CN118091427A - SOC estimation method and system based on-off instantaneous equivalent internal resistance combination - Google Patents
SOC estimation method and system based on-off instantaneous equivalent internal resistance combination Download PDFInfo
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Abstract
The invention provides an SOC estimation method and system based on-off instantaneous equivalent internal resistance combination, wherein the system comprises the following steps: SOC-OCV test; calculating the equivalent internal resistance of instant power on and power off according to the voltage difference between the terminals of preset time periods before and after the instant power on and power off and the instant average current; curve fitting to obtain the relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge (SOC) and related parameters; establishing an SOC estimation mathematical model; calculating a differential temperature offset; obtaining a temperature offset model according to the characteristics of the differential temperature offset; obtaining the relation between the internal resistance and the battery charge state at different temperatures through addition operation; expanding to obtain a state of charge (SOC) estimation model of the battery with different temperature; and carrying out SOC estimation on the battery to be tested by using a differential temperature battery state of charge SOC estimation model. The method solves the technical problems of limited application range, low estimation operation efficiency, high estimation cost, complex estimation model structure and low estimation precision.
Description
Technical Field
The invention relates to the field of battery state parameter detection, in particular to an SOC estimation method and system based on-off instantaneous equivalent internal resistance combination.
Background
The prior patent application publication No. CN114910796A, namely a MIAUKF algorithm-based lithium ion battery state of charge estimation method, comprises the following steps: performing a lithium ion battery open-circuit voltage characteristic test on a second-order R C equivalent circuit model of the lithium ion battery, and obtaining an OCV-SOC (Open Circuit Voltage-State of Charge) characteristic curve by utilizing eight-term fitting; based on the built second-order R C equivalent circuit model, carrying out parameter identification by using a least square method and verifying the precision of the model; combining a Multi-information algorithm with an AUKF (Adaptive Unscented KALMAN FILTER, self-adaptive unscented Kalman filtering) algorithm, and updating an estimated value by utilizing a new correction stage of a Multi-information error vector and a Kalman gain matrix to obtain a MIAUKF (Multi-Information Adaptive Unscented KALMAN FILTER, multi-information self-adaptive unscented Kalman filtering) algorithm model so as to improve the estimation accuracy of the state of charge of the lithium ion battery; and estimating the state of charge of the lithium ion battery based on MIAUKF algorithm model. As can be seen from the specific implementation of the prior art, the prior art obtains MIAUKF algorithm models by combining a multi-information algorithm and an AUKF algorithm, and obtains an OCV-SOC characteristic curve by utilizing eight-term fitting in the process of carrying out the open-circuit voltage characteristic test of the lithium ion battery. The prior patent application publication No. CN109444757A, namely a method for estimating the residual electric quantity of a power battery of an electric automobile, comprises the following steps: based on a volume Kalman algorithm, establishing a power battery residual electric quantity estimation model; acquiring polarized internal resistance, polarized capacitance, equivalent ohmic internal resistance, residual electric quantity and terminal voltage of the power battery at a specific moment; calculating the open-circuit voltage of the power battery at a specific moment; calculating a state estimation error and a noise error; constructing a BP neural network based on width learning, inputting a state estimation error and a noise error into the BP (Back Propagation) neural network, and outputting a variance compensation value of process noise distribution at a specific moment and a variance compensation value of observation noise distribution by the BP neural network; the variance compensation value and the variance compensation value of the observed noise distribution are used for compensating the variance of the previous moment and the variance of the measured noise distribution, and the variance of the specific moment and the variance of the measured noise distribution are generated; and calculating the parameters of the power battery residual capacity estimation model by adopting a volume Kalman algorithm, thereby obtaining the residual capacity at the later moment. According to the concrete application scene description of the prior art, the prior art fully charges the power battery, and after standing for a long time, discharges with 0.3C current, stands for one hour every 10% of SOC (State of Charge), measures once every hour, records the values of the residual electric quantity and the open-circuit voltage, fits an SOC-OCV curve, detects the open-circuit voltage of the power battery, calculates the residual electric quantity according to the SOC-OCV curve, and detects the initial terminal voltage, the polarized internal resistance, the voltage at two ends of the polarized internal resistance, the polarized capacitance and the equivalent ohmic internal resistance of the power battery. The prior art relies on an SOC-OCV curve, the relation between the internal resistance and the residual electric quantity is not obvious, so that the model estimation precision is low, the MIAUKF algorithm model and the BP neural network model based on width learning adopted by the prior art are large in parameter types and calculated amounts, the model complexity is high, and meanwhile the efficiency of actual estimation operation is restricted.
In summary, the prior art has the technical problems of limited application range, low estimation operation efficiency, high estimation cost, complex estimation model structure and low estimation precision.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: how to solve the technical problems of limited application range, low estimation operation efficiency, high estimation cost, complex estimation model structure and lower estimation precision in the prior art.
The invention adopts the following technical scheme to solve the technical problems: the SOC estimation method based on the combination of the on-off instant equivalent internal resistances comprises the following steps:
s1, performing SOC-OCV test on a battery to be tested at a preset temperature to obtain a test result, and processing to obtain terminal voltage difference data;
S2, processing to obtain terminal voltage differences and instantaneous average currents at preset time intervals before and after instantaneous power-on and power-off according to the terminal voltage difference data so as to obtain equivalent internal resistances of instantaneous power-on and power-off;
S3, performing curve fitting operation on the battery to be tested to obtain a relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge (SOC) and a relation parameter;
S4, establishing an SOC estimation mathematical model according to the instantaneous power-on and power-off equivalent internal resistances and the relation between the instantaneous power-on and power-off equivalent internal resistances and the state of charge (SOC) of the battery;
S5, under different environment temperatures, obtaining a repeated test result through repeated test operation, wherein the repeated test result comprises the following steps: the environment temperature corresponding to the equivalent internal resistance of instant power-on and power-off, the differential temperature offset relative to the preset standard environment temperature, and the change relation between the differential temperature offset and the SOC;
S6, obtaining characteristic information of the differential temperature offset, and processing to obtain a temperature offset model of the instantaneous power-on and power-off equivalent internal resistance according to repeated test results;
s7, processing the differential temperature offset by using a temperature offset model to obtain the relationship between the internal resistance and the battery state of charge at different temperatures;
S8, expanding an SOC estimation mathematical model according to the relation between the internal resistance and the battery state of charge at different temperatures to obtain a battery state of charge SOC estimation model at different temperatures;
s9, estimating the current battery charge state of the battery to be detected by using the differential temperature battery charge state SOC estimation model.
The invention establishes the SOC estimation model of the battery with different temperature and expands the application range of the estimation method. The instantaneous power-on and power-off equivalent internal resistances and the instantaneous average current adopted by the differential temperature battery state-of-charge SOC estimation model can be obtained in a short time, and after the differential temperature battery state-of-charge SOC estimation model is established, the estimation efficiency of the battery state-of-charge SOC can be improved, and the energy, time and cost are saved.
In a more specific technical solution, S1 includes:
s11, performing constant-current constant-voltage full charge operation on a battery to be tested;
S12, carrying out standing operation on the battery to be tested according to preset standing time;
S13, performing SOC interval discharging operation for the battery to be tested for at least 2 times until the battery to be tested reaches a preset test termination charge state, wherein interval standing operation is performed in an interval period between the SOC interval discharging operations.
In a more specific technical solution, S2 includes:
S21, extracting a preset period of end voltage difference delta U on、ΔUoff before and after instant power-on and power-off of each time from the end voltage difference data;
S22, processing according to the terminal voltage difference data to obtain the current instantaneous average current I Mean of the battery to be tested;
S23, comparing the instantaneous average current I Mean with the voltage difference delta U on、ΔUoff at the preset time intervals before and after the instantaneous power-on and power-off to obtain the equivalent internal resistance of the instantaneous power-on and power-off:
Ron=ΔUon/IMean
Roff=ΔUoff/IMean
where Mean represents average, on represents power on, and off represents power off.
In a more specific technical scheme, in step S3, a first-order function and a double-exponential function are adopted to instantly electrify and deenergize equivalent internal resistances under different battery charge states SOC、/>Curve fitting operations were performed separately using the following logic:
f(x) = p1×x + p2；
f(x) = a×exp(b×x)+c×exp(d×x)；
g(x) = p1×x + p2；
g(x) = a×exp(b×x)+c×exp(d×x)；
obtaining the relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC: =f(SOC)、/> relation parameters of =g (SOC) and power on/off/> And/>；
Wherein f represents a relationship function between the instantaneous power-on equivalent internal resistance and the battery state of charge, g represents a relationship function between the instantaneous power-off equivalent internal resistance and the battery state of charge, a is a first data point fitting parameter, b is a second data point fitting parameter, c is a third data point fitting parameter, d is a fourth data point fitting parameter, p 1 represents a polynomial first term coefficient, p 2 represents a polynomial second term coefficient, and x represents a value of the battery state of charge SOC.
According to the invention, in the differential temperature battery state of charge SOC estimation model, the calculation method of the relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC is simple, and the on-line SOC modeling and estimation can be realized only by measuring and calculating the instantaneous on-off equivalent internal resistance.
In a more specific technical scheme, in S4, the following logic is utilized to realize equivalent internal resistance according to instant power-on and power-off、And relation parameter/>And/>Constructing an SOC estimation mathematical model:
Where est denotes the expected energy consumption, T denotes the ambient temperature, Representing the state of charge SOC of the battery at the estimated energy consumption est and the ambient temperature T,/>, andRepresenting inverse function of instantaneous power-on equivalent internal resistance and SOC relation of battery charge state,/>And the inverse function of the relation between the instantaneous power-off equivalent internal resistance and the state of charge (SOC) of the battery is represented.
In a more specific technical solution, S5 includes:
S51, repeating test operation according to S1 to S4 at not less than 2 environmental temperatures to extract parameters and obtain differential temperature test parameters;
s52, according to the differential temperature test parameters, the differential temperature offset is obtained, and accordingly the change relation between the differential temperature offset and the battery state of charge (SOC) is determined.
In a more specific technical scheme, in step S6, according to the repeated test result, the following logic is used to perform linear fitting through a third-order polynomial to obtain a temperature offset model:
In the method, in the process of the invention, Representing the instantaneous power-on equivalent internal resistance change value,/>Representing the instantaneous power-on equivalent internal resistance change value when the ambient temperature is T,/>Representing the equivalent internal resistance change value of instant power failure,/>And (3) representing an instantaneous power-off equivalent internal resistance change value when the ambient temperature is T, wherein e is a fifth data point fitting parameter, h is a sixth data point fitting parameter, j is a seventh data point fitting parameter, and k is an eighth data point fitting parameter.
The invention gets rid of the dependence on the SOC-OCV curve, and the relationship between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC is more remarkable than the relationship between the internal resistance and the residual electric quantity in the prior art, so that the estimation error is reduced, and the model update is simpler when the battery ages.
In a more specific technical solution, S7 includes:
s71, carrying out addition operation on the difference temperature offset and a preset standard temperature offset to obtain an addition result;
s72, according to the addition result, the relation between the internal resistance and the battery charge state at different temperatures is obtained through processing.
In a more specific technical scheme, in S8, the obtained differential temperature battery state of charge SOC estimation model is extended using the following logic:
Wherein, Representing the power-on state relation parameter when the ambient temperature is T,/>A power-off state relation parameter when the ambient temperature is T; /(I)Indicates the instantaneous power-on equivalent internal resistance,/>, when the ambient temperature is TAnd the instantaneous power-off equivalent internal resistance when the ambient temperature is T is shown.
In a more specific technical scheme, the SOC estimation system based on-off instantaneous equivalent internal resistance combination comprises:
the SOC-OCV testing module is used for carrying out SOC-OCV testing on the battery to be tested at a preset temperature to obtain a testing result, and processing to obtain terminal voltage difference data according to the testing result;
the instantaneous power-on and power-off equivalent internal resistance acquisition module is used for processing to obtain the terminal voltage difference and the instantaneous average current of preset time periods before and after the instantaneous power-on and power-off according to the terminal voltage difference data so as to obtain the instantaneous power-on and power-off equivalent internal resistance, and the instantaneous power-on and power-off equivalent internal resistance acquisition module is connected with the SOC-OCV test module;
The equivalent internal resistance curve fitting module performs curve fitting operation on the battery to be tested to obtain the relation and relation parameters of the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge (SOC), and is connected with the instantaneous power-on and power-off equivalent internal resistance obtaining module;
the SOC estimation model building module is used for building an SOC estimation mathematical model according to the instantaneous power-on and power-off equivalent internal resistance and the relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC, and is connected with the equivalent internal resistance curve fitting module and the instantaneous power-on and power-off equivalent internal resistance acquisition module;
The difference temperature offset obtaining module is used for obtaining repeated test results through repeated test operation under different environment temperatures, wherein the repeated test results comprise: the system comprises an environment temperature corresponding to the instantaneous power-on and power-off equivalent internal resistance, a differential temperature offset relative to a preset standard environment temperature, and a change relation between the differential temperature offset and a battery state of charge (SOC), wherein a differential temperature offset acquisition module is connected with an SOC-OCV test module and an SOC estimation model construction module;
The temperature deviation model construction module is used for acquiring characteristic information of the differential temperature deviation amount so as to obtain a temperature deviation model of the instantaneous power-on and power-off equivalent internal resistance through processing according to the repeated test result, and is connected with the differential temperature deviation amount acquisition module;
the instantaneous internal resistance and state of charge relation acquisition module is used for processing the differential temperature offset by using the temperature offset model so as to acquire the relation between the internal resistance and the state of charge of the battery at different temperatures, and the instantaneous internal resistance and state of charge relation acquisition module at the differential temperature is connected with the temperature offset model construction module;
The differential temperature SOC estimation model expansion module is used for expanding an SOC estimation mathematical model according to the relationship between the internal resistance and the battery state of charge at different temperatures so as to obtain a differential temperature battery state of charge SOC estimation model, and the differential temperature SOC estimation model expansion module is connected with the relationship obtaining module of the instantaneous internal resistance and the state of charge at different temperatures;
the state of charge estimation result acquisition module is used for estimating the current battery state of charge of the battery to be measured by using the differential temperature battery state of charge SOC estimation model, and is connected with the differential temperature SOC estimation model expansion module.
Compared with the prior art, the invention has the following advantages:
The invention establishes the SOC estimation model of the battery with different temperature and expands the application range of the estimation method. The instantaneous power-on and power-off equivalent internal resistances and the instantaneous average current adopted by the differential temperature battery state-of-charge SOC estimation model can be obtained in a short time, and after the differential temperature battery state-of-charge SOC estimation model is established, the estimation efficiency of the battery state-of-charge SOC can be improved, and the energy, time and cost are saved.
According to the invention, in the differential temperature battery state of charge SOC estimation model, the calculation method of the relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC is simple, and the on-line SOC modeling and estimation can be realized only by measuring and calculating the instantaneous on-off equivalent internal resistance.
The invention gets rid of the dependence on the SOC-OCV curve, and the relationship between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC is more remarkable than the relationship between the internal resistance and the residual electric quantity in the prior art, so that the estimation error is reduced, and the model update is simpler when the battery ages.
The method solves the technical problems of limited application range, low estimation operation efficiency, high estimation cost, complex estimation model structure and low estimation precision in the prior art.
Drawings
Fig. 1 is a schematic diagram of basic steps of an SOC estimation method based on-off instantaneous equivalent internal resistance combination in embodiment 1 of the present invention;
FIG. 2 is a schematic diagram showing specific steps of the SOC-OCV test in embodiment 1 of the present invention;
FIG. 3 is a schematic diagram showing the steps for determining the instantaneous power-on/power-off equivalent internal resistance according to embodiment 1 of the present invention;
FIG. 4 is a first order curve fitting diagram of the relationship between the on-off instantaneous ohmic internal resistance and the SOC according to embodiment 1 of the present invention;
FIG. 5 is a graph showing the log-log curve fit of the relationship between the on-off instantaneous ohmic internal resistance and the SOC in example 1 of the present invention;
FIG. 6 is a schematic diagram showing the steps of the repeated test operation of example 1 of the present invention;
FIG. 7 is a graph of ohmic internal resistance offset versus SOC at power-off in example 1 of the present invention;
FIG. 8 is a graph showing the fit of the ohmic internal resistance offset at power-off instant at different temperatures according to example 1 of the present invention;
FIG. 9 is a graph of ohmic internal resistance offset versus SOC at power-on in example 1 of the present invention;
FIG. 10 is a graph showing the fit of the ohmic internal resistance offset at different temperatures for example 1 of the present invention;
FIG. 11 is a schematic diagram showing a specific step of the process differential temperature shift amount according to embodiment 1 of the present invention;
fig. 12 is a schematic diagram of a basic module of an SOC estimation system based on-off instantaneous equivalent internal resistance combination according to embodiment 1 of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions in the embodiments of the present invention will be clearly and completely described in the following in conjunction with the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. 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.
Example 1
As shown in fig. 1, the SOC estimation method based on-off instantaneous equivalent internal resistance combination provided by the invention comprises the following basic steps:
s1, performing SOC-OCV test on a battery to be tested at a preset temperature to obtain a test result, and processing to obtain terminal voltage difference data;
as shown in fig. 2, in the present embodiment, step S1 of the SOC-OCV test further includes the following specific steps:
s11, performing constant-current constant-voltage full charge operation on a battery to be tested;
in this embodiment, for example, may be selected from: the constant-current constant-voltage full charge is carried out on the battery to be tested in a temperature environment at 25 ℃; in the present embodiment, the foregoing battery to be tested includes, but is not limited to: a ternary lithium battery, a lithium iron phosphate power battery;
S12, carrying out standing operation on the battery to be tested according to preset standing time;
in the present embodiment, the preset rest time may be set to, for example: 45 minutes, 1 hour;
S13, performing SOC interval discharging operation for the battery to be tested for at least 2 times until the battery to be tested reaches a preset test termination charge state, wherein interval standing operation is performed in an interval period between the SOC interval discharging operations.
In this embodiment, after the battery to be measured is left to stand for a period of time, the SOC of the battery to be measured is discharged at intervals; in this embodiment, at each interval period, standing is performed until a preset test termination state of charge is reached: soc=0%;
S2, processing to obtain terminal voltage differences and instantaneous average currents at preset time intervals before and after instantaneous power-on and power-off according to the terminal voltage difference data so as to obtain equivalent internal resistances of instantaneous power-on and power-off;
as shown in fig. 3, in this embodiment, the step S2 of obtaining the equivalent internal resistances of instantaneous power-on and power-off further includes the following specific steps:
S21, extracting a preset period of end voltage difference delta U on、ΔUoff before and after instant power-on and power-off of each time from the end voltage difference data;
S22, processing according to the terminal voltage difference data to obtain the current instantaneous average current I Mean of the battery to be tested;
S23, comparing the instantaneous average current I Mean with the voltage difference delta U on、ΔUoff at the preset time intervals before and after the instantaneous power-on and power-off to obtain the equivalent internal resistance of the instantaneous power-on and power-off:
Ron=ΔUon/IMean
Roff=ΔUoff/IMean
where Mean represents average, on represents power on, and off represents power off.
S3, performing curve fitting operation on the battery to be tested to obtain a relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge (SOC) and a relation parameter;
as shown in fig. 4 and 5, in the present embodiment, a first order function is used:
f(x) = p1×x + p2；
g(x) = p1×x + p2；
double exponential function:
f(x) = a×exp(b×x)+c×exp(d×x)；
g(x) = a×exp(b×x)+c×exp(d×x)；
instantaneous power-on and power-off equivalent internal resistances under different battery charge states SOC 、/>Respectively performing curve fitting to obtain/>=f(SOC)、/>Relation parameters of =g (SOC) and power on/off/>And/>；
S4, establishing an SOC estimation mathematical model according to the instantaneous power-on and power-off equivalent internal resistances and the relation between the instantaneous power-on and power-off equivalent internal resistances and the state of charge (SOC) of the battery;
In the present embodiment, the SOC estimation mathematical model constructed in S4 is as follows:
S5, under different environment temperatures, obtaining a repeated test result through repeated test operation, wherein the repeated test result comprises the following steps: the environment temperature corresponding to the equivalent internal resistance of instant power-on and power-off, the differential temperature offset relative to the preset standard environment temperature, and the change relation between the differential temperature offset and the SOC;
As shown in fig. 6, in this embodiment, step S5 of the repeated test operation further includes the following specific steps:
s51, repeating the test operation according to the steps S1 to S4 at not less than 2 environmental temperatures to extract parameters and obtain differential temperature test parameters;
In this embodiment, the setting of different environmental temperatures refers to the actual scene temperature of the battery to be measured in the actual running process of the vehicle, and the environmental temperatures include, but are not limited to: 5 ℃,15 ℃, 35 ℃ and 45 ℃;
s52, according to the differential temperature test parameters, the differential temperature offset is obtained, and accordingly the change relation between the differential temperature offset and the battery state of charge (SOC) is determined.
In this embodiment, the above test is repeated at different temperatures to extract parameters and calculate the equivalent internal resistances of instantaneous power on and power off at different temperatures、/>Obtaining the variation relation between the differential temperature offset and the battery state of charge (SOC) relative to the differential temperature offset at the standard temperature of 25 ℃;
S6, obtaining characteristic information of the differential temperature offset, and processing to obtain a temperature offset model of the instantaneous power-on and power-off equivalent internal resistance according to repeated test results;
As shown in fig. 7, 8 and 9, in the present embodiment, according to the characteristic that the differential temperature offset is substantially unchanged in the whole battery state of charge SOC, the instantaneous power-on and power-off equivalent internal resistance can be obtained 、/>A corresponding temperature excursion model;
as shown in fig. 10, in this embodiment, according to the repeated test result, linear fitting is performed using a third-order polynomial, so as to obtain the following formula:
s7, processing the differential temperature offset by using a temperature offset model to obtain the relationship between the internal resistance and the battery state of charge at different temperatures;
as shown in fig. 11, in the present embodiment, step S7 of processing the differential temperature offset amount further includes the following specific steps:
s71, carrying out addition operation on the difference temperature offset and a preset standard temperature offset to obtain an addition result;
s72, according to the addition result, the relation between the internal resistance and the battery charge state at different temperatures is obtained through processing.
In the embodiment, the instant power-on and power-off equivalent internal resistances obtained at different ambient temperatures、/>Corresponding differential temperature offset is added with preset standard temperature offset at standard temperature to obtain the relation between internal resistance and battery state of charge at different temperatures, so as to realize SOC estimation of the battery state of charge at different temperatures;
In the embodiment, when the ambient temperature is 6 ℃, the equivalent internal resistance offset at the moment of electrification is 0.00049; when the ambient temperature is 15 ℃, the equivalent internal resistance offset at the moment of electrifying is 0.00013; when the ambient temperature is 25 ℃, the equivalent internal resistance offset at the moment of electrifying is 0.00008; when the ambient temperature is 35 ℃, the equivalent internal resistance offset at the moment of electrifying is 0.00011; when the ambient temperature is 45 ℃, the equivalent internal resistance offset at the moment of electrifying is 0.00013;
in the present embodiment, the preset standard temperature offset amount may be set to, for example: 0.00008.
S8, expanding an SOC estimation mathematical model according to the relation between the internal resistance and the battery state of charge at different temperatures to obtain a battery state of charge SOC estimation model at different temperatures;
in this embodiment, the extended differential temperature battery state of charge SOC estimation model is as follows:
s9, estimating the current battery charge state of the battery to be detected by using the differential temperature battery charge state SOC estimation model.
Example 2
In this embodiment, the SOC estimation system based on-off instantaneous equivalent internal resistance combination includes the following basic modules:
the SOC-OCV test module 1 is used for carrying out SOC-OCV test on a battery to be tested at a preset temperature to obtain a test result, and processing to obtain terminal voltage difference data according to the test result;
In the present embodiment, the SOC-OCV test module 1 may employ, for example: the system comprises an SOC-OCV tester and an SOC-OCV test curve characteristic test terminal; in the embodiment, the SOC-OCV test module 1 is deployed on a test site of a battery to be tested, the SOC-OCV test module 1 is connected to a circuit connecting wire through a data transmission line, and the circuit connecting wire is connected to the anode and the cathode of the battery to be tested;
The instantaneous power-on and power-off equivalent internal resistance acquisition module 2 is used for processing to obtain the instantaneous power-on and power-off equivalent internal resistance by processing the terminal voltage difference and the instantaneous average current of preset time periods before and after the instantaneous power-on and power-off according to the terminal voltage difference data, and the instantaneous power-on and power-off equivalent internal resistance acquisition module 2 is connected with the SOC-OCV test module 1;
In the present embodiment, the instantaneous power-on/power-off equivalent internal resistance acquisition module 2 may employ, for example: multimeter, accumulator internal resistance measuring instrument; connecting the instantaneous power-on and power-off equivalent internal resistance acquisition module 2 with the SOC-OCV test module 1 through a data transmission line;
The equivalent internal resistance curve fitting module 3 performs curve fitting operation on the battery to be tested to obtain the relation and relation parameters of the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC, and the equivalent internal resistance curve fitting module 3 is connected with the instantaneous power-on and power-off equivalent internal resistance obtaining module 2;
in the present embodiment, the equivalent internal resistance curve fitting module 3 may employ, for example: MATLAB, python and Origin;
Before the instantaneous power-on and power-off equivalent internal resistance of the battery to be tested is tested, the equivalent internal resistance curve fitting module 3 is preloaded to a test data processing end, and in this embodiment, the test data processing end may employ, for example: the system comprises a PC (personal computer) end, a mobile terminal and a battery data processing cloud platform;
the SOC estimation model construction module 4 is used for establishing an SOC estimation mathematical model according to the instantaneous power-on and power-off equivalent internal resistance and the relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC, and the SOC estimation model construction module 4 is connected with the equivalent internal resistance curve fitting module 3 and the instantaneous power-on and power-off equivalent internal resistance acquisition module 2;
In the present embodiment, the SOC estimation model construction module 4 may employ, for example: a Simulink modeling tool simscape;
The differential temperature offset obtaining module 5 is configured to obtain a repeated test result through repeated test operations under different environmental temperatures, where the repeated test result includes: the temperature difference obtaining module 5 is connected with the SOC-OCV testing module 1 and the SOC estimation model building module 4;
In this embodiment, the differential temperature offset obtaining module 5 triggers the SOC-OCV testing module 1, the instantaneous power on/off equivalent internal resistance obtaining module 2 and the equivalent internal resistance curve fitting module 3, so as to perform repeated test operation on the ternary lithium battery and the lithium iron phosphate power battery to be tested;
In this embodiment, when the ambient temperature is 25 ℃, and the battery state of charge SOC is 5%, the instantaneous internal resistance is 6.8Ω at power-off; when the SOC of the battery is 10%, the internal resistance at the instant of power failure is 6.18 omega; when the SOC of the battery is 15%, the instant internal resistance of the power failure is 5.7Ω; when the SOC of the battery is 20%, the instant internal resistance of the power failure is 5.5 omega; when the SOC of the battery is 30%, the instant internal resistance of the power failure is 5.36 omega; when the SOC of the battery is 40%, the instant internal resistance of the power failure is 5.2 omega; when the SOC of the battery is 50%, the instant internal resistance of the power failure is 4.5 omega; and acquiring data points of curve fitting according to the data.
The temperature deviation model construction module 6 is used for acquiring characteristic information of the differential temperature deviation amount, so as to obtain a temperature deviation model of the instantaneous power-on and power-off equivalent internal resistance through processing according to the repeated test result, and the temperature deviation model construction module 6 is connected with the differential temperature deviation amount acquisition module 5;
In the present embodiment, the temperature shift model construction module 6 may employ, for example: ising model building tools and Simulink temperature model building tools;
The instantaneous internal resistance and state of charge relation acquisition module 7 under different temperatures is used for processing the differential temperature offset by using a temperature offset model to acquire the relation between the internal resistance and the state of charge of the battery under different temperatures, and the instantaneous internal resistance and state of charge relation acquisition module 7 under different temperatures is connected with the temperature offset model construction module 6;
The differential temperature SOC estimation model expansion module 8 is used for expanding an SOC estimation mathematical model according to the relationship between the internal resistance and the battery state of charge at different temperatures to obtain a differential temperature battery state of charge SOC estimation model, and the differential temperature SOC estimation model expansion module 8 is connected with the relationship obtaining module 7 of the instantaneous internal resistance and the state of charge at different temperatures;
In the embodiment, a differential temperature SOC estimation model expansion module 8 and a differential temperature instantaneous internal resistance and state of charge relation acquisition module 7 are deployed to a test data processing end, and model expansion operation is carried out at the test data processing end by utilizing a preloaded Ising model building tool and a Simulink temperature model building tool;
The state of charge estimation result obtaining module 9 is configured to estimate a current battery state of charge of the battery to be measured using a differential temperature battery state of charge SOC estimation model, and the state of charge estimation result obtaining module 9 is connected to the differential temperature SOC estimation model expansion module 8.
In this embodiment, under a specific ambient temperature, a short-time constant-current discharge is performed on a battery to be tested of an unknown state of charge (SOC) of the battery which has been left standing, and the instantaneous internal resistance equivalent to power on and power off is extracted、/>Obtaining the instant power-on and power-off equivalent internal resistance/>, under the ambient temperature, by using a temperature deviation model、/>The state of charge estimation result acquisition module 9 uses a differential temperature battery state of charge SOC estimation model according to the instantaneous power-on and power-off equivalent internal resistance/>, in relation to the battery state of charge SOC、/>And the relation with the battery state of charge SOC is used for finding out the battery state of charge SOC at the ambient temperature, so as to realize the battery state of charge SOC estimation at different ambient temperatures.
In conclusion, the invention establishes the SOC estimation model of the battery with different temperature and expands the application range of the estimation method. The instantaneous power-on and power-off equivalent internal resistances and the instantaneous average current adopted by the differential temperature battery state-of-charge SOC estimation model can be obtained in a short time, and after the differential temperature battery state-of-charge SOC estimation model is established, the estimation efficiency of the battery state-of-charge SOC can be improved, and the energy, time and cost are saved.
According to the invention, in the differential temperature battery state of charge SOC estimation model, the calculation method of the relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC is simple, and the on-line SOC modeling and estimation can be realized only by measuring and calculating the instantaneous on-off equivalent internal resistance.
The invention gets rid of the dependence on the SOC-OCV curve, and the relationship between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC is more remarkable than the relationship between the internal resistance and the residual electric quantity in the prior art, so that the estimation error is reduced, and the model update is simpler when the battery ages.
The method solves the technical problems of limited application range, low estimation operation efficiency, high estimation cost, complex estimation model structure and low estimation precision in the prior art.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. The SOC estimation method based on the combination of the on-off instantaneous equivalent internal resistances is characterized by comprising the following steps:
s1, performing SOC-OCV test on a battery to be tested at a preset temperature to obtain a test result, and processing to obtain terminal voltage difference data;
s2, processing to obtain terminal voltage differences and instantaneous average currents of preset time periods before and after instantaneous power-on and power-off according to the terminal voltage difference data so as to obtain the equivalent internal resistances of instantaneous power-on and power-off;
s3, performing curve fitting operation on the battery to be tested to obtain the relation and relation parameters of the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge (SOC);
s4, establishing an SOC estimation mathematical model according to the instantaneous power-on and power-off equivalent internal resistance and the relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC;
S5, under different environment temperatures, obtaining a repeated test result through repeated test operation, wherein the repeated test result comprises the following steps: the environment temperature corresponding to the instantaneous power-on and power-off equivalent internal resistance, the differential temperature offset relative to the preset standard environment temperature, and the change relation between the differential temperature offset and the battery state of charge (SOC);
S6, obtaining characteristic information of the differential temperature offset, and processing to obtain a temperature offset model of the instantaneous power-on and power-off equivalent internal resistance according to the repeated test result;
S7, processing the differential temperature offset by using the temperature offset model to obtain the relation between the internal resistance and the battery state of charge at different temperatures;
S8, expanding the SOC estimation mathematical model according to the relation between the internal resistance and the battery state of charge at different temperatures to obtain a differential temperature battery state of charge SOC estimation model;
and S9, estimating the current battery charge state of the battery to be detected by using the battery charge state SOC estimation model with different temperatures.
2. The SOC estimation method based on-off instantaneous equivalent internal resistance combination according to claim 1, wherein the S1 includes:
S11, performing constant-current constant-voltage full charge operation on the battery to be tested;
S12, carrying out standing operation on the battery to be tested according to preset standing time;
S13, performing not less than 2 times of SOC interval discharging operation on the battery to be tested until the battery to be tested reaches a preset test termination charge state, wherein interval standing operation is performed in an interval period between the SOC interval discharging operation.
3. The SOC estimation method based on-off instantaneous equivalent internal resistance combination according to claim 1, wherein the S2 includes:
s21, extracting a preset period of end voltage difference delta U on、ΔUoff before and after the instant power-on and power-off of each time from the end voltage difference data;
S22, processing to obtain the current instantaneous average current I Mean of the battery to be tested according to the terminal voltage difference data;
S23, comparing the instantaneous average current I Mean with the terminal voltage difference delta U on、ΔUoff of the preset time period before and after the instantaneous power-on and power-off to obtain the equivalent internal resistance of the instantaneous power-on and power-off:
Ron=ΔUon/IMean
Roff=ΔUoff/IMean
where Mean represents average, on represents power on, and off represents power off.
4. The SOC estimation method based on-off instantaneous equivalent internal resistance combination as claimed in claim 1, wherein in the S3, a first order function and a double exponential function are adopted to perform instantaneous power-on and power-off equivalent internal resistances under different battery states of charge SOCs、/>The curve fitting operations were performed separately using the following logic:
f(x) = p1×x + p2；
f(x) = a×exp(b×x)+c×exp(d×x)；
Obtaining the relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC: =f(SOC)、/> the relation parameter of =g (SOC) and power on/off/> And/>；
Wherein f represents a relationship function between the instantaneous power-on equivalent internal resistance and the battery state of charge, g represents a relationship function between the instantaneous power-off equivalent internal resistance and the battery state of charge, a is a first data point fitting parameter, b is a second data point fitting parameter, c is a third data point fitting parameter, d is a fourth data point fitting parameter, p 1 represents a polynomial first term coefficient, p 2 represents a polynomial second term coefficient, and x represents a value of the battery state of charge SOC.
5. The SOC estimation method based on-off instant equivalent internal resistance combination as claimed in claim 1, wherein in S4, the logic is used to determine the instant on-off equivalent internal resistance、/>And the relation parameter/>AndConstructing the SOC estimation mathematical model:
where est denotes the expected energy consumption, T denotes the ambient temperature, Representing the state of charge, SOC, of the battery at the estimated energy consumption est and the ambient temperature, T,/>, ofRepresenting the inverse function of the relation between the instantaneous power-on equivalent internal resistance and the state of charge (SOC) of the battery,/>And expressing the inverse function of the relation between the instantaneous power-off equivalent internal resistance and the state of charge (SOC) of the battery.
6. The SOC estimation method based on-off instantaneous equivalent internal resistance combination according to claim 1, wherein the S5 includes:
S51, repeating test operation according to the steps from S1 to S4 at the environmental temperature of not less than 2 types, so as to extract parameters and obtain differential temperature test parameters;
s52, according to the differential temperature test parameters, the differential temperature offset is obtained, and accordingly the change relation between the differential temperature offset and the battery state of charge SOC is determined.
7. The SOC estimation method based on-off instantaneous equivalent internal resistance combination according to claim 1, wherein in S6, according to the repeated test result, linear fitting is performed by using the following logic through a third-order polynomial to obtain the temperature offset model:
In the method, in the process of the invention, Representing the instantaneous power-on equivalent internal resistance change value,/>Representing the instantaneous power-on equivalent internal resistance change value when the ambient temperature is T,/>Representing the equivalent internal resistance change value of instant power failure,/>And the instantaneous power-off equivalent internal resistance change value when the ambient temperature is T is represented, e is a fifth data point fitting parameter, h is a sixth data point fitting parameter, j is a seventh data point fitting parameter, and k is an eighth data point fitting parameter.
8. The SOC estimation method based on-off instantaneous equivalent internal resistance combination according to claim 1, wherein the S7 includes:
S71, carrying out addition operation on the difference temperature offset and a preset standard temperature offset to obtain an addition result;
s72, according to the addition result, the relation between the internal resistance and the battery state of charge at different temperatures is obtained through processing.
9. The SOC estimation method based on-off instantaneous equivalent internal resistance combination according to claim 1, wherein in the step S8, the obtained differential temperature battery state of charge SOC estimation model is expanded by using the following logic:
Wherein, Representing the power-on state relation parameter when the ambient temperature is T,/>A power-off state relation parameter when the ambient temperature is T; /(I)Indicates the instantaneous power-on equivalent internal resistance,/>, when the ambient temperature is TAnd the instantaneous power-off equivalent internal resistance when the ambient temperature is T is shown.
10. SOC estimation system based on combination of break-make instantaneous equivalent internal resistance, which is characterized in that the system comprises:
the SOC-OCV testing module is used for carrying out SOC-OCV testing on the battery to be tested at a preset temperature to obtain a testing result, and processing to obtain terminal voltage difference data according to the testing result;
The instantaneous power-on and power-off equivalent internal resistance acquisition module is used for processing and obtaining the terminal voltage difference and the instantaneous average current of preset time periods before and after the instantaneous power-on and power-off according to the terminal voltage difference data so as to obtain the instantaneous power-on and power-off equivalent internal resistance through processing, and the instantaneous power-on and power-off equivalent internal resistance acquisition module is connected with the SOC-OCV test module;
The equivalent internal resistance curve fitting module is used for performing curve fitting operation on the battery to be tested to obtain the relation and relation parameters of the instant power-on and power-off equivalent internal resistance and the battery state of charge SOC, and is connected with the instant power-on and power-off equivalent internal resistance obtaining module;
The SOC estimation model building module is used for building an SOC estimation mathematical model according to the instantaneous power-on and power-off equivalent internal resistance and the relation between the instantaneous power-on and power-off equivalent internal resistance and the battery state of charge SOC, and is connected with the equivalent internal resistance curve fitting module and the instantaneous power-on and power-off equivalent internal resistance acquisition module;
The differential temperature offset obtaining module is used for obtaining repeated test results through repeated test operation under different environment temperatures, wherein the repeated test results comprise: the environment temperature corresponding to the instantaneous power-on and power-off equivalent internal resistance, the differential temperature offset relative to a preset standard environment temperature and the change relation between the differential temperature offset and the battery state of charge (SOC), and the differential temperature offset acquisition module is connected with the SOC-OCV test module and the SOC estimation model construction module;
The temperature deviation model construction module is used for acquiring characteristic information of the differential temperature deviation amount so as to obtain a temperature deviation model of the instantaneous power-on and power-off equivalent internal resistance through processing according to the repeated test result, and the temperature deviation model construction module is connected with the differential temperature deviation amount acquisition module;
The temperature deviation model is used for processing the difference temperature deviation quantity to obtain the relationship between the internal resistance and the battery state of charge at different temperatures, and the relationship obtaining module between the instantaneous internal resistance and the state of charge at different temperatures is connected with the temperature deviation model construction module;
the differential temperature SOC estimation model expansion module is used for expanding the SOC estimation mathematical model according to the relationship between the internal resistance and the battery state of charge at different temperatures so as to obtain a differential temperature battery state of charge SOC estimation model, and the differential temperature SOC estimation model expansion module is connected with the relationship obtaining module of the instantaneous internal resistance and the state of charge at different temperatures;
The state of charge estimation result acquisition module is used for estimating the current state of charge of the battery to be measured by using the differential temperature battery state of charge SOC estimation model, and is connected with the differential temperature SOC estimation model expansion module.
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