CN111025156B - Battery state prediction method and device - Google Patents
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Abstract
The embodiment of the invention provides a method and a device for predicting the state of a battery. The state prediction method comprises the steps of establishing an equivalent circuit model of the battery, wherein the terminal voltage of the battery is determined according to the open-circuit voltage and the polarization voltage of the equivalent circuit model; the open circuit voltage is determined based on the correspondence between the open circuit voltage and the state of charge function, and the polarization voltage is determined according to a first functional relationship model of voltage, current and time; wherein the parameters of the first functional relationship model are determined based on a second functional relationship model between the state of charge function and the battery temperature; acquiring a current state of charge function and a current battery temperature; predicting one or more future states of the battery based on the current state of charge function and the current battery temperature, and the open circuit voltage and the polarization voltage. The technical scheme can predict the voltage of the battery at a certain time or a certain current in the future and predict the SOP of the battery so as to ensure that the battery can play the best performance in the operation and safety interval.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of power batteries, in particular to a battery state prediction method and device.
[ background of the invention ]
The power battery is used as an energy source of the electric automobile and is important for the development of the electric automobile, and the performance of the electric automobile is determined by the characteristics of the power battery. If the power battery is overcharged or overdischarged in the using process, the aging of the battery is accelerated, and in particular for quick charging, overcharge can cause serious safety problems. The state of power (SOP) is an important index for battery performance and also an important reference index for realizing energy management of the electric vehicle. If the voltage and the SOP of the battery can be effectively and accurately early warned in advance, safety protection measures can be taken in advance, and the battery is guaranteed to be in a safe and reasonable range.
The most commonly used N-order RC equivalent circuit model (N is more than or equal to 0) can simulate the voltage of the battery, but the voltage can not be predicted with high precision. The SOP estimation method based on the model is complex and difficult to solve, and high-precision SOP prediction cannot be realized. At present, no simple, quick and high-precision voltage prediction and power prediction means is available for effectively early warning the battery voltage and accurately predicting the SOP of the battery.
[ summary of the invention ]
In view of this, embodiments of the present invention provide a method and an apparatus for predicting a state of a battery, so as to solve the technical problem that the prior art cannot effectively warn a battery voltage and accurately predict an SOP of the battery.
In one aspect, an embodiment of the present invention provides a method for predicting a state of a battery, including: establishing an equivalent circuit model of a battery, wherein the terminal voltage of the battery is determined according to the open-circuit voltage and the polarization voltage of the equivalent circuit model; the open circuit voltage is determined based on a correspondence between the open circuit voltage and a state of charge function, the polarization voltage is determined according to a first functional relationship model of voltage to current and time; wherein the parameters of the first functional relationship model are determined based on a second functional relationship model between the state of charge function and the battery temperature; acquiring a current state of charge function and a current battery temperature; predicting one or more future states of the battery based on the current state of charge function and current battery temperature, and the open circuit voltage and the polarization voltage.
Optionally, the predicting one or more future states of the battery based on the current state of charge function and the current battery temperature, and the open-circuit voltage and the polarization voltage comprises:
determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature; wherein the second functional relationship model isSOC is the current state of charge function, T is the current battery temperature, k1~k6Is a coefficient; according to different k1~k6Determining parameters of the first functional relationship model respectively;
determining a predicted current and a polarization voltage under a predicted time according to the first functional relation model; wherein the first functional relationship model is Uop=aln2(t | I |) + bln (t | I |) + cI + d; wherein, UopThe polarization voltage, the predicted current, the predicted time and the parameters of a, b, c and d are respectively the parameters of the first functional relation model;
determining the open-circuit voltage under the predicted current and the predicted time according to the corresponding relation between the open-circuit voltage and the current state of charge function;
predicting the terminal voltage based on the predicted current and the polarization voltage and the open circuit voltage at the predicted time;
and predicting the power of the battery at the predicted current and predicted time based on the terminal voltage and the predicted current.
Optionally, the predicting one or more future states of the battery based on the current state of charge function and the current battery temperature, and the open-circuit voltage and the polarization voltage comprises:
determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature; wherein the second functional relationship model isT is the current battery temperature, k1~k6Is a coefficient; according to different k1~k6Determining parameters of the first functional relationship model respectively;
determining the open-circuit voltage under the predicted current according to the corresponding relation between the open-circuit voltage and the current state of charge function;
setting an upper cutoff voltage or a lower cutoff voltage, and based on the predicted current, according to the following formula: u shapemax/min-Uocv=aln2(tmax|I|)+bln(tmaxL I |) + cI + d predicts the time t required for the battery to reach the upper limit cutoff voltage or the lower limit cutoff voltage under the prediction currentmax(ii) a Wherein, UocvThe open-circuit voltage is represented, the predicted current is represented by I, and the parameters of the first functional relation model are represented by a, b, c and d respectively.
Optionally, the predicting one or more future states of the battery based on the current state of charge function and the current battery temperature, and the open-circuit voltage and the polarization voltage comprises:
determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature; wherein the second functional relationship model isT is the current battery temperature, k1~k6Is a coefficient; according to different k1~k6Determining parameters of the first functional relationship model respectively;
determining the open-circuit voltage at the predicted time according to the corresponding relation between the open-circuit voltage and the current state of charge function;
setting an upper cutoff voltage or a lower cutoff voltage, and based on the predicted time according to the following formula: u shapemax/min-Uocv=aln2(t|Imax|)+bln(t|Imax|)+cImax+ d predicting the maximum current I at which the battery reaches the upper or lower cutoff voltage within the predicted timemax(ii) a Wherein U ismax/minIs an upper cut-off voltage or a lower cut-off voltage, UocvThe open-circuit voltage is used, t is the predicted time, and a, b, c and d are parameters of the first functional relation model respectively;
based on the maximum current ImaxAnd the upper limit cut-off voltage or the lower limit cut-off voltage Umax/minPredicting a maximum power of the battery over the predicted time.
In another aspect, an embodiment of the present invention provides a device for predicting a state of a battery, including: the model establishing module is used for establishing an equivalent circuit model of the battery, and the terminal voltage of the battery is determined according to the open-circuit voltage and the polarization voltage of the equivalent circuit model; the open circuit voltage is determined based on a correspondence between the open circuit voltage and a state of charge function, the polarization voltage is determined according to a first functional relationship model of voltage to current and time; wherein the parameters of the first functional relationship model are determined based on a second functional relationship model between the state of charge function and the battery temperature; the power of the battery is determined according to the terminal voltage and the current; the parameter acquisition module is used for acquiring a current state of charge function and a current battery temperature; a prediction module to predict one or more future states of the battery based on the current state of charge function and current battery temperature, and the open circuit voltage and the polarization voltage.
Compared with the prior art, the technical scheme at least has the following beneficial effects:
according to the state prediction method of the battery provided by the embodiment of the invention, the voltage of the battery at a certain time or at a certain current in the future can be predicted, and the SOP of the battery can be predicted, so that the problem that the voltage of the battery cannot be effectively pre-warned and the SOP of the battery cannot be accurately predicted in the prior art is solved, and the optimal performance of the battery is ensured in the operation and safety interval of the battery.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic circuit diagram of an equivalent circuit model of a battery according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a battery state prediction method based on the equivalent circuit model shown in fig. 1 according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an embodiment of a battery state prediction apparatus according to an embodiment of the present invention.
[ detailed description ] embodiments
For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all 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.
Fig. 1 is a schematic circuit diagram of an equivalent circuit model of a battery according to an embodiment of the present invention. Referring to fig. 1, the equivalent circuit model of the battery includes: open circuit voltage UocvAnd a polarization voltage UopTherefore, the terminal voltage U of the battery can be determined according to the following formula (1):
U=Uocv+Uopformula (1)
Wherein the polarization voltage UopIs a potential difference that results from the electrode electromotive force deviating from the equilibrium electrode potential due to irreversible electrode processes of the battery. Open circuit voltage UocvIs the voltage across the cell in the open circuit condition.
Open circuit voltage UocvCan be based onThe corresponding relation between the over-open circuit voltage and the state of charge (SOC) function is obtained. Specific correspondences include, but are not limited to, table look-up, polynomial, logarithmic or a combination of various functions. In this embodiment, a specific corresponding relationship between the open-circuit voltage and the SOC function may be selected according to different battery characteristics, which is not limited herein.
In other embodiments, the open circuit voltage UocvOr the cell can be left standing for 30 minutes without current flowing.
Polarization voltage UopMay be determined as a function of voltage, current, and time, including but not limited to a polynomial, exponential, logarithmic, or a combination of functions. In the present embodiment, the polarization voltage UopMay be determined from a first functional relationship model of voltage with current and time, wherein the first functional relationship model is shown in equation (2):
Uop=aln2(t | I |) + bln (t | I |) + cI + d equation (2)
Wherein, I is current (unit is A) or current multiplying power (unit is C), the current multiplying power is equal to the ratio of the charging and discharging current to the rated capacity of the battery, I is positive in a charging state, and I is negative in a discharging state; t is the time (in seconds) for the current to flow through the battery; a. b, c and d are parameters of the first functional relationship model.
In this embodiment, the parameters of the first functional relationship model are determined based on a second functional relationship model between the state of charge function and the battery temperature.
Specifically, the second functional relationship model is shown in formula (3):
wherein T is temperature in degrees Celsius (in degrees C.) or temperature in Kelvin (in units of K), K1~k6Are coefficients.
Parameters a, b, c and d of the first functional relationship modelThe corresponding different k in the above formula (3) can be utilized1~k6To obtain the result. For example, using a set of k1~k6Obtaining a parameter a, using another set of k1~k6And obtaining a parameter b.
Specifically, based on the same SOC function, the battery is charged or discharged by adopting at least two pulse currents with different amplitudes, and each pulse lasts at least 2 seconds.
The pulse implementation can adopt any one of the following two modes:
1) the selected pulses are used to charge or discharge the battery. Any resting time may be added between each pulse, such as 0 seconds, 10 seconds, 30 minutes, etc.
2) The selected pulses are used to charge or discharge the battery. After charging or discharging with a selected pulse, the battery may be discharged or charged with any current, with the SOC function before and after being unchanged, and then left for any time (e.g., 0 second, 10 seconds, 30 minutes, etc.). The other selected pulses take the same form.
Collecting voltage and current data, and calculating to obtain polarization voltage U by using the formula (1)opAnd respectively calculating parameters a, b, c and d of the first functional relation model by using a formula (2).
k1~k6The determination method of (2) is as follows: selecting several SOC points and temperatures in the SOC function, respectively using the determination methods of a, b, c and d to obtain a, b, c and d of different SOC points and temperatures, and then using formula (3) to determine k1~k6。
The power SOP of the battery may be determined according to the following equation (4):
wherein, IpTo predict the predicted current at power SOP of the battery, tpIs a predicted time when predicting the power SOP of the battery.
Fig. 2 is a schematic flowchart of a battery state prediction method based on the equivalent circuit model shown in fig. 1 according to an embodiment of the present invention.
Referring to fig. 2, the state prediction method includes:
the open circuit voltage is determined based on a correspondence between the open circuit voltage and a state of charge function, the polarization voltage is determined according to a first functional relationship model of voltage to current and time; wherein the parameters of the first functional relationship model are determined based on a second functional relationship model between the state of charge function and the battery temperature; the power of the battery is determined according to the terminal voltage and the current;
and 203, predicting one or more future states of the battery based on the current state of charge function and the current battery temperature, and the open-circuit voltage and the polarization voltage.
Specifically, in step 201, the established equivalent circuit model of the battery is as shown in fig. 1, and the determining manner of the open-circuit voltage and the polarization voltage and the formulas of the first functional relationship model and the second functional relationship model may be according to the description of the embodiment described in fig. 1, and are not repeated here.
Then, the equivalent circuit model and the equations (1) to (4) can predict one or more future states of the battery. The current state of charge function and the current battery temperature are obtained as described in step 202. Predicting one or more future states of the battery based on the current state of charge function and current battery temperature, and the open circuit voltage and the polarization voltage, as set forth in step 203.
The specific process of predicting the future state of the battery is described below with reference to specific embodiments.
1. Predicting a certain current (i.e., predicted current), terminal voltage of battery at a certain time (i.e., predicted time), and power of battery
The prediction method comprises the following steps:
step 1.1, determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature.
The second functional relationship model is shown as the above formula (3):
wherein SOC is the current state of charge function, T is the current battery temperature, k1~k6Is a coefficient; in the manner described above, according to different k1~k6Determines parameters a, b, c and d of the first functional relationship model, respectively.
And 1.2, determining the predicted current and the polarization voltage under the predicted time according to the first function relation model.
The first functional relationship model is as shown in the above formula (2):
Uop=aln2(t|I|)+bln(t|I|)+cI+d;
wherein, UopThe polarization voltage, the predicted current, the predicted time and the parameters of the first functional relation model are respectively denoted by I, t, a, b, c and d. The polarization voltage U can be predicted by substituting the parameters a, b, c and d determined in the step 1.1 into the formula (2)op。
And 1.3, determining the open-circuit voltage under the predicted current and the predicted time according to the corresponding relation between the open-circuit voltage and the current state of charge function.
In particular, the open circuit voltage UocvCan be obtained according to the corresponding relation between the open-circuit voltage and the current state of charge function.
And 1.4, predicting the terminal voltage based on the predicted current and the polarization voltage and the open-circuit voltage under the predicted time.
Specifically, according to the above formula (1), the polarization voltages U predicted according to the above step 1.2 are respectivelyopAnd the open circuit voltage U predicted according to the above step 1.3ocvSubstituting into formula (1) to obtain the terminal voltage
And step 1.5, predicting the power of the battery under the predicted current and predicted time based on the terminal voltage and the predicted current.
Specifically, the predicted current is substituted into I in formula (4) according to formula (4) abovepSubstituting the predicted time into t in the formula (4)pThe power SOP of the battery at a certain current (i.e. predicted current) and a certain time (i.e. predicted time) can be predicted.
2. The method for predicting the time required for the battery to reach the cut-off voltage at a certain current (i.e., the predicted current) comprises the following steps:
and 2.1, determining parameters of the first functional relation model based on a second functional relation model between the current state of charge function and the current battery temperature.
The second functional relationship model is shown as the above formula (3):
wherein SOC is the current state of charge function, T is the current battery temperature, k1~k6Is a coefficient; in the manner described above, according to different k1~k6Determines parameters a, b, c and d of the first functional relationship model, respectively.
And 2.2, determining the open-circuit voltage under the predicted current according to the corresponding relation between the open-circuit voltage and the current state of charge function.
In particular, the open circuit voltage UocvCan be obtained according to the corresponding relation between the open-circuit voltage and the current state of charge function.
Step 2.3, setting upper limit cut-off voltage or lower limit cut-off voltageAnd based on the predicted current according to the following formula: u shapemax/min-Uocv=aln2(tmax|I|)+bln(tmaxL I |) + cI + d predicts the time t required for the battery to reach the upper limit cutoff voltage or the lower limit cutoff voltage under the prediction currentmax(ii) a Wherein, UocvIs open circuit voltage, is current, and a, b, c and d are parameters of the first functional relationship model respectively.
Specifically, the upper cutoff voltage UmaxThe cut-off voltage reached by the corresponding battery during charging; the lower limit cut-off voltage UminCorresponding to the cut-off voltage reached by the battery during discharge.
Will UmaxOr UminAnd the open-circuit voltage U predicted and obtained according to the step 2.2ocvThe predicted current I and the parameters a, b, c and d of the first functional relation model are substituted into the following formula:
Umax/min-Uocv=aln2(tmax|I|)+bln(tmax|I|)+cI+d
thereby predicting the time t required for the battery to reach the cutoff voltage (upper cutoff voltage or lower cutoff voltage) at a certain current (i.e., predicted current)max。
3. Predicting a maximum current at which a battery reaches a cut-off voltage within a certain time (i.e., a predicted time) and a maximum power of the battery within the predicted time
The prediction method comprises the following steps:
and 3.1, determining parameters of the first functional relation model based on a second functional relation model between the current state of charge function and the current battery temperature.
The second functional relationship model is shown as the above formula (3):
wherein SOC is the current state of charge function, T is the current battery temperature, k1~k6Is a coefficient; in the manner described above, according to different k1~k6Determines parameters a, b, c and d of the first functional relationship model, respectively.
And 3.2, determining the open-circuit voltage at the predicted time according to the corresponding relation between the open-circuit voltage and the current state of charge function.
In particular, the open circuit voltage UocvCan be obtained according to the corresponding relation between the open-circuit voltage and the current state of charge function.
And 3.3, setting an upper limit cut-off voltage or a lower limit cut-off voltage, and based on the predicted time, according to the following formula: u shapemax/min-Uocv=aln2(t|Imax|)+bln(t|Imax|)+cImax+ d predicting the maximum current I at which the battery reaches the upper or lower cutoff voltage within the predicted timemax(ii) a Wherein U ismax/minIs an upper cut-off voltage or a lower cut-off voltage, UocvThe open-circuit voltage is represented, t is time, and a, b, c and d are parameters of the first functional relation model respectively.
Specifically, the upper cutoff voltage UmaxThe cut-off voltage reached by the corresponding battery during charging; the lower limit cut-off voltage UminCorresponding to the cut-off voltage reached by the battery during discharge.
Will UmaxOr UminAnd the open-circuit voltage U predicted and obtained according to the step 2.2ocvThe predicted time t and the parameters a, b, c and d of the first functional relation model are substituted into the following formula:
Umax/min-Uocv=aln2(t|Imax|)+bln(t|Imax|)+cImax+d
thereby predicting the maximum current I when the battery reaches the cut-off voltage (upper cut-off voltage or lower cut-off voltage) within a certain time (i.e. predicted time)max。
Step 3.4, based on the maximum current ImaxAnd the upper limit cut-off voltage or the lower limit cut-off voltage Umax/minPredicting a maximum power of the battery over the predicted time.
In particular, the cutoff voltage U is dependent on the upper limitmaxAnd the maximum current ImaxThe maximum power SOP (U) corresponding to the upper limit cut-off voltage can be predictedmax×Imax(ii) a Cut-off voltage U according to lower limitminAnd the maximum current ImaxThe maximum power SOP ═ U corresponding to the lower cutoff voltage can be predictedmin×Imax。
Fig. 3 is a schematic structural diagram of an embodiment of a device for predicting a state of a battery according to an embodiment of the present invention.
Referring to fig. 3, the state prediction apparatus 3 includes: the model establishing module 31 is configured to establish an equivalent circuit model of the battery, and the terminal voltage of the battery is determined according to the open-circuit voltage and the polarization voltage of the equivalent circuit model. The open circuit voltage is determined based on a correspondence between the open circuit voltage and a state of charge function, the polarization voltage is determined according to a first functional relationship model of voltage to current and time; wherein the parameters of the first functional relationship model are determined based on a second functional relationship model between the state of charge function and the battery temperature; the power of the battery is determined based on the terminal voltage and the current. And the parameter acquisition module 32 is used for acquiring the current state of charge function and the current battery temperature. A prediction module 33 for predicting one or more future states of the battery based on the current state of charge function and the current battery temperature, and the open circuit voltage and the polarization voltage.
Wherein the prediction module 33 is further configured to: determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature; wherein the second functional relationship model isSOC is the current state of charge function, T is the current battery temperature, k1~k6Is a coefficient; according to different k1~k6Respectively determine the coefficient combinations ofAnd determining parameters of the first functional relation model. Determining a predicted current and a polarization voltage under a predicted time according to the first functional relation model; wherein the first functional relationship model is Uop=aln2(t | I |) + bln (t | I |) + cI + d; wherein, UopThe polarization voltage, the predicted current, the predicted time and the parameters of the first functional relation model are respectively denoted by I, t, a, b, c and d. And determining the open-circuit voltage under the predicted current and the predicted time according to the corresponding relation between the open-circuit voltage and the current state of charge function. Predicting the terminal voltage based on the predicted current and the polarization voltage and the open circuit voltage at the predicted time. And predicting the power of the battery at the predicted current and predicted time based on the terminal voltage and the predicted current.
The prediction module 33 is further configured to: determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature; wherein the second functional relationship model isT is the current battery temperature, k1~k6Is a coefficient; according to different k1~k6Respectively determine parameters of the first functional relationship model. And determining the open-circuit voltage under the predicted current according to the corresponding relation between the open-circuit voltage and the current state of charge function. Setting an upper cutoff voltage or a lower cutoff voltage, and based on the predicted current, according to the following formula: u shapemax/min-Uocv=aln2(tmax|I|)+bln(tmaxL I |) + cI + d predicts the time t required for the battery to reach the upper limit cutoff voltage or the lower limit cutoff voltage under the prediction currentmax(ii) a Wherein, UocvThe open-circuit voltage is represented, the predicted current is represented by I, and the parameters of the first functional relation model are represented by a, b, c and d respectively.
The prediction module 33 is further configured to: determining the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperatureThe parameters of (1); wherein the second functional relationship model isT is the current battery temperature, k1~k6Is a coefficient; according to different k1~k6Respectively determine parameters of the first functional relationship model. And determining the open-circuit voltage at the predicted time according to the corresponding relation between the open-circuit voltage and the current state of charge function. Setting an upper cutoff voltage or a lower cutoff voltage, and based on the predicted time according to the following formula: u shapemax/min-Uocv=aln2(t|Imax|)+bln(t|Imax|)+cImax+ d predicting the maximum current I at which the battery reaches the upper or lower cutoff voltage within the predicted timemax(ii) a Wherein U ismax/minIs an upper cut-off voltage or a lower cut-off voltage, UocvThe open-circuit voltage is represented, t is the predicted time, and a, b, c and d are parameters of the first functional relation model respectively. Based on the maximum current ImaxAnd the upper limit cut-off voltage or the lower limit cut-off voltage Umax/minPredicting a maximum power of the battery over the predicted time.
In summary, the state prediction method for the battery adopting the technical scheme can predict the voltage of the battery at a certain time or at a certain current in the future and the SOP of the battery, and is used for solving the problem of predicting the voltage and the power of the battery with high precision so as to ensure that the battery can perform the best performance within the operation and safety interval.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (6)
1. A method for predicting a state of a battery, the method comprising:
establishing an equivalent circuit model of a battery, wherein the terminal voltage of the battery is determined according to the open-circuit voltage and the polarization voltage of the equivalent circuit model;
the open circuit voltage is determined based on a correspondence between the open circuit voltage and a state of charge function, the polarization voltage is determined according to a first functional relationship model of voltage to current and time; wherein the parameters of the first functional relationship model are determined based on a second functional relationship model between the state of charge function and the battery temperature; the power of the battery is determined according to the terminal voltage and the current;
acquiring a current state of charge function and a current battery temperature;
predicting one or more future states of the battery based on the current state of charge function and current battery temperature, and the open circuit voltage and the polarization voltage;
said predicting one or more future states of said battery based on said current state of charge function and current battery temperature, and said open circuit voltage and said polarization voltage comprises:
determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature;
determining a predicted current and a polarization voltage under a predicted time according to the first functional relation model;
determining the open-circuit voltage under the predicted current and the predicted time according to the corresponding relation between the open-circuit voltage and the current state of charge function;
predicting the terminal voltage based on the predicted current and the polarization voltage and the open circuit voltage at the predicted time;
predicting the power of the battery at the predicted current and predicted time based on the terminal voltage and predicted current;
wherein the first functional relationship model is Uop=aln2(t|I|)+bln(t|I|)+cI+d;UopThe polarization voltage, the predicted current, the predicted time and the parameters of a, b, c and d are respectively the parameters of the first functional relation model; the second functional relationship model isSOC is the current state of charge function, T is the current battery temperature, k1~k6Is a coefficient; f (SOC, T) is the values of the parameters a, b, c and d of the first functional relation model, and the f (SOC, T) respectively corresponds to different k 1-k 6 when the f (SOC, T) is a, b, c and d.
2. The method of claim 1, wherein predicting one or more future states of the battery based on the current state of charge function and current battery temperature, and the open circuit voltage and the polarization voltage comprises:
determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature; wherein the second functional relationship model isT is the current battery temperature, k1~k6Is a coefficient; according to different k1~k6Determining parameters of the first functional relationship model respectively;
determining the open-circuit voltage under the predicted current according to the corresponding relation between the open-circuit voltage and the current state of charge function;
setting an upper cutoff voltage or a lower cutoff voltage, and based on the predicted current, according to the following formula: u shapemax/min-Uocv=aln2(tmax|I|)+bln(tmaxL I |) + cI + d predicts the time t required for the battery to reach the upper limit cutoff voltage or the lower limit cutoff voltage under the prediction currentmax(ii) a Wherein, UocvThe open-circuit voltage is represented, the predicted current is represented by I, and the parameters of the first functional relation model are represented by a, b, c and d respectively.
3. The method of claim 1, wherein predicting one or more future states of the battery based on the current state of charge function and current battery temperature, and the open circuit voltage and the polarization voltage comprises:
determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature; wherein the second functional relationship model isT is the current battery temperature, k1~k6Is a coefficient; according to different k1~k6Determining parameters of the first functional relationship model respectively;
determining the open-circuit voltage at the predicted time according to the corresponding relation between the open-circuit voltage and the current state of charge function;
setting an upper cutoff voltage or a lower cutoff voltage, and based on the predicted time according to the following formula: u shapemax/min-Uocv=aln2(t|Imax|)+bln(t|Imax|)+cImax+ d predicting the maximum current I at which the battery reaches the upper or lower cutoff voltage within the predicted timemax(ii) a Wherein U ismax/minIs an upper cut-off voltage or a lower cut-off voltage, UocvIs open circuit voltage, t is predicted time, a, b, c and d are the firstParameters of the functional relationship model;
based on the maximum current ImaxAnd the upper limit cut-off voltage or the lower limit cut-off voltage Umax/minPredicting a maximum power of the battery over the predicted time.
4. A state prediction apparatus for a battery, comprising:
the model establishing module is used for establishing an equivalent circuit model of the battery, and the terminal voltage of the battery is determined according to the open-circuit voltage and the polarization voltage of the equivalent circuit model;
the open circuit voltage is determined based on a correspondence between the open circuit voltage and a state of charge function, the polarization voltage is determined according to a first functional relationship model of voltage to current and time; wherein the parameters of the first functional relationship model are determined based on a second functional relationship model between the state of charge function and the battery temperature; the power of the battery is determined according to the terminal voltage and the current;
the parameter acquisition module is used for acquiring a current state of charge function and a current battery temperature;
a prediction module for predicting one or more future states of the battery based on the current state of charge function and current battery temperature, and the open circuit voltage and the polarization voltage;
the prediction module is further configured to:
determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature;
determining a predicted current and a polarization voltage under a predicted time according to the first functional relation model;
determining the open-circuit voltage under the predicted current and the predicted time according to the corresponding relation between the open-circuit voltage and the current state of charge function;
predicting the terminal voltage based on the predicted current and the polarization voltage and the open circuit voltage at the predicted time;
predicting the power of the battery at the predicted current and predicted time based on the terminal voltage and predicted current;
wherein the first functional relationship model is: u shapeop=aln2(t|I|)+bln(t|I|)+cI+d;UopThe polarization voltage, the predicted current, the predicted time and the parameters of a, b, c and d are respectively the parameters of the first functional relation model; the second functional relationship model isSOC is the current state of charge function, T is the current battery temperature, k1~k6Is a coefficient; f (SOC, T) is the values of the parameters a, b, c and d of the first functional relation model, and the f (SOC, T) respectively corresponds to different k 1-k 6 when the f (SOC, T) is a, b, c and d.
5. The apparatus of claim 4, wherein the prediction module is further to:
determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature; wherein the second functional relationship model isT is the current battery temperature, k1~k6Is a coefficient; according to different k1~k6Determining parameters of the first functional relationship model respectively;
determining the open-circuit voltage under the predicted current according to the corresponding relation between the open-circuit voltage and the current state of charge function;
setting an upper cutoff voltage or a lower cutoff voltage, and based on the predicted current, according to the following formula: u shapemax/min-Uocv=aln2(tmax|I|)+bln(tmaxL I |) + cI + d predicts the time t required for the battery to reach the upper limit cutoff voltage or the lower limit cutoff voltage under the prediction currentmax(ii) a Wherein, UocvFor open circuit voltage, I for predicted voltageAnd the flow, a, b, c and d are parameters of the first functional relation model respectively.
6. The apparatus of claim 4, wherein the prediction module is further to:
determining parameters of the first functional relationship model based on a second functional relationship model between the current state of charge function and the current battery temperature; wherein the second functional relationship model isT is the current battery temperature, k1~k6Is a coefficient; according to different k1~k6Determining parameters of the first functional relationship model respectively;
determining the open-circuit voltage at the predicted time according to the corresponding relation between the open-circuit voltage and the current state of charge function;
setting an upper cutoff voltage or a lower cutoff voltage, and based on the predicted time according to the following formula: u shapemax/min-Uocv=aln2(t|Imax|)+bln(t|Imax|)+cImax+ d predicting the maximum current I at which the battery reaches the upper or lower cutoff voltage within the predicted timemax(ii) a Wherein U ismax/minIs an upper cut-off voltage or a lower cut-off voltage, UocvThe open-circuit voltage is used, t is the predicted time, and a, b, c and d are parameters of the first functional relation model respectively;
based on the maximum current ImaxAnd the upper limit cut-off voltage or the lower limit cut-off voltage Umax/minPredicting a maximum power of the battery over the predicted time.
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104298793A (en) * | 2013-07-16 | 2015-01-21 | 浙江万向亿能动力电池有限公司 | Model inverse dynamic algorithm for extreme power of power battery pack |
JP2016109466A (en) * | 2014-12-02 | 2016-06-20 | 古河電気工業株式会社 | Secondary battery state detection device and secondary battery state detection method |
CN108062086A (en) * | 2017-12-08 | 2018-05-22 | 中航锂电技术研究院有限公司 | Method based on Simscape battery pack models verification battery charging and discharging control strategy |
CN108508371A (en) * | 2018-04-09 | 2018-09-07 | 重庆大学 | A kind of power battery SOC/SOH/SOP combined estimation methods based on equivalent-circuit model |
CN111025172A (en) * | 2019-12-31 | 2020-04-17 | 国联汽车动力电池研究院有限责任公司 | Method for realizing rapid measurement of maximum allowable power of charging and discharging of lithium ion battery |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP5379672B2 (en) * | 2009-12-25 | 2013-12-25 | プライムアースEvエナジー株式会社 | Secondary battery polarization voltage calculation device and charging state estimation device |
-
2019
- 2019-12-31 CN CN201911411201.XA patent/CN111025156B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104298793A (en) * | 2013-07-16 | 2015-01-21 | 浙江万向亿能动力电池有限公司 | Model inverse dynamic algorithm for extreme power of power battery pack |
JP2016109466A (en) * | 2014-12-02 | 2016-06-20 | 古河電気工業株式会社 | Secondary battery state detection device and secondary battery state detection method |
CN108062086A (en) * | 2017-12-08 | 2018-05-22 | 中航锂电技术研究院有限公司 | Method based on Simscape battery pack models verification battery charging and discharging control strategy |
CN108508371A (en) * | 2018-04-09 | 2018-09-07 | 重庆大学 | A kind of power battery SOC/SOH/SOP combined estimation methods based on equivalent-circuit model |
CN111025172A (en) * | 2019-12-31 | 2020-04-17 | 国联汽车动力电池研究院有限责任公司 | Method for realizing rapid measurement of maximum allowable power of charging and discharging of lithium ion battery |
Non-Patent Citations (5)
Title |
---|
Adaptive unscented Kalman filter based state of energy and power capability estimation approach for lithium-ion battery;Weige Zhang,Wei Shi,Zeyu Ma;《Journal of Power Sources》;20150930;50-62 * |
Model-based dynamic multi-parameter method for peak power estimation of lithium–ion batteries;Fengchun Sun et al;《Applied Energy》;20120831;378-386 * |
动力电池组峰值功率估计算法研究;张彩萍,张承宁,李军求;《系统仿真学报》;20100630;1524-1527 * |
基于阻抗电流模型的锂离子电池峰值功率估计;周宇欣等;《重庆理工大学学报(自然科学)》;20200630;9-17 * |
电池在线功率状态估算方法的研究;谢聪;《中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅱ辑》;20190715;全文 * |
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