CN108983100B - Method and device for processing residual electric quantity of battery - Google Patents
Method and device for processing residual electric quantity of battery Download PDFInfo
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Abstract
The invention discloses a method and a device for processing the residual electric quantity of a battery. Wherein, the method comprises the following steps: obtaining the electric quantity of the battery at the current moment according to a first preset algorithm, wherein the first preset algorithm obtains the electric quantity of the battery at the current moment through calculation of the current value of the battery; acquiring a learning factor at the previous moment and the residual electric quantity at the previous moment; and correcting the residual electric quantity at the previous moment according to the electric quantity at the current moment and the learning factor at the previous moment to obtain the residual electric quantity at the current moment. The invention solves the technical problems of low accuracy and high complexity of the method for processing the residual electric quantity of the battery in the prior art.
Description
Technical Field
The invention relates to the field of batteries, in particular to a method and a device for processing the residual electric quantity of a battery.
Background
The State Of Charge (SOC) Of a battery is an important index for reflecting the State Of Charge Of the battery. For the estimation of the battery SOC, SOC processing methods such as an open-circuit voltage method, an ampere-hour integration method, a kalman filter method, and the like are proposed in the prior art. The open-circuit voltage method calculates the SOC by measuring the terminal voltage of the battery by using the corresponding relation between the terminal voltage of the battery and the SOC, and is not suitable for calculating the dynamic SOC of the battery; the ampere-hour integration method is simple and easy to implement, but errors caused by factors such as current sampling are accumulated along with time and gradually increase, so that the calculation error of the SOC is increased, the requirement of long-term use in actual engineering cannot be met, and the ampere-hour integration method cannot calculate an initial SOC value; the Kalman filtering method has strong adaptivity, and can eliminate initial errors of SOC, so that the SOC value of the battery can be corrected, the SOC estimation precision is very high, but the algorithm is complex, the calculation amount is large, a background needs to measure data, and the requirement on a processor is high.
Aiming at the problems of low accuracy and high complexity of a method for processing the residual electric quantity of the battery in the prior art, an effective solution is not provided at present.
Disclosure of Invention
The embodiment of the invention provides a method and a device for processing the residual electric quantity of a battery, which are used for at least solving the technical problems of low accuracy and high complexity of a method for processing the residual electric quantity of the battery in the prior art.
According to an aspect of the embodiments of the present invention, there is provided a method for processing remaining battery power, including: obtaining the electric quantity of the battery at the current moment according to a first preset algorithm, wherein the first preset algorithm obtains the current moment through calculating the current value of the battery; acquiring a learning factor at the previous moment and the residual electric quantity at the previous moment; and correcting the residual electric quantity at the previous moment according to the electric quantity at the current moment and the learning factor at the previous moment to obtain the residual electric quantity at the current moment.
Further, correcting the remaining power at the previous moment according to the power at the current moment and the learning factor at the previous moment to obtain the remaining power at the current moment, including: acquiring the total electric quantity and rated capacity of the battery at the last moment; calculating the sum of the electric quantity at the current moment and the total electric quantity at the previous moment to obtain the total electric quantity at the current moment; calculating to obtain a correction parameter according to the learning factor at the previous moment, the total electric quantity and the rated capacity at the current moment; and correcting the residual electric quantity at the previous moment according to the correction parameters to obtain the residual electric quantity at the current moment.
Further, the remaining capacity at the current moment is calculated by the following formula: SOCt＝SOCt-1-Q*Kt-1/CNWherein, SOCtIs the remaining capacity, SOC, of the current timet-1Is the remaining capacity of the last moment, Q.Kt-1/CNFor correcting the parameters, Q is the total electric quantity at the current moment, Kt-1Is a learning factor at the previous moment, CNIs rated capacity.
Further, after the remaining power at the previous time is corrected according to the power at the current time and the learning factor at the previous time to obtain the remaining power at the current time, the method further includes: judging whether the residual electric quantity at the current moment is zero or not and whether the battery is in an overdischarge protection state or not; if the residual electric quantity at the current moment is judged to be not zero and the battery is in an overdischarge protection state, obtaining a learning factor at the current moment according to the total electric quantity at the current moment and the residual electric quantity at the current moment; and if the residual electric quantity at the current moment is zero and the battery is in an overdischarge protection state, obtaining the learning factor at the current moment according to the total electric quantity at the current moment.
Further, obtaining a learning factor at the current moment according to the total electric quantity at the current moment and the remaining electric quantity at the current moment, including: acquiring rated capacity and a plurality of historical learning factors of a battery; calculating to obtain a first learning factor according to the total electric quantity at the current moment, the residual electric quantity at the current moment and the rated capacity; and carrying out average value calculation on the first learning factor and the plurality of historical learning factors to obtain the learning factor at the current moment.
Further, the first learning factor is calculated by the following formula:
wherein, K'tIs a first learning factor, SOCtIs the remaining power at the current moment, Q is the total power at the current moment, CNIs rated capacity.
Further, obtaining a learning factor at the current moment according to the total electric quantity at the current moment, including: acquiring a plurality of historical learning factors; calculating the ratio of the electric quantity at the current moment to the total electric quantity at the current moment to obtain a first learning factor; and carrying out average value calculation on the first learning factor and the plurality of historical learning factors to obtain the learning factor at the current moment.
Further, obtaining the electric quantity of the battery at the current moment according to a first preset algorithm includes: collecting the current value of the battery; and calculating the electric quantity at the current moment according to the current value.
Further, before obtaining the current electric quantity of the battery according to the first preset algorithm, the method further includes: judging whether the battery is in a discharging state or not; if the battery is in a discharging state, obtaining the electric quantity at the current moment according to a first preset algorithm; and if the battery is not in a discharging state, obtaining the initial residual capacity of the battery according to a second preset algorithm, wherein the second preset algorithm obtains the initial residual capacity through calculation of the terminal voltage of the battery.
Further, obtaining the initial remaining capacity of the battery according to a second preset algorithm includes: acquiring terminal voltage and current temperature of a battery; calculating to obtain a temperature coefficient according to the current temperature; and calculating to obtain initial residual capacity according to the terminal voltage and the temperature coefficient.
Further, the first preset algorithm is an ampere-hour integration method, and the second preset algorithm is an open-circuit voltage method.
According to another aspect of the embodiments of the present invention, there is also provided a device for processing battery power, including: the first processing module is used for obtaining the electric quantity of the battery at the current moment according to a first preset algorithm, wherein the first preset algorithm is used for calculating the electric quantity of the battery at the current moment according to the current value of the battery; the acquisition module is used for acquiring the learning factor at the previous moment and the residual electric quantity at the previous moment; and the second processing module is used for correcting the residual electric quantity at the previous moment according to the electric quantity at the current moment and the learning factor at the previous moment to obtain the residual electric quantity at the current moment.
According to another aspect of the embodiments of the present invention, a computer-readable storage medium is further provided, where the computer-readable storage medium includes a stored program, and when the program runs, the apparatus where the computer-readable storage medium is located is controlled to execute the method for processing the remaining battery capacity in the foregoing embodiments.
According to another aspect of the embodiments of the present invention, there is also provided a processor, where the processor is configured to execute a program, where the program executes the method for processing the remaining battery capacity in the foregoing embodiments.
In the embodiment of the invention, the electric quantity of the battery at the current moment is obtained according to the first preset algorithm, the learning factor and the residual electric quantity at the previous moment are obtained, and the residual electric quantity at the previous moment is corrected according to the electric quantity at the current moment and the learning factor at the previous moment to obtain the residual electric quantity at the current moment, so that the residual electric quantity of the battery is calculated in real time. It is easy to notice that, because the learning factor of the previous moment and the residual electric quantity of the previous moment are obtained, and the residual electric quantity of the previous moment is corrected according to the electric quantity of the current moment and the learning factor of the previous moment to obtain the residual electric quantity of the current moment, the residual electric quantity can be corrected through the learning factor to gradually correct errors, so that errors accumulated by factors such as hardware sampling, clock temperature drift and the like along with the lapse of time are overcome, and the technical problems of low accuracy and high complexity of the processing method of the residual electric quantity of the battery in the prior art are solved. Therefore, the technical effects of reducing algorithm complexity, improving processing accuracy, reducing cost and improving reliability can be achieved through the scheme provided by the embodiment of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a flowchart of a method for processing remaining battery capacity according to an embodiment of the present invention;
FIG. 2 is a flow chart of an alternative method of processing remaining battery power in accordance with an embodiment of the present invention; and
fig. 3 is a schematic diagram of a device for processing remaining battery power according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
In accordance with an embodiment of the present invention, there is provided an embodiment of a method for processing remaining battery capacity, it should be noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order different than that described herein.
Fig. 1 is a flowchart of a method for processing remaining battery capacity according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, obtaining the electric quantity of the battery at the current moment according to a first preset algorithm, wherein the first preset algorithm obtains the electric quantity of the battery at the current moment through calculation of the current value of the battery.
Specifically, the first preset algorithm may be an ampere-hour integration method, and the ampere-hour integration method may be used to calculate the electric quantity of the battery in real time under the condition that the battery is dynamically discharged.
And step S104, acquiring the learning factor and the residual capacity at the previous moment.
Specifically, the learning factor at the previous time may be a learning factor calculated in the previous processing of the remaining power, and the initial learning factor may be 1; the remaining power at the previous time may be the remaining power calculated in the previous processing of the remaining power.
And S106, correcting the residual electric quantity at the previous moment according to the electric quantity at the current moment and the learning factor at the previous moment to obtain the residual electric quantity at the current moment.
In an optional scheme, in the prior art, the battery power is calculated in real time by an ampere-hour integration method, and the initial remaining power SOC is used0And calculating to obtain the residual electric quantity SOC at the current momenttI.e. according to SOC in the prior art0And the current battery electric quantity, and calculating to obtain the SOCt. In the embodiment of the present invention, in each complete discharge cycle (each complete discharge cycle may include a plurality of remaining power processing procedures), the remaining power at the current time, that is, the SOC, may be calculated according to the learning factor at the previous time and the power at the current timetThat is, the SOC can be calculated by the ampere-hour integration methodtIn the process of (1), a learning factor is introduced, and the SOC is subjected to learning by the learning factortPerforming correction to reduce SOCtIn calculating the SOC oftThereafter, the SOC at the current time may be determinedtStoring is performed so that it can be used as the remaining power SOC at the previous time in the process of the next remaining powert-1。
According to the embodiment of the invention, the electric quantity of the battery at the current moment is obtained according to the first preset algorithm, the learning factor and the residual electric quantity at the previous moment are obtained, and the residual electric quantity at the previous moment is corrected according to the electric quantity at the current moment and the learning factor at the previous moment to obtain the residual electric quantity at the current moment, so that the residual electric quantity of the battery is calculated in real time. It is easy to notice that, because the learning factor of the previous moment and the residual electric quantity of the previous moment are obtained, and the residual electric quantity of the previous moment is corrected according to the electric quantity of the current moment and the learning factor of the previous moment to obtain the residual electric quantity of the current moment, the residual electric quantity can be corrected through the learning factor to gradually correct errors, so that errors accumulated by factors such as hardware sampling, clock temperature drift and the like along with the lapse of time are overcome, and the technical problems of low accuracy and high complexity of the processing method of the residual electric quantity of the battery in the prior art are solved. Therefore, the technical effects of reducing algorithm complexity, improving processing accuracy, reducing cost and improving reliability can be achieved through the scheme provided by the embodiment of the invention.
Optionally, in the foregoing embodiment of the present invention, in step S106, correcting the remaining power at the previous time according to the power at the current time and the learning factor at the previous time to obtain the remaining power at the current time, where the step includes:
in step S1062, the total electric quantity and the rated capacity of the battery at the last time are obtained.
Specifically, the total electric energy at the previous time may be historical total electric energy accumulated in the previous processing of a plurality of remaining electric energy; the rated capacity may be a minimum amount of electricity that can be discharged from the battery, which is set in advance according to actual use requirements.
Step S1064, calculating the sum of the current power and the last power to obtain the current power.
In an optional scheme, after the electric quantity at the current moment is calculated according to the ampere-hour integral method, a sum of the electric quantity at the current moment and the total electric quantity at the previous moment can be calculated, that is, the electric quantity at the current moment is superimposed on the basis of the historical total electric quantity, so that the total electric quantity at the current moment is obtained.
And step S1066, calculating to obtain a correction parameter according to the learning factor at the previous moment, the total electric quantity and the rated capacity at the current moment.
Step S1068, correcting the remaining power at the previous time according to the correction parameter to obtain the remaining power at the current time.
Optionally, in the foregoing embodiment of the present invention, the remaining power at the current time is calculated by the following formula:
SOCt＝SOCt-1-Q*Kt-1/CNwherein, SOCtIs the remaining capacity, SOC, of the current timet-1Is the remaining capacity of the last moment, Q.Kt-1/CNFor correcting the parameters, Q is the total electric quantity at the current moment, Kt-1Is a learning factor at the previous moment, CNIs rated capacity.
In an alternative wayIn the case, the obtained remaining power SOC at the previous time may be usedt-1Last moment learning factor Kt-1And the total electric quantity Q at the current moment obtained by calculationtAnd rated capacity CNSubstituting the formula into the above formula to calculate and obtain the remaining capacity SOC at the current momenttThat is, in the calculation formula of the existing ampere-hour integral method, a learning factor is introduced, and the SOC is controlled by the learning factortCorrecting to obtain corrected SOCt。
Through the steps, the calculation formula of the residual electric quantity at the current moment is simple, so that the processing complexity and the calculation amount are reduced, the requirement on a processor is further reduced, and compared with the prior art, the method is easier to realize.
Optionally, in the foregoing embodiment of the present invention, in step S106, after the remaining power at the previous time is corrected according to the total power at the current time and the learning factor at the previous time, and the remaining power at the current time is obtained, the method further includes the following steps:
step S108, determining whether the remaining power at the current time is zero and the battery is in an over-discharge protection state.
In an optional scheme, the remaining power SOC at the current moment is calculated by an ampere-hour integral method and a learning factortAnd the actual SOC of the batterytThere is a possibility of non-compliance, and therefore, the SOC may be judged firsttAnd whether the voltage is zero or not is further judged, and whether the battery is in an over-discharge protection state or not is further judged.
It should be noted that, if it is determined that the battery is in the over-discharge protection state, it is determined that the complete discharge cycle is ended, the learning factor is updated, and the next complete discharge cycle is started.
Step S110, if the residual electric quantity at the current moment is judged not to be zero and the battery is in an overdischarge protection state, the learning factor at the current moment is obtained according to the total electric quantity at the current moment and the residual electric quantity at the current moment.
In step S112, if it is determined that the remaining power at the current time is zero and the battery is in the over-discharge protection state, the learning factor at the current time is obtained according to the total power at the current time.
In an optional scheme, the remaining power SOC of the current time may be first determinedtIf it is zero, determining the SOCtAfter the current state is not zero, whether the battery is in an over-discharge protection state or not can be further judged, and if the battery is in the over-discharge protection state, the total electric quantity and the SOC at the current moment are determinedtCalculating to obtain the learning factor K at the current momenttAnd stored as the learning factor K at the previous time in the next remaining capacity processing processt-1(ii) a And if the battery is not in the over-discharge protection state, directly entering the next residual capacity processing process without recalculating the learning factor. At the time of judging SOCtAfter the current electric quantity Q is zero, the total electric quantity Q at the current moment can be stored as the total electric quantity Q at the previous moment in the next remaining electric quantity processing process, then whether the battery is in an overdischarge protection state or not is judged, and if the battery is in the overdischarge protection state, the calculated current electric quantity Q at the current moment is used as the electric quantity QtAnd calculating to obtain a learning factor K at the current momenttAnd stored as the learning factor K at the previous time in the next remaining capacity processing processt-1(ii) a And if the battery is not in the over-discharge protection state, directly entering the next residual capacity processing process without recalculating the learning factor.
It should be noted that, during one complete discharge cycle, the learning factor is not changed until the next complete discharge cycle is started.
Optionally, in the foregoing embodiment of the present invention, in step S110, obtaining the learning factor at the current time according to the total power amount at the current time and the remaining power amount at the current time, where the obtaining includes:
in step S1102, the rated capacity of the battery and a plurality of history learning factors are acquired.
Specifically, the plurality of historical learning factors may be learning factors calculated at the end of the previous complete discharge cycles, and during actual use, the number of the plurality of historical learning factors may be determined according to the accuracy requirement.
In step S1104, a first learning factor is calculated according to the total power amount at the current time, the remaining power amount at the current time, and the rated capacity.
Alternatively, in the above embodiment of the present invention, the first learning factor is calculated by the following formula:
In an optional scheme, the electric quantity at the current moment, the total electric quantity at the current moment and the remaining electric quantity SOC at the current moment are obtained through calculationtThereafter, the total amount of power Q, SOC at the current time may be determinedtAnd rated capacity CNSubstituting the formula into the formula, and calculating to obtain the first learning factor.
In step S1106, an average value of the first learning factor and the plurality of historical learning factors is calculated to obtain the learning factor at the current time.
In an optional scheme, in order to reduce the influence degree of random errors such as temperature and the like on the learning factor, the learning factor calculated at the end of the current complete discharge cycle, that is, the first learning factor, and the average value of the plurality of historical learning factors calculated at the end of the previous complete discharge cycles may be calculated and stored as the learning factor at the current time.
Optionally, in the foregoing embodiment of the present invention, in step S112, obtaining the learning factor at the current time according to the total power amount at the current time includes:
in step S1122, a plurality of history learning factors are acquired.
In step S1124, a ratio between the current electric quantity and the total current electric quantity is calculated to obtain a first learning factor.
Step S1126, calculating the average value of the first learning factor and a plurality of historical learning factors to obtain the learning factor of the current time.
In an optional scheme, after the electric quantity at the current time and the total electric quantity at the current time are obtained through calculation, the electric quantity Q at the current time can be calculatedtAnd the ratio of the total electric quantity Q at the current moment is used for obtaining a first learning factor K'tI.e. K't＝Qtand/Q, calculating the average value of the first learning factor and the plurality of historical learning factors as the learning factor at the current moment, and storing the average value.
Through the steps, after the completion of the discharge of the battery is determined, namely a complete discharge cycle is completed, different first learning factors can be obtained through calculation according to different states of the battery, and the next complete discharge cycle is started, so that the learning factors can gradually approach to an error coefficient of a system in a continuous cycle process, the residual electric quantity is corrected, and the processing accuracy is further improved.
Optionally, in the foregoing embodiment of the present invention, in step S102, obtaining the electric quantity of the battery at the current time according to a first preset algorithm includes:
in step S1022, the current value of the battery is collected.
And step S1024, calculating the electric quantity at the current moment according to the current value.
In an optional scheme, when the battery is in dynamic discharge, a current value can be collected, and the electric quantity at the current moment is calculated by using an ampere-hour integration method.
Optionally, in the foregoing embodiment of the present invention, before the step S102 obtains the electric quantity of the battery at the current time according to a first preset algorithm, the method further includes the following steps:
step S114, determine whether the battery is in a discharge state.
And step S116, if the battery is in a discharging state, acquiring the electric quantity at the current moment according to a first preset algorithm.
Step S118, if the battery is not in a discharging state, obtaining an initial remaining capacity of the battery according to a second preset algorithm, where the second preset algorithm obtains the initial remaining capacity through calculating a terminal voltage of the battery.
Specifically, the second preset algorithm may be an open circuit voltage method.
In an optional scheme, the ampere-hour integration method cannot acquire the initial remaining capacity SOC of the battery0Therefore, it is first possible to determine whether the battery is in a discharge state, and if the battery is not in a discharge state, that is, the battery does not start discharging, the SOC of the battery may be calculated according to the open circuit voltage method0Therefore, after the battery is in a discharging state, namely in the first residual capacity processing process, the electric capacity at the current moment can be calculated according to the ampere-hour integral method, and the SOC is calculated according to the SOC0Initial learning factor K0Electric quantity Q at presentt(since the discharge cycle is performed for the first time, the total amount of electricity is not accumulated, and the total amount of electricity at the present time is equal to the amount of electricity at the present time) and the rated capacity CNAnd calculating to obtain the residual electric quantity SOC at the current momenttSo that the next remaining capacity processing can be continued until the whole discharge cycle is completed.
Optionally, in the foregoing embodiment of the present invention, in step S118, obtaining the initial remaining power of the battery according to a second preset algorithm includes:
step S1182, collecting a terminal voltage and a current temperature of the battery.
Specifically, the above-described current temperature may be the temperature acquired at the start time.
Alternatively, the current temperature at the start time may be acquired by a temperature sensor on a Battery Management System BMS (short for Battery Management System).
Step S1184, calculating to obtain a temperature coefficient according to the current temperature.
In an alternative, the temperature coefficient may be derived by a table look-up. Temperature and SOCtHas a non-linear relationship, different temperatures, corresponding to different SOCtCurve line.
Step S1186, calculating to obtain initial residual electric quantity according to the terminal voltage and the temperature coefficient.
In an alternative arrangementIn the state of static non-discharge of the battery, the battery terminal Voltage OCV (short for Open Circuit Voltage) can directly reflect SOCtThe value can be stored in EEPROM (Electrically Erasable-Programmable Read Only Memory) of processor, and can be obtained by looking up table in real timetAnd according to the temperature coefficient to the SOCtCompensating to obtain SOC0。
Fig. 2 is a flow chart of an alternative method for processing remaining battery power according to an embodiment of the present invention, and a preferred embodiment of the present invention is described in detail below with reference to fig. 2, and as shown in fig. 2, the method may include the following steps:
in step S201, it is determined whether the battery is discharged.
Optionally, after entering a remaining capacity processing procedure, first determining whether the battery is discharged, if it is determined that the battery is not discharged, i.e. the battery is in a static non-discharge state, entering step S202, and calculating an initial remaining capacity SOC by an open-circuit voltage method0(ii) a If the battery is determined to be discharged, that is, the battery is in a discharging state, the method proceeds to step S206, and the remaining capacity SOC at the current moment is obtained by using an ampere-hour integration method and a learning factort。
Step S202, reading the current temperature, and looking up a table to obtain a temperature system.
Alternatively, when the battery is not discharged statically, the current temperature can be read at the starting moment, and the temperature coefficient is obtained.
In step S203, the battery terminal voltage is measured.
Step S204, according to the temperature coefficient and the terminal voltage, the SOC is controlledtCompensation is performed.
Step S205, calculating SOCt。
Alternatively, the terminal voltage OCV of the battery may be measured, and the SOC may be obtained by looking up the table based on the temperature coefficient and the OCVtAnd as SOC0。
Step S206, calculating the current electric quantity Q by using an ampere-hour integral methodt。
Step S207, accumulating the total electric quantity Q, and inquiring the learning factor K at the previous momentt-1。
Step S208, calculating SOCt＝SOCt-1-Q*Kt-1/CN。
Optionally, when the battery is in dynamic discharge, the current value can be collected, and the current electric quantity Q is calculated by using an ampere-hour integration methodt. Calculating the accumulated total electric quantity Q and reading the learning factor K at the last momentt-1. Calculating the residual electric quantity SOC at the current momenttThe formula is as follows: SOCt＝SOCt-1-Q*Kt-1/CNWherein, SOCtIs the value of the residual electric quantity at the current moment, SOCt-1Is the value of the remaining power at the previous moment, Q is the accumulated total power, Kt-1For the last moment of learning factor, CNIs the rated capacity of the battery.
Step S209, saving SOCt。
Optionally, the remaining capacity SOC at the current moment is calculatedtAfter the value of (3), the SOC can be determinedtAnd the power is stored in an EEPROM of the processor, so that the next calculation of the residual power is facilitated.
Step S210, judging SOCtWhether it is zero.
Optionally, the remaining capacity SOC at the current moment is calculatedtThereafter, SOC may be determinedtWhether it becomes zero, if not, go to step S211; if it becomes zero, the flow proceeds to step S214.
Step S211, determining whether the battery is over-discharge protected.
Optionally, if the remaining capacity SOC at the current time is determinedtIf not, further judging whether the battery is in an overdischarge protection state, if not, directly entering the next residual capacity processing process without changing the learning factor, if so, determining to finish a complete discharge cycle, and entering step S212 to adjust the learning factor.
Step S212, calculating a first learning factor Kt'＝(Q+SOCt*CN) And calculating Kt' average value.
Step S213, SOCtAnd (6) clearing.
Optionally, the first learning factor K is calculated after battery over-discharge protectiontThe numerical value of' is as follows:
therein, SOCtIs the residual electric quantity at the current moment, Q is the total electric quantity at the current moment, K'tIs a first learning factor, CNIs the rated capacity of the battery. And calculating the average value K of multiple timestWhile simultaneously setting the current SOCtAnd (6) clearing.
Step S214, saving the current electric quantity Qt。
In step S215, it is determined whether the battery is over-discharge protected.
Optionally, the remaining capacity SOC at the current timetAfter becoming zero, the current amount of power Q may be first savedtAnd continuing to judge whether the battery is over-current protected, if not, continuing to accumulate the total electric quantity until the battery is over-discharge protected, and if so, entering step S216.
Step S216, calculating a first learning factor Kt'＝QtAnd calculating Kt' average value.
Optionally, after battery over-current protection, a self-learning factor K may be calculatedt'＝Qt/Q, and calculating the average value K of multiple timest。
Through the steps, a battery residual capacity processing method is provided, and a battery self-learning method is introduced on the basis of an open-circuit voltage method and an ampere-hour integration method, so that actual measured values and estimated values are verified, and errors are gradually corrected. By the scheme, on the basis of not replacing higher platform hardware, learning factors are introduced through optimization of a software algorithm, calculation errors of the system are corrected autonomously, the more learning times are, the more accurate residual capacity estimation is, errors accumulated by factors such as hardware sampling and clock temperature drift along with the lapse of time are overcome, and the purposes of estimating the residual capacity of the battery and preventing precision from being reduced in the using process are achieved. The method has the advantages of low cost, simplicity, feasibility, uncomplicated algorithm, small workload, easy operation and realization, high reliability, no need of upgrading the existing hardware platform and software platform, and capability of being popularized and applied in a large amount, and can be applied to battery application in the fields of energy, power, energy storage and the like, accurately estimate the residual electric quantity, effectively protect the battery, prevent the battery from being overcharged or overdischarged, improve the service life and the utilization rate of the battery, simultaneously master the residual electric quantity of the battery, know the endurance time of the battery in time and further plan the later charging and discharging work.
Example 2
According to an embodiment of the present invention, an embodiment of a device for processing remaining battery power is provided.
Fig. 3 is a schematic diagram of a device for processing remaining battery power according to an embodiment of the present invention, as shown in fig. 3, the device includes:
the first processing module 31 is configured to obtain an electric quantity of the battery at the current time according to a first preset algorithm, where the first preset algorithm calculates the electric quantity of the battery at the current time according to a current value of the battery.
Specifically, the first preset algorithm may be an ampere-hour integration method, and the ampere-hour integration method may be used to calculate the electric quantity of the battery in real time under the condition that the battery is dynamically discharged.
The obtaining module 33 is configured to obtain the learning factor at the previous time and the remaining power at the previous time.
Specifically, the learning factor at the previous time may be a learning factor calculated in the previous processing of the remaining power, and the initial learning factor may be 1; the remaining power at the previous time may be the remaining power calculated in the previous processing of the remaining power.
The second processing module 35 is configured to correct the remaining power at the previous time according to the power at the current time and the learning factor at the previous time, so as to obtain the remaining power at the current time.
In an alternative arrangement, theIn the prior art, the battery electric quantity is calculated in real time by an ampere-hour integral method, and the initial residual electric quantity SOC is used0And calculating to obtain the residual electric quantity SOC at the current momenttI.e. according to SOC in the prior art0And the current battery electric quantity, and calculating to obtain the SOCt. In the embodiment of the present invention, in each complete discharge cycle (each complete discharge cycle may include a plurality of remaining power processing procedures), the remaining power at the current time, that is, the SOC, may be calculated according to the learning factor at the previous time and the power at the current timetThat is, the SOC can be calculated by the ampere-hour integration methodtIn the process of (1), a learning factor is introduced, and the SOC is subjected to learning by the learning factortPerforming correction to reduce SOCtIn calculating the SOC oftThereafter, the SOC at the current time may be determinedtStoring is performed so that it can be used as the remaining power SOC at the previous time in the process of the next remaining powert-1。
According to the embodiment of the invention, the electric quantity of the battery at the current moment is obtained according to the first preset algorithm, the learning factor and the residual electric quantity at the previous moment are obtained, and the residual electric quantity at the previous moment is corrected according to the electric quantity at the current moment and the learning factor at the previous moment to obtain the residual electric quantity at the current moment, so that the residual electric quantity of the battery is calculated in real time. It is easy to notice that, because the learning factor of the previous moment and the residual electric quantity of the previous moment are obtained, and the residual electric quantity of the previous moment is corrected according to the electric quantity of the current moment and the learning factor of the previous moment to obtain the residual electric quantity of the current moment, the residual electric quantity can be corrected through the learning factor to gradually correct errors, so that errors accumulated by factors such as hardware sampling, clock temperature drift and the like along with the lapse of time are overcome, and the technical problems of low accuracy and high complexity of the processing method of the residual electric quantity of the battery in the prior art are solved. Therefore, the technical effects of reducing algorithm complexity, improving processing accuracy, reducing cost and improving reliability can be achieved through the scheme provided by the embodiment of the invention.
Optionally, in the foregoing embodiment of the present invention, the second processing module includes:
and the first acquisition submodule is used for acquiring the total electric quantity and the rated capacity of the battery at the last moment.
And the first calculating submodule is used for calculating the sum of the electric quantity at the current moment and the total electric quantity at the previous moment to obtain the total electric quantity at the current moment.
And the first processing submodule is used for calculating to obtain a correction parameter according to the learning factor at the previous moment, the total electric quantity and the rated capacity at the current moment.
And the correction submodule is used for correcting the residual electric quantity at the previous moment according to the correction parameters to obtain the residual electric quantity at the current moment.
Optionally, in the foregoing embodiment of the present invention, the first processing sub-module is further configured to calculate the remaining power at the current time by using the following formula:
SOCt＝SOCt-1-Q*Kt-1/CNwherein, SOCtIs the remaining capacity, SOC, of the current timet-1Is the remaining capacity of the last moment, Q.Kt-1/CNFor correcting the parameters, Q is the total electric quantity at the current moment, Kt-1Is a learning factor at the previous moment, CNIs rated capacity.
Optionally, in the above embodiment of the present invention, the apparatus further includes:
the first judgment module is used for judging whether the residual electric quantity at the current moment is zero or not and whether the battery is in an overdischarge protection state or not.
And the third processing module is used for obtaining the learning factor at the current moment according to the total electric quantity at the current moment and the residual electric quantity at the current moment if the residual electric quantity at the current moment is judged not to be zero and the battery is in an over-current protection state.
And the fourth processing module is used for obtaining the learning factor at the current moment according to the total electric quantity at the current moment if the residual electric quantity at the current moment is judged to be zero and the battery is in an over-current protection state.
Optionally, in the foregoing embodiment of the present invention, the third processing module includes:
and the second acquisition submodule is used for acquiring the rated capacity of the battery and a plurality of historical learning factors.
And the second calculation submodule is used for calculating to obtain a first learning factor according to the total electric quantity at the current moment, the residual electric quantity at the current moment and the rated capacity.
Optionally, in the foregoing embodiment of the present invention, the second calculating submodule is configured to calculate the first learning factor by using the following formula:
And the third calculation submodule is used for carrying out average value calculation on the first learning factor and the plurality of historical learning factors to obtain the learning factor at the current moment.
Optionally, in the foregoing embodiment of the present invention, the fourth processing module includes:
and the third acquisition submodule is used for acquiring a plurality of historical learning factors.
And the fourth calculating submodule is used for calculating the ratio of the electric quantity at the current moment to the total electric quantity at the current moment to obtain a first learning factor.
And the fifth calculating submodule is used for carrying out average value calculation on the first learning factor and the plurality of historical learning factors to obtain the learning factor at the current moment.
Optionally, in the foregoing embodiment of the present invention, the first processing module includes:
and the first acquisition submodule is used for acquiring the current value of the battery.
And the second processing submodule is used for calculating the electric quantity at the current moment according to the current value.
Optionally, in the above embodiment of the present invention, the apparatus further includes:
and the second judgment module is used for judging whether the battery is in a discharging state.
The first processing module is further used for obtaining the electric quantity at the current moment according to a first preset algorithm if the battery is in a discharging state.
And the fifth processing module is used for obtaining the initial residual capacity of the battery according to a second preset algorithm if the battery is not in a discharging state, wherein the second preset algorithm obtains the initial residual capacity through calculation of the terminal voltage of the battery.
Optionally, in the foregoing embodiment of the present invention, the fifth processing module includes:
and the second acquisition submodule is used for acquiring the terminal voltage and the current temperature of the battery.
And the sixth calculation submodule is used for calculating the temperature coefficient according to the current temperature.
And the seventh calculation submodule is used for calculating to obtain the initial residual electric quantity according to the terminal voltage and the temperature coefficient.
It should be noted that, for the preferred implementation in this embodiment, reference may be made to the description in embodiment 1, and details are not described here.
Example 3
According to an embodiment of the present invention, an embodiment of a computer-readable storage medium is provided, where the computer-readable storage medium includes a stored program, and when the program runs, a device where the computer-readable storage medium is located is controlled to execute the method for processing the remaining battery capacity in the foregoing embodiment 1.
Example 4
According to an embodiment of the present invention, an embodiment of a processor for running a program is provided, where the program runs to execute the method for processing the remaining battery capacity in embodiment 1.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute 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 Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (13)
1. A method for processing the residual capacity of a battery is characterized by comprising the following steps:
obtaining the electric quantity of a battery at the current moment according to a first preset algorithm, wherein the first preset algorithm calculates the electric quantity of the battery at the current moment according to the current value of the battery;
acquiring a learning factor at the previous moment and the residual electric quantity at the previous moment;
correcting the residual electric quantity at the previous moment according to the electric quantity at the current moment and the learning factor at the previous moment to obtain the residual electric quantity at the current moment;
after the remaining power at the previous moment is corrected according to the power at the current moment and the learning factor at the previous moment, the method further includes: judging whether the residual electric quantity at the current moment is zero or not and whether the battery is in an overdischarge protection state or not; if the residual electric quantity at the current moment is judged to be not zero and the battery is in an overdischarge protection state, obtaining a learning factor at the current moment according to the total electric quantity at the current moment and the residual electric quantity at the current moment; and if the residual electric quantity at the current moment is zero and the battery is in an overdischarge protection state, obtaining a learning factor at the current moment according to the total electric quantity at the current moment.
2. The method according to claim 1, wherein correcting the remaining power at the previous time according to the power at the current time and the learning factor at the previous time to obtain the remaining power at the current time comprises:
acquiring the total electric quantity and rated capacity of the battery at the last moment;
calculating the sum of the electric quantity at the current moment and the total electric quantity at the previous moment to obtain the total electric quantity at the current moment;
calculating to obtain a correction parameter according to the learning factor at the previous moment, the total electric quantity at the current moment and the rated capacity;
and correcting the residual electric quantity at the previous moment according to the correction parameters to obtain the residual electric quantity at the current moment.
3. The method according to claim 2, wherein the remaining capacity at the current time is calculated by the following formula:
SOCt＝SOCt-1-Q*Kt-1/CNwherein, SOCtIs the remaining capacity, SOC, of the current timet-1Is the remaining capacity of the previous moment, Q.Kt-1/CNFor the correction parameter, Q is the total electric quantity at the current moment, Kt-1Is the learning factor at the previous moment, CNIs the rated capacity.
4. The method of claim 1, wherein obtaining a learning factor at a current time according to the total power amount at the current time and the remaining power amount at the current time comprises:
acquiring rated capacity and a plurality of historical learning factors of the battery;
calculating to obtain a first learning factor according to the total electric quantity at the current moment, the residual electric quantity at the current moment and the rated capacity;
and carrying out average calculation on the first learning factor and the plurality of historical learning factors to obtain the learning factor at the current moment.
5. The method of claim 4, wherein the first learning factor is calculated by the formula:
6. The method of claim 1, wherein obtaining a learning factor at the current time according to the total power at the current time comprises:
acquiring a plurality of historical learning factors;
calculating the ratio of the electric quantity at the current moment to the total electric quantity at the current moment to obtain a first learning factor;
and carrying out average calculation on the first learning factor and the plurality of historical learning factors to obtain the learning factor at the current moment.
7. The method of claim 1, wherein obtaining the current battery level according to a first predetermined algorithm comprises:
collecting a current value of the battery;
and calculating the electric quantity at the current moment according to the current value.
8. The method of claim 1, wherein before obtaining the current battery level of the battery according to the first predetermined algorithm, the method further comprises:
judging whether the battery is in a discharging state or not;
if the battery is in the discharging state, obtaining the electric quantity at the current moment according to the first preset algorithm;
and if the battery is not in the discharging state, obtaining the initial residual capacity of the battery according to a second preset algorithm, wherein the second preset algorithm obtains the initial residual capacity through calculation of the terminal voltage of the battery.
9. The method of claim 8, wherein obtaining the initial remaining capacity of the battery according to a second predetermined algorithm comprises:
acquiring the terminal voltage and the current temperature of the battery;
calculating to obtain a temperature coefficient according to the current temperature;
and calculating to obtain the initial residual electric quantity according to the terminal voltage and the temperature coefficient.
10. The method of claim 8, wherein the first predetermined algorithm is ampere-hour integration and the second predetermined algorithm is open circuit voltage.
11. A device for processing remaining capacity of a battery, comprising:
the first processing module is used for obtaining the electric quantity of the battery at the current moment according to a first preset algorithm, wherein the first preset algorithm is used for calculating the electric quantity of the battery at the current moment according to the current value of the battery;
the acquisition module is used for acquiring the learning factor at the previous moment and the residual electric quantity at the previous moment;
the second processing module is used for correcting the residual electric quantity at the previous moment according to the electric quantity at the current moment and the learning factor at the previous moment to obtain the residual electric quantity at the current moment;
the device is further configured to, after correcting the remaining power at the previous time according to the power at the current time and the learning factor at the previous time to obtain the remaining power at the current time, determine whether the remaining power at the current time is zero and whether the battery is in an overdischarge protection state; if the residual electric quantity at the current moment is judged to be not zero and the battery is in an overdischarge protection state, obtaining a learning factor at the current moment according to the total electric quantity at the current moment and the residual electric quantity at the current moment; and if the residual electric quantity at the current moment is zero and the battery is in an overdischarge protection state, obtaining a learning factor at the current moment according to the total electric quantity at the current moment.
12. A computer-readable storage medium, comprising a stored program, wherein when the program runs, the computer-readable storage medium controls a device to execute the method for processing the remaining battery capacity according to any one of claims 1 to 10.
13. A processor, characterized in that the processor is configured to execute a program, wherein the program executes the method for processing the remaining battery capacity according to any one of claims 1 to 10.
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