Electrical signal control method and apparatus for energy storage system, and device, medium and product

Abstract

Disclosed in the present disclosure are an electrical signal control method and apparatus for an energy storage system, and a device, a medium and a product. The method comprises: on the basis of an expected value and actual value of a direct-current electrical signal output by an energy storage system, determining the error of the direct-current electrical signal and a sliding surface; performing proportional-integral regulation on the error by means of a target controller, performing sliding-mode regulation on the sliding surface, and determining an adjusted value of the direct-current electrical signal; at least on the basis of a reference direct-current electrical signal and the average electrical signal of one sub-module in the energy storage system, determining the number N of input modules, wherein the reference direct-current electrical signal is the sum of the adjusted value of the direct-current electrical signal and the expected value of the direct-current electrical signal, N being an integer greater than zero; and by means of an energy storage valve control module of the energy storage system, controlling N sub-modules in the energy storage system to be turned on, such that the energy storage system outputs the direct-current electrical signal on the basis of output capabilities of the N sub-modules.

Description

An electric signal control method, device, equipment, medium and product of an energy storage system

[0001] Cross-reference to related applications

[0002] The present disclosure is based on and claims priority to Chinese Patent Application No. 202411362725.5, filed on September 26, 2024, entitled "An electric signal control method, device, equipment, medium and product of an energy storage system", the contents of which are hereby incorporated by reference in its entirety into the present disclosure. TECHNICAL FIELD

[0003] The present disclosure relates to the field of electric power, and relates to but is not limited to an electric signal control method, device, equipment, medium and product of an energy storage system. BACKGROUND

[0004] Energy storage systems play an increasingly important role in renewable energy power generation, grid peak shaving, electric vehicle charging, and other fields. Through energy storage technology, smooth operation of the power system can be achieved, energy utilization efficiency can be improved, and grid flexibility can be enhanced. Among them, direct current voltage control is a crucial link in the energy storage system, and is directly related to the safety, reliability and service life of the energy storage unit.

[0005] For direct current voltage control, the related technology usually adopts proportional integral derivative (PID) feedback control. However, due to the characteristics of nonlinearity, time-varying, uncertainty, etc. in the process of direct current voltage control, the PID controller is difficult to meet the requirements of control accuracy, fast response and anti-interference ability. SUMMARY

[0006] In order to solve the above problems, the present disclosure provides an electric signal control method, device, equipment, medium and product of an energy storage system. This scheme can be applied to the control of linear and nonlinear systems, and has the characteristics of wide application scenarios, fast response, good stability and high robustness.

[0007] The technical scheme of the present disclosure is implemented as follows:

[0008] In a first aspect, the disclosure provides an electric signal control method of an energy storage system, the method comprising: determining an error of a direct current electric signal and a sliding surface based on an expected value and an actual value of the direct current electric signal output by the energy storage system; determining an adjustment value of the direct current electric signal by proportionally and integrally adjusting the error and slidingly adjusting the sliding surface through a target controller; determining a number N of input modules based on at least a reference direct current electric signal and an average electric signal of one sub-module in the energy storage system; the reference direct current electric signal being a sum of the adjustment value of the direct current electric signal and the expected value of the direct current electric signal; N being an integer greater than zero; and controlling N sub-modules in the energy storage system to be turned on through an energy storage valve control module of the energy storage system, so that the energy storage system outputs the direct current electric signal according to output capabilities of the N sub-modules.

[0009] It can be seen that, in the process of controlling the electric signal, the actual electric signal value is the output capability of the N sub-modules outputting the direct current electric signal, which may not be completely consistent with the expected value of the direct current electric signal; the traditional PID control may have instability problems, the target controller of the disclosure combines PI control and sliding mode control, and the adjustment value of the electric signal is determined through PI adjustment and sliding mode adjustment. This control scheme can be applied to linear, nonlinear, unlocking and other scenes. The PI adjustment realizes fast response; the sliding mode control meets the requirements of stability and robustness. This scheme combines the advantages of PI control and sliding mode control, and has the characteristics of wide application scene, fast response, good stability and high robustness.

[0010] In a possible implementation, the adjustment value of the direct current electric signal is determined by proportionally and integrally adjusting the error and slidingly adjusting the sliding surface through the target controller, comprising: determining a proportional gain, an integral gain, a sliding gain and a saturation function in the target controller; determining a proportional adjustment value as a product of the proportional gain and the error; determining an integral adjustment value as a product of the integral gain and an integral operation result of the error; determining a sliding adjustment value based on the sliding surface, the saturation function and the sliding gain; and determining the adjustment value of the direct current electric signal as a sum of the proportional adjustment value, the integral adjustment value and the sliding adjustment value.

[0011] It can be seen that, in this possible implementation, the proportional gain, the integral gain, the sliding gain and the saturation function in the target controller are first determined, and then the proportional adjustment value, the integral adjustment value and the sliding adjustment value are determined based on these gains and the saturation function; and finally the adjustment value of the direct current electric signal is obtained from the proportional adjustment value, the integral adjustment value and the sliding adjustment value. The adjustment value can be directly summed, or the adjustment value can be obtained by weighting and summing the various adjustment values according to actual requirements. It has the characteristics of flexible and reliable implementation.

[0012] In a possible implementation, the integral gain in the target controller is determined by: determining whether the error of the direct current signal is greater than a first error threshold; determining the integral gain based on the error of the direct current signal when the error of the direct current signal is greater than the first error threshold; wherein the greater the absolute value of the error of the direct current signal, the closer the integral gain is to zero; the smaller the absolute value of the error of the direct current signal, the closer the integral gain is to a first integral gain; and determining the integral gain as zero when the error of the direct current signal is less than or equal to the first error threshold.

[0013] It can be seen that the first error threshold is set, and the integral gain is set as zero when the error of the direct current signal is less than or equal to the first error threshold, integral separation is achieved, and a large integral value of the system voltage near the equilibrium point is avoided, which leads to poor system stability; and thus the stability is further improved.

[0014] In a possible implementation, the integral gain is determined based on the error of the direct current signal by: determining an inverse function and a first exponential function for integral adjustment; determining an inverse adjustment value based on the absolute value of the error of the direct current signal and the inverse function; wherein the greater the absolute value of the error of the direct current signal, the closer the inverse adjustment value is to zero; the smaller the absolute value of the error of the direct current signal, the closer the inverse adjustment value is to a first value; determining a first exponential adjustment value based on the absolute value of the error of the direct current signal and the first exponential function; wherein the greater the absolute value of the error of the direct current signal, the closer the first exponential adjustment value is to zero; the smaller the absolute value of the error of the direct current signal, the closer the first exponential adjustment value is to a second value; and multiplying the sum of the inverse adjustment value and the first exponential adjustment value by a reference integral coefficient to obtain the integral gain; wherein the first integral gain is the result of the sum of the first value and the second value multiplied by the reference integral coefficient.

[0015] It can be seen that when the absolute value of the error is large, the function value will tend to 0, thereby reducing the integral gain and preventing integral saturation. When the absolute value of the error is small, the coefficient value will tend to the first integral gain, maintaining a high integral gain and achieving fast response. And the integral gain is determined by the inverse function and the exponential function, which has the characteristics of simple implementation and reliability.

[0016] In a possible implementation, the saturation function in the target controller is determined, including: determining a second exponential function, a proportional function and a hyperbolic tangent function for the sliding mode regulation; determining a first coefficient based on a first reference parameter of the saturation function, a sliding surface and the exponential function; determining a second coefficient based on a second reference parameter of the saturation function, the sliding surface and the proportional function; determining the saturation function based on the first coefficient, the second coefficient, the sliding surface and the hyperbolic tangent function; wherein the greater the absolute value of the sliding surface is, the smaller the value of the first coefficient is, and the greater the value of the second coefficient is; the smaller the absolute value of the sliding surface is, the greater the value of the first coefficient is, and the smaller the value of the second coefficient is; and the value range of the saturation function is between a third value and a fourth value.

[0017] It can be seen that when the sliding surface s is large, the first coefficient decreases and the second coefficient increases to improve stability; when the sliding surface s is small, the first coefficient increases and the second coefficient decreases to improve response speed. The saturation function is implemented by the exponential function, the proportional function and the hyperbolic tangent function, and can achieve smooth transition, avoid mutation and enhance overall robustness. The adaptive saturation function can dynamically adjust the control characteristics according to the actual running state of the sliding mode controller to improve the performance of the sliding mode control.

[0018] In a possible implementation, the sliding mode gain in the target controller is determined, including: determining a derivative of an error of the direct current signal based on the error of the direct current signal; performing fuzzy processing on the error and the derivative of the error to obtain a fuzzy input of the error and a fuzzy input of the derivative of the error; searching, in a fuzzy rule base, a fuzzy output of the sliding mode gain corresponding to the fuzzy input of the error and the fuzzy input of the derivative of the error; and performing defuzzy processing on the fuzzy output of the sliding mode gain to obtain the sliding mode gain.

[0019] In the sliding mode control, a larger disturbance requires a larger switching gain to ensure the stability of the closed-loop system, which causes chattering. Compared with the traditional controller, the fuzzy controller has better robustness and adaptability. In actual application, the fuzzy controller can be combined with the sliding mode control to optimize the sliding mode gain by adjusting the parameters and the rule base of the fuzzy set, so as to eliminate the chattering effect.

[0020] In a possible implementation, the number N of the input modules is determined based on at least a reference direct current signal and an average direct current signal of one sub-module in the energy storage system, including: dividing the reference direct current signal by the average direct current signal to obtain an integer part and a decimal part; obtaining a current amplitude of a reference triangular wave; the amplitude of the reference triangular wave ranges from zero to one; in a case where the decimal part is greater than or equal to the amplitude, determining that the N is the integer part plus 1; and in a case where the decimal part is less than the amplitude, determining that the N is the integer part.

[0021] In practice, the ratio of the reference DC signal to the average electric signal is not necessarily an integer, and in the case of a result including a decimal fraction, the integer is generally directly obtained by rounding. In this way, the stable phase problem may occur, and in this embodiment, the number of input modules N is determined based on the triangular wave, so that the system can be controlled to change between N and N+1 according to the carrier period, thereby improving the stability.

[0022] In a possible implementation, the error of the DC signal and the sliding surface are determined based on the expected value and the actual value of the DC signal output by the energy storage system, including: determining the error of the DC signal based on the expected value and the actual value of the DC signal; determining the derivative of the error of the DC signal based on the error of the DC signal; determining the sliding surface based on the error of the DC signal and the derivative of the error of the DC signal.

[0023] As can be seen, in this embodiment, the sliding surface is determined based on the error of the DC signal and the derivative of the error of the DC signal, and on the basis of realizing the sliding mode control, the weight can be increased according to the actual demand, and the implementation is flexible.

[0024] In a possible implementation, in the case of the DC signal being a DC voltage, the method further includes: determining that the energy storage system is in a constant voltage control mode; and in the case of determining that the energy storage valve in the energy storage system is unlocked, performing the determination of the error of the DC signal and the sliding surface based on the expected value and the actual value of the DC signal output by the energy storage system.

[0025] As can be seen, the electric signal control method of the energy storage system can be applied to the scenario of unlocking the energy storage valve in the constant voltage mode. Since in the energy storage system, the system voltage changes due to the change of the number of input sub-modules (the change of the average capacitor voltage) at the unlocking moment, thereby causing disturbance. The target controller can improve the stability of the voltage at the unlocking moment.

[0026] In a second aspect, the present disclosure provides an electric signal control device of an energy storage system, the device comprising:

[0027] a first determination unit configured to determine the error of the DC signal and the sliding surface based on the expected value and the actual value of the DC signal output by the energy storage system;

[0028] a second determination unit configured to determine the adjustment value of the DC signal by performing proportional integral adjustment on the error and sliding mode adjustment on the sliding surface through a target controller;

[0029] a third determination unit configured to determine the number of input modules N based on at least the reference DC signal and the average electric signal of one sub-module in the energy storage system; the reference DC signal is the sum of the adjustment value of the DC signal and the expected value of the DC signal; N is an integer greater than zero.

[0030] The control unit is configured to control N sub-modules in the energy storage system to be turned on by an energy storage valve control module of the energy storage system, so that the energy storage system outputs a direct current signal according to the output capacity of the N sub-modules.

[0031] In a third aspect, the present disclosure provides an electronic device, which comprises a memory and a processor, and the memory stores a computer program or instructions, and the computer program or instructions are executed by the processor to implement any method provided in the first aspect.

[0032] In a fourth aspect, the present disclosure further provides a computer readable storage medium, which stores a computer program or instructions, and the computer program or instructions are executed by a processor to implement any method provided in the first aspect.

[0033] In a fifth aspect, the present disclosure further provides a computer program product, which comprises a computer program or instructions, and the computer program or instructions are executed by a processor to implement any method provided in the first aspect.

[0034] It should be noted that the electrical signal control device of the energy storage system, the electronic device, the storage medium and the computer program product have the same technical effects as the electrical signal control method of the energy storage system. For the technical effects corresponding to the electrical signal control device of the energy storage system, the electronic device, the storage medium and the computer program product, reference can be made to the detailed description of the first aspect, which will not be repeated here. BRIEF DESCRIPTION OF DRAWINGS

[0035] FIG. 1 is a schematic structural diagram of an optional electrical signal control system according to an embodiment of the present disclosure;

[0036] FIG. 2 is a first optional flow diagram of an electrical signal control method of an energy storage system according to an embodiment of the present disclosure;

[0037] FIG. 3 is a second optional flow diagram of an electrical signal control method of an energy storage system according to an embodiment of the present disclosure;

[0038] FIG. 4 is a third optional flow diagram of an electrical signal control method of an energy storage system according to an embodiment of the present disclosure;

[0039] FIG. 5 is a fourth optional flow diagram of an electrical signal control method of an energy storage system according to an embodiment of the present disclosure;

[0040] FIG. 6 is a fifth optional flow diagram of an electrical signal control method of an energy storage system according to an embodiment of the present disclosure;

[0041] FIG. 7 is a sixth optional flowchart of the method for controlling the electrical signal of the energy storage system according to an embodiment of the present disclosure;

[0042] FIG. 8 is a seventh optional flowchart of the method for controlling the electrical signal of the energy storage system according to an embodiment of the present disclosure;

[0043] FIG. 9 is an eighth optional flowchart of the method for controlling the electrical signal of the energy storage system according to an embodiment of the present disclosure;

[0044] FIG. 10 is a ninth optional flowchart of the method for controlling the electrical signal of the energy storage system according to an embodiment of the present disclosure;

[0045] FIG. 11 is another optional structure diagram of the control system of the electrical signal according to an embodiment of the present disclosure;

[0046] FIG. 12 is an optional structure diagram of the fuzzy control according to an embodiment of the present disclosure;

[0047] FIG. 13 is an optional structure diagram of the controller according to an embodiment of the present disclosure;

[0048] FIG. 14 is an optional flowchart of the optimization process of the integral gain K I according to an embodiment of the present disclosure;

[0049] FIG. 15 is an optional flowchart of the voltage control process according to an embodiment of the present disclosure;

[0050] FIG. 16 is an optional structure diagram of the comparison process of the carrier comparison module according to an embodiment of the present disclosure;

[0051] FIG. 17 is an optional flowchart of the carrier comparison function according to an embodiment of the present disclosure;

[0052] FIG. 18 is an optional structure diagram of the electrical signal control device of the energy storage system according to an embodiment of the present disclosure;

[0053] FIG. 19 is an optional structure diagram of the electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the following will further describe the specific technical solutions of the present disclosure with reference to the drawings in the embodiments of the present disclosure. The following embodiments are used to explain the present disclosure but not to limit the scope of the present disclosure.

[0055] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" can be the same subset or a different subset of all possible embodiments, and can be combined with each other, without conflict.

[0056] In the following description, the terms "first\second\third" are only used to distinguish different objects, and do not represent a specific order of the objects, and do not have a sequence limitation. It can be understood that "first\second\third" can be interchanged in a specific order or sequence as allowed, so that the embodiments of the disclosure described herein can be implemented in an order other than that illustrated or described herein.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present disclosure belongs. The terms used herein are only for the purpose of describing the embodiments of the present disclosure, and are not intended to limit the present disclosure.

[0058] The embodiments of the present disclosure provide an electric signal control method, device, equipment, medium and product of an energy storage system. In practical application, the electric signal control method of the energy storage system is realized by an electric signal control device of the energy storage system, and each functional entity of the electric signal control device of the energy storage system can be realized by hardware resources of an electronic device, such as computing resources, communication resources, and the like.

[0059] Next, each embodiment of the electric signal control method, device, equipment, medium and product of the energy storage system provided by the embodiments of the present disclosure are described.

[0060] For ease of understanding, first, the control system of the electric signal is described.

[0061] Exemplarily, referring to the content shown in FIG. 1, the control system of the electric signal 10 can include a converter valve control module 10, an energy storage valve control module 20, and a plurality of sub-modules 30.

[0062] The converter valve control module 10 is configured to convert an alternating current signal into a direct current signal.

[0063] The energy storage valve control module 20 is configured to determine an error of the direct current signal and a sliding surface based on an expected value and an actual value of the direct current signal output by the energy storage system, determine an adjustment value of the direct current signal by proportionally and integrally adjusting the error and slidingly adjusting the sliding surface through a target controller, determine the number N of input modules based on at least a reference direct current signal and an average electric signal of one sub-module in the energy storage system, the reference direct current signal being a sum of the adjustment value of the direct current signal and the expected value of the direct current signal, N being an integer greater than zero, and control N sub-modules in the energy storage system to be turned on through the energy storage valve control module of the energy storage system, so that the energy storage system outputs the direct current signal according to the output capacity of the N sub-modules.

[0064] The energy storage valve control module 20 can include but is not limited to an energy storage valve and a controller.

[0065] The sub-module 30 is configured to output an electric signal. The sub-module 30 includes some Insulate-Gate Bipolar Transistor (IGBT) circuits.

[0066] In a first aspect, the embodiments of the present disclosure provide an electric signal control method of an energy storage system, which is used for controlling an electric signal to stabilize the output electric signal near an expected value of the electric signal.

[0067] Hereinafter, the electric signal control method of the energy storage system is described by taking an electronic device (for example, the controller in FIG. 1) as an execution subject.

[0068] Referring to the content shown in FIG. 2, the process can include but is not limited to the following S201 to S204.

[0069] S201, determining an error of a direct current signal and a sliding surface based on an expected value and an actual value of the direct current signal output by the energy storage system.

[0070] The direct current signal can include but is not limited to a direct current voltage signal or a direct current current signal.

[0071] The expected value of the direct current signal refers to a value of the direct current signal in an instruction.

[0072] The actual value of the direct current signal refers to a value of the direct current signal output by each sub-module in the energy storage system collected.

[0073] S201 can be implemented by first obtaining the expected value and the actual value of the direct current signal output by the energy storage system, then determining the difference between the expected value and the actual value of the direct current signal as the error of the direct current signal, and determining the sliding surface based on the error of the direct current signal and a derivative of the error.

[0074] S202, proportionally and integrally adjusting the error of the direct current signal by the target controller, and performing sliding mode adjustment on the sliding mode surface to determine an adjustment value of the direct current signal.

[0075] The target controller can be a proportional-integral sliding mode controller.

[0076] The sliding mode adjustment (also referred to as sliding mode control) herein can be pure sliding mode adjustment or fuzzy sliding mode adjustment.

[0077] The specific expression of the target controller can be configured according to actual requirements, and is not uniquely limited herein.

[0078] S202 can be implemented as: proportionally and integrally adjusting the error of the direct current signal by the target controller, performing sliding mode adjustment on the sliding mode surface, fusing the results of the proportional-integral adjustment and the sliding mode adjustment, and obtaining the adjustment value of the direct current signal.

[0079] For example, the error of the direct current signal is proportionally and integrally adjusted by the target controller, the sliding mode surface is adjusted by the sliding mode, and the results of the proportional-integral adjustment and the sliding mode adjustment are summed to obtain the adjustment value of the direct current signal.

[0080] S203, determining the number N of input modules based at least on the reference direct current signal and the average electric signal of one sub-module in the energy storage system.

[0081] The reference direct current signal is the sum of the adjustment value of the direct current signal and the expected value of the direct current signal.

[0082] N is an integer greater than zero. The value of N is not limited by the embodiments of the disclosure and can be configured according to actual conditions.

[0083] S203 can be implemented as: summing the adjustment value of the direct current signal and the expected value of the direct current signal to obtain the reference direct current signal; and then determining the number N of input modules based at least on the reference direct current signal and the average electric signal.

[0084] For the implementation of determining the number N of input modules based at least on the reference direct current signal and the average electric signal:

[0085] In one possible implementation, the reference direct current signal is divided by the average electric signal to obtain an integer part and a decimal part, and then the integer part is directly determined as the number N of input modules; or the integer part is directly determined as the number N of input modules by adding one; or the number N of input modules is obtained by rounding the decimal part based on the rounding principle and adding the integer part.

[0086] In another possible implementation, the reference direct current signal is divided by the average electrical signal to obtain an integer part and a decimal part, and then the decimal part is compared with a reference waveform (for example, a triangular wave) to obtain the number N of input modules.

[0087] S204, control the N sub-modules in the energy storage system to be turned on by the energy storage valve control module of the energy storage system, so that the energy storage system outputs a direct current signal according to the output capacity of the N sub-modules.

[0088] In a possible implementation, in the case of an electrical signal being a voltage signal, the N sub-modules in the energy storage system are controlled to be turned on by the energy storage valve control module of the energy storage system, so that the energy storage system outputs a direct current voltage signal according to the output capacity of the N sub-modules. Wherein, after obtaining the number N of input modules, the controller in the energy storage valve control module outputs N to the energy storage valve, and the energy storage valve controls the N sub-modules in the energy storage system to be turned on, so that the energy storage system outputs a direct current voltage signal according to the output capacity of the N sub-modules.

[0089] In the case of an electrical signal being a current signal, the implementation process is similar to that of a voltage signal, which will not be described here.

[0090] The electrical signal control method of the energy storage system provided by the present disclosure includes: determining the error of a direct current signal and a sliding surface based on the expected value and the actual value of the direct current signal output by the energy storage system; determining the adjustment value of the direct current signal by proportionally integrating the error and slidingly adjusting the sliding surface through a target controller; determining the number N of input modules based on at least a reference direct current signal and an average electrical signal of one sub-module in the energy storage system; the reference direct current signal is the sum of the adjustment value of the direct current signal and the expected value of the direct current signal; N is an integer greater than zero; and controlling the N sub-modules in the energy storage system to be turned on by the energy storage valve control module of the energy storage system, so that the energy storage system outputs a direct current signal according to the output capacity of the N sub-modules.

[0091] As can be seen, in the process of controlling the electrical signal, the actual electrical signal value is the output capacity of the N sub-modules outputting a direct current signal, which may not be completely consistent with the expected value of the direct current signal; the traditional PID control may have instability problems, and the target controller of the present disclosure combines PI control and sliding mode control to determine the adjustment value of the electrical signal through PI adjustment and sliding mode adjustment. This control scheme can be applied to linear, nonlinear, and unlocked scenarios. The PI adjustment realizes fast response; the sliding mode control meets the stability and robustness requirements. This scheme combines the advantages of PI control and sliding mode control, and has the characteristics of wide application scenarios, fast response, good stability, and high robustness.

[0092] Next, the process of determining the adjustment value of the direct current signal by proportionally and integrally adjusting the error through the target controller and by sliding mode adjusting the sliding surface in S202 is described.

[0093] Referring to the content shown in FIG. 3, the process can include, but is not limited to, the following S2021 to S2025.

[0094] S2021, determine the proportional gain, integral gain, sliding mode gain and saturation function in the target controller.

[0095] The values of the proportional gain, integral gain, sliding mode gain and saturation function here can be empirical values, or can be according to the dynamic adjustment value.

[0096] S2022, determine the proportional adjustment value as the product of the proportional gain and the error.

[0097] S2023, determine the integral adjustment value as the product of the integral gain and the integral operation of the error.

[0098] S2024, determine the sliding mode adjustment value based on the sliding surface, the saturation function and the sliding mode gain.

[0099] Here, the way of determining the sliding mode adjustment value based on the sliding surface, the saturation function and the sliding mode gain is not specifically limited, and can be configured according to actual needs.

[0100] For example, the sliding mode adjustment value can be determined according to the following first formula. The first formula includes: A = K s |s| r sat(s). In the first formula, A represents the sliding mode adjustment value; Ks represents the sliding mode gain; sat(s) represents the saturation function; s represents the sliding surface; and r is a coefficient.

[0101] S2025, determine the adjustment value of the direct current signal based on the proportional adjustment value, the integral adjustment value and the sliding mode adjustment value.

[0102] In one possible implementation, the proportional adjustment value, the integral adjustment value and the sliding mode adjustment value are summed to obtain the adjustment value of the direct current signal.

[0103] In another possible implementation, the weights corresponding to the proportional adjustment value, the integral adjustment value and the sliding mode adjustment value are first determined respectively, and then the weighted sum is performed to obtain the adjustment value of the direct current signal.

[0104] It can be seen that in this possible real-time manner, the proportional gain, the integral gain, the sliding mode gain and the saturation function in the target controller are first determined, and then the proportional adjustment value, the integral adjustment value and the sliding mode adjustment value are determined based on the gains and the saturation function; and then the adjustment value of the direct current signal is obtained based on the proportional adjustment value, the integral adjustment value and the sliding mode adjustment value. The adjustment value can be directly summed up, or the weight coefficients can be added to the various adjustment values according to actual requirements, and the adjustment value can be obtained by weighted sum. It has the characteristics of flexible and reliable implementation.

[0105] Next, the process of determining the proportional gain in the target controller in S2021 is described.

[0106] Referring to the content shown in FIG. 4, the process can include but is not limited to the following S401 to S403.

[0107] S401, determining whether the error of the direct current signal is greater than a first error threshold.

[0108] The value of the first error threshold is not limited in the embodiments of the present disclosure, and can be determined according to actual conditions.

[0109] S402, in the case where the error of the direct current signal is greater than the first error threshold, determining the integral gain based on the error of the direct current signal.

[0110] Wherein, the greater the absolute value of the error of the direct current signal, the closer the integral gain is to zero; the smaller the absolute value of the error of the direct current signal, the closer the integral gain is to the first integral gain.

[0111] The implementation of determining the integral gain based on the error of the direct current signal can be configured according to actual requirements. For example, it can be implemented based on an inverse function and an exponential function. Of course, other functions can also be used to implement it, which are not listed one by one here.

[0112] S403, in the case where the error of the direct current signal is less than or equal to the first error threshold, determining the integral gain as zero.

[0113] It can be seen that by setting the first error threshold, when the error of the direct current signal is less than or equal to the first error threshold, the integral gain is set to zero, realizing integral separation, avoiding the system voltage to produce a larger integral value near the equilibrium point, leading to poor system stability; thereby further improving the stability.

[0114] Next, the process of determining the integral gain based on the error of the direct current signal in S402 is described.

[0115] Referring to the content shown in FIG. 5, the process can include but is not limited to S4021 to S4024.

[0116] S4021, determine an inverse function and a first exponential function for integral adjustment.

[0117] S4022, determine an inverse adjustment value based on the absolute value of the error of the direct current signal and the inverse function.

[0118] Wherein, the greater the absolute value of the error of the direct current signal, the closer the inverse adjustment value to zero; the smaller the absolute value of the error of the direct current signal, the closer the inverse adjustment value to the first value.

[0119] Exemplarily, the inverse function can refer to the second formula.

[0120] The second formula includes: In the second formula, B represents the inverse adjustment value; |e| represents the absolute value of the error of the direct current signal; a1 and b1 are the coefficients of the inverse function respectively; a1 and b1 can be determined according to empirical values.

[0121] In the second formula, the first value is 1 / a1.

[0122] S4023, determine a first exponential adjustment value based on the absolute value of the error of the direct current signal and the first exponential function.

[0123] Wherein, the greater the absolute value of the error of the direct current signal, the closer the first exponential adjustment value to zero; the smaller the absolute value of the error of the direct current signal, the closer the first exponential adjustment value to the second value.

[0124] The first exponential function can refer to the third formula.

[0125] The third formula includes: C=c1×e -d1×|e| ; In the third formula, C represents the first exponential adjustment value; |e| represents the absolute value of the error of the direct current signal; c1 and d1 are the coefficients of the first exponential function respectively; c1 and d1 can be determined according to empirical values.

[0126] In the third formula, the second value is c1.

[0127] S4024, multiply the sum of the inverse adjustment value and the first exponential adjustment value by the reference integral coefficient to obtain the integral gain.

[0128] Wherein, the first integral gain is the result of the sum of the first value and the second value multiplied by the reference integral coefficient.

[0129] The determination process of the integral gain can refer to the fourth formula.

[0130] The fourth formula includes: K I =K i ×(B+C); In the fourth formula, K I represents the integral gain; K iK represents a reference integral coefficient; B represents an inverse adjustment value; and C represents a first exponential adjustment value.

[0131] For example, the first integral gain is K i ×(1 / a1+c1).

[0132] It can be seen that when the absolute value of the error is large, the function value will tend to 0, thereby reducing the integral gain and preventing integral saturation. When the absolute value of the error is small, the coefficient value will tend to the first integral gain, maintaining a high integral gain and achieving fast response. The integral gain is determined by the inverse function and the exponential function, which is simple and reliable to implement.

[0133] Next, the process of determining the saturation function in the target controller in S2021 is described.

[0134] Referring to the content shown in FIG. 6, the process can include, but is not limited to, the following S601 to S604.

[0135] S601, determining a second exponential function, a proportional function, and a hyperbolic tangent function for sliding mode regulation.

[0136] The second exponential function, the proportional function, and the hyperbolic tangent function can be configured based on actual needs.

[0137] S602, determining a first coefficient based on a first reference parameter of the saturation function, a sliding surface, and an exponential function.

[0138] For example, the first coefficient can be determined with reference to a fifth formula.

[0139] The fifth formula can include: In the fifth formula, K represents the first coefficient; s represents the sliding surface; k2 represents the first reference parameter of the saturation function; a2 represents an adjustment coefficient; and the value of a2 can be configured according to experience.

[0140] S603, determining a second coefficient based on a second reference parameter of the saturation function, the sliding surface, and a proportional function.

[0141] For example, the second coefficient can be determined with reference to a sixth formula.

[0142] The sixth formula can include: L=L2×(1+b2×|s|); in the sixth formula, L represents the second coefficient; s represents the sliding surface; L2 represents the second reference parameter of the saturation function; and b2 represents an adjustment coefficient; and the value of b2 can be configured according to experience.

[0143] S604, determining the saturation function based on the first coefficient, the second coefficient, the sliding surface, and the hyperbolic tangent function.

[0144] The greater the absolute value of the sliding surface is, the smaller the value of the first coefficient is, and the greater the value of the second coefficient is; the smaller the absolute value of the sliding surface is, the greater the value of the first coefficient is, and the smaller the value of the second coefficient is; and the value range of the saturation function is between the third value and the fourth value.

[0145] For example, the saturation function can be determined according to a seventh formula. The seventh formula can include: In the seventh formula, K represents the first coefficient; L represents the second coefficient; s represents the sliding surface; and tanh represents the hyperbolic tangent function.

[0146] It can be seen that when the sliding surface s is large, the first coefficient decreases and the second coefficient increases, thereby improving the stability; and when the sliding surface s is small, the first coefficient increases and the second coefficient decreases, thereby improving the response speed. The saturation function is realized by an exponential function, a proportional function and a hyperbolic tangent function, and can realize smooth transition, avoid mutation and enhance the overall robustness. The adaptive saturation function can dynamically adjust the control characteristics according to the actual running state of the sliding mode controller, thereby improving the performance of the sliding mode control.

[0147] Next, the process of determining the sliding mode gain in the target controller in S2021 is described.

[0148] Referring to the content shown in FIG. 7, the process can include, but is not limited to, the following S701 to S704.

[0149] S701, determining the error derivative of the direct current signal based on the error of the direct current signal.

[0150] Deriving the error of the direct current signal, the error derivative of the direct current signal is obtained.

[0151] S702, performing fuzzy processing on the error and the error derivative to obtain the fuzzy input of the error and the fuzzy input of the error derivative.

[0152] Here, the way of fuzzy processing is not limited, and can be configured according to actual needs. For example, the fuzzy processing can be performed according to a graded fuzzy set method or a membership value method.

[0153] S703, searching the fuzzy rule base to find the fuzzy output of the sliding mode gain corresponding to the fuzzy input of the error and the fuzzy input of the error derivative.

[0154] The fuzzy rule base stores the fuzzy output corresponding to each set of error fuzzy input and error derivative fuzzy input. The fuzzy input of the error and the fuzzy input of the error derivative obtained in S702 are limited, and then the fuzzy output corresponding to the fuzzy input of the error and the fuzzy input of the error derivative is searched; and the fuzzy output is determined as the fuzzy output of the sliding mode gain.

[0155] S704, defuzzification is performed on the fuzzy output of the sliding mode gain to obtain the sliding mode gain.

[0156] Here, the defuzzification method is not limited, and can be configured according to actual needs. For example, the maximum membership degree method, the barycenter method, and the weighted average method can be used for defuzzification to obtain the sliding mode gain.

[0157] In the sliding mode control, a larger disturbance requires a larger switching gain to ensure the stability of the closed-loop system, which causes chattering. However, the fuzzy controller has better robustness and adaptability than the traditional controller. In practical applications, the fuzzy controller can be combined with the sliding mode control to optimize the sliding mode gain by adjusting the parameters of the fuzzy set and the rule base, so as to eliminate the chattering effect.

[0158] Next, the process of determining the number N of modules to be put into operation based on at least the reference direct current signal and the average electric signal of one sub-module in the energy storage system in S203 is described.

[0159] Referring to the content shown in FIG. 8, the process can include but is not limited to the following S801 to S804.

[0160] S801, divide the reference direct current signal by the average electric signal to obtain an integer part and a decimal part.

[0161] S802, obtain the current amplitude of the reference triangular wave.

[0162] The amplitude of the reference triangular wave ranges from zero to one.

[0163] The frequency of the reference triangular wave can be configured according to actual needs.

[0164] For example, the frequency of the reference triangular wave is related to one or more of the following parameters: control period, IGBT conduction frequency, and electric signal effect.

[0165] The control period refers to the time length occupied by a complete process of the electric signal. The period length corresponding to the frequency of the reference triangular wave can be set to be greater than the control period. For example, if a control period is 50 microseconds, the period corresponding to the frequency of the reference triangular wave needs to be greater than 50 microseconds.

[0166] The IGBT conduction frequency refers to the conduction frequency of the IGBT device in the sub-module.

[0167] When the frequency of the reference triangular wave is too high, the fast switching of the single sub-module can cause the trigger frequency to exceed the limit protection, causing the energy storage valve control module (such as the energy storage valve) to trip. Therefore, the frequency of the reference triangular wave is less than the conduction frequency of the IGBT device, so as to reduce the conduction frequency and improve the problem that the fast switching of the single sub-module can cause the trigger frequency to exceed the limit protection.

[0168] The frequency of the reference triangular wave can be adjusted according to the effect of the actual electrical signal, so that the frequency of the reference triangular wave has a good electrical signal effect.

[0169] S803, in the case where the decimal part is greater than or equal to the amplitude, determining N as the integer part plus 1.

[0170] The amplitude here is the amplitude of the reference triangular wave at the current time.

[0171] S804, in the case where the decimal part is less than the amplitude, determining N as the integer part.

[0172] It should be noted that if the decimal part is zero, i.e. there is no decimal part, the integer part is directly determined as N.

[0173] In practice, the reference DC signal divided by the average electrical signal may not be an integer value, and in the case where the result includes a decimal fraction, it is generally rounded directly. In this way, the stable phase problem may occur, and in this embodiment, the number of input modules N is determined based on the triangular wave mode, which can control the system to change between N and N+1 according to the carrier period, thereby improving the stability.

[0174] Next, the process of determining the error of the DC signal and the sliding surface based on the expected value and the actual value of the DC signal output by the energy storage system in S201 is described.

[0175] Referring to the content shown in FIG. 9, the process can include but is not limited to the following S901 to S903.

[0176] S901, determining the error of the DC signal based on the expected value and the actual value of the DC signal.

[0177] The difference between the expected value and the actual value of the DC signal is determined as the error of the DC signal.

[0178] S902, determining the error derivative of the DC signal based on the error of the DC signal.

[0179] The error derivative of the DC signal is obtained by differentiating the error of the DC signal.

[0180] S903, determining the sliding surface based on the error of the DC signal and the error derivative of the DC signal.

[0181] For example, the sum of the error of the DC signal and the error derivative of the DC signal can be determined as the sliding surface.

[0182] For another example, the error of the DC signal can be multiplied by a coefficient and then summed with the error derivative to obtain the sliding surface.

[0183] It can be seen that, in this embodiment, the sliding mode surface is determined based on the error of the flow signal and the derivative of the error of the direct current signal, and on the basis of realizing the sliding mode control, the weight can be increased according to actual needs, and the implementation is flexible.

[0184] In the case of a direct current signal being a direct current voltage, the process can include but is not limited to the following S1001 to S1005 according to the content shown in FIG. 10.

[0185] S1001, determining that the energy storage system is in a constant voltage control mode.

[0186] Read the configuration information of the voltage control to obtain the voltage control mode, and in the case that the voltage control mode is a constant voltage control mode, determine that the energy storage system is in a constant voltage control mode.

[0187] S1002, in the case that the energy storage valve in the energy storage system is determined to be unlocked, based on the expected value and the actual value of the direct current voltage signal output by the energy storage system, the error of the direct current voltage signal and the sliding mode surface are determined.

[0188] The implementation of S1002 can refer to the description of S201 described above, which will not be described here.

[0189] S1003, the error is proportionally integrated by the target controller, and the sliding mode surface is adjusted by the sliding mode adjustment to determine the adjustment value of the direct current voltage signal.

[0190] The implementation of S1003 can refer to the description of S202 described above, which will not be described here.

[0191] S1004, based on at least the reference direct current voltage signal and the average voltage signal of one sub-module in the energy storage system, the number N of modules to be put into operation is determined.

[0192] The implementation of S1004 can refer to the description of S203 described above, which will not be described here.

[0193] S1005, the N sub-modules in the energy storage system are controlled to be turned on by the energy storage valve control module of the energy storage system, so that the energy storage system outputs the direct current voltage signal according to the output capacity of the N sub-modules.

[0194] The implementation of S1005 can refer to the description of S204 described above, which will not be described here.

[0195] It can be seen that the energy signal control method of the energy storage system can be applied to the energy storage valve unlocking scene in the constant voltage mode. Because in the energy storage system, the system voltage changes due to the change of the number of sub-modules to be put into operation (the average capacitor voltage changes) at the unlocking moment, thereby appearing disturbance. The target controller can improve the stability of the voltage at the unlocking moment.

[0196] The control method provided by the embodiments of the present disclosure is described below.

[0197] Energy storage systems play an increasingly important role in renewable energy generation, grid peak shaving, electric vehicle charging, and other fields. Through energy storage technology, smooth operation of the power system, improvement of energy utilization efficiency, and enhancement of grid flexibility can be achieved. Among them, direct current voltage control is a crucial link in the energy storage system, directly related to the safety, reliability and service life of the energy storage unit.

[0198] Direct current voltage control has been widely used in various industrial and energy fields, such as grid energy storage systems, power, renewable energy systems, etc. Traditional direct current voltage control methods usually use proportional integral derivative (PID) feedback control, but due to the existence of nonlinearity, time-varying, uncertainty and other characteristics of the system, the PID controller is difficult to meet the requirements of control accuracy, fast response and anti-interference ability.

[0199] In recent years, adaptive fuzzy sliding mode control (AFSMC) has received widespread attention in the field of direct current voltage control due to its excellent robustness and adaptive ability. AFSMC combines the fuzzy reasoning of fuzzy logic control and the strong robustness of sliding mode control, which can effectively suppress the influence of system parameter changes and external disturbances on control performance. However, existing AFSMC methods still have some problems in practical application, such as high controller design complexity, strong dependence on system model, etc.

[0200] Therefore, the embodiments of the present disclosure propose a direct current voltage adaptive fuzzy sliding mode control method based on energy storage valve control. This method makes full use of the dynamic characteristics of the energy storage valve control system, adopts a simplified AFSMC algorithm, and realizes fast and accurate control of direct current voltage. Compared with the method in the related art, the method of the embodiments of the present disclosure has the advantages of high control accuracy, strong anti-interference ability, easy engineering implementation, etc., and can meet the harsh requirements of direct current voltage control in industrial production and energy applications.

[0201] The related technology provides a direct-current voltage control method of a static synchronous compensator (STATCOM) integrated energy storage system, including: acquiring a direct-current voltage value (UDCX) of a power module in the system; performing logical subtraction operation on the direct-current voltage value UDCX and a direct-current voltage reference value (Udcref); and performing integral operation on a result of the logical subtraction operation by using a PI controller to acquire a current reference value (Idref1X). The embodiment of the present disclosure can realize fast and flexible control of active power of the STATCOM integrated energy storage system.

[0202] The related technology has the following problems: the method cannot well cope with the problem of system voltage variation caused by the change of the number of sub-modules (average capacitor voltage variation) at the moment of unlocking of the energy storage valve base controller (VBC) and the voltage source coverter (VSC). The method only uses a conventional PI control, and the stability and robustness in the face of system uncertainty, disturbance or failure may be challenged.

[0203] The embodiment of the present disclosure can solve the following problems: solving the problem of system voltage variation caused by the change of the number of sub-modules (average capacitor voltage variation) at the moment of unlocking of the VBC (energy storage valve base controller) and the VSC (pole control); solving the problem of slow system dynamic response; solving the problem of poor system voltage anti-interference ability and weak robustness during stable operation of the system.

[0204] The embodiment designs an adaptive fuzzy sliding mode controller suitable for direct-current voltage control of an energy storage system. An adaptive adjustment strategy of integral gain, saturation function and sliding mode gain is designed. A carrier comparison method for enhancing the robustness of the system is designed.

[0205] The technical effects of the embodiment: the energy storage valve fuzzy sliding mode control method provided by the embodiment combines the advantages of fuzzy control, sliding mode control and PI control, is very suitable for the energy storage valve control system with high nonlinearity, has high adaptability, the parameters are easy to adjust, and can adjust the integral gain, sliding mode gain and saturation function according to different working conditions and voltage errors; the control method provided by the embodiment has strong robustness, can well cope with the electrical quantity fluctuation caused by the unlocking of the VBC and the VSC, and improve the anti-interference ability of the system in the steady state; the integral gain setting method in the controller provided by the embodiment combines the characteristics of inverse ratio and exponential function, and realizes smoother adjustment. The integral separation method designed at the same time can prevent the integral oversaturation phenomenon of the system near the steady state point. The carrier comparison function designed by the embodiment can improve the dynamic response and robustness of the system in the voltage control steady state, avoid saturation and overcharging, and make the system swing near the equilibrium point to achieve better performance.

[0206] Referring to the content shown in FIG. 11, the system architecture of this embodiment can include VSC valve 1101 and energy storage valve VBC 1102 and LC, etc. 1103. Among them, VBC is an energy storage valve control, VSC is a converter valve control, the voltage of the energy storage valve VBC control system is controlled, and the current of the system is controlled in the VSC. The voltage instruction value 1104 is issued by the VSC to the VBC to achieve voltage control. Unlocking means that the system is converted from a non-working state to a working state, and the logic of unlocking the system is in the order of unlocking the fixed voltage side first and unlocking the fixed power side later, which is to ensure that the system can preferentially establish a stable voltage control loop during the starting process to ensure the voltage stability of the system and the safe operation of the equipment. However, when the VBC and VSC are unlocked at the moment, the controller needs to adjust the output to adapt to the new working requirements, which may cause instability of voltage and current. In order to reduce this fluctuation, coordination and smooth switching between VBC and VSC need to be ensured to ensure the stability of the system.

[0207] The principle of the control system of this embodiment to control voltage is: after receiving the voltage instruction value (equivalent to the expected value of the above-mentioned electric signal) transmitted by the VSC and the current controller calculation (equivalent to the adjustment value of the above-mentioned electric signal) calculated by the current controller, the input reference value Ndc_ref (equivalent to the above-mentioned reference electric signal) is obtained, and the number of system input modules is calculated by dividing Ndc_ref by the average capacitor voltage of the sub-module. The voltage of the system is controlled by the switching of the sub-module, and the actual value of the voltage is measured in real time to realize closed-loop control.

[0208] Fuzzy control is a control method based on fuzzy logic theory, which converts the precise calculation and deterministic rules in traditional control into calculation and rules based on experience and fuzzy concepts. Compared with traditional control methods, fuzzy control has stronger adaptability and robustness, and has excellent performance in nonlinear systems where control rules are not easy to establish or difficult to accurately describe. 12 is the basic principle diagram of fuzzy control. Simply put, after the data is fuzzed according to the set method, it is compared and calculated with the set rule base, the result is inferred, and the output is obtained after defuzzification.

[0209] Referring to the content shown in FIG. 12, the input 1201 is transmitted to the fuzzification interface 1202, the fuzzification interface 1202 performs fuzzification processing and transmits it to the inference machine 1203, the inference machine 1203 compares and calculates the fuzzed data with the knowledge base 1204 (database 12041 and rule base 12042) (equivalent to fuzzy rule base), and then performs defuzzification processing through the defuzzification interface 1205 and outputs 1206.

[0210] Sliding mode control, also known as variable structure control, can be divided into two parts: sliding surface design and sliding mode control law design. The main idea is to introduce a sliding mode variable to divide the control task of the controlled object into several different subsystems, so that the controller can switch between different subsystems to achieve control of the system. Fuzzy sliding mode control (FSMC) is a control algorithm that combines fuzzy logic and sliding mode control. In the control process, the system first performs fuzzy reasoning based on the current state and control input through fuzzy logic to obtain a fuzzy controller output, and then inputs the output into the sliding mode controller for further processing. Fuzzy sliding mode control has a simple structure, is not dependent on the model, and has strong robustness, making it very suitable for voltage control under this system architecture.

[0211] In this embodiment, the voltage error and the derivative of the error are taken as the inputs of the fuzzy controller, and the sliding mode gain coefficient of the sliding mode controller is calculated and updated in real time by setting rules. Referring to the content shown in FIG. 13, the difference between the Uord voltage 1301 and the Umea voltage 1302 is obtained as an error 1303, and the error 1303 and the derivative 1304 of the error are input to a sliding mode controller 1305. The sliding mode controller 1305 includes an adaptive integral function 13051, a fuzzy controller 13052, and an adaptive saturation function 13053. The sliding mode controller 1305 obtains a Δ function by processing through an integral gain KI, a saturation function sat(s), and a sliding mode gain Ks, obtains a Δ function difference and error, inputs the Δ function difference and error to a carrier comparator 1307 after summing with the Uord voltage 1301, and obtains a number of input modules N after processing. Voltage control is performed based on the N input modules.

[0212] Exemplarily, the sliding mode controller designed in this embodiment selects a commonly used linear sliding surface based on a standard type, which can be referred to formula (1-1); the sliding mode reaching law adopts a power reaching law, which can be referred to formula (1-2); and the designed sliding mode controller can be referred to formula (1-3).

[0213] The controller combines PI control and fuzzy sliding mode control. The PI controller part can provide fast dynamic response, thereby improving the tracking performance of the system; the fuzzy sliding mode controller part can well resist external disturbances and system parameter uncertainties, thereby improving the robustness of the entire control system; and the introduced saturation function can make the control quantity change more smoothly. u = K P e + K I ∫e + K s |s| r sat(s), 0 < r < 1 (1-3);

[0214] In the formula (1-1) to formula (1-3), s(t) represents a sliding surface, e(t) represents an error function, c, r, k represent coefficients; represents a derivative of an error, sgn(s) represents a sign function, a represents a control coefficient, k represents a control coefficient; u represents a control function, K P represents a proportional gain, K I represents an integral gain, K s represents a sliding gain, and sat(s) represents a saturation function.

[0215] It can be understood that the sliding surface can also be a linear sliding surface, a saturation sliding surface, or a second-order sliding surface, etc.; and the sliding reaching law can also be a saturation reaching law, a linear reaching law, etc.

[0216] In the sliding mode control, the reaching law design determines the speed and manner of the system moving from the initial state to the ideal sliding surface. The power-type reaching law has the following effects:

[0217] 1. Adjustment of control force: the |s| a term in the power-type reaching law can provide a control force of corresponding size according to the size of the sliding surface error s. When |s| is large, |s| a is also large, and the controller output will be large, so that the system quickly approaches the sliding surface. When |s| is small, |s| a is also small, and the control output will be appropriately reduced, avoiding the oscillation of the system near the sliding surface.

[0218] 2. Adjustment of reaching dynamic characteristics: the index a in the power-type reaching law determines the dynamic characteristics of the system approaching the sliding surface. When a is large, the speed of the system approaching the sliding surface will be faster, but a larger overshoot can be generated. When a is small, the speed of the system approaching the sliding surface will be relatively slow, but a smoother transition can be obtained.

[0219] 3. Anti-interference ability: the sign(s) term in the power-type reaching law can provide constant anti-interference ability to overcome the influence of system parameters and external disturbances.

[0220] In this embodiment, K I , K s and sat(s) are also optimized.

[0221] 1. Optimization of the integral gain K I .

[0222] K I can be optimized according to the following formula (2).

[0223] In formula (2), K I represents an integral gain; Ki represents the reference integral coefficient; |e| represents the absolute value of the error of the direct current signal; a1, b1, c1, d1, and the delta parameter can be pre-set according to experience.

[0224] An adaptive integral gain function is designed, which combines the characteristics of inverse and exponential functions to achieve smoother adjustment. When the error is large, the exponential function quickly reduces the gain, and when the error is small, the gain quickly recovers.

[0225] Specifically, when the error is large, |e| is large, and the function value will tend to 0, thereby reducing the integral gain and preventing integral saturation. When the error is small, |e| is small, and the coefficient value will tend to 1 / a1+c1, maintaining a high integral gain.

[0226] In particular, the error threshold is set to delta, and when the error is less than the threshold delta, the integral gain is set to 0, realizing integral separation and avoiding the system voltage to generate a large integral value near the equilibrium point, resulting in poor system stability.

[0227] Integral gain K I The optimization process can refer to the content shown in FIG. 14, including but not limited to the following S1401 to S1404.

[0228] S1401, integral gain setting;

[0229] S1402, judge whether e is less than delta;

[0230] If yes, execute the following S1403; if no, execute the following S1404.

[0231] S1403, K I is set to 0, integral separation.

[0232] S1404,

[0233] 2, optimization of saturation function sat(s).

[0234] The sliding mode controller adopts an adaptive sat(s) function, that is, the parameters of the sat(s) function are adjusted in real time according to the system state.

[0235] First, configure the k parameter and the delta parameter in the sat(s) function according to the following formula (3-2) and formula (3-3), and then substitute the k parameter and the delta parameter into formula (3-1) to obtain the sat(s) function. delta=delta2×(1+b2×|s|) (3-3);

[0236] In the formula (3-1) to formula (3-3), s represents the sliding surface; k2 and delta2 are the reference parameters of the sat function; a2 and b2 are the adjustment coefficients, controlling the adaptive speed and amplitude. The k2, delta2, a2 and b2 in the formula (3-1) to formula (3-3) can also be pre-set according to experience.

[0237] By designing such an adaptive sat function based on the sliding surface s, the following is achieved: when the sliding surface s is large, k decreases and delta increases, improving stability; when the sliding surface s is small, k increases and delta decreases, improving response speed; smooth transition is achieved, avoiding sudden changes and enhancing overall robustness; the adaptive sat function thus designed can dynamically adjust the control characteristics according to the actual running state of the sliding mode controller, improving the performance of the sliding mode control.

[0238] 3. Optimization of the sliding mode gain Ks.

[0239] In sliding mode control, for larger disturbances, a larger switching gain is needed to ensure the stability of the closed-loop system, which causes chattering. Fuzzy controllers have better robustness and adaptability than traditional controllers. In practical applications, fuzzy controllers can be combined with sliding mode control to optimize control effects by adjusting the parameters and rule base of fuzzy sets, thereby eliminating chattering.

[0240] The existence condition of the sliding mode is: Ks is the gain that drives the system state to the sliding surface, and under the condition of , the smaller the gain Ks is used as much as possible to reduce chattering. Secondly, when the system moves to a position far from the switching surface, i.e. is large, the larger the Ks value is, the better the system response is; when the system is close to the switching surface, i.e. is small, the smaller the Ks value is, the better the system stability is.

[0241] In fuzzy control, positive big (PB), positive medium (PM), positive small (PS), zero (ZO), negative small (NS), negative medium (NM), and negative big (NB) are commonly used to distinguish fuzzy states. The following figure is an example of a triangular wave membership function.

[0242] Based on the above principles, the is converted into e and The fuzzy rule base is designed to estimate ΔKs, and the content in Table 1 can be referred to.

[0243] Table 1 Fuzzy Rule Base Example

[0244] Finally, the upper bound of Ks is estimated using the following equation (4) through de-fuzzification strategies such as area barycenter method: s = R∫ΔK s , R > 0 (4).

[0245] In equation (4), K s represents the sliding mode gain, and R is a coefficient; ΔK s is the fuzzy output in Table 1.

[0246] In summary, the voltage control of this embodiment can refer to the content shown in FIG. 15, which can include but is not limited to the following S1501 to S1508.

[0247] Wherein:

[0248] S1501, constant voltage control mode.

[0249] In short, it is determined that the current working mode of the energy storage system is the constant voltage working mode.

[0250] S1502, VBC unlocking.

[0251] VBC unlocking action is performed.

[0252] S1503, using adaptive integral gain limiting strategy to control the value of the controller K I .

[0253] The adaptive integral gain limiting strategy here is equivalent to: substituting the real-time error into the above equation (2) to obtain the current integral gain K I ; based on the current integral gain K I , integral control is performed.

[0254] S1504, judge whether the voltage error value is less than the set threshold Δ1, if less than, set K I = 0.

[0255] S1505, using fuzzy control, using sliding mode gain adaptive adjustment according to expert library logic.

[0256] The expert library here is equivalent to the above module rule base. The fuzzy rule base stores the fuzzy output (corresponding to the fuzzy sliding mode gain) corresponding to each set of error fuzzy input and error derivative fuzzy input.

[0257] In short, after fuzzy processing the current error and error derivative, and after searching in the expert library, the current sliding mode gain is obtained after de-fuzzification processing.

[0258] S1506, using adaptive sat function, adjusting the parameters of the sat function in real time according to the system state.

[0259] S1507, VSC is unlocked.

[0260] S1508, determine whether the voltage error value is less than the set threshold value Δ2, less than K I = 0.

[0261] 4, carrier comparison function

[0262] Due to the nonlinearity of the system, in order to increase the stability and anti-interference ability of the system in the steady state process, the carrier comparison function is designed, and the number of system input sub-modules changes between n and n+1 according to the set frequency.

[0263] Referring to the contents shown in FIG. 16, the comparison process of the carrier comparison module can include: inputting the number of input modules N 1601 and the triangular wave 1602 into the carrier comparison module 1603, and the carrier comparison module 1603 obtains the number of input modules N1 (1604) through the carrier comparison function.

[0264] After ΔNdc_ref calculated by the adaptive fuzzy sliding mode controller is added to the voltage command value, the result is divided by the average capacitor voltage of the available sub-modules to obtain the reference input module number n. The carrier comparison module generates a carrier such as a triangular wave with an amplitude of 0-1 and a period of X, and compares it with the decimal part of the reference input module number n to determine whether the decimal part of the input module number is rounded or truncated. At the same time, the frequency of the final input module number N of the system changing between n and n+1 can be controlled according to the carrier period X.

[0265] Referring to the contents shown in FIG. 17, the carrier comparison function can include but is not limited to the following S1701 to S1708.

[0266] S1701, calculate ΔNdc_ref by adaptive fuzzy sliding mode control.

[0267] S1702, Ndc_ref = Uord + ΔNdc_ref.

[0268] Sum ΔNdc_ref and Uord (voltage command value) to obtain the input reference value Ndc_ref.

[0269] S1703, the reference input module number n is Ndc_ref divided by the average capacitor voltage of the available sub-modules.

[0270] Divide Ndc_ref by the average capacitor voltage of the available sub-modules to obtain the reference input module number n.

[0271] S1704, calculate the integer and decimal parts of the reference input module number n as int(N) and frac(N) respectively.

[0272] S1705, a triangular wave Wave with an amplitude of 0-1 is generated.

[0273] The amplitude of the triangular wave herein ranges from 0 to 1.

[0274] S1706, it is determined whether frac(N) is greater than |Wave|.

[0275] It is determined whether frac(N) is greater than the current amplitude |Wave| of the triangular wave.

[0276] If yes, S1707 is executed, and if no, S1708 is executed.

[0277] S1707, N = int(N) + 1.

[0278] The final number of input modules N is determined as int(N) + 1.

[0279] S1708, N = int(N).

[0280] The final number of input modules N is determined as int(N).

[0281] In a second aspect, the embodiments of the present disclosure provide an electric signal control device of an energy storage system, as shown in FIG. 18, the electric signal control device 180 of the energy storage system includes a first determination unit 1801, a second determination unit 1802, a third determination unit 1803, and a control unit 1804.

[0282] Among them:

[0283] The first determination unit 1801 is configured to determine an error of a direct current signal and a sliding surface based on an expected value and an actual value of the direct current signal output by the energy storage system.

[0284] The second determination unit 1802 is configured to determine an adjustment value of the direct current signal by performing proportional integral adjustment on the error and sliding mode adjustment on the sliding surface through a target controller.

[0285] The third determination unit 1803 is configured to determine a number of input modules N based on at least a reference direct current signal and an average electric signal of one sub-module in the energy storage system; the reference direct current signal is a sum of the adjustment value of the direct current signal and the expected value of the direct current signal; N is an integer greater than zero.

[0286] The control unit 1804 is configured to control N sub-modules in the energy storage system to be turned on through an energy storage valve control module of the energy storage system, so that the energy storage system outputs the direct current signal according to the output capacity of the N sub-modules.

[0287] In some embodiments, the second determining unit 1802 is further configured to determine a proportional gain, an integral gain, a sliding mode gain and a saturation function in the target controller; determine a proportional adjustment value as a product of the proportional gain and the error; determine an integral adjustment value as a product of the integral gain and an integral operation result of the error; determine a sliding mode adjustment value based on the sliding mode surface, the saturation function and the sliding mode gain; and determine the adjustment value of the direct current signal based on the proportional adjustment value, the integral adjustment value and the sliding mode adjustment value.

[0288] In some embodiments, the second determining unit 1802 is further configured to determine whether the error of the direct current signal is greater than a first error threshold; determine the integral gain based on the error of the direct current signal in a case where the error of the direct current signal is greater than the first error threshold; wherein the greater the absolute value of the error of the direct current signal, the closer the integral gain is to zero; the smaller the absolute value of the error of the direct current signal, the closer the integral gain is to the first integral gain; and determine the integral gain as zero in a case where the error of the direct current signal is less than or equal to the first error threshold.

[0289] In some embodiments, the second determining unit 1802 is further configured to determine an inverse proportional function and a first exponential function for integral adjustment; determine an inverse proportional adjustment value based on the absolute value of the error of the direct current signal and the inverse proportional function; wherein the greater the absolute value of the error of the direct current signal, the closer the inverse proportional adjustment value is to zero; the smaller the absolute value of the error of the direct current signal, the closer the inverse proportional adjustment value is to a first value; determine a first exponential adjustment value based on the absolute value of the error of the direct current signal and the first exponential function; wherein the greater the absolute value of the error of the direct current signal, the closer the first exponential adjustment value is to zero; the smaller the absolute value of the error of the direct current signal, the closer the first exponential adjustment value is to a second value; and obtain the integral gain by multiplying a reference integral coefficient with a sum of the inverse proportional adjustment value and the first exponential adjustment value; wherein the first integral gain is a result of multiplying the sum of the first value and the second value by the reference integral coefficient.

[0290] In some embodiments, the second determining unit 1802 is further configured to determine a second exponential function, a proportional function and a hyperbolic tangent function for sliding mode adjustment; determine a first coefficient based on a first reference parameter of the saturation function, the sliding mode surface and the exponential function; determine a second coefficient based on a second reference parameter of the saturation function, the sliding mode surface and the proportional function; determine the saturation function based on the first coefficient, the second coefficient, the sliding mode surface and the hyperbolic tangent function; wherein the greater the absolute value of the sliding mode surface, the smaller the value of the first coefficient and the greater the value of the second coefficient; the smaller the absolute value of the sliding mode surface, the greater the value of the first coefficient and the smaller the value of the second coefficient; and the value range of the saturation function is between a third value and a fourth value.

[0291] In some embodiments, the second determining unit 1802 is further configured to: determine a derivative of the error of the direct current signal based on the error of the direct current signal; perform fuzzy processing on the error and the derivative of the error to obtain a fuzzy input of the error and a fuzzy input of the derivative of the error; search the fuzzy rule base for a fuzzy output of the sliding mode gain corresponding to the fuzzy input of the error and the fuzzy input of the derivative of the error; and perform defuzzy processing on the fuzzy output of the sliding mode gain to obtain the sliding mode gain.

[0292] In some embodiments, the third determining unit 1803 is further configured to: divide the reference direct current signal by the average electric signal to obtain an integer part and a decimal part; obtain a current amplitude of the reference triangular wave; the amplitude of the reference triangular wave ranges from zero to one; in a case where the decimal part is greater than or equal to the amplitude, determine N as the integer part plus 1; and in a case where the decimal part is less than the amplitude, determine N as the integer part.

[0293] In some embodiments, the first determining unit 1801 is further configured to: determine the error of the direct current signal based on an expected value and an actual value of the direct current signal; determine the derivative of the error of the direct current signal based on the error of the direct current signal; and determine the sliding surface based on the error of the direct current signal and the derivative of the error of the direct current signal.

[0294] In some embodiments, in a case where the direct current signal is a direct current voltage, the electric signal control device 180 of the energy storage system can further include a fourth determining unit configured to determine that the energy storage system is in a constant voltage control mode.

[0295] In a case where the energy storage valve in the energy storage system is determined to be unlocked, the error of the direct current signal and the sliding surface are determined based on an expected value and an actual value of the direct current signal output by the energy storage system.

[0296] It should be noted that the apparatus provided by the embodiments of the present disclosure includes various units included therein, which can be implemented by a processor in an electronic device; of course, it can also be implemented by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU), a micro processing unit (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0297] The above apparatus embodiments are similar to the description of the above-mentioned method embodiments, and have similar beneficial effects to the method embodiments. For technical details not disclosed in the apparatus embodiments of the present disclosure, please refer to the description of the method embodiments of the present disclosure for understanding.

[0298] It should be noted that, in the embodiments of the present disclosure, if the above method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present disclosure can be embodied in the form of a software product, and the computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the embodiments of the present disclosure. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk, and various media that can store program codes. Therefore, the embodiments of the present disclosure are not limited to any specific hardware and software combination.

[0299] In a third aspect, the embodiments of the present disclosure provide an electronic device, which includes a memory and a processor, and the memory stores computer programs or instructions, and the computer programs or instructions are executed by the processor to implement the method described in the first aspect.

[0300] In an example, referring to the content shown in FIG. 19, the electronic device 190 includes a processor 1901, at least one communication bus 1902, a user interface 1903, at least one external communication interface 1904, and a memory 1905. The communication bus 1902 is configured to realize the connection and communication between the components. The user interface 1903 can include a user input receiving unit, and the external communication interface 1904 can include a standard wired interface and a wireless interface.

[0301] The memory 1905 is configured to store instructions and applications executable by the processor 1901, and can also cache data to be processed by the processor 1901 and modules in the electronic device (for example, image data, audio data, voice communication data, and video communication data) that have been processed or are being processed. The memory 1905 can be implemented by a flash memory (FLASH) or a random access memory (RAM).

[0302] In a fourth aspect, the embodiments of the present disclosure provide a storage medium, that is, a computer readable storage medium, which stores computer programs or instructions, and the computer programs or instructions are executed by a processor to implement any method provided in the first aspect in the above embodiments.

[0303] In a fifth aspect, the embodiments of the present disclosure provide a computer program product, which includes computer programs or instructions, and the computer programs or instructions are executed by a processor to implement any method provided in the first aspect in the above embodiments.

[0304] It should be noted that the above description of the embodiments of the storage medium, device, apparatus and program product is similar to the description of the above method embodiments, and has similar beneficial effects as the method embodiments. For technical details not disclosed in the embodiments of the storage medium, device, apparatus and program product of the present disclosure, please refer to the description of the method embodiments of the present disclosure for understanding.

[0305] It should be understood that the "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present disclosure. Therefore, "in one embodiment" or "in some embodiments" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that the size of the sequence number of each process in various embodiments of the present disclosure does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure. The sequence number of the above embodiments of the present disclosure is only for description, not representing the advantages and disadvantages of the embodiments.

[0306] It should be noted that in this document, the term "comprising" or "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or apparatus including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or apparatus. Without more limitations, the element defined by the statement "including a" does not exclude the presence of additional identical elements in the process, method, article or apparatus including the element.

[0307] In several embodiments provided by the present disclosure, it should be understood that the disclosed devices and methods can be implemented in other ways. The above-described device embodiments are only schematic, for example, the division of units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the various components shown or discussed can be indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or in other forms.

[0308] The units described as separate components above can or can not be physically separate, and the components shown as units can or can not be physical units; they can be located in one place or distributed on multiple network units; and part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0309] In addition, each functional unit in each embodiment of the present disclosure can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be realized in the form of hardware or in the form of hardware plus software functional units.

[0310] Those skilled in the art can understand that all or part of the steps of the above method embodiments can be completed by program instruction related hardware, and the foregoing program can be stored in a computer readable storage medium, and the program executes the steps including the above method embodiments when executed; and the foregoing storage medium includes mobile storage devices, read only memory (ROM), magnetic discs or optical discs, and various storage medium that can store program codes.

[0311] Alternatively, the integrated units of the present disclosure, if implemented in the form of software functional modules and sold or used as independent products, can also be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present disclosure can be embodied in the form of software products, which are stored in a storage medium and include several instructions for making a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the methods of the embodiments of the present disclosure. The foregoing storage medium includes mobile storage devices, ROM, magnetic discs or optical discs, and various storage medium that can store program codes.

[0312] The above is only an embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present disclosure, which should be covered within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

Claims

1. A method for controlling an electrical signal of an energy storage system, the method comprising: determining an error of a direct current electrical signal output by the energy storage system and a sliding surface based on a desired value and an actual value of the direct current electrical signal; determining an adjustment value of the direct current electrical signal by performing proportional integral adjustment on the error and sliding surface adjustment on the sliding surface through a target controller; determining a number N of modules to be turned on based on at least a reference direct current electrical signal and an average electrical signal of one sub-module in the energy storage system; wherein the reference direct current electrical signal is a sum of the adjustment value of the direct current electrical signal and the desired value of the direct current electrical signal, and the N is an integer greater than zero; and controlling N sub-modules in the energy storage system to be turned on through an energy storage valve control module of the energy storage system, so that the energy storage system outputs a direct current electrical signal according to output capabilities of the N sub-modules. The determining of the adjustment value of the direct current electrical signal by performing proportional integral adjustment on the error and sliding surface adjustment on the sliding surface through the target controller comprises: determining a proportional gain, an integral gain, a sliding gain and a saturation function in the target controller; determining a proportional adjustment value as a product of the proportional gain and the error; determining an integral adjustment value as a product of the integral gain and an integral operation result of the error; determining a sliding adjustment value based on the sliding surface, the saturation function and the sliding gain; and determining the adjustment value of the direct current electrical signal based on the proportional adjustment value, the integral adjustment value and the sliding adjustment value. The determining of the integral gain in the target controller comprises: determining whether the error of the direct current electrical signal is greater than a first error threshold; determining the integral gain based on the error of the direct current electrical signal in a case where the error of the direct current electrical signal is greater than the first error threshold; wherein the integral gain tends to be zero as the absolute value of the error of the direct current electrical signal is greater, and the integral gain tends to be a first integral gain as the absolute value of the error of the direct current electrical signal is smaller; and determining the integral gain as zero in a case where the error of the direct current electrical signal is less than or equal to the first error threshold. The determining of the integral gain based on the error of the direct current electrical signal comprises: determining an inverse function and a first exponential function for integral adjustment; determining an inverse adjustment value based on the absolute value of the error of the direct current electrical signal and the inverse function; wherein the inverse adjustment value tends to be zero as the absolute value of the error of the direct current electrical signal is greater, and the inverse adjustment value tends to be a first value as the absolute value of the error of the direct current electrical signal is smaller; determining a first exponential adjustment value based on the absolute value of the error of the direct current electrical signal and the first exponential function; wherein the first exponential adjustment value tends to be zero as the absolute value of the error of the direct current electrical signal is greater, and the first exponential adjustment value tends to be a second value as the absolute value of the error of the direct current electrical signal is smaller; and obtaining the integral gain by multiplying a reference integral coefficient with a sum of the inverse adjustment value and the first exponential adjustment value; wherein the first integral gain is a result of multiplying a sum of the first value and the second value by the reference integral coefficient. ​ ​ 2. The method of claim 1, wherein, ​ ​ ​ ​ ​ ​ 3. The method of claim 2, wherein, ​ ​ ​ ​ 4. The method of claim 3, wherein, ​ ​ ​ ​ ​ ​ 5. The method according to any one of claims 2 to 4, wherein, The determining the saturation function in the target controller comprises: determining a second exponential function, a proportional function and a hyperbolic tangent function for sliding mode regulation; determining a first coefficient based on a first reference parameter of the saturation function, the sliding surface and the exponential function; determining a second coefficient based on a second reference parameter of the saturation function, the sliding surface and the proportional function; determining the saturation function based on the first coefficient, the second coefficient, the sliding surface and the hyperbolic tangent function; wherein the greater the absolute value of the sliding surface is, the smaller the value of the first coefficient is, and the greater the value of the second coefficient is; the smaller the absolute value of the sliding surface is, the greater the value of the first coefficient is, and the smaller the value of the second coefficient is; the value range of the saturation function is between a third value and a fourth value.

6. The method according to any one of claims 2 to 5, wherein, The determining the sliding mode gain in the target controller comprises: determining a derivative of the error of the direct current signal based on the error of the direct current signal; fuzzifying the error and the derivative of the error to obtain a fuzzy input of the error and a fuzzy input of the derivative of the error; finding, in a fuzzy rule base, a fuzzy output of the sliding mode gain corresponding to the fuzzy input of the error and the fuzzy input of the derivative of the error; defuzzifying the fuzzy output of the sliding mode gain to obtain the sliding mode gain.

7. The method according to any one of claims 1 to 6, wherein, The determining the number N of input modules based on at least a reference direct current signal and an average electric signal of one sub-module in the energy storage system comprises: dividing the reference direct current signal by the average electric signal to obtain an integer part and a decimal part; obtaining a current amplitude of a reference triangular wave; the amplitude of the reference triangular wave ranges from zero to one; in a case that the decimal part is greater than or equal to the amplitude, determining that the N is the integer part plus 1; in a case that the decimal part is less than the amplitude, determining that the N is the integer part.

8. The method according to any one of claims 1 to 7, wherein, The determining the error of the direct current signal and the sliding surface based on an expected value and an actual value of a direct current signal output by the energy storage system comprises: determining the error of the direct current signal based on the expected value and the actual value of the direct current signal; determining a derivative of the error of the direct current signal based on the error of the direct current signal; determining the sliding surface based on the error of the direct current signal and the derivative of the error of the direct current signal.

9. The method according to any one of claims 1 to 8, wherein, In a case that the direct current signal is a direct current voltage, the method further comprises: determining that the energy storage system is in a constant voltage control mode; in a case that it is determined that an energy storage valve in the energy storage system is unlocked, performing the determining the error of the direct current signal and the sliding surface based on the expected value and the actual value of the direct current signal output by the energy storage system.

10. An electric signal control device of an energy storage system, the device comprising: a first determining unit configured to determine an error of a direct current signal and a sliding surface based on an expected value and an actual value of a direct current signal output by an energy storage system; a second determining unit configured to determine an adjustment value of the direct current signal by performing proportional integral regulation on the error and sliding mode regulation on the sliding surface through a target controller. The third determining unit is configured to determine the number N of the sub-modules to be turned on based on at least the reference DC signal and the average DC signal of one of the sub-modules in the energy storage system; The reference DC signal is a sum of an adjusted value of the DC signal and an expected value of the DC signal; and the N is an integer greater than zero; The control unit is configured to control the N sub-modules in the energy storage system to be turned on by the energy storage valve control module of the energy storage system, so that the energy storage system outputs the DC signal according to the output capacity of the N sub-modules.

11. The apparatus of claim 10, wherein, The second determining unit is further configured to: determine a proportional gain, an integral gain, a sliding mode gain and a saturation function in the target controller; determine a proportional adjustment value as a product of the proportional gain and the error; determine an integral adjustment value as a product of the integral gain and an integral operation result of the error; determine a sliding mode adjustment value based on the sliding mode surface, the saturation function and the sliding mode gain; determine an adjusted value of the DC signal based on the proportional adjustment value, the integral adjustment value and the sliding mode adjustment value.

12. The apparatus of claim 11, wherein, The second determining unit is further configured to: determine whether the error of the DC signal is greater than a first error threshold value; in a case where the error of the DC signal is greater than the first error threshold value, determine the integral gain based on the error of the DC signal; wherein the greater the absolute value of the error of the DC signal, the closer the integral gain is to zero; and the smaller the absolute value of the error of the DC signal, the closer the integral gain is to a first integral gain; in a case where the error of the DC signal is less than or equal to the first error threshold value, determine the integral gain as zero.

13. The apparatus of claim 12, wherein, The second determining unit is further configured to: determine an inverse proportional function and a first exponential function for integral adjustment; determine an inverse proportional adjustment value based on the absolute value of the error of the DC signal and the inverse proportional function; wherein the greater the absolute value of the error of the DC signal, the closer the inverse proportional adjustment value is to zero; and the smaller the absolute value of the error of the DC signal, the closer the inverse proportional adjustment value is to a first value; determine a first exponential adjustment value based on the absolute value of the error of the DC signal and the first exponential function; wherein the greater the absolute value of the error of the DC signal, the closer the first exponential adjustment value is to zero; and the smaller the absolute value of the error of the DC signal, the closer the first exponential adjustment value is to a second value; multiply a sum of the inverse proportional adjustment value and the first exponential adjustment value by a reference integral coefficient to obtain the integral gain; wherein the first integral gain is a result of a sum of the first value and the second value multiplied by the reference integral coefficient.

14. The apparatus of any one of claims 11 to 13, wherein, The second determining unit is further configured to: determine a second exponential function, a proportional function and a hyperbolic tangent function for sliding mode adjustment; determine a first coefficient based on a first reference parameter of the saturation function, the sliding mode surface and the exponential function; determine a second coefficient based on a second reference parameter of the saturation function, the sliding mode surface and the proportional function; determine the saturation function based on the first coefficient, the second coefficient, the sliding mode surface and the hyperbolic tangent function; and The absolute value of the sliding surface is greater, the first coefficient is smaller, and the second coefficient is greater. The absolute value of the sliding surface is smaller, the first coefficient is greater, and the second coefficient is smaller. The saturation function has a value range between a third value and a fourth value.

15. The apparatus of any one of claims 11 to 14, wherein, The second determining unit is further configured to: determine a derivative of the error of the direct current signal based on the error of the direct current signal; perform fuzzy processing on the error and the derivative of the error to obtain fuzzy input of the error and fuzzy input of the derivative of the error; find, in a fuzzy rule base, fuzzy output of a sliding mode gain corresponding to the fuzzy input of the error and the fuzzy input of the derivative of the error; perform defuzzy processing on the fuzzy output of the sliding mode gain to obtain the sliding mode gain.

16. The apparatus of any one of claims 10 to 15, wherein, The third determining unit is further configured to: divide the reference direct current signal by the average electric signal to obtain an integer part and a decimal part; obtain a current amplitude of a reference triangular wave; the amplitude of the reference triangular wave ranges from zero to one; in a case where the decimal part is greater than or equal to the amplitude, determine that the N is the integer part plus 1; in a case where the decimal part is less than the amplitude, determine that the N is the integer part.

17. The apparatus of any one of claims 10 to 16, wherein, The third determining unit is further configured to: determine the error of the direct current signal based on an expected value and an actual value of the direct current signal; determine the derivative of the error of the direct current signal based on the error of the direct current signal; determine the sliding surface based on the error of the direct current signal and the derivative of the error of the direct current signal. 18.An electronic device, comprising a memory and a processor, wherein the memory stores a computer program or instructions, and the computer program or instructions are executed by the processor to implement the method in any one of claims 1 to 9. 19.A computer readable storage medium, wherein the storage medium stores a computer program or instructions, and the computer program or instructions are executed by a processor to implement the method in any one of claims 1 to 9. 20.A computer program product, comprising a computer program or instructions, and the computer program or instructions are executed by a processor to implement the method in any one of claims 1 to 9.

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