CN113466728A - Method and system for online identification of parameters of two-stage battery model - Google Patents
Method and system for online identification of parameters of two-stage battery model Download PDFInfo
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Abstract
The invention provides a method for identifying parameters of a two-stage battery model on line, which comprises the steps of firstly, sequentially dividing the accumulated charge/discharge amount percentage of each moment according to the charge/discharge time of a battery to be tested to obtain the accumulated charge/discharge amount percentage of any moment in each time period; then obtaining the open-circuit voltage at any time in the current time period and a system state equation in the current time period according to the open-circuit voltage at the initial time; and finally, analyzing the system state equation in the current time period to obtain the battery model parameters in the current time period. According to the invention, the open-circuit voltage at the ending moment in the current time period is used as the open-circuit voltage at the initial moment in the next time period, and the model parameters of each time period are identified by applying a recursion method, so that the model parameter change caused by battery aging can be corrected, and the accuracy of the whole period calculation is ensured. The invention also provides a two-stage battery model parameter online identification system.
Description
Technical Field
The invention belongs to the technical field of battery model parameter identification, and particularly relates to a two-stage battery model parameter online identification method and system.
Background
In recent years, with the development of new national energy and the improvement of power supply reliability, an energy storage power station for storing electric power by using an ultra-large battery pack is taken as a support technology of an intelligent power grid and internet intelligent energy, and rapid development is achieved. The lithium ion battery has the remarkable advantages of high stability, large capacity, long service life, environmental friendliness and the like, and is widely applied to energy storage power stations. The lithium ion battery internal resistance, the polarization capacitor and the polarization network voltage are key parameters for representing the battery health state, and the online parameter identification of the battery of the energy storage power station is necessary for ensuring the safe operation of the battery in the energy storage power station and carrying out effective energy management and state evaluation.
The idea of battery model parameter identification is essentially to estimate the terminal voltage based on the circuit equation by using the data of current, voltage, temperature and the like measured in real time by the battery, correct the model parameters according to the error of the estimated battery terminal voltage and the measured terminal voltage, and gradually reduce the estimation deviation so that the estimated model parameters converge to the true value.
The current testing method for the internal resistance of the battery mainly comprises the following steps: open circuit voltage method, direct current discharge method and alternating current test method. The open-circuit voltage method estimates the internal resistance through the voltage of the battery, but the precision is obviously reduced under the condition of insufficient battery; the direct current discharge method is to inject a large constant direct current into the battery, measure the voltage at two ends of the battery, and calculate the current internal resistance by using the current voltage and current; the alternating current test method is to calculate the internal resistance by obtaining the voltage at two ends of the battery by using low-frequency alternating current.
The internal resistance is one of important indexes of the service state of the battery, the ohmic internal resistance and the polarization internal resistance are accurately identified and calculated, the degradation degree of the battery of the energy storage station can be found in time, and the accident potential is reduced to the minimum. The direct current discharge method is used for measuring the internal resistance when the battery is in a static state or off-line state, and the battery needs to be charged immediately after the test is finished, so that the online test cannot be carried out. Although the alternating current test method can carry out online test, potential safety hazards cannot be generated, the alternating current test cannot be finished well obviously when the charging state of the battery is required to be changed in the energy storage power station; in addition, the alternating current test method is designed to remove noise of ripple current and other interference on a circuit, and execution difficulty is greatly increased.
The traditional RLS method generally simplifies the assumption that the open-circuit voltage in a unit sampling interval is not changed, so that the identification accuracy is influenced, and the description of the open-circuit voltage change needs to be enhanced. In the conventional method for determining the open-circuit voltage, the SOC is obtained by an ampere-hour integration method, and then the corresponding ocv is obtained by searching an SOC-ocv table. Due to the nonlinearity of the SOC-ocv curve, if the analytic expression needs polynomials of 6 th degree, the number of identification parameters is greatly increased, and the difficulty of online identification is increased. And the SOC-ocv curves for different cells vary and change as the cell ages, further increasing the complexity and difficulty of the problem.
Disclosure of Invention
The invention aims to provide a method and a system for identifying parameters of a two-stage battery model on line, and aims to solve the problems of low accuracy of the parameters of the battery model calculated by the conventional battery parameter identification method and complex calculation process.
In order to achieve the purpose, the invention adopts the technical scheme that: a method for online identification of parameters of a two-stage battery model comprises the following steps:
step 1: acquiring continuous charging/discharging data of a battery to be tested;
step 2: obtaining the accumulated charge/discharge amount percentage at each moment according to the continuous charge/discharge data of the battery to be tested;
and step 3: sequentially dividing the accumulated charge/discharge amount percentage at each moment according to the charge/discharge time of the battery to be tested to obtain the accumulated charge/discharge amount percentage at any moment in each time period;
and 4, step 4: acquiring the open-circuit voltage of the initial moment in the current time period;
and 5: obtaining the open-circuit voltage at any time in the current time period according to the open-circuit voltage at the initial time;
step 6: obtaining a system state equation in the current time period according to the open-circuit voltage at any moment in the current time period and the accumulated charge/discharge amount percentage at each moment;
and 7: analyzing the system state equation in the current time period to obtain a battery model parameter in the current time period;
and 8: and taking the open-circuit voltage at the ending moment in the current time period as the open-circuit voltage at the initial moment in the next time period, and returning to the step 4.
Preferably, the step 2: obtaining the accumulated charge/discharge capacity percentage at each moment according to the continuous charge/discharge data of the battery to be tested, wherein the accumulated charge/discharge capacity percentage comprises the following steps:
integrating current data in the continuous charging/discharging data of the battery to be tested by using an ampere-hour integration method to obtain the accumulated charging/discharging amount percentage at each moment; wherein the cumulative charge/discharge amount percentage at each time is:
wherein, CkRepresenting the percentage of the cumulative charge/discharge at time k, Δ t being the data sampling step, IL,kCurrent at time k, CratedThe rated capacity of the battery.
Preferably, the open circuit voltage at any time in the current time period is:
wherein, UocvRepresenting the open circuit voltage of the battery, P representing the proportionality coefficient, SOC representing the state of charge of the battery, Uocv，kRepresenting the open circuit voltage of the cell at time k,
representing the open circuit voltage at the initial instant in the current time period.
Preferably, the step 6: obtaining a system state equation in the current time period according to the open-circuit voltage at any moment in the current time period and the accumulated charge/discharge amount percentage at each moment, wherein the system state equation comprises:
step 6.1: constructing a transfer function of a first-order RC circuit model of the battery by using the first-order circuit model; wherein the transfer function is:
wherein, IL(s) represents a current, R0Indicating the ohmic internal resistance, R1Indicating internal resistance to polarization, C1Representing the polarization capacitance, s represents the mapping of the time variable t in the frequency domain;
step 6.2: obtaining a battery terminal voltage formula in the current time period according to the transfer function and the open-circuit voltage at any time in the current time period;
step 6.3: and obtaining a system state equation in the current time period according to the battery terminal voltage formula in the current time period.
Preferably, the formula of the battery terminal voltage in the current time period is as follows:
wherein, Ut,kRepresenting the battery terminal voltage at time k in the current time period, c1Representing the first coefficient to be solved, c2Representing the second coefficient to be solved, c3Representing the coefficient to be solved for, Ut,k-1Representing the terminal voltage of the battery at time k-1 in the current time period, IL,kRepresenting the current at time k in the current time period, IL,k-1Representing the current at time k-1 during the current time period.
Preferably, the system state equation in the current time period is:
yk＝ΦkΘk
wherein phikRepresenting a data matrix, ΘkA parameter matrix is represented.
Preferably, the step 7: analyzing the system state equation in the current time period to obtain the battery model parameters in the current time period, wherein the method comprises the following steps:
step 7.1: identifying a parameter matrix by using a least square recursion method according to the system state equation in the current time period to obtain an identification result;
step 7.2: and adopting a formula according to the identification result:
and obtaining the battery model parameters in the current time period.
The invention also provides a two-stage battery model parameter online identification system, which comprises:
the charging/discharging data acquisition module is used for acquiring continuous charging/discharging data of the battery to be tested;
the accumulated charge/discharge capacity percentage calculation module is used for obtaining the accumulated charge/discharge capacity percentage at each moment according to the continuous charge/discharge data of the battery to be tested;
the charge/discharge data dividing module is used for sequentially dividing the accumulated charge/discharge amount percentage at each moment according to the charge/discharge time of the battery to be tested to obtain the accumulated charge/discharge amount percentage at any moment in each time period;
the initial time open-circuit voltage acquisition module is used for acquiring the open-circuit voltage of the initial time in the current time period;
the open-circuit voltage calculation module is used for obtaining the open-circuit voltage at any moment in the current time period according to the open-circuit voltage at the initial moment;
the system state equation building module is used for obtaining a system state equation in the current time period according to the open-circuit voltage at any time in the current time period and the accumulated charge/discharge amount percentage at each time;
the battery model parameter calculation module is used for analyzing the system state equation in the current time period to obtain battery model parameters in the current time period;
and the returning module is used for returning the open-circuit voltage at the ending moment in the current time period to the initial moment obtaining module by taking the open-circuit voltage at the ending moment in the next time period as the open-circuit voltage at the initial moment.
The two-stage battery model parameter online identification method and the two-stage battery model parameter online identification system have the advantages that: compared with the prior art, the method for identifying the parameters of the two-stage battery model on line comprises the steps of firstly obtaining the accumulated charge/discharge amount percentage at each moment according to the continuous charge/discharge data of the battery to be tested; sequentially dividing the accumulated charge/discharge amount percentage at each moment according to the charge/discharge time of the battery to be tested to obtain the accumulated charge/discharge amount percentage at any moment in each time period; then obtaining the open-circuit voltage at any time in the current time period and a system state equation in the current time period according to the open-circuit voltage at the initial time; and finally, analyzing the system state equation in the current time period to obtain the battery model parameters in the current time period. According to the invention, the open-circuit voltage at the ending moment in the current time period is used as the open-circuit voltage at the initial moment in the next time period, and the model parameters of each time period are identified by applying a recursion method, so that the model parameter change caused by battery aging can be corrected, and the accuracy of the whole period calculation is ensured.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed for the embodiments or the prior art descriptions 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 without creative efforts.
Fig. 1 is a flowchart of a two-stage battery model parameter online identification method according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a two-stage battery model parameter online identification method according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a first-order circuit model according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention aims to provide a method and a system for identifying parameters of a two-stage battery model on line, and aims to solve the problems of low accuracy of the parameters of the battery model calculated by the conventional battery parameter identification method and complex calculation process.
Referring to fig. 1-2, to achieve the above object, the present invention adopts the following technical solutions: a method for online identification of parameters of a two-stage battery model comprises the following steps:
s1: acquiring continuous charging/discharging data of a battery to be tested;
the battery internal resistance calculation method comprises the steps of constructing a data vector through data such as battery voltage, current and temperature, considering that in a shorter SOC interval, an ocv-SOC curve can be approximate to a straight line, and the variation of ocv is in direct proportion to the variation of SOC; based on the assumption, a battery model parameter identification method is provided.
S2: obtaining the accumulated charge/discharge amount percentage at each moment according to the continuous charge/discharge data of the battery to be tested;
s2 includes:
integrating current data in continuous charging/discharging data of the battery to be tested by using an ampere-hour integration method to obtain the accumulated charging/discharging amount percentage at each moment; wherein the cumulative charge/discharge amount percentage at each time is:
wherein, CkRepresenting the percentage of the cumulative charge/discharge at time k, Δ t being the data sampling step, IL,kCurrent at time k, CratedThe rated capacity of the battery.
In practical application, firstly, continuous charge/discharge data of the battery is selected, and current data is integrated by using an ampere-hour integration method to obtain the accumulated charge/discharge capacity percentage C at each moment k from the initial momentkAnd is used for representing the variation of the SOC.
S3: sequentially dividing the accumulated charge/discharge amount percentage at each moment according to the charge/discharge time of the battery to be tested to obtain the accumulated charge/discharge amount percentage at any moment in each time period;
in the invention, a plurality of data segments can be obtained by segment division based on the charge and discharge amount percentage, the capacity of a single data segment is 5-10% of the nominal capacity of the battery, and the length of the interval is slightly short (such as 5% of the nominal capacity) due to large parameter change of a battery model in a low SOC interval; the parameter variation of the high SOC interval is not large, and the interval length can be slightly longer. And for each data segment (the percentage of the accumulated charge/discharge amount at any time in each time period), performing parameter identification by using a least square recursion method.
S4: acquiring the open-circuit voltage of the initial moment in the current time period;
s5: obtaining the open-circuit voltage at any moment in the current time period according to the open-circuit voltage at the initial moment;
the open circuit voltage at any time in the current time period is as follows:
wherein, UocvRepresenting the open circuit voltage of the battery, P representing the proportionality coefficient, SOC representing the state of charge of the battery, Uocv，kRepresenting the open circuit voltage of the cell at time k,
representing the open circuit voltage at the initial instant in the current time period.
Specifically, the initial value of the open-circuit voltage at the time when k is 0 is given
Since it can be approximately considered in the data segment
(where P is constant within a data segment), so the open circuit voltage at any time is
S6: obtaining a system state equation in the current time period according to the open-circuit voltage at any moment in the current time period and the accumulated charge/discharge amount percentage at each moment;
s6 includes:
s6.1: constructing a transfer function of a first-order RC circuit model of the battery by using the first-order circuit model;
in the present invention, a first-order circuit model is shown in fig. 3, and all characteristic parameters of the circuit model can be described as: ohmic internal resistance R0Polarization resistance R1,C1Current I ofLOpen circuit voltage U of batteryocvTerminal voltage U of batterytVoltage of polarization network U1The ohmic internal resistance is formed by electrode material, diaphragm and contact partThe polarized impedance is formed by polarization when the anode and cathode react with each other. The differential equation of the model is:
discretizing the differential equation of the model to obtain:
U1,k+1＝D·U1,k+(1-D)·IL,k·R1
Uocv,k+1＝Ut,k+1+U1,k+1+IL,k+1·R0
wherein D ═ exp (- Δ t/R)1·C1) For data of fixed step size, it can be considered as a constant.
Definition EL(s)＝Ut(s)-Uocv(s) obtaining a transfer function of the system in a frequency domain by performing a Laplace transform, wherein the transfer function of the first-order RC circuit model is as follows:
wherein, IL(s)Represents the current, R0Indicating the ohmic internal resistance, R1Indicating internal resistance to polarization, C1Representing the polarization capacitance and s represents the mapping of the time variable t in the frequency domain.
S6.2: obtaining a battery terminal voltage formula in the current time period according to the transfer function and the open-circuit voltage at any time in the current time period;
specifically, the transfer function is first converted into a discrete time sequence through bilinear transformation, so as to obtain:
EL,k＝c1EL,k-1+c2IL,k+c3IL,k-1
further processing to obtain:
Ut,k＝Uocv,k-c1Uocv,k-1+c1Ut,k-1+c2IL,k+c3IL,k-1
and finally, obtaining the battery terminal voltage formula in the current time period by combining the open-circuit voltage value mapped by ampere-hour integral:
wherein, Ut,kRepresenting the battery terminal voltage at time k in the current time period, c1Is represented by c2Is represented by c3Represents, Ut,k-1Representing the terminal voltage of the battery at time k-1 in the current time period, IL,kRepresenting the current at time k in the current time period, IL,k-1Representing the current at time k-1 during the current time period.
S6.3: and considering that the voltage and current data have sampling time intervals under the actual working condition, obtaining a discretization system state equation in the current time period according to the battery terminal voltage formula in the current time period.
The system state equation in the current time period is as follows:
yk＝ΦkΘk
wherein phikRepresenting a data matrix, ΘkA parameter matrix is represented.
S7: analyzing a system state equation in the current time period to obtain a battery model parameter in the current time period;
s7 includes:
s7.1: identifying the parameter matrix by using a least square recursion method according to a system state equation in the current time period to obtain an identification result;
s7.2: and adopting a formula according to the identification result:
and obtaining the parameters of the battery model in the current time period.
In the present invention, S1-S7 are the first stage recursions of the present invention.
S8: the open circuit voltage at the end time in the current time period is set as the open circuit voltage at the initial time in the next time period, and the process returns to S4.
The second stage of the present invention recurs as: according to the method (S4-S7), model parameters of each data segment are identified by applying a recursive algorithm, wherein the initial open-circuit voltage value of each segment is the open-circuit voltage value at the end of the segment obtained by the last data segment according to the identified model parameters, that is:
By the method, the identification result of the previous segment can be continuously inherited, the deviation can be gradually corrected, and the accurate battery model parameters in each time segment can be obtained.
Compared with the prior art, the calculation method for optimizing the battery parameters reduces the iteration times of calculation, improves the real-time performance of calculation, and can ensure the precision of model calculation at the same time.
The invention also provides a two-stage battery model parameter online identification system, which comprises:
the charging/discharging data acquisition module is used for acquiring continuous charging/discharging data of the battery to be tested;
the accumulated charge/discharge capacity percentage calculation module is used for obtaining the accumulated charge/discharge capacity percentage at each moment according to the continuous charge/discharge data of the battery to be tested;
the charge/discharge data dividing module is used for sequentially dividing the accumulated charge/discharge amount percentage at each moment according to the charge/discharge time of the battery to be tested to obtain the accumulated charge/discharge amount percentage at any moment in each time period;
the initial time open-circuit voltage acquisition module is used for acquiring the open-circuit voltage of the initial time in the current time period;
the open-circuit voltage calculation module is used for obtaining the open-circuit voltage at any moment in the current time period according to the open-circuit voltage at the initial moment;
the system state equation building module is used for obtaining a system state equation in the current time period according to the open-circuit voltage at any time in the current time period and the accumulated charge/discharge amount percentage at each time;
the battery model parameter calculation module is used for analyzing a system state equation in the current time period to obtain battery model parameters in the current time period;
and the return module is used for taking the open-circuit voltage at the ending moment in the current time period as the open-circuit voltage at the initial moment in the next time period and returning to the initial moment open-circuit voltage acquisition module.
The invention discloses a method and a system for identifying parameters of a two-stage battery model on line, and the method for identifying the parameters of the two-stage battery model on line comprises the steps of firstly obtaining the accumulated charge/discharge amount percentage at each moment according to continuous charge/discharge data of a battery to be tested; sequentially dividing the accumulated charge/discharge amount percentage at each moment according to the charge/discharge time of the battery to be tested to obtain the accumulated charge/discharge amount percentage at any moment in each time period; then obtaining the open-circuit voltage at any time in the current time period and a system state equation in the current time period according to the open-circuit voltage at the initial time; and finally, analyzing the system state equation in the current time period to obtain the battery model parameters in the current time period. According to the invention, the open-circuit voltage at the ending moment in the current time period is used as the open-circuit voltage at the initial moment in the next time period, and the model parameters of each time period are identified by applying a recursion method, so that the model parameter change caused by battery aging can be corrected, and the accuracy of the whole period calculation is ensured.
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 and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (8)
1. A method for online identification of parameters of a two-stage battery model is characterized by comprising the following steps:
step 1: acquiring continuous charging/discharging data of a battery to be tested;
step 2: obtaining the accumulated charge/discharge amount percentage at each moment according to the continuous charge/discharge data of the battery to be tested;
and step 3: sequentially dividing the accumulated charge/discharge amount percentage at each moment according to the charge/discharge time of the battery to be tested to obtain the accumulated charge/discharge amount percentage at any moment in each time period;
and 4, step 4: acquiring the open-circuit voltage of the initial moment in the current time period;
and 5: obtaining the open-circuit voltage at any time in the current time period according to the open-circuit voltage at the initial time;
step 6: obtaining a system state equation in the current time period according to the open-circuit voltage at any moment in the current time period and the accumulated charge/discharge amount percentage at each moment;
and 7: analyzing the system state equation in the current time period to obtain a battery model parameter in the current time period;
and 8: and taking the open-circuit voltage at the ending moment in the current time period as the open-circuit voltage at the initial moment in the next time period, and returning to the step 4.
2. The method of claim 1, wherein the step 2: obtaining the accumulated charge/discharge capacity percentage at each moment according to the continuous charge/discharge data of the battery to be tested, wherein the accumulated charge/discharge capacity percentage comprises the following steps:
integrating current data in the continuous charging/discharging data of the battery to be tested by using an ampere-hour integration method to obtain the accumulated charging/discharging amount percentage at each moment; wherein the cumulative charge/discharge amount percentage at each time is:
wherein, CkRepresenting the percentage of the cumulative charge/discharge at time k, Δ t being the data sampling step, IL,kCurrent at time k, CratedThe rated capacity of the battery.
3. The method for online identification of parameters of a two-stage battery model according to claim 2, wherein the open-circuit voltage at any time in the current time period is:
wherein, UocvRepresenting the open circuit voltage of the battery, P representing the proportionality coefficient, SOC representing the state of charge of the battery, Uocv，kRepresenting the open circuit voltage of the cell at time k,
representing the open circuit voltage at the initial instant in the current time period.
4. The method of claim 3, wherein the step 6 is: obtaining a system state equation in the current time period according to the open-circuit voltage at any moment in the current time period and the accumulated charge/discharge amount percentage at each moment, wherein the system state equation comprises:
step 6.1: constructing a transfer function of a first-order RC circuit model of the battery by using the first-order circuit model; wherein the transfer function is:
wherein, IL(s)Represents the current, R0Indicating the ohmic internal resistance, R1Indicating internal resistance to polarization, C1Representing the polarization capacitance, s represents the mapping of the time variable t in the frequency domain;
step 6.2: obtaining a battery terminal voltage formula in the current time period according to the transfer function and the open-circuit voltage at any time in the current time period;
step 6.3: and obtaining a system state equation in the current time period according to the battery terminal voltage formula in the current time period.
5. The method of claim 4, wherein the formula of the battery terminal voltage in the current time period is as follows:
wherein, Ut,kRepresenting the battery terminal voltage at time k in the current time period, c1Representing the first coefficient to be solved, c2Representing the second coefficient to be solved, c3Representing the coefficient to be solved for, Ut,k-1Representing the terminal voltage of the battery at time k-1 in the current time period, IL,kRepresenting the current at time k in the current time period, IL,k-1Representing the current at time k-1 during the current time period.
6. The method of claim 5, wherein the system state equation in the current time period is:
yk＝ΦkΘk
wherein phikRepresenting a data matrix, ΘkA parameter matrix is represented.
7. The method of claim 6, wherein the step 7 is: analyzing the system state equation in the current time period to obtain the battery model parameters in the current time period, wherein the method comprises the following steps:
step 7.1: identifying a parameter matrix by using a least square recursion method according to the system state equation in the current time period to obtain an identification result;
step 7.2: and adopting a formula according to the identification result:
and obtaining the battery model parameters in the current time period.
8. A two-stage battery model parameter online identification system is characterized by comprising:
the charging/discharging data acquisition module is used for acquiring continuous charging/discharging data of the battery to be tested;
the accumulated charge/discharge capacity percentage calculation module is used for obtaining the accumulated charge/discharge capacity percentage at each moment according to the continuous charge/discharge data of the battery to be tested;
the charge/discharge data dividing module is used for sequentially dividing the accumulated charge/discharge amount percentage at each moment according to the charge/discharge time of the battery to be tested to obtain the accumulated charge/discharge amount percentage at any moment in each time period;
the initial time open-circuit voltage acquisition module is used for acquiring the open-circuit voltage of the initial time in the current time period;
the open-circuit voltage calculation module is used for obtaining the open-circuit voltage at any moment in the current time period according to the open-circuit voltage at the initial moment;
the system state equation building module is used for obtaining a system state equation in the current time period according to the open-circuit voltage at any time in the current time period and the accumulated charge/discharge amount percentage at each time;
the battery model parameter calculation module is used for analyzing the system state equation in the current time period to obtain battery model parameters in the current time period;
and the returning module is used for returning the open-circuit voltage at the ending moment in the current time period to the initial moment obtaining module by taking the open-circuit voltage at the ending moment in the next time period as the open-circuit voltage at the initial moment.
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