CN113682183B - Intelligent electric automobile charging system based on SCADA system - Google Patents
Intelligent electric automobile charging system based on SCADA system Download PDFInfo
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- CN113682183B CN113682183B CN202111153646.XA CN202111153646A CN113682183B CN 113682183 B CN113682183 B CN 113682183B CN 202111153646 A CN202111153646 A CN 202111153646A CN 113682183 B CN113682183 B CN 113682183B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
- B60L53/60—Monitoring or controlling charging stations
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
- B60L53/60—Monitoring or controlling charging stations
- B60L53/62—Monitoring or controlling charging stations in response to charging parameters, e.g. current, voltage or electrical charge
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/12—Electric charging stations
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
- Secondary Cells (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention discloses an intelligent electric automobile charging system based on an SCADA system, which comprises: a central monitoring device; the central monitoring device is connected with an output end monitoring system through a communication module; the output end monitoring system is provided with: charger, temperature sensor, current sensor, microseism sensor, voltage sensor; the output end monitoring system uploads the multi-source heterogeneous charging information such as temperature, current, voltage, vibration and the like measured by the device in the charging process to the central monitoring device in real time, and acquires static and dynamic automobile battery information and monitors the charging state of the automobile battery in real time through the central monitoring device, so that a multi-source heterogeneous charging early warning model of the charging process is constructed, early prediction and early warning of a charging operation fault are realized, and the charging operation process is timely controlled through the central monitoring device, so that the battery is prevented from being broken down in the charging process.
Description
Technical Field
The disclosure belongs to the technical field of electric automobile charging, and particularly relates to an intelligent electric automobile charging system based on a SCADA system.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The use of conventional fossil fuels causes a great degree of pollution to the atmosphere, and meanwhile, as a non-renewable energy source, the reserves of the fossil fuels are also smaller and smaller; therefore, many countries and scientific institutions are actively devoting to the development and production of electric vehicles, and the development of electric vehicles has become a necessary trend for energy conservation, emission reduction and global environment improvement.
However, the disadvantage of weak cruising ability and inconvenient charging of electric vehicles is also an obstacle to limit the wide range of use.
Therefore, how to solve the charging problem of the electric automobile, meanwhile, the power battery can be maintained, and the electric automobile is convenient to operate and use by users through humanized man-machine interaction interface and perfect communication capability, so that the electric automobile is a key for popularization of the power-assisted electric automobile.
However, in recent years, as users of electric vehicles increase, charging and firing events of the electric vehicles also frequently occur; the method also limits the steps of building the charging piles and the charging stations by vast vehicle enterprises and charging companies, but the existing electric vehicle charging process is not provided with a prediction early warning device and a corresponding prediction early warning method, and the dangerous situation is usually found after the battery smokes and fires, obviously, the economic loss is caused at this time, and the great risk is caused to the surrounding environment and people.
Disclosure of Invention
Aiming at the defects existing in the prior art, one or more embodiments of the present disclosure provide an intelligent electric vehicle charging system based on an SCADA system, by the data acquisition and process monitoring functions based on the SCADA system, static and dynamic multi-source heterogeneous charging information is acquired and the charging state of a vehicle battery is monitored in real time, so as to construct a multi-source heterogeneous charging information early warning model of a charging process, realize early prediction and early warning of a charging operation fault, and timely control the charging operation process through a central monitoring device, so as to avoid the battery from generating faults in the charging process.
According to an aspect of one or more embodiments of the present disclosure, there is provided an intelligent electric vehicle charging system based on a SCADA system, including: a central monitoring device; the central monitoring device is connected with an output end monitoring system through a communication module.
The output end monitoring system is provided with: charger, temperature sensor, current sensor, microseism sensor, voltage sensor; the output end monitoring system uploads the multi-source heterogeneous charging information such as temperature, current, voltage, vibration and the like measured by the device in the charging process to the central monitoring device in real time.
Furthermore, the central monitoring device is also connected with an input end monitoring system through a communication module, and the input end monitoring system is a monitoring system which is arranged on the electric automobile and is used for maintenance of the automobile battery.
Further, the information of the total capacity of the battery, the current electric quantity of the battery, the current temperature of the battery, the current charging current value and the current charging voltage value in the charging process measured by the input end monitoring system is uploaded to the central monitoring device in real time.
Further, the central monitoring device is connected with an external monitoring device through a communication module.
Further, based on the multi-source heterogeneous charging information parameters collected by the central monitoring device, an inherent logic symbiotic relation between the multi-source heterogeneous charging information parameters and battery faults is mined by adopting a correlation criterion algorithm, and a multi-source heterogeneous charging information early warning model of a charging process is constructed, so that each early warning information parameter is quantized.
Further, the supporting probability of the multi-source heterogeneous charging information parameters on the occurrence of the charging faults is obtained by utilizing the multi-source heterogeneous charging information early warning model; and the central monitoring device sends an early warning signal and a control instruction.
According to one aspect of one or more embodiments of the present disclosure, a method for constructing a multi-source heterogeneous charging process early-warning information early-warning model is provided, and the intelligent electric vehicle charging system based on the SCADA system is used for collecting multi-source heterogeneous early-warning information parameters.
Further, the multi-source heterogeneous early warning information adopts four algorithms of dispersion standardization, an arctangent function, a logarithmic function method and a zero-mean method to process the early warning information parameters of the charging faults, eliminates interference information and retains effective information.
Further, according to the acquired charging fault early-warning information, single parameter attribute measurement is carried out, and the supporting probability of single parameter on the occurrence of the charging fault is calculated by adopting a log audit algorithm in combination with the acquired multi-source charging fault early-warning information, wherein the value range is [ 0,1 ].
Further, a depth fusion method of the multi-source heterogeneous early warning information of the charging fault is constructed according to the probability of supporting the occurrence of the charging fault by a single parameter, all the early warning information parameters are fused, the probability of supporting the occurrence of the charging fault by the multi-source heterogeneous early warning information parameters is calculated, and the range of the probability is [ 0,1 ].
Advantageous effects
According to the intelligent electric vehicle charging system based on the SCADA system, through the data acquisition and process monitoring functions based on the SCADA system, static and dynamic multi-source charging device and vehicle battery information are acquired, and the charging state of the vehicle battery is monitored in real time, so that a multi-source heterogeneous charging early warning model of a charging process is built, early prediction and early warning of a charging operation fault are realized, the charging operation process is timely controlled through the central monitoring device, and the battery is prevented from being broken down in the charging process.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application.
Fig. 1 is a diagram of a multi-source heterogeneous charging information charging early warning model of an intelligent electric vehicle charging system based on a SCADA system according to one or more embodiments of the present disclosure.
The specific embodiment is as follows:
technical solutions in one or more embodiments of the present disclosure will be clearly and fully described below in conjunction with the accompanying drawings in one or more embodiments of the present disclosure, and it is apparent that the described embodiments are only some embodiments of the present disclosure, not all embodiments. All other embodiments, which may be made by one of ordinary skill in the art without undue burden based on one or more embodiments of the present disclosure, are intended to be within the scope of the present disclosure.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present application. Unless defined otherwise, all technical and scientific terms used in this example have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
It is further noted that the flowcharts or block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods and systems according to various embodiments of the present disclosure. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the logical functions specified in the various embodiments. In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by special purpose hardware-based systems which perform the specified functions or operations, or combinations of special purpose hardware and computer instructions.
Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict, and the present disclosure will be further described with reference to the drawings and embodiments.
Example 1
As shown in fig. 1, an intelligent electric vehicle charging system based on a SCADA system, the charging system includes: the system comprises a central monitoring device, a communication module, an output end monitoring system, an input end monitoring system, an external monitoring device and a fault early warning device.
The central monitoring device, as the core of the charging system, comprises: and the computer and software are connected with the field external equipment, the modules and the system and are used for collecting the process data and sending control instructions to the field connected equipment, modules and the system.
The output monitoring system includes: charger, temperature sensor, current sensor, microseism sensor, voltage sensor.
The micro-vibration sensor is arranged on the charger and is attached to the contact surface of the battery through the connection between the charger and the battery charging port, the micro-vibration signal of the charger is received through the contact surface induction of the micro-vibration sensor and the charger, and meanwhile, the micro-vibration signal of the battery is received through the contact surface induction of the micro-vibration sensor and the battery charging port.
The input end monitoring system is based on a monitoring system which is installed and arranged by each vehicle producer on vehicles of different models and used for maintaining the battery of the automobile.
The input monitoring system generally comprises the following monitoring information: the total capacity of the battery, the current electric quantity of the battery, the current temperature of the battery, the current charging current value, the current charging voltage value and the like.
The external monitoring device includes: video monitoring devices, infrared temperature detectors, and other external monitoring devices.
The fault early warning device adopts an audible and visual alarm device.
The communication module includes: the system comprises an output end communication unit, an input end communication unit, an external monitoring communication unit and a fault early warning communication unit.
The data information of the output end monitoring system, the input end monitoring system and the external monitoring device, which are acquired by each communication unit based on the SCADA system, comprises the following components: the temperature of the output end and the input end, microseismic signals of the output end and the input end, currents of the output end and the input end, voltages of the output end and the input end, dynamic change values of various information parameters of the output end and the input end and the like are all information, structured, semi-structured, unstructured, dynamic values, static values and other multi-structure data are covered, an inherent logic symbiotic relation between multi-source heterogeneous charging information parameters and battery faults is excavated by adopting a correlation criterion algorithm, a multi-source heterogeneous charging information early warning model of a charging process is constructed, and each early warning information parameter is quantized.
S1: and four algorithms of dispersion standardization, arctangent function, logarithmic function method and zero-mean method are carried out by using the central monitoring device, and the charging fault early warning information parameters are processed by the four algorithms, so that interference information is removed, and effective information is reserved.
S2: and (3) carrying out attribute measurement of a single parameter according to the acquired early warning information of the charging faults, and respectively calculating the supporting probability of the single parameter on the occurrence of the charging faults by adopting a log audit algorithm in combination with the acquired early warning information of the multi-source charging faults, wherein the value range is 0 and 1.
S3: and constructing a depth fusion method of the multi-source heterogeneous early warning information of the charging fault according to the probability of supporting the occurrence of the charging fault by a single parameter, fusing all the early warning information parameters, and calculating the probability of supporting the occurrence of the charging fault by the multi-source heterogeneous early warning information parameters, wherein the range of the probability is 0 and 1.
S4: and taking the DeltaT time period as a sliding window, calculating to obtain a charging fault occurrence probability situation based on real-time data, and predicting the occurrence probability of the charging fault of the next DeltaT time period by adopting a GM (1, 1), ARMA or Hol T-Wi nters model. Meanwhile, the multi-source heterogeneous information data in the charging process are collected through each communication unit of the SCADA system, and the occurrence probability of the charging fault in the charging process is continuously corrected, so that the accuracy of the charging system in predicting the occurrence probability of the charging fault is improved.
The supporting probability of the multi-source heterogeneous early warning information parameter to the occurrence of the charging fault is between 0.65 and 0.75, and the central monitoring device sends a first-level early warning signal to the fault early warning device and sends early warning information to staff and a vehicle owner through the SCADA system; between 0.75 and 0.85, the central monitoring device sends a secondary early warning signal to the fault early warning device and sends early warning information to staff and vehicle owners through the SCADA system; and between 0.85 and 1, the central monitoring device sends three-level early warning signals to the fault early warning device and controls the charger to immediately stop charging operation.
It should be noted that while several modules or sub-modules of the device are mentioned in the detailed description above, such partitioning is merely exemplary and not mandatory. Indeed, the features and functions of two or more modules described above may be embodied in one module in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module described above may be further divided into a plurality of modules to be embodied.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the same, but rather, various modifications and variations may be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and features disclosed herein.
Claims (8)
1. An intelligent electric automobile charging system based on SCADA system, which is characterized by comprising: a central monitoring device; the central monitoring device is connected with an output end monitoring system through a communication module;
the output end monitoring system is provided with: charger, temperature sensor, current sensor, microseism sensor, voltage sensor; the output end monitoring system uploads the multisource heterogeneous charging information such as temperature, current, voltage, vibration and the like in the charging process measured by the device to the central monitoring device in real time;
the multi-source heterogeneous charging information collected based on the central monitoring device adopts an association criterion algorithm to mine an inherent logic symbiotic relation between the multi-source heterogeneous charging information and the battery fault, and a multi-source heterogeneous charging information early warning model of the charging process is constructed, so that each early warning information parameter is quantized; the multi-source heterogeneous charging information early warning model is utilized to obtain the supporting probability of the multi-source heterogeneous early warning information parameters on the occurrence of the charging faults; and the central monitoring device sends an early warning signal and a control instruction.
2. The intelligent electric vehicle charging system based on the SCADA system of claim 1, wherein the central monitoring device is further connected with an input end monitoring system through a communication module, and the input end monitoring system is a monitoring system which is installed and arranged on an electric vehicle and is used for maintaining a vehicle battery.
3. The intelligent electric vehicle charging system based on the SCADA system of claim 2, wherein the information of the total battery capacity, the current battery power, the current battery temperature, the current charging current value and the current charging voltage value in the charging process measured by the input monitoring system is uploaded to the central monitoring device in real time.
4. The SCADA system-based intelligent electric vehicle charging system of claim 3 wherein the central monitoring device is connected with an external monitoring device through a communication module.
5. The construction method of the multi-source heterogeneous charging process early warning information early warning model is characterized in that the intelligent electric vehicle charging system based on the SCADA system is used for collecting multi-source heterogeneous early warning information parameters according to any one of claims 1-4.
6. The method for constructing a multi-source heterogeneous charging process early warning information early warning model according to claim 5, wherein the multi-source heterogeneous early warning information is processed by adopting four algorithms of dispersion standardization, arctangent function, logarithmic function and zero-mean method, interference information is removed, and effective information is reserved.
7. The method for constructing the early warning model of the multi-source heterogeneous charging process early warning information according to claim 6, wherein the single parameter attribute measurement is performed according to the acquired charging fault early warning information, and the supporting probability of the single parameter on the occurrence of the charging fault is calculated by adopting a log audit algorithm in combination with the acquired multi-source charging fault early warning information, wherein the value range is [ 0,1 ].
8. The method for constructing the multi-source heterogeneous charging process early-warning information early-warning model according to claim 7 is characterized by constructing a multi-source heterogeneous early-warning information deep fusion method for charging faults according to the probability of supporting the occurrence of the charging faults by a single parameter, fusing all early-warning information parameters, and calculating the probability of supporting the occurrence of the charging faults by the multi-source heterogeneous early-warning information parameters, wherein the range of the probability is [ 0,1 ].
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