CN117932909A - SOC algorithm applied to energy storage system and SOC system - Google Patents
SOC algorithm applied to energy storage system and SOC system Download PDFInfo
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Abstract
The invention provides an SOC algorithm applied to an energy storage system and the SOC system, wherein the method reads the design capacity and the residual capacity of the energy storage system, initializes SOC parameters and obtains first SOC parameters; the first SOC parameters at least comprise correction coefficients, corrected SOC threshold ranges and a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures; estimating a first SOC value of the energy storage system according to an open circuit voltage method and a plurality of groups of open circuit voltage-electric quantity curve parameters at different temperatures; judging whether the first SOC value exceeds a corrected SOC threshold range according to the energy storage system mode; if yes, an open-circuit voltage-electric quantity curve is obtained according to the current temperature; if not, integrating the first SOC value and then taking the integrated first SOC value as an output result; compared with the prior art, the method and the device solve the problem that in the prior art, accuracy and reliability of a calculation result are difficult to maintain under the condition of temperature range variation.
Description
Technical Field
The invention belongs to the technical field of battery energy storage management, and particularly relates to an SOC algorithm applied to an energy storage system and an SOC system.
Background
SOC, collectively referred to as State of Charge, i.e., the remaining capacity of the battery, represents the percentage of Charge in the State of Charge of the battery. The SOC algorithm, i.e., a battery capacity estimation algorithm, is used to estimate the remaining capacity of the battery.
With the development of energy storage technology, an energy storage system plays an increasingly important role in energy storage and scheduling, and an SOC algorithm has become a key technology for evaluating the actual capacity and the actual residual electric quantity of a battery. In the conventional SOC algorithm, only basic parameters such as current and voltage parameters are usually considered during operation, and the influence of temperature on the battery performance is usually ignored, so that the accuracy and the reliability of estimation are difficult to maintain under the condition of temperature range variation.
Disclosure of Invention
The invention provides an SOC algorithm applied to an energy storage system and the SOC system, which are used for solving the problems in the prior art.
In a first aspect, to achieve the above object, the present invention provides an SOC algorithm applied to an energy storage system, including:
Reading the design capacity and the residual capacity of the energy storage system, and initializing the SOC parameters to obtain first SOC parameters; the first SOC parameters at least comprise correction coefficients, corrected SOC threshold ranges and a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures;
estimating a first SOC value of the energy storage system according to an open circuit voltage method and a plurality of groups of open circuit voltage-electric quantity curve parameters at different temperatures;
Judging whether the first SOC value exceeds the corrected SOC threshold range according to an energy storage system mode;
If so, correcting the first SOC value to obtain a second SOC value according to the open-circuit voltage-electric quantity curve parameter of the current temperature or the correction coefficient, and taking the second SOC value as an output result.
Preferably, the estimating the first SOC value of the energy storage system according to the open circuit voltage method and a plurality of sets of open circuit voltage-electric quantity curve parameters at different temperatures includes:
Measuring the internal resistance and the current of the energy storage system by adopting an open circuit voltage method;
According to the internal resistance and the current of the energy storage system, calculating to obtain the open-circuit voltage of the energy storage system;
acquiring a temperature coefficient in a current temperature environment according to a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures;
And estimating the current SOC value of the energy storage system according to the temperature coefficient and the open-circuit voltage.
Preferably, the temperature of the plurality of groups of open-circuit voltage-electric quantity curve parameters is used in a range of-10 ℃ to 40 ℃.
Preferably, the obtaining the temperature coefficient in the current temperature environment according to the open-circuit voltage-electric quantity curve parameters at the plurality of groups of different temperatures includes:
Taking an open-circuit voltage-electric quantity curve parameter of one temperature in the temperature taking range as a reference parameter;
Comparing the multiple groups of open-circuit voltage-electric quantity curve parameters in the temperature taking range with the reference parameters to obtain voltage difference values of the multiple groups of open-circuit voltage-electric quantity curve parameters in the temperature taking range;
and generating a temperature coefficient of the current temperature according to the voltage difference values.
Preferably, the energy storage system modes include a charging mode, a discharging mode, and a stationary mode.
Preferably, the determining, according to the energy storage system mode, whether the first SOC value exceeds the corrected SOC threshold range includes:
If the system mode is a charging mode, the modified SOC threshold range is 0% -90% of the designed voltage point after the energy storage system is fully charged;
If the system mode is a discharging mode, the corrected SOC threshold range is 10% -100% of the designed voltage point after the energy storage system is fully charged;
and if the system mode is a static mode, the modified SOC threshold range is 0% -100% of the designed voltage point after the energy storage system is fully charged.
Preferably, the correcting the first SOC value to obtain a second SOC value according to the open-circuit voltage-electric quantity curve parameter of the current temperature or the correction coefficient includes:
and linearly correcting the first SOC value to obtain a second SOC value by adopting a linear fitting method according to the open-circuit voltage-electric quantity curve parameters of the current temperature.
Preferably, the correcting the first SOC value to obtain a second SOC value according to the open-circuit voltage-electric quantity curve parameter of the current temperature or the correction coefficient includes:
and calculating the product of the correction coefficient and the first SOC value to obtain a second SOC value.
Preferably, after the output result is output, the method further includes:
And predicting the charging time or the discharging time of the energy storage system according to the output result.
In a second aspect, to achieve the above object, the present invention provides an SOC system applied to an energy storage system, in which the SOC algorithm applied to the energy storage system is built, the system including:
The initialization module is used for reading the design capacity and the residual capacity of the energy storage system, initializing the SOC parameters and obtaining first SOC parameters; the first SOC parameters at least comprise correction coefficients, corrected SOC threshold ranges and a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures;
The estimation module is used for estimating a first SOC value of the energy storage system according to an open circuit voltage method and a plurality of groups of open circuit voltage-electric quantity curve parameters at different temperatures;
The judging module is used for judging whether the first SOC value exceeds the corrected SOC threshold range according to the energy storage system mode;
the first output module is used for correcting the first SOC value to obtain a second SOC value according to the open-circuit voltage-electric quantity curve parameter of the current temperature or the correction coefficient when the first SOC exceeds the corrected SOC threshold range, and the second SOC value is used as an output result.
Compared with the prior art, the invention has at least the following advantages:
1) The method has stronger temperature adaptability, the existing SOC algorithm only usually considers basic parameters such as current, voltage and the like when estimating the battery SOC, and ignores the influence of temperature on the battery performance, and the SOC algorithm compensates the SOC value by collecting the open-circuit voltage-electric quantity curve parameters of the energy storage system at different temperatures and extracting the temperature coefficient at the corresponding temperature, thereby improving the accuracy of the calculation of the SOC value.
2) The mathematical model of the method processes various electrical parameters of the energy storage system, and compared with a simple SOC model in the prior art, the accuracy and stability of the SOC value calculated by the method are higher.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of an SOC algorithm applied to an energy storage system according to a first embodiment of the present invention;
FIG. 2 is a flowchart of a step S2 of the SOC algorithm applied to the energy storage system according to the first embodiment of the present invention;
FIG. 3 is a graph of open-circuit voltage versus power applied to the step S2 of the SOC algorithm of the energy storage system according to the first embodiment of the present invention;
FIG. 4 is a flowchart of step S3 of the SOC algorithm applied to the energy storage system according to the first embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating a second SOC value obtained by correction in a charging mode of an energy storage system according to a first embodiment of the present invention;
FIG. 6 is a graph illustrating a second SOC value obtained by correction in a charging mode of an energy storage system according to a first embodiment of the present invention;
FIG. 7 is a schematic diagram of a second SOC value obtained by correction in a discharging mode of the energy storage system according to the first embodiment of the present invention;
FIG. 8 is a graph illustrating a second SOC value obtained by correction in a discharge mode of the energy storage system according to the first embodiment of the present invention;
fig. 9 is a schematic diagram of an SOC system applied to an energy storage system in accordance with a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention.
The embodiment discloses an SOC algorithm and an SOC system applied to an energy storage system, which are used for solving the problems in the prior art.
Example 1
As shown in fig. 1, an SOC algorithm applied to an energy storage system includes:
S1: and reading the design capacity and the residual capacity of the energy storage system, and initializing the SOC parameters to obtain first SOC parameters.
In this embodiment, the energy storage system mainly refers to a battery energy storage system.
In this embodiment, the first SOC parameter includes at least a correction coefficient, a corrected SOC threshold range, and a plurality of sets of open-circuit voltage-power curve parameters at different temperatures. In other embodiments, full charge capacity, residual capacity, initial open circuit voltage, charge-discharge state parameters, cycle update capacity, pre-correction SOC value, and post-correction SOC value of the energy storage system may also be included.
The design capacity, that is, the capacity that the battery has when fully charged, is an ideal capacity designed for the battery, and FCC is generally expressed in ampere hours (Ah). The remaining capacity, i.e., the amount of charge remaining in the battery, is equal to the product of the design capacity and the SOC value. RC is typically expressed in ampere hours (Ah). The initial open circuit voltage, i.e., the voltage value of the battery when the battery is not being charged and discharged, OCV is generally expressed in units of volts (V). The charge-discharge state parameter, i.e., a parameter representing the current charge level of the battery, the SOC describes the percentage of the battery that has been charged or discharged to its full charge capacity, and is typically expressed as a percentage (%). The open-circuit voltage-electric quantity curve parameter, namely the SOC-OCV curve parameter, is used for estimating the SOC value according to the open-circuit voltage of the battery. The SOC value before correction and the SOC value after correction are dynamic real-time data obtained through real-time calculation, and are set to zero after initialization. The correction coefficient is used for correcting the coefficient or parameter of the SOC value, and the SOC value obtained by subsequent calculation is corrected by multiplying the correction coefficient. And correcting the SOC threshold, namely defining a good voltage point judging range under the state of battery charge or discharge, and judging whether the initially calculated SOC needs correction or not. And cyclically updating the capacity, namely, in the process of battery charging and discharging cycles, the SOC estimation and the battery capacity updating operation are periodically carried out so as to realize dynamic tracking and control of the battery capacity, and the updated battery capacity can be used for the establishment of charging and discharging strategies, the estimation of charging time, the prediction of battery life and other applications.
S2: and estimating a first SOC value of the energy storage system according to the open-circuit voltage method and a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures.
As shown in fig. 2, step S2 includes:
S21: measuring the internal resistance and current of the energy storage system by adopting an open circuit voltage method;
s22: according to the internal resistance and the current of the energy storage system, calculating to obtain the open-circuit voltage of the energy storage system;
S23: acquiring a temperature coefficient in a current temperature environment according to a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures;
S24: and estimating the current SOC value of the energy storage system according to the temperature coefficient and the open-circuit voltage.
Wherein the temperature of the plurality of groups of open-circuit voltage-electric quantity curve parameters is used in a range of-10 ℃ to 40 ℃.
Specifically, step S23 includes:
taking an open-circuit voltage-electric quantity curve parameter at 25 ℃ as a reference parameter;
Comparing the multiple groups of open-circuit voltage-electric quantity curve parameters in the temperature taking range with the reference parameters to obtain voltage difference values of the multiple groups of open-circuit voltage-electric quantity curve parameters in the temperature taking range;
And generating a temperature coefficient of the current temperature according to the voltage difference values.
It should be noted that, according to the current SOC value obtained in the step S21-S2, specific experiments and data analysis are required to be combined, and the following specific experimental methods are provided:
setting a plurality of charge and discharge test samples at different temperatures
Sample one: resting constant temperature 40 ℃ to 3.00V to 0.5 hours at 0.5C charge to 3.65V to 0.5 hours at 0.2C charge to 3.00V (cell temperature guaranteed at 40 ℃);
Sample two: resting constant temperature 25 ℃ to 3.00V to 0.5 hours at 0.5C charge to 3.65V to 0.5 hours at 0.2C charge to 3.00V (cell temperature guaranteed at 25 ℃);
Sample three: resting constant temperature 10 ℃ to 3.00V to 0.5 hours at 0.5C charge to 3.65V to 0.5 hours at 0.2C charge to 3.00V (cell temperature guaranteed at 10 ℃);
Sample four: resting constant temperature 0 ℃ to 3.00V to 0.5 hours with 0.5C discharge to 3.65V to 0.5 hours with 0.2C charge to 3.01C discharge to 3.00V (cell temperature guaranteed at 0 ℃);
Sample five: resting constant temperature-10 ℃ to discharge at 0.5C to 3.00V to rest for 0.5 hours to charge at 0.2C to 3.65V to rest for 0.5 hours to discharge at 0.01C to 3.00V (cell temperature is guaranteed to be at-10 ℃).
Through the five groups of sample experiments, the battery is tested in an incubator and stores data, the data is once in 1 second, the recorded data is about 300 ten thousand, the open-circuit voltage-electric quantity curves of 40 ℃, 25 ℃, 10 ℃,0 ℃ and minus 10 ℃ are extracted, the voltage difference of the SOC at each temperature is obtained through data comparison, and a temperature coefficient is generated.
In this embodiment, in the step S23, the voltage of 25 ℃ is required to be used as a reference point to obtain an open-circuit voltage-electric quantity curve of the current temperature, and the following is specific test data:
From the above test data, an open circuit voltage-charge graph as shown in fig. 3 can be obtained. The open-circuit voltage-electric quantity curve graph acquisition method of other temperatures is the same.
Specifically, in order to predict the actual values of the open circuit voltage at different temperatures, the following calculation formulas can be obtained by combining the above-mentioned multiple groups of tests to generalize specific parameters:
The SOC in formula (1) is a first SOC value, S Full is a full capacity of the energy storage system, S Surplus is a residual capacity of the energy storage system, and K 1 is an amplification factor, in this embodiment, K 1 =1000.
V(SOC，I，T)＝OCV(SOC，T)-IR(SOC，T) (2)
In this embodiment, the relationship between voltage and SOC at different currents and temperatures is predicted by equation (2). V (SOC, I, T) represents the voltage difference, OCV (SOC, T) represents the open-circuit voltage at the current temperature, R (SOC, T) represents the internal resistance of the energy storage system at the current temperature, I represents the output current of the energy storage system at the current temperature, and T represents the temperature. V (SOC, I, T) was used to compensate for EDV (end-of-discharge voltage) and a CEDV model was used consisting of 7 CEDV parameters, 7 CEDV parameters EMF, C0, C1, R0, R1, T0, TC, respectively.
Specifically, the simple formula of CEDV model is:
CEDV＝EMF×f(C0，C+C1，T)-I×R0×f(R1，T0，T，C+C1，TC，A0) (3)
wherein EMF is a CEDV model parameter stored in the fuel gauge, in mV, which represents the open circuit voltage; f (C0, C) is an open-circuit voltage-power curve parameter function of the reference point C0; f (C1, T) is an open-circuit voltage-electric quantity curve parameter function at the current temperature; r0×f (R1, T0, T, C) is a function of the energy storage system at the reference temperature T0. The CEDV voltage point increases as the EMF increases. C0 is a CEDV model parameter stored in the fuel gauge, and f (C0, C+C1, T) represents the open circuit voltage as a function of the capacity SOC and temperature, i.e., how quickly the open circuit voltage drops to EDV0. The CEDV voltage points decrease as C0 increases. C1 is a CEDV model parameter stored in the fuel gauge, f (R1, T0, T, c+c1, TC, A0) representing a functional relation of the reserved capacity expected at EDV0 (rm=0, soc=0%).
It should be noted that, the functional relationship between f (C0, c+c1, T) and f (R1, T0, T, c+c1, TC, A0) may be calculated by using a machine learning algorithm such as a vector machine, a random forest, a neural network, or a nonlinear algorithm such as a deep learning algorithm.
In this embodiment, the relationship between f (C0, c+c1, T) and the 7 CEDV parameters is:
f(C0，C+C1，T)＝a0+a1*C0+a2*C+C1+a3*T+a4*C0*T+a5*C+C1*T+a6*C0*C+C1+a7*C0*T*C+C1 (4)
Wherein, a0, a1, a2, a3, a4, a5, a6 and a7 are all constants, and the method is obtained by millions of test calculation and combination.
In this embodiment, the relationship between f (R1, T0, T, c+c1, TC, A0) and the 7 CEDV parameters is:
f(R1，T0，T，C+C1，TC，A0)＝b0+b1*R1+b2*T0+b*T+b4*R1*T0+b5*T0*T+b6*R1*T*T0+b7*R1*T0*T*T (5)
Wherein b0, b1, b2, b3, b4, b5, b6, b7 are constants, and are obtained by millions of experimental calculation and combination of the above methods.
S3: and judging whether the first SOC value exceeds the corrected SOC threshold range according to the energy storage system mode.
As shown in fig. 4, the energy storage system mode includes a charging mode, a discharging mode and a rest mode, and step S3 includes:
S31: if the system mode is a charging mode, correcting the SOC threshold range to be 0% -90% of the designed voltage point after the energy storage system is fully charged;
S32: if the system mode is a discharging mode, correcting the SOC threshold range to be 10% -100% of the designed voltage point after the energy storage system is fully charged;
s33: if the system mode is a static mode, the correction SOC threshold range is 0% -100% of the designed voltage point after the energy storage system is fully charged.
Through the steps S31 to S33, it is determined whether the first SOC value needs to be corrected.
Compared with the prior art, the method combines a conventional algorithm and a specific algorithm, and ensures the accuracy of SOC calculation. The full charge capacity of the FCC is allowed to be updated when the discharge is reduced to 10%, and the full charge capacity of the FCC is updated when the charge is reduced from 10% to 100%, so that the problem of inaccurate SOC of the battery caused by lack of deep discharge is solved.
S4: if so, correcting the first SOC value to obtain a second SOC value according to the open-circuit voltage-electric quantity curve parameter or the correction coefficient of the current temperature, and taking the second SOC value as an output result.
In this embodiment, step S4 includes:
and linearly correcting the first SOC value and the second SOC value by adopting a linear fitting method according to the open-circuit voltage-electric quantity curve parameters of the current temperature.
In other embodiments, step S4 may also include:
And calculating the product of the correction coefficient and the first SOC value to obtain a second SOC value.
Specifically, as shown in fig. 5 and fig. 6, in the charging mode, the first SOC value is greater than the SOC value corresponding to the design voltage after the energy storage system is fully charged, and the currently displayed SOC value (the display value of the small display of the energy storage system) is smaller than the first SOC value, which indicates that the displayed SOC value is lower, and the first SOC value needs to be corrected by adopting a linear fitting method or a correction coefficient to obtain the second SOC value.
Specifically, as shown in fig. 7 and 8, in the discharging mode, the first SOC value is smaller than the SOC value corresponding to the design voltage after the energy storage system is fully charged, and the currently displayed SOC value is smaller than the first SOC value, which indicates that the first SOC value is higher, and the first SOC value and the second SOC value need to be corrected by adopting a linear fitting method or a correction coefficient.
In the stationary mode, the first SOC value does not need to be corrected.
S5: if not, integrating the first SOC value and then taking the integrated result as an output result.
Compared with the prior art, the method has stronger temperature adaptability, the existing SOC algorithm only usually considers basic parameters such as current, voltage and the like when estimating the battery SOC, and ignores the influence of temperature on the battery performance, and the method compensates the SOC value by collecting open-circuit voltage-electric quantity curve parameters of the energy storage system at different temperatures and extracting temperature coefficients at corresponding temperatures, thereby improving the accuracy of SOC value calculation.
After the output result is obtained, the method of the invention further comprises the following steps:
And predicting the charging time or the discharging time of the energy storage system according to the output result.
Specifically, the calculation formula is:
T＝C/I
wherein, C is battery capacity, and I is load current.
In addition, after the output result is obtained, the method of the invention further comprises:
the FCC capacity and SOH health status are updated.
Specifically, in order to update the FCC capacity, the lower the SOC, the better the battery is when the capacity of the battery is discharged to 10% or less during the discharging process, and FCC (First Cycle Capacity) is allowed, i.e., the charging must be fully charged at one time. During charging, the amount of charge that is flushed in can be recorded and the full charge capacity can be estimated again. Assuming that the residual capacity is C0, after discharging to less than 10%, charging is performed again, and the flushed electric quantity is recorded as C1.Δc is the latest full charge capacity. The SOC value corresponding to C0 is X%, and the specific full charge capacity formula is:
ΔC＝C1/(100％-x％)
specifically, the calculation formula of the SOH health state is:
Where Q aged is the maximum current available charge of the battery and Q new is the maximum unused charge of the battery. SOH state of health is used to evaluate battery life, where SOH is defined as the ratio of the current actual capacity of the battery to the rated capacity, e.g., when the actual capacity of the battery drops to 80% of the rated capacity, the battery is generally considered to have reached its useful life. The definition method needs to know the accurate value of the current capacity, and can generally charge the battery at a certain SOC value, and calculate the actual capacity of the battery according to the charged electric quantity when the battery is full. Therefore, compared with the prior art, the SOH precision obtained by the method is higher, and the method is suitable for judging the SOH health state of the energy storage system.
In summary, the method of the invention has the beneficial effects that:
1) The temperature characteristics, chemical reactions, voltage characteristics and other factors of the energy storage system are considered, and the charging and discharging processes of the energy storage system can be accurately described.
2) Based on high-precision current and voltage measurement data, real-time state information of the battery can be accurately obtained, and accurate SOC calculation is realized.
3) By adopting a method of fusing multiple algorithms and combining multiple calculation methods such as a voltage method, a current method and a capacity method, different factors are comprehensively considered, and the calculation precision and stability are improved.
4) The parameters of the algorithm can be adaptively adjusted according to the actual working state and environmental conditions of the battery, so that the accuracy and adaptability of calculation are improved.
5) By adopting various compensation and calibration methods, the influence of factors such as temperature, aging, internal resistance and the like is considered, and the accuracy and stability of calculation are improved.
6) The calculation result can be dynamically updated in real time, and the calculation result is timely adjusted according to the change in the actual charging and discharging process, so that the calculation precision and response speed are improved.
7) The calculated result is compared with the actual battery capacity and verified, and the calculated capacity is proved to have high precision by comparing the calculated result with the actual measurement result.
Example two
As shown in fig. 9, the present embodiment discloses an SOC system applied to an energy storage system, in which the SOC algorithm applied to the energy storage system is built, the system includes:
the initialization module 10 is used for reading the design capacity and the residual capacity of the energy storage system, initializing historical SOC parameters and obtaining first SOC parameters; the first SOC parameters at least comprise correction coefficients, corrected SOC threshold ranges and a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures;
The estimation module 20 is configured to estimate a first SOC value of the energy storage system according to an open circuit voltage method and a plurality of sets of open circuit voltage-electric quantity curve parameters at different temperatures;
the judging module 30 is configured to judge whether the first SOC value exceeds the corrected SOC threshold range according to the energy storage system mode;
The first output module 40 is configured to, when the first SOC exceeds the corrected SOC threshold range, correct the first SOC value to obtain a second SOC value according to the open-circuit voltage-electric quantity curve parameter or the correction coefficient of the current temperature, and use the second SOC value as an output result;
the second output module 50 is configured to integrate the first SOC value and then use the integrated first SOC value as an output result when the first SOC is within the corrected SOC threshold range.
Wherein the estimation module 20 comprises:
The measuring unit is used for measuring the internal resistance and the current of the energy storage system by adopting an open-circuit voltage method;
the first calculation unit is used for calculating the open-circuit voltage of the energy storage system according to the internal resistance and the current of the energy storage system;
The data acquisition unit is used for acquiring temperature coefficients in the current temperature environment according to a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures;
And the estimation unit is used for estimating the current SOC value of the energy storage system according to the temperature coefficient and the open-circuit voltage.
Wherein, the judging module 30 includes:
the first judging subunit is used for correcting the SOC threshold range to be 0% -90% of the voltage point of the design voltage after the energy storage system is fully charged if the system mode is the charging mode;
The second judging subunit is used for correcting the SOC threshold range to be 10% -100% of the designed voltage point after the energy storage system is fully charged if the system mode is a discharging mode;
and the second judging subunit is used for correcting the SOC threshold range to be 0% -100% of the voltage point of the design voltage after the energy storage system is fully charged if the system mode is the static mode.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above embodiments may be implemented by hardware associated with program instructions, and the foregoing program may be stored in a computer readable storage medium, which when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: various media capable of storing program codes such as ROM, RAM, magnetic disk or optical disk
It will be apparent to those skilled in the art from this disclosure that various other changes and modifications can be made which are within the scope of the invention as defined in the appended claims.
Claims (10)
1. An SOC algorithm for use with an energy storage system, comprising:
Reading the design capacity and the residual capacity of the energy storage system, and initializing the SOC parameters to obtain first SOC parameters; the first SOC parameters at least comprise correction coefficients, corrected SOC threshold ranges and a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures;
estimating a first SOC value of the energy storage system according to an open circuit voltage method and a plurality of groups of open circuit voltage-electric quantity curve parameters at different temperatures;
Judging whether the first SOC value exceeds the corrected SOC threshold range according to an energy storage system mode;
If so, correcting the first SOC value to obtain a second SOC value according to the open-circuit voltage-electric quantity curve parameter of the current temperature or the correction coefficient, and taking the second SOC value as an output result.
2. The SOC algorithm as claimed in claim 1, wherein estimating the first SOC value of the energy storage system based on the open circuit voltage method and a plurality of sets of open circuit voltage-charge curve parameters at different temperatures comprises:
Measuring the internal resistance and the current of the energy storage system by adopting an open circuit voltage method;
According to the internal resistance and the current of the energy storage system, calculating to obtain the open-circuit voltage of the energy storage system;
acquiring a temperature coefficient in a current temperature environment according to a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures;
And estimating the current SOC value of the energy storage system according to the temperature coefficient and the open-circuit voltage.
3. The SOC algorithm as claimed in claim 1, wherein the temperature range of the plurality of sets of open-circuit voltage-power curve parameters is-10 ℃ -40 ℃.
4. The SOC algorithm as claimed in claim 3, wherein the obtaining the temperature coefficient in the current temperature environment according to the open-circuit voltage-power curve parameters at the plurality of sets of different temperatures comprises:
Taking an open-circuit voltage-electric quantity curve parameter of one temperature in the temperature taking range as a reference parameter;
Comparing the multiple groups of open-circuit voltage-electric quantity curve parameters in the temperature taking range with the reference parameters to obtain voltage difference values of the multiple groups of open-circuit voltage-electric quantity curve parameters in the temperature taking range;
and generating a temperature coefficient of the current temperature according to the voltage difference values.
5. The SOC algorithm as recited in claim 1 wherein the energy storage system modes include a charge mode, a discharge mode and a rest mode.
6. The SOC algorithm as claimed in claim 5, wherein the determining whether the first SOC value exceeds the corrected SOC threshold range based on the energy storage system mode comprises:
If the system mode is a charging mode, the modified SOC threshold range is 0% -90% of the designed voltage point after the energy storage system is fully charged;
If the system mode is a discharging mode, the corrected SOC threshold range is 10% -100% of the designed voltage point after the energy storage system is fully charged;
and if the system mode is a static mode, the modified SOC threshold range is 0% -100% of the designed voltage point after the energy storage system is fully charged.
7. The SOC algorithm as claimed in claim 1, wherein the correcting the first SOC value to obtain a second SOC value according to the open-circuit voltage-to-charge curve parameter of the current temperature or the correction factor comprises:
and linearly correcting the first SOC value to obtain a second SOC value by adopting a linear fitting method according to the open-circuit voltage-electric quantity curve parameters of the current temperature.
8. The SOC algorithm as claimed in claim 1, wherein the correcting the first SOC value to obtain a second SOC value according to the open-circuit voltage-to-charge curve parameter of the current temperature or the correction factor comprises:
and calculating the product of the correction coefficient and the first SOC value to obtain a second SOC value.
9. The SOC algorithm as claimed in claim 1, wherein after the output result is output, the method further comprises:
And predicting the charging time or the discharging time of the energy storage system according to the output result.
10. An SOC system for use in an energy storage system incorporating the SOC algorithm of claims 1-9 for use in an energy storage system, the system comprising:
The initialization module is used for reading the design capacity and the residual capacity of the energy storage system, initializing the SOC parameters and obtaining first SOC parameters; the first SOC parameters at least comprise correction coefficients, corrected SOC threshold ranges and a plurality of groups of open-circuit voltage-electric quantity curve parameters at different temperatures;
The estimation module is used for estimating a first SOC value of the energy storage system according to an open circuit voltage method and a plurality of groups of open circuit voltage-electric quantity curve parameters at different temperatures;
The judging module is used for judging whether the first SOC value exceeds the corrected SOC threshold range according to the energy storage system mode;
the first output module is used for correcting the first SOC value to obtain a second SOC value according to the open-circuit voltage-electric quantity curve parameter of the current temperature or the correction coefficient when the first SOC exceeds the corrected SOC threshold range, and the second SOC value is used as an output result.
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