CN116359763A - Intelligent analysis method and device for chemical component capacity energy consumption - Google Patents

Intelligent analysis method and device for chemical component capacity energy consumption Download PDF

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Publication number
CN116359763A
CN116359763A CN202310638656.5A CN202310638656A CN116359763A CN 116359763 A CN116359763 A CN 116359763A CN 202310638656 A CN202310638656 A CN 202310638656A CN 116359763 A CN116359763 A CN 116359763A
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module
data
energy consumption
analysis
production line
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CN116359763B (en
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华麟
李�浩
陈燚平
陈成
李东升
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Shenzhen Herunda Technology Co ltd
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Shenzhen Herunda Technology Co ltd
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    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/44—Methods for charging or discharging
    • H01M10/446—Initial charging measures
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G01R31/387—Determining ampere-hour charge capacity or SoC
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/05—Accumulators with non-aqueous electrolyte
    • H01M10/052—Li-accumulators
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/05—Accumulators with non-aqueous electrolyte
    • H01M10/058—Construction or manufacture

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  • Manufacturing & Machinery (AREA)
  • Chemical & Material Sciences (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Electrochemistry (AREA)
  • General Chemical & Material Sciences (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Secondary Cells (AREA)

Abstract

The invention discloses an intelligent analysis method and device for chemical composition energy consumption, wherein the method comprises the following steps: acquiring module data corresponding to the parallelization and composition operation of a plurality of modules in the automatic power battery production line in real time; calculating parameter data corresponding to a plurality of electrical parameters of each module in real time, wherein the parameter data at least comprises energy consumption data; performing analysis optimization operation on all parameter data according to the acquired optimization reference data of the power supply system to obtain analysis optimization results, wherein the analysis optimization results comprise a step optimization result of a step flow for at least one module and/or an energy consumption optimization result of energy consumption data for at least one module; and then, performing comparative analysis operation according to the acquired process comparison data and analysis optimization results to obtain electricity-saving data serving as analysis data for accounting carbon data for the automatic production line of the power battery. Therefore, the method and the device can improve the determination efficiency and the determination accuracy of the energy consumption data of the automatic production line of the power battery.

Description

Intelligent analysis method and device for chemical component capacity energy consumption
Technical Field
The invention relates to the technical field of formation and capacity-division data intelligent processing, in particular to an intelligent analysis method and device for formation and capacity-division energy consumption.
Background
Along with the application of the automatic production line of the power battery, the improvement of the formation and capacity-dividing efficiency is more and more important. In practical application, the battery cell of the lithium battery must be charged and activated after the assembly is completed, and the first charging process of the battery cell is called formation, and is used for activating the active material in the battery cell to generate an SEI film (i.e. SolidElectrolyte Interface, solid electrolyte interface film). The battery cells are subjected to formation and then are subjected to capacity division, and the capacity division is to charge and discharge the formed battery cells so as to detect the performance of the battery cells, so that the battery cells are conveniently graded and assembled according to the capacity.
At present, formation and capacity division of the battery cell are mainly realized through a preset process step file, and in the specific formation and capacity division process, the charging and discharging of the battery cell are usually realized through a set power circuit. Based on the processing requirement of mass data of the automatic power battery production line, it is necessary to maintain the electrical parameters of the automatic power battery production line, and the electrical parameter processing scheme corresponding to the automatic power battery production line is approximately as follows:
and when the energy consumption analysis is needed, the electric parameters related to the energy consumption analysis are extracted from the massive electric parameters of the database for analysis, so that the analysis difficulty is high and the analysis efficiency is low. In addition, if the energy consumption of each electric core in the analysis production line needs to be refined, the electric parameters required in the formation/capacity separation process are optimized and adjusted, the energy consumption data of each electric core needs to be subdivided on the basis of the original electric parameters, then the relevant analysis of the energy consumption of the electric core is performed, a large amount of resources are consumed, and meanwhile, the accuracy of the finally obtained energy consumption analysis result is low. Therefore, it is important to provide a method for improving the energy consumption data determining efficiency and accuracy of the automatic power battery production line.
Disclosure of Invention
The invention aims to solve the technical problem of providing an intelligent analysis method and device for the chemical composition energy consumption, which can improve the energy consumption data determination efficiency and accuracy of an automatic power battery production line and simultaneously provide guidance data support for optimizing a production process, the energy utilization rate and the like.
In order to solve the technical problems, the first aspect of the invention discloses an intelligent analysis method for chemical composition energy consumption, which comprises the following steps:
collecting electric data corresponding to a power battery automatic production line to be analyzed in real time, wherein the power battery automatic production line is provided with a plurality of modules, the electric data comprises module data corresponding to a plurality of modules performing a formation operation according to a preset process flow, and all the modules comprise the modules;
for each module, calculating parameter data corresponding to each electrical parameter of the module in real time according to the module data corresponding to the module and combining a plurality of preset electrical parameters, wherein the parameter data corresponding to each module at least comprises energy consumption data after the module executes the chemical composition operation;
acquiring optimization reference data of a power supply system corresponding to the automatic power battery production line, and executing analysis optimization operation on all the parameter data according to the optimization reference data to obtain analysis optimization results of all the parameter data, wherein the analysis optimization results of all the parameter data comprise a step optimization result of the step process corresponding to at least one module and/or an energy consumption optimization result of the energy consumption data corresponding to at least one module;
And obtaining process comparison data corresponding to the automatic power battery production line, and executing comparison analysis operation according to the process comparison data and the analysis and optimization result to obtain electricity-saving data of the automatic power battery production line after executing the analysis and optimization operation, wherein the electricity-saving data is used as analysis data for accounting the carbon data of the automatic power battery production line.
As an optional implementation manner, in the first aspect of the present invention, the collecting, in real time, electric data corresponding to an automated power battery production line to be analyzed includes:
determining all modules to be analyzed currently in the automatic power battery production line, and collecting the step information of each module in real time, wherein the step information of each module comprises first information and second information corresponding to formation and composition operations executed by each electric core in the module according to a preset step flow in a current real-time monitoring period, and the first information comprises a first operation period of the formation operation executed by each electric core and power consumption data corresponding to each first operation period; the second information comprises a second operation period corresponding to each battery cell executing capacity-dividing operation and feed data corresponding to each second operation period;
And for each module, determining the power consumption data and the feed data corresponding to all the battery cells in the module as module data of the module, and taking the module data as electric data corresponding to an automatic production line of the power battery.
As an optional implementation manner, in the first aspect of the present invention, the electrical parameter includes at least one electrical parameter of a formation electrical parameter, a capacity-division electrical parameter, an actual electrical parameter, and an energy consumption and production parameter corresponding to a unit energy consumption production cell capacity;
for each module, according to the module data corresponding to the module, combining a plurality of preset electrical parameters, calculating parameter data corresponding to the module and each electrical parameter in real time, including:
for each electric core in each module, calculating to obtain comprehensive power consumption data corresponding to the electric core and the first information and comprehensive feed data corresponding to the second information according to the first information and the second information corresponding to the electric core;
calculating the difference between the comprehensive power consumption data and the comprehensive feed data corresponding to the battery cell to obtain actual power consumption data corresponding to the actual power consumption parameters of the battery cell; calculating the ratio of the battery cell capacity corresponding to the battery cell to the actual power consumption data to obtain battery cell energy consumption data corresponding to the battery cell;
For each module, multiplying the energy consumption data of the battery core corresponding to each battery core in the module by the product coefficient corresponding to the battery core, and comprehensively calculating to obtain the module energy consumption data corresponding to the module; and determining the comprehensive power consumption data, the comprehensive feed data and the module energy consumption data corresponding to the module as parameter data of the module.
As an optional implementation manner, in the first aspect of the present invention, the process comparison data includes historical energy consumption analysis data of the power battery automation line in a preset backtracking period; the duration of the preset backtracking period is greater than or equal to the duration of the real-time monitoring period, and the preset backtracking period corresponds to the real-time monitoring period;
and performing a comparison analysis operation according to the process comparison data and the analysis optimization result to obtain electricity saving data of the power battery automatic production line after performing the analysis optimization operation, wherein the electricity saving data comprises:
calculating an energy consumption difference value between the historical energy consumption analysis data and the analysis optimization result, and calculating a power saving value corresponding to the power battery automatic production line after the preset backtracking period is separated from the power battery automatic production line according to the energy consumption difference value and a preset carbon conversion coefficient when the energy consumption difference value indicates that the historical energy consumption analysis data is higher than the analysis optimization result;
And generating electricity-saving data aiming at the automatic power battery production line according to the electricity-saving value and the carbon-saving value.
As an optional implementation manner, in the first aspect of the present invention, the process comparison data further includes a historical process step management scheme executed for each of the modules in the preset backtracking period; when the energy consumption difference value represents that the historical energy consumption analysis data is lower than or equal to the analysis optimization result, the method further comprises:
analyzing the historical energy consumption analysis data corresponding to each battery cell in all the modules to obtain at least one module to be optimized, wherein the energy consumption difference value between the energy consumption data corresponding to the module to be optimized and the historical energy consumption analysis data corresponding to the module to be optimized is larger than a preset standard difference value;
according to a preset power saving optimization scheme, combining the historical process step management and control scheme corresponding to each module to be optimized, and generating process step optimization information aiming at each module to be optimized as power saving data after the analysis and optimization operation is executed by the automatic power battery production line.
As an alternative embodiment, in the first aspect of the present invention, the optimization reference data of the power supply system includes a module load operation characteristic and/or a power efficiency characteristic; the power supply system comprises a plurality of load modules and a load module group constructed by the plurality of load modules, wherein any one of the process steps calls at least one load module group;
The module load operation characteristics comprise load operation characteristics corresponding to each load module group;
when any load module group is called by different sub-process flows, the load operation characteristic corresponding to the load module group is matched with the process step requirement corresponding to the current sub-process flow.
As an optional implementation manner, in the first aspect of the present invention, the module data corresponding to each module includes a cell identifier of each cell in the module, where the cell identifier is used to determine a cell state of the cell, and the cell state includes an active state or an inactive state in which a cell activation operation has been performed on the cell;
for each module, performing hierarchical division on each battery cell according to the battery cell state corresponding to each battery cell in the module, wherein each module comprises at least two division levels, and the battery cells in the activated state and the deactivated state correspond to one division level respectively;
and when the number of the levels corresponding to the division levels is larger than 2, determining at least three division sets by taking the formation component execution times as a reference, wherein each division set corresponds to one formation component execution time interval.
The second aspect of the invention discloses an intelligent analysis device for the energy consumption of chemical composition, which comprises:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring electric data corresponding to a power battery automatic production line to be analyzed in real time, the power battery automatic production line is provided with a plurality of modules, the electric data comprises module data corresponding to a plurality of modules which execute a partitioning operation according to a preset process flow, and all the modules comprise the modules;
the calculation module is used for calculating the parameter data corresponding to each electric parameter of the module in real time according to the module data corresponding to the module and a plurality of preset electric parameters, and the parameter data corresponding to each module at least comprises the energy consumption data after the module executes the formation component operation;
the acquisition module is used for acquiring the optimized reference data of the power system corresponding to the automatic power battery production line;
the analysis optimization module is used for executing analysis optimization operation on all the parameter data according to the optimization reference data to obtain analysis optimization results of all the parameter data, wherein the analysis optimization results of all the parameter data comprise a step optimization result of the step flow corresponding to at least one module and/or an energy consumption optimization result of the energy consumption data corresponding to at least one module;
The acquisition module is also used for acquiring process comparison data corresponding to the automatic power battery production line;
and the comparison analysis module is used for executing comparison analysis operation according to the process comparison data and the analysis optimization result to obtain electricity-saving data of the power battery automatic production line after executing the analysis optimization operation, and the electricity-saving data is used as analysis data for accounting the carbon data of the power battery automatic production line.
In a second aspect of the present invention, the method for collecting, by the collecting module, the electrical data corresponding to the automated power battery production line to be analyzed in real time specifically includes:
determining all modules to be analyzed currently in the automatic power battery production line, and collecting the step information of each module in real time, wherein the step information of each module comprises first information and second information corresponding to formation and composition operations executed by each electric core in the module according to a preset step flow in a current real-time monitoring period, and the first information comprises a first operation period of the formation operation executed by each electric core and power consumption data corresponding to each first operation period; the second information comprises a second operation period corresponding to each battery cell executing capacity-dividing operation and feed data corresponding to each second operation period;
And for each module, determining the power consumption data and the feed data corresponding to all the battery cells in the module as module data of the module, and taking the module data as parameter data corresponding to an automatic production line of the power battery.
In a second aspect of the present invention, the electrical parameter includes at least one electrical parameter of a formation electrical parameter, a capacity-division electrical parameter, an actual electrical parameter, and an energy consumption and production parameter corresponding to a capacity of a unit energy consumption production cell;
the calculation module combines a plurality of preset electric parameters for each module according to the module data corresponding to the module, and the mode of calculating the parameter data corresponding to the module and each electric parameter in real time specifically comprises the following steps:
for each electric core in each module, calculating to obtain comprehensive power consumption data corresponding to the electric core and the first information and comprehensive feed data corresponding to the second information according to the first information and the second information corresponding to the electric core;
calculating the difference between the comprehensive power consumption data and the comprehensive feed data corresponding to the battery cell to obtain actual power consumption data corresponding to the actual power consumption parameters of the battery cell; calculating the ratio of the battery cell capacity corresponding to the battery cell to the actual power consumption data to obtain battery cell energy consumption data corresponding to the battery cell;
For each module, multiplying the energy consumption data of the battery core corresponding to each battery core in the module by the product coefficient corresponding to the battery core, and comprehensively calculating to obtain the module energy consumption data corresponding to the module; and determining the comprehensive power consumption data, the comprehensive feed data and the module energy consumption data corresponding to the module as parameter data of the module.
As an optional implementation manner, in the second aspect of the present invention, the process comparison data includes historical energy consumption analysis data of the power battery automation line in a preset backtracking period; the duration of the preset backtracking period is greater than or equal to the duration of the real-time monitoring period, and the preset backtracking period corresponds to the real-time monitoring period;
the comparison analysis module executes comparison analysis operation according to the process comparison data and the analysis optimization result, and the power saving data after the analysis optimization operation is executed by the automatic power battery production line is obtained by the steps of:
calculating an energy consumption difference value between the historical energy consumption analysis data and the analysis optimization result, and calculating a power saving value corresponding to the power battery automatic production line after the preset backtracking period is separated from the power battery automatic production line according to the energy consumption difference value and a preset carbon conversion coefficient when the energy consumption difference value indicates that the historical energy consumption analysis data is higher than the analysis optimization result;
And generating electricity-saving data aiming at the automatic power battery production line according to the electricity-saving value and the carbon-saving value.
As an optional implementation manner, in the second aspect of the present invention, the process comparison data further includes a historical process step management scheme performed for each of the modules in the preset backtracking period;
the comparison analysis module executes comparison analysis operation according to the process comparison data and the analysis optimization result, and the method for obtaining the electricity-saving data of the power battery automatic production line after executing the analysis optimization operation specifically further comprises the following steps:
when the energy consumption difference value represents that the historical energy consumption analysis data is lower than or equal to the analysis optimization result, analyzing the historical energy consumption analysis data corresponding to each cell in all the modules to obtain at least one module to be optimized, wherein the energy consumption difference value between the energy consumption data corresponding to the module to be optimized and the historical energy consumption analysis data corresponding to the module to be optimized is larger than a preset standard difference value;
according to a preset power saving optimization scheme, combining the historical process step management and control scheme corresponding to each module to be optimized, and generating process step optimization information aiming at each module to be optimized as power saving data after the analysis and optimization operation is executed by the automatic power battery production line.
As an alternative embodiment, in the second aspect of the present invention, the optimized reference data of the power supply system includes a module load operation characteristic and/or a power efficiency characteristic; the power supply system comprises a plurality of load modules and a load module group constructed by the plurality of load modules, wherein any one of the process steps calls at least one load module group;
the module load operation characteristics comprise load operation characteristics corresponding to each load module group;
when any load module group is called by different sub-process flows, the load operation characteristic corresponding to the load module group is matched with the process step requirement corresponding to the current sub-process flow.
As an optional implementation manner, in the second aspect of the present invention, the module data corresponding to each module includes a cell identifier of each cell in the module, where the cell identifier is used to determine a cell state of the cell, and the cell state includes an active state or an inactive state in which a cell activation operation has been performed on the cell;
for each module, performing hierarchical division on each battery cell according to the battery cell state corresponding to each battery cell in the module, wherein each module comprises at least two division levels, and the battery cells in the activated state and the deactivated state correspond to one division level respectively;
And when the number of the levels corresponding to the division levels is larger than 2, determining at least three division sets by taking the formation component execution times as a reference, wherein each division set corresponds to one formation component execution time interval.
In a third aspect, the invention discloses another intelligent analysis device for the energy consumption of chemical composition, the device comprising:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the intelligent analysis method for the chemical component energy consumption disclosed in the first aspect of the present invention.
A fourth aspect of the invention discloses a computer storage medium storing computer instructions which, when invoked, are adapted to perform the intelligent analysis method of the chemical composition energy consumption disclosed in the first aspect of the invention.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
in an embodiment of the present invention, an intelligent analysis method for forming energy consumption of a component is provided, where the method includes: collecting electric data corresponding to a power battery automatic production line to be analyzed in real time, wherein the power battery automatic production line is provided with a plurality of modules, the electric data comprises module data corresponding to a plurality of modules which execute a composition operation according to a preset process flow, and all the modules comprise modules; for each module, calculating parameter data corresponding to each electrical parameter of the module in real time according to module data corresponding to the module and a plurality of preset electrical parameters, wherein the parameter data corresponding to each module at least comprises energy consumption data after the module performs a parallelization operation; acquiring optimization reference data of a power supply system corresponding to an automatic power battery production line, and executing analysis optimization operation on all parameter data according to the optimization reference data to obtain analysis optimization results of all parameter data, wherein the analysis optimization results of all parameter data comprise a process step optimization result of a process step flow corresponding to at least one module and/or an energy consumption optimization result of energy consumption data corresponding to at least one module; and obtaining process comparison data corresponding to the automatic power battery production line, and executing comparison analysis operation according to the process comparison data and the analysis optimization result to obtain electricity-saving data after the automatic power battery production line executes the analysis optimization operation, wherein the electricity-saving data is used as analysis data for accounting carbon data for the automatic power battery production line. Therefore, the method can realize the real-time acquisition of the corresponding electric data of the automatic production line of the power battery, is different from the traditional simple recording of important data of the production line, and performs screening and calling from mass data of a database when the data are required to be called, and the timeliness and the data calling efficiency of the electric data are improved by the real-time data acquisition mode; furthermore, after the electric data are collected in real time, the parameter data comprising the energy consumption data can be calculated in real time by combining a plurality of electric parameters, so that the real-time energy consumption analysis of the electric data corresponding to the module is realized, meanwhile, the analysis optimization is automatically executed on all the parameter data based on the obtained optimized reference data, the intelligent analysis optimization of the power battery automatic production line related parameter data is realized, and the analysis optimization efficiency and the analysis optimization accuracy of the parameter data are improved; and then, the obtained process comparison data can be intelligently compared with an analysis optimization result to obtain electricity-saving data, so that the intelligent comparison of the optimization effect of the electricity data is realized, and finally the obtained electricity-saving data can be used as analysis data for accounting the carbon data of the automatic production line of the power battery, and the accounting efficiency of carbon accounting is improved to a certain extent.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an intelligent analysis method for the energy consumption of chemical composition according to an embodiment of the invention;
FIG. 2 is a flow chart of another intelligent analysis method for chemical composition energy consumption disclosed in an embodiment of the present invention;
FIG. 3 is a schematic diagram of an intelligent analysis device for the formation of component energy consumption according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of another intelligent analysis device for the chemical composition energy consumption according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a modular load operating characteristic of a power system according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a power efficiency characteristic of a power system according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of power corresponding to a charge/discharge operation in a chemical composition process flow according to an embodiment of the present invention;
FIG. 8 is a flow chart of another intelligent analysis method for the chemical composition energy consumption according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or article.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The invention discloses an intelligent analysis method and device for chemical composition energy consumption, which can realize real-time acquisition of corresponding electric data of an automatic production line of a power battery, is different from the traditional method for simply recording important data of the production line, and performs screening and calling from mass data of a database when the data are required to be called, and improves timeliness and data calling efficiency of the electric data in a real-time data acquisition mode; furthermore, after the electric data are collected in real time, the parameter data comprising the energy consumption data can be calculated in real time by combining a plurality of electric parameters, so that the real-time energy consumption analysis of the electric data corresponding to the module is realized, meanwhile, the analysis optimization is automatically executed on all the parameter data based on the obtained optimized reference data, the intelligent analysis optimization of the power battery automatic production line related parameter data is realized, and the analysis optimization efficiency and the analysis optimization accuracy of the parameter data are improved; and then, the obtained process comparison data can be intelligently compared with an analysis optimization result to obtain electricity-saving data, so that the intelligent comparison of the optimization effect of the electricity data is realized, and finally the obtained electricity-saving data can be used as analysis data for accounting the carbon data of the automatic production line of the power battery, and the accounting efficiency of carbon accounting is improved. The following will describe in detail.
Example 1
Referring to fig. 1, fig. 1 is a flow chart of an intelligent analysis method for component energy consumption in accordance with an embodiment of the present invention. The intelligent analysis method of the formation component energy consumption described in fig. 1 can be applied to an intelligent analysis device of the formation component energy consumption, and optionally, the method can also be applied to formation/capacity separation equipment in an automatic power battery production line, such as a formation/capacity separation integrated machine, and the embodiment of the invention is not limited. As shown in fig. 1, the intelligent analysis method for the chemical composition energy consumption may include the following operations:
101. and acquiring electric data corresponding to the automatic power battery production line to be analyzed in real time.
In the embodiment of the invention, the power battery automatic production line is provided with a plurality of modules, and the electric data comprises module data corresponding to the module data which are formed by the modules according to the preset process flow.
In the embodiment of the invention, the module data corresponding to each module comprises a battery core identifier of each battery core in the module, wherein the battery core identifier is used for determining the battery core state of the battery core, and the battery core state comprises an activated state or a non-activated state of executing battery core activation operation on the battery core;
for each module, according to the state of each cell in the module, performing hierarchical division on each cell, wherein each module comprises at least two division levels, and the cells in an activated state and a non-activated state correspond to one division level respectively;
When the number of the corresponding divided levels is larger than 2, at least three divided sets are determined based on the number of the divided component execution times, and each divided set corresponds to one divided component execution time interval.
In the embodiment of the invention, specific to the division of different battery cell states, all the battery cells in the inactive state correspond to one division set and storage partition; all the active cells correspond to other partition sets and storage partitions; for example, the number of times of performing the formation is (0, 50) times as the first division set, and (50, 100) times as the second division set, and the number of times of performing the formation corresponding to each division set is not limited in the embodiment of the present invention.
In the embodiment of the invention, preferably, the cell identifier of each cell can be an identifier updated in real time, and the cell is not required to be divided and placed from a physical storage position at this time, and only the cell is required to perform the formation times accumulation 1 on the cell identifier of the cell automatically every time the cell performs the formation operation, so that the embodiment of the invention is not limited.
102. For each module, according to the module data corresponding to the module, combining a plurality of preset electric parameters, and calculating the parameter data corresponding to each electric parameter of the module in real time.
In the embodiment of the invention, the parameter data corresponding to each module at least comprises the energy consumption data after the module performs the formation operation.
103. And obtaining optimization reference data of a power supply system corresponding to the automatic power battery production line, and executing analysis optimization operation on all parameter data according to the optimization reference data to obtain analysis optimization results of all parameter data.
In the embodiment of the invention, the analysis and optimization result of all the parameter data comprises a process step optimization result of a process step flow corresponding to at least one module and/or an energy consumption optimization result of energy consumption data corresponding to at least one module.
In the embodiment of the present invention, please refer to fig. 5 and fig. 6, fig. 5 is a schematic diagram of a module load operation characteristic of a power supply system according to the embodiment of the present invention; fig. 6 is a schematic diagram of a power efficiency characteristic of a power supply system according to an embodiment of the present invention. Optionally, the optimization reference data of the power supply system includes module load operating characteristics and/or power efficiency characteristics; the power supply system comprises a plurality of load modules and a load module group constructed by the plurality of load modules, and at least one load module group is called by any one sub-process flow in the process flow.
In the embodiment of the invention, the module load operation characteristics comprise load operation characteristics corresponding to each load module group, and as shown in fig. 5, the load rates corresponding to single module operation, double module operation, three module operation, five module operation and six module operation are different; and the power supply efficiency also changes under different load rates. As shown in fig. 6, the load factor increases corresponding to an inefficient area where the power efficiency increases rapidly; and as the load rate increases, the load rate corresponds to a high-efficiency area which slowly decreases after the power efficiency is slowly increased.
In the embodiment of the invention, when any load module group is called by different sub-process flows, the load operation characteristic corresponding to the load module group is matched with the process step requirement corresponding to the current sub-process flow.
Taking any sub-process flow as an example, after the optimization reference data of the power supply system is obtained, according to all load module groups currently called by the sub-process flow and load operation characteristics corresponding to all load module groups, the information of power consumption optimization of the sub-process flow is obtained by independent analysis, wherein the information can be information indicating the number of the load module groups to be called, such as the current call load module group A, B, C, D; after analysis, the load module group A, B, C is regulated to be called only on the premise of not influencing the normal operation of the sub-process flow; alternatively, the information may refer to adjusting the operation time of each load module group, and the embodiment of the present invention is not limited.
In the embodiment of the present invention, when the operation period of each load module group is adjusted, the operation period of all load module groups called by the sub-process flow is adjusted by combining the power efficiency characteristic of the power system in fig. 8.
104. And obtaining process comparison data corresponding to the automatic power battery production line, and executing comparison analysis operation according to the process comparison data and the analysis optimization result to obtain electricity-saving data after the automatic power battery production line executes the analysis optimization operation, wherein the electricity-saving data is used as analysis data for accounting carbon data for the automatic power battery production line.
Therefore, by implementing the intelligent analysis method for the chemical composition energy consumption described in fig. 1, the real-time acquisition of the corresponding electric data of the automatic power battery production line can be realized, which is different from the traditional simple recording of important data of the production line, and when the data needs to be called, screening and calling are performed from the mass data of the database, and the timeliness and the data calling efficiency of the electric data are improved by the real-time data acquisition mode; furthermore, after the electric data are collected in real time, the parameter data comprising the energy consumption data can be calculated in real time by combining a plurality of electric parameters, so that the real-time energy consumption analysis of the electric data corresponding to the module is realized, meanwhile, the analysis optimization is automatically executed on all the parameter data based on the obtained optimized reference data, the intelligent analysis optimization of the power battery automatic production line related parameter data is realized, and the analysis optimization efficiency and the analysis optimization accuracy of the parameter data are improved; and then, the obtained process comparison data can be intelligently compared with an analysis optimization result to obtain electricity-saving data, so that the intelligent comparison of the optimization effect of the electricity data is realized, and finally the obtained electricity-saving data can be used as analysis data for accounting the carbon data of the automatic production line of the power battery, and the accounting efficiency of carbon accounting is improved to a certain extent.
In an alternative embodiment, the method of collecting, in real time, the electrical data corresponding to the automated power battery production line to be analyzed in step 101 specifically includes:
determining all modules to be analyzed currently in an automatic power battery production line, and collecting the process step information of each module in real time, wherein the process step information of each module comprises first information and second information corresponding to formation and composition operation of each battery cell in the module according to a preset process step flow in a current real-time monitoring period, and the first information comprises a first operation period of formation and formation operation of each battery cell and power consumption data corresponding to each first operation period; the second information comprises a second operation period corresponding to the capacity-dividing operation of each cell and feed data corresponding to each second operation period;
and for each module, determining the power consumption data and the feed data corresponding to all the battery cells in the module as the module data of the module, and taking the module data as the electric data corresponding to the automatic power battery production line.
In this alternative embodiment, the step information of each module may be collected in real time, and fig. 7 is a schematic diagram of the power corresponding to the charging/discharging operation in the process of forming the component step according to the embodiment of the present invention. For any module, actually collecting the published information of each module may refer to collecting the charging power, the charging duration corresponding to the charging power, the discharging (feeding) power and the discharging duration corresponding to the discharging (feeding) power of each electric core in the module in real time, which is not limited in the embodiment of the present invention.
Therefore, in the optional embodiment, when collecting the electrical data in real time, the method can be subdivided into collecting the published information of each module, the first information and the second information of each electric core in each module, and the fine data monitoring and collecting mode improves the timeliness and accuracy of collecting the data of each electric core in the automatic production line of the power battery; in addition, the method can also distinguish and collect operation information corresponding to the battery cell performing formation operation and capacity division operation, and is beneficial to improving the analysis efficiency of the subsequent data analysis.
In another optional embodiment, the electrical parameters include at least one electrical parameter of formation electrical parameters, capacity-division electrical parameters, actual electrical parameters, and energy consumption and production parameters corresponding to the capacity of the unit energy consumption production cell;
for each module, the method of calculating the parameter data corresponding to each electrical parameter of the module in real time according to the module data corresponding to the module and combining a plurality of preset electrical parameters specifically includes:
for each electric core in each module, calculating to obtain comprehensive power consumption data corresponding to the electric core and the first information and comprehensive feed data corresponding to the second information according to the first information and the second information corresponding to the electric core;
Calculating the difference between the comprehensive power consumption data and the comprehensive feed data corresponding to the battery cell to obtain actual power consumption data corresponding to the battery cell and the actual power consumption parameters; calculating the ratio of the capacity of the battery cell corresponding to the battery cell to actual power consumption data to obtain battery cell energy consumption data corresponding to the battery cell;
for each module, multiplying the energy consumption data of the battery core corresponding to each battery core in the module by the product coefficient corresponding to the battery core, and comprehensively calculating to obtain the module energy consumption data corresponding to the module; and determining the comprehensive power consumption data, the comprehensive feed data and the module energy consumption data corresponding to the module as the parameter data of the module.
In this alternative embodiment, referring specifically to fig. 8, a schematic flow chart of another intelligent analysis method for forming component energy consumption is disclosed in the embodiment of the present invention in fig. 8. To be used forFor example, when the battery core in any module performs formation operation, for the power supply system, the battery core is charged, and the electric quantity of the power supply system needs to be consumed; at this time, the operation time t of each execution of the formation operation is calculated in real time 1 And operating power consumption P C And then integrating to obtain the integrated power consumption data Q of the battery cell C The specific calculation formula is as follows: q (Q) C =∫（P C ×t 1 ) The method comprises the steps of carrying out a first treatment on the surface of the When the capacity-dividing operation is performed on the battery core, for the power supply system, the charging and discharging operation is performed on the battery core, the electric quantity of the power supply system is consumed when the battery core is charged, and the electric quantity is fed back to the power supply system when the battery core is discharged. At this time, the operation time t of each execution of the capacity division operation is calculated in real time 2 And operating the power supply P D (here the feeding power P D Refer to the product of charging power and discharging power), and then integrating to obtain the comprehensive feed data Q of the battery cell D The specific calculation formula is as follows: q (Q) D =∫（P D ×t 2 ) The method comprises the steps of carrying out a first treatment on the surface of the The actual electricity consumption data Q is calculated to synthesize electricity consumption data Q C And comprehensive feed data Q D The numerical value difference is obtained, and the specific calculation formula is as follows: q= Σq C -∑Q D . The calculation formula of the cell energy consumption data corresponding to the cell is as follows: C/Q, wherein C is the corresponding electric core capacity of this electric core.
In this optional embodiment, the analysis and optimization result of all the parameter data obtained in the step 103 may be specifically reflected in that after the production process/step flow of each cell is optimized, the value of C/Q is increased, and at this time, it may be confirmed that the optimizing effect of the cell reaches the standard.
Therefore, in the alternative embodiment, the cell energy consumption data corresponding to each cell is calculated in real time by taking the cell as a unit, so that the calculation accuracy and reliability of the cell energy consumption data for each cell are improved, the calculation accuracy of the parameter data of each module is further improved, and the accuracy of the follow-up execution data analysis and data optimization are improved to a certain extent.
Example two
Referring to fig. 2, fig. 2 is a flow chart of another intelligent analysis method for component energy consumption in accordance with an embodiment of the present invention. The intelligent analysis method of the formation component energy consumption described in fig. 2 may be applied to an intelligent analysis device of the formation component energy consumption, and optionally, the method may also be applied to formation/capacity separation equipment in an automatic power battery production line, such as a formation/capacity separation integrated machine, which is not limited in the embodiment of the present invention. As shown in fig. 2, the intelligent analysis method for the chemical composition energy consumption may include the following operations:
201. and acquiring electric data corresponding to the automatic power battery production line to be analyzed in real time.
202. For each module, according to the module data corresponding to the module, combining a plurality of preset electric parameters, and calculating the parameter data corresponding to each electric parameter of the module in real time.
203. And obtaining optimization reference data of a power supply system corresponding to the automatic power battery production line, and executing analysis optimization operation on all parameter data according to the optimization reference data to obtain analysis optimization results of all parameter data.
204. And acquiring process comparison data corresponding to the automatic power battery production line, wherein the process comparison data comprises historical energy consumption analysis data of the automatic power battery production line in a preset backtracking period.
In the embodiment of the invention, the duration of the preset backtracking period is greater than or equal to the duration of the real-time monitoring period, and the preset backtracking period corresponds to the real-time monitoring period.
In the embodiment of the present invention, specifically, it is assumed that the current electrical data collected in real time is data of the month of the february, and the historical energy consumption analysis data may be energy consumption data determined after analysis of data collected in the month of the last year of the february.
In the embodiment of the present invention, the other descriptions of step 201 to step 204 refer to the other specific descriptions of step 101 to step 104 in the first embodiment, and the description of the embodiment of the present invention is omitted.
205. And calculating an energy consumption difference value between the historical energy consumption analysis data and the analysis optimization result, and calculating to obtain a power saving value corresponding to the power battery automatic production line after a preset backtracking period and a power saving value corresponding to the power saving value according to the energy consumption difference value and a preset carbon conversion coefficient when the energy consumption difference value indicates that the historical energy consumption analysis data is higher than the analysis optimization result.
206. And generating electricity-saving data aiming at the automatic power battery production line according to the electricity-saving value and the carbon-saving value, and taking the electricity-saving data as analysis data for accounting the carbon data of the automatic power battery production line.
In the embodiment of the invention, the electricity-saving data can be intuitively displayed in the modes of charts, reports, analysis curves and the like.
In the embodiment of the present invention, optionally, the process comparison data further includes executing the above-mentioned historical step management and control scheme for each module in a preset backtracking period;
when the energy consumption difference value represents that the historical energy consumption analysis data is lower than or equal to the analysis optimization result, the method further comprises:
analyzing the historical energy consumption analysis data corresponding to each battery core in all the modules to obtain at least one module to be optimized, wherein the energy consumption difference value between the energy consumption data corresponding to the module to be optimized and the historical energy consumption analysis data corresponding to the module to be optimized is larger than a preset standard difference value;
according to a preset power saving optimization scheme, combining a historical process step management and control scheme corresponding to each module to be optimized, generating process step optimization information aiming at each module to be optimized, and taking the process step optimization information as power saving data after analysis and optimization operation of a power battery automatic production line.
In the embodiment of the invention, optionally, the process comparison data may further include industry average energy consumption data, and at this time, the energy consumption data after the power battery automatic production line performs production line data optimization may be obtained by comprehensively comparing the industry average energy consumption data with the energy consumption data after the power battery automatic production line performs production line optimization, and analysis and generation of carbon consumption and carbon saving data are performed according to the difference. Or analysis of the line optimization direction.
Therefore, after implementing the intelligent analysis method for the formation component energy consumption described in fig. 2, the intelligent analysis optimization can be performed on the electric data and the parameter data of the automatic power battery production line, and then the energy consumption difference can be automatically calculated based on the acquired process comparison data and the analysis optimization result, and the power saving value and the carbon saving value are intelligently calculated or the module to be optimized is determined and the process step optimization information of the module to be optimized is generated according to different value conditions (the historical energy consumption analysis data and the analysis optimization result) of the energy consumption difference, so that the intelligent calculation and the evaluation of the power saving and the carbon saving data or the intelligent integration of the process step optimization information of the module to be optimized are realized, and auxiliary analysis data of one hand is provided for the carbon data for the automatic power battery production line to be calculated, thereby being beneficial to improving the analysis efficiency of the carbon consumption and the carbon saving data.
Example III
Referring to fig. 3, fig. 3 is a schematic structural diagram of an intelligent analysis device for converting component energy consumption according to an embodiment of the present invention. The intelligent analysis device for the energy consumption of the formation component can be an intelligent analysis terminal, equipment, a system or a server for the energy consumption of the formation component, and the server can be a local server, a remote server or a cloud server (also called cloud server), and when the server is a non-cloud server, the non-cloud server can be in communication connection with the cloud server, and the embodiment of the invention is not limited. As shown in fig. 3, the intelligent analysis device for converting component energy consumption may include an acquisition module 301, a calculation module 302, an acquisition module 303, an analysis optimization module 304, and a comparison analysis module 305, where:
The collection module 301 is configured to collect, in real time, electrical data corresponding to a power battery automation line to be analyzed, where the power battery automation line is configured with a plurality of modules, the electrical data includes module data corresponding to a plurality of modules performing a formation operation according to a preset process flow, and all the modules include modules.
In the embodiment of the invention, optionally, the module data corresponding to each module includes a cell identifier of each cell in the module, where the cell identifier is used to determine a cell state of the cell, and the cell state includes an activated state or a non-activated state in which a cell activation operation is performed on the cell;
for each module, according to the state of each cell in the module, performing hierarchical division on each cell, wherein each module comprises at least two division levels, and the cells in an activated state and a non-activated state correspond to one division level respectively;
when the number of the corresponding divided levels is larger than 2, at least three divided sets are determined based on the number of the divided component execution times, and each divided set corresponds to one divided component execution time interval.
The calculating module 302 is configured to calculate, in real time, parameter data corresponding to each electrical parameter of each module according to module data corresponding to the module and a plurality of preset electrical parameters, where the parameter data corresponding to each module at least includes energy consumption data after the module performs a composition operation.
And the obtaining module 303 is configured to obtain optimized reference data of a power system corresponding to the automatic power battery production line.
In an embodiment of the present invention, optionally, the optimization reference data of the power supply system includes a module load operation characteristic and/or a power efficiency characteristic; the power supply system comprises a plurality of load modules and a load module group constructed by the plurality of load modules, wherein any one sub-process flow in the process step flow at least calls one load module group;
the module load operation characteristics comprise load operation characteristics corresponding to each load module group;
when any load module group is called by different sub-process flows, the load operation characteristic corresponding to the load module group is matched with the process step requirement corresponding to the current sub-process flow.
The analysis optimization module 304 is configured to perform an analysis optimization operation on all the parameter data according to the optimization reference data, so as to obtain an analysis optimization result of all the parameter data, where the analysis optimization result of all the parameter data includes a process step optimization result of a process step corresponding to at least one module and/or an energy consumption optimization result of energy consumption data corresponding to at least one module.
The obtaining module 303 is further configured to obtain process comparison data corresponding to the automated power battery production line.
And the comparison analysis module 305 is configured to perform comparison analysis operation according to the process comparison data and the analysis optimization result, and obtain power saving data after the analysis optimization operation is performed on the automated power battery production line, as analysis data for accounting carbon data for the automated power battery production line.
Therefore, the implementation of the intelligent analysis device for the chemical composition energy consumption described in fig. 3 can realize the real-time acquisition of corresponding electric data of the automatic production line of the power battery, and is different from the traditional simple recording of important data of the production line, and when the important data are required to be called, screening and calling are carried out from mass data in a database, so that timeliness and data calling efficiency of the electric data are improved in a real-time data acquisition mode; furthermore, after the electric data are collected in real time, the parameter data comprising the energy consumption data can be calculated in real time by combining a plurality of electric parameters, so that the real-time energy consumption analysis of the electric data corresponding to the module is realized, meanwhile, the analysis optimization is automatically executed on all the parameter data based on the obtained optimized reference data, the intelligent analysis optimization of the power battery automatic production line related parameter data is realized, and the analysis optimization efficiency and the analysis optimization accuracy of the parameter data are improved; and then, the obtained process comparison data can be intelligently compared with an analysis optimization result to obtain electricity-saving data, the intelligent comparison of the optimization effect of the electricity data is realized, and finally the obtained electricity-saving data provides auxiliary analysis data for accounting the carbon data for the automatic production line of the power battery, so that the analysis efficiency of the carbon-saving data is improved.
In an alternative embodiment, the manner in which the acquisition module 301 acquires, in real time, the electrical data corresponding to the automated power battery production line to be analyzed specifically includes:
determining all modules to be analyzed currently in an automatic power battery production line, and collecting the process step information of each module in real time, wherein the process step information of each module comprises first information and second information corresponding to formation and composition operation of each battery cell in the module according to a preset process step flow in a current real-time monitoring period, and the first information comprises a first operation period of formation and formation operation of each battery cell and power consumption data corresponding to each first operation period; the second information comprises a second operation period corresponding to the capacity-dividing operation of each cell and feed data corresponding to each second operation period;
and for each module, determining the power consumption data and the feed data corresponding to all the battery cells in the module as the module data of the module, and taking the module data as the electric data corresponding to the automatic power battery production line.
Therefore, in the optional embodiment, when collecting the electrical data in real time, the method can be subdivided into collecting the published information of each module, the first information and the second information of each electric core in each module, and the fine data monitoring and collecting mode improves the timeliness and accuracy of collecting the data of each electric core in the automatic production line of the power battery; in addition, the method can also distinguish and collect operation information corresponding to the battery cell performing formation operation and capacity division operation, and is beneficial to improving the analysis efficiency of the subsequent data analysis.
In another optional embodiment, the electrical parameters include at least one electrical parameter of formation electrical parameters, capacity-division electrical parameters, actual electrical parameters, and energy consumption and production parameters corresponding to the capacity of the unit energy consumption production cell;
for each module, the calculating module 302 combines a plurality of preset electrical parameters according to the module data corresponding to the module, and the manner of calculating the parameter data corresponding to each electrical parameter of the module in real time specifically includes:
for each electric core in each module, calculating to obtain comprehensive power consumption data corresponding to the electric core and the first information and comprehensive feed data corresponding to the second information according to the first information and the second information corresponding to the electric core;
calculating the difference between the comprehensive power consumption data and the comprehensive feed data corresponding to the battery cell to obtain actual power consumption data corresponding to the battery cell and the actual power consumption parameters; calculating the ratio of the capacity of the battery cell corresponding to the battery cell to actual power consumption data to obtain battery cell energy consumption data corresponding to the battery cell;
for each module, multiplying the energy consumption data of the battery core corresponding to each battery core in the module by the product coefficient corresponding to the battery core, and comprehensively calculating to obtain the module energy consumption data corresponding to the module; and determining the comprehensive power consumption data, the comprehensive feed data and the module energy consumption data corresponding to the module as the parameter data of the module.
Therefore, in the alternative embodiment, the cell energy consumption data corresponding to each cell is calculated in real time by taking the cell as a unit, so that the calculation accuracy and reliability of the cell energy consumption data for each cell are improved, the calculation accuracy of the parameter data of each module is further improved, and the accuracy of the follow-up execution data analysis and data optimization are improved to a certain extent.
In yet another alternative embodiment, the process comparison data includes historical energy consumption analysis data for the power cell automation line over a predetermined backtracking period; the duration of the preset backtracking period is greater than or equal to the duration of the real-time monitoring period, and the preset backtracking period corresponds to the real-time monitoring period;
the comparison analysis module 305 performs a comparison analysis operation according to the process comparison data and the analysis optimization result, and the method for obtaining the power saving data after the analysis optimization operation is performed by the automated power battery production line specifically includes:
calculating an energy consumption difference value between the historical energy consumption analysis data and the analysis optimization result, and calculating to obtain a power saving value corresponding to the power battery automatic production line after a preset backtracking period and a power saving value corresponding to the power saving value according to the energy consumption difference value and a preset carbon conversion coefficient when the energy consumption difference value indicates that the historical energy consumption analysis data is higher than the analysis optimization result;
And generating electricity-saving data aiming at the automatic production line of the power battery according to the electricity-saving value and the carbon-saving value.
Optionally, the process comparison data further includes executing the above-described historical process step management and control scheme for each module in a preset backtracking period;
the comparison analysis module 305 executes comparison analysis operation according to the process comparison data and the analysis optimization result, and the method for obtaining the electricity saving data after the analysis optimization operation is executed by the automatic power battery production line specifically further comprises:
when the energy consumption difference value represents that the historical energy consumption analysis data is lower than or equal to the analysis optimization result, analyzing the historical energy consumption analysis data corresponding to each cell in all the modules to obtain at least one module to be optimized, wherein the energy consumption difference value between the energy consumption data corresponding to the module to be optimized and the historical energy consumption analysis data corresponding to the module to be optimized is larger than a preset standard difference value;
according to a preset power saving optimization scheme, combining a historical process step management and control scheme corresponding to each module to be optimized, generating process step optimization information aiming at each module to be optimized, and taking the process step optimization information as power saving data after analysis and optimization operation of a power battery automatic production line.
Therefore, in this optional embodiment, after intelligent analysis optimization is performed on the electrical data and parameter data of the automated power battery production line, the energy consumption difference can be automatically compared and calculated based on the acquired process comparison data and the analysis optimization result, and for different values of the energy consumption difference (the historical energy consumption analysis data and the analysis optimization result), the electricity saving value and the carbon saving value are intelligently calculated, or the module to be optimized is determined, and the process optimization information of the module to be optimized is generated, so that intelligent calculation and evaluation of the electricity saving and carbon saving data, or intelligent integration of the process optimization information of the module to be optimized is realized, auxiliary analysis data of one hand is provided for the carbon data for the automated power battery production line, and the analysis efficiency of the carbon and carbon saving data is improved.
Example IV
Referring to fig. 4, fig. 4 is a schematic structural diagram of an intelligent analysis device for converting component energy consumption according to another embodiment of the present invention. As shown in fig. 4, the intelligent analysis device for the chemical composition energy consumption may include:
a memory 401 storing executable program codes;
a processor 402 coupled with the memory 401;
the processor 402 invokes executable program code stored in the memory 401 to perform the steps in the intelligent analysis method described in the first or second embodiment of the present invention.
Example five
The embodiment of the invention discloses a computer storage medium which stores computer instructions for executing the steps in the intelligent analysis method for the component energy consumption in the chemical conversion described in the first embodiment or the second embodiment of the invention when the computer instructions are called.
Example six
An embodiment of the present invention discloses a computer program product comprising a non-transitory computer storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps of the intelligent analysis method for the chemical composition energy consumption described in embodiment one or embodiment two.
The apparatus embodiments described above are merely illustrative, in which the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer storage medium including Read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), programmable Read-Only Memory (PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disk Memory, tape Memory, or any other medium readable by a computer that can be used to carry or store data.
Finally, it should be noted that: the embodiment of the invention discloses an intelligent analysis method and device for chemical composition energy consumption, which are only disclosed as a preferred embodiment of the invention, and are only used for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims (10)

1. An intelligent analysis method for chemical component energy consumption, which is characterized by comprising the following steps:
collecting electric data corresponding to a power battery automatic production line to be analyzed in real time, wherein the power battery automatic production line is provided with a plurality of modules, and the electric data comprises module data corresponding to the module performing a formation operation according to a preset process flow;
for each module, calculating parameter data corresponding to the module and each electrical parameter in real time according to the module data corresponding to the module and combining a plurality of preset electrical parameters, wherein the parameter data corresponding to each module at least comprises energy consumption data of the module;
Acquiring optimization reference data of a power supply system corresponding to the automatic power battery production line, and executing analysis optimization operation on all the parameter data according to the optimization reference data to obtain analysis optimization results of all the parameter data, wherein the analysis optimization results of all the parameter data comprise a step optimization result of the step process corresponding to at least one module and/or an energy consumption optimization result of the energy consumption data corresponding to at least one module;
and obtaining process comparison data corresponding to the automatic power battery production line, and executing comparison analysis operation according to the process comparison data and the analysis and optimization result to obtain electricity-saving data of the automatic power battery production line after executing the analysis and optimization operation, wherein the electricity-saving data is used as analysis data for accounting the carbon data of the automatic power battery production line.
2. The intelligent analysis method for the chemical composition energy consumption according to claim 1, wherein the collecting, in real time, the electric data corresponding to the automated power battery production line to be analyzed includes:
determining all modules to be analyzed currently in the automatic power battery production line, and collecting the step information of each module in real time, wherein the step information of each module comprises first information and second information corresponding to formation and composition operations executed by each electric core in the module according to a preset step flow in a current real-time monitoring period, and the first information comprises a first operation period of the formation operation executed by each electric core and power consumption data corresponding to each first operation period; the second information comprises a second operation period corresponding to each battery cell executing capacity-dividing operation and feed data corresponding to each second operation period;
And for each module, determining the power consumption data and the feed data corresponding to all the battery cells in the module as module data of the module, and taking the module data as electric data corresponding to an automatic production line of the power battery.
3. The intelligent analysis method for the formation component energy consumption according to claim 2, wherein the electrical parameters comprise at least one electrical parameter of formation electrical parameters, separation electrical parameters, actual electrical parameters and energy consumption and production parameters corresponding to the capacity of a unit energy consumption production cell;
for each module, according to the module data corresponding to the module, combining a plurality of preset electrical parameters, calculating parameter data corresponding to the module and each electrical parameter in real time, including:
for each electric core in each module, calculating to obtain comprehensive power consumption data corresponding to the electric core and the first information and comprehensive feed data corresponding to the second information according to the first information and the second information corresponding to the electric core;
calculating the difference between the comprehensive power consumption data and the comprehensive feed data corresponding to the battery cell to obtain actual power consumption data corresponding to the actual power consumption parameters of the battery cell; calculating the ratio of the battery cell capacity corresponding to the battery cell to the actual power consumption data to obtain battery cell energy consumption data corresponding to the battery cell;
For each module, multiplying the energy consumption data of the battery core corresponding to each battery core in the module by the product coefficient corresponding to the battery core, and comprehensively calculating to obtain the module energy consumption data corresponding to the module; and determining the comprehensive power consumption data, the comprehensive feed data and the module energy consumption data corresponding to the module as parameter data of the module.
4. An intelligent analysis method for chemical composition energy consumption according to claim 2 or 3, wherein the process comparison data comprises historical energy consumption analysis data of the automated power cell production line in a preset backtracking period; the duration of the preset backtracking period is greater than or equal to the duration of the real-time monitoring period, and the preset backtracking period corresponds to the real-time monitoring period;
and performing a comparison analysis operation according to the process comparison data and the analysis optimization result to obtain electricity saving data of the power battery automatic production line after performing the analysis optimization operation, wherein the electricity saving data comprises:
calculating an energy consumption difference value between the historical energy consumption analysis data and the analysis optimization result, and calculating a power saving value corresponding to the power battery automatic production line after the preset backtracking period is separated from the power battery automatic production line according to the energy consumption difference value and a preset carbon conversion coefficient when the energy consumption difference value indicates that the historical energy consumption analysis data is higher than the analysis optimization result;
And generating electricity-saving data aiming at the automatic power battery production line according to the electricity-saving value and the carbon-saving value.
5. The intelligent analysis method of chemical composition energy consumption according to claim 4, wherein the process comparison data further comprises a historical process step management scheme performed for each of the modules during the preset backtracking period; when the energy consumption difference value represents that the historical energy consumption analysis data is lower than or equal to the analysis optimization result, the method further comprises:
analyzing the historical energy consumption analysis data corresponding to each battery cell in all the modules to obtain at least one module to be optimized, wherein the energy consumption difference value between the energy consumption data corresponding to the module to be optimized and the historical energy consumption analysis data corresponding to the module to be optimized is larger than a preset standard difference value;
according to a preset power saving optimization scheme, combining the historical process step management and control scheme corresponding to each module to be optimized, and generating process step optimization information aiming at each module to be optimized as power saving data after the analysis and optimization operation is executed by the automatic power battery production line.
6. The intelligent analysis method for the formation component energy consumption according to claim 5, wherein the optimization reference data of the power supply system comprises module load operation characteristics and/or power supply efficiency characteristics; the power supply system comprises a plurality of load modules and a load module group constructed by the plurality of load modules, wherein any one of the process steps calls at least one load module group;
The module load operation characteristics comprise load operation characteristics corresponding to each load module group;
when any load module group is called by different sub-process flows, the load operation characteristic corresponding to the load module group is matched with the process step requirement corresponding to the current sub-process flow.
7. An intelligent analysis method for the formation of component energy consumption according to claim 5 or 6, wherein the module data corresponding to each module includes a cell identifier of each cell in the module, the cell identifier being used to determine a cell state of the cell, the cell state including an active state or a non-active state in which a cell activation operation has been performed for the cell;
for each module, performing hierarchical division on each battery cell according to the battery cell state corresponding to each battery cell in the module, wherein each module comprises at least two division levels, and the battery cells in the activated state and the deactivated state correspond to one division level respectively;
and when the number of the levels corresponding to the division levels is larger than 2, determining at least three division sets by taking the formation component execution times as a reference, wherein each division set corresponds to one formation component execution time interval.
8. An intelligent analysis device for the energy consumption of chemical components, characterized in that the device comprises:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring electric data corresponding to a power battery automatic production line to be analyzed in real time, the power battery automatic production line is provided with a plurality of modules, the electric data comprises module data corresponding to a plurality of modules which execute a partitioning operation according to a preset process flow, and all the modules comprise the modules;
the calculation module is used for calculating the parameter data corresponding to each electric parameter of the module in real time according to the module data corresponding to the module and a plurality of preset electric parameters, and the parameter data corresponding to each module at least comprises the energy consumption data after the module executes the formation component operation;
the acquisition module is used for acquiring the optimized reference data of the power system corresponding to the automatic power battery production line;
the analysis optimization module is used for executing analysis optimization operation on all the parameter data according to the optimization reference data to obtain analysis optimization results of all the parameter data, wherein the analysis optimization results of all the parameter data comprise a step optimization result of the step flow corresponding to at least one module and/or an energy consumption optimization result of the energy consumption data corresponding to at least one module;
The acquisition module is also used for acquiring process comparison data corresponding to the automatic power battery production line;
and the comparison analysis module is used for executing comparison analysis operation according to the process comparison data and the analysis optimization result to obtain electricity-saving data of the power battery automatic production line after executing the analysis optimization operation, and the electricity-saving data is used as analysis data for accounting the carbon data of the power battery automatic production line.
9. An intelligent analysis device for the energy consumption of chemical components, characterized in that the device comprises:
a memory storing executable program code;
a processor coupled to the memory;
the processor invokes the executable program code stored in the memory to perform the intelligent analysis method of chemical composition energy consumption as claimed in any one of claims 1-7.
10. A computer storage medium storing computer instructions which, when invoked, are adapted to perform the method of intelligent analysis of chemical composition energy consumption according to any one of claims 1-7.
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