flow channel of the liquid cooling plate can be a parallel flow channel, and the 4 sub-plates a/b/c/d are connected in series. The flow channel of each sub-board is formed by combining a baffle, a cover plate and a bottom plate. Wherein 1 is a liquid cooling plate cooling liquid inlet pipeline; 2 is a liquid cooling plate cooling liquid outlet pipeline; and 3 is a liquid cooling plate runner frame. 4. 5, 6 are the flow passage baffles of the liquid cooling plate sub-plate a; 7. 8, 9 and 10 are 4 parallel flow channels of the liquid cooling plate sub-plate a divided by the baffle plate; 11. 12 and 13 are liquid cooling plate sub-plate b flow passage baffles; 18. 19 and 20 are liquid cooling plate sub-plate c flow passage baffles; 25. 26 and 27 are the flow passage baffles of the liquid cooling plate sub-plate f; 14. 15, 16, 17 are parallel flow channels of the liquid cooling plate sub-board b; 21. 22, 23 and 24 are parallel flow channels of the liquid cooling plate daughter board c; 28. 29, 30 and 31 are parallel flow channels of the liquid cooling plate daughter board d; d1 to D25 are distances from the flow passage baffles to the frame.
The cold plate is divided into four parallel flow channels by the baffle plate, and the 4 sub-plates are mutually connected in series; the cooling liquid flows in through the inlet pipeline, then is split into 4 parallel pipelines, flows to the rightmost side and then is converged, and flows down to the daughter board b along the side flow; after entering the subplate b, the flow is split into 4 parallel pipelines, flows to the leftmost rear confluence, and flows downwards to the subplate c along the side flow path; after entering the subplate c, the flow is split into 4 parallel pipelines, flows to the rightmost side and is converged, and flows downwards to the subplate d along the side flow path; and the flow enters the subplate d and is split into 4 parallel pipelines, flows to the leftmost side and is converged, and flows out through an outlet.
The liquid cooling plate has compact structure, taking the subplate a as an example, the cooling liquid inlet is close to the subflow channel, wherein the 8 flow channel and the 9 flow channel are nearest to the inlet; meanwhile, after the 4 sub-channels are converged at the rightmost side, the flow resistance of each sub-channel is larger through the next sub-board of the channel with the D6 section, the flow resistance of the obvious sub-channel 10 is minimum, and the flow resistance of the sub-channel 8 is maximum, so that the flow of each channel is uneven. Similarly, the sub-board b/c/d also has the problem of uneven flow distribution, which results in poor temperature uniformity.
As shown in fig. 2, the embodiment of the application provides an optimization method for a liquid cooling plate in a lithium battery energy storage system, specifically, the distances (D1-D25) between baffle plates of each sub-channel of the liquid cooling plate are taken as optimization variables, the fluid performance of the liquid cooling plate is evaluated, and the optimization of multiple parameters of the structure is performed, so that the optimization method can be applied to a terminal or a server, the terminal can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers and portable intelligent devices, and the server can be realized by an independent server or a server cluster formed by a plurality of servers. The terminal or the server can cooperate with the running of the simulation platform. The method comprises the following steps:
The collaborative simulation optimization platform can be a platform capable of integrating geometric modeling and processing of a complex mechanical system, hydrodynamic simulation analysis, structural mechanical simulation analysis, multi-parameter optimization and the like. In one embodiment, the simulation collaboration platform may be a platform developed from the integrated object itself, or may be a business software platform, such as: the Dassault3DExperience, ANSYSWORKBENCH, SIEMENS Teamcenter analysis platform, the geometric parameterization unit may be Solidworks, spacelaim, NX UG, etc. (direct modeling tool for geometric operations, for geometric modeling, repair, preparation and parameterization), the CFD modeling and analysis unit may be open-source Openform, or ANSYSSFLUENT, STAR CCM, XFLOW, etc. unit under the commercial software platform (CFD package), and the multiparameter optimization may be MATLAB, ISight, designXplorer. Based on the analysis flow established by the platform, each module realizes data seamless connection through the cooperative platform, and additional works such as interface development, data conversion and the like are not required to be carried out. CFD (Computational Fluid Dynamics) the fluid dynamics are calculated.
And simplifying the geometric CAD model of the liquid cooling plate by adopting a geometric parameterization unit to obtain the geometric dimension parameters of the liquid cooling plate after simplification, and outputting the parameterized geometric model. The inner runner of the liquid cooling plate can be a parallel runner and is formed by connecting a plurality of sub-plates in series. The flow channel of each sub-board is formed by combining a baffle, a cover plate and a bottom plate. The geometric CAD model is constructed according to the size parameters of the liquid cooling plate to be optimized. The geometric CAD model is simplified, mainly by performing geometric cleaning on the geometric model, for example, removing fine features and structures that have no influence on the flow field, such as: bolt holes, chamfers, etc.
And 203, carrying out CFD mesh division on the parameterized geometric model by adopting a CFD modeling and analyzing unit, establishing a liquid cooling plate CFD mesh model, updating analysis parameters according to the actual flowing condition of the liquid cooling plate, carrying out CFD modeling and analysis calculation, and parameterizing an input variable and a result variable so as to output.
CFD modeling and analysis units are adopted to carry out CFD mesh division on the parameterized geometric model, a liquid cooling plate CFD mesh model is established, analysis parameters are updated according to actual flowing conditions of the liquid cooling plate, CFD modeling and analysis calculation are carried out, and input variables and result variables are parameterized so as to be output. The geometric model can be subjected to grid division and grid independence analysis through the grid division module under the unit; after the analysis is completed, a turbulence model and a calculation model are selected, inlet and outlet boundary conditions are set, iterative calculation is carried out to obtain an analysis result, and data communication is realized after the flow and inlet and outlet pressure drops of each flow channel in the analysis result are parameterized.
And 204, defining an objective function, design variables and a constraint space by adopting a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variables according to parameter data and design requirements output by the CFD modeling and analysis unit.
And defining an objective function, design variables and a constraint space by adopting a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variables according to parameter data and design requirements output by the CFD modeling and analysis unit. The design variables are D1-D25, and a constraint interval (8 mm,40 mm) of the design variables is given; and calculating the response result of each sample according to the data acquisition design parameter samples of the input parameters, wherein the calculated sample point number is 268. The variable constraint interval can be set according to the required precision.
And 205, substituting a plurality of calculation points into a fitting algorithm to carry out fitting analysis, obtaining a response surface and a sensitivity map of the output parameters of each calculation point, and generating a fitting model.
Substituting the plurality of calculation points into a fitting algorithm to carry out fitting analysis, obtaining a response surface and a sensitivity map of the output parameters of each calculation point, and generating a fitting model. For example, in one embodiment, a Neural-Network algorithm is used to perform fitting analysis on all calculation points, so as to obtain a response surface and a sensitivity map of each input parameter to the output parameter, and obtain a fitting model.
And 206, obtaining an optimal solution of the design variable based on a multi-objective genetic algorithm, verifying by adopting a CFD modeling and analysis unit, and outputting an optimal value of the liquid cooling plate.
Based on the multi-objective optimization algorithm MOGA, the two parameters of the objective variables delta P and (Sigma|x-x' |) and 4 are set to be minimum. And after the simulation optimization calculation is carried out, returning to the generated optimal design scheme of the liquid cooling plate, adding scheme parameters to design points, calculating and verifying by using a CFD modeling analysis unit, and outputting the optimized value of the liquid cooling plate when the flow rate in each flow passage sub-pipeline channel is judged to be uniform. Fig. 3 is a graph of flow rates of all sub-channels before and after optimization, and it can be seen from the graph that the flow rates of all the channels before optimization are large (the flow rates of the sub-channels are 57% at maximum and 9% at minimum), and the flow rates after optimization are 2% different from the minimum value of the maximum value, and the uniformity is extremely high.
The method utilizes CFD software to quantitatively evaluate the design scheme, and solves the error problem caused by simple formula calculation and the long period and high cost problem of the test means; the parameterized optimization method comprising the integration of the geometric model, the simulation model and the optimization model is established based on the same platform to replace manual optimization, so that the effects of greatly shortening the optimization period, improving the optimization efficiency and reducing the labor cost are achieved (the manual optimization mode is used for an industrial skilled engineer, the optimization flow takes no less than 15 days, the parameterized intelligent optimization mode is adopted now, the high-performance server is used for calculation, and the whole process takes about 3-5 days); meanwhile, the obtained optimization scheme can be effectively guaranteed to be an optimal result, and therefore the overall battery system achieves an optimal heat dissipation effect.
And all units run on the same platform, so that the integration of the whole design optimization process is realized, additional interface development and data conversion work are not needed, the execution difficulty of the whole optimization method is reduced, the secondary development link of software in the analysis optimization process is simplified, and the standardization of the analysis optimization flow is facilitated. The method also establishes a simulation driving design flow field and realizes the high integration based on simulation and design optimization, and the forward design and the rapid iteration of the booster liquid cooling plate are realized.
In one embodiment, a geometric parameterization unit is used to simplify a geometric CAD model of the liquid cooling plate, so as to obtain geometric dimension parameters of the liquid cooling plate after simplification, and the method comprises the following steps: obtaining a geometric CAD model of a liquid cooling plate to be optimized; parameterizing the geometric dimension of the liquid cooling plate by adopting a geometric parameterization unit to obtain an initial geometric dimension parameter consistent with the liquid cooling plate; analyzing the initial geometric parameters, and identifying redundant parameters with the influence on the flow field smaller than a preset threshold value; and screening redundant parameters from the initial geometric parameters, and compensating the initial geometric parameters to obtain simplified geometric parameters.
And analyzing the geometric CAD model, and extracting all initial geometric dimension parameters consistent with the liquid cooling plate in the geometric CAD model. The server can determine the corresponding mechanical structure through the initial geometric dimension parameters, and judge the redundancy parameters through the mechanical structure; the server can also acquire all preset redundancy parameters, and then compare the redundancy parameters with the initial geometric dimension parameters to determine the redundancy parameters. And the server screens redundant parameters from the initial geometric parameters, compensates the initial geometric parameters, and obtains the simplified geometric parameters. For example, the parameter data of the bolt holes are removed, the server compensates the parameters of the interrupted flow channels based on the size values of the bolt holes, and the two interrupted flow channels are compensated into a complete flow channel.
The method can reduce the data operation amount and further shorten the time consumption while ensuring the accuracy of the model.
In one embodiment, according to the actual flow condition of the liquid cooling plate, updating analysis parameters, performing CFD modeling and analysis calculation, and parameterizing input variables and result variables for output, including: according to the actual flow condition, carrying out CFD grid division on the liquid cooling plate, and defining calculation parameters, wherein the calculation parameters comprise inlet and outlet speeds, temperature and turbulence models, and carrying out CFD flow field calculation analysis; and obtaining inlet and outlet pressure and section flow of each branch pipe runner in the CFD calculation result of the liquid cooling plate, and setting the result variables as output parameters for parameterization.
CFD mesh division is carried out on the simplified geometric model through a CFD modeling and analyzing unit, a liquid cooling plate CFD mesh model is established, and the liquid cooling plate CFD mesh model meets the calculation precision requirement. The method comprises the steps of obtaining preset boundary conditions and a solving algorithm, calculating an initialized CFD grid model of the liquid cooling plate, and parameterizing the CFD grid model by setting result variables as output parameters based on obtained inlet and outlet pressures of the liquid cooling plate and the section flow of each branch pipe.
The server can take the average difference of the section flow of each branch pipe of the liquid cooling plate and the total inlet and outlet pressure difference of the liquid cooling plate as result targets, and the section geometric parameters of the flow channels of each branch pipe and the distance between the flow channel baffle and the end part are taken as input variables, so that the parameterized CFD grid model of the liquid cooling plate is optimized. Specifically, the inlet-outlet pressure drop Δp and the average difference of the flow rates of the sub-pipelines (Σ|x-x '|) per n can be used as objective functions by adopting a multi-parameter optimization unit, wherein x is the section flow rate of each branch pipe in the sample, x' is the average value of the section flow rates of a plurality of branch pipes in the sample, n is the number of branch pipes in the sample, and n=4 of each sub-pipeline in fig. 1.
In one embodiment, defining an objective function, a design variable, and a constraint space by using a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by a CFD modeling and analysis unit, including:
the multi-parameter optimization unit is adopted, the average difference of the section flow of each branch pipe of the liquid cooling plate and the total inlet and outlet pressure difference of the liquid cooling plate are taken as optimization targets, the geometric parameters of each flow passage section and the distance between the flow passage baffle and the end part are taken as design variables, and the variable constraint interval is taken as a boundary condition, wherein i is less than j, and i and j are positive numbers;
Determining the precision of the parameter data from the design requirement, and determining the number of settable calculation points in the parameter data according to the precision;
a plurality of calculation points corresponding to the design variables are determined based on the number of calculation points and the parameter data.
In one embodiment, as shown in fig. 4, an optimization device for a liquid cooling plate in a lithium battery energy storage system is provided, where the device includes a unit integration module 501, a simplification module 502, a CFD analysis calculation module 503, a parameter definition module 504, a fitting module 505, and a verification module 506.
The unit integration module 501 is used for constructing a geometric parameterization unit, a CFD modeling and analysis unit and a multi-parameter optimization unit which are connected in series based on the simulation collaboration platform.
The simplifying module 502 is configured to simplify the geometric CAD model of the liquid cooling plate by using a geometric parameterization unit, obtain the simplified geometric dimension parameter of the liquid cooling plate, and output a parameterized geometric model.
The CFD analysis calculation module 503 is configured to perform CFD mesh division on the parameterized geometric model by using a CFD modeling and analysis unit, establish a liquid cooling plate CFD mesh model, update analysis parameters according to an actual flow condition of the liquid cooling plate, perform CFD modeling and analysis calculation, and parameterize an input variable and a result variable for output.
The parameter definition module 504 is configured to define an objective function, a design variable, and a constraint space by using the multi-parameter optimization unit, and determine a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by the CFD modeling and analysis unit.
The fitting module 505 is configured to apply the plurality of calculation points to a fitting algorithm to perform fitting analysis, obtain a response surface and a sensitivity map of output parameters of each calculation point, and generate a fitting model.
And the verification module 506 is configured to obtain an optimal solution of the design variable based on the multi-objective genetic algorithm, perform verification by using the CFD modeling and analysis unit, and output an optimized value of the liquid cooling plate.
In one embodiment, the simplification module comprises:
and the model acquisition unit is used for acquiring the geometric CAD model of the liquid cooling plate to be optimized.
And the parameterization unit is used for parameterizing the geometric dimension of the liquid cooling plate by adopting the geometric parameterization unit to obtain the initial geometric dimension parameter consistent with the liquid cooling plate.
And the analysis unit is used for analyzing the initial geometric dimension parameters and identifying redundant parameters with the influence on the flow field smaller than a preset threshold value.
And the screening unit is used for screening redundant parameters from the initial geometric dimension parameters, and compensating the initial geometric dimension parameters to obtain simplified geometric dimension parameters.
In one embodiment, the CFD analysis computation module includes:
and the output parameter analysis unit is used for carrying out CFD grid division on the liquid cooling plate according to the actual flow condition, defining calculation parameters such as inlet and outlet speed, temperature, turbulence model and the like, and carrying out CFD flow field calculation analysis.
And the parameter setting unit is used for acquiring inlet and outlet pressure and section flow of each branch pipe flow passage in the CFD calculation result of the liquid cooling plate, and setting the result variables as output parameters for parameterization.
In one embodiment, the parameter definition module comprises:
the variable obtaining unit is used for adopting the multi-parameter optimizing unit to take the average difference of the section flow of each branch pipe of the liquid cooling plate and the total inlet and outlet pressure difference of the liquid cooling plate as optimizing targets, taking the geometric parameters of each flow passage section and the distance between the flow passage baffle and the end part as design variables and taking a variable constraint interval as boundary conditions, wherein i is less than j, and i and j are positive numbers.
And the calculation point number determining unit is used for determining the precision of the parameter data from the design requirement and determining the number of settable calculation points in the parameter data according to the precision.
And a calculation point setting unit for determining a plurality of calculation points corresponding to the design variables based on the number of calculation points and the parameter data.
In one embodiment, the fitting module comprises:
the fitting unit is used for carrying out fitting analysis by adopting a Neural-Network algorithm to obtain a response surface and a sensitivity map of each input parameter to the output parameter, and a fitting model is obtained.
For specific limitation of the optimizing device of the liquid cooling plate in the lithium battery energy storage system, reference may be made to the limitation of the optimizing method of the liquid cooling plate in the lithium battery energy storage system, and the detailed description is omitted herein. All or part of each module in the optimizing device of the liquid cooling plate in the lithium battery energy storage system can be realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing data such as boundary conditions, input variables and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by the processor is used for realizing an optimization method of the liquid cooling plate in the lithium battery energy storage system.
It will be appreciated by those skilled in the art that the structure shown in fig. 5 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory storing a computer program and a processor that when executing the computer program performs the steps of: based on a simulation collaboration platform, a geometric parameterization unit, a CFD modeling and analysis unit and a multi-parameter optimization unit which are connected in series are constructed; simplifying a geometric CAD model of the liquid cooling plate by adopting a geometric parameterization unit to obtain geometric dimension parameters of the liquid cooling plate after simplification, and outputting a parameterized geometric model; performing CFD mesh division on the parameterized geometric model by adopting a CFD modeling and analyzing unit, establishing a liquid cooling plate CFD mesh model, updating analysis parameters according to the actual flowing condition of the liquid cooling plate, performing CFD modeling and analysis calculation, and parameterizing input variables and result variables so as to output; defining an objective function, a design variable and a constraint space by adopting a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by a CFD modeling and analyzing unit; substituting a plurality of calculation points into a fitting algorithm to carry out fitting analysis to obtain a response surface and a sensitivity map of output parameters of each calculation point, and generating a fitting model; based on a multi-objective genetic algorithm, an optimal solution of the design variable is obtained, and a CFD modeling and analysis unit is adopted for verification, so that an optimal value of the liquid cooling plate is output.
In one embodiment, the simplifying the geometric CAD model of the liquid cooling plate by using the geometric parameterization unit when the processor executes the computer program, to obtain the simplified geometric dimension parameter of the liquid cooling plate, includes: obtaining a geometric CAD model of a liquid cooling plate to be optimized; parameterizing the geometric dimension of the liquid cooling plate by adopting a geometric parameterization unit to obtain an initial geometric dimension parameter consistent with the liquid cooling plate; analyzing the initial geometric parameters, and identifying redundant parameters with the influence on the flow field smaller than a preset threshold value; and screening redundant parameters from the initial geometric parameters, and compensating the initial geometric parameters to obtain simplified geometric parameters.
In one embodiment, the processor, when executing the computer program, performs CFD modeling and analysis calculations according to the actual flow conditions of the liquid cooling plate, updates analysis parameters, and parameterizes input variables and result variables for output, including: according to the actual flow condition, carrying out CFD grid division on the liquid cooling plate, defining computing parameters such as inlet and outlet speed, temperature, turbulence model and the like, and carrying out CFD flow field computing analysis; and obtaining inlet and outlet pressure and section flow of each branch pipe flow passage in the CFD calculation result of the liquid cooling plate, and setting the result variables as output parameters for parameterization.
In one embodiment, defining an objective function, a design variable, a constraint space by using a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by a CFD modeling and analysis unit when the processor executes a computer program, includes: the multi-parameter optimization unit is adopted, the average difference of the section flow of each branch pipe of the liquid cooling plate and the total inlet and outlet pressure difference of the liquid cooling plate are taken as optimization targets, the geometric parameters of each flow passage section and the distance between the flow passage baffle and the end part are taken as design variables, and the variable constraint interval is taken as a boundary condition, wherein i is less than j, and i and j are positive numbers; determining the precision of the parameter data from the design requirement, and determining the number of settable calculation points in the parameter data according to the precision; a plurality of calculation points corresponding to the design variables are determined based on the number of calculation points and the parameter data.
In one embodiment, the inlet-outlet pressure drop Δp, the average difference Σ|x-x '|) of the flow rates of each sub-pipeline and/n are used as an objective function when the processor executes the computer program, wherein x is the section flow rate of each branch pipe in the sample, x' is the average value of the section flow rates of a plurality of branch pipes in the sample, and n is the number of branch pipes in the sample.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of: based on a simulation collaboration platform, a geometric parameterization unit, a CFD modeling and analysis unit and a multi-parameter optimization unit which are connected in series are constructed; simplifying a geometric CAD model of the liquid cooling plate by adopting a geometric parameterization unit to obtain geometric dimension parameters of the liquid cooling plate after simplification, and outputting a parameterized geometric model; performing CFD mesh division on the parameterized geometric model by adopting a CFD modeling and analyzing unit, establishing a liquid cooling plate CFD mesh model, updating analysis parameters according to the actual flowing condition of the liquid cooling plate, performing CFD modeling and analysis calculation, and parameterizing input variables and result variables so as to output; defining an objective function, a design variable and a constraint space by adopting a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by a CFD modeling and analyzing unit; substituting a plurality of calculation points into a fitting algorithm to carry out fitting analysis to obtain a response surface and a sensitivity map of output parameters of each calculation point, and generating a fitting model; based on a multi-objective genetic algorithm, an optimal solution of the design variable is obtained, and a CFD modeling and analysis unit is adopted for verification, so that an optimal value of the liquid cooling plate is output.
In one embodiment, a geometric parameterization unit is used to simplify a geometric CAD model of a liquid cooling plate when a computer program is executed by a processor, to obtain simplified geometric parameters of the liquid cooling plate, including: obtaining a geometric CAD model of a liquid cooling plate to be optimized; parameterizing the geometric dimension of the liquid cooling plate by adopting a geometric parameterization unit to obtain an initial geometric dimension parameter consistent with the liquid cooling plate; analyzing the initial geometric parameters, and identifying redundant parameters with the influence on the flow field smaller than a preset threshold value; and screening redundant parameters from the initial geometric parameters, and compensating the initial geometric parameters to obtain simplified geometric parameters.
In one embodiment, a computer program, when executed by a processor, performs CFD modeling and analytical calculations based on actual flow conditions of a liquid cooling panel, updates analytical parameters, and parameterizes input variables and result variables for output, comprising: according to the actual flow condition, carrying out CFD grid division on the liquid cooling plate, defining computing parameters such as inlet and outlet speed, temperature, turbulence model and the like, and carrying out CFD flow field computing analysis; and obtaining inlet and outlet pressure and section flow of each branch pipe flow passage in the CFD calculation result of the liquid cooling plate, and setting the result variables as output parameters for parameterization.
In one embodiment, a computer program, when executed by a processor, defines an objective function, a design variable, a constraint space using a multi-parameter optimization unit, and determines a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by a CFD modeling and analysis unit, including: the multi-parameter optimization unit is adopted, the average difference of the section flow of each branch pipe of the liquid cooling plate and the total inlet and outlet pressure difference of the liquid cooling plate are taken as optimization targets, the geometric parameters of each flow passage section and the distance between the flow passage baffle and the end part are taken as design variables, and the variable constraint interval is taken as a boundary condition, wherein i is less than j, and i and j are positive numbers; determining the precision of the parameter data from the design requirement, and determining the number of settable calculation points in the parameter data according to the precision; a plurality of calculation points corresponding to the design variables are determined based on the number of calculation points and the parameter data.
In one embodiment, the computer program when executed by the processor performs the objective function of the inlet-outlet pressure drop Δp, the average difference Σ|x-x '|) of the flow rates of each branch in the sample, where x is the cross-sectional flow rate of each branch in the sample, x' is the average of the cross-sectional flow rates of a plurality of branches in the sample, and n is the number of branches in the sample.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily conceivable by those skilled in the art within the technical scope of the present application should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (9)
1. The optimization method of the liquid cooling plate in the lithium battery energy storage system is characterized by comprising the following steps of:
constructing a collaborative simulation optimization platform of data interconnection, and integrating a geometric parameterization unit, a CFD modeling and analysis unit and a multi-parameter optimization unit;
simplifying a geometric CAD model of the liquid cooling plate by adopting the geometric parameterization unit, parameterizing the key geometric dimension to obtain a dimension parameterized CAD data model of the liquid cooling plate after simplification, and outputting a parameterized geometric model;
performing CFD mesh division on the parameterized geometric model by adopting the CFD modeling and analysis unit, establishing a liquid cooling plate CFD mesh model, setting boundary conditions and analysis model parameters according to the actual flowing working condition of the liquid cooling plate, performing CFD modeling and analysis calculation, and parameterizing boundary condition input variables and result variables so as to output;
Defining an objective function, a design variable and a constraint space by adopting a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by the CFD modeling and analysis unit;
substituting a plurality of calculation points into a fitting algorithm to carry out fitting analysis, obtaining a response surface and a sensitivity map of output parameters of each calculation point, and generating a fitting model;
based on a multi-objective genetic algorithm, an optimal solution of the design variable is obtained, and the CFD modeling and analysis unit is adopted for verification, so that an optimal value of the liquid cooling plate is output.
2. The optimization method according to claim 1, wherein the simplifying the geometric CAD model of the liquid cooling plate by using the geometric parameterization unit to obtain the simplified geometric parameters of the liquid cooling plate comprises:
obtaining a geometric CAD model of a liquid cooling plate to be optimized;
the geometric parameterization unit is adopted to parameterize the geometric dimension of the liquid cooling plate, so as to obtain an initial geometric dimension parameter consistent with the liquid cooling plate;
analyzing the initial geometric dimension parameters, and identifying redundant parameters with the influence on the flow field smaller than a preset threshold value;
And screening out the redundant parameters from the initial geometric parameters, and compensating the initial geometric parameters to obtain the simplified geometric parameters.
3. The optimization method according to claim 1, wherein the performing CFD modeling and analysis calculation according to the actual flow condition of the liquid cooling plate, updating analysis parameters, and parameterizing input variables and result variables for output, comprises:
according to the actual flow condition, carrying out CFD grid division on the liquid cooling plate, and defining calculation parameters, wherein the calculation parameters comprise inlet and outlet speeds, temperature and turbulence models, and carrying out CFD flow field calculation analysis;
and obtaining inlet and outlet pressure and section flow of each branch pipe runner in the CFD calculation result of the liquid cooling plate, and setting the result variables as output parameters for parameterization.
4. The optimization method according to claim 1, wherein the defining an objective function, a design variable, a constraint space by using a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by the CFD modeling and analysis unit, comprises:
The multi-parameter optimization unit is adopted, the average difference of the section flow of each branch pipe of the liquid cooling plate and the total inlet and outlet pressure difference of the liquid cooling plate are taken as optimization targets, the geometric parameters of each flow passage section and the distance between the flow passage baffle and the end part are taken as design variables, and the variable constraint interval is taken as a boundary condition, wherein i is less than j, and i and j are positive numbers;
determining the precision of the parameter data from the design requirement, and determining the number of settable calculation points in the parameter data according to the precision;
and determining a plurality of calculation points corresponding to the design variable according to the number of calculation points and the parameter data.
5. The optimization method according to claim 4, wherein inlet-outlet pressure drop deltap and average difference sigma (|x-x '|)/n of flow rates of each sub-pipeline are taken as objective functions, wherein x is the section flow rate of each branch pipe in the sample, x' is the average value of the section flow rates of a plurality of branch pipes in the sample, and n is the number of branch pipes in the sample.
6. The optimization method according to claim 1, wherein the fitting analysis of the plurality of calculation points into a fitting algorithm to obtain a response surface and a sensitivity map of output parameters of each calculation point, and generating a fitting model comprises:
And performing fitting analysis by adopting a Neural-Network algorithm to obtain a response surface and a sensitivity graph of each input parameter to the output parameter, and obtaining a fitting model.
7. An optimizing device of a liquid cooling plate in a lithium battery energy storage system, which is characterized by comprising:
the unit integration module is used for building a collaborative simulation optimization platform for data interconnection and integrating all sub-units: the system comprises a geometric parameterization unit, a CFD modeling and analysis unit and a multi-parameter optimization unit;
the simplifying module is used for simplifying the geometric CAD model of the liquid cooling plate by adopting the geometric parameterization unit, obtaining the geometric dimension parameters of the liquid cooling plate after being simplified, and outputting a parameterized geometric model;
the CFD analysis calculation module is used for carrying out CFD mesh division on the parameterized geometric model by adopting the CFD modeling and analysis unit, establishing a liquid cooling plate CFD mesh model, carrying out CFD analysis calculation according to the actual flowing working condition of the liquid cooling plate and updating analysis parameters, and parameterizing an input variable and a result variable so as to output;
the parameter definition module is used for defining an objective function, a design variable and a constraint space by adopting a multi-parameter optimization unit, and determining a plurality of calculation points corresponding to the design variable according to parameter data and design requirements output by the CFD modeling and analysis unit;
The fitting module is used for substituting a plurality of calculation points into a fitting algorithm to carry out fitting analysis, so as to obtain a response surface and a sensitivity map of the output parameters of each calculation point, and generate a fitting model;
and the verification module is used for acquiring an optimal solution of the design variable based on a multi-target genetic algorithm, adopting the CFD modeling and analysis unit to verify, and outputting an optimal value of the liquid cooling plate.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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