A method and system for estimating the effective capacity of a supercapacitor energy storage system

Abstract

This invention provides a method and system for estimating the effective capacity of a supercapacitor energy storage system. The method includes: establishing a nonlinear electrical model of a single supercapacitor cell and an equivalent electrical model of the supercapacitor system; conducting a charging test on the single supercapacitor cell to obtain first test data; setting initial values ​​for the parameters of the nonlinear electrical model of the single supercapacitor cell based on the first test data using a preset algorithm; identifying the parameters of the nonlinear electrical model of the supercapacitor using the least squares method; obtaining the electrical parameters of the equivalent electrical model of the supercapacitor system, excluding connection resistance parameters; conducting a charging test on the supercapacitor system to obtain connection resistance parameters; and estimating the effective capacity of the supercapacitor energy storage system based on the parameter-identified equivalent electrical model. By implementing this invention, the accuracy of estimating the effective capacity of a supercapacitor energy storage system is improved.

Description

Technical Field

[0001] This invention relates to the field of supercapacitor energy storage, and specifically to a method and system for estimating the effective capacity of a supercapacitor energy storage system. Background Technology

[0002] Supercapacitor energy storage systems have become a hot topic for solving the problem of brake energy recovery in urban rail trains. However, the available capacity of supercapacitor systems limits their energy savings. Currently, the available capacity of supercapacitors is estimated using an equivalent circuit with a resistor and capacitor in series, employing a capacity calculation formula that ignores the capacitance variation across the entire voltage range and the nonlinear characteristics of capacitance and voltage. This simplistic estimation of effective capacity significantly reduces the energy savings of supercapacitor energy storage systems, leading to increased equipment costs per unit of energy saved. Summary of the Invention

[0003] Therefore, the technical problem to be solved by the present invention is to overcome the defect that the effective capacity estimation in the prior art is too simple, which leads to an increase in the equipment cost per unit of electricity saved, thereby providing a method and system for estimating the effective capacity of a supercapacitor energy storage system.

[0004] In a first aspect, embodiments of the present invention provide a method for estimating the effective capacity of a supercapacitor energy storage system, comprising:

[0005] Establish nonlinear electrical models for individual supercapacitor cells and equivalent electrical models for the supercapacitor system;

[0006] A charging test was performed on a single supercapacitor cell to obtain the first test data.

[0007] Based on the first test data, the initial values ​​of the nonlinear electrical model parameters of the supercapacitor cell are set using a preset algorithm.

[0008] The parameters of the nonlinear electrical model of a single supercapacitor cell are identified using the least squares method, resulting in a nonlinear electrical model with accurate parameters.

[0009] Obtain the electrical parameters of the supercapacitor system's equivalent electrical model, excluding the connection resistance parameters. Perform a charging test on the supercapacitor system to obtain the connection resistance parameters. Based on the parameter-identified equivalent electrical model of the supercapacitor system, estimate the effective capacity of the supercapacitor energy storage system.

[0010] Optionally, the nonlinear electrical model of the supercapacitor cell is a two-branch electrical model, which includes: a connecting resistor, a first branch, and a second branch, wherein...

[0011] The first branch and the second branch are connected in parallel and then connected in series with the connecting resistor;

[0012] The first branch includes a first resistor, a first capacitor, and a voltage-controlled capacitor. The first capacitor and the voltage-controlled capacitor are connected in parallel and then connected in series with the first resistor.

[0013] The second branch includes a second resistor and a second capacitor, with the second resistor and the second capacitor connected in series.

[0014] Optionally, the step of setting initial values ​​for the nonlinear electrical model parameters of a single supercapacitor cell based on the first test data using a preset algorithm includes:

[0015] Constant current charging is applied to individual supercapacitor cells;

[0016] When the charging time reaches the first preset time, the voltage across the supercapacitor cell is measured as the first voltage.

[0017] Calculate the initial values ​​of the parameters of the first resistor based on the first voltage and the constant current charging current;

[0018] When the supercapacitor cell is detected to be charged to the second voltage, the constant current charging time of the supercapacitor cell is recorded as the second preset time.

[0019] The initial parameter values ​​of the first capacitor are calculated based on the first preset time, the second preset time, the first voltage, the second voltage, and the constant current charging current.

[0020] Optionally, the step of setting initial values ​​for the nonlinear electrical model parameters of a single supercapacitor cell based on the first test data using a preset algorithm further includes:

[0021] When the supercapacitor cell is detected to be charged to the rated voltage, the charging ends and the constant current charging time of the supercapacitor cell is recorded as the third preset time.

[0022] After charging is completed, the charge redistribution stage of the two branches begins. When the supercapacitor cell is detected to discharge to the fourth voltage, the discharge time is recorded as the fourth preset time.

[0023] Record the actual constant current charging time of a single supercapacitor cell based on the fourth preset time and the first preset time.

[0024] The actual amount of the first charge stored in a supercapacitor cell is calculated based on the actual constant current charging time and constant current charging current of the supercapacitor cell.

[0025] Based on the integral formula of the transient capacitance of the first branch, calculate the second charge when the two ends of the supercapacitor cell are charged to the fourth voltage;

[0026] The coefficient of the voltage-controlled capacitor is calculated based on the first charge calculation formula and the second charge calculation formula.

[0027] Optionally, the step of setting initial values ​​for the nonlinear electrical model parameters of a single supercapacitor cell based on the first test data using a preset algorithm further includes:

[0028] When the supercapacitor cell is detected to discharge to the fifth voltage, the discharge time is recorded as the fifth preset time.

[0029] Based on the fourth preset time, the fifth preset time, the coefficient of the first capacitor and the voltage-controlled capacitor, and the preset voltage value of the voltage-controlled capacitor, the equations for the charging current of the first branch to the second branch are established from the perspectives of resistor voltage drop and charge redistribution, respectively, and the initial values ​​of the parameters of the second resistor are calculated.

[0030] When the monitoring discharge time reaches the sixth preset time, the voltage across the supercapacitor cell is measured to be the sixth voltage, and the charge at the sixth preset time and the initial parameter values ​​of the second capacitor are calculated. The time interval between the sixth preset time and the fifth preset time is the time interval between the completion of the traction work and the start of the braking work of the urban rail transit vehicle.

[0031] Optionally, the step of obtaining electrical parameters other than connection resistance parameters from the equivalent electrical model of the supercapacitor system, performing a charging test on the supercapacitor system to obtain connection resistance parameters, and estimating the effective capacity of the supercapacitor energy storage system based on the parameter-identified equivalent electrical model of the supercapacitor system includes:

[0032] Establish the correspondence between the nonlinear electrical model of a single supercapacitor and the equivalent electrical model of the supercapacitor system. Based on the parameter identification results of the nonlinear electrical model of the single supercapacitor, obtain the electrical parameters of the equivalent electrical model of the supercapacitor system other than the connection resistance parameters.

[0033] A charging test was conducted on the supercapacitor system to obtain the second test data;

[0034] Calculate the parameter identification value of the connection resistance based on the second test data;

[0035] The identification parameters of the equivalent electrical model of the supercapacitor system are obtained based on the other electrical parameters except for the connection resistance parameter and the identification parameter value of the connection resistance.

[0036] Obtain the operating voltage range of the supercapacitor system and estimate the effective capacity of the supercapacitor energy storage system based on the available power estimation formula.

[0037] Optionally, an equivalent electrical model for an n-series m-parallel supercapacitor system is derived from the nonlinear electrical model of a single supercapacitor cell.

[0038] Secondly, embodiments of the present invention provide an effective capacity estimation system for a supercapacitor energy storage system, comprising:

[0039] The module is used to build nonlinear electrical models of individual supercapacitors and equivalent electrical models of supercapacitor systems.

[0040] The acquisition module is used to perform charging tests on individual supercapacitor cells and acquire the first test data.

[0041] The setting module is used to set initial values ​​for the nonlinear electrical model parameters of a single supercapacitor cell based on the first test data and using a preset algorithm.

[0042] The identification module is used to identify the parameters of the nonlinear electrical model of a single supercapacitor cell using the least squares method, thereby obtaining a nonlinear electrical model with accurate parameters.

[0043] The estimation module obtains the electrical parameters of the equivalent electrical model of the supercapacitor system, excluding the connection resistance parameters. It performs a charging test on the supercapacitor system to obtain the connection resistance parameters and estimates the effective capacity of the supercapacitor energy storage system based on the equivalent electrical model of the supercapacitor system after parameter identification.

[0044] Thirdly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions for causing the computer to execute the effective capacity estimation method for a supercapacitor energy storage system described in the first aspect of the present invention.

[0045] Fourthly, embodiments of the present invention provide a computer device, including: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the effective capacity estimation method for a supercapacitor energy storage system described in the first aspect of the present invention.

[0046] The technical solution of this invention has the following advantages:

[0047] This invention provides a method for estimating the effective capacity of a supercapacitor energy storage system, comprising: establishing a nonlinear electrical model of a single supercapacitor cell and an equivalent electrical model of the supercapacitor system; conducting charging tests on the single supercapacitor cell to obtain first test data; based on the first test data, setting initial values ​​for the parameters of the nonlinear electrical model of the single supercapacitor cell using a preset algorithm; identifying the parameters of the nonlinear electrical model of the single supercapacitor cell using the least squares method to obtain a nonlinear electrical model with accurate parameters; obtaining the electrical parameters of the equivalent electrical model of the supercapacitor system, excluding connection resistance parameters; conducting charging tests on the supercapacitor system to obtain connection resistance parameters; and estimating the effective capacity of the supercapacitor energy storage system based on the parameter-identified equivalent electrical model of the supercapacitor system. The initial value setting and parameter identification for the nonlinear electrical model of the single supercapacitor cell better reflect the electrical characteristics under operating conditions of supercapacitors. The charging tests on the supercapacitor system adjust the available power of the supercapacitor system, further aligning with the electrical characteristics under system-level operating conditions. By setting the electrical external characteristics that conform to the operating conditions of individual supercapacitors and the supercapacitor system, the accuracy of the effective capacity estimation of the supercapacitor energy storage system is improved, thereby increasing the power saving of the supercapacitor energy storage system and reducing the equipment cost per unit of power saving. Attached Figure Description

[0048] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0049] Figure 1 This is the electrical model of the single-cell RC series equivalent circuit in the embodiments of the present invention;

[0050] Figure 2 This is the electrical model of the RC series equivalent circuit of the system in the embodiment of the present invention;

[0051] Figure 3 This is a capacitor voltage curve of the RC series equivalent model under constant current charging conditions in an embodiment of the present invention.

[0052] Figure 4 This is a graph showing the actual capacitor voltage curve under constant current charging conditions in an embodiment of the present invention.

[0053] Figure 5 A flowchart illustrating a specific example of the effective capacity estimation method for a supercapacitor energy storage system in an embodiment of the present invention;

[0054] Figure 6This is a nonlinear electrical model of a single supercapacitor cell in an embodiment of the present invention;

[0055] Figure 7 This is the equivalent electrical model of the supercapacitor system in the embodiments of the present invention;

[0056] Figure 8 This is a graph showing the recording of the first test data in an embodiment of the present invention.

[0057] Figure 9 A schematic diagram of the nonlinear electrical model charging of a single supercapacitor cell, as shown in a specific example of an embodiment of the present invention;

[0058] Figure 10 A schematic diagram of the nonlinear electrical model charging of a single supercapacitor cell, which is another specific example in an embodiment of the present invention;

[0059] Figure 11 This is a schematic diagram of the data recording curve of the supercapacitor system in an embodiment of the present invention;

[0060] Figure 12 This is a schematic diagram illustrating a specific example of the effective capacity estimation system for a supercapacitor energy storage system in an embodiment of the present invention.

[0061] Figure 13 This is a composition diagram of a specific example of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0062] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0064] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can also refer to the internal connection of two components; and they can refer to a wireless connection or a wired connection. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0065] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0066] Existing typical supercapacitor energy storage systems measure the internal resistance and capacitance of individual cells according to the Maxwell six-step method or the cell measurement method in the IEC 62391 standard to obtain the electrical parameters of the RC series equivalent circuit. The equivalent circuit electrical model is as follows: Figure 1 As shown, where V c This is the open-circuit voltage of a single unit.

[0067] Based on the parameters of each supercapacitor cell and the series and parallel connections of the cells in the energy storage system, the RC series equivalent circuit of the supercapacitor system is obtained. Let the supercapacitor system consist of n series and m parallel cells. Then the RC series equivalent circuit of a traditional supercapacitor energy storage system is as follows: Figure 2 As shown, where V s This is the open-circuit voltage of the supercapacitor system.

[0068] This equivalent method primarily considers the linear characteristics of supercapacitors, assuming that the capacitance value of the supercapacitor remains constant. Under constant current charging conditions, the supercapacitor voltage and charging time exhibit a linear relationship, such as... Figure 3 As shown.

[0069] Formula (1) is often used when calculating effective charge.

[0070] I*t=C*V (1)

[0071] In the formula, I is the constant charging current, t is the constant current charging time, V is the terminal voltage of the supercapacitor system, and C is the capacitance of the supercapacitor system.

[0072] Available power is estimated to be

[0073]

[0074] In equation (2), U h and U l These are the upper and lower limits of the supercapacitor's operating voltage, respectively.

[0075] In reality, supercapacitors exhibit certain nonlinear characteristics, and the connection resistance during series-parallel connection of supercapacitors also needs to be taken into account. The constant current charging curve of a supercapacitor is shown below. Figure 4 As shown, the capacitance C varies over a wide range as the charging voltage increases or decreases.

[0076] Considering the actual variations in capacitor voltage, equation (2) will no longer be applicable, necessitating a new method for calculating effective capacity to replace the old one. Therefore, this invention provides a method for estimating the effective capacity of a supercapacitor energy storage system, such as... Figure 5 As shown, it includes the following steps:

[0077] Step S1: Establish the nonlinear electrical model of a single supercapacitor cell and the equivalent electrical model of the supercapacitor system.

[0078] In one specific embodiment, with Figure 6 Based on the nonlinear electrical model of the supercapacitor cell shown, the effective capacity of the supercapacitor energy storage system is estimated.

[0079] In embodiments of the present invention, such as Figure 6 As shown, the nonlinear electrical model of a single supercapacitor cell is a two-branch electrical model. The nonlinear electrical model of a single supercapacitor cell includes: connection resistance R... conn The system comprises a first branch and a second branch, wherein the first branch and the second branch are connected in parallel and then in series with a connecting resistor; the first branch includes a first resistor R1, a first capacitor C1, and a voltage-controlled capacitor C0, wherein the first capacitor C1 and the voltage-controlled capacitor C0 are connected in parallel and then in series with the first resistor R1; the second branch includes a second resistor R2 and a second capacitor C2, wherein the second resistor R2 and the second capacitor C2 are connected in series. In this embodiment of the invention, the complex circuit of the supercapacitor system is equivalent to a two-branch electrical model based on the single-unit electrical model, thereby reducing the complexity of the system electrical model.

[0080] Specifically, Figure 6 In the middle, V c R represents the voltage at the terminal of a single supercapacitor cell, while R represents the voltage measured by the supercapacitor management unit. conn This represents the equivalent connection resistance caused by the series and parallel connection of the supercapacitors. R1 and C1 are the resistance and capacitance of the first branch, and R2 and C2 are the resistance and capacitance of the second branch. K v The coefficient of the voltage-controlled capacitor is C0, which is calculated according to formula (3).

[0081] C0 = K v *V c (3)

[0082] According to such Figure 6 The nonlinear electrical model of the supercapacitor cell shown is used to derive the following: Figure 7 The diagram shows the equivalent electrical model of an n-series, m-parallel supercapacitor system. Where V... s This is the system open-circuit voltage.

[0083] Step S2: Perform a charging test on a single supercapacitor cell to obtain the first test data.

[0084] In one specific embodiment, the time interval between the completion of traction and the start of braking of the urban rail transit vehicle is taken as τ. A constant current I charging test is performed on each supercapacitor cell, with the cell voltage varying from 0 to the rated voltage V3. When the cell voltage reaches V3, charging is stopped, and then the charge redistribution phase of the two branches begins. During this process, the first test data of the constant current I charging test is recorded. Figure 8 In the given information, t6-t5 = τ.

[0085] Step S3: Based on the first test data, the initial values ​​of the nonlinear electrical model parameters of the supercapacitor cell are set using a preset algorithm.

[0086] In one specific embodiment, the initial values ​​of the nonlinear electrical model of a single supercapacitor cell are set through the following steps:

[0087] Step S301: Perform constant current charging on the supercapacitor cells.

[0088] Step S302: When the charging time reaches the first preset time, measure the voltage across the supercapacitor cell to get the first voltage.

[0089] Step S303: Calculate the initial values ​​of the parameters of the first resistor based on the first voltage and the constant current charging current.

[0090] Step S304: When the supercapacitor cell is detected to be charged to the second voltage, the constant current charging time of the supercapacitor cell is recorded as the second preset time.

[0091] Step S305: Calculate the initial parameter values ​​of the first capacitor based on the first preset time, the second preset time, the first voltage, the second voltage, and the constant current charging current.

[0092] Step S306: When the supercapacitor cell is detected to be charged to the rated voltage, the charging is stopped, and the constant current charging time of the supercapacitor cell is recorded as the third preset time.

[0093] Step S307: After charging ends, the charge redistribution stage of the two branches begins. When the supercapacitor cell is detected to discharge to the fourth voltage, the discharge time is recorded as the fourth preset time.

[0094] Step S308: Record the actual constant current charging time of the supercapacitor cell according to the fourth preset time and the first preset time.

[0095] Step S309: Calculate the actual amount of the first charge stored in the supercapacitor cell based on the actual constant current charging time and constant current charging current of the supercapacitor cell.

[0096] Step S310: Calculate the second charge amount when the two ends of the supercapacitor cell are charged to the fourth voltage according to the integral formula of the transient capacitance of the first branch.

[0097] Step S311: Calculate the coefficient of the voltage-controlled capacitor according to the first charge calculation formula and the second charge calculation formula.

[0098] Step S312: When the discharge of a single supercapacitor cell to the fifth voltage is detected, the discharge time is recorded as the fifth preset time.

[0099] Step S313: Based on the fourth preset time, the fifth preset time, the coefficients of the first capacitor and the voltage-controlled capacitor, and the preset voltage value of the voltage-controlled capacitor, establish the equation for the charging current of the first branch to the second branch from the perspectives of resistor voltage drop and charge redistribution, and calculate the initial value of the parameters of the second resistor.

[0100] Step S314: When the monitoring discharge time reaches the sixth preset time, measure the voltage across the supercapacitor cell to be the sixth voltage, and calculate the charge amount at the sixth preset time and the initial parameter value of the second capacitor. The time interval between the sixth preset time and the fifth preset time is the time interval between the completion of the traction work and the start of the braking work of the urban rail transit vehicle.

[0101] In this embodiment of the invention, a first preset time, such as 20ms, can be selected based on error assessment, corresponding to a first voltage of V1. When the supercapacitor voltage starts constant current charging from 0V, the voltage will undergo a short-term sudden change due to the influence of the resistance of each branch of the supercapacitor. Figure 6 In the diagram, the first branch is a short-time constant branch, and the second branch is a long-time constant branch. In the short-time characteristics, the second branch can be considered not to participate in the charging process. Figure 8 The schematic diagram of the charging electrical equivalent model for the 0-t4 time period is shown below. Figure 9 As shown. During the time interval t1, the voltage across capacitor C1 is assumed to be 0V. Then... Figure 6 The initial values ​​of the parameters of R1 in the model are:

[0102]

[0103] Furthermore, the second voltage V2 = V1 + i is taken, corresponding to the second preset time t2. The value of i can be set according to the minimum resolution of the test equipment. The smaller i is, the closer the calculated value is to the true value. Based on error assessment, i can be selected in the voltage range of 100mV. During the time period t1-t2, since the supercapacitor voltage Vc is approximately 0V, the voltage-controlled capacitor is negligible. The increase in voltage is mainly due to current injection into C1. Figure 6 The initial values ​​of the parameters of the first capacitor C1 in the model are:

[0104]

[0105] Further, V3 is the rated voltage, and the constant current charging time of the supercapacitor cell is recorded as the third preset time t3. Charging ends at time t3, entering the charge redistribution stage of the two branches. When the supercapacitor cell is detected discharging to the fourth voltage V4, the fourth preset time t4 is recorded. t4 is taken as t3 + 20ms. In this embodiment of the invention, the time difference between the fourth preset time t4 and the third preset time t3 is 20ms, based on the error assessment of the test data. Due to the influence of internal resistance, t1-t4 can be equivalently considered as the actual constant current charging time of the supercapacitor.

[0106] Therefore, the actual amount of charge stored in a supercapacitor is:

[0107] Q4=I*(t4-t1) (6)

[0108] The transient capacitance of the first branch of the supercapacitor is:

[0109]

[0110] The points are calculated as follows:

[0111]

[0112] When the supercapacitor voltage is V4

[0113]

[0114] According to equations (6) and (9), Figure 6 K in the model v The initial value of the parameter is

[0115]

[0116] Furthermore, during the t4-t6 stage, the supercapacitor charging process is complete, and the process enters the charge redistribution stage between the two branches. During this stage, some charge from the first branch will gradually transfer to the second branch. The resistance R1 of the first branch is negligible because it is much smaller than R2. The equivalent electrical model is illustrated below. Figure 10 As shown.

[0117] The fifth voltage V5 is set to V4 - 100mV, corresponding to a fifth preset time t5. In this embodiment of the invention, the difference between the fifth voltage V5 and the fourth voltage V4 can be selected as 100mV based on the error assessment of the test data. Since the time is very short, it is assumed that the charging current I from the first branch to the second branch is... c Unchanged. The charging current, from the perspective of resistor voltage drop, is:

[0118]

[0119] Short-time voltage changes can be considered linear, and the voltage of the voltage-controlled capacitor can be selected. Considering the charging current from the perspective of charge redistribution:

[0120]

[0121] According to equations (11) and (12), Figure 6 The initial values ​​of the parameters of R2 in the model are

[0122]

[0123] Taking the sixth preset time t6 = t5 + τ, corresponding to the sixth voltage of a single unit being V6, under this operating condition, it is assumed that charge redistribution occurred during this time period. The total charge during this stage is:

[0124]

[0125] Among them, Q tot The amount of charge at the sixth preset time.

[0126] The total charge includes the charge stored in the first branch capacitor and the charge stored in the second branch capacitor. Figure 6 The initial values ​​of the parameters of C2 in the model are:

[0127]

[0128] Step S4: Use the least squares method to identify the parameters of the nonlinear electrical model of a single supercapacitor cell and obtain a nonlinear electrical model with accurate parameters.

[0129] In one specific embodiment, after initializing the nonlinear electrical model parameters of a single supercapacitor cell, the least squares method is used to identify the parameters and obtain an accurate nonlinear electrical model.

[0130] Step S5: Obtain the electrical parameters of the equivalent electrical model of the supercapacitor system, excluding the connection resistance parameters. Perform a charging test on the supercapacitor system to obtain the connection resistance parameters. Based on the equivalent electrical model of the supercapacitor system after parameter identification, estimate the effective capacity of the supercapacitor energy storage system.

[0131] In one specific embodiment, the effective capacity of the supercapacitor energy storage system is estimated through the following steps:

[0132] Step S501: Establish the correspondence between the nonlinear electrical model of a single supercapacitor cell and the equivalent electrical model of the supercapacitor system. Based on the parameter identification results of the nonlinear electrical model of the single supercapacitor cell, obtain the electrical parameters of the equivalent electrical model of the supercapacitor system, excluding the connection resistance parameters.

[0133] Step S502: Perform a charging test on the equivalent electrical model of the supercapacitor system to obtain the second test data.

[0134] Step S503: Calculate the parameter identification value of the connection resistor based on the second test data.

[0135] Step S504: Obtain the identification parameters of the equivalent electrical model of the supercapacitor system based on the other electrical parameters except for the connection resistance parameters and the identification parameter values ​​of the connection resistance.

[0136] Step S505: Obtain the operating voltage range of the supercapacitor system and estimate the effective capacity of the supercapacitor energy storage system according to the available power estimation formula.

[0137] In this embodiment of the invention, based on the parameter identification results, the following can be obtained: Figure 7 The system model shown includes electrical parameters other than the connection resistance parameters. The supercapacitor system is charged with a charging current of I. s When the charging voltage reaches the rated voltage V from 0V. s When charging stops, the voltage will drop to V. e .but Figure 5 R in the model conn The parameter identification value is:

[0138]

[0139] Figure 11 This is a schematic diagram of the data recording curve of the supercapacitor system, taking V as the value. h and V l Given the operating voltage range of the supercapacitor system, the available charge E1 is:

[0140]

[0141] Equation (17) replaces Equation (2) as a new expression for estimating the available charge of a supercapacitor system.

[0142] In this embodiment, by adjusting the available power of the supercapacitor system, it is better suited to the operating conditions of the supercapacitor system, thereby improving the regenerative energy recovery effect.

[0143] This invention provides a method for estimating the effective capacity of a supercapacitor energy storage system, comprising: establishing a nonlinear electrical model of a single supercapacitor cell and an equivalent electrical model of the supercapacitor system; conducting charging tests on the single supercapacitor cell to obtain first test data; based on the first test data, setting initial values ​​for the parameters of the nonlinear electrical model of the single supercapacitor cell using a preset algorithm; identifying the parameters of the nonlinear electrical model of the single supercapacitor cell using the least squares method; obtaining the equivalent electrical model of the supercapacitor system after parameter identification; conducting charging tests on the supercapacitor system; and estimating the effective capacity of the supercapacitor energy storage system. The initial value setting and parameter identification for the nonlinear electrical model of the single supercapacitor cell better match the electrical external characteristics of supercapacitors under operating conditions. The charging tests on the supercapacitor system adjust the available power of the supercapacitor system to better match the electrical external characteristics of the system-level operating conditions. By setting electrical external characteristics that conform to the operating conditions of both single supercapacitor cells and the supercapacitor system, the accuracy of the effective capacity estimation of the supercapacitor energy storage system is improved, thereby increasing the power saving of the supercapacitor energy storage system and reducing the equipment cost per unit of power saving.

[0144] This invention also provides an effective capacity estimation system for supercapacitor energy storage systems, such as... Figure 12 As shown, it includes:

[0145] Module 1 is used to establish the nonlinear electrical model of a single supercapacitor cell and the equivalent electrical model of the supercapacitor system. For details, please refer to the relevant description of step S1 in the above method embodiments, which will not be repeated here.

[0146] Module 2 is used to perform charging tests on individual supercapacitor cells and acquire first test data. For details, please refer to the relevant description of step S2 in the above method embodiments, which will not be repeated here.

[0147] The setting module 3 is used to set initial values ​​for the nonlinear electrical model parameters of a single supercapacitor cell based on the first test data using a preset algorithm. For details, please refer to the relevant description of step S3 in the above method embodiments, which will not be repeated here.

[0148] The identification module 4 is used to identify the parameters of the nonlinear electrical model of a single supercapacitor cell using the least squares method, thereby obtaining a nonlinear electrical model with accurate parameters. For details, please refer to the relevant description of step S4 in the above method embodiment, which will not be repeated here.

[0149] The estimation module 5 is used to obtain the electrical parameters of the equivalent electrical model of the supercapacitor system, excluding the connection resistance parameters. It performs a charging test on the supercapacitor system to obtain the connection resistance parameters and estimates the effective capacity of the supercapacitor energy storage system based on the parameter-identified equivalent electrical model. For details, please refer to the relevant description of step S5 in the above method embodiments, which will not be repeated here.

[0150] This invention provides a computer device, such as... Figure 13 As shown, the device may include a processor 81 and a memory 82, wherein the processor 81 and the memory 82 may be connected via a bus or other means. Figure 13 Take a bus connection as an example.

[0151] Processor 81 can be a central processing unit (CPU). Processor 81 can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips.

[0152] The memory 82, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the corresponding program instructions / modules in the embodiments of the present invention. The processor 81 executes various functional applications and data processing by running the non-transitory software programs, instructions, and modules stored in the memory 82, thereby implementing the effective capacity estimation method for the supercapacitor energy storage system in the above method embodiments.

[0153] The memory 82 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor 81, etc. Furthermore, the memory 82 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 82 may optionally include memory remotely located relative to the processor 81, and these remote memories may be connected to the processor 81 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, mobile communication networks, and combinations thereof.

[0154] One or more modules are stored in memory 82, and when executed by processor 81, they perform actions such as... Figures 5-11 The method for estimating the effective capacity of a supercapacitor energy storage system is shown.

[0155] For specific details regarding the aforementioned computer equipment, please refer to the relevant documentation. Figures 5-11 The relevant descriptions and effects in the illustrated embodiments are for understanding purposes only and will not be repeated here.

[0156] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0157] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for estimating the effective capacity of a supercapacitor energy storage system, characterized in that, include: A nonlinear electrical model of a single supercapacitor cell is established, and an equivalent electrical model of an n-series m-parallel supercapacitor energy storage system is derived based on the nonlinear electrical model of the single supercapacitor cell; charging tests are performed on the single supercapacitor cell to obtain the first test data; Based on the first test data, the initial values ​​of the nonlinear electrical model parameters of the supercapacitor cell are set using a preset algorithm. The parameters of the nonlinear electrical model of a single supercapacitor cell are identified using the least squares method, resulting in a nonlinear electrical model with accurate parameters. Establish the correspondence between the nonlinear electrical model of a single supercapacitor and the equivalent electrical model of the supercapacitor energy storage system. Based on the parameter identification results of the nonlinear electrical model of the single supercapacitor, obtain the electrical parameters of the equivalent electrical model of the supercapacitor energy storage system, excluding the connection resistance parameters. A charging test was conducted on the supercapacitor energy storage system to obtain the second test data; Calculate the parameter identification value of the connection resistance based on the second test data; The identification parameters of the equivalent electrical model of the supercapacitor energy storage system are obtained based on the electrical parameters other than the connection resistance parameters and the identification parameter values ​​of the connection resistance. Obtain the operating voltage range of the supercapacitor energy storage system, and estimate the effective capacity of the supercapacitor energy storage system based on the available power estimation formula.

2. The method for estimating the effective capacity of a supercapacitor energy storage system according to claim 1, characterized in that, The nonlinear electrical model of the supercapacitor cell is a two-branch electrical model, which includes: a connecting resistor, a first branch, and a second branch, wherein... The first branch and the second branch are connected in parallel and then connected in series with the connecting resistor; The first branch includes a first resistor, a first capacitor, and a voltage-controlled capacitor. The first capacitor and the voltage-controlled capacitor are connected in parallel and then connected in series with the first resistor. The second branch includes a second resistor and a second capacitor, with the second resistor and the second capacitor connected in series.

3. The method for estimating the effective capacity of a supercapacitor energy storage system according to claim 2, characterized in that, The initial setting of nonlinear electrical model parameters for a single supercapacitor cell based on the first test data using a preset algorithm includes: Constant current charging is applied to individual supercapacitor cells; When the charging time reaches the first preset time, the voltage across the supercapacitor cell is measured as the first voltage. Calculate the initial values ​​of the parameters of the first resistor based on the first voltage and the constant current charging current; When the supercapacitor cell is detected to be charged to the second voltage, the constant current charging time of the supercapacitor cell is recorded as the second preset time. The initial parameter values ​​of the first capacitor are calculated based on the first preset time, the second preset time, the first voltage, the second voltage, and the constant current charging current.

4. The method for estimating the effective capacity of a supercapacitor energy storage system according to claim 3, characterized in that, The step of setting initial values ​​for the nonlinear electrical model parameters of a single supercapacitor cell based on the first test data using a preset algorithm also includes: When the supercapacitor cell is detected to be charged to the rated voltage, the charging ends and the constant current charging time of the supercapacitor cell is recorded as the third preset time. After charging is completed, the charge redistribution stage of the two branches begins. When the supercapacitor cell is detected to discharge to the fourth voltage, the discharge time is recorded as the fourth preset time. Record the actual constant current charging time of a single supercapacitor cell based on the fourth preset time and the first preset time. The actual amount of the first charge stored in a supercapacitor cell is calculated based on the actual constant current charging time and constant current charging current of the supercapacitor cell. Based on the integral formula of the transient capacitance of the first branch, calculate the second charge when the two ends of the supercapacitor cell are charged to the fourth voltage; The coefficient of the voltage-controlled capacitor is calculated according to the first charge calculation formula and the second charge calculation formula.

5. The method for estimating the effective capacity of a supercapacitor energy storage system according to claim 4, characterized in that, The step of setting initial values ​​for the nonlinear electrical model parameters of a single supercapacitor cell based on the first test data using a preset algorithm also includes: When the supercapacitor cell is detected to discharge to the fifth voltage, the discharge time is recorded as the fifth preset time. Based on the fourth preset time, the fifth preset time, the coefficient of the first capacitor and the voltage-controlled capacitor, and the preset voltage value of the voltage-controlled capacitor, the equations for the charging current of the first branch to the second branch are established from the perspectives of resistor voltage drop and charge redistribution, respectively, and the initial values ​​of the parameters of the second resistor are calculated. When the monitoring discharge time reaches the sixth preset time, the voltage across the supercapacitor cell is measured to be the sixth voltage, and the charge at the sixth preset time and the initial parameter values ​​of the second capacitor are calculated. The time interval between the sixth preset time and the fifth preset time is the time interval between the completion of the traction work and the start of the braking work of the urban rail transit vehicle.

6. A supercapacitor energy storage system effective capacity estimation system, characterized in that, include: The module is used to build a nonlinear electrical model of a single supercapacitor cell, and to derive an equivalent electrical model of an n-series m-parallel supercapacitor energy storage system based on the nonlinear electrical model of the single supercapacitor cell. The acquisition module is used to perform charging tests on individual supercapacitor cells and acquire the first test data. The setting module is used to set initial values ​​for the nonlinear electrical model parameters of a single supercapacitor cell based on the first test data and using a preset algorithm. The identification module is used to identify the parameters of the nonlinear electrical model of a single supercapacitor cell using the least squares method, thereby obtaining a nonlinear electrical model with accurate parameters. The estimation module includes: Establish the correspondence between the nonlinear electrical model of a single supercapacitor and the equivalent electrical model of the supercapacitor energy storage system. Based on the parameter identification results of the nonlinear electrical model of the single supercapacitor, obtain the electrical parameters of the equivalent electrical model of the supercapacitor energy storage system, excluding the connection resistance parameters. A charging test was conducted on the supercapacitor energy storage system to obtain the second test data; Calculate the parameter identification value of the connection resistance based on the second test data; The identification parameters of the equivalent electrical model of the supercapacitor energy storage system are obtained based on the electrical parameters other than the connection resistance parameters and the identification parameter values ​​of the connection resistance. Obtain the operating voltage range of the supercapacitor energy storage system, and estimate the effective capacity of the supercapacitor energy storage system based on the available power estimation formula.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the effective capacity estimation method for a supercapacitor energy storage system as described in any one of claims 1-5.

8. A computer device, characterized in that, include: The system includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the effective capacity estimation method for a supercapacitor energy storage system as described in any one of claims 1-5.

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