Two-stage energy storage converter control method based on sliding mode reaching law fuzzy rule

Abstract

The invention discloses a two-stage energy storage converter control method based on a sliding mode reaching law fuzzy rule. The two-stage energy storage converter control method comprises the steps of obtaining voltage data of a direct-current bus of a two-stage energy storage converter; the difference value between the obtained voltage data and the reference voltage is used as the input of a sliding mode controller; the sliding mode control reaching law adopts a variable-rate function expression, and the speed reaching the sliding mode surface is adjusted according to different states of the system; the fuzzy controller takes an absolute value of the sliding mode surface function s as input, and obtains an approaching gain alpha and a sliding gain beta of a sliding mode approaching law through a fuzzy rule; and according to the obtained approaching gain alpha and the sliding gain beta, obtaining a control law which integrally takes sliding mode control as a main body. According to the method, the robustness of sliding mode control and the good adaptability of fuzzy control to the uncertainty and nonlinearity of the system are combined, and the high robustness to disturbance can be kept while the chattering phenomenon of sliding mode control can be effectively reduced; and the steady-state performance is improved while the dynamic response speed of the system is increased.

Description

Technical Field

[0001] The present invention belongs to the technical field of power electronic converter control, and particularly relates to a control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule, which is applicable to bidirectional flow control in scenarios such as new energy energy storage systems and microgrids. Background Technique

[0002] Energy storage technology, as an important supporting technology for promoting the transformation of the energy structure, has functions such as regulating the balance between energy supply and demand, improving the utilization efficiency of renewable energy, and enhancing the stability of the power grid. Its core component, the energy storage converter (Power Conversion System, PCS), is a key device connecting the energy storage system and the power grid, and it can achieve bidirectional energy flow, that is, the charging and discharging processes.

[0003] At present, the most mature control technology for energy storage converters used in engineering is PI control. Its principle is simple and easy to implement. Different control strategies are adopted for the two working modes of the energy storage converter. That is, constant voltage control, constant current control, and constant power (PQ) control can be used in the grid-connected mode, and constant voltage and constant frequency (VF) control, droop control, etc. can be used in the island mode. However, the traditional PI control has insufficient adaptability and robustness in dealing with grid fluctuations and load changes, and cannot well balance stability and dynamic performance. Summary of the Invention

[0004] Object of the Invention: The object of the present invention is to provide a control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule, which can improve the system response speed and control accuracy, and at the same time maintain strong robustness to uncertain disturbances, significantly improving the system dynamic quality.

[0005] Technical Solution: A control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule of the present invention includes the following steps:

[0006] Step 1: Obtain the voltage data of the DC bus of the two-stage energy storage converter;

[0007] Step 2: Take the difference between the obtained voltage data and the reference voltage as the input of the sliding mode controller;

[0008] Step 3: The sliding mode control reaching law adopts a function expression with a variable rate to adjust the speed of approaching the sliding mode surface according to different states of the system;

[0009] Step 4: The fuzzy controller takes the absolute value of the sliding mode surface function s as the input, and obtains the reaching gain α and the sliding gain β of the sliding mode reaching law through fuzzy rules;

[0010] Step 5: Obtain the overall control law with the sliding mode control as the main body according to the obtained reaching gain α and sliding gain β.

[0011] Furthermore, the two-stage energy storage converter adopts a sliding mode fuzzy combined control method.

[0012] Furthermore, step 1 is specifically as follows: according to the topological circuit diagram of the three-phase two-stage energy storage converter and Kirchhoff's law, the voltage and current equations of the energy storage converter are obtained as follows:

[0013]

[0014] In formula (1), R d is the damping resistor of the LCL filter, L1 and L2 are the two series inductors of the LCL filter, u sA 、u sB 、u sc are the voltages of the switches of the upper and lower bridge arms in the three-phase bridge circuit, u a 、u b 、u c are the three-phase voltages output by the DC / AC converter, i 1a The a-phase current flows from the output of the DC / AC converter to the LCL filter and is about to pass through the inductor L1. 1b The b-phase current flows from the output of the DC / AC converter to the LCL filter and is about to pass through the inductor L1. 1c The c-phase current flows from the output of the DC / AC converter to the LCL filter and is about to pass through the inductor L1. 2a The current flowing in the second part of the LCL filter is the a-phase current that is about to pass through the second inductor L2, i 2b The b-phase current i flows through the second inductor L2 in preparation for the LCL filter. 2c The c-phase current that flows through the second inductor L2 in the LCL filter, u ca is the voltage across capacitor C in phase a current, u cb is the voltage across capacitor C in phase b current, u cc is the voltage across capacitor C formed in the c-phase current;

[0015] The filter capacitor circuit satisfies:

[0016]

[0017] DC bus voltage u dc satisfy:

[0018]

[0019] The three-phase abc coordinate system used in the above system is transformed by matrix, and the voltage and current equations in the d, q synchronous coordinate system are obtained as follows:

[0020]

[0021] Wherein, u od and u oq respectively represent the d-axis and q-axis components of the three-phase capacitor voltage, and i od and i oq respectively represent the d-axis and q-axis components of the three-phase load current, and ω represents the angular frequency.

[0022] Furthermore, step 2 is specifically as follows: The input of the sliding mode controller is the error between the DC bus reference voltage and the actual voltage, which is represented by the following formula:

[0023] e = u dc ref - u dc ⑹

[0024] Wherein, u dc ref represents the DC bus reference voltage, and u dc represents the actual voltage.

[0025] Furthermore, step 3 is specifically as follows: The reaching law of the sliding mode controller adopts an improved variable rate reaching law, enabling the system state to approach quickly when far from the designed sliding mode surface and slow down when approaching the sliding mode surface, reducing chattering near the sliding mode surface; The general expression of the improved reaching law is shown in the following formula:

[0026]

[0027] Wherein, α is a positive constant that determines the approaching speed. A larger α value will make the system state approach the sliding mode surface faster, but will increase chattering; A smaller α value reduces chattering, but the approaching speed will slow down. δ is used to smooth the derivative of the reaching law near s = 0 to avoid the denominator being zero at s = 0.

[0028] Furthermore, step 4 is specifically as follows: The fuzzy controller adopts a second-order fuzzy controller. The inputs are the absolute value and the change rate of the sliding mode surface function s, and the outputs are the reaching gain α and the sliding gain β of the sliding mode reaching law. Five fuzzy subsets are defined, namely {ZO zero, ZS positive small, ZM positive medium, ZNB nearly positive large, ZB positive large}. The input and output of the fuzzy controller adopt Gaussian membership functions and triangular membership functions respectively. The fuzzy rules are as follows:

[0029] When the sliding mode variable |s| is large, the output gain α takes a large value, enabling the system to approach the sliding mode surface at a faster speed. At the same time, β takes a small value to avoid excessive damping of the system;

[0030] When the sliding mode variable |s| is at an intermediate value, the reaching gain α and the sliding gain β of the output should take moderate values to ensure the fast response ability of the system;

[0031] When the sliding mode variable |s| is small, the approaching gain α should be decreased to reduce the chattering phenomenon. At the same time, the sliding gain β should be increased to ensure the regulation speed of the system.

[0032] Further, step 5 is specifically as follows: Obtain the sliding mode control law u according to the variable speed rate reaching law. The control law consists of two parts: one is the term that makes the system state approach the sliding mode surface, that is, u nonlinear , and the other is the term that ensures the system state slides on the sliding mode surface after reaching the sliding mode surface, that is, u eq , and the expression is as follows:

[0033] u = u eq + u nonlinear ⑻

[0034] In the formula, the equivalent control u eq is to ensure that the system state satisfies the desired dynamic behavior when moving on the sliding mode surface. It is obtained by linearizing the system dynamics on the sliding mode surface. The equivalent control term is expressed as follows:

[0035]

[0036] In the formula, f(s, x) is the uncertainty and external disturbance of the system, and g(s, x) is the coefficient of the control input;

[0037] The non-control term u nonlinear is to ensure that the system state can reach and remain on the sliding mode surface, and contains a sign function or other non-linear elements to provide a control action to resist uncertainty and external disturbance; the non-linear control term is expressed as:

[0038]

[0039] Combining the two gives the complete control law u, as follows:

[0040]

[0041] In the formula, the former u eq ensures the stable movement of the system on the sliding mode surface, while the latter u nonlinear ensures that the system state can quickly reach and remain on the sliding mode surface.

[0042] Further, the sliding mode surface is verified for stability by constructing a Lyapunov function; it is determined whether the designed sliding mode surface can achieve the expected effect through the Lyapunov equation:

[0043]

[0044] If it conforms to then the system can be stable.

[0045] The present invention also discloses a two-stage energy storage converter system, including:

[0046] Sampling module: used to sample the voltage and current data of the two-stage energy storage converter;

[0047] Calculation module: used to obtain the d-axis and q-axis components of the voltage and current through matrix transformation of the acquired three-phase voltage and current data;

[0048] Processing module: used to input the calculated voltage and current data into a pre-optimized sliding mode fuzzy controller to control the voltage of the energy storage converter; wherein the pre-optimized sliding mode fuzzy controller is: the sliding mode controller adopts a control law based on a variable rate reaching law, and the reaching gain and sliding gain of the control law take corresponding values according to the fuzzy rules designed in the fuzzy controller.

[0049] The present invention also discloses a computer device, including a memory, a processor, and a computer program stored on the memory, and the processor executes the computer program to implement the steps of the method of the present invention.

[0050] Beneficial effects: Compared with the prior art, the present invention has the following remarkable advantages:

[0051] The present invention samples the voltage and current data of the DC bus of the energy storage converter; takes the difference between the acquired actual voltage and the reference voltage as the input of the sliding mode controller; the fuzzy controller takes the absolute value of the sliding mode surface function s as the input, and obtains the reaching gain α and sliding gain β of the sliding mode reaching law through fuzzy rules, and the speed at which the system reaches the sliding mode surface is determined by α; wherein, the sliding mode reaching law adopted above is different from the traditional first-order reaching law and exponential reaching law, and is a variable rate sliding mode control reaching law.

[0052] The present invention combines the robustness of the sliding mode control itself and the good adaptability of the fuzzy control to the uncertainty and nonlinearity of the system, can effectively reduce the chattering phenomenon of the sliding mode control while maintaining strong robustness to disturbances; improve the dynamic response speed of the system while improving the steady-state performance. With the continuous development of control technology and the wide application of some advanced control technologies in the future, it will surely become an effective way to achieve high-quality voltage control of the energy storage converter. Description of the Drawings

[0053] Figure 1 is a schematic flow chart of a control method for an energy storage converter provided by the present invention;

[0054] Figure 2 is the circuit topology diagram of the two-stage energy storage converter provided by the present invention

[0055] Figure 3It is the control structure diagram of a two - stage energy storage converter based on sliding - mode fuzzy control provided by the present invention. Specific embodiments

[0056] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0057] Embodiment 1: A control method for an energy storage converter includes:

[0058] Obtain the voltage data of the DC bus of the two - stage energy storage converter;

[0059] Take the difference between the obtained actual voltage and the reference voltage as the input of the sliding - mode controller; and then control the voltage of the energy storage converter. Among them, the structure diagram is as Figure 3 shown: The fuzzy controller takes the absolute value of the sliding - mode surface function s as the input, and obtains the approaching gain α and the sliding gain β of the sliding - mode reaching law through fuzzy rules; the speed at which the system reaches the sliding - mode surface is determined by α.

[0060] The two - stage energy storage converter adopts a control method combining sliding - mode and fuzzy control. The specific steps are as follows:

[0061] Step 1: Obtain the voltage data of the DC bus of the two - stage energy storage converter.

[0062] Figure 2 is the circuit topology structure diagram of the two - stage energy storage converter. According to the power topology diagram and Kirchhoff's law, the voltage - current equation of the energy storage converter is obtained as:

[0063]

[0064] In formula (1), R d is the damping resistance of the LCL filter, L1 and L2 are the two cascaded inductors of the LCL filter, u sA , u sB , u sc are the voltages of the switches of the upper and lower arms in the three - phase bridge circuit respectively, u a , u b , u c are the three - phase voltages output by the DC / AC converter respectively, i 1a is the a - phase current flowing from the output end of the DC / AC converter to the LCL filter and ready to pass through the inductor L1, i 1b is the b - phase current flowing from the output end of the DC / AC converter to the LCL filter and ready to pass through the inductor L1, i 1c is the c - phase current flowing from the output end of the DC / AC converter to the LCL filter and ready to pass through the inductor L1, i 2a is the current flowing in the second part of the LCL filter, which is the a - phase current ready to pass through the second inductor L2,2b Prepare the b-phase current, i, flowing through the second inductor L2 for flowing in the LCL filter 2c Prepare the c-phase current, u, flowing through the second inductor L2 for flowing in the LCL filter ca The voltage across both ends formed by the capacitor C in the a-phase current, u cb The voltage across both ends formed by the capacitor C in the b-phase current, u cc The voltage across both ends formed by the capacitor C in the c-phase current;

[0065] Among them, the filter capacitor loop satisfies:

[0066]

[0067] The DC bus voltage u dc Satisfy:

[0068]

[0069] After matrix transformation of the three-phase abc coordinate system adopted by the above system, the voltage-current equations in the d, q synchronous coordinate system are:

[0070]

[0071] In Equation (5), u od , u oq Respectively represent the d-axis and q-axis components of the three-phase capacitor voltages, i od , i oq Respectively represent the d-axis and q-axis components of the three-phase load currents, and ω represents the angular frequency.

[0072] Step 2: Design of the sliding mode controller.

[0073] Step 2.1: Use the difference between the acquired voltage data and the reference voltage as the input of the sliding mode controller.

[0074] Specifically, it is expressed by the following formula:

[0075] e = u dc ref - u dc ⑹

[0076] In Equation (6), u dc ref Represents the DC bus reference voltage, and u dc Represents the actual voltage.

[0077] Step 2.2: Obtain the improved sliding mode control reaching law.

[0078] Specifically, the general expression of the improved reaching law is shown as follows:

[0079]

[0080] In Equation (7), α is a positive constant that determines the speed of approach. A larger value of α will cause the system state to approach the sliding surface faster, but may increase chattering; a smaller value of α can reduce chattering, but the speed of approach will slow down. δ is used to smooth the derivative of the approach law near s = 0 to avoid a zero denominator at s = 0, and a relatively small positive number is usually chosen.

[0081] Step 3: Design of the fuzzy controller.

[0082] Specifically, a second-order fuzzy controller is adopted. The inputs are the absolute value and the rate of change of the sliding surface function s, and the outputs are the approach gain α and the sliding gain β of the sliding mode approach law. Five fuzzy subsets are defined, namely {ZO (zero), ZS (positive small), ZM (positive medium), ZNB (near positive large), ZB (positive large)}. Gaussian membership functions and triangular membership functions are used for the input and output of the fuzzy controller respectively. The fuzzy rules are as follows:

[0083] (1) When the sliding mode variable |s| is large, in order to improve the dynamic response of the system, the output gain α should be taken larger so that the system approaches the sliding surface at a faster speed. At the same time, β is taken as a smaller value to avoid excessive damping of the system.

[0084] (2) When the sliding mode variable |s| is at an intermediate value, the approach gain α and the sliding gain β of the output should be taken as moderate values to ensure the fast response ability of the system.

[0085] (3) When the sliding mode variable |s| is small, the approach gain α should be decreased to reduce the chattering phenomenon. At the same time, the sliding gain β should be relatively large to ensure the adjustment speed of the system.

[0086] The fuzzy rule table is as follows:

[0087] Table 1 Fuzzy rule table

[0088]

[0089] Step 4: Obtain the sliding mode control law u according to the designed variable rate approach law.

[0090] Specifically, the control law generally consists of two parts: one is the term that makes the system state approach the sliding surface, i.e., u nonlinear , and the other is the term that ensures the system state slides on the sliding surface after reaching the sliding surface, i.e., u eq , and the general expression is as follows:

[0091] u = u eq + u nonlinear ⑻

[0092] In Equation (8), the equivalent control u eqIt is to ensure that the system state satisfies the desired dynamic behavior when moving on the sliding mode surface. It is usually obtained by linearizing the system dynamics on the sliding mode surface, aiming to eliminate the system uncertainties and the influence of external factors on the system performance. The equivalent control term can be expressed as follows:

[0093]

[0094] In Equation (9), f(s, x) is the system uncertainty and external disturbance, and g(s, x) is the coefficient of the control input.

[0095] The non - control term u nonlinear is to ensure that the system state can reach and stay on the sliding mode surface. It contains a sign function or other non - linear elements to provide sufficient control action to resist uncertainties and external disturbances. The non - linear control term can be expressed as:

[0096]

[0097] Combining the two can obtain the complete control law u, as follows:

[0098]

[0099] In Equation (11), the former u eq ensures the stable movement of the system on the sliding mode surface, while the latter u nonlinear ensures that the system state can quickly reach and stay on the sliding mode surface. Combining the two, the sliding mode control law can not only handle the system uncertainties and external disturbances, but also reduce the chattering phenomenon when reaching the sliding mode surface, thus improving the performance of the control system.

[0100] Step 5: Verify the system stability.

[0101] Specifically, construct a Lyapunov function to verify the stability of the sliding mode surface. Through the Lyapunov equation, it can be determined whether the designed sliding mode surface can achieve the expected effect. The basic function expression is as follows:

[0102]

[0103] If it meets then the system can be stable.

[0104] Step 6: Verify through simulation experiments.

[0105] Specifically, after all the simulation models are built, the traditional PI control, fuzzy PI control adopted by the energy storage converter will be compared with the sliding mode fuzzy control proposed in the present invention through simulation experiments, so as to verify the improvement of the control performance of the proposed control strategy.

[0106] Embodiment 2:

[0107] This embodiment discloses a control system for an energy storage converter, including:

[0108] Sampling module: sampling the voltage and current data of the dual-stage energy storage converter;

[0109] Calculation module: obtaining the d-axis and q-axis components of the voltage and current by matrix transformation of the acquired three-phase voltage and current data.

[0110] Processing module: inputting the calculated voltage and current data into a pre-optimized sliding mode fuzzy controller to control the voltage of the energy storage converter; wherein the pre-optimized sliding mode fuzzy controller is: the sliding mode controller adopts a control law based on a variable rate reaching law, and at the same time, the reaching gain and sliding gain of the control law take corresponding values according to the fuzzy rules designed in the fuzzy controller.

[0111] The above is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and deformations can be made, and these improvements and deformations should also be regarded as the protection scope of the present invention.

Claims

1. A control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule, characterized in that It includes the following steps: Step 1: Obtain the voltage data of the DC bus of the dual-stage energy storage converter; Step 2: Use the difference between the obtained voltage data and the reference voltage as the input of the sliding mode controller; Step 3: The sliding mode control reaching law adopts a variable rate function expression to adjust the speed of approaching the sliding mode surface according to different states of the system; Step 4: The fuzzy controller takes the absolute value of the sliding mode surface function s as the input, and obtains the reaching gain α and the sliding gain β of the sliding mode reaching law through fuzzy rules; Step 5: Obtain the overall control law mainly based on sliding mode control according to the obtained reaching gain α and sliding gain β.

2. A control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule according to claim 1, characterized in that, The dual-stage energy storage converter adopts a control method combining sliding mode and fuzzy control.

3. A control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule according to claim 1, characterized in that, Specifically, Step 1 is: According to the topological circuit diagram of the three-phase dual-stage energy storage converter and Kirchhoff's law, the voltage-current equation of the energy storage converter is obtained as: In formula (1), R d is the damping resistance of the LCL filter, L1 and L2 are the two cascaded inductors of the LCL filter, u sA , u sB , u sc are the voltages of the switches of the upper and lower arms in the three-phase bridge circuit respectively, u a , u b , u c are the three-phase voltages output by the DC / AC converter respectively, i 1a is the phase-a current flowing from the output terminal of the DC / AC converter to the LCL filter and ready to pass through inductor L1, i 1b is the phase-b current flowing from the output terminal of the DC / AC converter to the LCL filter and ready to pass through inductor L1, i 1c is the phase-c current flowing from the output terminal of the DC / AC converter to the LCL filter and ready to pass through inductor L1, i 2a is the current flowing in the second part of the LCL filter, which is the phase-a current ready to pass through the second inductor L2, i 2b is the phase-b current flowing in the LCL filter and ready to pass through the second inductor L2, i 2c is the phase-c current flowing in the LCL filter and ready to pass through the second inductor L2, u ca is the voltage across both ends formed by capacitor C in the phase-a current, u cb is the voltage across both ends formed by capacitor C in the phase-b current, u cc is the voltage across both ends formed by capacitor C in the phase-c current; Among them, the filter capacitor circuit satisfies: DC bus voltage u dc Satisfy: After matrix transformation of the three-phase abc coordinate system adopted by the above system, the voltage-current equation in the d, q synchronous coordinate system is obtained as: where u od and u oq represent the d-axis and q-axis components of the three-phase capacitor voltages respectively, i od and i oq represent the d-axis and q-axis components of the three-phase load currents respectively, and ω represents the angular frequency.

4. A control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule according to claim 1, characterized in that, Specifically, Step 2 is: The input of the sliding mode controller is the error between the DC bus reference voltage and the actual voltage, which is expressed by the following formula: e = u dc ref -u dc ⑹ where u dc ref represents the DC bus reference voltage, and u dc represents the actual voltage.

5. A control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule according to claim 1, characterized in that, Specifically, Step 3 is: The sliding mode controller reaching law adopts an improved variable rate reaching law, so that the system state approaches quickly when it is far from the designed sliding mode surface, and slows down when approaching the sliding mode surface, reducing the chattering near the sliding mode surface; The general expression of the improved reaching law is shown in the following formula: In the formula, α is a positive constant, which determines the speed of approaching. A larger α value will make the system state approach the sliding mode surface faster, but will increase the chattering; A smaller α value reduces the chattering, but the approaching speed will slow down. δ is used to smooth the derivative of the reaching law near s = 0 to avoid the denominator being zero at s = 0.

6. A control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule according to claim 1, characterized in that Specifically, Step 4 is: The fuzzy controller adopts a second-order fuzzy controller, with the input being the absolute value and the rate of change of the sliding mode surface function s, and the output being the reaching gain α and the sliding gain β of the sliding mode reaching law. Define 5 fuzzy subsets, namely {ZO zero, ZS positive small, ZM positive middle, ZNB close to positive large, ZB positive large}. The input and output of the fuzzy controller adopt Gaussian membership functions and triangular membership functions respectively. The fuzzy rules are as follows: When the sliding mode variable |s| is large, the output gain α takes a large value, so that the system approaches the sliding mode surface at a faster speed. At the same time, β takes a small value to avoid excessive damping of the system; When the sliding mode variable |s| is at an intermediate value, the output reaching gain α and sliding gain β should take appropriate values to ensure the fast response ability of the system; When the sliding mode variable |s| is small, the reaching gain α should be reduced to reduce the chattering phenomenon. At the same time, the sliding gain β takes a large value to ensure the adjustment speed of the system.

7. A control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule according to claim 1, characterized in that, Step 5 is specifically as follows: Obtain the sliding mode control law u according to the variable speed rate reaching law. The control law consists of two parts: one is the term that makes the system state approach the sliding mode surface, i.e., u nonlinear , and the other is the term that ensures the system state slides on the sliding mode surface after reaching the sliding mode surface, i.e., u eq , and the expression is as follows: u = u eq + u nonlinear (8) where the equivalent control u eq ensures that the system state satisfies the desired dynamic behavior when moving on the sliding surface and is obtained by linearizing the system dynamics on the sliding surface. The equivalent control term is expressed as follows: In the formula, f(s, x) is the uncertainty and external disturbance of the system, and g(s, x) is the coefficient of the control input; Non - controlled item u nonlinear is to ensure that the system state can reach and remain on the sliding mode surface, including a sign function or other non - linear elements to provide a control action to resist uncertainties and external disturbances; the non - linear control item is expressed as: The two are combined to obtain the complete control law u, as shown below: where the former \(u\) eq ensures the stable motion of the system on the sliding surface, while the latter \(u\) nonlinear ensures that the system state can quickly reach and remain on the sliding surface.

8. A control method for a two-stage energy storage converter based on a sliding mode reaching law fuzzy rule according to claim 1, characterized in that The sliding mode surface is verified for stability by constructing a Lyapunov function; it is determined whether the designed sliding mode surface can achieve the expected effect through the Lyapunov equation: If it meets then the system can be stable.

9. A dual-stage energy storage converter system for implementing the method as described in claim 1, characterized in that, It includes: Sampling module: used to sample the voltage and current data of the dual-stage energy storage converter; Calculation module: It is used to obtain the d-axis and q-axis components of voltage and current by matrix transformation of the acquired three-phase voltage and current data; Processing module: It is used to input the calculated voltage and current data into a pre-optimized sliding mode fuzzy controller to control the voltage of the energy storage converter; the pre-optimized sliding mode fuzzy controller is: the sliding mode controller adopts a control law based on a variable rate reaching law, and at the same time, the reaching gain and sliding gain of the control law take corresponding values according to the fuzzy rules designed in the fuzzy controller.

10. A computer device, comprising a memory, a processor, and a computer program stored on the memory, characterized in that, The processor executes the computer program to implement the steps of the method described in claim 1.

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