Method for detecting the state of charge of a battery

Abstract

The application discloses a method for detecting the state of battery power, comprising the following steps: dividing the estimation error by the sum of the estimation error and the measurement error to obtain an error coefficient; calculating the difference between the last discharge depth after the previous charge and discharge of the battery and the discharge depth measured at the initial moment; multiplying the difference by the error coefficient to obtain the discharge depth difference; adding the discharge depth difference to the last discharge depth to obtain the initial discharge depth; and using the instantaneous voltage and the changed charge amount at each moment and the dual extended Kalman filter (DEKF) to calculate the battery discharge depth at each moment based on the initial discharge depth when the battery is charged and discharged, and converting the battery discharge depth into the remaining battery power percentage.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of battery, in particular to a battery state of charge detection method. BACKGROUND

[0002] With the rapid development of rechargeable battery technology, the increasing attention to harmful gas and carbon emission pollution, electric vehicles gradually become the future direction of the automotive industry. In order to make electric vehicles gradually popular in the future. Whether it is any type of electric vehicle, the detection and evaluation of the remaining battery percentage of the electric vehicle is crucial. SUMMARY

[0003] The technical problem to be solved by the present application is to provide a battery state of charge detection method to solve the problems of the prior art. The present application is suitable for detecting the remaining battery percentage of the battery and comprises the following steps: using the open circuit voltage method to discharge the battery, measuring the relationship curve between the open circuit voltage and the discharge depth of the battery during the discharge process, and performing function to establish an open circuit voltage curve model; calculating the last discharge depth of the previous charge and discharge of the battery at the end of the previous charge and discharge; calculating the difference between the last discharge depth of the previous charge and discharge of the battery and the actual discharge depth at the end of the previous charge and discharge of the battery to generate an estimation error; measuring the open circuit voltage of the battery at the initial time; converting the measured open circuit voltage at the initial time into the discharge depth at the initial time as the measured discharge depth based on the open circuit voltage curve model; calculating the difference between the last discharge depth of the previous charge and discharge of the battery and the measured discharge depth; adjusting the calculated difference between the last discharge depth of the previous charge and discharge of the battery and the measured discharge depth according to the estimation error to obtain the discharge depth difference; adding the discharge depth difference to the last discharge depth of the previous charge and discharge of the battery to obtain the initial discharge depth at the initial time; converting the initial discharge depth into an actual initial open circuit voltage based on the open circuit voltage curve model; establishing a battery model, including connecting a direct current voltage source and an internal resistance in series between the first end and the second end of the battery model, connecting the direct current voltage source in series with the internal resistance, and taking the actual initial open circuit voltage as the initial voltage of the direct current voltage source; measuring the equivalent voltage between the first end and the second end of the battery model; subtracting the equivalent voltage between the first end and the second end of the battery model from the actual initial open circuit voltage to obtain the voltage of the internal resistance; simulating a parameter of the battery model at a certain time using the battery model, including measuring the open circuit voltage and the equivalent voltage of the direct current voltage source; and substituting the parameter into the open circuit voltage curve model to calculate the remaining battery percentage of the battery model at the certain time.

[0004] In an embodiment, the battery state of charge detection method further comprises the following steps: substituting the last discharge depth of the previous charge and discharge of the battery, the measured discharge depth, the estimation error, and a measurement error into the following equation to calculate the initial discharge depth:

[0005]

[0006] wherein DOD0 represents the initial depth of discharge, DOD A represents the last depth of discharge, DOD F represents the measured depth of discharge, P represents the estimation error, and S represents the measurement error.

[0007] In one embodiment, the method for detecting the state of charge of the battery further comprises the step of: calculating the measurement error S according to an idle time interval between the end of the previous charge-discharge and the time of calculation, as shown in the following equation:

[0008] S = e -ΔT ,

[0009] wherein S represents the measurement error, and ΔT represents the idle time.

[0010] In one embodiment, the method for detecting the state of charge of the battery further comprises the steps of: measuring a first open circuit voltage of the battery at a certain time; measuring a second open circuit voltage of the battery at a next time after the certain time; calculating the difference between the second open circuit voltage and the first open circuit voltage, and taking the absolute value to obtain a pressure difference; and substituting the pressure difference into the following equation to calculate the measurement error:

[0011]

[0012] wherein S represents the measurement error, dv represents the pressure difference, mdv represents a preset pressure difference, Ndv represents a stable pressure difference preset at an ideal stable state, and C represents a scaling factor.

[0013] In one embodiment, the method for detecting the state of charge of the battery further comprises the steps of: defining the relationship between the open circuit voltage and the depth of discharge into a function of Voc = f(DOD) and DOD = f(Voc), wherein Voc represents the open circuit voltage, and DOD represents the depth of discharge, and performing function fitting with the least square error to determine the selected function order, as shown in the following first equation:

[0014]

[0015] wherein Voc i represents the open circuit voltage, DOD i represents the depth of discharge, MSE represents the least square error, and m represents the number of experimental data points referred to when fitting the first equation.

[0016] In one embodiment, the method for detecting the state of charge of the battery further comprises the following steps: establishing a linear battery model comprises a DC voltage source and an internal resistance in the battery model; dividing the amount of charge changed from the previous time to a certain time by the maximum amount of charge of the linear battery model to obtain a charge ratio; adding the discharge depth of the linear battery model at the previous time to the charge ratio to obtain the discharge depth of the linear battery model at a certain time, which is expressed by the equation:

[0017]

[0018] wherein represents the discharge depth at a certain time, DOD k-1 represents the discharge depth at the previous time, ΔQ represents the amount of charge changed from the previous time to a certain time, Q max represents the maximum amount of charge;

[0019] subtracting the voltage of the internal resistance at a certain time from the open circuit voltage of the DC voltage source of the linear battery model at a certain time to calculate the equivalent voltage of the linear battery model at a certain time, which is expressed by the equation:

[0020]

[0021] wherein V k represents the equivalent voltage at a certain time, f(DOD k ) represents the open circuit voltage at a certain time, represents the voltage of the internal resistance at a certain time;

[0022] substituting the actual voltage measurement of the battery at a certain time and the estimated value of the equivalent voltage of the linear battery model calculated according to the voltage of the internal resistance and the discharge depth of the linear battery model into the DEKF to calculate the actual voltage of the internal resistance, and updating the system noise of the linear battery model by the second equation; substituting the actual voltage measurement at a certain time and the estimated value of the equivalent voltage calculated according to the actual voltage of the internal resistance and the discharge depth of the linear battery model into the DEKF to calculate the actual discharge depth of the linear battery model, and updating the system noise of the linear battery model by the second equation.

[0023] wherein the second equation is as follows:

[0024]

[0025] wherein Q k represents the system noise at model k time, when k is zero, Q0=MSE, Z k represents the actual voltage measurement at k time, h(x k represents the discharge depth at k time according to the equation the calculated voltage estimate.

[0026] In one embodiment, the method for detecting the state of charge of the battery further comprises the steps of: establishing a first-order RC battery model comprising a DC voltage source, an internal resistance, and a resistance-capacitance (RC) circuit, the internal resistance being connected in series between the DC voltage source and the RC circuit, the RC circuit comprising an equivalent resistance and an equivalent capacitance connected in parallel to each other; calculating an equivalent voltage of the first-order RC battery model; multiplying the equivalent resistance value of the RC circuit by the equivalent capacitance value to calculate a time constant; and substituting the equivalent resistance value, the equivalent voltage, and the time constant into the following equation to calculate a voltage of the RC circuit and a depth of discharge (DOD) of the battery:

[0027]

[0028] where V th represents the equivalent voltage of the RC circuit, DOD represents the depth of discharge, k represents a certain time, t represents a discharge time length, τ represents the time constant of the RC circuit, k-1 represents a previous time, R th represents the equivalent resistance value of the RC circuit, ΔQ represents a change in charge amount from the previous time to the certain time, Q max represents a maximum charge amount, I k represents a current value at the certain time; and calculating an equivalent voltage estimate of the first-order RC battery model according to the depth of discharge, a voltage of the internal resistance, and a voltage of the RC circuit, as follows:

[0029]

[0030] where V k represents the equivalent voltage estimate, f(DOD k ) represents an open-circuit voltage, represents the voltage of the internal resistance, represents the voltage of the RC circuit. The voltage of the RC circuit is calculated using a capacitance value and a resistance value of the first-order RC battery model, the measured voltage value of the actual battery is substituted into the DEKF along with the voltage estimate calculated according to the voltage of the internal resistance, the equivalent voltage estimate of the RC circuit, and the depth of discharge estimate of the next time to calculate an actual voltage of the internal resistance and actual capacitance and resistance values of the first-order RC battery model, and the second equation is used to update the system noise of the first-order RC battery model; the measured value of the actual battery at the certain time is substituted into the DEKF along with the actual voltage of the internal resistance, the actual capacitance and resistance values of the first-order RC battery model, and the voltage estimate calculated according to the depth of discharge estimate of the next time to calculate an actual depth of discharge at the next time and a voltage value of the adjusted RC circuit, and the second equation is used to update the system noise of the first-order RC battery model. The second equation is as follows:

[0031]

[0032] wherein Q k represents the system noise at time k, when k is zero, Q0= MSE, Z k represents the actual voltage measurement, h(x k ) represents the equivalent voltage estimate.

[0033] As described above, the present application provides a battery state of charge detection method, which uses a dual extended Kalman filter in its computational technique. During the charging and discharging of the battery, the actual voltage measurement is used to optimize the calculation results of the coulomb counting method every second, thereby improving the calculation accuracy of the remaining battery percentage.

[0034] In order to further understand the features and technical contents of the present application, please refer to the following detailed description and drawings of the present application. However, the drawings provided are only used for reference and illustration, and are not used to limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 The flow chart of the battery state of charge detection method of the embodiment of the present application.

[0036] Figure 2A The schematic diagram of the linear battery model of the battery state of charge detection method of the embodiment of the present application.

[0037] Figure 2B The schematic diagram of the first-order RC battery model of the battery state of charge detection method of the embodiment of the present application.

[0038] Figure 3 The curve diagram of the open-circuit voltage and the depth of discharge of the battery of the battery state of charge detection method of the embodiment of the present application.

[0039] Figure 4 The curve diagram of the open-circuit voltage and the depth of discharge of the battery of the battery state of charge detection method of the embodiment of the present application. DETAILED DESCRIPTION

[0040] The following detailed description discusses embodiments of the application in terms of specific embodiments thereof. Those skilled in the art will recognize that the embodiments described herein are not intended to be exhaustive or represent the only designs in which the application can be practiced. Those skilled in the art will further recognize that they can readily use other embodiments of the application and modifications and alterations of the embodiments described herein, without departing from the scope and spirit of the application. Those skilled in the art will appreciate the benefits of the application based on the following detailed description. The drawings described herein are for illustration purposes only. A clear understanding of the present application is provided by the detailed description in conjunction with the accompanying drawings, in which reference characters refer to like numerals throughout the various figures. The following detailed description is not intended to limit the application. Other means of implementing the various processes described herein can be employed and the disclosed aspects should not be limited to those disclosed herein without intent to limit the scope of the application.

[0041] Please refer to Figures 1 to 4 wherein Figure 1 is a flow chart of the method for detecting the state of charge of a battery according to an embodiment of the application; Figure 2A is a schematic diagram of a linear battery model of the method for detecting the state of charge of a battery according to an embodiment of the application; Figure 2B is a schematic diagram of a first-order RC battery model of the method for detecting the state of charge of a battery according to an embodiment of the application; Figure 3 and Figure 4 are both graphs of open-circuit voltage versus depth of discharge of a battery of the method for detecting the state of charge of a battery according to an embodiment of the application, Figure 3 is a graph of open-circuit voltage versus depth of discharge of a battery based on actual experimental values when performing open-circuit voltage experiments on a physical battery; Figure 4 is a graph of open-circuit voltage versus depth of discharge of a battery based on equation fitting.

[0042] The method for detecting the state of charge of a battery according to an embodiment of the application can include steps S101-S117 as shown in Figure 1 In practice, the execution order, number of times, and content of these steps can be adjusted as appropriate according to actual needs, and some steps can be selectively omitted according to needs.

[0043] In step S101, the battery is discharged using the open-circuit voltage method to measure the relationship curve between open-circuit voltage (OCV) and depth of discharge (DOD) during discharging, and to perform functionalization to establish an open-circuit voltage curve model, for example, as shown in Figure 3

[0044] If necessary, the relationship curve between open-circuit voltage and depth of discharge is functionalized into Voc=f(DOD) and DOD=f(Voc), where Voc represents open-circuit voltage and DOD represents depth of discharge, and the function is fitted using the least squares method to determine the selected function order number, such as the following first equation, for example​Figure 3 The open-circuit voltage curve model shown is functionally fitted with the least square error, for example Figure 4 The fitting shown uses a ninth-order equation, and the order of the function selected is determined by the minimum mean square error (MSE). The following equation is used:

[0045]

[0046] where Voc represents the open-circuit voltage, DOD represents the depth of discharge, MSE represents the minimum mean square error, and m represents the number of experimental data points referenced when fitting the equation. i i

[0047] If the DOD=f(Voc) curve cannot be fitted with a single function, the curve is segmented according to the trend and fitted with multiple polynomials. This related technology is generally known to those skilled in the art and will not be described here.

[0048] In step S103, the initial state of charge of the battery is obtained, which can include executing the procedures described below.

[0049] First, the last depth of discharge (Depth of Discharge, DOD) of the previous charge and discharge of the battery is calculated at the time when the previous charge and discharge of the battery ended. The difference between the last depth of discharge of the previous charge and discharge of the battery and the actual depth of discharge at the time when the previous charge and discharge of the battery ended is calculated to generate an estimation error. Then, the estimation error is divided by the sum of the estimation error and a measurement error to obtain an error coefficient, which is represented by the following equation:

[0050] where P represents the estimation error, S represents the measurement error, and K represents the error coefficient.

[0051] The measurement error described above is illustrated by two calculation methods as follows.

[0052] In the first example, the measurement error is calculated according to an idle time interval between the end of the previous charge and discharge and the time of calculation, which is represented by the following equation:

[0053] S = e -ΔT ,

[0054] where S represents the measurement error and ΔT represents the idle time.

[0055] In the second example, the first open-circuit voltage of the battery at a certain time is measured, then the second open-circuit voltage of the battery at a certain time is measured, and then the difference between the second open-circuit voltage and the first open-circuit voltage is calculated. The absolute value of the calculated result is taken to obtain the pressure difference as follows:

[0056] dv = |Voc k ​​-Voc k-t |,

[0057] where dv represents the pressure difference, Voc k represents the open-circuit voltage at the next moment, Voc k-t represents the open-circuit voltage at the previous moment, and t represents the time interval between the previous moment and the moment before the previous moment.

[0058] Next, based on the above pressure difference, the measurement error is calculated as the following equation:

[0059]

[0060] where S represents the measurement error, dv represents the pressure difference, mdv represents a preset pressure difference (such as but not limited to 1000), Ndv represents a stable pressure difference preset under an ideal steady state (such as but not limited to 40), and C represents a scaling factor (such as but not limited to 10). When dv < Ndv, it enters the steady state, and when dv < max dv, the depth of discharge DOD F is only of reference value. The above t, Ndv, mdv, and C depend on the cell capacity, characteristics, and application.

[0061] After obtaining the measurement error in the above procedure, the final depth of discharge, measured depth of discharge, estimation error, and a measurement error of the previous charge and discharge of the battery are substituted into the following equation to calculate the initial depth of discharge:

[0062]

[0063] where DODO0 represents the initial depth of discharge, DOD A represents the final depth of discharge of the previous charge and discharge of the battery, DOD F represents the measured depth of discharge, P represents the estimation error, and S represents the measurement error.

[0064] In step S105, as Figure 2A shown, the open-circuit voltage Voc of the DC voltage source of the linear battery model is subtracted from the terminal voltage V of the linear battery model to obtain the voltage of the internal resistance R, which is expressed by the following equation:

[0065] V int = f(DOD1) - V,

[0066] where V int represents the voltage of the internal resistance R of the linear battery model, f(DOD1) represents the open-circuit voltage Voc of the linear battery model, and V represents the voltage between the first end and the second end of the linear battery model.

[0067] As Figure 2BAs shown, the voltage across the internal resistance is obtained by subtracting the open-circuit voltage Voc of the DC voltage source of the linear battery model from the terminal voltage of the linear battery model, expressed by the following equation:

[0068] V int =f(DOD1)-VV th ,

[0069] Where V int Let f(DOD1) represent the voltage across the internal resistance R of the linear battery model, f(DOD1) represent the open-circuit voltage Voc of the linear battery model, and V represent the voltage between the first and second terminals of the linear battery model. th This represents the voltage of the RC circuit in the equivalent circuit.

[0070] In step S107, a battery model is established to simulate the actual charging and discharging characteristics of a battery, for example... Figure 2A The embodiment shown uses a linear battery model, such as... Figure 2B The first-order RC battery model shown is only an example and is not limited to this application. In practice, it can also be applied to second-order RC battery models or other battery models.

[0071] like Figure 2A As shown, the linear battery model may include a DC voltage source (whose voltage is represented by Voc) and an internal resistor R connected in series with the DC voltage source between the first and second terminals of the linear battery model.

[0072] like Figure 2B As shown, a first-order RC battery model includes a DC voltage source (whose voltage is represented by Voc), an internal resistor Rin, and an RC circuit. The internal resistor Rin is connected in series between the DC voltage source and the RC circuit. Figure 2B The first-order RC battery model shown includes a set of resistors and capacitors connected in parallel, with values ​​as follows: Figure 2B The equivalent resistance Rth and equivalent capacitance Cth are shown. In a second-order RC battery model, the RC circuit can contain two sets of resistors and capacitors connected in parallel, and so on.

[0073] The initial battery parameters and battery state of charge are estimated using a mathematical model. This embodiment employs the equations of an existing Dual Extended Kalman Filter (DEKF), as follows:

[0074] x k -=f(x k-1 u k-1 w k-1 ),

[0075] z k =h(xk , v k ).

[0076] It should be understood that the content of the equations of the dual extended Kalman filter, which is well known to those skilled in the art, is only briefly described herein.

[0077] Further, if a linear battery model as shown in FIG. 2 is used, the battery parameter model equation is established according to the cell characteristics and the equivalent circuit as follows: Figure 2A

[0078]

[0079]

[0080] where k represents the next time, k-1 represents the previous time, represents the voltage of the internal resistance at the next time, represents the voltage of the internal resistance at the previous time, V k represents the terminal voltage of the linear battery model at the next time, represents a function value after the function of the measured discharge depth of the battery model at the next time is functionized (equal to the open circuit voltage value).

[0081] First, according to the calculation steps of the DEKF, the voltage value of the internal resistance and the discharge depth of the battery are calculated according to the existing formula at a certain time, the internal resistance voltage value at the previous time is regarded as the internal resistance voltage value at a certain time, and the equation is expressed as:

[0082]

[0083] The charge amount of the internal resistance changed from the previous time to a certain time is divided by the maximum charge amount of the linear battery model to obtain a charge amount ratio. Then, the charge amount ratio is added to the discharge depth of the linear battery model at the previous time to obtain the discharge depth of the linear battery model at a certain time, and the equation is expressed as:

[0084]

[0085] where represents the discharge depth at a certain time, DOD k-1 represents the discharge depth at the previous time, ΔQ represents the charge amount changed from the previous time to a certain time, Q max represents the maximum charge amount.

[0086] Then, the discharge depth of the linear battery model at a certain time is substituted into the open circuit voltage curve function model to obtain the corresponding open circuit voltage, and the equivalent voltage of the linear battery model at a certain time is calculated by subtracting the internal resistance voltage value at a certain time, and the equation is expressed as:​

[0087]

[0088] Where V k f(DOD) represents the equivalent voltage at a certain moment. k () represents the open-circuit voltage at a certain moment. The voltage representing the internal resistance at a certain moment.

[0089] In different cases, if such as Figure 2B The first-order RC battery model shown can then perform the following calculations. First, establish the battery parameter module:

[0090]

[0091] Where V in The voltage R represents the internal resistance. th C represents the equivalent resistance value. th V represents the equivalent capacitance value of a first-order RC battery model, k represents a certain moment, k-1 represents the previous moment, and V k f(DOD) represents the equivalent voltage at a certain moment. k () represents the open-circuit voltage at a certain moment. The voltage representing the internal resistance at a given moment. This represents the voltage of the RC circuit in the equivalent circuit at a certain moment.

[0092] According to DEKF's calculation steps, at a certain moment, the battery parameter values ​​(including the voltage of the internal resistance, the resistance and capacitance of the RC circuit), the battery discharge depth, and the voltage of the RC circuit are first calculated according to existing formulas. The battery parameters at the previous moment are regarded as the battery parameters at this moment, expressed by the following equation:

[0093]

[0094] Multiply the resistance and capacitance values ​​of the RC circuit in the battery's equivalent circuit to calculate the time constant; substitute the resistance value, the voltage of the RC circuit, and the time constant into the following equations to calculate the voltage of the RC circuit and the depth of discharge of the battery:

[0095]

[0096] Where V th The voltage of the RC circuit is represented by DOD, the depth of discharge is represented by k, the time of discharge is represented by t, the time constant of the resistor-capacitor circuit is represented by τ, and k-1 represents the previous time. th ΔQ represents the resistance value of the RC circuit in the battery's equivalent circuit, and ΔQ represents the change in charge from one moment to another. max I represents the maximum charge.V k represents the current value at a certain time.

[0097] Next, the discharge depth of the first-order RC battery model at a certain time is substituted into the open-circuit voltage curve function model to obtain the corresponding open-circuit voltage, and then the internal resistance voltage value and the RC circuit voltage value at the certain time are subtracted to calculate the equivalent voltage of the first-order RC battery model at the certain time, which is expressed by the following equation:

[0098]

[0099] where V k represents the equivalent voltage at a certain time, f(DOD k ) represents the open-circuit voltage at a certain time, represents the voltage of the internal resistance at a certain time, represents the voltage of the RC circuit at a certain time.

[0100] In step S109, if the linear battery model as shown in FIG. 4 is used, x of the following equation is substituted into the formula of the estimated equivalent voltage of the linear battery model Figure 2A The operating parameter values of the dual extended Kalman filter are set according to the battery parameter model equation:

[0101]

[0102] The actual voltage measurement value of the battery at a certain time and the equivalent voltage of the linear battery model at a certain time are substituted into the DEKF to calculate the adjusted internal resistance voltage value at a certain time, and the second equation is used to update the system noise Q k of the battery parameter model. In the Kalman filter, the coefficient P represents the estimation error, Q represents the system noise, and S represents the measurement error. The initial values of P, Q, and S and the iteration method are determined according to the characteristics of the battery and the application, for example, P0=0, P k The equation of the dual extended Kalman filter is iterated, Q0=MSE, Q k The weighted moving average method (WMA) is used for iteration, and S is set according to the measurement error of the machine, for example, S k = (V k × 2%) 2 .

[0103] The second equation for establishing the operating system noise of the battery model is as follows:

[0104]

[0105] where Q kZ represents the system noise of the battery model, K represents the Kalman coefficient, and when k is zero, Z k h(x) represents the measured voltage value. k ) represents substituting into DOD k With V in The voltage estimate is given, and the m in the second equation is the same as the m in the first equation.

[0106] In different cases, if adopted Figure 2B The first-order RC battery model shown below, by substituting x from the following equation into the formula for estimating the equivalent voltage of the first-order RC battery model. The operational parameters of the dual extended Kalman filter are set according to the battery parameter model equations:

[0107]

[0108] The actual voltage measurement of the battery at a certain moment is substituted into the equivalent voltage of the first-order RC battery model at that moment. The adjusted battery parameter value Y (including the voltage of the internal resistance, the resistance and capacitance of the RC circuit) is calculated by substituting it into DEKF. The system noise Q of the battery parameter model is then updated using the second equation. k The coefficients P, Q, and S in the Kalman filter are obtained and iterated in the same way as in the linear model.

[0109] In step S111, if the following is adopted Figure 2A The linear battery model shown uses the equivalent voltage formula. The depth of discharge at a given moment is substituted into the open-circuit voltage curve functional model to obtain the corresponding open-circuit voltage. This is then subtracted from the adjusted internal resistance voltage at that moment to calculate the equivalent voltage of the adjusted linear battery model. Next, using a dual extended Kalman filter, the depth of discharge at that moment is adjusted based on the actual measured voltage of the battery at that moment and the adjusted equivalent voltage of the linear battery model. The system noise Q of the battery model is then updated using the second equation. k For use in the next moment.

[0110] If adopted Figure 2B The first-order RC battery model shown uses the equivalent voltage formula. The discharge depth at a certain time is substituted into the open-circuit voltage function model to obtain the corresponding open-circuit voltage, and then the adjusted internal resistance voltage value at a certain time and the voltage value Vth of the RC circuit calculated according to the adjusted resistance and capacitance values of the RC circuit are subtracted to calculate the equivalent voltage of the adjusted first-order RC battery model at a certain time. Then, the dual extended Kalman filter is used to adjust the discharge depth and the voltage value of the RC circuit at a certain time according to the actual voltage measurement value of the battery at a certain time and the equivalent voltage of the adjusted first-order RC battery model at a certain time, and the second equation is used to update the system noise Q of the battery model k for use in the next time.

[0111] In step S113, the adjusted discharge depth (DOD k ) at the next time is converted into the percentage of the remaining battery capacity.

[0112] In step S115, it is determined whether the charging / discharging is stopped. If not, steps S105 to S115 are repeatedly executed. If yes, the operation is ended as in step S117.

[0113] In summary, the present application provides a method for detecting the state of battery capacity, which uses the dual extended Kalman filter (DEKF) in the calculation technology. During the charging and discharging of the battery, the actual voltage measurement value is used to optimize the calculation results of the coulomb counting method every second, thereby improving the calculation accuracy of the percentage of the remaining battery capacity.

[0114] The above disclosure is only the preferred and feasible embodiments of the present application, and does not limit the claims of the present application. Any equivalent technical changes made according to the content of the specification and drawings are included in the claims of the present application.

Claims

1. A method for detecting the state of charge of a battery, characterized in that, The method for detecting battery state includes the following steps: The battery is discharged using the open-circuit voltage method. The relationship between the battery's open-circuit voltage and the depth of discharge is measured during the discharge process. The relationship is then functionalized to establish an open-circuit voltage curve model. At the end of the previous charge and discharge cycle, calculate the final depth of discharge of the battery. The difference between the final discharge depth of the battery during the previous charge and discharge cycle and the actual discharge depth at the end of the previous charge and discharge cycle is calculated to generate an estimation error. At the initial moment, the open-circuit voltage of the battery is measured; Based on the open-circuit voltage curve model, the open-circuit voltage measured at the initial moment is converted into the discharge depth at the initial moment as the measured discharge depth. Calculate the difference between the last discharge depth of the battery during the previous charge and discharge cycle and the measured discharge depth. Based on the estimation error, the difference between the calculated final discharge depth of the battery's previous charge and discharge and the measured discharge depth is adjusted to obtain the discharge depth difference. The discharge depth difference is added to the last discharge depth of the battery during the previous charge and discharge cycle to obtain the initial discharge depth at the initial moment. Based on the open-circuit voltage curve model, the initial discharge depth is converted into the actual initial open-circuit voltage; Establishing a battery model includes connecting a DC voltage source and an internal resistor in series between the first and second terminals of the battery model, connecting the DC voltage source in series with the internal resistor, and using the actual initial open-circuit voltage as the initial voltage of the DC voltage source. Measure the equivalent voltage between the first and second terminals of the battery model; The voltage of the internal resistor is obtained by subtracting the equivalent voltage between the first and second terminals of the battery model from the actual initial open-circuit voltage. Using the battery model, simulate the parameters of the battery model at a certain moment, including measuring the open-circuit voltage and equivalent voltage of the DC voltage source; and The parameters are substituted into the open-circuit voltage curve model to calculate the remaining percentage of the battery capacity at a certain moment.

2. The method for detecting battery state of charge according to claim 1, characterized in that, The method for detecting battery state of charge also includes the following steps: The estimation error is divided by the sum of the estimation error and the measurement error to obtain the error coefficient, which is expressed by the following equation: Where P represents the estimation error, S represents the measurement error, and K represents the error coefficient; Substitute the last discharge depth from the previous charge-discharge cycle, the measured discharge depth, the estimation error, and the measurement error into the following equation to calculate the initial discharge depth: Where DOD0 represents the initial discharge depth, DOD A The depth of discharge (DOD) represents the last discharge point of the battery during its previous charge and discharge cycle. F P represents the estimated depth of discharge, and S represents the measurement error.

3. The method for detecting battery state of charge according to claim 2, characterized in that, The method for detecting battery state of charge also includes the following steps: The measurement error is calculated based on the idle time between the end of the previous charge / discharge cycle and the calculated time, and is expressed by the following equation: S=e -ΔT Where S represents the measurement error and ΔT represents the idle time.

4. The method for detecting battery state of charge according to claim 2, characterized in that, The method for detecting battery state of charge also includes the following steps: Measure the first open-circuit voltage of the battery at a certain moment; Measure the second open-circuit voltage of the battery at a certain moment and the next moment. Calculate the difference between the second open-circuit voltage and the first open-circuit voltage, and take the absolute value to obtain the voltage difference; and Substitute the pressure difference into the following equation to calculate the measurement error: Where S represents the measurement error, dv represents the pressure difference, and mdv represents the preset pressure difference. Ndv represents the preset stable pressure difference under ideal steady-state conditions, and C represents the scaling factor.

5. The method for detecting battery state of charge according to claim 2, characterized in that, The method for detecting battery state of charge also includes the following steps: The relationship between the open-circuit voltage and the depth of discharge is transformed into Voc = f(DOD) and DOD = f(Voc), where Voc represents the open-circuit voltage and DOD represents the depth of discharge. The least squares difference is used to fit the function, and the power of the function is determined, as shown in the following first equation: Voc i Represents the open-circuit voltage, DOD i The depth of discharge is represented by MSE, the minimum mean square error is represented by m, and the number of experimental data points referenced when fitting the first equation is represented by m.

6. The method for detecting battery state of charge according to claim 5, characterized in that, The method for detecting battery state of charge also includes the following steps: The establishment of a linear battery model is included in the battery model, which includes the DC voltage source and the internal resistance; The charge ratio is obtained by dividing the change in internal resistance from one moment to another by the maximum charge of the linear battery model. The charge ratio is added to the discharge depth of the linear battery model at the previous time step to obtain the discharge depth of the linear battery model at a certain time step, expressed by the equation: in The depth of discharge (DOD) represents the depth of discharge at a given moment. k-1 The discharge depth represents the value of Q at the previous moment, and ΔQ represents the change in charge from the previous moment to a certain moment. max This represents the maximum charge amount; The equivalent voltage of the linear battery model at a given moment is calculated by subtracting the voltage of its internal resistance from the open-circuit voltage of the DC voltage source at that moment. This equivalent voltage is expressed as an equation: Where V k The equivalent voltage f(DOD) of the linear battery model at a certain moment. k () represents the open-circuit voltage at a certain moment. The voltage representing the internal resistance at a given moment; The actual voltage measurement of the battery at a certain moment, and the equivalent voltage estimate of the linear battery model calculated based on the voltage of the internal resistance and the depth of discharge of the linear battery model, are substituted into a dual extended Kalman filter to calculate the actual voltage of the internal resistance, and the system noise of the linear battery model is updated with the second equation. The actual voltage measurement at a certain moment, the actual voltage of the internal resistance, and the estimated equivalent voltage calculated from the depth of discharge of the linear battery model are substituted into the dual extended Kalman filter to calculate the actual depth of discharge of the linear battery model, and the system noise of the linear battery model is updated with the second equation. The second equation is as follows: Q k The system noise at time k is represented by Q0 = MSE when k is zero. k h(x) represents the actual voltage measurement value. k ) represents the estimated equivalent voltage, and K represents the error coefficient.

7. The method for detecting battery state of charge according to claim 5, characterized in that, The method for detecting battery state of charge also includes the following steps: A first-order resistive-capacitive battery model is established within the battery model. The first-order resistive-capacitive battery model includes the DC voltage source, the internal resistor, and the resistive-capacitive circuit. The internal resistor is connected in series between the DC voltage source and the resistive-capacitive circuit. The resistive-capacitive circuit includes equivalent resistors and equivalent capacitors connected in parallel. Calculate the equivalent voltage of a first-order resistive-capacitive battery model; The time constant is calculated by multiplying the equivalent resistance value of the equivalent resistance of the resistor-capacitor circuit with the equivalent capacitance value of the equivalent capacitor. Substituting the equivalent resistance value, the equivalent voltage of the first-order resistive-capacitive battery model, and the time constant into the following equations, the voltage of the resistive-capacitive circuit and the depth of discharge of the battery can be calculated: Where V th The equivalent voltage of the resistor-capacitor circuit is represented by DOD, the depth of discharge is represented by k, the moment is represented by t, the discharge time is represented by τ, the time constant of the resistor-capacitor circuit is represented by k-1, and R represents the previous moment. th The value represents the equivalent resistance, ΔQ represents the change in charge from the previous moment to a certain moment, and Q represents the change in charge. max I represents the maximum charge. k The current value at a specific moment; as well as Based on the battery's depth of discharge, the voltage across the internal resistor, the equivalent resistance value, and the capacitance value of the resistor-capacitor circuit, the estimated equivalent voltage is calculated using the following equation: Where V k The estimated equivalent voltage value at a certain moment. This represents a function value derived from the functionalization of the depth of discharge of the battery model measured at the next time step. The voltage representing the internal resistance at a given moment. The voltage of the resistor-capacitor circuit at a certain moment is calculated from the equivalent resistance value and the capacitance value of the resistor-capacitor circuit at that moment. The actual voltage measurement of the battery at a certain moment, along with the equivalent voltage of the first-order resistive-capacitor battery model calculated based on the voltage of the internal resistance at a certain moment, the voltage of the resistive-capacitor circuit at a certain moment, and the depth of discharge at a certain moment, are substituted into a dual extended Kalman filter to calculate the adjusted voltage of the internal resistance and the adjusted capacitance and resistance values ​​of the first-order resistive-capacitor battery model. The system noise of the first-order resistive-capacitor battery model is then updated using the second equation. Using the adjusted capacitance and resistance values ​​of the resistor-capacitor circuit calculated by the previous dual extended Kalman filter, the voltage value of the resistor-capacitor circuit is calculated. Then, the equivalent voltage of the first-order resistor-capacitor battery model at a certain moment is calculated by combining the actual voltage measurement value at a certain moment, the voltage value of the resistor-capacitor circuit, and the discharge depth at a certain moment. The equivalent voltage of the first-order resistor-capacitor battery model at a certain moment is then substituted into the dual extended Kalman filter to calculate the adjusted discharge depth and the adjusted voltage value of the resistor-capacitor circuit of the first-order resistor-capacitor battery model. The system noise of the first-order resistor-capacitor battery model is then updated using the second equation. The second equation is as follows: Q k The system noise at time k is represented by Q0 = MSE when k is zero. k h(x) represents the actual voltage measurement value. k ) represents the estimated equivalent voltage, and K represents the error coefficient.

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