CN113794254A - Thermal management strategy configuration method and device, computer equipment and storage medium - Google Patents
Thermal management strategy configuration method and device, computer equipment and storage medium Download PDFInfo
- Publication number
- CN113794254A CN113794254A CN202111070539.0A CN202111070539A CN113794254A CN 113794254 A CN113794254 A CN 113794254A CN 202111070539 A CN202111070539 A CN 202111070539A CN 113794254 A CN113794254 A CN 113794254A
- Authority
- CN
- China
- Prior art keywords
- battery
- thermal management
- capacity
- management strategy
- temperature
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
- H02J7/0048—Detection of remaining charge capacity or state of charge [SOC]
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/60—Heating or cooling; Temperature control
- H01M10/61—Types of temperature control
- H01M10/613—Cooling or keeping cold
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/60—Heating or cooling; Temperature control
- H01M10/61—Types of temperature control
- H01M10/615—Heating or keeping warm
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/60—Heating or cooling; Temperature control
- H01M10/63—Control systems
- H01M10/633—Control systems characterised by algorithms, flow charts, software details or the like
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0029—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with safety or protection devices or circuits
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/007—Regulation of charging or discharging current or voltage
- H02J7/007188—Regulation of charging or discharging current or voltage the charge cycle being controlled or terminated in response to non-electric parameters
- H02J7/007192—Regulation of charging or discharging current or voltage the charge cycle being controlled or terminated in response to non-electric parameters in response to temperature
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Landscapes
- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Chemical & Material Sciences (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Electrochemistry (AREA)
- General Chemical & Material Sciences (AREA)
- Power Engineering (AREA)
- Automation & Control Theory (AREA)
- Secondary Cells (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
本发明实施例提供了一种热管理策略配置方法、装置、计算机设备和存储介质，该方法包括：获取用于在温度的维度下电池充电操作和/或放电操作时的热管理策略，按照热管理策略仿真电池在指定的应用场景中运行，以检测电池的运行数据。根据运行数据预测电池在多个时间周期中老化后、剩余的容量。若剩余的容量不符合预设的标准，则更新热管理策略。本发明通过比较预测得到的电池剩余容量和预设的标准，指导电池热管理策略的更新，摆脱了对人工经验的依赖，使热管理策略的制定更具有科学性，其中仿真运算的使用也使得本发明的计算过程简单，效率高。
Embodiments of the present invention provide a thermal management strategy configuration method, apparatus, computer equipment, and storage medium, the method comprising: acquiring a thermal management strategy for battery charging and/or discharging operations in the dimension of temperature, according to the thermal management strategy. The management strategy simulates the operation of the battery in the specified application scenario to detect the battery's operating data. Predict the remaining capacity of the battery after aging over multiple time periods based on operating data. If the remaining capacity does not meet the preset criteria, the thermal management strategy is updated. The invention guides the update of the battery thermal management strategy by comparing the predicted remaining capacity of the battery with the preset standard, gets rid of the dependence on manual experience, and makes the formulation of the thermal management strategy more scientific, and the use of the simulation operation also makes the The calculation process of the invention is simple and the efficiency is high.
Description
Technical Field
The embodiment of the invention relates to the technical field of batteries, in particular to a thermal management strategy configuration method and device, computer equipment and a storage medium.
Background
With the rapid development of electric vehicles, batteries are being paid attention to safety and use cost as components of electric vehicles. In order to keep the battery performance good and prolong the service life of the battery, a thermal management strategy arranged in a battery thermal management system is generally utilized, so that the battery can be kept at the optimal working temperature, and meanwhile, the temperature difference among battery modules is reduced, so that the environmental protection performance and the energy-saving effect of the whole vehicle are optimized, and the running safety, the driving comfort and the like of the vehicle are improved.
The current thermal management strategy applied to the battery is mainly to control the temperature of each battery module in the battery by a temperature sensor through a battery thermal management system, and when the temperature exceeds or is lower than a maximum temperature standard, a minimum temperature standard and a temperature difference standard preset during the charging or discharging of the battery, a liquid cooling device is used for heating or cooling the interior of the battery. However, the battery is an integral formed by a series of battery cells through certain electrical connection, the suitable working conditions of the battery can be changed continuously in the actual working process due to the working principle of telecommunication and the physical connection characteristics of copper bars, high-voltage wire harnesses and the like, the current thermal management strategy is adjusted usually manually, the manual adjustment is performed by depending on experience, the experience is usually wrong and leaked, the adaptation degree of the adjusted thermal management strategy and the suitable working conditions of the battery is poor, and the thermal management strategy with poorer quality in long-term use of the battery is poor, so that the safety of the battery is easy to cause problems, and the service life of the battery is shortened.
Disclosure of Invention
The embodiment of the invention provides a method and a device for configuring a thermal management strategy, computer equipment and a storage medium, which are used for solving the problems of unstable safety and short service life of a power battery caused by poor quality of a manually formulated thermal management strategy.
In a first aspect, an embodiment of the present invention provides a method for configuring a thermal management policy, including:
obtaining a thermal management strategy for battery charging operation and/or discharging operation under the dimension of temperature;
simulating the battery to run in a specified application scene according to the thermal management strategy so as to detect the running data of the battery;
predicting the residual capacity of the battery after aging in a plurality of time periods according to the operation data;
checking whether the residual capacity meets a preset standard;
and if not, updating the thermal management strategy.
In a second aspect, an embodiment of the present invention further provides a device for configuring a thermal management policy, including:
the thermal management strategy acquisition module is used for acquiring a thermal management strategy during battery charging operation and/or discharging operation under the temperature dimension;
the battery simulation module is used for simulating a battery running in a specified application scene according to a thermal management strategy so as to detect running data of the battery;
the battery capacity prediction module is used for predicting the residual capacity of the battery after aging in a plurality of time periods according to the operation data;
the battery capacity inspection module is used for inspecting whether the residual capacity after the battery is aged meets a preset standard or not, and if not, the battery capacity inspection module calls a thermal management strategy updating module;
and the thermal management strategy updating module is used for updating the thermal management strategy of the battery.
In a third aspect, an embodiment of the present invention further provides a computer device, where the computer device includes:
one or more processors;
a memory for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the thermal management policy configuration method of the first aspect.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the thermal management policy configuration method according to the first aspect.
According to the technical scheme provided by the invention, the thermal management strategy used for the battery charging operation and/or discharging operation under the temperature dimension is obtained, the battery is simulated to run in the specified application scene according to the thermal management strategy, so that the thermal management strategy designed in the simulation can meet the running requirement of the real battery, the residual capacity after the battery is aged in a plurality of time periods is predicted according to the running data, the influence of temperature difference on the battery aging is introduced, and the accuracy of the residual capacity prediction after the battery is aged is improved. The use of simulation operation also makes the calculation process of the invention simple and efficient. Meanwhile, the method guides the updating of the battery heat management strategy by comparing the predicted residual capacity of the battery with the preset standard, gets rid of the dependence on manual experience, and enables the formulation of the heat management strategy to be more scientific.
Drawings
Fig. 1A is a flowchart of a method for configuring a thermal management policy according to an embodiment of the present invention;
fig. 1B is a diagram illustrating an exemplary capacity fade of a battery according to an embodiment of the invention;
FIG. 1C is a graph illustrating an example of a modified battery capacity fade provided in accordance with an embodiment of the present invention;
fig. 2 is a flowchart of a method for configuring a thermal management policy according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a thermal management policy configuration apparatus according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a computer device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1A is a flowchart of a thermal management policy configuration method according to an embodiment of the present invention, where this embodiment is applicable to designing a thermal management policy condition for a battery, predicting remaining capacity of the battery by creating a simulation environment, and iteratively updating a thermal management policy according to a capacity prediction result in a loop, where the method may be executed by a thermal management policy configuration device, where the thermal management policy configuration device may be implemented by software and/or hardware, and may be configured in a computer device, where the method specifically includes the following steps:
The battery in this embodiment is a chemical power source, commonly referred to as a battery, and can directly convert energy released by chemical reaction of substances into electric energy. The battery can be a power battery, namely a battery for providing a power source for an electric automobile. The current power battery system technology presents the following trends and characteristics: 1) lithium ion batteries become the mainstream of power batteries, both pure electric vehicles and plug-in electric vehicles adopt the lithium ion batteries, and the power batteries of hybrid electric vehicles are also transited from nickel-hydrogen batteries to the lithium ion batteries; 2) compared with batteries for electronic products (digital products or electric tools, the same applies below), the power battery system for the vehicle has the characteristics of large size, grouping, modularization, more rigorous use conditions and the like. For example, the capacity of batteries for electronic products is mostly below 3Ah, and the capacity of power batteries for vehicles is mostly between 1550 Ah. The large-scale of the volume and the capacity increases the difficulty of battery management and safety guarantee. Most batteries for small electronic products are used singly, and the notebook computers are not used in groups but are 4-9. The power battery system for the vehicle is mostly used in a mixed mode of hundreds or even thousands of batteries, the performance and the reliability of the system depend on the weakest battery (short plate effect), the safety of the system depends on the most unstable battery (bottom plate effect), and therefore, the requirement on the consistency of the single batteries is much higher than that of the batteries for electronic products. On the other hand, the combined use of the batteries may also induce and accelerate the performance degradation of the weaker batteries, so that the original inconsistency of the batteries is continuously increased in use, thereby making the equalization circuit an essential component of the battery system, and the battery management system becomes more complicated. In order to facilitate layout, improve safety, increase universality and accelerate research and development processes, the power battery system for the vehicle basically adopts a modular design.
The battery management system is an important component of the power battery system of the electric automobile. On one hand, the method detects, collects and preliminarily calculates the real-time state parameters of the battery, and controls the on-off of a power supply loop according to the comparison relationship between a detection value and an allowable value. And on the other hand, the acquired key data is reported to the whole vehicle controller, and the instruction of the controller is received to coordinate with other systems on the vehicle. Different cell types often have different requirements for management systems.
Thermal management systems are included in the various subsystems of the battery management system because heat build-up is the most important cause of power system failure and safety hazards. The power battery generates a large amount of heat in use, and the battery temperature influences the operation, the cycle life, the charging acceptability, the power, the energy, the safety and the reliability of a power supply system. The influence of the temperature on the discharge performance of the battery directly reflects on the discharge capacity and the discharge voltage, the temperature is reduced, the internal resistance of the battery is increased, the electrochemical reaction speed is slowed down, the polarization internal resistance is rapidly increased, the discharge capacity and the discharge platform of the battery are reduced, and the output of the power and the energy of the battery is influenced. The effect of temperature on the charging performance of the battery is more pronounced. The obvious characteristic of the charging of the power battery under the low temperature condition at present is that the voltage rises rapidly, which brings about a plurality of problems, for example, when the lithium ion battery is charged at low temperature, the positive electrode lithium is extracted rapidly, the negative electrode lithium is embedded into the battery slowly, which causes the accumulation of lithium metal on the surface of the battery, generates dendrite, and causes the short circuit of the battery. Exemplarily, power batteries are used in groups in an electric automobile, certain temperature difference exists between the batteries due to temperature change, aging rates of electrolyte, electrodes and a partition plate can be accelerated due to high temperature, when the temperature difference of a battery pack is large, the aging rate of a high-temperature part is obviously higher than that of a low-temperature part, and physical property differences of different batteries in the battery pack are more and more obvious along with time accumulation, so that the consistency of the battery pack is damaged, and finally, the whole battery pack fails in advance.
Therefore, to achieve optimal performance and life of the battery requires temperature control of the battery pack within a range that provides thermal management of the battery, reduces uneven temperature distribution within the battery pack to avoid module-to-module imbalance, reduces battery performance decay rates, and eliminates the associated potential hazards.
The thermal management of the power battery is mainly realized through a battery thermal management system. The main functions of the thermal management system include: carry out effective heat dissipation when battery temperature is higher, prevent to produce the thermal runaway accident and preheat when battery temperature is lower, promote battery temperature, ensure charging, discharge performance and security under the low temperature. The temperature difference in the battery pack is reduced, the formation of local hot areas is inhibited, the battery at a high-temperature position is prevented from being attenuated too fast, and the service life of the whole battery pack is shortened.
Different battery thermal management systems are configured with different thermal management strategies, wherein the thermal management strategies refer to determining the active heating/radiating strength according to temperature distribution information and charging and discharging requirements in the battery pack, and determining the heating power, the radiating power, an upper limit value of the acceptable temperature in the battery, a lower limit value of the temperature and an allowable temperature difference range among modules in the battery.
And 102, simulating the battery to run in a specified application scene according to the thermal management strategy so as to detect the running data of the battery.
In this embodiment, after the thermal management policies during the battery charging operation and/or the battery discharging operation in the dimension of the temperature are obtained, the simulation software is used to simulate the operation of the batteries with the same thermal management policies in a specified scene, so as to obtain the operation data of the batteries. These operational data include data needed to predict the remaining capacity of the battery after aging over a number of time periods, including battery temperature, battery charge and discharge rate, battery depth of discharge and number of battery cycles, battery state of charge and battery calendar time, data needed to calculate temperature differences within the battery, and also the temperature change of each battery cell.
In this embodiment, the simulation software used for simulating the battery is AMESim, which is a complex system modeling simulation platform in the multidisciplinary field. A user can establish a complex multidisciplinary system model on the platform, and carry out simulation calculation and deep analysis on the basis, and can also research the steady-state and dynamic performance of any element or system on the platform. In the embodiment, after the electrochemical and thermal effects of the battery are analyzed, the battery unit simulation model can be built through AMESim. It is worth noting that Amesim can also establish a battery model with multi-level complexity based on different analysis targets, can simulate the charge-discharge transient characteristics of a battery system and the aging rule of a large time scale under different working condition boundaries, optimize a battery pack thermal management system and a charge-discharge strategy, and ensure that a design scheme is the same as an expected result before a physical test is performed.
And 103, predicting the residual capacity of the battery after aging in a plurality of time periods according to the operation data.
A rechargeable battery undergoes a charge and discharge cycle called a cycle or a cycle, and under repeated charge and discharge, the battery capacity gradually decreases, and this process is called the cycle aging of the battery. Generally, the number of charge and discharge cycles when the battery capacity drops to 60% or 80% of its rated capacity is referred to as the cycle life. The cycle aging of the battery is influenced by the design, manufacturing process and material performance degradation of the battery, and on the other hand, the cycle aging is also related to the influence of the external environment on the battery during the use process, such as the use environment, charge and discharge schedule and the like. The aging of the battery also comprises calendar aging besides cycle aging, the calendar aging corresponds to the calendar life of the battery, the calendar life refers to the period from the production date to the end of the life of the battery, and the period comprises different links such as laying aside, aging, high and low temperature, cycle, working condition simulation and the like by taking years as a metering unit. External factors of battery calendar life include temperature, state of charge, charge and discharge rate, degree cut-off voltage, and discharge window. The aging speed of the battery is high due to the existence of unstable factors in the electrolyte at high temperature, the performance of the battery is adversely affected by low-temperature charging, and the aging of the lithium ion battery is accelerated in the charging and discharging processes with different multiplying powers. In the embodiment, the residual capacity after the aging of the battery is predicted, the cyclic aging and calendar aging conditions of the battery are considered at the same time, and the prediction is performed according to data items related to the calculation of the cyclic aging and the calendar aging in the operation data.
In one embodiment of the present invention, step 103 comprises the steps of:
and step 1031, equating the operation data of the battery simulation to real operation data.
The equivalence of the operation data in this step includes equivalence of the temperature of the battery simulation to the true temperature. And calculating the root mean square of the current simulated by the battery, wherein the root mean square is equivalent to the real current. The number of simulated, cyclic charges and discharges in the battery is equivalent to the number of true depths of discharge. And (4) equating the simulated charge-discharge multiplying power in the battery to be real charge-discharge multiplying power. The simulated state of charge in the battery is equivalent to the true state of charge.
In this embodiment, the operating condition information of the simulated battery may be obtained according to an application scenario specified in the simulation process, so as to analyze the ambient temperature distribution of the battery system and the charge-discharge current distribution of the battery system, then the temperature and SOC variation condition of the battery system is calculated according to the thermal management strategy obtained in step 101 of this embodiment, and the equivalent processing of the temperature, the current and the cycle number is performed according to the operating condition running time and the calculation step length, for example, if the lifetime degradation of 8 years needs to be predicted, the output may be performed once according to 1 year, the calculation may be performed every 300 seconds, and the current within 300 seconds may be subjected to root mean square processing to perform the equivalent processing
The temperature in 300 seconds is equivalent to the initial temperature of 300 seconds, and the number of cycles in 300 seconds is equivalent to the number of 100% DOD cycles
i is the charging and discharging current of the battery, irms is the charging and discharging current of the battery after the rms processing, DOD indicates the discharging depth of the battery, Q indicates the battery capacity, and t2 is a period of time intercepted in the charging and discharging process of the battery, and the unit is second, for example, in this embodiment, 300 seconds can be selected as t2, and the rms calculation of the current within 300 seconds can be performed. Then substituting the equivalent value into the equation to utilize the multi-factor cyclic aging equationAnd predicting the residual capacity of the first year by using a multi-factor Hitachi aging equation to obtain a first sub-attenuation curve and a second sub-attenuation curve.
And step 1032, calculating the relation of the capacity of the battery to decay with time according to the real operation data to be used as a capacity decay curve.
In this step, the operation state related to the capacity fading of the battery is first distinguished, and in one embodiment of the present invention, how to distinguish the operation state may be by calculating a current root mean square value when the battery is in operation, determining the operation state as a cyclic charge and discharge state if the current root mean square value is not 0, and determining the operation state as a standing state if the current root mean square value is 0, thereby distinguishing the operation state of the battery.
If the battery is cyclically charged and discharged at a certain time, the cyclically charged and discharged state of the battery is used as a first operation state of the battery, and the relation of capacity attenuation along with time of the battery in the operation state is calculated by using real operation data related to the first operation state and is used as a first sub-attenuation curve. It should be understood that the cells in the battery have consistency, and the consistency refers to the consistency of each performance of each cell constituting the battery. Due to production and environment, a small error is generated on the performance consistency of the battery core, and the error directly influences the service life of the battery. Therefore, in the calculation of the battery life or capacity attenuation, the operation data of one cell is often selected to predict the attenuation of the whole battery, and the attenuation of the battery is usually predicted by starting from the cell with the highest temperature in the battery in the industry. Therefore, the calculation process of the battery capacity fading with time in this embodiment is first shown as establishing a single-factor cyclic aging equation of the battery cell according to the real operation data related to cyclic charge and discharge in the real operation data in this operation time, such as the battery temperature, the battery charge and discharge rate, the battery discharge depth, and the battery cycle number. The single-factor cyclic aging fitting equation takes the influence of two dimensions into consideration in this embodiment, and the influence of the battery temperature is expressed as:
on the other hand, the single-factor cyclic aging fitting equation is influenced by the charge and discharge rate of the battery and is represented as follows:
according to the established single-factor cyclic aging equation of the battery cell, a multi-factor cyclic aging equation of the battery cell can be established:
then, when the battery is in a static state within a certain operation time, the static state of the battery is used as a second operation state of the battery, and the relation of the content amount of the battery decaying along with the time at the operation time is calculated by using real operation data related to the second operation state and is used as a second sub-decay curve. The calculation process is represented by establishing a single-factor calendar aging equation for the battery cell based on the actual operating data and operating data related to the aging of the battery time, such as the battery temperature, the battery state of charge, and the battery calendar time of the battery. The single-factor calendar aging fitting equation takes the influence of two dimensions into consideration in the embodiment, and on one hand, the influence of the battery temperature is expressed as:
on the other hand, the single-factor calendar aging fitting equation is influenced by the charge state of the battery and is represented as follows:
according to the established single-factor calendar aging equation of the battery cell, a multi-factor calendar aging equation of the battery cell can be established:
and obtaining a multi-factor cyclic aging equation according to the obtained single-factor cyclic aging fitting equation and the single-factor calendar aging fitting equation, wherein the multi-factor calendar aging equation is obtained by fitting through a nonlinear regression method on the basis of the Arrhenius equation.
The arrhenius equation is expressed as:
where k is the rate constant, R is the molar gas constant, T is the temperature, EaFor apparent activation energy, A is a pre-exponential factor.
In the above calculation formula, Qloss1-1，Qloss1-2，Qloss1，Qloss2-1，Qloss2-2，Qloss2And the attenuation capacity of the battery is shown, N is the number of times of cyclic charging and discharging of the battery, T is the temperature of the battery, T1 is the time corresponding to the second running state of the battery, the unit is day, C is the charging and discharging multiplying power of the battery, SOC is the charge state of the battery, and N1-N20 and m1-m24 are hyper parameters.
And accumulating the first sub-attenuation curve and the second sub-attenuation curve to obtain the relation of the capacity of the battery with the time attenuation, and using the relation as a capacity attenuation curve.
In this embodiment, since the attenuation of the battery capacity is the accumulation of the attenuation caused by the cyclic charge and discharge of the battery during the operation time and the attenuation of the battery that is aged with time while the battery is standing during the operation time, the first sub-attenuation curve and the second sub-attenuation curve are added to obtain the capacity attenuation curve.
Illustratively, the capacity fade of the battery may be predicted for eight years from the equivalent data in step 1031. In the above equation, n1-n20 and m1-m24 are used as the super-parameters, which can be obtained through a plurality of experiments, and the super-parameter values in the present embodiment are obtained through experiments and are applied in the following equation for calculating the attenuation capacity of the battery. For example, the cyclic aging single factor equation behaves as:
the cyclic aging single-factor equation shows as follows under the influence of the battery charge-discharge rate dimension:
the calendar aging one-factor equation behaves on the one hand under the influence of temperature as:
the calendar aging single factor equation, on the other hand, behaves under the influence of battery state of charge as:
according to the obtained cyclic aging single-factor equation and the calendar aging single-factor equation, a multi-factor cyclic aging equation can be derived on the basis of an Arrhenius equation, and each coefficient of the multi-factor calendar aging equation is represented as:
when the life decay of 8 years needs to be predicted, equivalent processing of temperature, current and cycle number is carried out according to the working condition running time and the calculation step length, for example, output can be carried out once according to 1 year, calculation is carried out once every 300 seconds, the current within 300 seconds can be subjected to root mean square processing for equivalence, the temperature within 300 seconds is equivalent to the initial temperature of 300 seconds, and the cycle number within 300 seconds is equivalent to the cycle number under 100% DOD (dot over direct) cycle. And substituting parameters such as multiplying power, temperature, battery charge state and the like into a multi-factor cyclic aging equation and a multi-factor calendar aging equation to respectively obtain a first sub-attenuation curve and a second sub-attenuation curve, and accumulating the first sub-attenuation curve and the second sub-attenuation curve as the battery capacity attenuation is the accumulation of the capacity attenuation caused by cyclic aging and calendar aging to obtain the relation of the capacity attenuation rate of the battery along with the change of time, namely the capacity attenuation curve of the battery, as shown in fig. 1B, the vertical axis in fig. 1B is the battery capacity attenuation rate, the horizontal axis represents the time period, and the first capacity attenuation in fig. 1B represents the capacity attenuation condition of the battery obtained after the first sub-attenuation curve and the second sub-attenuation curve are accumulated.
Step 1033, query the capacity decay curve for the remaining capacity of the battery after aging over a plurality of time periods.
And according to the attenuation curve and the appointed aging elapsed time period, the residual capacity of the battery after aging in different time periods can be inquired. In the present embodiment, for example, the aged remaining capacity of the battery in the eighth year may be predicted from the above-described decay curve obtained by predicting the remaining capacity in the first year.
In another embodiment of the present invention, step 103 may comprise the steps of:
step 1034, the operation data of the battery simulation is equivalent to real operation data.
In this step, in addition to the equivalent operation data required in step 1031, the battery simulation temperature difference is also equivalent to a real temperature difference.
And 1035, calculating the relation of the battery capacity with the time attenuation according to the real operation data to be used as a capacity attenuation curve.
In step 1035, after the calculation process in step 1032 is executed, a temperature difference influence is also introduced, where the temperature difference in this embodiment refers to the inside of the battery, and because the heat-generating battery bodies are densely arranged, the heat is inevitably accumulated more in the middle area, and the edge area is less, so the temperatures of the monomers in the battery pack are not balanced, and a temperature difference, referred to as a temperature difference, is formed. The battery temperature difference has accelerated influence on the battery aging, mainly because the internal temperature difference of the power battery can influence the charge state of the power battery. When the internal temperature distribution of the battery pack inside the power battery is not uniform, different charging efficiencies will be caused, and due to the difference of the capacities of the batteries in the battery pack, a part of the batteries are easily overcharged, and accordingly, the part of the overcharged batteries are also easily over-discharged during the discharging process. After the power battery is subjected to multiple charge-discharge cycles, the performance difference between the batteries is larger and larger, and vicious cycles are caused. The performance degradation of the battery is manifested in that the chargeable amount of electricity is reduced, the heat generation is more serious, and the capacity of the battery is more rapidly attenuated. As mentioned above, the attenuation of the battery capacity is usually predicted from the attenuation of one battery cell in the battery, so that there is a large deviation from the actual attenuation of the battery capacity, because such an approach does not consider the acceleration of the system life caused by the system temperature difference. The introduction of the effect of temperature differences in the calculation of the capacity prediction may increase the accuracy of the capacity prediction. The temperature difference employed in this embodiment is the maximum temperature difference of the battery. The temperature difference of the battery is required to be obtained according to the temperature change condition of each battery cell, the highest temperature change curve and the lowest temperature change curve of each battery cell can be calculated after the temperature change condition of each battery cell is obtained through simulation, then the temperature difference change curve of each battery cell is obtained through calculation according to the highest temperature change curve and the lowest temperature change curve of each battery cell, and finally the maximum temperature difference of each battery cell can be obtained through calculation according to the temperature difference change curve.
Step 1036, calculating a correction coefficient according to the temperature difference.
In this embodiment, the correction coefficient is calculated according to the temperature difference, a preset mapping table needs to be queried first, and a mapping relationship between the temperature difference and the correction coefficient is recorded in the mapping table. The mapping relation recorded by the mapping table can be obtained through multiple experiments, and corresponding correction coefficients can be obtained according to the battery capacity attenuation condition under different battery temperature difference conditions in the experiments, so that the mapping table for recording the temperature difference and the correction coefficients is obtained. Then, according to the maximum temperature difference of the battery electric core obtained in the step 1035, a correction coefficient of the maximum temperature difference mapping can be inquired in the mapping table.
And step 1037, correcting the capacity fading curve by using the correction coefficient.
The process of correcting the capacity fading curve by using the correction coefficient is represented by multiplying the capacity fading curve by the searched correction coefficient to obtain a new corrected capacity fading curve, for example, when the capacity fading of the battery for 8 years needs to be predicted, the capacity fading curve corrected by using the correction coefficient is represented as shown in fig. 1C, it is to be understood that the vertical axis in fig. 1C is the battery capacity fading rate, the horizontal axis is the time period, and the second capacity fading in fig. 1C is the battery capacity fading represented by the capacity fading curve corrected by using the correction coefficient.
Step 1038, query the capacity decay curve for the capacity remaining after the battery's capacity has aged over a plurality of time periods.
After the influence of temperature difference is introduced, the residual capacity of the battery after aging in different time periods can be inquired according to the attenuation curve after the correction of the correction coefficient and the appointed time period after aging, and the temperature difference has accelerated influence on the capacity attenuation of the battery, so that the accuracy of the service life prediction of the battery system can be realized by correcting the capacity attenuation curve by using the temperature difference.
And 104, checking whether the residual capacity of the aged battery meets a preset standard, and if not, executing a step 105. In this embodiment, the predicted remaining capacity after the battery ages is compared with a preset standard, and it can be determined whether the remaining capacity after the battery ages meets the preset standard under the guidance of the current thermal management strategy, where the preset standard in this embodiment refers to the length of the service life of the battery required in the quality assurance standard of the battery. When the capacity of the battery is attenuated to below 70%, the service life of the battery is terminated, and whether the service life length of the battery meets the quality assurance standard of the battery or not can be calculated according to the aged residual capacity of the battery in the embodiment. In this embodiment, if it is checked that the remaining capacity after the battery aging meets the preset standard, it is determined that the battery configuration is actually obtained and input to a thermal management strategy used for calculating the remaining capacity after the battery aging in the simulation system.
And step 105, updating the thermal management strategy.
In this embodiment, the updating of the thermal management policy includes first exhausting the first threshold, the second threshold, and the target temperature difference range in the thermal management policy, and then updating the first threshold in the thermal management policy, that is, the upper limit value of the temperature of the battery during charging and discharging, according to different combinations of the three data of the first threshold, the second threshold, and the target temperature difference range that are exhausted. A second threshold in the thermal management strategy, i.e. a lower limit value for the temperature of the battery when charging and discharging, is updated. And updating a target temperature difference range in the thermal management strategy, wherein the target range is a range of temperature fluctuation of the battery during charging and discharging.
In an embodiment of the present invention, if it is checked that the remaining capacity meets the preset standard, the battery is configured with the thermal management policy, for example, in reality, it may be determined that the original thermal management policy of the real battery is not changed or it is determined that the battery is configured with an updated thermal management policy that enables the remaining capacity after aging of the battery to meet the preset standard. The configuration process is different according to different cooling modes of the battery thermal management system, for example, if the battery is cooled by adopting a liquid cooling method, the liquid cooling thermal management system is generally composed of a heater, a radiator, a water pump, a three-way valve and a fan, and a new thermal management strategy for the real battery is configured, the new thermal management strategy comprises the adjustment of the power of the heater, the power of the radiator, the flow rate of a water inlet and the like, so that the original thermal management strategy is adjusted, and the first threshold, the second threshold and the target temperature difference range in the original thermal management strategy are consistent with the first threshold, the second threshold and the target temperature difference range of the thermal management strategy which meets the preset standard after updating. According to the technical scheme provided by the invention, the thermal management strategy used for the battery charging operation and/or discharging operation under the temperature dimension is obtained, the battery is simulated to run in the specified application scene according to the thermal management strategy, so that the thermal management strategy designed in the simulation can meet the running requirement of the real battery, the residual capacity after the battery is aged in a plurality of time periods is predicted according to the running data, the influence of temperature difference on the battery aging is introduced, and the accuracy of the residual capacity prediction after the battery is aged is improved. The use of simulation operation also makes the calculation process of the invention simple, less time-consuming and high-efficiency. Meanwhile, the method guides the updating of the battery heat management strategy by comparing the predicted residual capacity of the battery with the preset standard, gets rid of the dependence on manual experience, and enables the formulation of the heat management strategy to be more scientific.
Example two
Fig. 2 is a flowchart of a thermal management policy configuration method according to a second embodiment of the present invention, where the step of the thermal management policy configuration method is analyzed in this embodiment, and the method further includes a corresponding operation after updating the thermal management policy, and specifically includes:
And step 203, predicting the residual capacity of the battery after aging in a plurality of time periods according to the operation data.
And step 206, simulating the battery to run in a specified application scene according to the updated thermal management strategy so as to detect the running data of the battery.
In this embodiment, the updating of the thermal management policy is a random combination of the values of the first threshold, the second threshold and the target temperature difference range in the thermal management policy after being changed, and it cannot be guaranteed that the updated thermal management policy can certainly make the attenuated capacity of the battery after aging in multiple cycles meet the preset standard, so after the thermal management policy is updated, the updated thermal management policy also needs to be verified again in the simulation software, because the first threshold, the second threshold and the target temperature difference range in the thermal management policy change compared with the initial thermal management policy, parameters in the battery thermal management policy, such as the first threshold, the second threshold and the target temperature difference range, can be adjusted in the simulation software, and the original specified application scenario is kept unchanged, the change situation in the simulation process is controlled, and then the simulation software is continuously used to simulate the battery to operate in the specified application scenario, and thus various operational data of the battery under the guidance of the updated thermal management strategy can be detected.
And step 207, predicting the residual capacity of the battery after aging in a plurality of time periods according to the operation data, checking whether the residual capacity meets a preset standard, if not, executing step 208, and if so, executing step 209.
In this embodiment, after the thermal management policy is updated, the updated thermal management policy guides the operation of the battery in the simulation software, and new operation data is generated. The aging condition of the battery under the guidance of the updated thermal management strategy can be calculated according to the new operating data, and the remaining capacity of the battery after aging in multiple time periods is predicted, the calculation method can refer to step 203, the predicted result needs to be compared with the preset standard again after the calculation result is obtained, whether the updated thermal management strategy can enable the capacity of the battery after aging in multiple periods to meet the preset standard or not is checked, and if the remaining capacity of the battery obtained through the verification according to the new operating data still cannot meet the preset standard under the guidance of the updated thermal management strategy, step 208 is executed. If it is verified that the battery aging condition can meet the predetermined standard under the guidance of the updated thermal management strategy, step 209 is executed.
And step 208, updating the thermal management strategy again until the remaining capacity is verified to meet the preset standard.
In this embodiment, under the guidance of the updated thermal management policy, if the attenuated capacity of the battery after aging in multiple cycles cannot meet the preset standard, the thermal management policy needs to be updated again, for example, the three related thresholds are continuously adjusted in the simulation software, then the operation returns to the execution step 202, the remaining capacity of the battery after aging in multiple time cycles under the guidance of the updated thermal management policy is calculated until the updated thermal management policy can make the attenuated capacity of the simulated battery after aging in multiple cycles meet the preset standard, and then the current updated thermal management policy can be configured on the battery in practice, where the thermal management policy can make the battery meet the preset standard.
Step 209 determines the updated thermal management policy for the battery configuration.
In this embodiment, when the simulation software guides the operation of the battery according to the updated thermal management policy, and the remaining capacity calculated according to the operation data meets the preset standard, it is determined that the updated thermal management policy is actually configured for the battery.
According to the technical scheme provided by the embodiment, the thermal management strategy is updated through loop iteration, the updated thermal management strategy is input into the simulation software again, the attenuated capacity of the battery guided by the updated thermal management strategy is calculated, an optimal thermal management strategy is found for use, the attenuated capacity of the battery after aging in a plurality of cycles can meet the thermal management strategy of a preset standard, and then the optimal thermal management strategy is actually configured on the battery, so that the battery operates in a better temperature environment, the safety is guaranteed, and the effects of maintaining the safety of the battery and prolonging the service life of the battery are achieved finally.
EXAMPLE III
Fig. 3 is a block diagram of a thermal management policy configuration apparatus according to a third embodiment of the present invention, where the apparatus may specifically include the following modules:
a thermal management policy obtaining module 310 is configured to obtain a thermal management policy for a battery charging operation and/or a battery discharging operation in a dimension of temperature.
And a battery simulation module 320, configured to simulate a battery operating in a specified application scenario according to the thermal management policy, so as to detect operating data of the battery.
A battery capacity prediction module 330, configured to predict, according to the operation data, a remaining capacity of the battery after aging in a plurality of time periods.
And the battery capacity checking module 340 is configured to check whether the remaining capacity after the battery ages meets a preset standard, and if not, invoke the thermal management policy updating module.
And a thermal management policy updating module 350, configured to update the thermal management policy of the battery.
In an embodiment of the present invention, the thermal management policy configuration apparatus further includes:
and the thermal management strategy determining module is used for determining to configure the thermal management strategy for the battery if the remaining capacity is checked to meet the preset standard.
In an embodiment of the present invention, the battery simulation module 320 is further configured to simulate the operation of the battery in a specified application scenario according to the updated thermal management policy, so as to detect the operation data of the battery;
the battery capacity prediction module 330 is further configured to predict, according to the operation data, a remaining capacity of the battery after aging in a plurality of time periods;
the battery capacity checking module 340 is further configured to check whether the remaining capacity meets a preset standard, and if not, invoke the thermal management policy updating module 350;
the thermal management policy updating module 350 is further configured to update the thermal management policy again until it is checked that the remaining capacity meets a preset standard.
In one embodiment of the invention, if yes, a thermal management policy determination module is invoked;
and the thermal management strategy determining module is also used for determining the updated thermal management strategy configured for the battery.
In one embodiment of the present invention, the battery capacity prediction module 330 includes:
the operation data equivalence module is used for enabling the operation data of the battery simulation to be equivalent to real operation data;
the capacity attenuation curve calculation module is used for calculating the relation of the capacity of the battery with the time attenuation according to the real operation data to be used as a capacity attenuation curve;
and the residual capacity query module is used for querying the residual capacity of the battery after the capacity of the battery is aged in a plurality of time periods in the capacity fading curve.
In one embodiment of the present invention, the operation data equivalence module includes:
the temperature equivalence module is used for enabling the temperature of the battery simulation to be equivalent to a real temperature;
the current equivalent module is used for calculating the root mean square of the current simulated by the battery, and the root mean square is equivalent to a real current;
and the discharge frequency equivalent module is used for equivalent the simulated and circulating charge and discharge frequency in the battery to the frequency of the real discharge depth.
In one embodiment of the present invention, the capacity fade curve calculation module includes:
an operation state distinguishing module for distinguishing an operation state related to capacity fade of the battery;
a first sub-attenuation curve calculation module, configured to, if the battery is cyclically charged and discharged during the operating time, use the cyclically charged and discharged state of the battery as a first operating state of the battery, and calculate, using the real operating data associated with the first operating state, a relationship of a content amount of the battery in the first operating state, which attenuates with time, as a first sub-attenuation curve;
a second sub-attenuation curve calculation module, configured to, if the battery is stationary within the operating time, use the stationary state of the battery as a second operating state of the battery, and calculate a relationship, with time, of a content amount of the battery in the second operating state, using the real operating data associated with the second operating state, as a second sub-attenuation curve;
and the sub-attenuation curve accumulation module is used for accumulating the first sub-attenuation curve and the second sub-attenuation curve to obtain the relation of the capacity of the battery decaying along with time, and the relation is used as a capacity attenuation curve.
In another embodiment of the present invention, the capacity fade curve calculation module includes:
a first sub-decay curve formula application module, configured to calculate a relation of capacity decay of the battery with time during the operation time as a first sub-decay curve by the following formula if the battery is cyclically charged and discharged during the operation time:
a second sub-decay curve formula application module, configured to, if the battery is stationary during the operating time, calculate a relation of capacity decay with time of the battery during the operating time as a second sub-decay curve by using the following formula:
in one embodiment of the present invention, the operation state distinguishing module includes:
the current root mean square calculation module is used for calculating a current root mean square value when the battery runs, if the current root mean square value is not 0, the cyclic charging and discharging state module is called, and if the current root mean square value is 0, the standing state module is called;
a cyclic charge and discharge state module for determining the operation state as a cyclic charge and discharge state;
and the standing state module is used for determining that the running state is a standing state.
In another embodiment of the present invention, the operation data equivalence module further includes:
and the temperature difference equivalent module is used for equivalent the temperature difference simulated by the battery into a real temperature difference.
In one embodiment of the present invention, the capacity fade curve calculation module includes:
the correction coefficient calculation module is used for calculating a correction coefficient according to the temperature difference;
and the capacity attenuation curve correction module is used for correcting the capacity attenuation curve by using the correction coefficient.
In one embodiment of the present invention, the correction coefficient calculation module includes:
the mapping table query module is used for querying a preset mapping table, and the mapping relation between the temperature difference and the correction coefficient is recorded in the mapping table;
the correction coefficient query module is used for querying the correction coefficient of the temperature difference mapping in the query table;
in one embodiment of the present invention, the capacity fade curve modification module includes:
and the correction coefficient application module is used for multiplying the capacity attenuation curve by the correction coefficient to obtain a new capacity attenuation curve.
In one embodiment of the invention, the thermal management policy update module 350 includes:
the first threshold updating module of the thermal management strategy is used for updating a first threshold in the thermal management strategy, wherein the first threshold is an upper limit value of the temperature of the battery during charging and discharging;
the second threshold updating module of the thermal management strategy is used for updating a second threshold in the thermal management strategy, and the first threshold is a lower limit value of the temperature of the battery during charging and discharging;
and the thermal management strategy temperature difference updating module is used for updating a target temperature difference range in the thermal management strategy, wherein the target range is the temperature fluctuation range of the battery during charging and discharging.
The thermal management policy configuration device provided by the embodiment of the invention can execute the thermal management policy configuration method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Example four
Fig. 4 is a schematic structural diagram of a computer device according to a fourth embodiment of the present invention. FIG. 4 illustrates a block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention. The computer device 12 shown in FIG. 4 is only one example and should not bring any limitations to the functionality or scope of use of embodiments of the present invention.
As shown in FIG. 4, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, and commonly referred to as a "hard drive"). Although not shown in FIG. 4, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The processing unit 16 executes programs stored in the system memory 28 to execute various functional applications and data processing, such as implementing a thermal management policy configuration method provided by an embodiment of the present invention.
EXAMPLE five
A fifth embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the thermal management policy configuration method, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.
A computer readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments illustrated herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (15)
1. A method for configuring a thermal management policy, comprising:
obtaining a thermal management strategy for battery charging operation and/or discharging operation under the dimension of temperature;
simulating the battery to run in a specified application scene according to the thermal management strategy so as to detect the running data of the battery;
predicting the capacity remaining after the battery is aged in a plurality of time periods according to the operation data;
checking whether the residual capacity meets a preset standard;
and if not, updating the thermal management strategy.
2. The thermal management policy configuration method of claim 1, further comprising: and if the remaining capacity is checked to meet a preset standard, determining to configure the thermal management strategy for the battery.
3. The method of claim 1, wherein after updating the thermal management policy, further comprising:
simulating the battery to run in a specified application scene according to the updated thermal management strategy so as to detect the running data of the battery;
predicting the residual capacity of the battery after aging in a plurality of time periods according to the operation data, and checking whether the residual capacity meets a preset standard;
and if not, updating the thermal management strategy again until the remaining capacity is checked to meet the preset standard.
4. The thermal management policy configuration method of claim 3, further comprising: and if so, determining to configure the updated thermal management strategy for the battery.
5. The thermal management strategy configuration method of any of claims 1 or 4, wherein predicting the capacity of the battery remaining after aging over a plurality of time periods based on the operational data comprises:
equating the operation data of the battery simulation to real operation data;
calculating the relation of the capacity of the battery with the time attenuation according to the real operation data to be used as a capacity attenuation curve;
querying the capacity decay curve for the capacity remaining after the capacity of the battery has aged over a plurality of time periods.
6. The method according to claim 5, wherein the equating the operating data of the battery simulation to real operating data comprises:
equating the battery simulated temperature to a true temperature;
calculating the root mean square of the current simulated by the battery, wherein the root mean square is equivalent to a real current;
and the times of simulated cyclic charge and discharge in the battery are equivalent to the times of the real discharge depth.
7. The method according to claim 5, wherein the calculating a relation of the capacity of the battery to decay with time according to the real operation data as a capacity decay curve comprises:
differentiating an operating state related to capacity fade of the battery;
using the battery cycle charge and discharge state as a first operating state of the battery, calculating the battery in the first operating state using the real operating data associated with the first operating state
The relation of the capacity attenuation along the time is used as a first sub-attenuation curve;
taking the battery resting state as a second operating state of the battery, and calculating the battery in the second operating state by using the real operating data related to the second operating state
The relation of the capacity attenuation along the time is used as a second sub-attenuation curve;
and accumulating the first sub-attenuation curve and the second sub-attenuation curve to obtain the relation of the capacity of the battery with the time attenuation, and using the relation as a capacity attenuation curve.
8. The method of claim 7, wherein the differentiating the operating state associated with the capacity fade of the battery comprises:
calculating the current root mean square value when the battery runs;
if the current root mean square value is not 0, determining that the running state is a cyclic charging and discharging state;
and if the current root mean square value is 0, determining that the running state is a standing state.
9. The method according to claim 7, wherein the accumulating the first sub-attenuation curve and the second sub-attenuation curve to obtain a relation of the capacity of the battery decaying with time as a capacity attenuation curve comprises:
if the battery is in the first operation state, calculating the relation of the capacity of the battery with the time decay in the operation time through the following formula to be used as a first sub-decay curve:
if the battery is in the second operation state, calculating the relation of the capacity of the battery with the time attenuation in the operation time through the following formula to be used as a second sub-attenuation curve:
wherein Q isloss1，Qloss2Representing the attenuated capacity of the battery, N is the number of times of cyclic charge and discharge of the battery, T is the temperature of the battery, T1 is the time corresponding to the second running state of the battery, C is the charge and discharge multiplying power of the battery, N1-N20 is a hyperparameter, and SOC is the SOCThe state of charge of the battery.
10. The thermal management policy configuration method of claim 5, wherein said operational data comprises a temperature difference, said method further comprising:
calculating a correction coefficient according to the temperature difference;
and correcting the capacity fading curve by using the correction coefficient.
11. The method according to claim 10, wherein calculating a correction factor based on the temperature difference comprises:
inquiring a preset mapping table, wherein the mapping relation between the temperature difference and the correction coefficient is recorded in the mapping table;
inquiring a correction coefficient of the temperature difference mapping in the lookup table;
the correcting the capacity attenuation curve by using the correction coefficient comprises the following steps:
and multiplying the capacity attenuation curve by the correction coefficient to obtain a new capacity attenuation curve.
12. The method of any of claims 1-11, wherein the updating the thermal management policy comprises:
updating a first threshold in the thermal management strategy, wherein the first threshold is an upper limit value of the temperature of the battery during charging and discharging;
updating a second threshold in the thermal management strategy, wherein the first threshold is a lower limit value of the temperature of the battery during charging and discharging;
and updating a target temperature difference range in the thermal management strategy, wherein the target range is a range of temperature fluctuation of the battery during charging and discharging.
13. A thermal management policy configuration apparatus, comprising:
the thermal management strategy acquisition module is used for acquiring a thermal management strategy during battery charging operation and/or discharging operation under the temperature dimension;
the battery simulation module is used for simulating a battery running in a specified application scene according to the thermal management strategy so as to detect running data of the battery;
the battery capacity prediction module is used for predicting the residual capacity of the battery after aging in a plurality of time periods according to the operation data;
the battery capacity inspection module is used for inspecting whether the residual capacity after the battery is aged meets a preset standard or not, and if not, the battery capacity inspection module calls a thermal management strategy updating module;
and the thermal management strategy updating module is used for updating the thermal management strategy of the battery.
14. A computer device, characterized in that the computer device comprises:
one or more processors;
a memory for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the thermal management policy configuration method of any of claims 1-12.
15. A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, implements a thermal management policy configuration method according to any one of claims 1-12.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111070539.0A CN113794254B (en) | 2021-09-13 | 2021-09-13 | A thermal management strategy configuration method, device, computer equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111070539.0A CN113794254B (en) | 2021-09-13 | 2021-09-13 | A thermal management strategy configuration method, device, computer equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113794254A true CN113794254A (en) | 2021-12-14 |
| CN113794254B CN113794254B (en) | 2023-09-01 |
Family
ID=79183151
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111070539.0A Active CN113794254B (en) | 2021-09-13 | 2021-09-13 | A thermal management strategy configuration method, device, computer equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113794254B (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114583738A (en) * | 2022-05-09 | 2022-06-03 | 西南交通大学 | A Balanced Control Method for Energy Storage System Considering Aging Rate |
| CN114996926A (en) * | 2022-05-25 | 2022-09-02 | 北京新能源汽车股份有限公司 | Battery system optimization method, device, equipment and storage medium for vehicle |
| CN115098963A (en) * | 2022-06-20 | 2022-09-23 | 青岛优云智联科技有限公司 | Simulation-based design method for simultaneous electricity utilization and utilization coefficients of battery cell capacity |
| CN115728658A (en) * | 2022-11-02 | 2023-03-03 | 欣旺达电动汽车电池有限公司 | Method for estimating aging degree of internal resistance of battery cell, electric vehicle and storage medium |
| CN117491899A (en) * | 2024-01-03 | 2024-02-02 | 强钧能源技术(深圳)有限公司 | Reliability diagnosis system of mobile energy storage power supply |
| WO2024037411A1 (en) * | 2022-08-19 | 2024-02-22 | 奇瑞汽车股份有限公司 | Thermal management method and device for battery pack |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105974326A (en) * | 2016-06-01 | 2016-09-28 | 华霆（合肥）动力技术有限公司 | Lithium battery service life pre-estimation method and device |
| US20180321324A1 (en) * | 2017-05-05 | 2018-11-08 | Texas Instruments Incorporated | Voltage based zero configuration battery management |
| CN109765491A (en) * | 2018-12-19 | 2019-05-17 | 深圳市比克动力电池有限公司 | The modification method of battery temperature and capacity, device and terminal device |
| CN109870659A (en) * | 2019-03-14 | 2019-06-11 | 燕山大学 | Lithium-ion battery state of health estimation method using sliding window optimization strategy |
| CN110764009A (en) * | 2019-10-31 | 2020-02-07 | 重庆长安新能源汽车科技有限公司 | Method for estimating battery pack circulation capacity and health state of electric automobile |
| CN111611750A (en) * | 2020-05-28 | 2020-09-01 | 北京理工大学 | A lithium-ion battery charging and thermal management method using digital twin technology |
-
2021
- 2021-09-13 CN CN202111070539.0A patent/CN113794254B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105974326A (en) * | 2016-06-01 | 2016-09-28 | 华霆（合肥）动力技术有限公司 | Lithium battery service life pre-estimation method and device |
| US20180321324A1 (en) * | 2017-05-05 | 2018-11-08 | Texas Instruments Incorporated | Voltage based zero configuration battery management |
| CN109765491A (en) * | 2018-12-19 | 2019-05-17 | 深圳市比克动力电池有限公司 | The modification method of battery temperature and capacity, device and terminal device |
| CN109870659A (en) * | 2019-03-14 | 2019-06-11 | 燕山大学 | Lithium-ion battery state of health estimation method using sliding window optimization strategy |
| CN110764009A (en) * | 2019-10-31 | 2020-02-07 | 重庆长安新能源汽车科技有限公司 | Method for estimating battery pack circulation capacity and health state of electric automobile |
| CN111611750A (en) * | 2020-05-28 | 2020-09-01 | 北京理工大学 | A lithium-ion battery charging and thermal management method using digital twin technology |
Non-Patent Citations (1)
| Title |
|---|
| LISA CALEARO: "Modeling of Battery Electric Vehicles for Degradation Studies", 《2019 54TH INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE》, pages 1 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114583738A (en) * | 2022-05-09 | 2022-06-03 | 西南交通大学 | A Balanced Control Method for Energy Storage System Considering Aging Rate |
| CN114583738B (en) * | 2022-05-09 | 2022-08-02 | 西南交通大学 | A Balanced Control Method for Energy Storage System Considering Aging Rate |
| CN114996926A (en) * | 2022-05-25 | 2022-09-02 | 北京新能源汽车股份有限公司 | Battery system optimization method, device, equipment and storage medium for vehicle |
| CN115098963A (en) * | 2022-06-20 | 2022-09-23 | 青岛优云智联科技有限公司 | Simulation-based design method for simultaneous electricity utilization and utilization coefficients of battery cell capacity |
| CN115098963B (en) * | 2022-06-20 | 2024-10-01 | 青岛优云智联科技有限公司 | Simulation-based design method for simultaneous use coefficient of battery cell capacity machine electricity utilization |
| WO2024037411A1 (en) * | 2022-08-19 | 2024-02-22 | 奇瑞汽车股份有限公司 | Thermal management method and device for battery pack |
| CN115728658A (en) * | 2022-11-02 | 2023-03-03 | 欣旺达电动汽车电池有限公司 | Method for estimating aging degree of internal resistance of battery cell, electric vehicle and storage medium |
| CN115728658B (en) * | 2022-11-02 | 2024-04-30 | 欣旺达动力科技股份有限公司 | Aging degree estimation method for internal resistance of battery cell, electric automobile and storage medium |
| CN117491899A (en) * | 2024-01-03 | 2024-02-02 | 强钧能源技术(深圳)有限公司 | Reliability diagnosis system of mobile energy storage power supply |
| CN117491899B (en) * | 2024-01-03 | 2024-04-12 | 强钧能源技术(深圳)有限公司 | Reliability diagnosis system of mobile energy storage power supply |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113794254B (en) | 2023-09-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113794254A (en) | Thermal management strategy configuration method and device, computer equipment and storage medium | |
| US11408942B2 (en) | Method for predicting service life of retired power battery | |
| Kong et al. | Fault diagnosis and quantitative analysis of micro-short circuits for lithium-ion batteries in battery packs | |
| CN109586373B (en) | Battery charging method and device | |
| CN112964991B (en) | Method for processing temperature information in battery, computer device and storage medium | |
| Yao et al. | Modeling of lithium-ion battery using MATLAB/simulink | |
| Torchio et al. | Lionsimba: a matlab framework based on a finite volume model suitable for li-ion battery design, simulation, and control | |
| Ganesan et al. | Physics based modeling of a series parallel battery pack for asymmetry analysis, predictive control and life extension | |
| Fan et al. | Simplified battery pack modeling considering inconsistency and evolution of current distribution | |
| Darcovich et al. | Coupled electrochemical and thermal battery models for thermal management of prismatic automotive cells | |
| Kim et al. | Cooling performance of thermal management system for lithium-ion batteries using two types of cold plate: Experiment and MATLAB/Simulink-Simscape simulation | |
| CN116699445B (en) | Capacity prediction method and system for battery energy storage system | |
| Binelo et al. | Mathematical modeling and parameter estimation of battery lifetime using a combined electrical model and a genetic algorithm | |
| Zhu et al. | An improved reliability assessment method for lithium-ion battery system considering imbalanced current and uneven cooling | |
| Qian et al. | On‐line equalization for lithium iron phosphate battery packs based on voltage threshold integral | |
| Wang et al. | Development of a one-dimensional thermal-electrochemical model of lithium ion battery | |
| CN115545335A (en) | Battery power comprehensive prediction method, device, equipment and storage medium | |
| KR20220016685A (en) | Method for simulating battery pack | |
| CN111308352A (en) | Method for estimating battery attenuation of lithium ions | |
| Zhang et al. | Critical review and analysis of available capacity estimation of LiFePO ₄ battery using Peukert's law: A case study | |
| Shi et al. | Study on the aging characteristics of Li-ion battery based on the electro-thermal and aging joint simulation platform | |
| CN115598542A (en) | Lithium ion battery heat production power prediction method | |
| CN118095032A (en) | Modeling and simulation analysis method for lithium iron phosphate battery based on digital twin | |
| CN114498857A (en) | Electrochemical device control method, electronic device and storage medium | |
| CN108199397B (en) | Configuration method and device of energy storage battery pack |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |