CN117369422B - Controller factory parameter calibration method, parameter calibration device and storage medium - Google Patents
Controller factory parameter calibration method, parameter calibration device and storage medium Download PDFInfo
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Abstract
The invention particularly provides a factory parameter calibration method, a parameter calibration device and a storage medium of a controller. Responding to an input control demand, and comparing a parameter library based on the control demand and a preset demand to obtain a plurality of groups of target parameters; generating corresponding configuration instructions based on a plurality of groups of target parameters, and sequentially configuring the test load modules based on each configuration instruction to obtain corresponding execution results; substituting the execution results into a calibration module for analysis to determine calibration parameters; and acquiring the factory parameters of the controller, comparing the factory parameters with the calibration parameters, and selectively adjusting the factory parameters of the controller based on the comparison result. And obtaining a plurality of groups of target parameters according to the input control requirements, further configuring the test load module to obtain corresponding execution results, analyzing and determining calibration parameters through the calibration module, and adjusting the factory parameters of the controller, so that the factory parameters are adjusted according to the control requirements, and the requirements are matched with the factory parameters.
Description
Technical Field
The invention relates to the technical field of controller delivery parameter calibration, and particularly provides a controller delivery parameter calibration method, a parameter calibration device and a storage medium.
Background
With the rapid development of modern technology, the power system needs to supply electric energy with high reliability and accurate dynamic control to modern information equipment, and the quality of a controller of the power system directly affects the stable operation of the whole power system;
because the specific structures of the power systems are different, the execution parameters of the controllers of the power systems are inevitably different from actual requirements, and in actual operation, the power systems can generate additional electric quantity loss, and even cause unstable electric energy supply.
Accordingly, there is a need in the art for a new controller factory parameter calibration scheme to address the above-described issues.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks, the present invention provides a method, device and storage medium for calibrating factory parameters of a controller, which solves or at least partially solves the technical problem that the power system generates extra power loss during actual operation and even causes unstable power supply due to the difference between the execution parameters of the controller and the actual requirements.
In a first aspect, the present invention provides a method for calibrating factory parameters of a controller, the method being applied to a parameter calibration device, the parameter calibration device interacting with the controller, a calibration module and an adjustable test load module being provided in the parameter calibration device, the test load module at least comprising a transformation unit and/or a power distribution unit, the method comprising the steps of:
responding to an input control demand, and obtaining at least one group of target parameters based on the control demand and a preset demand comparison parameter library, wherein the types of the target parameters at least comprise input voltage, input current, at least one group of output voltage and at least one group of output current;
generating corresponding configuration instructions based on the at least one group of target parameters, and configuring the test load modules in sequence based on each configuration instruction to obtain corresponding execution results, wherein the configuration instructions at least comprise a configuration designating unit and an adjusting instruction corresponding to the configuration designating unit;
substituting the execution results into a calibration module for analysis to determine calibration parameters;
and acquiring factory parameters of the controller, comparing the factory parameters with the calibration parameters, and selectively adjusting the factory parameters of the controller based on the comparison result.
In one technical scheme of the controller factory parameter calibration method, the output ends of the transformation unit and the distribution unit are both connected with a feedback unit, the test load module is configured in sequence based on each configuration instruction, and the corresponding execution result is obtained by the following steps:
classifying each configuration instruction based on a configuration designating unit in each configuration instruction;
sequencing at least one configuration instruction in the same category to obtain the sequence and classification result of each configuration instruction;
and configuring the test load module by each configuration instruction in sequence based on the classification result and the sequence condition of each configuration instruction, and obtaining an execution result corresponding to each configuration instruction through a feedback unit, wherein the execution result at least comprises an actual input voltage, an actual input current, at least one group of actual output voltages and at least one group of actual output currents.
In one technical scheme of the controller factory parameter calibration method, a simulation calibration model is arranged in the calibration module, the calibration module is substituted for analysis based on each execution result, and the determination of the calibration parameters comprises:
substituting each execution result and the target parameter corresponding to each execution result into a simulation calibration model to obtain an analysis result of each target parameter;
and selecting the target parameter as a calibration parameter based on the analysis result.
In one technical scheme of the controller factory parameter calibration method, before substituting each execution result and the target parameter corresponding to each execution result into the simulation calibration model to obtain the analysis result of each target parameter, the method further comprises:
comparing the target parameters based on each execution result and corresponding target parameters of each execution result to obtain conversion efficiency of each target parameter;
comparing the conversion efficiency of each target parameter, and selecting the target parameter with the highest conversion efficiency and the second highest conversion efficiency;
and marking the selected target parameters and sending the marked target parameters to the controller so that the controller can store the target parameters into a memory of the controller.
In one technical scheme of the controller factory parameter calibration method, substituting each execution result and the target parameter corresponding to each execution result into the simulation calibration model to obtain an analysis result of each target parameter includes:
the selected multiple target parameters and the conversion efficiency corresponding to each target parameter are brought into a trained simulation calibration model, and the multiple target parameters are selectively optimized to obtain optimized target parameters;
based on the optimized target parameters, obtaining corresponding configuration instructions, configuring the test load module based on the configuration instructions to obtain execution results corresponding to the optimized target parameters, and obtaining conversion efficiency of the optimized target parameters based on the optimized target parameters and the execution results corresponding to the optimized target parameters;
and comparing the conversion efficiency of all the non-optimized target parameters with the conversion efficiency of all the optimized target parameters to obtain at least one target parameter with the highest conversion efficiency.
In one technical scheme of the controller factory parameter calibration method, before substituting the selected plurality of target parameters into the trained simulation calibration model, the method further comprises the following steps of:
acquiring a training parameter sample set, wherein the training parameter sample set comprises a plurality of groups of training parameter samples and conversion efficiency of each training parameter sample;
judging whether each training parameter sample needs to be optimized based on the conversion efficiency of each training parameter sample:
if the conversion efficiency of the training parameter sample is lower than a preset optimization threshold, judging that the training parameter sample needs to be optimized; otherwise, judging that the training parameter sample does not need to be optimized;
if the training parameter samples are judged to be optimized, based on comparison results of conversion efficiency of the training parameter samples and each preset threshold range, a corresponding optimization scheme is used for the training parameter samples, so that a plurality of temporary training parameter samples are correspondingly generated for each training parameter sample;
performing one-by-one simulation based on a plurality of temporary training parameter samples corresponding to each training parameter sample to obtain conversion efficiency corresponding to each temporary training parameter sample;
based on the conversion efficiency, selecting a temporary training parameter sample with highest conversion efficiency from a plurality of temporary training parameter samples corresponding to each training parameter sample, and adjusting the training parameter sample based on the selected temporary training parameter sample to obtain each optimized training parameter sample.
In one technical scheme of the controller factory parameter calibration method, the step of using a corresponding optimization scheme for the training parameter samples based on the comparison result of the conversion efficiency of the training parameter samples and each preset threshold range, so that each training parameter sample correspondingly generates a plurality of temporary training parameter samples includes:
based on a preset threshold range in which the conversion efficiency of the training parameter sample is located, an optimization scheme of a level corresponding to the preset threshold range is used for the training parameter sample, wherein the optimization scheme at least comprises a preset value range, a preset value number and a preset value interval corresponding to the level, so that temporary training parameter samples with the preset value number corresponding to the training parameter sample are obtained;
wherein the preset threshold range with high level is higher than the preset threshold range with low level, and the preset optimization threshold is higher than the highest value in the preset threshold range with highest level.
In one technical scheme of the controller factory parameter calibration method, after obtaining the conversion efficiency of the optimized target parameter based on the optimized target parameter and an execution result corresponding to the optimized target parameter, the method further includes:
calculating based on the conversion efficiency of the optimized target parameter and the conversion efficiency corresponding to the optimized target parameter simulated in the simulation calibration model to obtain an error value;
and if the error value exceeds a preset error threshold value, retraining the simulation calibration model.
In a second aspect, a parameter calibration device is provided, the parameter calibration device at least comprises a control module, a calibration module and an adjustable test load module, the test load module at least comprises a transformation unit and/or a power distribution unit, the parameter calibration device interacts with a controller, the control module comprises a processor and a memory, the memory is suitable for storing a plurality of program codes, and the program codes are suitable for being loaded and operated by the processor to execute the controller factory parameter calibration method according to any one of the technical schemes of the controller factory parameter calibration method.
In a third aspect, a computer readable storage medium is provided, in which a plurality of program codes are stored, the program codes being adapted to be loaded and run by a processor to perform the controller factory parameter calibration method according to any one of the above-mentioned controller factory parameter calibration methods.
The technical scheme provided by the invention has at least one or more of the following beneficial effects:
the method comprises the steps of obtaining a plurality of groups of target parameters through input control requirements, configuring a test load module according to the plurality of groups of target parameters to obtain corresponding execution results, analyzing the execution results through a calibration module to determine calibration parameters, adjusting factory parameters of a controller according to the calibration parameters, and adjusting the factory parameters according to the control requirements so as to achieve the matching of the requirements and the factory parameters, further improving the working efficiency of an electric power system where the controller is located, and avoiding the technical problems that in the prior art, due to the fact that the execution parameters of the controller of the electric power system are different from actual requirements, extra electric quantity loss occurs in the electric power system in actual operation, and even electric energy supply is unstable.
In the technical scheme of implementing the invention, in model training, whether the training parameter sample needs to be optimized is judged according to the conversion efficiency of the training parameter sample, a plurality of temporary training parameter samples are generated through the comparison result of the conversion efficiency and each preset threshold range, simulation is carried out according to each temporary training parameter sample to obtain the conversion efficiency of each temporary training parameter sample, the temporary training parameter sample with the highest conversion efficiency is selected to adjust the training parameter sample so as to obtain the optimized training parameter sample, the further optimization of the target parameter is realized, the target parameter with higher conversion efficiency is obtained, and the conversion rate of the controller to the power system is improved under the condition that the matching degree of the controller and the control requirement is ensured.
In the technical scheme of the invention, whether the simulation calibration model needs retraining is judged by calculating the error of the conversion efficiency of the optimized target parameter and the conversion efficiency of the optimized target parameter simulated in the simulation calibration model, so that the simulation accuracy of the simulation calibration model is improved, and the accuracy of analyzing the target parameter through the simulation calibration model is further improved.
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The present disclosure will become more readily understood with reference to the accompanying drawings. As will be readily appreciated by those skilled in the art: the drawings are for illustrative purposes only and are not intended to limit the scope of the present invention. Moreover, like numerals in the figures are used to designate like parts, wherein:
FIG. 1 is a flow chart illustrating the main steps of a method for calibrating factory parameters of a controller according to an embodiment of the invention;
fig. 2 is a main structural block diagram of a parameter calibration device according to an embodiment of the present invention.
List of reference numerals: 200: parameter calibration means; 201: a control module; 2011: a processor; 2012: a memory; 2013: program code; 202: a calibration module; 203: and testing the load module.
Detailed Description
Some embodiments of the invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
In the description of the present invention, a "module," "processor" may include hardware, software, or a combination of both. A module may comprise hardware circuitry, various suitable sensors, communication ports, memory, or software components, such as program code, or a combination of software and hardware. The processor may be a central processor, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. The processor has data and/or signal processing functions. The processor may be implemented in software, hardware, or a combination of both. Non-transitory computer readable storage media include any suitable medium that can store program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, and the like. The term "a and/or B" means all possible combinations of a and B, such as a alone, B alone or a and B. The term "at least one A or B" or "at least one of A and B" has a meaning similar to "A and/or B" and may include A alone, B alone or A and B. The singular forms "a", "an" and "the" include plural referents.
Referring to fig. 1, fig. 1 is a schematic flow chart of main steps of a method for calibrating factory parameters of a controller according to an embodiment of the invention. As shown in fig. 1, the method for calibrating the factory parameters of the controller in the embodiment of the invention is applied to a parameter calibration device, the parameter calibration device interacts with the controller, a calibration module and an adjustable test load module are arranged in the parameter calibration device, the test load module at least comprises a transformation unit and/or a power distribution unit, and the method mainly comprises the following steps S101-S104.
Step S101: responding to an input control demand, and obtaining at least one group of target parameters based on the control demand and a preset demand comparison parameter library, wherein the types of the target parameters at least comprise input voltage, input current, at least one group of output voltage and at least one group of output current;
specifically, in some embodiments, the requirement control parameter library stores a preset plurality of groups of requirements and at least one group of target parameters corresponding to each requirement, and the obtaining at least one group of target parameters based on the control requirement and the preset requirement control parameter library includes:
comparing the control requirement with the preset requirement comparison parameter library, and determining the requirement matched with the control requirement in the requirement comparison parameter library;
and obtaining at least one set of target parameters corresponding to the requirement based on the requirement.
Step S102: generating corresponding configuration instructions based on the at least one group of target parameters, and configuring the test load modules in sequence based on each configuration instruction to obtain corresponding execution results, wherein the configuration instructions at least comprise a configuration designating unit and an adjusting instruction corresponding to the configuration designating unit;
further, in some embodiments, the output ends of the transformation unit and the distribution unit are both connected with a feedback unit, and the configuring the test load module based on each configuration instruction sequentially, to obtain a corresponding execution result includes:
classifying each configuration instruction based on a configuration designating unit in each configuration instruction;
sequencing at least one configuration instruction in the same category to obtain the sequence and classification result of each configuration instruction;
and configuring the test load module by each configuration instruction in sequence based on the classification result and the sequence condition of each configuration instruction, and obtaining an execution result corresponding to each configuration instruction through a feedback unit, wherein the execution result at least comprises an actual input voltage, an actual input current, at least one group of actual output voltages and at least one group of actual output currents.
Specifically, in some embodiments, classification of each configuration instruction is implemented by a cross entropy loss function, where selection of a classification method is only illustrated by way of example, and a person skilled in the art may select the classification method according to actual needs in actual testing, which is not described herein.
Step S103: substituting the execution results into a calibration module for analysis to determine calibration parameters;
specifically, in some embodiments, a simulation calibration model is set in the calibration module, and the calibration parameter is determined based on the execution results substituted into the calibration module for analysis, which includes:
substituting each execution result and the target parameter corresponding to each execution result into a simulation calibration model to obtain an analysis result of each target parameter;
and selecting the target parameter as a calibration parameter based on the analysis result.
Specifically, in some embodiments, the selecting the target parameter as the calibration parameter based on the analysis result includes:
if the number of at least one target parameter with the highest conversion efficiency is 1, taking the target parameter as a calibration parameter;
and if the number of at least one target parameter with the highest conversion efficiency exceeds 1, taking any one target parameter as a calibration parameter, marking the rest target parameters and sending the marked target parameters to the controller so that the controller can store the target parameters into a memory of the controller.
Further, in some embodiments, before substituting each execution result and the target parameter corresponding to each execution result into the simulation calibration model to obtain the analysis result of each target parameter, the method further includes:
comparing the target parameters based on each execution result and corresponding target parameters of each execution result to obtain conversion efficiency of each target parameter;
comparing the conversion efficiency of each target parameter, and selecting the target parameter with the highest conversion efficiency and the second highest conversion efficiency;
and marking the selected target parameters and sending the marked target parameters to the controller so that the controller can store the target parameters into a memory of the controller.
Specifically, in some embodiments, substituting each execution result and the target parameter corresponding to each execution result into the simulation calibration model to obtain the analysis result of each target parameter includes:
the selected multiple target parameters and the conversion efficiency corresponding to each target parameter are brought into a trained simulation calibration model, and the multiple target parameters are selectively optimized to obtain optimized target parameters;
based on the optimized target parameters, obtaining corresponding configuration instructions, configuring the test load module based on the configuration instructions to obtain execution results corresponding to the optimized target parameters, and obtaining conversion efficiency of the optimized target parameters based on the optimized target parameters and the execution results corresponding to the optimized target parameters;
and comparing the conversion efficiency of all the non-optimized target parameters with the conversion efficiency of all the optimized target parameters to obtain at least one target parameter with the highest conversion efficiency.
Specifically, in some embodiments, before substituting the selected plurality of target parameters into the trained simulated calibration model, the method further includes training the simulated calibration model by:
acquiring a training parameter sample set, wherein the training parameter sample set comprises a plurality of groups of training parameter samples and conversion efficiency of each training parameter sample;
judging whether each training parameter sample needs to be optimized based on the conversion efficiency of each training parameter sample:
if the conversion efficiency of the training parameter sample is lower than a preset optimization threshold, judging that the training parameter sample needs to be optimized; otherwise, judging that the training parameter sample does not need to be optimized;
if the training parameter samples are judged to be optimized, based on comparison results of conversion efficiency of the training parameter samples and each preset threshold range, a corresponding optimization scheme is used for the training parameter samples, so that a plurality of temporary training parameter samples are correspondingly generated for each training parameter sample;
performing one-by-one simulation based on a plurality of temporary training parameter samples corresponding to each training parameter sample to obtain conversion efficiency corresponding to each temporary training parameter sample;
based on the conversion efficiency, selecting a temporary training parameter sample with highest conversion efficiency from a plurality of temporary training parameter samples corresponding to each training parameter sample, and adjusting the training parameter sample based on the selected temporary training parameter sample to obtain each optimized training parameter sample.
Specifically, in some embodiments, the using a corresponding optimization scheme for the training parameter samples based on the comparison result of the conversion efficiency of the training parameter samples and each preset threshold range, so that generating a plurality of temporary training parameter samples corresponding to each training parameter sample includes:
based on a preset threshold range in which the conversion efficiency of the training parameter sample is located, an optimization scheme of a level corresponding to the preset threshold range is used for the training parameter sample, wherein the optimization scheme at least comprises a preset value range, a preset value number and a preset value interval corresponding to the level, so that temporary training parameter samples with the preset value number corresponding to the training parameter sample are obtained;
wherein the preset threshold range with high level is higher than the preset threshold range with low level, and the preset optimization threshold is higher than the highest value in the preset threshold range with highest level.
Specifically, in some embodiments, the optimizing method according to the level of the training parameter sample corresponding to the preset threshold range is used for the training parameter sample based on the preset threshold range where the conversion efficiency of the training parameter sample is located, where the optimizing method at least includes a preset value range, a preset value number, and a preset value interval corresponding to the level, so as to obtain temporary training parameter samples corresponding to the training parameter sample in the preset value number, where the temporary training parameter samples include: if the conversion efficiency of the training parameter samples is within a first preset threshold range, a first-level optimization scheme is used for the training parameter samples, wherein the first-level optimization scheme at least comprises a first preset value range, a first preset value number and a first preset value interval, so that temporary training parameter samples with the corresponding number of the training parameter samples being the first preset value number are obtained;
if the conversion efficiency of the training parameter samples is in a second preset threshold range, a second-level optimization scheme is used for the training parameter samples, wherein the second-level optimization scheme at least comprises a second preset value range, a second preset value number and a second preset value interval, so that temporary training parameter samples with the number of second preset value numbers corresponding to the training parameter samples are obtained;
if the conversion efficiency of the training parameter samples is within a third preset threshold range, a third-level optimization scheme is used for the training parameter samples, wherein the third-level optimization scheme at least comprises a third preset value range, a third preset value number and a third preset value interval, so that temporary training parameter samples with the number of the third preset value number corresponding to the training parameter samples are obtained;
the first preset threshold range is lower than a second preset threshold range, the second preset threshold range is lower than a third preset threshold range, and the preset optimization threshold is higher than the highest value of the third preset threshold range.
Specifically, in some embodiments, the third preset threshold range may be 80% to 89%, the second preset threshold range may be 60% to 79%, the first preset threshold range may be 50% to 59%, and the preset optimal threshold may be 90% or 92%, where the selection of each preset threshold range and the preset optimal threshold is only exemplary, and those skilled in the art may select according to actual needs in actual testing, which is not repeated herein.
Specifically, in some embodiments, taking the conversion efficiency of the training parameter sample being within a third preset threshold as an example, the "using a third level optimization scheme on the training parameter sample" includes: and respectively taking values of all the parameters in the training parameter samples within a third preset value range, wherein the value number is the second preset value number, and obtaining temporary training parameter samples corresponding to the training parameter samples and having the third preset value number.
In the above embodiment, in model training, whether the training parameter sample needs to be optimized is determined according to the conversion efficiency of the training parameter sample, then a plurality of temporary training parameter samples are generated through the comparison result of the conversion efficiency and each preset threshold range, and simulation is performed according to each temporary training parameter sample to obtain the conversion efficiency of each temporary training parameter sample, and then the temporary training parameter sample with the highest conversion efficiency is selected to adjust the training parameter sample so as to obtain the optimized training parameter sample, so that further optimization of the target parameter is realized, the target parameter with higher conversion efficiency is obtained, and further, under the condition that the matching degree of the controller and the control requirement is ensured, the conversion rate of the controller to the power system is improved.
Step S104: and acquiring factory parameters of the controller, comparing the factory parameters with the calibration parameters, and selectively adjusting the factory parameters of the controller based on the comparison result.
Based on the above steps S101-S104, multiple sets of target parameters are obtained through the input control requirements, then the test load module is configured according to the multiple sets of target parameters to obtain corresponding execution results, then the calibration module is used for analyzing the execution results, the calibration parameters are determined, and the factory parameters of the controller are adjusted according to the calibration parameters, so that the factory parameters are adjusted according to the control requirements, the matching between the requirements and the factory parameters is achieved, the working efficiency of the electric power system where the controller is located is improved, and the technical problems that in the prior art, due to the fact that the execution parameters of the controller of the electric power system are different from actual requirements, extra electric quantity loss occurs in the electric power system in actual operation, and even the electric power supply is unstable are solved.
Further, in some embodiments, after the obtaining the conversion efficiency of the optimized target parameter based on the optimized target parameter and the execution result corresponding to the optimized target parameter, the method further includes:
calculating based on the conversion efficiency of the optimized target parameter and the conversion efficiency corresponding to the optimized target parameter simulated in the simulation calibration model to obtain an error value;
and if the error value exceeds a preset error threshold value, retraining the simulation calibration model.
Specifically, in some embodiments, the preset error threshold may be 5% or 10%, where the selection of the preset error threshold is only illustrated, and the selection by those skilled in the art may be performed according to actual needs in the actual test, which is not described herein.
In the above embodiment, by calculating the error between the conversion efficiency of the optimized target parameter and the conversion efficiency of the optimized target parameter simulated in the simulation calibration model, it is determined whether the simulation calibration model needs retraining, so that the simulation accuracy of the simulation calibration model is improved, and the accuracy of analyzing the target parameter by the simulation calibration model is further improved.
It should be noted that, although the foregoing embodiments describe the steps in a specific order, it will be understood by those skilled in the art that, in order to achieve the effects of the present invention, the steps are not necessarily performed in such an order, and may be performed simultaneously (in parallel) or in other orders, and these variations are within the scope of the present invention.
The invention further provides a parameter calibration device.
Referring to fig. 2, fig. 2 is a main block diagram of a parameter calibration device according to an embodiment of the present invention. As shown in fig. 2, the parameter calibration device 200 in the embodiment of the present invention mainly includes a control module 201, a calibration module 202, and an adjustable test load module 203, where the test load module 203 includes at least a conversion unit and/or a power distribution unit, and the parameter calibration device 200 interacts with a controller. The control module 201 includes a processor 2011 and a memory 2012, the memory 2012 may be configured to store program code 2013 for performing the controller factory parameter calibration method of the method embodiment described above, and the processor 2011 may be configured to execute the program code 2013 in the memory 2012, the program code 2013 including, but not limited to, the program code 2013 for performing the controller factory parameter calibration method of the method embodiment described above. For convenience of explanation, only those portions of the embodiments of the present invention that are relevant to the embodiments of the present invention are shown, and specific technical details are not disclosed, please refer to the method portions of the embodiments of the present invention. The control module 201 may be a control module 201 device that includes various electronic devices.
Further, in some embodiments, a preset plurality of groups of requirements and at least one group of target parameters corresponding to each requirement are stored in the requirement comparison parameter library, the output ends of the transformation unit and the distribution unit are connected with a feedback unit, and a simulation calibration model is set in the calibration module 202.
In one embodiment, the description of the specific implementation functions may be described with reference to step S101-step S104.
The above-mentioned parameter calibration device 200 is used for executing the embodiment of the controller factory parameter calibration method shown in fig. 1, and the technical principles of the two are similar, the technical problems to be solved and the technical effects to be produced are similar, and those skilled in the art can clearly understand that, for convenience and brevity of description, the specific working process and the related description of the parameter calibration device 200 can refer to the description of the embodiment of the controller factory parameter calibration method, and will not be repeated here.
It will be appreciated by those skilled in the art that the present invention may implement all or part of the above-described methods according to the above-described embodiments, or may be implemented by means of a computer program for instructing relevant hardware, where the computer program may be stored in a computer readable storage medium, and the computer program may implement the steps of the above-described embodiments of the method when executed by the processor 2011. The computer program includes computer program code 2013, where the computer program code 2013 may be in source code form, object code form, executable file or some intermediate form, etc. The computer readable storage medium may include: any entity or device capable of carrying the computer program code 2013, medium, usb disk, removable hard disk, magnetic disk, optical disk, computer memory 2012, read-only memory 2012, random access memory 2012, electrical carrier signal, telecommunications signal, software distribution medium, and so forth. It should be noted that the computer readable storage medium may include content that is subject to appropriate increases and decreases as required by jurisdictions and by jurisdictions in which such computer readable storage medium does not include electrical carrier signals and telecommunications signals.
Further, the invention also provides a computer readable storage medium. In one computer readable storage medium embodiment according to the present invention, the computer readable storage medium may be configured to store program code 2013 for performing the controller factory parameter calibration method of the above-described method embodiment, the program code 2013 being loadable and executable by the processor 2011 to implement the controller factory parameter calibration method described above. For convenience of explanation, only those portions of the embodiments of the present invention that are relevant to the embodiments of the present invention are shown, and specific technical details are not disclosed, please refer to the method portions of the embodiments of the present invention. The computer readable storage medium may be a memory 2012 device comprising a variety of electronic devices, and optionally the computer readable storage medium in embodiments of the present invention is a non-transitory computer readable storage medium.
Further, it should be understood that, since the respective modules are merely set to illustrate the functional units of the apparatus of the present invention, the physical devices corresponding to the modules may be the processor itself, or a part of software in the processor, a part of hardware, or a part of a combination of software and hardware. Accordingly, the number of individual modules in the figures is merely illustrative.
Those skilled in the art will appreciate that the various modules in the apparatus may be adaptively split or combined. Such splitting or combining of specific modules does not cause the technical solution to deviate from the principle of the present invention, and therefore, the technical solution after splitting or combining falls within the protection scope of the present invention.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will fall within the scope of the present invention.
Claims (8)
1. The method is applied to a parameter calibration device, the parameter calibration device interacts with the controller, a calibration module and an adjustable test load module are arranged in the parameter calibration device, the test load module at least comprises a transformation unit and/or a power distribution unit, and the method comprises the following steps:
responding to an input control demand, and obtaining at least one group of target parameters based on the control demand and a preset demand comparison parameter library, wherein the types of the target parameters at least comprise input voltage, input current, at least one group of output voltage and at least one group of output current;
generating corresponding configuration instructions based on the at least one group of target parameters, and configuring the test load modules in sequence based on each configuration instruction to obtain corresponding execution results, wherein the configuration instructions at least comprise a configuration designating unit and an adjusting instruction corresponding to the configuration designating unit;
substituting the execution results into a calibration module for analysis to determine calibration parameters;
acquiring factory parameters of the controller, comparing the factory parameters with the calibration parameters, and selectively adjusting the factory parameters of the controller based on the comparison result;
the calibration module is internally provided with a simulation calibration model, the calibration module is substituted for analysis based on each execution result, and the determination of the calibration parameters comprises:
substituting each execution result and the target parameter corresponding to each execution result into a simulation calibration model to obtain an analysis result of each target parameter;
selecting a target parameter as a calibration parameter based on the analysis result;
before substituting each execution result and the target parameter corresponding to each execution result into the simulation calibration model to obtain the analysis result of each target parameter, the method further comprises:
comparing the target parameters based on each execution result and corresponding target parameters of each execution result to obtain conversion efficiency of each target parameter;
comparing the conversion efficiency of each target parameter, and selecting the target parameter with the highest conversion efficiency and the second highest conversion efficiency;
and marking the selected target parameters and sending the marked target parameters to the controller so that the controller can store the target parameters into a memory of the controller.
2. The method for calibrating factory parameters of a controller according to claim 1, wherein the transforming unit and the power distribution unit are both connected with a feedback unit, the configuring the test load module based on each configuration instruction in turn, and obtaining the corresponding execution result comprises:
classifying each configuration instruction based on a configuration designating unit in each configuration instruction;
sequencing at least one configuration instruction in the same category to obtain the sequence and classification result of each configuration instruction;
and configuring the test load module by each configuration instruction in sequence based on the classification result and the sequence condition of each configuration instruction, and obtaining an execution result corresponding to each configuration instruction through a feedback unit, wherein the execution result at least comprises an actual input voltage, an actual input current, at least one group of actual output voltages and at least one group of actual output currents.
3. The method for calibrating factory parameters of a controller according to claim 2, wherein substituting each execution result and the target parameter corresponding to each execution result into the simulation calibration model to obtain the analysis result of each target parameter comprises:
the selected multiple target parameters and the conversion efficiency corresponding to each target parameter are brought into a trained simulation calibration model, and the multiple target parameters are selectively optimized to obtain optimized target parameters;
based on the optimized target parameters, obtaining corresponding configuration instructions, configuring the test load module based on the configuration instructions to obtain execution results corresponding to the optimized target parameters, and obtaining conversion efficiency of the optimized target parameters based on the optimized target parameters and the execution results corresponding to the optimized target parameters;
and comparing the conversion efficiency of all the non-optimized target parameters with the conversion efficiency of all the optimized target parameters to obtain at least one target parameter with the highest conversion efficiency.
4. A method of calibrating factory parameters of a controller according to claim 3, wherein prior to said substituting the selected plurality of target parameters into a trained simulated calibration model, the method further comprises the steps of:
acquiring a training parameter sample set, wherein the training parameter sample set comprises a plurality of groups of training parameter samples and conversion efficiency of each training parameter sample;
judging whether each training parameter sample needs to be optimized based on the conversion efficiency of each training parameter sample:
if the conversion efficiency of the training parameter sample is lower than a preset optimization threshold, judging that the training parameter sample needs to be optimized; otherwise, judging that the training parameter sample does not need to be optimized;
if the training parameter samples are judged to be optimized, based on comparison results of conversion efficiency of the training parameter samples and each preset threshold range, a corresponding optimization scheme is used for the training parameter samples, so that a plurality of temporary training parameter samples are correspondingly generated for each training parameter sample;
performing one-by-one simulation based on a plurality of temporary training parameter samples corresponding to each training parameter sample to obtain conversion efficiency corresponding to each temporary training parameter sample;
based on the conversion efficiency, selecting a temporary training parameter sample with highest conversion efficiency from a plurality of temporary training parameter samples corresponding to each training parameter sample, and adjusting the training parameter sample based on the selected temporary training parameter sample to obtain each optimized training parameter sample.
5. The method for calibrating factory parameters of a controller according to claim 4, wherein the using a corresponding optimization scheme for the training parameter samples based on the comparison result of the conversion efficiency of the training parameter samples and each preset threshold range, so that each training parameter sample correspondingly generates a plurality of temporary training parameter samples includes:
based on a preset threshold range in which the conversion efficiency of the training parameter sample is located, an optimization scheme of a level corresponding to the preset threshold range is used for the training parameter sample, wherein the optimization scheme at least comprises a preset value range, a preset value number and a preset value interval corresponding to the level, so that temporary training parameter samples with the preset value number corresponding to the training parameter sample are obtained;
wherein the preset threshold range with high level is higher than the preset threshold range with low level, and the preset optimization threshold is higher than the highest value in the preset threshold range with highest level.
6. The method according to claim 5, wherein after the obtaining the conversion efficiency of the optimized target parameter based on the optimized target parameter and the execution result corresponding to the optimized target parameter, the method further comprises:
calculating based on the conversion efficiency of the optimized target parameter and the conversion efficiency corresponding to the optimized target parameter simulated in the simulation calibration model to obtain an error value;
and if the error value exceeds a preset error threshold value, retraining the simulation calibration model.
7. A parameter calibration device, characterized in that it comprises at least a control module, a calibration module and an adjustable test load module, said test load module comprising at least a transformation unit and/or a distribution unit, said parameter calibration device interacting with a controller, said control module comprising a processor and a memory, said memory being adapted to store a plurality of program codes, said program codes being adapted to be loaded and run by said processor to perform the controller factory parameter calibration method of any one of claims 1 to 6.
8. A computer readable storage medium having stored therein a plurality of program codes, wherein the program codes are adapted to be loaded and executed by a processor to perform the controller factory parameter calibration method of any one of claims 1 to 6.
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