CN113848487A - Equalization control method based on proprietary SOC estimation - Google Patents
Equalization control method based on proprietary SOC estimation Download PDFInfo
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Abstract
The invention discloses a balance control method based on proprietary SOC estimation, which comprises the following steps: s01: acquiring the SOC value of each single battery; s02: calculating the difference value of the maximum SOC and the minimum SOC of the delta SOC value delta SOC by using a formula delta SOC as max (SOC [ i ]) -min (SOC [ j ]), wherein i and j are battery numbers, and SOC [ i ] represents the SOC value of the battery with the number of i; s03: when the Δ SOC result is smaller than the set threshold, the process returns to S01 to wait for the next SOC estimation value, otherwise, the next equalization operation is performed. In the invention, the equalization control method based on the proprietary SOC estimation is different from the method that the terminal voltage is used as the equalization evaluation index, and the equalization strategy based on the battery SOC can essentially improve the unbalance problem of the battery, because the battery SOC is the comprehensive expression of the voltage, the capacity and the like of the battery, the accurate battery capacity information can be provided.
Description
Technical Field
The invention relates to the technical field of battery equalization control, in particular to an equalization control method based on proprietary SOC estimation.
Background
Due to the limitation of the battery manufacturing process, the inconsistency among the unit cells in the battery pack still exists even though the same working environment and charging and discharging operations are performed. The inconsistency of the batteries means that the characteristics of voltage, soc (state of charge), internal resistance, capacity and the like of the batteries are different, so that when the batteries are used, not all the batteries can reach a full-charge or empty state, and the effective capacity of the energy storage system is reduced. In order to maximize the effective capacity of the battery and maintain the consistency of the battery voltage and SOC, battery equalization is typically performed during charging and discharging. At present, terminal voltage is used as a balance evaluation index in practical application, and the terminal voltage of a battery is convenient to measure. However, the terminal voltage cannot provide accurate battery capacity information, which results in over-balancing of the battery pack and frequent start-up of the balancing system. This not only makes equalization inefficient but also shortens battery life. In addition, in the SOC-based equalization algorithm, if the SOC estimation accuracy is not high, effective battery equalization still cannot be achieved.
Disclosure of Invention
The invention aims to solve the problems of battery pack over-balancing and frequent starting of a balancing system in the prior art, and provides a balancing control method based on proprietary SOC estimation.
In order to achieve the purpose, the invention adopts the following technical scheme: a balance control method based on proprietary SOC estimation comprises the following steps:
s01: acquiring the SOC value of each single battery;
s02: calculating the difference value of the maximum SOC and the minimum SOC of the delta SOC value delta SOC by using a formula delta SOC as max (SOC [ i ]) -min (SOC [ j ]), wherein i and j are battery numbers, and SOC [ i ] represents the SOC value of the battery with the number of i;
s03: when the delta SOC result is smaller than the set threshold value, returning to S01 to wait for the next SOC estimation value, otherwise, carrying out the next balancing operation;
s04: and (3) equalizing operation: in the balancing operation, except the single battery with the minimum SOC, a balancing start signal is sent to other batteries, the charge is sent back to the whole battery pack for redistribution, and then the charge returns to the SO1 to wait for the next SOC estimated value.
As a further description of the above technical solution:
the step S01 of obtaining the SOC value of each battery cell includes the following steps:
s001, performing a pulse discharge experiment on the target battery in a thermostat to respectively obtain voltage data of battery terminal voltage at the ambient temperature of 5 ℃, 20 ℃ and 40 ℃;
s002: the method comprises the steps of utilizing an offline parameter identification and extraction method to carry out parameter identification and extraction on experimental data of a pulse discharge experiment, so that two-dimensional lookup tables of R0, R1, C1 and OCV related to SOC and ambient temperature T are established, and the two-dimensional lookup tables of SOC are obtained through conversion of the OCV two-dimensional lookup tables;
s003: measuring the initial terminal voltage value of the battery, namely the initial OCV value, taking the initial OCV value and the environment temperature value at the moment as input, and determining the initial value of the SOC through a two-dimensional SOC table look-up;
s004: the initial value of the state variable of the UKF algorithm module is determined by the initial value of the SOC, and the updated SOC value is calculated by the UKF algorithm module;
SO 05: determining the OCV value at the moment by using the SOC value at the moment and the environmental temperature value at the moment as input through an OCV two-dimensional table lookup;
s006: updating a state vector of the RLS algorithm module according to the OCV value, the terminal voltage value and the current value at the moment, and obtaining the latest online model parameter value through the RLS algorithm module;
s007: updating a state equation and a measurement equation in the UKF algorithm module by using the new model parameter values, and updating the SOC value in real time through the UKF algorithm module;
s008: the steps S05, S06 and S07 are continuously cycled to achieve real-time estimation of SOC.
As a further description of the above technical solution:
the UKF algorithm module in the step S004 comprises a first-order RC battery equivalent circuit model module and a UKF formula module, the UKF algorithm module establishes a state equation and a measurement equation of the UKF according to the first-order RC battery equivalent circuit model, and takes the initial value of SOC as an initial value to form an initial value of a state vector of the UKF, real-time terminal voltage value and current value are also input into the UKF algorithm module, the SOC value at a new moment is obtained according to the UKF algorithm module, and the two-dimensional lookup table of the SOC value, the environmental temperature T and the OCV at the moment is used for determining the current value to be given to the RLS algorithm module.
As a further description of the above technical solution:
in the step S006, the RLS algorithm module includes a first-order RC battery equivalent circuit model module and an RLS formula module, the RLS algorithm module determines a conversion relationship between a battery model parameter and an RLS parameter vector according to the first-order RC battery equivalent circuit model, the OCV value at the new time obtained by the RLS formula module plus the real-time terminal voltage value and the real-time current value is used to update the state vector of the RLS formula module, so as to obtain an online identification result of the model parameter, update the battery model parameter value, feed back the online identification result to the UKF algorithm module, and update the state equation and the measurement equation in the UKF algorithm module.
As a further description of the above technical solution:
in the step S002, the method for identifying and extracting the off-line parameters includes a pulse discharge experiment and parameter identification and extraction, the target battery is subjected to the pulse discharge experiment in the thermostat to obtain a terminal voltage value and a discharge current value of the target battery, and the off-line parameter identification and extraction result of the model parameters is obtained by using the parameter identification and extraction.
As a further description of the above technical solution:
in step S003, the initial value of SOC is obtained by using an SOC two-dimensional lookup table, where the inputs of the SOC two-dimensional lookup table are an initial OCV value and an ambient temperature T, and the SOC two-dimensional lookup table is obtained by converting the OCV two-dimensional lookup table, where the initial OCV value is obtained from an initial terminal voltage value of the battery immediately after the battery operates.
Advantageous effects
The invention provides a balance control method based on proprietary SOC estimation. The method has the following beneficial effects:
(1) in the invention, the equalization control method based on the proprietary SOC estimation is different from the method that the terminal voltage is used as the equalization evaluation index, and the equalization strategy based on the battery SOC can essentially improve the unbalance problem of the battery, because the battery SOC is the comprehensive expression of the voltage, the capacity and the like of the battery, the accurate battery capacity information can be provided.
(2) In the invention, the equalization control method based on the proprietary SOC estimation utilizes the proprietary high-accuracy SOC estimation to realize the equalization control algorithm, so that more effective battery equalization can be achieved.
Drawings
FIG. 1 is a flow chart of a method for equalization control based on proprietary SOC estimation according to the present invention;
fig. 2 is a schematic diagram of an equalization control method based on proprietary SOC estimation according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
As shown in fig. 1-2, a method for equalization control based on proprietary SOC estimation includes the following steps:
s01: acquiring the SOC value of each single battery;
s02: calculating the difference value of the maximum SOC and the minimum SOC of the delta SOC value delta SOC by using a formula delta SOC as max (SOC [ i ]) -min (SOC [ j ]), wherein i and j are battery numbers, and SOC [ i ] represents the SOC value of the battery with the number of i;
s03: when the delta SOC result is smaller than the set threshold value, returning to S01 to wait for the next SOC estimation value, otherwise, carrying out the next balancing operation;
s04: and (3) equalizing operation: in the balancing operation, except the single battery with the minimum SOC, a balancing start signal is sent to other batteries, the charge is sent back to the whole battery pack for redistribution, and then the charge returns to the SO1 to wait for the next SOC estimated value.
The step S01 of acquiring the SOC value of each battery cell includes the steps of:
s001, performing a pulse discharge experiment on the target battery in a thermostat to respectively obtain voltage data of battery terminal voltage at the ambient temperature of 5 ℃, 20 ℃ and 40 ℃;
s002: the method comprises the steps of utilizing an offline parameter identification and extraction method to carry out parameter identification and extraction on experimental data of a pulse discharge experiment, so that two-dimensional lookup tables of R0, R1, C1 and OCV related to SOC and ambient temperature T are established, and the two-dimensional lookup tables of SOC are obtained through conversion of the OCV two-dimensional lookup tables;
s003: measuring the initial terminal voltage value of the battery, namely the initial OCV value, taking the initial OCV value and the environment temperature value at the moment as input, and determining the initial value of the SOC through a two-dimensional SOC table look-up;
s004: the initial value of the state variable of the UKF algorithm module is determined by the initial value of the SOC, and the updated SOC value is calculated by the UKF algorithm module;
SO 05: determining the OCV value at the moment by using the SOC value at the moment and the environmental temperature value at the moment as input through an OCV two-dimensional table lookup;
s006: updating a state vector of the RLS algorithm module according to the OCV value, the terminal voltage value and the current value at the moment, and obtaining the latest online model parameter value through the RLS algorithm module;
s007: updating a state equation and a measurement equation in the UKF algorithm module by using the new model parameter values, and updating the SOC value in real time through the UKF algorithm module;
s008: the steps S05, S06 and S07 are continuously cycled to achieve real-time estimation of SOC.
The UKF algorithm module in the step S004 comprises a first-order RC battery equivalent circuit model module and a UKF formula module, the UKF algorithm module establishes a state equation and a measurement equation of the UKF according to the first-order RC battery equivalent circuit model, and takes the initial value of SOC as an input to form an initial value of a state vector of the UKF, real-time terminal voltage value and current value are also input into the UKF algorithm module, the SOC value at a new moment is obtained according to the UKF algorithm module, and the two-dimensional lookup table of the SOC value, the environmental temperature T and the OCV at the moment is utilized to determine the OCV value at the moment and give the value to the RLS algorithm module.
In step S006, the RLS algorithm module includes a first-order RC battery equivalent circuit model module and an RLS formula module, the RLS algorithm module determines a conversion relationship between a battery model parameter and an RLS parameter vector according to the first-order RC battery equivalent circuit model, the OCV value at the new time obtained by the RLS formula module plus the real-time terminal voltage value and the real-time current value is used to update the state vector of the RLS formula module, so as to obtain an online identification result of the model parameter, update the battery model parameter value, and then feed back the online identification result to the UKF algorithm module, thereby updating the state equation and the measurement equation in the UKF algorithm module.
The first-order RC battery equivalent circuit model module comprises a voltage source OCV, a resistor R0, a resistor R1 and a capacitor C1 which are all functions of SOC and ambient temperature T, wherein the positive pole of the voltage source OCV is connected with one end of the resistor R1 and one end of the capacitor C1, the negative pole of the voltage source OCV is connected with a power ground, the other end of the resistor R1 is connected with the other end of the capacitor C1 and one end of the resistor R0, and the output of the other end of the resistor R0 and the power ground is E (T).
In step S002, the off-line parameter identification and extraction method includes a pulse discharge experiment and parameter identification and extraction, the target battery is subjected to the pulse discharge experiment in the thermostat to obtain a terminal voltage value and a discharge current value of the target battery, and the off-line parameter identification and extraction result of the model parameter is obtained by the parameter identification and extraction.
In step S003, the initial SOC value is obtained from an SOC two-dimensional lookup table, the inputs of which are the initial OCV value and the ambient temperature T, and the SOC two-dimensional lookup table is converted from the OCV two-dimensional lookup table, and the initial OCV value is obtained from the initial terminal voltage value of the battery immediately after the battery operates.
Table 1 equalization control algorithm test results
The experimental tests were performed without and with the equalization control algorithm, respectively. The experimental test results in table 1 show that the operating time of the battery pack is increased from 1 hour 42 minutes to 3 hours 34 minutes after the equalization control algorithm is added, which indicates that the equalization control algorithm of the present invention can effectively increase the effective capacity of the battery.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (6)
1. A balance control method based on proprietary SOC estimation is characterized by comprising the following steps:
s01: acquiring the SOC value of each single battery;
s02: calculating the difference value of the maximum SOC and the minimum SOC of the delta SOC value delta SOC by using a formula delta SOC as max (SOC [ i ]) -min (SOC [ j ]), wherein i and j are battery numbers, and SOC [ i ] represents the SOC value of the battery with the number of i;
s03: when the delta SOC result is smaller than the set threshold value, returning to S01 to wait for the next SOC estimation value, otherwise, carrying out the next balancing operation;
s04: and (3) equalizing operation: in the balancing operation, except the single battery with the minimum SOC, a balancing start signal is sent to other batteries, the charge is sent back to the whole battery pack for redistribution, and then the charge returns to the SO1 to wait for the next SOC estimated value.
2. The method for controlling equalization based on proprietary SOC estimation according to claim 1, characterized in that said step S01 of obtaining the SOC value of each battery cell comprises the following steps:
s001, performing pulse discharge experiment on the target battery in a constant temperature box to respectively obtain voltage data of battery terminal voltage at the environmental temperature of 5 ℃, 20 ℃ and 40 DEG C
S002: the method comprises the steps of utilizing an offline parameter identification and extraction method to carry out parameter identification and extraction on experimental data of a pulse discharge experiment, so that two-dimensional lookup tables of R0, R1, C1 and OCV related to SOC and ambient temperature T are established, and the two-dimensional lookup tables of SOC are obtained through conversion of the OCV two-dimensional lookup tables;
s003: measuring the initial terminal voltage value of the battery, namely the initial OCV value, taking the initial OCV value and the environment temperature value at the moment as input, and determining the initial value of the SOC through a two-dimensional SOC table look-up;
s004: the initial value of the state variable of the UKF algorithm module is determined by the initial value of the SOC, and the updated SOC value is calculated by the UKF algorithm module;
SO 05: determining the OCV value at the moment by using the SOC value at the moment and the environmental temperature value at the moment as input through an OCV two-dimensional table lookup;
s006: updating a state vector of the RLS algorithm module according to the OCV value, the terminal voltage value and the current value at the moment, and obtaining the latest online model parameter value through the RLS algorithm module;
s007: updating a state equation and a measurement equation in the UKF algorithm module by using the new model parameter values, and updating the SOC value in real time through the UKF algorithm module;
s008: the steps S05, S06 and S07 are continuously cycled to achieve real-time estimation of SOC.
3. The method according to claim 2, wherein the UKF algorithm module in step S004 comprises a first-order RC battery equivalent circuit model module and a UKF formula module, the UKF algorithm module establishes a state equation and a measurement equation of the UKF according to the first-order RC battery equivalent circuit model, and uses the initial value of the SOC as an input to form an initial value of a state vector of the UKF, and real-time terminal voltage value and current value are also input to the UKF algorithm module, and obtains a new SOC value according to the UKF algorithm module, and determines the OCV value at the moment to be given to the RLS algorithm module by using the SOC value at the moment, the ambient temperature T and the OCV two-dimensional lookup table.
4. The method according to claim 2, wherein in step S006, the RLS algorithm module includes a first-order RC battery equivalent circuit model module and an RLS formula module, the RLS algorithm module determines a conversion relationship between battery model parameters and RLS parameter vectors according to the first-order RC battery equivalent circuit model, and the OCV value at the new time obtained by the RLS formula module plus the real-time terminal voltage value and the real-time current value are used to update the state vectors of the RLS formula module, so as to obtain the online identification result of the model parameters, update the battery model parameter values, and then feed back the online identification result to the UKF algorithm module, and update the state equations and the measurement equations in the UKF algorithm module.
5. The method as claimed in claim 2, wherein the step S002 includes pulse discharge test and parameter identification and extraction by using off-line parameter identification and extraction method, the target battery is subjected to the pulse discharge test in the oven to obtain the terminal voltage value and the discharge current value of the target battery, and the off-line parameter identification and extraction result of the model parameter is obtained by using the parameter identification and extraction method.
6. The method of claim 2, wherein the initial value of SOC in step S003 is obtained by a SOC two-dimensional lookup table, the inputs of which are the initial OCV value and the ambient temperature T, and the SOC two-dimensional lookup table is converted from the OCV two-dimensional lookup table, and the initial OCV value is obtained from the initial voltage value of the battery immediately after the battery is operated.
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