Battery early warning method and device for energy storage power station
In the sampling and correction process of battery performance values in the energy storage power station, the performance value coordination correction module is used to perform concurrent and coordinated correction, which solves the problem of inconsistency in the prior art performance value correction and improves the coordination of performance values accuracy of correction.
Patent Information
- Application Number
- CN202411303205.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-19
- Publication Date
- 2025-02-11
AI Technical Summary
In the process of sampling and correction of battery performance values in energy storage power stations, the correction of various types of performance values is inconsistent, resulting in the effect of different dimensions such as scenes, devices, workers, and models, affecting the accuracy of the sampling values.
The performance value coordination correction module is adopted to obtain the correlation mode between the battery performance value and the standard performance value in each type of energy storage power station through standard performance value through standard performance value. Concurrent coordination of performance value for each channel is achieved. Correction.
Through concurrent and coordinated correction, the differential effects introduced during the correction of different types of performance values are avoided, the coordinated correction accuracy of performance values is improved, and the correctness of sampling values is ensured.
Smart Images
Figure CN119416170A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to a battery early warning method and device for an energy storage power station, and specifically belongs to the technical field of battery early warning. Background Art
[0002] Energy storage power stations are equipment systems that store, convert and release cyclical electrical energy through electrochemical batteries or electromagnetic energy storage media. The reliability of batteries in energy storage power stations is important, so early warning of working defects of batteries in energy storage power stations must be implemented.
[0003] In order to issue an early warning for working defects of batteries in energy storage power stations, as pointed out in the prior art solution with patent application number "CN" and patent name "A battery pack early warning device for energy storage power stations", it mainly relies on voltage transmitters, temperature detection transmitters, humidity transmitters, smoke transmitters and buzzers connected to the controller. The voltage transmitter, temperature detection transmitter, humidity transmitter and smoke transmitter are respectively used to sample the voltage value, temperature measurement value, humidity value and smoke concentration value of the batteries in the energy storage power station and transmit them to the controller. The controller is used to determine whether the collected voltage value, temperature measurement value, humidity value and smoke concentration value of the batteries in the energy storage power station have any abnormality. If an abnormality occurs, the buzzer is operated to issue an early warning. The voltage value, temperature measurement value, humidity value or smoke concentration value of the batteries in the energy storage power station is the performance value of the batteries in the energy storage power station.
[0004] On the other hand, the battery performance values in the energy storage power station must ensure the coordinated sampling properties of the battery performance values in each type of energy storage power station, that is, under the same energy storage power station battery performance conditions, the battery performance values in different types of energy storage power stations must ensure coordination.
[0005] To meet the sampling accuracy requirements, it is necessary to go through a strict standard system optimization processing method to ensure the accuracy of the sampling device used. The current common method is to ensure the accuracy of each sampling device to meet the accuracy requirements of different types of performance value sampling. However, the defect of this method is that different types of performance values are corrected one by one, rather than concurrently and collaboratively performing sampling values for the same performance value standard. During different correction periods, the effects of different dimensions such as scenes, devices, workers, and modes will be introduced. For strict accuracy sampling requirements, the differences cannot be ignored. Summary of the invention
[0006] In order to solve the defects existing in the prior art, the present invention proposes a battery early warning method and device for an energy storage power station, which initially obtains a standard performance value verification value of a performance value coordination correction module, obtains a standard performance value through standard performance value verification value calculation, then obtains battery performance values of each type of energy storage power station in a plurality of sampling devices, performs regression calculation on the battery performance values of each type of energy storage power station and the standard performance values, obtains a correlation pattern between the battery performance values of each type of energy storage power station in the plurality of sampling devices and the standard performance values, and uses the correlation pattern to obtain a coordination correction value of the performance value of each channel in the plurality of sampling devices, so as to obtain the performance value more accurately.
[0007] The present invention provides a battery early warning method for an energy storage power station. The method comprises the following steps: sampling the voltage value, temperature value, humidity value and smoke concentration value of the battery in the energy storage power station respectively through a voltage transmitter, a performance value detection transmitter, a humidity transmitter and a smoke transmitter, and transmitting the samples to a controller; after the controller processes the collected voltage value, temperature value, humidity value and smoke concentration value, it is determined whether the voltage value, temperature value, humidity value and smoke concentration value of the battery in the energy storage power station after the processing are abnormal, and if abnormal, a buzzer is operated to warn; The process of the controller performing processing on the received voltage value, temperature value, humidity value and smoke concentration value includes the following steps: Step 1: obtaining a standard performance value verification value of a performance value coordination correction module, and obtaining a standard performance value by calculation based on the standard performance value verification value; Step 2: Obtain the battery performance values in the energy storage power station currently sampled by several sampling devices, and perform regression operations on the battery performance values in the energy storage power station and the standard performance values to obtain the correlation mode between each sampling device and the standard performance value; Step 3: By sending the battery performance values sampled by a plurality of sampling devices into the obtained correlation model, the coordinated correction value of the performance value obtained from each type of sampling can be obtained.
[0008] The performance value coordination correction module uses a Gaussian filtering method to filter the battery performance values of the voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station that were previously sampled within a certain set time period and stored in the controller, so as to obtain a standard performance value verification value.
[0009] The standard performance values are obtained by using the mean distribution formula, which is: ; Where: U y (u) is the standard performance value, U yk (u) is the standard performance value verification value, is the number of standard performance value verification values, u is the serial number corresponding to the sampling time point determined according to the order of the sampling time points, and k is the type serial number of the standard performance value verification value.
[0010] The step 2 includes using a high-order equation as a predefined regression equation; using the highest order of a predefined high-order equation, using the smoothing method to determine each order factor of the high-order equation, obtaining the respective regression equations of the battery performance value and the standard performance value in the energy storage power station currently sampled by each sampling device, and obtaining the regression residual between the battery performance value currently sampled and the standard performance value based on the regression equation.
[0011] The performance value coordination correction value is the battery performance value in the energy storage power station after treatment.
[0012] The higher order equation is: ; In the formula, is the battery performance value in the energy storage power station sampled by several sampling devices, b l is each factor of the higher-order equation, is the degree of the higher-order equation, It is the highest degree of a higher-order equation.
[0013] If the regression residual cannot meet the accuracy requirement of the sampling device, the highest order of the higher-order equation is increased until it meets the accuracy requirement. The higher-order equation obtained in this way is the association model between each sampling device and the standard performance value.
[0014] The battery warning device includes a voltage transmitter, a performance value detection transmitter, a humidity transmitter, a smoke transmitter and a buzzer connected to the controller; the voltage transmitter, the performance value detection transmitter, the humidity transmitter and the smoke transmitter are respectively used to sample the voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station and transmit them to the controller, and the controller is used to perform processing on the collected voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station to determine whether the voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station after processing have abnormalities, and if abnormalities occur, the buzzer is operated to warn, and the voltage value, temperature measurement value, humidity value or smoke concentration value of the battery in the energy storage power station is the performance value of the battery in the energy storage power station.
[0015] The operation module of the controller includes a performance value coordination correction module, a regression module and a coordination module; The performance value coordination correction module is used to filter the battery performance values in the energy storage power station, such as the voltage value, temperature value, humidity value and smoke concentration value of the battery in the energy storage power station sampled in a certain set period of time, stored in the controller by using the Gaussian filtering method, so as to obtain the standard performance value verification value; The regression module is used to obtain the battery performance values in the energy storage power station currently sampled by a plurality of sampling devices, and to perform regression operations on the battery performance values in the energy storage power station of the plurality of sampling devices respectively with the standard performance values to obtain the association mode between each sampling device and the standard performance value; The coordination module is used to send the performance values sampled by a plurality of sampling devices into the obtained association mode, so as to obtain the coordination correction value of the performance value obtained from each type of sampling.
[0016] The beneficial effects of the present invention are as follows: initially, a standard performance value verification value of a performance value coordination correction module is obtained, a standard performance value is obtained through calculation of the standard performance value verification value, then the battery performance value of each type of energy storage power station in a plurality of sampling devices is obtained, and the battery performance value of each type of energy storage power station is regressed with the standard performance value to obtain a correlation pattern between the battery performance value of each type of energy storage power station in a plurality of sampling devices and the standard performance value, and the coordination correction value of the performance value of each channel in the plurality of sampling devices is obtained by using the correlation pattern. Unlike the current method, this invention does not perform independent correction on each channel, but concurrently and collaboratively performs sampling values for the same performance value standard. Therefore, during the correction period, there is no distinguishing quantity in the scene condition, device condition, mode, etc., so no deviation caused by the distinguishing quantity effect will be introduced. Therefore, compared with the current method, the coordination correction value of the performance value of each type in the plurality of sampling devices can be obtained more accurately, and the performance value can be obtained more accurately. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Figure 1 : Flow chart of the battery early warning method of the energy storage power station described in the present invention; Figure 2 : Schematic diagram of the operating module architecture of the controller of the battery warning device of the energy storage power station described in the present invention.
[0018] Among them, step is the English expression of step. DETAILED DESCRIPTION
[0019] like Figure 1As shown, a battery early warning method for an energy storage power station includes a voltage transmitter, a performance value detection transmitter, a humidity transmitter, and a smoke transmitter, which respectively sample the voltage value, temperature measurement value, humidity value, and smoke concentration value of the battery in the energy storage power station and transmit them to the controller. The controller processes the collected voltage value, temperature measurement value, humidity value, and smoke concentration value of the battery in the energy storage power station and determines whether the voltage value, temperature measurement value, humidity value, and smoke concentration value of the battery in the energy storage power station after the processing is abnormal. If an abnormality occurs, the buzzer is operated to warn. The voltage value, temperature measurement value, humidity value, or smoke concentration value of the battery in the energy storage power station is the battery performance value in the energy storage power station. The types of battery performance values in the energy storage power station are four types: the voltage value, temperature measurement value, humidity value, and smoke concentration value of the battery in the energy storage power station. The voltage transmitter, temperature detection transmitter, humidity transmitter, and smoke transmitter are corresponding different types of sampling devices. The voltage value, temperature measurement value, humidity value, or smoke concentration value of the battery in the energy storage power station after the processing is the battery performance value in the energy storage power station after the processing.
[0020] The controller processes the collected voltage value, temperature value, humidity value, and smoke concentration value of the battery in the energy storage power station, including: Step 1: obtaining a standard performance value verification value of a performance value coordination correction module, and obtaining a standard performance value by calculation based on the standard performance value verification value; In step 1, the performance value coordination correction module is used to concurrently coordinate the correction of several sampling devices based on the centralized standard performance value measurement, so as to avoid the effects of the scenes, devices, workers, modes and other dimensions introduced by the batch and part correction on the correction value. That is, the Gaussian filtering method is used to filter the battery performance values in the energy storage power station such as the voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station sampled within a set time period stored in the controller, so as to obtain the standard performance value verification value.
[0021] In a preferred but non-limiting implementation method of the present invention, in Step 1, the standard performance value can be obtained by using the mean value arrangement formula, which is: ; In the formula, is the standard performance value, is the standard performance value verification value, is the number of standard performance value verification values, It is the serial number corresponding to the sampling time point determined according to the order of the sampling time points. Is the type number of the standard performance value verification value, The value of is often four.
[0022] In this way, the standard performance value can be obtained through the above mean arrangement formula calculation.
[0023] Step 2: obtaining the battery performance values in the energy storage power station currently sampled by a plurality of sampling devices, and performing regression operations on the battery performance values in the energy storage power station of the plurality of sampling devices respectively with the standard performance values, to obtain the correlation pattern between each sampling device and the standard performance value; Step 2 includes: a plurality of sampling devices including a voltage transmitter, a performance value detection transmitter, a humidity transmitter, and a smoke transmitter respectively sample the voltage value, temperature value, humidity value, and smoke concentration value of the battery in the energy storage power station and transmit them to the controller.
[0024] Ability to use higher-order equations as pre-defined regression equations; The higher order equation is:
[0025] Where: It is the battery performance value in the energy storage power station sampled by several sampling devices. is each factor of the higher-order equation, is the degree of the higher-order equation, It is the highest degree of a higher-order equation.
[0026] Then, through the highest degree of a high-order equation defined in advance, the smoothing method is used to identify each degree factor of the high-order equation, and the regression equations of the battery performance value and the standard performance value in the energy storage power station currently sampled by each sampling device are obtained. According to the regression equation, the regression residual between the battery performance value currently sampled and the standard performance value can be obtained.
[0027] Step 2 also includes: the regression residual must be at least one order of magnitude higher than the accuracy requirement of the sampling device. If the regression residual cannot meet the accuracy requirement of the sampling device, the maximum order of the high-order equation is increased until it meets the accuracy requirement. The high-order equation obtained in this way is the association pattern between each sampling device and the standard performance value.
[0028] Step 3: In the actual application of performance value balance, the performance values sampled by several sampling devices are sent into the obtained correlation model to obtain the coordinated correction value of the performance value from each type of sampling.
[0029] The performance value coordination correction value is the battery performance value in the energy storage power station after treatment.
[0030] like Figure 2As shown, a battery early warning device for an energy storage power station includes a voltage transmitter, a performance value detection transmitter, a humidity transmitter, a smoke transmitter and a buzzer connected to a controller. The voltage transmitter, the performance value detection transmitter, the humidity transmitter and the smoke transmitter are respectively used to sample the voltage value, the temperature measurement value, the humidity value and the smoke concentration value of the battery in the energy storage power station and transmit them to the controller. The controller is used to perform processing on the collected voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station and determine whether the voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station after processing have abnormalities. If abnormalities occur, the buzzer is operated to warn. The voltage value, temperature measurement value, humidity value or smoke concentration value of the battery in the energy storage power station is the performance value of the battery in the energy storage power station.
[0031] The modules running on the controller include the operating modules of the controller, including the performance value coordination correction module, the regression module and the coordination module. The performance value coordination correction module is used to filter the battery performance values in the energy storage power station, such as the voltage value, temperature value, humidity value and smoke concentration value of the battery in the energy storage power station, which are previously sampled in a certain set period and stored in the controller by using the Gaussian filtering method, so as to obtain the standard performance value verification value; the regression module is used to obtain the battery performance values in the energy storage power station currently sampled by several sampling devices, and perform regression operations with the standard performance values according to the battery performance values in the energy storage power station of the several sampling devices, so as to obtain the association mode of each sampling device and the standard performance value; the coordination module is used to send the performance values sampled by several sampling devices into the obtained association mode, so as to obtain the coordination correction value of the performance value from each type of sampling.
[0032] In order to meet the sampling accuracy requirements, it is necessary to ensure the accuracy of the sampling device used through the optimization processing method of the strict standard system. The current common method is to ensure the accuracy of each sampling device to meet the accuracy requirements of different types of performance value sampling. However, the defect of this method is that different types of performance values are corrected one by one, rather than concurrently and collaboratively performing sampling values for the same performance value standard. During different correction periods, the role of differentiating quantities in dimensions such as scenes, devices, workers, and modes will be introduced. For the strict requirements of accuracy sampling, the differentiating quantities cannot be ignored. The present application initially obtains the standard performance value verification value of the performance value coordination correction module, obtains the standard performance value through the standard performance value verification value calculation, and then obtains several The battery performance value of each type of energy storage power station in the sampling device is regressed with the standard performance value to obtain the correlation pattern between the battery performance value of each type of energy storage power station in the several sampling devices and the standard performance value, and the coordination correction value of the performance value of each channel in the several sampling devices is obtained by using the correlation pattern. Unlike the current method, this method does not perform independent correction on each channel, but concurrently and collaboratively performs sampling values for the same performance value standard. Therefore, during the correction period, there is no distinguishing quantity in the scene condition, device condition, mode, etc., so no deviation caused by the distinguishing quantity effect will be introduced. Therefore, compared with the current method, the coordination correction value of each type of performance value in the several sampling devices can be obtained more accurately.
[0033] Here, each type of performance value has different sampling attributes. If different sampling types are corrected one after another, the effects of scene, device, worker, mode and other dimensional differences on the correction value will be introduced. The correction method in the present invention is based on the centralized performance value standard, and the correction of each sampling channel is achieved in parallel and collaboratively. Such correction values can more truly reflect the coordination attributes between different sampling types.
[0034] The present invention aims at correcting the defects of coordination properties between different types, and achieves coordination correction of several sampling devices through a correction device with a centralized performance value standard to correct different sampling types of sampling devices, thereby avoiding the effects of different correction processes and the introduction of different dimensions such as devices, workers, and modes.
[0035] The present invention is disclosed as a system, method and / or computer program product. The computer program product can include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement each aspect of the present disclosure.
[0036] A computer-readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium can be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the above. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (such as, a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.
[0037] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.
[0038] The computer program instructions for performing the disclosed operations of the present invention can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, etc., and conventional procedural programming languages such as "C" language or similar programming languages. Computer-readable program instructions can be executed entirely on the controller computer, partially on the controller computer, as a separate software package, partially on the controller computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the controller computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (just as using an Internet service provider to connect through the Internet). In some embodiments, each aspect of the present disclosure is implemented by utilizing state information of computer-readable program instructions to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), which can execute computer-readable program instructions.
[0039] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.
Claims
1. A battery early warning method for an energy storage power station, characterized in that: The battery early warning method is to sample the voltage value, temperature value, humidity value and smoke concentration value of the battery in the energy storage power station through the voltage transmitter, the performance value detection transmitter, the humidity transmitter and the smoke transmitter respectively and transmit them to the controller; after the controller processes the collected voltage value, temperature value, humidity value and smoke concentration value, it is determined whether the voltage value, temperature value, humidity value and smoke concentration value of the battery in the energy storage power station after the processing are abnormal, and if they are abnormal, the buzzer is operated to warn; The process of the controller performing processing on the received voltage value, temperature value, humidity value and smoke concentration value includes the following steps: Step 1: obtaining a standard performance value verification value of a performance value coordination correction module, and obtaining a standard performance value by calculation based on the standard performance value verification value; Step 2: Obtain the battery performance values in the energy storage power station currently sampled by several sampling devices, and perform regression operations on the battery performance values in the energy storage power station and the standard performance values to obtain the correlation mode between each sampling device and the standard performance value; Step 3: By sending the battery performance values sampled by a plurality of sampling devices into the obtained correlation model, the coordinated correction value of the performance value obtained from each type of sampling can be obtained.
2. A battery early warning method for an energy storage power station according to claim 1, characterized in that: The performance value coordination correction module uses a Gaussian filtering method to filter the battery performance values of the voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station that were previously sampled within a certain set time period and stored in the controller, so as to obtain a standard performance value verification value.
3. The battery early warning method of an energy storage power station according to claim 1, characterized in that: The standard performance values are obtained by using the mean distribution formula, which is: ; Where: U y (u) is the standard performance value, U yk (u) is the standard performance value verification value, is the number of standard performance value verification values, u is the serial number corresponding to the sampling time point determined according to the order of the sampling time points, and k is the type serial number of the standard performance value verification value.
4. The battery early warning method of an energy storage power station according to claim 1, characterized in that: The step 2 includes using a high-order equation as a predefined regression equation; using the highest order of a predefined high-order equation, using the smoothing method to determine each order factor of the high-order equation, obtaining the respective regression equations of the battery performance value and the standard performance value in the energy storage power station currently sampled by each sampling device, and obtaining the regression residual between the battery performance value currently sampled and the standard performance value based on the regression equation.
5. The battery early warning method of an energy storage power station according to claim 1, characterized in that: The performance value coordination correction value is the battery performance value in the energy storage power station after treatment.
6. A battery early warning method for an energy storage power station according to claim 4, characterized in that: The higher order equation is: ; In the formula, is the battery performance value in the energy storage power station sampled by several sampling devices, b l is each factor of the higher-order equation, is the degree of the higher-order equation, It is the highest degree of a higher-order equation.
7. A battery early warning method for an energy storage power station according to claim 4, characterized in that: If the regression residual cannot meet the accuracy requirement of the sampling device, the highest order of the higher-order equation is increased until it meets the accuracy requirement. The higher-order equation obtained in this way is the association model between each sampling device and the standard performance value.
8. A battery early warning device for an energy storage power station, characterized in that: The battery warning device includes a voltage transmitter, a performance value detection transmitter, a humidity transmitter, a smoke transmitter and a buzzer connected to the controller; the voltage transmitter, the performance value detection transmitter, the humidity transmitter and the smoke transmitter are respectively used to sample the voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station and transmit them to the controller, and the controller is used to perform processing on the collected voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station to determine whether the voltage value, temperature measurement value, humidity value and smoke concentration value of the battery in the energy storage power station after processing have abnormalities, and if abnormalities occur, the buzzer is operated to warn, and the voltage value, temperature measurement value, humidity value or smoke concentration value of the battery in the energy storage power station is the performance value of the battery in the energy storage power station.
9. A battery warning device for an energy storage power station according to claim 8, characterized in that: The operation module of the controller includes a performance value coordination correction module, a regression module and a coordination module; The performance value coordination correction module is used to filter the battery performance values in the energy storage power station, such as the voltage value, temperature value, humidity value and smoke concentration value of the battery in the energy storage power station sampled in a certain set period of time, stored in the controller by using the Gaussian filtering method, so as to obtain the standard performance value verification value; The regression module is used to obtain the battery performance values in the energy storage power station currently sampled by a plurality of sampling devices, and to perform regression operations on the battery performance values in the energy storage power station of the plurality of sampling devices respectively with the standard performance values to obtain the association mode between each sampling device and the standard performance value; The coordination module is used to send the performance values sampled by a plurality of sampling devices into the obtained association mode, so as to obtain the coordination correction value of the performance value obtained from each type of sampling.