CN113158461A - Multi-objective optimization design method for vehicle-mounted lithium ion power battery pack thermal management system - Google Patents
Multi-objective optimization design method for vehicle-mounted lithium ion power battery pack thermal management system Download PDFInfo
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Abstract
The invention relates to a multi-objective optimization design method for a vehicle-mounted lithium ion power battery pack heat management system, which comprises the following steps of: step S1, determining design parameters of the battery pack thermal management system; s2, acquiring initial values and actual value ranges of various design parameters according to actual vehicle-mounted working conditions; step S3, performing representative sample extraction on the value domain space formed by each design parameter to obtain a plurality of preliminary design schemes; step S4, defining an optimization target; step S5, acquiring a mathematical model of the design parameters and the optimization target parameters; s6, constructing an optimized design mathematical model according to the design parameters, the optimized targets and the mathematical model of the design parameters and the optimized target parameters, and acquiring optimized target parameter values of each preliminary design scheme of the sample based on simulation and numerical calculation; and step S7, screening to obtain an optimal design scheme based on the balance among the optimization targets. Compared with the prior art, the method has the advantages of short research and development period, good design effect, low research and development cost and the like.
Description
Technical Field
The invention relates to the technical field of lithium ion power battery thermal management, in particular to a multi-objective optimization design method for a vehicle-mounted lithium ion power battery pack thermal management system.
Background
The lithium ion power battery is widely applied to electronic products, pure electric vehicles and hybrid electric vehicles by virtue of the characteristics of high energy density and the like. However, as the market demand continuously increases in the aspects of endurance mileage, charging speed and the like, the application scenarios under high-magnification working conditions such as rapid charging and the like are higher and higher. And the lithium ion power battery under the heavy current operating mode can produce heat rapidly, and the temperature inconsistency between the battery monomer in the battery package and even between the battery modules is more obvious. In order to control the temperature and the temperature difference of the lithium ion power battery pack within a proper working temperature range, the design of a vehicle-mounted battery thermal management system is more important, the problems of overheating, uneven temperature distribution and the like cannot be effectively solved by simply increasing the flow/speed of a coolant, and unnecessary cost is added to the aspects of power consumption, quality, volume and the like of the thermal management system, so that the optimal design of the lithium ion power battery pack carrying the thermal management system is more important.
At present, two main methods for optimally designing a battery pack based on a thermal management system are provided, namely, design aiming at a single arrangement mode of the battery pack and design and optimization of structure selection comparison of a flow channel, an air port and the like of the thermal management system of the battery pack.
For the improvement of the temperature control effect, most of the methods proposed at present adjust the flow rate/flow rate, and research results show that the temperature control effect reaches the peak value when the flow rate/flow rate is increased to a certain degree, and the temperature control effect cannot be further improved by continuously increasing the flow rate/flow rate.
In fact, the degree of optimization of the thermal management effect which can be achieved by adjusting the arrangement of the monomers in the battery pack is very limited; the battery pack volume is increased and the energy density is reduced only by increasing the distance between the battery monomers to improve the cooling effect, so that the market demand of the long endurance mileage of the future pure electric automobile is not facilitated.
The optimization design considering a single design parameter and a target parameter can achieve improvement of the thermal management effect in the target dimension, but is not beneficial to the overall performance optimization of the battery pack, and even brings further deterioration to the target parameter with an inverse relation. Therefore, how to comprehensively consider the overall performance and the economical multi-objective optimization design of the lithium ion power battery pack carrying the thermal management system becomes a technical problem to be solved in the field.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a multi-objective optimization design method for a vehicle-mounted lithium ion power battery pack thermal management system.
The purpose of the invention can be realized by the following technical scheme:
a multi-objective optimization design method for a vehicle-mounted lithium ion power battery pack heat management system is used for obtaining an optimal design scheme of the vehicle-mounted lithium ion power battery pack heat management system, and comprises the following steps:
step S1, determining design parameters of the battery pack thermal management system;
s2, acquiring initial values and actual value ranges of various design parameters according to actual vehicle-mounted working conditions;
step S3, performing representative sample extraction on the value domain space formed by each design parameter to obtain a plurality of preliminary design schemes;
step S4, defining an optimization target of the design of the heat management system of the vehicle-mounted lithium ion power battery pack;
step S5, acquiring a mathematical model of the design parameters and the optimization target parameters;
s6, constructing an optimized design mathematical model according to the design parameters, the optimized targets and the mathematical model of the design parameters and the optimized target parameters, and acquiring optimized target parameter values of each preliminary design scheme of the sample based on simulation and numerical calculation;
s7, screening to obtain an optimal design scheme based on balance among optimization targets;
and S8, verifying whether the error between the numerical calculation of the selected optimal design scheme and the experimental measurement value is within a set allowable range by experiments, if so, determining that the selected design scheme is effective, and if the error is overlarge, returning to the step S3.
In step S1, parameters affecting the thermal management effect and the system power consumption in the lithium-ion power battery pack are selected as design parameters of the battery pack thermal management system.
The design parameters of the battery pack heat management system are heat exchange medium parameters and structural parameters.
The parameters of the heat exchange medium comprise the flow in the liquid cooling plate and the wind speed of the fan in the management system, and the structural parameters comprise the monomer space, the monomer and cold cooling plate edge distance, the flow channel depth, the transverse width of the flow channel of the liquid cooling plate and the longitudinal width of the flow channel of the liquid cooling plate.
In step S4, for the heat transfer medium parameters, the optimization target of the design of the heat management system of the vehicle-mounted lithium ion power battery pack is the temperature control effect, the temperature distribution uniformity and the power consumption of the heat management system under the 3C high-rate discharge condition.
In step S6, the expression of the optimal design mathematical model is:
wherein Q is1、Q2、…、QnRespectively, flow in n liquid cooling plates, Q1max、Q2max…、QnmaxAnd Q1min、Q2min…、QnminRespectively corresponding to the upper and lower limits, T, of the flow in the n liquid cooling platesmax、TSD、PmaxThe maximum temperature of the battery pack, the standard deviation of the temperature of the battery pack and the maximum pressure of the thermal management system are respectively used as concrete embodiments of optimization targets, T and delta T, P are respectively set thresholds V and V corresponding to each targetamaxAnd VaminRespectively the wind speed V of the fan in the management systemaUpper and lower limits of fTmax、fTSD、fPmaxAnd the mathematical models respectively represent the design parameters and the optimization target parameters.
In step S4, the design optimization targets of the thermal management system for the vehicle-mounted lithium-ion power battery pack for the structural parameters are the temperature control effect, the temperature distribution uniformity, the power consumption, the volume and the weight of the thermal management system under the 2.5C fast charging condition.
In step S6, the expression of the optimal design mathematical model is:
wherein d is1,d2,…dnRespectively, the monomer spacing, sd1,sd2,…sdnRespectively, the edge distance W between the monomer and the liquid-cooled plateh1,Wh2,…WhnRespectively, the transverse width, W, of the flow passage of the liquid cooling platev1,Wv2,…WvnRespectively, longitudinal width, T, of the flow passage of the liquid cooling platehFor the channel depth, T, Δ T, P are respectively set thresholds, d, corresponding to each targetmax、dminRespectively, the upper and lower limits of the monomer spacing, sdmax、sdminRespectively the upper and lower limits of the edge distance between the monomer and the liquid cooling plate, Whmax、WhminRespectively the upper and lower limits of the transverse width of the flow passage of the liquid cooling plate, Wvmax、WvminRespectively, the upper and lower limits of the longitudinal width of the liquid cooling plate flow passage, Thmax、ThminRespectively, the upper and lower limits of the depth of the flow channel, fTmax、fTSD、fPmaxAnd the mathematical models respectively represent the design parameters and the optimization target parameters.
In step S7, the design parameter values corresponding to the preliminary design solutions are substituted into the optimized design mathematical model, and each objective function value is calculated and compared with the set objective function range, and if the requirements are met, the design parameter values are used as candidate design solutions.
In step S7, if the candidate design solution exceeds the set upper limit of the number, the range of the objective function is further narrowed to reduce the number of the candidate design solutions until the optimal design solution is obtained.
Compared with the prior art, the invention has the following advantages:
(1) the practicality is stronger: the design parameters defined by the invention are combined with simulation and numerical calculation to judge whether the design parameters are key influence parameters, and the parameter value range and the value precision take the selection standards in the production, manufacture, assembly and application of the actual battery pack into consideration;
(2) sample extraction is representative: the sampled sample covers each value section of a full set sample space formed by orthogonal design of design parameters;
(3) the calculation amount is effectively reduced: on the premise of ensuring that the sampled book has representativeness, the sampled book has no interval superposition, thereby avoiding unnecessary computing resource waste;
(4) the optimization target is more comprehensive: the optimization design provided by the invention needs to comprehensively consider all extreme working conditions (such as low temperature, quick charging, overheating environment and thermal runaway), and defines the temperature control effect, the temperature distribution uniformity, the power consumption of the thermal management system, the volume of the thermal management system and the weight of the thermal management system as optimization targets;
(5) and (3) combining a mathematical model support theory analysis: the mathematical model of the relationship between the design parameters and the target parameters, which is obtained in the optimization design, can be used for analyzing the influence trend and degree of each design parameter on each target parameter.
(6) The reliability of the preferred protocol was verified in combination with the experiment: the optimal scheme for balancing the optimization targets selected by the invention needs to be verified by experiments under various working conditions, and the reliability of the method can be proved only by ensuring that the error between the actual measured parameter value and the theoretical calculated value is within a certain range.
Drawings
FIG. 1 is a block flow diagram of the present invention.
Fig. 2 is a cloud diagram of the temperature distribution of a 18650 lithium iron phosphate battery pack under the effect of an initial thermal management system in example 1 of the invention.
Fig. 3 is a cloud view of a coolant pressure distribution in a flow passage according to an initial design of a liquid cooling plate in embodiment 1 of the present invention.
Fig. 4 is a cloud diagram of temperature distribution of a 18650 lithium iron phosphate battery pack under the effect of an optimal thermal management system in embodiment 1 of the invention.
Fig. 5 is a cloud view of the distribution of the cooling liquid pressure in the optimal liquid cooling plate flow passage in embodiment 1 of the present invention.
Fig. 6 is a schematic response surface diagram of an influence relationship between design parameters and target parameters of a thermal management system in embodiment 1 of the present invention.
Fig. 7 is a schematic diagram of sensitivity analysis of an influence relationship between design parameters and target parameters of the thermal management system in embodiment 1 of the present invention.
Fig. 8 is a schematic view of parameters of the width of the flow passage of the liquid cooling plate in embodiment 2 of the present invention.
Fig. 9 is a schematic diagram of sensitivity analysis of an influence relationship between design parameters and target parameters of the thermal management system in embodiment 2 of the present invention.
Fig. 10 is a cloud diagram of the temperature distribution of the square lithium ion power battery pack under the effect of the initial thermal management system in embodiment 2 of the invention.
Fig. 11 is a pressure distribution cloud chart of the initial design scheme of the liquid cooling plate in embodiment 2 of the present invention.
Fig. 12 is a cloud diagram of the temperature distribution of the square lithium ion power battery pack under the effect of the optimal thermal management system in embodiment 2 of the invention.
Fig. 13 is a pressure distribution cloud chart of an optimal design scheme of a liquid cooling plate in embodiment 2 of the present invention.
Fig. 14 is a response surface diagram illustrating an influence relationship between design parameters and target parameters of the thermal management system in embodiment 2 of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. Note that the following description of the embodiments is merely a substantial example, and the present invention is not intended to be limited to the application or the use thereof, and is not limited to the following embodiments.
The invention starts from two aspects of fluid medium and battery structure respectively, carries out parameter design on the vehicle-mounted lithium ion power battery pack thermal management system, integrates various factors, provides an efficient and comprehensive multi-objective optimization design technical scheme for the lithium ion power battery pack carrying the thermal management system, can improve the performance problem of the thermal management system which cannot be involved in a single optimization objective design method, effectively designs the efficient thermal management system which is more suitable for practical application, and has the advantages of short research and development period, good design effect, low research and development cost and the like.
Example 1
As shown in fig. 1 to 7, the embodiment provides a multi-objective optimization design method for a thermal management system of a vehicle-mounted lithium ion power battery pack, which includes the following steps:
step S1, defining design parameters of battery pack thermal management system (flow Q in each liquid cooling plate)1、Q2、Q3、Q4Fan wind speed V in thermal management systema)；
Step S2, defining initial values and actual value ranges of all parameters according to actual vehicle-mounted working conditions;
step S3, performing representative sample extraction on the value domain space formed by each design parameter;
step S4, defining an optimization target (temperature control effect, temperature distribution uniformity and power consumption of a thermal management system under a 3C high-rate discharge working condition);
step S5, constructing a mathematical model of the design parameters and the optimization target parameters;
s6, solving target parameters of each design scheme of the sample based on simulation and numerical calculation;
step S7, based on the balance among optimization targets, iteratively screening an optimal thermal management system design scheme;
step S8, verifying whether the error between the calculation of the selected optimal solution value and the experimental measurement value is within the allowable range through experiments, if so, the selected design solution is valid. If the error is too large, the process returns to step S3.
The specific introduction of each step is as follows:
and selecting key design parameters influencing the thermal management effect, the system power consumption and the like in the lithium ion power battery pack in the processes of the steps S1 to S2, and defining initial values and actual reachable value ranges of the parameters according to factors such as the energy density and the available space size of the actual battery pack of the electric automobile.
In the step S3, orthogonal design is carried out by considering the value ranges of the design parameters to obtain a multi-dimensional sample space, and a general sampling method is adopted to extract the design scheme samples, so that the selected samples are representative and the calculation workload of the computer numerical value can be effectively reduced.
In the step S4, extreme conditions (such as 3C discharge) need to be considered in the forced optimization design, and the temperature control effect, the temperature distribution uniformity, and the power consumption of the thermal management system are defined as optimization targets.
In step S5, a mathematical model of the optimal design function between the optimal target parameters and the design parameters is constructed.
In the step S7, all optimization objectives (temperature control effect, temperature distribution uniformity, and power consumption of the thermal management system) need to be considered comprehensively, rather than realizing a certain objective and neglecting realistic factors such as weight, volume, and economy of the system.
In the step S8, the optimized scheme is required to be verified to build a test battery pack and a system. And if the error between the repeated measured value and the expected value of the target parameter of the prototype under the specified working condition is in an allowable range, the reliability of the selected optimization scheme is proved.
by applying the multi-objective optimization design method, the comprehensive optimization of the battery pack temperature control effect, the temperature distribution uniformity and the power consumption of the thermal management system can be realized, and the limitation of the single-objective optimization design method of the thermal management system and the thermal management improvement effect are greatly improved. The power consumption can be effectively controlled on the premise of ensuring the heat management effect by optimizing the flow of the cooling liquid and the air speed of the fan.
Example 2
As shown in fig. 8 to 14, the present embodiment provides a multi-objective optimization design method for a thermal management system of a vehicle-mounted lithium-ion power battery pack, including the following steps:
step S1, defining design parameters (cell spacing d) of thermal management system of battery pack1、d2…d7Distance sd between single body and liquid cooling plate1、sd2Flow channelDepth ThTransverse width W of liquid cooling plate flow passageh1、Wh2…Wh6Longitudinal width W of liquid cooling plate flow passagev1、Wv2)；
Step S2, defining initial values and actual value ranges of all parameters according to actual vehicle-mounted working conditions;
step S3, performing representative sample extraction on the value domain space formed by each design parameter;
step S4, defining an optimization target (temperature control effect, temperature distribution uniformity and power consumption of a thermal management system under a 2.5C quick-charging working condition);
step S5, constructing a mathematical model of the design parameters and the optimization target parameters;
s6, solving target parameters of each design scheme of the sample based on simulation and numerical calculation;
step S7, based on the balance among optimization targets, iteratively screening an optimal thermal management system design scheme;
and S8, verifying whether the error between the calculation of the selected optimal scheme value and the experimental measurement value is in an allowable range through experiments, if so, determining that the selected design scheme is effective, and if the error is overlarge, returning to the S3 step.
And selecting key design parameters influencing the thermal management effect, the system power consumption and the like in the lithium ion power battery pack in the processes of the steps S1 to S2, and defining initial values and actual reachable value ranges of the parameters according to factors such as the energy density and the available space size of the actual battery pack of the electric automobile.
In the step S3, orthogonal design is carried out by considering the value ranges of the design parameters to obtain a multi-dimensional sample space, and a general sampling method is adopted to extract the design scheme samples, so that the selected samples are representative and the calculation workload of the computer numerical value can be effectively reduced.
In the step S4, the forced optimization design needs to consider the 2.5C fast charging condition, and the temperature control effect, the temperature distribution uniformity, and the power consumption of the thermal management system are defined as optimization targets.
In step S5, a mathematical model of the optimal design function between the optimal target parameters and the design parameters is constructed.
In the step S7, all optimization objectives (temperature control effect, temperature distribution uniformity, and power consumption of the thermal management system) need to be considered comprehensively, rather than realizing a certain objective and neglecting realistic factors such as weight, volume, and economy of the system.
In the step S8, the optimized scheme is required to be verified to build a test battery pack and a system. And if the error between the repeated measured value and the expected value of the target parameter of the prototype under the specified working condition is in an allowable range, the reliability of the selected optimization scheme is proved.
In this case with a spacing d of 7 monomers1、d2…d7Distance sd between single body and liquid cooling plate1、sd2Depth of flow channel ThTransverse width W of liquid cooling plate flow passageh1、Wh2…Wh6Longitudinal width W of liquid cooling plate flow passagev1、Wv2For design parameters, the maximum temperature of the battery pack, the standard deviation of the temperature of the battery pack and the maximum pressure of the thermal management system are taken as optimization targets, and an optimized design mathematical model is constructed as follows:
by applying the multi-objective optimization design method, the comprehensive optimization of the battery pack temperature control effect, the temperature distribution uniformity and the power consumption of the thermal management system can be realized, and the limitation of the single-objective optimization design method of the thermal management system and the thermal management improvement effect are greatly improved. The power consumption can be effectively controlled on the premise of ensuring the heat management effect by optimizing the flow of the cooling liquid. In addition, the optimization to battery monomer interval also can effectively control the volume of battery module.
The above embodiments are merely examples and do not limit the scope of the present invention. These embodiments may be implemented in other various manners, and various omissions, substitutions, and changes may be made without departing from the technical spirit of the present invention.
Claims (10)
1. A multi-objective optimization design method for a vehicle-mounted lithium ion power battery pack heat management system is used for obtaining an optimal design scheme for the vehicle-mounted lithium ion power battery pack heat management system, and is characterized by comprising the following steps:
step S1, determining design parameters of the battery pack thermal management system;
s2, acquiring initial values and actual value ranges of various design parameters according to actual vehicle-mounted working conditions;
step S3, performing representative sample extraction on the value domain space formed by each design parameter to obtain a plurality of preliminary design schemes;
step S4, defining an optimization target of the design of the heat management system of the vehicle-mounted lithium ion power battery pack;
step S5, acquiring a mathematical model of the design parameters and the optimization target parameters;
s6, constructing an optimized design mathematical model according to the design parameters, the optimized targets and the mathematical model of the design parameters and the optimized target parameters, and acquiring optimized target parameter values of each preliminary design scheme of the sample based on simulation and numerical calculation;
s7, screening to obtain an optimal design scheme based on balance among optimization targets;
and S8, verifying whether the error between the numerical calculation of the selected optimal design scheme and the experimental measurement value is within a set allowable range by experiments, if so, determining that the selected design scheme is effective, and if the error is overlarge, returning to the step S3.
2. The multi-objective optimization design method for the vehicle-mounted lithium ion power battery pack thermal management system according to claim 1, wherein in the step S1, parameters influencing the thermal management effect and the system power consumption in the lithium ion power battery pack are selected as design parameters of the battery pack thermal management system.
3. The multi-objective optimization design method for the vehicle-mounted lithium ion power battery pack heat management system according to claim 2, wherein the design parameters of the battery pack heat management system are heat exchange medium parameters and structure parameters.
4. The multi-objective optimization design method for the vehicle-mounted lithium ion power battery pack heat management system according to claim 3, wherein the heat exchange medium parameters comprise flow in the liquid cooling plate and fan wind speed in the management system, and the structural parameters comprise monomer spacing, monomer-to-cold plate edge distance, flow channel depth, transverse width of the flow channel of the liquid cooling plate and longitudinal width of the flow channel of the liquid cooling plate.
5. The multi-objective optimization design method for the vehicle-mounted lithium ion power battery pack heat management system according to claim 4, wherein in the step S4, for the heat exchange medium parameters, the optimization objectives of the design of the vehicle-mounted lithium ion power battery pack heat management system are temperature control effect, temperature distribution uniformity and power consumption of the heat management system under the condition of high-rate discharge.
6. The multi-objective optimization design method for the vehicle-mounted lithium ion power battery pack thermal management system according to claim 5, wherein in the step S6, the expression of the mathematical model for optimization design is as follows:
wherein Q is1、Q2、…、QnRespectively, flow in n liquid cooling plates, Q1max、Q2max…、QnmaxAnd Q1min、Q2min…、QnminRespectively corresponding to the upper and lower limits, T, of the flow in the n liquid cooling platesmax、TSD、PmaxThe maximum temperature of the battery pack, the standard deviation of the temperature of the battery pack and the maximum pressure of the thermal management system are respectively used as concrete embodiments of optimization targets, T and delta T, P are respectively set thresholds V and V corresponding to each targetamaxAnd VaminRespectively the wind speed V of the fan in the management systemaUpper and lower limits of fTmax、fTSD、fPmaxAnd the mathematical models respectively represent the design parameters and the optimization target parameters.
7. The multi-objective optimization design method for the vehicle-mounted lithium ion power battery pack thermal management system according to claim 3, wherein in the step S4, the design optimization objectives of the vehicle-mounted lithium ion power battery pack thermal management system for the structural parameters are temperature control effect, temperature distribution uniformity, power consumption, volume and weight of the thermal management system under the fast charging condition.
8. The multi-objective optimization design method for the vehicle-mounted lithium ion power battery pack thermal management system according to claim 7, wherein in the step S6, the expression of the mathematical model for optimization design is as follows:
wherein d is1,d2,…dnRespectively, the monomer spacing, sd1,sd2,…sdnRespectively, the edge distance W between the monomer and the liquid-cooled plateh1,Wh2,…WhnRespectively, the transverse width, W, of the flow passage of the liquid cooling platev1,Wv2,…WvnRespectively, longitudinal width, T, of the flow passage of the liquid cooling platehFor the channel depth, T, Δ T, P are respectively set thresholds, d, corresponding to each targetmax、dminRespectively, the upper and lower limits of the monomer spacing, sdmax、sdminRespectively the upper and lower limits of the edge distance between the monomer and the liquid cooling plate, Whmax、WhminRespectively the upper and lower limits of the transverse width of the flow passage of the liquid cooling plate, Wvmax、WvminRespectively, the upper and lower limits of the longitudinal width of the liquid cooling plate flow passage, Thmax、ThminRespectively, the upper and lower limits of the depth of the flow channel, fTmax、fTSD、fPmaxAnd the mathematical models respectively represent the design parameters and the optimization target parameters.
9. The multi-objective optimization design method for the vehicle-mounted lithium ion power battery pack thermal management system according to claim 1, wherein in step S7, the design parameter values corresponding to the preliminary design schemes are substituted into the mathematical model for optimization design, and the objective function values are calculated and compared with the set objective function range, and if the requirements are met, the objective function values are used as candidate design schemes.
10. The multi-objective optimization design method for the vehicle-mounted lithium ion power battery pack thermal management system according to claim 9, wherein in step S7, if the candidate design solution exceeds the set upper limit of the number, the number of the candidate design solutions is reduced by further narrowing the range of the objective function until the optimal design solution is obtained.
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