CN112380785A - Battery thermal management optimization method and device, readable storage medium and computer equipment - Google Patents
Battery thermal management optimization method and device, readable storage medium and computer equipment Download PDFInfo
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Abstract
A battery thermal management optimization method, a device, a readable storage medium and a computer device are provided, wherein the method comprises the following steps: acquiring grouped material thermophysical parameters, design parameters and transmission performance parameters of a single battery cell, and structural parameters and thermophysical parameters of a battery pack; an electrochemical-thermal coupling model and a three-dimensional battery pack thermal-flow coupling model are constructed according to the obtained parameters, and the heat production rates of the single batteries at different temperatures and different multiplying powers are calculated according to the electrochemical-thermal coupling model; leading heat production rates at different temperatures and different multiplying powers into a three-dimensional battery pack heat-flow coupling model, and solving the three-dimensional battery pack heat-flow coupling model to obtain the overall temperature field distribution of the battery pack; monitoring the temperature of the battery pack based on the temperature field distribution, and calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the battery system; and when the maximum temperature difference of the monitoring body and the maximum temperature difference of the system are not in the corresponding design range, changing the design parameters.
Description
Technical Field
The invention relates to the technical field of batteries, in particular to a battery thermal management optimization method, a battery thermal management optimization device, a readable storage medium and computer equipment.
Background
Lithium ion power batteries are the core components of new energy automobiles, and the safety and cycle life of the lithium ion power batteries are continuously concerned by consumers. The power battery is used as a power source of the electric automobile, and when the temperature is generally within the range of 20-45 ℃, the power battery has the best charge and discharge performance, the best service life and the best safety. Therefore, the thermal management design of the battery pack is a key factor in controlling the safety and performance of the electric vehicle.
In the related art, thermal management of a battery pack is mainly based on optimization of an air cooling system on a macro scale. The influence of the property of the electric core material on the micro scale, the design of the single battery core and the like on the thermal management system of the battery pack is not considered in the optimization mode, and the existing optimization mode is relatively unilateral and has poor optimization effect.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a battery thermal management optimization method and apparatus, a readable storage medium, and a computer device, for solving the problem in the prior art that the optimization effect of a battery thermal management system is poor.
A method of optimizing thermal management of a battery, comprising:
acquiring thermophysical parameters, transmission performance parameters and design parameters of grouped materials of the single battery cells, and acquiring the structure and the thermophysical parameters of the battery pack;
constructing an electrochemical-thermal coupling model according to the acquired thermophysical parameters and design parameters of the single battery cell, and calculating the heat production rate of the single battery at different temperatures and different multiplying powers according to the electrochemical-thermal coupling model;
constructing a three-dimensional battery pack thermal-current coupling model according to the structure and thermophysical parameters of the battery pack;
leading heat production rates at different temperatures and different multiplying powers into the three-dimensional battery pack heat-flow coupling model as heat sources, and solving the three-dimensional battery pack heat-flow coupling model by using a finite element method to obtain the overall temperature field distribution of the battery pack;
carrying out temperature monitoring on a plurality of monitoring bodies preset in the battery pack based on the temperature field distribution, and calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the battery system;
and when the maximum temperature difference of any monitoring body or the maximum temperature difference of the system is not in the corresponding design range, changing any one of the thermal performance parameter and the transmission performance parameter of the material of the single battery cell, the design parameter of the single battery cell and the design parameter of the cooling system of the battery pack, and returning to execute the steps of obtaining the thermal physical property parameter, the transmission performance parameter and the design parameter of the grouped material of the single battery cell, and obtaining the structure and the thermal physical property parameter of the battery pack.
Further, the method for optimizing thermal management of a battery includes the steps of monitoring the temperature of a plurality of monitoring bodies preset in the battery pack based on the temperature field distribution, and calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the battery system, where the monitoring bodies include surfaces of individual electric cores, interiors of individual electric cores, and cold plate interfaces:
monitoring the temperature of each monitoring point on each monitoring body in the battery pack based on the temperature field distribution;
calculating the maximum temperature difference of the temperature change of each monitoring point on the current monitoring body, carrying out mean value calculation, and taking the value of the mean value calculation as the maximum temperature difference of the temperature change of the current monitoring body;
and monitoring each temperature point of the current monitoring body based on the temperature field distribution, carrying out extreme value calculation, and taking the value of the extreme value calculation as the maximum temperature difference of the battery system.
Further, in the method for optimizing thermal management of a battery, the thermophysical parameters of the grouped materials of the individual electric cores include: density, specific heat capacity and thermal conductivity and positive negative pole material entropy coefficient of heat, the unitized material transmission performance parameter of monomer electricity core includes: the electronic conductivity and ion diffusion rate of the anode and cathode materials, the open-circuit voltage and the ion diffusion rate of the electrolyte, and the design parameters of the monomer battery cell comprise: the battery pack comprises a positive electrode coating material, a negative electrode coating material, positive electrode material particle radius, an active material volume fraction, an electrolyte phase volume fraction, a battery cell serial-parallel number and a positive electrode current collector unilateral coating surface density, the structural parameters of the battery pack comprise the size of each component and the material attribute parameters of each component, the components of the battery pack comprise a single battery cell, foam, a liquid cooling plate, a mica sheet and a heat conduction aluminum plate, and the material attribute parameters comprise heat conductivity and specific heat capacity.
Further, in the above battery thermal management optimization method, the step of changing the design parameters of the cooling system of the battery pack includes:
the inlet water temperature, flow rate, water pump turn-on temperature and turn-off temperature were optimized by CFD simulation.
Further, in the method for optimizing thermal management of a battery, the step of constructing an electrochemical-thermal coupling model according to the obtained thermophysical parameters and design parameters of the cell includes:
according to the acquired thermophysical parameters and design parameters of the monomer battery cell, respectively establishing a mass conservation, an electronic charge and an ionic charge conservation of lithium ions in a solid-liquid phase, an electrochemical reaction kinetic equation of a solid-liquid interface, heat conduction generated inside the lithium ion battery and a convection and radiation heat dissipation model of the monomer surface.
An embodiment of the present invention further provides a battery thermal management optimization apparatus, including:
the acquisition module is used for acquiring the thermophysical property parameters, the transmission performance parameters and the design parameters of the grouped materials of the single battery cell, and acquiring the structure and the thermophysical property parameters of the battery pack;
the first model building module is used for building an electrochemical-thermal coupling model according to the acquired thermophysical parameters and design parameters of the single battery cell and calculating the heat production rate of the single battery at different temperatures and different multiplying powers according to the electrochemical-thermal coupling model;
the second model building module is used for building a three-dimensional battery pack thermal-current coupling model according to the structure and the thermophysical parameters of the battery pack;
the solving module is used for introducing heat production rates at different temperatures and different multiplying powers into the three-dimensional battery pack heat-flow coupling model as heat sources, and solving the three-dimensional battery pack heat-flow coupling model by using a finite element method so as to obtain the overall temperature field distribution of the battery pack;
the calculation module is used for monitoring the temperature of a plurality of monitoring bodies preset in the battery pack based on the temperature field distribution and calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the battery system;
and the modification module is used for changing any one of the thermal performance parameter and the transmission performance parameter of the material of the single battery cell, the design parameter of the single battery cell and the design parameter of the cooling system of the battery pack when the maximum temperature difference of any monitoring body or the maximum temperature difference of the system is not in the corresponding design range, and returning to execute the steps of obtaining the thermophysical property parameter, the transmission performance parameter and the design parameter of the grouped material of the single battery cell and obtaining the structure and the thermophysical property parameter of the battery pack.
Further, the above battery thermal management optimization apparatus, wherein the monitoring bodies include surfaces of individual electric cores, interiors of individual electric cores, and cold plate interfaces, the temperature monitoring is performed on a plurality of monitoring bodies preset in the battery pack based on the temperature field distribution, and the step of calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the battery system includes:
monitoring the temperature of each monitoring point on each monitoring body in the battery pack based on the temperature field distribution;
and calculating the maximum temperature difference of the temperature change of each monitoring point on the current monitoring body, calculating the mean value, and taking the value calculated by the mean value as the maximum temperature difference of the temperature change of the current monitoring body.
Further, in the above battery thermal management optimization apparatus, the step of changing the design parameters of the cooling system of the battery pack includes:
the inlet water temperature, flow rate, water pump turn-on temperature and turn-off temperature were optimized by CFD simulation.
An embodiment of the present invention further provides a readable storage medium, on which a program is stored, where the program, when executed by a processor, implements any of the methods described above.
An embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a program stored in the memory and executable on the processor, and when the processor executes the program, the method described in any one of the above is implemented.
The battery thermal management method based on the multi-scale simulation calculation converts the engineering problem of thermal management control of the battery pack into the mathematical problem, and provides a simple and quick method for controlling and optimizing the temperature field of the battery pack so as to improve the safety and the endurance mileage of the electric automobile.
Drawings
Fig. 1 is a flowchart of a battery thermal management optimization method according to a first embodiment of the present invention;
fig. 2 is a block diagram of a battery thermal management optimization apparatus according to a second embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
These and other aspects of embodiments of the invention will be apparent with reference to the following description and attached drawings. In the description and drawings, particular embodiments of the invention have been disclosed in detail as being indicative of some of the ways in which the principles of the embodiments of the invention may be practiced, 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 changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.
Referring to fig. 1, a method for optimizing thermal management of a battery according to a first embodiment of the present invention includes steps S11-S17.
Step S11, obtaining thermophysical parameters, transmission performance parameters, and design parameters of the grouped material of the individual battery cells, and obtaining the structure and thermophysical parameters of the battery pack.
Step S12, constructing an electrochemical-thermal coupling model according to the acquired thermophysical parameters and design parameters of the single battery cell, and calculating the heat production rate of the single battery at different temperatures and different multiplying powers according to the electrochemical-thermal coupling model.
The battery pack generally comprises a plurality of single battery cells, foam, a liquid cooling plate, a mica sheet, a heat conducting aluminum plate and a cooling system. The present embodiment is based first on analyzing and optimizing the performance of the various components of the battery pack on a micro-scale. Wherein, the thermophysical parameters of the grouped material of the monomer battery cell comprise: density, specific heat capacity and thermal conductivity and positive negative pole material entropy coefficient of heat, the unitized material transmission performance parameter of monomer electricity core includes: electron conductivity and ion diffusion rate of the anode and cathode materials, open circuit voltage, and ion diffusion rate of the electrolyte. The design parameters of the single battery cell comprise the thickness of the coating materials of the positive and negative electrodes, the particle radius of the positive and negative electrode materials, the volume fraction of the active materials, the volume fraction of the electrolyte phase, the serial-parallel number of the battery cell and the single-side coating surface density of the current collectors of the positive and negative electrodes.
Wherein, the thermal conductivity of the material can be obtained by calculation through a first linear principle phonon calculation method. The ion diffusion rate of the battery cell group anode and cathode materials can be calculated by adopting a first principle elastic band method to calculate the diffusion energy barrier of lithium ions in material crystal lattices, and the diffusion rate of the lithium ions in the anode and the cathode is obtained by the following formula:
D＝d2v0exp(-Ea/kBT)
in the formula, EaIs Li+Diffusion barrier, kBIs the Boltzmann constant, T is the Kelvin temperature, d is the lithium ion diffusion distance, v0Is the vibration frequency.
Based on thermophysical parameters and design parameters of the monomer battery cell, an electrochemical-thermal coupling model is constructed, which mainly comprises the following models:
the model comprises a mass conservation model of lithium ions in a solid-liquid phase, an electronic charge and ionic charge conservation model, a dynamic process model of electrochemical reaction of a solid-liquid interface, a heat conduction of heat generated in a lithium ion battery and a convection and radiation heat dissipation model of a monomer surface.
The mass conservation model expression of the lithium ion in the solid-liquid phase is as follows:
the expression of the electron charge and ion charge conservation model is as follows:
the solid-liquid interface electrochemical reaction dynamic process model expression is as follows:
the heat conduction of heat generated inside the lithium ion battery and the convection and radiation heat dissipation model expression of the monomer surface are as follows:
wherein c is the concentration of lithium ions, R is the radius of a reaction interface, epsilon is the volume fraction, t is the time, D is the diffusion coefficient, t + is the ion transport number, F is the Faraday constant, R isiIs the particle size of the electrode. Specifically, subscripts 1, 2, i in the above formula represent solid phase, liquid phase and different battery compositions, respectively; the superscript eff indicates that the Bruggeman correction is performed on the parameter, and the correction coefficient can be 1.5.
In the above formula, (1) (2) describes the mass conservation of lithium ions in the solid-liquid phase, respectively, (3) (4) describes the conservation of electron charges and ion charges, respectively, (5) (6) describes the electrochemical reaction kinetics process of the solid-liquid interface, and (7) (8) describes the heat conduction generated inside the lithium ion battery and the convection and radiation heat dissipation of the monomer surface, respectively.
In this step, the heat generation rate can be calculated by the following formula of the electrochemical-thermal coupling model:
wherein Q is a heat generation rate per unit time and volume of the battery, VbEffective volume calculation for the battery, I is the current flowing through the battery, U and U0Respectively, the measured voltage and the open-circuit voltage of the battery, T is the current temperature of the battery,
is the entropy thermal coefficient of the cell.
And step S13, constructing a three-dimensional battery pack thermal-flow coupling model according to the structure and the thermophysical parameters of the battery pack.
The structural parameters of the battery pack include the dimensions of the components and the material property parameters of the components. The battery pack comprises a single battery cell, foam, a liquid cooling plate, a mica sheet and a heat conduction aluminum plate, wherein the material attribute parameters comprise heat conductivity and specific heat capacity. In specific implementation, a three-dimensional heat flow coupling model of the battery pack can be established according to a finite element theory and a finite element method.
Step S14, heat production rates at different temperatures and different multiplying powers are used as heat sources to be led into the three-dimensional battery pack heat-flow coupling model, and the three-dimensional battery pack heat-flow coupling model is solved by using a finite element method to obtain the overall temperature field distribution of the battery pack;
step S15, carrying out temperature monitoring on a plurality of monitoring bodies preset in the battery pack based on the temperature field distribution, and calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the battery system;
and step S16, judging whether the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the system are both in the corresponding design range, if not, executing step S17, and returning to execute step S11.
Step S17, any one of the thermal performance parameter and the transmission performance parameter of the material of the individual electric core, the design parameter of the individual electric core, and the design parameter of the cooling system of the battery pack is changed.
The design parameters of the cooling system of the battery pack include a coolant inlet water temperature, an inlet flow rate, a maximum opening temperature, and a closing temperature.
The monitoring body comprises all single battery cores of a grouped battery pack and a cold plate interface. In specific implementation, several representative monitoring points can be selected on the monitoring body for temperature monitoring. The step of monitoring the temperature of a plurality of monitoring bodies preset in the battery pack based on the temperature field distribution and calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the battery system comprises the following steps:
monitoring the temperature of each monitoring point on each monitoring body in the battery pack based on the temperature field distribution;
calculating the maximum temperature difference of the temperature change of each monitoring point on the current monitoring body, carrying out mean value calculation, and taking the value of the mean value calculation as the maximum temperature difference of the temperature change of the current monitoring body;
and monitoring each temperature point of the current monitoring body based on the temperature field distribution, carrying out extreme value calculation, and taking the value of the extreme value calculation as the maximum temperature difference of the battery system.
The temperature field distribution is a dynamic temperature field which changes along with time, and the temperature of each point of the battery pack can be obtained through the temperature field distribution of the battery pack. According to the distribution of the temperature field of the battery pack and the temperature monitoring points, the maximum temperature change condition and the maximum temperature difference of the individual monitoring bodies of the battery pack can be calculated. And if the design range is within the design range, the thermal management requirement of the battery pack is met, and the iterative design is stopped. Otherwise, repeating the steps S11-S16 to carry out iterative design until the maximum temperature difference and the maximum temperature change of the final battery pack are within the design range.
In the embodiment, on a microscopic scale, properties such as an energy band structure, an electron state density, a phonon state density and the like of a main grouped material anode and cathode, an electrolyte and a diaphragm of a battery are calculated through a first principle calculation based on a density functional theory, the electron/ion conductivity, the specific heat capacity and the heat conductivity of the grouped material are calculated, the heat transport performance and the heat generation performance of the related grouped material are investigated, and the heat transport performance and the heat generation performance of the material are optimized through material modification means such as doping and surface coating of the material.
On a mesoscale, calculating the specific heat capacity, the thermal conductivity and the electronic/ionic conductivity of the obtained grouped material through a first principle, and constructing an electrochemical-thermal coupling monomer battery cell calculation model to obtain the temperature field distribution and the heat generation quantity of the monomer battery cell.
On a macroscopic scale, according to the temperature field distribution and the heat production quantity of the single battery cell, the module and Pack of the battery Pack are subjected to temperature field simulation and flow distribution of a cooling plate through Computational Fluid Dynamics (CFD) software, the thermal field and the flow field are coupled for calculation, the cooling effect of the liquid cooling on the battery Pack is inspected, and heat management strategies such as inlet water temperature, flow speed, water pump opening temperature and closing temperature are optimized through CFD simulation.
And (3) according to the related thermophysical parameters of the grouped materials calculated by the first principle, transmitting the parameters among different scales, programming the parameters on a Matlab software platform, establishing a gray prediction model, and managing and optimizing the temperature of the battery pack.
The battery thermal management method based on the multi-scale simulation calculation converts the engineering problem of thermal management control of the battery pack into the mathematical problem, and provides a simple and quick method for temperature field control and optimization of the battery pack so as to improve the safety and the endurance mileage of the electric vehicle.
Referring to fig. 2, a battery thermal management optimization apparatus according to a second embodiment of the present invention includes:
the acquisition module 10 is configured to acquire thermophysical parameters, transmission performance parameters, and design parameters of a grouped material of a single battery cell, and acquire a structure and thermophysical parameters of a battery pack;
the first model building module 20 is configured to build an electrochemical-thermal coupling model according to the acquired thermophysical parameters and design parameters of the individual battery cells, and calculate heat generation rates of the individual battery cells at different temperatures and at different multiplying powers according to the electrochemical-thermal coupling model;
the second model building module 30 is used for building a three-dimensional battery pack thermal-current coupling model according to the structure and the thermophysical parameters of the battery pack;
the solving module 40 is used for introducing heat production rates at different temperatures and different multiplying powers into the three-dimensional battery pack heat-flow coupling model as heat sources, and solving the three-dimensional battery pack heat-flow coupling model by using a finite element method to obtain the overall temperature field distribution of the battery pack;
the calculation module 50 is configured to perform temperature monitoring on a plurality of monitoring bodies preset in the battery pack based on the temperature field distribution, and calculate a maximum temperature difference of temperature change of each monitoring body and a maximum temperature difference of the battery system;
and a modifying module 60, configured to, when the maximum temperature difference of any one of the monitoring bodies or the maximum system temperature difference is not within the corresponding design range, modify any one of the thermal performance parameter and the transmission performance parameter of the material of the individual electrical cores, the design parameter of the individual electrical cores, and the design parameter of the cooling system of the battery pack, and return to the step of obtaining the thermophysical property parameter, the transmission performance parameter, and the design parameter of the grouped material of the individual electrical cores, and obtaining the structure and the thermophysical property parameter of the battery pack.
Further, the above battery thermal management optimization apparatus, wherein the monitoring bodies include surfaces of individual electric cores, interiors of individual electric cores, and cold plate interfaces, the temperature monitoring is performed on a plurality of monitoring bodies preset in the battery pack based on the temperature field distribution, and the step of calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the battery system includes:
monitoring the temperature of each monitoring point on each monitoring body in the battery pack based on the temperature field distribution;
and calculating the maximum temperature difference of the temperature change of each monitoring point on the current monitoring body, calculating the mean value, and taking the value calculated by the mean value as the maximum temperature difference of the temperature change of the current monitoring body.
Further, in the above battery thermal management optimization apparatus, the step of changing the design parameters of the cooling system of the battery pack includes:
the inlet water temperature, flow rate, water pump turn-on temperature and turn-off temperature were optimized by CFD simulation.
The implementation principle and the generated technical effect of the battery thermal management optimization device provided by the embodiment of the invention are the same as those of the method embodiment, and for brief description, no part of the embodiment of the device is mentioned, and reference may be made to the corresponding content in the method embodiment.
An embodiment of the present invention further provides a readable storage medium, on which a program is stored, where the program, when executed by a processor, implements any of the methods described above.
An embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a program stored in the memory and executable on the processor, and when the processor executes the program, the method described in any one of the above is implemented.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement 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). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can 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 should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean 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 invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. 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 above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A battery thermal management optimization method is characterized by comprising the following steps:
acquiring thermophysical parameters, transmission performance parameters and design parameters of grouped materials of the single battery cells, and acquiring the structure and the thermophysical parameters of the battery pack;
constructing an electrochemical-thermal coupling model according to the acquired thermophysical parameters, transmission performance parameters and design parameters of the single battery cell, and calculating the heat production rate of the single battery at different temperatures and different multiplying powers according to the electrochemical-thermal coupling model;
constructing a three-dimensional battery pack thermal-current coupling model according to the structure and thermophysical parameters of the battery pack;
leading heat production rates at different temperatures and different multiplying powers into the three-dimensional battery pack heat-flow coupling model as heat sources, and solving the three-dimensional battery pack heat-flow coupling model by using a finite element method to obtain the overall temperature field distribution of the battery pack;
carrying out temperature monitoring on a plurality of monitoring bodies preset in the battery pack based on the temperature field distribution, and calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the battery system;
and when the maximum temperature difference of any monitoring body or the maximum temperature difference of the system is not in the corresponding design range, changing any one of the thermal performance parameter and the transmission performance parameter of the material of the single battery cell, the design parameter of the single battery cell and the design parameter of the cooling system of the battery pack, and returning to execute the steps of obtaining the thermal physical property parameter, the transmission performance parameter and the design parameter of the grouped material of the single battery cell, and obtaining the structure and the thermal physical property parameter of the battery pack.
2. The battery thermal management optimization method of claim 1, wherein the monitoring bodies comprise surfaces of single cells, interiors of the single cells and cold plate interfaces, and the step of monitoring the temperatures of the plurality of monitoring bodies preset in the battery pack based on the temperature field distribution and calculating the maximum temperature difference of each temperature change of the monitoring bodies and the maximum temperature difference of the battery system comprises:
monitoring the temperature of each monitoring point on each monitoring body in the battery pack based on the temperature field distribution;
calculating the maximum temperature difference of the temperature change of each monitoring point on the current monitoring body, carrying out mean value calculation, and taking the value of the mean value calculation as the maximum temperature difference of the temperature change of the current monitoring body;
and monitoring each temperature point of the current monitoring body based on the temperature field distribution, carrying out extreme value calculation, and taking the value of the extreme value calculation as the maximum temperature difference of the battery system.
3. The battery thermal management optimization method of claim 1, wherein the thermophysical parameters of the battery cell pack material comprise: density, specific heat capacity and thermal conductivity and positive negative pole material entropy coefficient of heat, the unitized material transmission performance parameter of monomer electricity core includes: the electronic conductivity and ion diffusion rate of the anode and cathode materials, the open-circuit voltage and the ion diffusion rate of the electrolyte, and the design parameters of the monomer battery cell comprise: the battery pack comprises a positive electrode coating material, a negative electrode coating material, positive electrode material particle radius, an active material volume fraction, an electrolyte phase volume fraction, a battery cell serial-parallel number and a positive electrode current collector unilateral coating surface density, the structural parameters of the battery pack comprise the size of each component and the material attribute parameters of each component, the components of the battery pack comprise a single battery cell, foam, a liquid cooling plate, a mica sheet and a heat conduction aluminum plate, and the material attribute parameters comprise heat conductivity and specific heat capacity.
4. The battery thermal management optimization method of claim 1, wherein the step of modifying design parameters of a cooling system of the battery pack comprises:
the inlet water temperature, flow rate, water pump turn-on temperature and turn-off temperature were optimized by CFD simulation.
5. The battery thermal management optimization method of claim 1, wherein the step of constructing an electrochemical-thermal coupling model according to the obtained thermophysical property parameters, transmission performance parameters and design parameters of the cell units comprises:
according to the acquired thermophysical parameters, transmission performance parameters and design parameters of the monomer battery cell, respectively establishing a mass conservation, an electronic charge and ionic charge conservation of lithium ions in a solid-liquid phase, an electrochemical reaction kinetic equation of a solid-liquid interface, heat conduction generated inside the lithium ion battery and a convection and radiation heat dissipation model of the monomer surface.
6. A battery thermal management optimization apparatus, comprising:
the acquisition module is used for acquiring thermophysical parameters and transmission performance parameters of grouped materials of the single battery cell, acquiring design parameters of the single battery cell, and acquiring the structure and thermophysical parameters of the battery pack;
the first model building module is used for building an electrochemical-thermal coupling model according to the acquired thermophysical property parameters, transmission performance parameters and design parameters of the single battery cell and calculating the heat production rate of the single battery at different temperatures and different multiplying powers according to the electrochemical-thermal coupling model;
the second model building module is used for building a three-dimensional battery pack thermal-current coupling model according to the structure and the thermophysical parameters of the battery pack;
the solving module is used for introducing heat production rates at different temperatures and different multiplying powers into the three-dimensional battery pack heat-flow coupling model as heat sources, and solving the three-dimensional battery pack heat-flow coupling model by using a finite element method so as to obtain the overall temperature field distribution of the battery pack;
the calculation module is used for monitoring the temperature of a plurality of monitoring bodies preset in the battery pack based on the temperature field distribution and calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of a system;
and the modification module is used for changing any one of the thermal performance parameter and the transmission performance parameter of the material of the single battery cell, the design parameter of the single battery cell and the design parameter of the cooling system of the battery pack when the maximum temperature difference of any monitoring body is not in the corresponding design range, and returning to execute the steps of obtaining the thermophysical property parameter, the transmission performance parameter and the design parameter of the grouped material of the single battery cell, and obtaining the structure and the thermophysical property parameter of the battery pack.
7. The battery thermal management optimization apparatus of claim 6, wherein the monitoring bodies comprise surfaces of individual cells, interiors of the individual cells, and cold plate interfaces, and the step of monitoring the temperatures of the plurality of monitoring bodies preset in the battery pack based on the temperature field distribution and calculating the maximum temperature difference of the temperature change of each monitoring body and the maximum temperature difference of the system comprises:
monitoring the temperature of each monitoring point on each monitoring body in the battery pack based on the temperature field distribution;
calculating the maximum temperature difference of the temperature change of each monitoring point on the current monitoring body, carrying out mean value calculation, and taking the value of the mean value calculation as the maximum temperature difference of the temperature change of the current monitoring body;
and monitoring each temperature point of the current monitoring body based on the temperature field distribution, carrying out extreme value calculation, and taking the value of the extreme value calculation as the maximum temperature difference of the battery system.
8. The battery thermal management optimization apparatus of claim 6, wherein the step of modifying design parameters of a cooling system of the battery pack comprises:
the inlet water temperature, flow rate, water pump turn-on temperature and turn-off temperature were optimized by CFD simulation.
9. A readable storage medium on which a program is stored, which program, when executed by a processor, carries out the method according to any one of claims 1-5.
10. A computer device comprising a memory, a processor and a program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-5 when executing the program.
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