CN114337204B - Predictive control specified harmonic suppression switching strategy with low switching frequency characteristics - Google Patents
Predictive control specified harmonic suppression switching strategy with low switching frequency characteristics Download PDFInfo
- Publication number
- CN114337204B CN114337204B CN202111461583.4A CN202111461583A CN114337204B CN 114337204 B CN114337204 B CN 114337204B CN 202111461583 A CN202111461583 A CN 202111461583A CN 114337204 B CN114337204 B CN 114337204B
- Authority
- CN
- China
- Prior art keywords
- harmonic
- state
- signal
- time
- switching
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000001629 suppression Effects 0.000 title claims abstract description 19
- 238000000034 method Methods 0.000 claims abstract description 41
- 238000005070 sampling Methods 0.000 claims abstract description 38
- 238000004364 calculation method Methods 0.000 claims abstract description 37
- 230000008569 process Effects 0.000 claims abstract description 19
- 230000006870 function Effects 0.000 claims description 38
- 230000000694 effects Effects 0.000 claims description 10
- 238000000605 extraction Methods 0.000 claims description 10
- 238000001228 spectrum Methods 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 5
- 230000001960 triggered effect Effects 0.000 claims description 4
- 230000003247 decreasing effect Effects 0.000 claims description 3
- 230000005484 gravity Effects 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 2
- 238000004458 analytical method Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
- 230000001276 controlling effect Effects 0.000 description 5
- 238000012360 testing method Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 238000010248 power generation Methods 0.000 description 3
- 239000000523 sample Substances 0.000 description 3
- 238000011217 control strategy Methods 0.000 description 2
- 230000007423 decrease Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 238000007792 addition Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000003749 cleanliness Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 238000007667 floating Methods 0.000 description 1
- 238000013139 quantization Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 230000007306 turnover Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Landscapes
- Inverter Devices (AREA)
Abstract
The invention discloses a predictive control appointed harmonic suppression switching strategy with low switching frequency characteristics, which comprises the steps of obtaining a system predictive model so as to predict the state of a controlled object at a future moment; extracting the base wave and each subharmonic amplitude of the controlled object at the future moment; calculating a cost function, and selecting a switch state which minimizes the cost function to feed back to a control system; at the next sampling moment, the process is circulated to obtain the switching state of the complete period, so that the suppression requirement of the control system on the designated subharmonic is met; the predictive control algorithm provided by the invention can effectively inhibit even harmonic waves, and the switching frequency of the system can be reduced to 700Hz at the lowest while ensuring that low harmonic waves are effectively inhibited; compared with the on-line calculation, the method has better real-time performance and can effectively reduce the burden of hardware resources.
Description
Technical Field
The invention relates to the field of inverter control, in particular to a predictive control specified harmonic suppression switching strategy with low switching frequency characteristics.
Background
In recent years, a distributed power generation system based on renewable energy sources such as wind energy and solar energy is becoming a research hotspot because of its advantages such as cleanliness, economy, sustainable development and the like. The micro-grid is used as a small power generation and distribution system which organically integrates a distributed power supply device, an energy storage system and various load devices, and can fully utilize distributed renewable energy sources and better exert the power generation potential of the renewable energy sources. The micro-grid can run off the island of the large grid, wherein the inverter is an important interface between the island micro-grid and the independent load, and the control of the grid-side voltage of the micro-source in the island micro-grid is realized mainly by controlling the inverter. In an island-type microgrid, the inverter supplies the load with the required electrical energy. Since no external power grid is supported, the nonlinear load on the inverter and load side can cause a large number of harmonics to appear in the output voltage waveform, thereby generating serious distortion. This can have a serious impact on the voltage quality of the island micro-grid, and cannot meet the requirements of users with higher requirements on the power quality. An inverter with an L-type or LCL-type filter can be selected to filter out harmonics, however, the lower harmonics (usually 5 th 、7 th Etc.) are difficult to filter out. And the larger the lower harmonic content of the output waveform of the inverter is, the larger the switching loss is correspondingly, so that the inversion efficiency is reduced. Therefore, the research on the optimal control of the inverter is a key technology for improving the output power quality of the power system during off-grid operation.
In order to reduce the harmonic distortion content, an appropriate control strategy is selected to control the inverter. Common control strategies, such as carrier-based Pulse Width Modulation (PWM) and conventional space voltage vector modulation (SVPWM) asynchronous pulse width modulation methods, have relatively good load harmonic performance. In order to reduce the switching losses of an inverter and to increase its output efficiency, it is often necessary to operate it at a low switching frequency. However, as the switching frequency decreases, harmonics in waveforms output by the two modulation methods are continuously increased, which may cause the power system to fail to operate normally.
The appointed harmonic elimination PWM strategy (selective harmonic elimination-PWM, SHE-PWM) can effectively inhibit the harmonic wave of the output waveform of the inverter while reducing the switching frequency, and compared with carrier modulation, the output efficiency of the inverter is effectively improved. At present, the SHEPWM technology generally performs Fourier analysis on voltage waveforms, solves switching angles corresponding to different modulation ratios m, stores a switching mode and the switching angles obtained by offline solving in a memory space of a controller, and inquires about the corresponding switching angles according to switching times N and the modulation ratios m. Although the method can eliminate the designated subharmonic to a certain extent, the calculation of the switch angle needs to solve the overrun equation and is completed under the off-line condition, the solving process is complex, the algorithm instantaneity is poor, and the dynamic response is not high.
Disclosure of Invention
The invention aims to overcome the defects of poor algorithm instantaneity and low dynamic performance in a SHEPWM (synchronous digital hierarchy) modulation strategy, and provides a specified harmonic suppression switching strategy based on a predictive control method, so that an inverter can be operated at a low switching frequency, and meanwhile, the suppression of harmonic waves is realized, and the dynamic performance of a control system is improved.
For this purpose, the technical scheme provided by the invention is as follows: a predictive control-specified harmonic rejection switching strategy with low switching frequency characteristics, consisting essentially of the following process:
(1) Acquiring a system prediction model so as to predict the state of a controlled object at a future moment;
(2) Extracting the base wave and each subharmonic amplitude of the controlled object at the future moment;
(3) Calculating a cost function, and selecting a switch state which minimizes the cost function to feed back to a control system;
(4) And at the next sampling moment, the process is circulated to obtain the switching state of the complete period, so that the suppression requirement of the control system on the designated subharmonic is realized.
Preferably, the obtaining of the system prediction model mainly comprises the following steps:
1-1) extracting each subharmonic signal is needed to be carried out in a sampling window of at least one fundamental wave period, initializing the input of the first N sampling points by a system, and setting flag_init as an identification signal for judging whether the system enters the initialization;
1-2) when flag_init=1, the system performs initialization processing;
1-3) when flag_init+.1, the system prediction model is acquired so as to predict the state of the controlled object at the future time.
Preferably, the harmonic extraction mainly comprises the following steps:
2-1) sampling the harmonic voltage signal at each moment by the signalObtaining a unit harmonic amplitude component in the form of formula (1);
in the above formula, x n is a discrete time signal; x k is discrete frequency domain signal, k value is expressed as multiple of fundamental frequency, i.e. harmonic frequency; n is the number of sampling points in the fundamental wave period; n is the number of sampling points of c;
2-2) sliding window discrete fourier transform is performed on equation (1): calculating X [ k ] at time t]| t At the next sampling instant t+T s Only X [ k ] is required]| t The earliest time domain signal sampling point x [ T- (N-1) T in the calculation result s ]Remove and add the latest sampling point x [ t+T ] s ]Finally, multiplying by a shift factor to obtain a value at t+T s Calculation of time of daySolving the frequency spectrum of the time domain signal is realized;
preferably, the calculating the cost function specifically includes the steps of:
3-1) each phase voltage signal u * (A, B, C) the states at future time are two, denoted as u ad1 (u * ) And u ad2 (u * ) Sampling the harmonic voltage signal at each moment by the signalObtaining unit harmonic amplitude components in the form of formula (1) and respectively converting states u ad1 (u * ) Store to memory m h1 In the state u ad2 (u * ) Store to memory m h2 And stores the frequency domain calculation result of one fundamental wave period into a memory M h In (a) and (b);
by signalObtaining unit harmonic amplitude components in the form of formula (1) and respectively converting states u ad1 (u * ) Store to memory m f1 In the state u ad2 (u * ) Store to memory m f2 And stores the frequency domain calculation result of one fundamental wave period into a memory M f In (a) and (b);
3-2) for each phase of the voltage signal of the control target, the state of the harmonic amplitude component calculated each time according to the future time of the voltage signal is u ad1 (u * ) Or u ad2 (u * ) According to this, the state result is stored in m h1 Or m is h2 Judging which data set value is triggered and selected at the moment according to the predicting result of the last moment;
3-3) the individual subharmonic components are then extracted for the complete data points for each fundamental period by sliding window discrete Fourier transform and stored in data set M h In (a) and (b);
3-4) sending the extracted harmonic component into a cost function for calculation, and selecting the most suitable voltage signal to obtain the expected output voltage waveform of the inverter;
3-5) determining the cost function according to the following control objective: (1) the low harmonic distortion is controlled, so that the damage to a power system is avoided; (2) switching loss is reduced, and the load of inverter equipment is lightened; (3) the dynamic performance of the system is improved;
thus, according to the above objective, the cost function is determined as:
in U * [1]The middle is the fundamental wave amplitude of the reference voltage signal; u (U) P [1]Predicting the fundamental amplitude of the voltage signal; u (U) P [k]Predicting the amplitude of each subharmonic of the voltage signal; g 1 、g k The weight coefficient of each item; n is n sw Representing a predicted switching number when the current output voltage signal becomes the predicted voltage; g c Is a weight coefficient for controlling the switching frequency.
Preferably, after the amplitude of each subharmonic is extracted according to the formula (2), the corresponding weight coefficient g can be adjusted according to the requirement of the control system k To achieve suppression of the specified subharmonics.
Preferably, n is according to formula (2) sw Then the number of predicted switch times when the current output voltage signal is changed to the predicted voltage is represented by adjusting the weight coefficient g c Increasing or decreasing the value of g in the cost function F c n sw The specific gravity of the control circuit is used for forcing the switching state at the next moment to be consistent with the current state or to be switched, so as to achieve the effect of controlling the switching frequency.
Preferably, according to formula (2), the calculation of the respective state cost functions of the controlled object at the future time is performed: if the switch state u is at this time ad1 (u * ) Is effective, then the weighted sum at this time will be stored in F 1 Among them; if it is effective at this time, u ad2 (u * ) Will be stored in F 2 Among them;
after the cost function for all future time states has been calculated, the pass ratioCompared with the stored value F 1 、F 2 Selecting a switching state which minimizes a cost function, generating a spot signal and feeding back the spot signal to mf in harmonic extraction s 、m hs A memory; at the same time, the feedback of the spot signal will be from the corresponding memory m fs 、m hs Extracting the selected state as u ad1 (u * ) Or u ad2 (u * ) And replace the harmonic amplitude component stored in M f 、M h Harmonic amplitude components of the last position switch state; at the same time, memory M f 、M h The harmonic amplitude component of the first position switch state is deleted and the u calculated at the current moment is loaded ad1 (u * )、u ad2 (u * ) And (5) switching state results.
After the scheme is adopted, the invention has the following advantages: (1) The predictive control algorithm provided by the invention can effectively inhibit even harmonic wave which is basically eliminated, 5 th Harmonic duty ratio of 0.529%,7 th The harmonic ratio is 0.195%; and the switching frequency of the system can be reduced to 700Hz at the lowest while ensuring that the low harmonics are effectively suppressed.
(2) The invention can achieve the same effect as the SHEPEM strategy, and effectively inhibit the harmonic wave of the output waveform of the inverter while reducing the switching frequency; compared with the on-line calculation, the method has better real-time performance and can effectively reduce the burden of hardware resources.
(3) The predictive control with low switching frequency characteristic designates a harmonic suppression switching strategy, reduces the low-order harmonic content of an output voltage signal, effectively suppresses harmonic distortion and realizes adjustable control of switching frequency.
(4) The harmonic extraction algorithm is an important key for realizing the method, and when the traditional DFT algorithm is adopted for carrying out harmonic extraction, the calculated amount of the algorithm is large, and the practical application effect is poor.
(5) By applying the technical scheme of the invention, the three-phase converter can work under severe operation conditions with serious voltage distortion, so that the voltage quality of the island micro-grid is obviously improved; and the cost of the filter is reduced, and meanwhile, the harmonic suppression effect is better.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and that other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of an algorithm implementation of the discrete fourier transform in the present invention.
Fig. 2 is a schematic diagram of a sliding window discrete fourier transform process in accordance with the present invention.
Fig. 3 is a diagram of a sliding window discrete fourier transform basic form signal flow in the present invention.
Fig. 4 is a diagram of a harmonic extraction signal flow of a controlled object in the present invention.
Fig. 5 is a flow chart (single phase) of an algorithm in the present invention.
Fig. 6 is a graph of the algorithm signal flow (single phase) in the present invention.
FIG. 7 is a graph of the time-consuming results of the discrete Fourier transform algorithm calculation of the present invention.
FIG. 8 is a graph of the time-consuming results of the sliding window discrete Fourier transform algorithm calculation of the present invention.
FIG. 9 is a graph showing the results of the predictive control algorithm performance analysis in the present invention.
FIG. 10 is a graph of the results of an analysis of the performance of the predictive control algorithm after adjustment in the present invention.
FIG. 11 is a graph showing the results of SHEPWM modulation strategy performance analysis in accordance with the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Examples
The invention relates to a predictive control appointed harmonic suppression switching strategy with low switching frequency characteristics, which mainly comprises the following steps:
(1) Acquiring a system prediction model so as to predict the state of a controlled object at a future moment;
(2) Extracting the base wave and each subharmonic amplitude of the controlled object at the future moment;
(3) Calculating a cost function, and selecting a switch state which minimizes the cost function to feed back to a control system;
(4) And at the next sampling moment, the process is circulated to obtain the switching state of the complete period, so that the suppression requirement of the control system on the designated subharmonic is realized.
For the harmonic extraction method, in digital systems, only discrete signals of finite length can be processed, so that a continuous time signal X (t) and its discrete time fourier transform X (e jw ) A discretization process, namely Discrete Fourier Transform (DFT), is performed, and the transform formula is:
in the above formula, x n is a discrete time signal; x k is discrete frequency domain signal, k value is expressed as multiple of fundamental frequency, i.e. harmonic frequency; n is the number of sampling points in the fundamental wave period; n is the number of sampling points of c;
the Euler expansion of the formula (1) can be obtained:
from equation (2), the real part of the frequency domain in the discrete fourier transform is:
the imaginary part is:
in summary, the discrete fourier transform is used to determine the magnitude of the harmonic wave included in the signal by using the correlation between the time domain signal and the sine function, so that the discrete fourier transform is commonly used in an electric power system to extract the harmonic wave of the voltage waveform. However, when this method is applied to an engineering requiring high real-time performance such as a power system, it is not desirable to extract the amplitude of each harmonic by discrete fourier transform.
As shown in fig. 1, at t (i-1) Time of day includes t (i-N) To t (i-1) The N sampling points are subjected to accumulation calculation as shown in formulas (3) and (4) when discrete Fourier transform analysis is carried out, and finally, the amplitude of each subharmonic is calculated according to the obtained values of the real part and the imaginary part; at t (i) At the moment, the same principle needs to be applied to t i-(N-1) To t (i-1) The N sampling points at the moment are calculated and accumulated. The middle box in fig. 1 performs N-1 repeated calculations at two adjacent sampling moments, which consumes a lot of time. The quantization of the time domain signal can be known that N is needed when discrete Fourier transform is carried out on the time domain signal sampling points 2 Complex multiplication and N (N-1) complex additions. It can be seen that as the sampling points are increased, the calculation amount of the algorithm is increased, and the actual application effect is poorer.
However, FIG. 1 shows a schematic diagram of a discrete Fourier transform calculation process, and it can be seen that from t (i-1) To t (i) At the moment, a large part of the sample sequence of these two moments is coincident, only the new incoming sample point t (i) Extruded sampling point t (i-N) Different, this indicates that the adjacent time calculatedThe frequency domain components are linked;
assume that at time t, the corresponding N-point sequence is: x [ T- (N-1) T s ]、x[t-(N-2)T s ]……x[t-T s ]、x[t]The method comprises the steps of carrying out a first treatment on the surface of the Next sampling time, t+T s At the moment, the corresponding N point sequence is: x [ T- (N-2) T s ]、x[t-(N-3)T s ]……x[t]、x[t+T s ]；
Therefore, at time t:
at t+T s The time is:
comparing equation (5) with equation (6) yields:
in the above formula, x [ T- (N-1) T ] s ]Representing the earliest time domain signal sampling point in the fundamental wave period in the previous sampling time; x [ t+T ] s ]A sampling point representing the current time;
the specific implementation process is shown in figure 2, namely t+T s Time of day calculationOnly the calculation result X [ k ] of the last time t is needed]| t The earliest time domain signal sampling point x [ T- (N-1) T ] is removed s ]Add the latest sampling point x [ t+T ] s ]And multiplying the shift factor to solve the time signal spectrum.
Meanwhile, equation (7) may be euler-expanded and converted into a trigonometric function form, as shown in fig. 3.
For establishing cost function, state acquisition of controlled object at future timeThen, the amplitude of fundamental wave and each subharmonic contained in the voltage signal can be extracted according to the method, and the signal flow diagram is shown in figure 4; in FIG. 4, two levels are taken as an example, and each phase of voltage signal u * (A, B, C) the states at future time are two, denoted as u ad1 (u * ) And u ad2 (u * ) By signalObtaining unit harmonic amplitude components in the form of formula (1) and respectively converting states u ad1 (u * ) Stored to data set m h1 In the state u ad2 (u * ) Stored to data set mh 2 In (a) and (b);
taking phase a as an example (the other two phases can be obtained by phase shifting): for each phase of voltage signal of the control target, the harmonic amplitude component calculated each time is u according to the state of the future moment of the voltage signal ad1 (u * ) Or u ad2 (u * ) According to this, the state result is stored in m h1 Or m is h2 Judging which data set value is triggered and selected at the moment according to the predicting result of the last moment; the subharmonic components are then extracted for the complete data points for each fundamental period by sliding window discrete Fourier transform and stored in data set M h In (a) and (b); finally, the extracted harmonic component is sent into a cost function for calculation, and the most proper voltage signal is selected to obtain the expected output voltage waveform of the inverter;
wherein establishment of a cost function is particularly important, the present application determines the cost function according to the following control objectives: (1) the low harmonic distortion is controlled, so that the damage to a power system is avoided; (2) switching loss is reduced, and the load of inverter equipment is lightened; (3) the dynamic performance of the system is improved;
thus, according to the above objective, the cost function is determined as:
in U * [1]The middle is the fundamental wave amplitude of the reference voltage signal; u (U) P [1]Predicting the fundamental amplitude of the voltage signal; u (U) P [k]Predicting the amplitude of each subharmonic of the voltage signal; g 1 、g k The weight coefficient of each item; n is n sw Representing a predicted switching number when the current output voltage signal becomes the predicted voltage; g c Is a weight coefficient for controlling the switching frequency.
As can be seen from the above, with reference to fig. 5 and fig. 6, taking two levels as an example, the implementation of the prediction algorithm of the present invention mainly includes the following steps:
(1) Extracting each subharmonic signal is needed to be carried out in a sampling window of at least one fundamental wave period, the system initializes the input of the first N sampling points, and sets a flag_init as an identification signal for judging whether the system enters initialization;
(2) When flag_init=1, the system performs initialization processing;
(3) When flag_init is not equal to 1, a system prediction model is acquired so as to predict the state of the controlled object at a future time.
(4) Sequentially extracting the amplitude of each subharmonic of the controlled object in future time, and recording the signal asBy signal->Obtaining a unit harmonic amplitude component in the form of formula (1), and storing the frequency domain calculation result of one fundamental wave period in a memory M h In (a) and (b);
by signalObtaining unit harmonic amplitude components in the form of formula (1) and respectively converting states u ad1 (u * ) Store to memory m f1 In the state u ad2 (u * ) Store to memory m f2 And storing the frequency domain calculation result of one fundamental wave period in a memoryM f In (a) and (b);
(5) Taking phase a as an example at this time: the state of the harmonic amplitude component calculated each time according to the future time of the voltage signal is u ad1 (u * ) Or u ad2 (u * ) According to this, the state result is stored in m h 1 or m h2 Judging which data set value is triggered and selected at the moment according to the predicting result of the last moment;
(6) The subharmonic components are then extracted for the complete data points for each fundamental period by sliding window discrete Fourier transform and stored in data set M h In (a) and (b);
(7) The cost function is determined according to the following control objectives: (1) the low harmonic distortion is controlled, so that the damage to a power system is avoided; (2) switching loss is reduced, and the load of inverter equipment is lightened; (3) the dynamic performance of the system is improved;
thus, according to the above objective, the cost function is determined as formula (8);
(8) Finally, calculating the cost function of each state of the controlled object at the future moment: if the switch state u is at this time ad1 (u * ) Is effective, then the weighted sum at this time will be stored in F 1 Among them; if it is effective at this time, u ad2 (u * ) Will be stored in F 2 Among them;
referring to FIG. 6, for state u ad1 (u * ) State u ad2 (u * ) There are two choices for the switch Se, se=1 is state u ad1 (u * ) Se=2 is state u ad2 (u * ) When s=s e At this time, the cost function of all future time states has been calculated by comparing the stored value F 1 、F 2 Selecting a switching state which minimizes a cost function, generating a spot signal and feeding the spot signal back to m in harmonic extraction fs 、m hs A memory; at the same time, the feedback of the spot signal will be from the corresponding memory m fs 、m hs Extracting the selected state as u ad1 (u * ) Or u ad2 (u * ) And replace the harmonic amplitude component stored in M f 、M h Last in (3)A harmonic amplitude component of the position switch state; at the same time, memory M f 、M h The harmonic amplitude component of the first position switch state is deleted and the u calculated at the current moment is loaded ad1 (u * )、u ad2 (u * ) And (5) switching state results.
(9) The core of the predictive control algorithm is that the fundamental wave of the state of the controlled object at the future moment and the amplitude of each subharmonic are extracted in sequence, and a sliding window discrete Fourier transform algorithm is mainly applied; wherein the fundamental wave amplitude is extracted and is matched with the reference fundamental wave amplitude ref_u 1 Comparing; in order for the voltage signal to better follow the reference signal at the next time, it can be forced to follow the reference signal by adjusting its weight coefficients to obtain the ideal waveform.
(10) According to the cost function, after the amplitude of each subharmonic is extracted, the corresponding weight coefficient g can be adjusted according to the requirement of a control system k To achieve suppression of the specified subharmonics.
(11) According to the cost function, n sw Then the number of predicted switch times when the current output voltage signal is changed to the predicted voltage is represented by adjusting the weight coefficient g c Increasing or decreasing the value of g in the cost function F c n sw The specific gravity of the control circuit is used for forcing the switching state at the next moment to be consistent with the current state or to be switched, so as to achieve the effect of controlling the switching frequency.
1. Experimental testing and verification
1.1, predictive control of harmonic extraction algorithm time consuming
And (3) experimental comparison analysis is carried out on the time taken by extracting each subharmonic by using discrete Fourier transform and sliding window discrete Fourier transform in the algorithm implementation process, wherein an experimental platform controller uses a TMS320F28379D high-performance real-time controller produced by Texas instruments, and the actual time consumption of each part of the algorithm is mainly checked through the turnover of a GPIO port of a DSP chip. After the real part and the imaginary part of the frequency domain value are solved, the two methods are consistent in mathematical solving operation of the amplitude spectrum and are equal in time consumption, so that the method is not described herein.
Fig. 7 shows the calculation time of the discrete fourier transform algorithm, which shows the calculation time of the equation (2) and the equation (3) in the process of solving the frequency domain value from the time domain value, and it can be seen that the calculation time of the process is Δt= 864.748 μs.
Fig. 8 is a diagram showing the calculation time consumption of the sliding window discrete fourier transform algorithm, where fig. 8 (a) shows the calculation time consumption of the time domain signal at the current time in the process of calculating the real part and the imaginary part of the frequency domain value according to the formula (3) and the formula (4), and the time taken in the process is: Δt=1.59 μs;
fig. 8 (b) shows that the time consumed for calculating the real part and the imaginary part of the frequency domain value of the time domain signal at the current moment in one fundamental period is calculated, and the time consumed for the calculation of the real part and the imaginary part is: Δt=2.27 μs.
Through the experimental demonstration, when the sliding window discrete Fourier transform is adopted in the predictive control algorithm to extract the harmonic wave, the calculation time is shorter, the calculation time is reduced by 86088 mu s, and the complexity of signal processing is effectively reduced. Therefore, the method extracts fundamental waves and all subharmonics in predictive control, so that the method has better real-time online computing capacity and improves the computing efficiency.
1.2, predictive control Algorithm Performance analysis
In order to verify the control effect of a predictive control algorithm on low-order harmonics, a TMS320F28379D is adopted as a main controller, and experiments are carried out on the method; the voltage is obtained by using a high-voltage probe, and observation and record are carried out through an oscilloscope;
the result of the performance analysis of the predictive control algorithm is shown in FIG. 9, where FIG. 9 (a) is the voltage U between the inverter A and the negative terminal of the power supply ao The method comprises the steps of carrying out a first treatment on the surface of the FIG. 9 (b) shows the corresponding spectrum, 5 th Harmonic duty ratio of 0.729%,7 th The harmonic ratio is 0.236%, the ratio of each subharmonic is shown in Table 2, 5 th 、7 th The harmonic wave and even harmonic wave basically meet the requirements of national standard GB/T14549; FIG. 9 (c) is a graph showing the average switching frequency change at this time, the value of which is in a greatly fluctuating state before one fundamental period (20 ms), and which is floating in a small range by 60ms due to the need to predict the future voltage signal state, and which gradually stabilizes to 1000 after 60msHz。
However, in order to meet the requirement of the island micro-grid on field power supply, the harmonic voltage generated by the test network end of the island micro-grid should meet 5 according to international standards of limitation of household and low-voltage appliances with electronic devices on power supply network interference th The maximum harmonic voltage content of the harmonic wave is not higher than 0.65%, 7% th The harmonic maximum harmonic voltage content should be not higher than 0.6%, and the even harmonic maximum harmonic voltage content should be not higher than 0.2%. Therefore, the selection result is shown in table 1 by adjusting and setting the selection value of the weight coefficient in the expression (10).
TABLE 1 selection of weight coefficients
Comparing fig. 9 (a), the number of voltage state switching times in one fundamental wave period (20 ms) is 20; after the weight coefficient is adjusted, the inverter outputs the voltage U ao The waveform is shown in fig. 10 (a), the number of switching times is 14, and it can be seen that the adjustment of the weight makes the voltage state switching significantly smaller. The situation occurs just because the n of the predicted switching times in the cost function is up-regulated sw The weight coefficient makes the algorithm more prone to maintaining the current switching state, thereby causing the switching frequency to decrease. At this time, the average switching frequency change curve is shown in fig. 10 (c) and a more proper switching state is selected between 20ms and 60ms, so that a part of time fluctuation occurs and the average switching frequency change curve is stabilized at 700Hz after 60 ms. At the same time, the weight ratio of each subharmonic is changed, and the frequency spectrum corresponding to the voltage waveform is shown as fig. 10 (b), 5 th Harmonic duty ratio of 0.529%,7 th The harmonic ratio is 0.195%, and the ratio of each subharmonic is shown in Table 2, which shows that at this time 5 th 、7 th Harmonics are substantially reduced and even harmonics are substantially eliminated.
When the SHEPWM modulation strategy processes the 5th and 7th harmonics, the number of switching angles n=3 in the first 1/4 period, and the waveform of the inverter output voltage Uao is shown in fig. 11 (a). The switching frequency of the voltage state in one fundamental wave period (20 ms) is 14 times, namely the switching frequency is 700Hz; meanwhile, the frequency spectrum corresponding to the voltage waveform is shown in fig. 11 (b), the 5th harmonic wave duty ratio is 0.119%, the 7th harmonic wave duty ratio is 0.0955, and the duty ratio of each subharmonic wave is shown in table 2.
TABLE 2 duty cycle of harmonic components (%)
Comparing the SHEPWM modulation strategy and the experimental performance results of the provided predictive control algorithm, the provided predictive control method can achieve the same effect as the SHEPWM, namely, effectively inhibit the harmonic wave of the output waveform of the inverter while reducing the switching frequency, so that the output efficiency of the inverter is effectively improved. However, for SHEPWM, the overrun equation needs to be solved in advance under the offline condition, and the obtained switching angle is stored in the storage space of the DSP so as to perform the table look-up operation. However, the solving process is complex, the algorithm real-time performance is poor, and the table look-up operation occupies a large amount of memory resources. The prediction control harmonic suppression method can realize online operation, has better real-time performance, can save the occupied space of a memory and lighten the resource burden of a DSP chip.
2. Conclusion(s)
Nonlinear loads on the inverter and load sides can cause serious distortion due to the occurrence of a large number of harmonics in the output voltage waveform, which can have serious influence on the voltage quality of the island-type micro-grid. A predictive control specified harmonic rejection switching strategy with low switching frequency characteristics is presented herein for the above-described problems. The main work has the following points:
1) The complexity of the discrete Fourier transform algorithm and the sliding window discrete Fourier transform algorithm is compared and studied when the complexity of each subharmonic is extracted, and compared with the former algorithm, the complexity is O (N 2 ) The latter is only O (N), and the calculation amount of signal processing is greatly reduced. Experiments prove that the calculation consumption of the sliding window discrete Fourier transform algorithm is reduced by 860.88 mu s compared with the sliding window discrete Fourier transform algorithm, the calculation efficiency is greatly improved, and the sliding window discrete Fourier transform algorithm has higher real-time performance.
2) A low switching frequency is proposedThe predictive control of the characteristics designates a harmonic suppression switching strategy, considers future behavior characteristics of a controlled object, tracks fundamental waves, suppresses harmonic waves, selects the optimal switching state at the next moment to obtain a required control effect, and through experimental tests, the provided predictive control algorithm effectively suppresses low-order harmonic energy, wherein even-order harmonic waves are basically eliminated, 5 th Harmonic duty ratio of 0.529%,7 th The harmonic ratio was 0.195%.
3) The experimental test is carried out on the method for suppressing the model predictive control harmonic wave, which can effectively reduce the switching frequency, and the switching frequency of the system can be reduced to 700Hz at the lowest while ensuring that the lower harmonic wave is effectively suppressed.
4) Compared with a SHEPWM modulation strategy, the model predictive control harmonic suppression method can achieve the same effect as the SHEPM strategy, and can effectively suppress the harmonic wave of the output waveform of the inverter while reducing the switching frequency; compared with the on-line calculation, the method has better real-time performance and can effectively reduce the burden of hardware resources.
The invention and its embodiments have been described above with no limitation, and the actual construction is not limited to the embodiments of the invention as shown in the drawings. In summary, if one of ordinary skill in the art is informed by this disclosure, a structural manner and an embodiment similar to the technical solution should not be creatively devised without departing from the gist of the present invention.
Claims (1)
1. A predictive control specified harmonic rejection switching strategy with low switching frequency characteristics, characterized by essentially comprising the following procedures:
(1) Acquiring a system prediction model so as to predict the state of a controlled object at a future moment;
(2) Extracting the base wave and each subharmonic amplitude of the controlled object at the future moment;
(3) Calculating a cost function, and selecting a switch state which minimizes the cost function to feed back to a control system;
(4) At the next sampling moment, the process is circulated to obtain the switching state of the complete period, so that the suppression requirement of the control system on the designated subharmonic is met;
in the process (1), the acquisition of the system prediction model mainly comprises the following steps:
1-1) extracting each subharmonic signal is needed to be carried out in a sampling window of at least one fundamental wave period, initializing the input of the first N sampling points by a system, and setting flag_init as an identification signal for judging whether the system enters the initialization;
1-2) when flag_init=1, the system performs initialization processing;
1-3) when flag_init is not equal to 1, acquiring a system prediction model so as to predict the state of the controlled object at the future moment; the harmonic extraction in the process (2) mainly comprises the following steps:
2-1) sampling the harmonic voltage signal at each moment by the signalObtaining a unit harmonic amplitude component in the form of formula (1);
in the above formula, x n is a discrete time signal; x k is discrete frequency domain signal, k value is expressed as multiple of fundamental frequency, i.e. harmonic frequency; n is the number of sampling points in the fundamental wave period; n is the number of sampling points;
2-2) sliding window discrete fourier transform is performed on equation (1): calculating X [ k ] at time t]| t At the next sampling instant t+T s Only X [ k ] is required]| t The earliest time domain signal sampling point x [ T- (N-1) T in the calculation result s ]Remove and add the latest sampling point x [ t+T ] s ]Finally, multiplying by a shift factor to obtain a value at t+T s Calculation of time of dayRealizing the frequency spectrum of the time domain signalSolving;
the calculating the cost function specifically comprises the following steps:
3-1) each phase voltage signal u * (A, B, C) the states at future time are two, denoted as u ad1 (u * ) And u ad2 (u * ) Sampling the harmonic voltage signal at each moment by the signalObtaining unit harmonic amplitude components in the form of formula (1) and respectively converting states u ad1 (u * ) Store to memory m h1 In the state u ad2 (u * ) Store to memory m h2 And stores the frequency domain calculation result of one fundamental wave period into a memory M h In (a) and (b);
by signalObtaining unit harmonic amplitude components in the form of formula (1) and respectively converting states u ad1 (u * ) Store to memory m f1 In the state u ad2 (u * ) Store to memory m f2 And stores the frequency domain calculation result of one fundamental wave period into a memory M f In (a) and (b);
3-2) for each phase of the voltage signal of the control target, the state of the harmonic amplitude component calculated each time according to the future time of the voltage signal is u ad1 (u * ) Or u ad2 (u * ) According to this, the state result is stored in m h1 Or m is h2 Judging which data set value is triggered and selected at the moment according to the predicting result of the last moment;
3-3) the individual subharmonic components are then extracted for the complete data points for each fundamental period by sliding window discrete Fourier transform and stored in data set M h In (a) and (b);
3-4) sending the extracted harmonic component into a cost function for calculation, and selecting the most suitable voltage signal to obtain the expected output voltage waveform of the inverter;
3-5) determining the cost function according to the following control objective: (1) the low harmonic distortion is controlled, so that the damage to a power system is avoided; (2) switching loss is reduced, and the load of inverter equipment is lightened; (3) the dynamic performance of the system is improved; therefore, according to the above control target, the cost function is determined as:
in U * [1]The middle is the fundamental wave amplitude of the reference voltage signal; u (U) P [1]Predicting the fundamental amplitude of the voltage signal; u (U) P [k]Predicting the amplitude of each subharmonic of the voltage signal; g 1 、g k The weight coefficient of each item; n is n sw Representing a predicted switching number when the current output voltage signal becomes the predicted voltage; g c Is a weight coefficient for controlling the switching frequency;
according to formula (2), calculating the cost function of each state of the controlled object at the future moment: if the switch state u is at this time ad1 (u * ) Is effective, then the weighted sum at this time will be stored in F 1 Among them; if it is effective at this time, u ad2 (u * ) Will be stored in F 2 Among them;
by comparing stored values F after the cost function for all future time states has been calculated 1 、F 2 Selecting a switching state which minimizes a cost function, generating a spot signal and feeding the spot signal back to m in harmonic extraction fs 、m hs A memory; at the same time, the feedback of the spot signal will be from the corresponding memory m fs 、m hs Extracting the selected state as u ad1 (u * ) Or u ad2 (u * ) And replace the harmonic amplitude component stored in M f 、M h Harmonic amplitude components of the last position switch state; at the same time, memory M f 、M h The harmonic amplitude component of the first position switch state is deleted and the u calculated at the current moment is loaded ad1 (u * )、u ad2 (u * ) A switch state result;
the core of the predictive control algorithm is to sequentially extract the fundamental wave and the amplitude of each subharmonic of the controlled object in the future moment, and mainly apply a sliding window discrete Fourier transform algorithm; wherein the fundamental wave amplitude is extracted and is matched with the reference fundamental wave amplitude ref_u 1 Comparing; in order to make the voltage signal at the next moment follow the reference signal better, the weight coefficient of the voltage signal is adjusted to force the voltage signal to follow the reference signal so as to obtain an ideal waveform;
according to the formula (2), after the amplitude of each subharmonic is extracted, the corresponding weight coefficient g is adjusted according to the requirement of a control system k To achieve suppression of designated subharmonics; according to formula (2), n sw Then the predicted switching times when the current output voltage signal is changed to the predicted voltage is represented by adjusting the weight coefficient g c Increasing or decreasing the value of g in the cost function F c n sw The specific gravity of the control circuit is used for forcing the switching state at the next moment to be consistent with the current state or to be switched, so as to achieve the effect of controlling the switching frequency.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111461583.4A CN114337204B (en) | 2021-12-02 | 2021-12-02 | Predictive control specified harmonic suppression switching strategy with low switching frequency characteristics |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111461583.4A CN114337204B (en) | 2021-12-02 | 2021-12-02 | Predictive control specified harmonic suppression switching strategy with low switching frequency characteristics |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114337204A CN114337204A (en) | 2022-04-12 |
| CN114337204B true CN114337204B (en) | 2024-01-30 |
Family
ID=81049617
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111461583.4A Active CN114337204B (en) | 2021-12-02 | 2021-12-02 | Predictive control specified harmonic suppression switching strategy with low switching frequency characteristics |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114337204B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115372698A (en) * | 2022-10-26 | 2022-11-22 | 东方电子股份有限公司 | Measurement and control device and method for suppressing higher harmonics of power system |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4977492A (en) * | 1990-04-25 | 1990-12-11 | Sundstrand Corporation | Suppression of switching harmonics |
| WO1991003862A1 (en) * | 1989-09-11 | 1991-03-21 | Siemens Aktiengesellschaft | Device and process for optimum operation of a power converter connected to a power supply |
| US5383107A (en) * | 1992-11-06 | 1995-01-17 | Sundstrand Corporation | Harmonic control for an inverter by use of an objective function |
| JP2004295226A (en) * | 2003-03-25 | 2004-10-21 | Matsushita Electric Works Ltd | Demand prediction support system, its program, and computer readable recording medium for recording this program |
| CN104092394A (en) * | 2014-05-27 | 2014-10-08 | 中国矿业大学(北京) | Method for solving selected harmonic eliminated switching angle of ladder wave multilevel converter |
| CN104732113A (en) * | 2015-04-21 | 2015-06-24 | 武汉科力源电气工程技术有限公司 | Harmonic source injection based method of estimating installed capacity of parallel APF (active power filter) |
| CN105205242A (en) * | 2015-09-15 | 2015-12-30 | 河南理工大学 | Space vector PWM (pulse width modulation) harmonic analysis method |
| CN106208737A (en) * | 2016-08-24 | 2016-12-07 | 中南大学 | Model prediction current control method based on third-harmonic zero-sequence voltage matrix converter |
| CN106897556A (en) * | 2017-02-23 | 2017-06-27 | 中国矿业大学(北京) | The real-time computing technique of particular harmonic controlling switch angle |
| CN111832158A (en) * | 2020-06-22 | 2020-10-27 | 中国石油大学(华东) | Improved particle swarm algorithm-based multi-level inverter harmonic suppression optimization strategy |
| CN112054732A (en) * | 2020-09-09 | 2020-12-08 | 上海大学 | PMSM multi-step current prediction control method based on cost function pre-selection |
| CN112532094A (en) * | 2020-11-27 | 2021-03-19 | 江苏科技大学 | Compound control method of T-type three-level NPC inverter |
| CN113315126A (en) * | 2021-05-31 | 2021-08-27 | 华中科技大学 | Specified subharmonic suppression secondary sampling method and system for active power filter |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI309910B (en) * | 2006-04-13 | 2009-05-11 | Tatung Co Ltd | Design of random pulse-width modulated inverter with lower-order harmonic elimination |
| EP2546979A1 (en) * | 2011-07-15 | 2013-01-16 | ABB Research Ltd. | Method for controlling harmonics and resonances in an inverter |
-
2021
- 2021-12-02 CN CN202111461583.4A patent/CN114337204B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1991003862A1 (en) * | 1989-09-11 | 1991-03-21 | Siemens Aktiengesellschaft | Device and process for optimum operation of a power converter connected to a power supply |
| US4977492A (en) * | 1990-04-25 | 1990-12-11 | Sundstrand Corporation | Suppression of switching harmonics |
| US5383107A (en) * | 1992-11-06 | 1995-01-17 | Sundstrand Corporation | Harmonic control for an inverter by use of an objective function |
| JP2004295226A (en) * | 2003-03-25 | 2004-10-21 | Matsushita Electric Works Ltd | Demand prediction support system, its program, and computer readable recording medium for recording this program |
| CN104092394A (en) * | 2014-05-27 | 2014-10-08 | 中国矿业大学(北京) | Method for solving selected harmonic eliminated switching angle of ladder wave multilevel converter |
| CN104732113A (en) * | 2015-04-21 | 2015-06-24 | 武汉科力源电气工程技术有限公司 | Harmonic source injection based method of estimating installed capacity of parallel APF (active power filter) |
| CN105205242A (en) * | 2015-09-15 | 2015-12-30 | 河南理工大学 | Space vector PWM (pulse width modulation) harmonic analysis method |
| CN106208737A (en) * | 2016-08-24 | 2016-12-07 | 中南大学 | Model prediction current control method based on third-harmonic zero-sequence voltage matrix converter |
| CN106897556A (en) * | 2017-02-23 | 2017-06-27 | 中国矿业大学(北京) | The real-time computing technique of particular harmonic controlling switch angle |
| CN111832158A (en) * | 2020-06-22 | 2020-10-27 | 中国石油大学(华东) | Improved particle swarm algorithm-based multi-level inverter harmonic suppression optimization strategy |
| CN112054732A (en) * | 2020-09-09 | 2020-12-08 | 上海大学 | PMSM multi-step current prediction control method based on cost function pre-selection |
| CN112532094A (en) * | 2020-11-27 | 2021-03-19 | 江苏科技大学 | Compound control method of T-type three-level NPC inverter |
| CN113315126A (en) * | 2021-05-31 | 2021-08-27 | 华中科技大学 | Specified subharmonic suppression secondary sampling method and system for active power filter |
Non-Patent Citations (6)
| Title |
|---|
| 三相SPWM逆变器的谐波抑制策略;李新君;张敏;;防爆电机;-;第-卷(第01期) * |
| 下垂控制并网逆变器的选择性谐波发生研究;刘勋昊;陶勇;李广地;邓焰;电力电子技术;第49卷(第8期) * |
| 基于电流谐波频谱分析的感应电机无速度传感器速度辨识方法;刘晓红;于艳;张还;;现代电子技术;-;第-卷(第18期) * |
| 基于谐波观测器的永磁同步电机谐波电流抑制策略研究;张剑;温旭辉;李文善;彭萌;;中国电机工程学报(第10期) * |
| 应用于频率宽范围波动电网的自适应采样相位差校正法;林申力;陈隆道;;电力系统自动化(第09期) * |
| 开关点预置最优SPWM控制的四桥臂三相逆变器;王慧贞;丁勇;张方华;陈新;严仰光;;中国电机工程学报;-;第-卷(第03期) * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114337204A (en) | 2022-04-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zahira et al. | A technical survey on control strategies of active filter for harmonic suppression | |
| CN106549400B (en) | A kind of control method of the distribution static synchronous compensator based on voltage prediction | |
| CN107134939B (en) | A kind of three level grid-connected inverter dual models prediction direct Power Control method | |
| CN109038673B (en) | Model prediction optimization control method of photovoltaic power generation system | |
| CN103595069A (en) | Method for carrying out model prediction control on grid-side converter of photovoltaic power generation system under unbalanced voltage | |
| CN114337204B (en) | Predictive control specified harmonic suppression switching strategy with low switching frequency characteristics | |
| CN111817598A (en) | Three-vector model prediction current control method for three-phase grid-connected inverter | |
| CN110460089A (en) | A kind of LCL gird-connected inverter FCS-MPC control method based on multivariable prediction | |
| Ginn et al. | Flexible active compensator control for variable compensation objectives | |
| CN115276094A (en) | Grid-connected converter prediction control method and system based on structure adaptive ESO | |
| Das et al. | Improvement of power quality in a three-phase system using an adaline-based multilevel inverter | |
| Zhou et al. | Hybrid prediction-based deadbeat control for a high-performance shunt active power filter | |
| KR101769795B1 (en) | Superconducting magnetic energy storage system in microgrids for eddy current losses reduction and method of controlling the same | |
| Qi et al. | Two‐voltage hierarchical model predictive control for a single‐phase cascaded H‐bridge rectifier | |
| Yue et al. | Robust predictive dual-loop control method based on Lyapunov function stability and energy equilibrium though double-core processors for active power filter | |
| Elvira-Ortiz et al. | Study of the harmonic and interharmonic content in electrical signals from photovoltaic generation and their relationship with environmental factors | |
| Vargas et al. | Data mining techniques for very short term prediction of wind power | |
| CN109888824B (en) | Photovoltaic grid-connected inversion control method based on predictive control | |
| CN114710055B (en) | Two-parallel power converter model prediction control method based on finite set single vector | |
| Van Ngo et al. | Model predictive power control based on virtual flux for grid connected three-level neutral-point clamped inverter | |
| Rao et al. | A literature review on reduction of harmonics using active power filter | |
| Gulbudak et al. | Finite state model predictive control for 3× 3 matrix converter based on switching state elimination | |
| Liu et al. | Real-time implementation of finite control set model predictive control for matrix converter based solid state transformer | |
| Lee et al. | A novel method to improve output voltage quality of grid-connected cascaded H-bridge multilevel converter with phase-shifted PWM and serial bus communication | |
| Gonuguntala et al. | Performance analysis of finite control set model predictive controlled active harmonic filter |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: 528000 No. 2, Daliang Zhihui Road, Shunde District, Foshan City, Guangdong Province Applicant after: Shunde Innovation College of Beijing University of Science and Technology Address before: No.2, Daliang Zhihui Road, Shunde District, Foshan City, Guangdong Province 528300 Applicant before: Shunde Graduate School of Beijing University of science and technology |
|
| CB02 | Change of applicant information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |