CN116381499A - Method and device for predicting multiple peak power performance parameters of storage battery - Google Patents
Method and device for predicting multiple peak power performance parameters of storage battery Download PDFInfo
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Abstract
The invention provides a method and a device for predicting multiple peak power performance parameters of a storage battery, which belong to the technical field of battery detection and comprise the following steps: constructing a peak power function of the target battery based on the charge voltage function of the target battery and a physical model of the target battery; determining a battery voltage function in the charging and discharging process of the target battery; based on the peak power function, the battery voltage function, and the battery state function of the target battery, a performance parameter of the target battery is predicted, the performance parameter including peak power or charge-discharge time. The method and the device for predicting the multiple peak power performance parameters of the storage battery provided by the invention can be used for carrying out lossless and accurate prediction on the performance parameters such as the maximum allowable power of the battery in each stage, can provide technical support for reducing the peak power detection workload, and the peak power in an actual battery management system, design, whole vehicle design, road-surfing and the like, and can be used for verifying reference basis for the experiment of system science.
Description
Technical Field
The invention relates to the technical field of battery detection, in particular to a method and a device for predicting multiple peak power performance parameters of a storage battery.
Background
With the development of new energy technology, the development of the electric automobile industry is rapid, the sales volume is rapidly increased, and secondary battery technologies such as lithium ion batteries and the like which are closely related to the development of the new energy technology are also becoming popular research directions. With the improvement of the requirements of high-rate and fast-charge technologies, the importance of the peak power of the battery is continuously improved, and the method has a wide application prospect.
In the actual driving process, the situation that the vehicle accelerates for a period of time and continues to accelerate after a short time is remained often occurs, and the prediction of the power in the stages has important significance on the whole vehicle design and the like.
However, no prediction method for the maximum allowable power for these phases has yet emerged.
Disclosure of Invention
The method and the device for predicting the multiple peak power performance parameters of the storage battery are used for solving the defect that the prior art does not have a prediction method for the maximum allowable power of the stage of accelerating for a period of time in advance and stopping for a short time and continuing accelerating, realizing nondestructive and accurate prediction of the performance parameters of the battery such as the maximum allowable power of each stage, providing technical support for reducing the detection workload of the peak power, providing technical support for the actual battery management system, design, whole vehicle design, road-surfing and the like of the peak power, and providing reference basis for experimental verification of system science.
The invention provides a method for predicting multiple peak power performance parameters of a storage battery, which comprises the following steps:
constructing a peak power function of a target battery based on a charge voltage function of the target battery and a physical model of the target battery; and determining a battery voltage function in the charging and discharging process of the target battery;
predicting a performance parameter of the target battery based on the peak power function, the battery voltage function, and the battery state function of the target battery, the performance parameter including peak power or charge-discharge time.
According to the method for predicting the multiple peak power performance parameters of the storage battery, before the peak power function of the target battery is constructed based on the charge voltage function of the target battery and the physical model of the target battery, the method further comprises the following steps:
determining voltage stability values of the sample battery under a plurality of different charge states;
fitting a charge voltage curve according to each charge state and the voltage stabilization value corresponding to each charge state;
and determining the charge voltage function according to the charge voltage curve.
According to the method for predicting the multiple peak power performance parameter of the storage battery, before predicting the performance parameter of the target battery based on the peak power function, the battery voltage function and the battery state function of the target battery, the method further comprises:
performing RPT test on a plurality of sample batteries based on the physical model of the target battery, and determining the relation between the internal resistance of the target battery and the temperature and the state of charge;
and constructing the battery state function according to the relation between the internal resistance of the target battery and the temperature and the state of charge.
According to the method for predicting the multiple peak power performance parameters of the storage battery, the peak power function of the target battery is constructed based on the charge voltage function of the target battery and the physical model of the target battery, and the method comprises the following steps:
based on a physical model of the target battery, determining the relation between the peak power and the state of charge of the target battery by utilizing a plurality of calculation modes of the discharge capacity within the preset charge-discharge time;
and constructing the peak power function according to the charge voltage function and the relation between the peak power and the charge state of the target battery.
According to the method for predicting the multiple peak power performance parameters of the storage battery, the determining of the battery voltage function in the charging and discharging process of the target battery comprises the following steps:
determining an initial charge state and a cut-off charge state of the target battery and an actual voltage at the time of charge and discharge cut-off in the process of discharging the target battery each time;
determining a cut-off voltage corresponding to each cut-off state of charge in the charge voltage function;
the battery voltage function is constructed according to each actual voltage and a cut-off voltage corresponding to each actual voltage.
According to the method for predicting multiple peak power performance parameters of a storage battery provided by the invention, the predicting the performance parameters of the target battery based on the peak power function, the battery voltage function and the battery state function of the target battery comprises the following steps:
constructing a peak discharge power charge-discharge time function of the target battery based on the peak power function, the battery voltage function and the battery state function of the target battery;
determining the charge and discharge time of the target battery according to the peak discharge power charge and discharge time function and the peak power; or alternatively, the first and second heat exchangers may be,
and determining the peak power of the target battery according to the peak discharge power charge-discharge time function and the charge-discharge time.
The invention also provides a device for predicting the multiple peak power performance parameters of the storage battery, which comprises the following steps:
the construction module is used for constructing a peak power function of the target battery based on a charge voltage function of the target battery and a physical model of the target battery; and determining a battery voltage function in the charging and discharging process of the target battery;
and the prediction module is used for predicting the performance parameter of the target battery based on the peak power function, the battery voltage function and the battery state function of the target battery, wherein the performance parameter comprises peak power or charge and discharge time.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the multi-peak power performance parameter prediction method of the storage battery.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a multi-peak power performance parameter prediction method for a battery as described in any of the above.
The invention also provides a computer program product comprising a computer program which when executed by a processor implements a method of predicting a multi-peak power performance parameter of a battery as described in any one of the above.
The method and the device for predicting the multiple peak power performance parameters of the storage battery provided by the invention have the advantages that the simple and effective peak power prediction model is constructed by establishing the relation function between the performance parameters of the battery and the easily-measured parameters such as voltage, charge quantity and the like, so that the maximum allowable power and other performance parameters of the battery in each stage are predicted nondestructively and accurately, the technical support can be provided for reducing the peak power detection workload, and the peak power can be provided for the actual battery management system, design, whole vehicle design, road-surfing and the like, and the reference basis is verified for the experiment of the system science.
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In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for predicting multiple peak power performance parameters of a storage battery according to the present invention;
FIG. 2 is a second flow chart of a method for predicting multiple peak power performance parameters of a battery according to the present invention;
FIG. 3 is a schematic diagram of a device for predicting multiple peak power performance parameters of a storage battery according to the present invention;
fig. 4 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The prior art can realize online estimation of the maximum allowable power, but the required initial parameters are more, and the model is more complex.
The battery Power State (SOP) is the limit Power which can be input and output by the battery in different states, the parameter reflects the bearing capacity Of the battery to the charge and discharge Power, and the method has important significance in the aspects Of reasonably using the battery, avoiding abuse phenomena such as overcharge and overdischarge, evaluating the service life Of the battery, furthest exerting the vehicle braking energy recovery capacity and the like.
Hybrid pulse power performance (Hybrid Pulse Power Characteristic, HPPC) testing, JEVS method (Japan Electric Vehicle Society), and electric car battery test procedure manual (Electric Vehicle Battery Test Procedures Manual) are three main mainstream detection methods that do not result in peak power values that are actually true peak power.
The actual intrinsic peak power can be detected by a constant power method, but the method needs to test power values for a plurality of times, and a large amount of manpower and material resources are consumed for each test, so that the performance of the battery per se can be damaged in the repeated test process, and the detection efficiency is low.
If the battery peak power can be accurately predicted through various parameters of the battery, the practical application value of the method can be greatly improved, and the detection efficiency can be greatly improved.
The current peak power prediction method comprises a power calculation method based on State Of Charge (SOC) change Of a new generation automobile partner project (Partnership for a New Generation Of Vehicles, PNGV) composite pulse method, and the like, and has certain defects, or is too simple to consider, has insufficient accuracy, or is relatively complex in using model, is not suitable for basic prediction before detection, cannot directly predict the maximum allowable power in the continuous repeated charging and discharging process, has insufficient reference meaning for the design Of the whole automobile, and has insufficient practicability.
The invention provides a continuous repeated peak power prediction method based on easily-measured parameters, instantaneous voltage and resistance change conditions, which can realize the prediction method of peak power in different states.
The following describes a method and an apparatus for predicting multiple peak power performance parameters of a battery according to embodiments of the present invention with reference to fig. 1 to 4.
Fig. 1 is a flow chart of a method for predicting multiple peak power performance parameters of a storage battery according to the present invention, as shown in fig. 1, including but not limited to the following steps:
firstly, in step S1, constructing a peak power function of a target battery based on a charge voltage function of the target battery and a physical model of the target battery; and determining a battery voltage function during charging and discharging of the target battery.
The target battery may be a lithium ion battery.
In the process of modeling the battery, the battery can be equivalent to a physical model of an ideal voltage source U and a resistor R in series, wherein the resistor R is the internal resistance of the battery.
Optionally, before the constructing the peak power function of the target battery based on the charge voltage function of the target battery and the physical model of the target battery, the method further includes:
determining voltage stability values of the sample battery under a plurality of different charge states;
fitting a charge voltage curve according to each charge state and the voltage stabilization value corresponding to each charge state;
and determining the charge voltage function according to the charge voltage curve.
The sample battery can be the same model or the same batch as the target battery, and has the same parameters and properties.
First, each sample cell was charged in accordance with the charging method defined by the sample cell, and after the sample cell was fully charged, the sample cell was allowed to stand for 2 hours, so that the voltage of the sample cell was stabilized.
Second, the sample cell is charged with current I 1 Discharging to 5% of the measured discharge capacity, namely 5% SOC, standing for 2 hours, measuring and recording a voltage stabilization value OCV after voltage stabilization, repeatedly discharging the sample battery with current, and performing I 1 Discharging until 5% of the measured discharge capacity, standing for 2 hours, recording the measured voltage stability value OCV until the sample battery is discharged, and measuring the voltage stability values OCV under a plurality of SOCs; wherein I is 1 The discharge capacity of the sample cell was numerically equal.
Here, state Of Charge (SOC) = (remaining amount/rated amount) ×100%; voltage stability value ocv=open circuit voltage (Open Circuit Voltage, OCV).
Then, according to the detected voltage stability value OCV under each SOC, fitting an SOC-OCV curve by adopting modes such as polynomial fitting or exponential fitting and the like, and further obtaining a charge voltage function corresponding to the batch of batteries: soc=h (OCV), and ocv=f (SOC).
According to the method for predicting the multiple peak power performance parameters of the storage battery, disclosed by the invention, before the actual detection of the battery, the established lithium ion single battery is utilized to charge and discharge for a certain time, after the battery is stood for a short time, the battery with the same parameters and properties is utilized to conduct a charge and discharge measurement experiment, so that the relation curve of the capacity and the voltage of the battery batch is fitted, a charge voltage function is obtained, and a basis is provided for the accurate prediction of the performance parameters of the lithium ion battery in different states.
Optionally, the constructing the peak power function of the target battery based on the charge voltage function of the target battery and the physical model of the target battery includes:
based on a physical model of the target battery, determining the relation between the peak power and the state of charge of the target battery by utilizing a plurality of calculation modes of the discharge capacity within the preset charge-discharge time;
and constructing the peak power function according to the charge voltage function and the relation between the peak power and the charge state of the target battery.
After obtaining the charge voltage function, constructing a peak power function of the target battery based on a physical model U-R of the target battery, wherein the charge voltage function soc=h (OCV) of the target battery:
wherein, P is peak power, unit: a tile (W); u is the average voltage of the target battery in the charge and discharge process; t is t 1 The charge and discharge time of the target battery; OCV (optical clear video) 1 At the initial SOC for the target battery 1 A corresponding open circuit voltage; u (U) aim To require a cut-off voltage, units: volt (V); cap is the actual capacity of battery calibration, unit: amp Hour (AH); SOC (State of Charge) 1 For initial state of charge of battery, SOC 1 ＝h(OCV 1 )。
The peak power P may be a constant value of the target battery in a certain state, and may vary according to the SOC.
According to the method for predicting the multiple peak power performance parameters of the storage battery, provided by the invention, the change conditions of the battery voltage and the resistance in the charge and discharge process are fully considered, and compared with a single parameter prediction model, the accuracy is higher, and the reliability is better; the method can also be combined with the actual running condition of the whole vehicle, the easily-measured parameters (OCV, R and the like) of the battery are considered, the maximum power allowed in the continuous and repeated charging and discharging process of the battery is explored, reference is provided for the design of the output power of the whole vehicle, namely, the change condition of voltage and resistance after the battery is charged and discharged is combined, and the obtained peak power model is used. And obtaining the maximum power allowed by the batch of batteries in the continuous multi-time charge and discharge process.
Optionally, the determining the battery voltage function during the charging and discharging of the target battery includes:
determining an initial charge state and a cut-off charge state of the target battery and an actual voltage at the time of charge and discharge cut-off in the process of discharging the target battery each time;
determining a cut-off voltage corresponding to each cut-off state of charge in the charge voltage function;
the battery voltage function is constructed according to each actual voltage and a cut-off voltage corresponding to each actual voltage.
On the other hand, the target battery was charged and left standing, and then the target battery was charged and discharged to conduct a change prediction study of OCV.
For example, after discharging the battery, the SOC is changed from the initial state of charge SOC 1 Becomes the cut-off state of charge SOC 2 Respectively corresponding to the initial voltage OCV in the stable state 1 And cut-off voltage OCV 2 Considering that the battery is in an unstable state when left standing for a short time, the SOC 2 The state can be reached rapidly, but the value of the voltage OCV gradually rises along with the time, and cannot rise to the state of SOC in a short time 2 Corresponding cut-off voltage OCV 2 Wherein, OCV 2 Can be used forAccording to SOC 2 Directly obtained in the charge voltage function and recorded in a certain standing time t 2 The detected actual voltage achievable by the internal OCV is OCV 3 . After discharge the voltage rebounds for a certain time t 2 After that, but not yet stable, the OCV value at the time of continuous discharge was recorded as OCV 3 This time t 2 Is determined according to actual needs, such as the time interval between two accelerator pedal steps of the automobile.
Note Δocv=ocv 2 -OCV 3 Based on all measured voltages OCV 3 And cut-off voltage OCV 2 Constructing a battery voltage function in the discharging process of the target battery, wherein the battery voltage function is specifically as follows:
ΔOCV＝k(I，R，t 2 )；
i is average current in the charging and discharging process of the target battery; r is the internal resistance of the target battery; t is t 2 Is the rest time period of the target battery after the charge and discharge are stopped.
According to the multi-peak power performance parameter prediction method of the storage battery, provided by the invention, by constructing a relation function between theoretical voltage and actually measured voltage of the storage battery after charging and discharging, taking the influences of polarized voltage and polarized internal resistance into consideration, accurate modeling of the battery voltage can be realized by utilizing the mathematical relation between actual SOC and actual OCV and theoretical OCV, and the maximum power allowed in the continuous multi-charging and discharging process of the same batch of batteries is predicted, explored and corrected by combining the established peak power prediction model of the same batch of batteries, so that a foundation is provided for the performance parameter prediction of a target battery.
Optionally, before predicting the performance parameter of the target battery based on the peak power function, the battery voltage function, and the battery state function of the target battery, the method further comprises:
performing RPT test on a plurality of sample batteries based on the physical model of the target battery, and determining the relation between the internal resistance of the target battery and the temperature and the state of charge;
and constructing the battery state function according to the relation between the internal resistance of the target battery and the temperature and the state of charge.
And (3) carrying out reasonable performance testers (Rational Performance Tester, RPT) on the plurality of sample batteries to obtain a plurality of groups of DC resistance, temperature and SOC data of the sample batteries.
From each set of dc resistance, temperature, and SOC data, a relationship between the dc internal resistance R and the temperature T, SOC of the target battery can be determined.
According to the relation between the direct current internal resistance R and the temperature T, SOC of the sample battery, a battery state function is constructed as follows:
R＝g(SOC，T)；
wherein R is the direct current resistance of the target battery; t is the temperature of the target battery in degrees Celsius (C); the SOC is the state of charge of the target battery.
According to the method for predicting the multiple peak power performance parameters of the storage battery, the internal resistances of the storage battery under different SOC are combined, and the storage battery is charged and discharged for a short time and is kept stand for voltage. The complex model is reduced, the relation between the charge and discharge current and the easily-measured parameters (current voltage, cut-off voltage, charge and discharge time) and the like is established by skillfully utilizing different calculation modes of the discharge capacity, so that the accurate prediction method of the actual intrinsic peak power of different SOC batteries is established under a multi-parameter system, and powerful theory and data support are provided for battery detection, BMS design, whole vehicle design and the like.
Further, in step S2, a performance parameter of the target battery is predicted based on the peak power function, the battery voltage function, and the battery state function of the target battery, the performance parameter including peak power or charge-discharge time.
Substituting the battery voltage function and the battery state function into the peak power function can obtain the relation between the peak power and the charge and discharge time of the target battery, and further can obtain the charge and discharge time through the known peak power or obtain the peak power through the known charge and discharge time.
Optionally, the predicting the performance parameter of the target battery based on the peak power function, the battery voltage function, and the battery state function of the target battery includes:
constructing a peak discharge power charge-discharge time function of the target battery based on the peak power function, the battery voltage function and the battery state function of the target battery;
determining the charge and discharge time of the target battery according to the peak discharge power charge and discharge time function and the peak power; or alternatively, the first and second heat exchangers may be,
and determining the peak power of the target battery according to the peak discharge power charge-discharge time function and the charge-discharge time.
Specifically, by utilizing the charge and discharge characteristics of the lithium ion battery, the voltage and internal resistance of the battery change in the process of short standing, and the actual OCV after the battery is charged and discharged and the short standing 3 ＝OCV 2 Δocv and battery state function r=g (SOC, T) are substituted into the peak power function of the battery
In the method, a multi-parameter model of a peak discharge power charge-discharge time function can be obtained, and the performance parameters are converted into the expression of the easy-to-measure parameters, so that the method is simple and practical, and specifically comprises the following steps:
(P，t 1 )＝h(SOC，R)＝h[f(OCV)，g(T)]；
can obtain a certain charge-discharge time t according to the peak power-charge-discharge time function 1 Internal peak power prediction, or maximum charge and discharge and minimum charge and discharge time prediction achievable at a certain discharge power.
The method for predicting the multiple peak power performance parameters of the storage battery provided by the invention constructs a simple and effective peak power prediction model by establishing a relation function between the performance parameters of the battery and easy-to-measure parameters such as voltage, charge quantity and the like, thereby carrying out nondestructive prediction on the performance of the battery, providing technical support for reducing the workload of peak power detection, and providing technical support for the peak power in an actual battery management system (Battery Management System, BMS), design, whole vehicle design, road-surfing and the like, and providing a reference basis for experimental verification of system science.
Fig. 2 is a second flow chart of a method for predicting multiple peak power performance parameters of a storage battery according to the present invention, as shown in fig. 2, including:
the same batch of batteries are subjected to activation and capacity calibration tests, so that the consistency of basic parameters and basic properties of the same batch of batteries is ensured, and the reliability of subsequent data fitting and data verification is improved;
three sample batteries with consistent basic properties are selected to establish a simplified physical model of the lithium ion battery, the physical model is formed by connecting an ideal voltage source OCV and a direct current resistor R in series, wherein R is the internal resistance of the battery, the battery is subjected to SOC-OCV test, and the OCV is measured once when the SOC is reduced by 5%, and the specific test method is as follows:
firstly, each sample battery is charged according to a charging mode specified by the sample battery, and the sample battery is kept stand for 2 hours after being fully charged;
second, the sample cell is charged with current I 1 Discharging to 5% of the measured discharge capacity, standing for 2 hr, measuring and recording voltage stabilization value OCV after voltage stabilization, repeatedly discharging sample cell with current, and collecting the sample cell 1 Discharging until 5% of the measured discharge capacity, standing for 2 hours, recording the measured OCV value until the sample battery is discharged, and measuring the OCV values under a plurality of SOCs; wherein I is 1 The discharge capacity of the sample cell was numerically equal.
Then, according to the detected OCV data under each SOC, fitting an SOC-OCV curve by adopting modes such as polynomial fitting or exponential fitting and the like, and further obtaining a charge voltage function corresponding to the batch of batteries: soc=h (OCV), and ocv=f (SOC).
The three sample batteries are used for RPT test, so that the relationship between the direct current internal resistance R and the temperature T, SOC is obtained, and the relationship is a battery state function: r=g (SOC, T).
And obtaining a corresponding calculation formula and verifying. Data fitting relation curve fitting degree r 2 Not less than 0.99, and the verification error of the detection data must not exceed 10%. Wherein, the fitting degree of the linear regression is used for measuring the fitting degree of the data of the linear regression prediction and the real data, and r is used for measuring the fitting degree of the data of the linear regression prediction 2 R represents 2 The closer to 1, the better the fitting degree, i.e. the better the linear regression model。
Under different SOC states, the relation between P, T and OCV, temperature T is explored, and the peak power function of the battery between the peak power P and the easy-to-measure parameters SOC, R and the like is established by utilizing different calculation modes of discharge capacity within a certain charge and discharge time T:
wherein, P is peak power, unit: a tile (W); u is the average voltage of the target battery in the charge and discharge process; t is the charge and discharge time of the target battery; OCV (optical clear video) 1 At the initial SOC for the target battery 1 A corresponding open circuit voltage; u (U) aim To require a cut-off voltage, units: volt (V); cap is the actual capacity of battery calibration, unit: amp Hour (AH); SOC (State of Charge) 1 The initial state of charge of the battery;
the average voltage U in the charge and discharge process is a value to be adjusted in the experiment, the internal resistance R is a value to be determined in the experiment, and the peak power P is a solution value.
And determining whether the selection of U is proper according to whether the actually measured peak power is consistent with the predicted peak power in the peak power function of the battery. The actually measured peak power can be determined according to a constant power detection method, namely the actual intrinsic peak power, and is more accurate and has practical reference and application significance compared with other detection methods.
And under a certain temperature condition, such as 25+/-2 ℃, charging and standing the target battery, and discharging the target battery to perform OCV change prediction research. For example, after the battery is discharged, the SOC state is changed from SOC 1 Becomes SOC 2 Corresponds to OCV respectively in stable state 1 And OCV (optical clear video) 2 。
Considering that the battery is in an unstable state when left standing for a short time, the SOC 2 The state can be reached quickly, and the value of OCV gradually rises along with the time, but cannot rise to the state of SOC in a short time 2 Corresponding OCV 2 Wherein, OCV 2 Can be according to SOC 2 In charge voltage functionDirectly obtaining, recording at a certain standing time t 2 The detection voltage which can be achieved by the internal OCV is OCV 3 。
Note Δocv=ocv 2 -OCV 3 In the actual detection process, the delta OCV and charge-discharge current, the internal resistance (ohmic internal resistance, polarized internal resistance) of the battery and the standing time t can be determined by precisely monitoring the change of the OCV in the standing time after charge-discharge by shortening the sampling time 2 And the like.
And fitting the experimentally measured data to obtain a battery voltage function:
ΔOCV＝k(I，R，t 2 )；
i is average current in the charging and discharging process of the target battery; r is the internal resistance of the target battery; t is t 2 Is the rest time period of the target battery after the charge and discharge are stopped.
Next, the battery voltage function is verified.
Finally, the battery is charged and discharged for a short time and then is kept still for actual OCV 3 ＝OCV 2 The substitution of Δocv into the peak power function of the battery, the peak discharge power charge-discharge time function is obtained as follows:
(P，t 1 )＝h(SOC，R)＝h[f(OCV)，g(T)]；
can obtain a certain charge-discharge time t according to the peak power-charge-discharge time function 1 Internal peak power prediction, or maximum charge and discharge and minimum charge and discharge time prediction achievable at a certain discharge power. The mathematical model required by the peak power-charge-discharge time function is relatively simple, the parameters are easy to obtain, and the method can be applied to a computing system with low calculation force.
According to the method for predicting the multiple peak power performance parameters of the storage battery, provided by the invention, mathematical model fitting is carried out on the relation between the state of charge (SOC) and the voltage (U) of the storage battery, the change condition of the internal resistance (R), the polarization voltage change condition in the standing process and the like; the method has the advantages that the method utilizes a simplified physical model, combines a certain battery discharge capacity, takes power, voltage, internal resistance and the like as initial conditions, establishes an equation and solves the equation, verifies and adjusts the maximum allowable power through an actual test, can be used for predicting the maximum allowable power in continuous multiple acceleration and continuous multiple rapid charging processes, realizes rapid and accurate prediction of the maximum power state in the continuous multiple charging and discharging processes of the lithium ion battery, can greatly save time and labor cost of a constant power detection method, overcomes the difficulty that the constant power detection method for actual peak power consumes a large amount of manpower and material resources, predicts the maximum allowable power in the continuous multiple charging and discharging processes under the condition of reducing damage to battery performance as much as possible, ensures the speed and accuracy of measurement, provides good theoretical technical support for design of the output power of the whole vehicle and control of power in the actual whole vehicle operation process, and has important significance for vehicle enterprises and battery detection industry.
The multi-peak power performance parameter prediction device of the storage battery provided by the invention is described below, and the multi-peak power performance parameter prediction device of the storage battery described below and the multi-peak power performance parameter prediction method of the storage battery described above can be correspondingly referred to each other.
Fig. 3 is a schematic structural diagram of a multi-peak power performance parameter prediction apparatus for a storage battery according to the present invention, as shown in fig. 3, including:
a construction module 301, configured to construct a peak power function of a target battery based on a charge voltage function of the target battery and a physical model of the target battery; and determining a battery voltage function in the charging and discharging process of the target battery;
a prediction module 302, configured to predict a performance parameter of the target battery based on the peak power function, the battery voltage function, and the battery state function of the target battery, where the performance parameter includes peak power or charge-discharge time.
During operation of the device, the construction module 301 constructs a peak power function of the target battery based on a charge voltage function of the target battery and a physical model of the target battery; and determining a battery voltage function in the charging and discharging process of the target battery; the prediction module 302 predicts a performance parameter of the target battery based on the peak power function, the battery voltage function, and the battery state function of the target battery, the performance parameter including peak power or charge-discharge time.
The multiple peak power performance parameter prediction device of the storage battery provided by the invention constructs a simple and effective peak power prediction model by establishing a relation function between the performance parameter of the battery and easy-to-measure parameters such as voltage, charge quantity and the like, thereby carrying out nondestructive prediction on the performance of the battery, providing technical support for reducing the workload of peak power detection, and providing the peak power in an actual battery management system, design, whole vehicle design, road and the like, and verifying reference basis for experiments of system science.
Fig. 4 is a schematic structural diagram of an electronic device according to the present invention, as shown in fig. 4, the electronic device may include: processor 410, communication interface (Communications Interface) 420, memory 430 and communication bus 440, wherein processor 410, communication interface 420 and memory 430 communicate with each other via communication bus 440. Processor 410 may invoke logic instructions in memory 430 to perform a battery multi-peak power performance parameter prediction method comprising: constructing a peak power function of a target battery based on a charge voltage function of the target battery and a physical model of the target battery; and determining a battery voltage function in the charging and discharging process of the target battery; predicting a performance parameter of the target battery based on the peak power function, the battery voltage function, and the battery state function of the target battery, the performance parameter including peak power or charge-discharge time.
Further, the logic instructions in the memory 430 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product including a computer program, the computer program being storable on a non-transitory computer readable storage medium, the computer program, when executed by a processor, being capable of executing a method for predicting multiple peak power performance parameters of a battery provided by the above methods, the method comprising: constructing a peak power function of a target battery based on a charge voltage function of the target battery and a physical model of the target battery; and determining a battery voltage function in the charging and discharging process of the target battery; predicting a performance parameter of the target battery based on the peak power function, the battery voltage function, and the battery state function of the target battery, the performance parameter including peak power or charge-discharge time.
In yet another aspect, the present invention provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform a method of predicting multiple peak power performance parameters of a battery provided by the above methods, the method comprising: constructing a peak power function of a target battery based on a charge voltage function of the target battery and a physical model of the target battery; and determining a battery voltage function in the charging and discharging process of the target battery; predicting a performance parameter of the target battery based on the peak power function, the battery voltage function, and the battery state function of the target battery, the performance parameter including peak power or charge-discharge time.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for predicting multiple peak power performance parameters of a battery, comprising:
constructing a peak power function of a target battery based on a charge voltage function of the target battery and a physical model of the target battery; and determining a battery voltage function in the charging and discharging process of the target battery;
predicting a performance parameter of the target battery based on the peak power function, the battery voltage function, and the battery state function of the target battery, the performance parameter including peak power or charge-discharge time.
2. The method for predicting multiple peak power performance parameters of a battery according to claim 1, further comprising, before said constructing a peak power function of said target battery based on a charge voltage function of said target battery and a physical model of said target battery:
determining voltage stability values of the sample battery under a plurality of different charge states;
fitting a charge voltage curve according to each charge state and the voltage stabilization value corresponding to each charge state;
and determining the charge voltage function according to the charge voltage curve.
3. The method for predicting multiple peak power performance parameters of a battery according to claim 1, further comprising, before said predicting performance parameters of said target battery based on said peak power function, said battery voltage function, and a battery state function of said target battery:
performing RPT test on a plurality of sample batteries based on the physical model of the target battery, and determining the relation between the internal resistance of the target battery and the temperature and the state of charge;
and constructing the battery state function according to the relation between the internal resistance of the target battery and the temperature and the state of charge.
4. The method of claim 1, wherein constructing the peak power function of the target battery based on the charge voltage function of the target battery and the physical model of the target battery comprises:
based on a physical model of the target battery, determining the relation between the peak power and the state of charge of the target battery by utilizing a plurality of calculation modes of the discharge capacity within the preset charge-discharge time;
and constructing the peak power function according to the charge voltage function and the relation between the peak power and the charge state of the target battery.
5. The method of claim 1, wherein said determining a battery voltage function during charging and discharging of said target battery comprises:
determining an initial charge state and a cut-off charge state of the target battery and an actual voltage at the time of charge and discharge cut-off in the process of discharging the target battery each time;
determining a cut-off voltage corresponding to each cut-off state of charge in the charge voltage function;
the battery voltage function is constructed according to each actual voltage and a cut-off voltage corresponding to each actual voltage.
6. The method of predicting a multiple peak power performance parameter of a battery according to claim 1, wherein said predicting a performance parameter of said target battery based on said peak power function, said battery voltage function, and a battery state function of said target battery comprises:
constructing a peak discharge power charge-discharge time function of the target battery based on the peak power function, the battery voltage function and the battery state function of the target battery;
determining the charge and discharge time of the target battery according to the peak discharge power charge and discharge time function and the peak power; or alternatively, the first and second heat exchangers may be,
and determining the peak power of the target battery according to the peak discharge power charge-discharge time function and the charge-discharge time.
7. A multiple peak power performance parameter prediction apparatus for a battery, comprising:
the construction module is used for constructing a peak power function of the target battery based on a charge voltage function of the target battery and a physical model of the target battery; and determining a battery voltage function in the charging and discharging process of the target battery;
and the prediction module is used for predicting the performance parameter of the target battery based on the peak power function, the battery voltage function and the battery state function of the target battery, wherein the performance parameter comprises peak power or charge and discharge time.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements a method of predicting a multi-peak power performance parameter of a battery as claimed in any one of claims 1 to 6 when the program is executed by the processor.
9. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements a method of predicting multiple peak power performance parameters of a battery according to any one of claims 1-6.
10. A computer program product comprising a computer program which, when executed by a processor, implements a method of predicting a multiple peak power performance parameter of a battery as claimed in any one of claims 1 to 6.
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| CN117060553B (en) * | 2023-10-13 | 2024-01-02 | 快电动力(北京)新能源科技有限公司 | Battery management method, device, system and component of energy storage system |
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