CN110401191B - Electric vehicle charging pile service logic consistency analysis method based on time sequence logic - Google Patents

Electric vehicle charging pile service logic consistency analysis method based on time sequence logic Download PDF

Info

Publication number
CN110401191B
CN110401191B CN201910690107.6A CN201910690107A CN110401191B CN 110401191 B CN110401191 B CN 110401191B CN 201910690107 A CN201910690107 A CN 201910690107A CN 110401191 B CN110401191 B CN 110401191B
Authority
CN
China
Prior art keywords
charging
data
charging pile
current
voltage
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201910690107.6A
Other languages
Chinese (zh)
Other versions
CN110401191A (en
Inventor
徐文渊
冀晓宇
王凯
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang University ZJU
Original Assignee
Zhejiang University ZJU
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang University ZJU filed Critical Zhejiang University ZJU
Priority to CN201910690107.6A priority Critical patent/CN110401191B/en
Publication of CN110401191A publication Critical patent/CN110401191A/en
Application granted granted Critical
Publication of CN110401191B publication Critical patent/CN110401191B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • 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
    • B60L53/64—Optimising energy costs, e.g. responding to electricity rates
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • 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
    • 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
    • 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
    • Y02T90/167—Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S30/00—Systems supporting specific end-user applications in the sector of transportation
    • Y04S30/10—Systems supporting the interoperability of electric or hybrid vehicles
    • Y04S30/12—Remote or cooperative charging

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

The invention discloses an electric vehicle charging pile service logic consistency analysis method based on sequential logic, and provides a server-side data reliability verification method aiming at potential safety hazards in a data transmission process of an electric vehicle charging pile monitoring system, so that malicious attacks of error adjustment of a power grid caused by transmission of wrong charging parameters are effectively prevented. The method mainly comprises the steps of carrying out time sequence correlation on charging pile feedback data and user mobile terminal feedback data, and carrying out combined verification on multi-mode data, so that whether data abnormity caused by hacker intrusion occurs or not is judged, and the safety detection of service logic consistency of a charging pile monitoring system based on time sequence logic is realized.

Description

Electric vehicle charging pile service logic consistency analysis method based on time sequence logic
Technical Field
The invention belongs to the field of intelligent power grid safety, relates to an analysis method for an electric vehicle charging pile power terminal, and particularly relates to an electric vehicle charging pile service logic consistency analysis method based on sequential logic.
Background
The charging mode of the electric automobile mainly comprises three modes of quick charging, conventional charging and battery pack replacement. The multi-user charging pile mainly aims at a conventional charging mode and is generally used in a parking lot. The electric automobile charging has two main points on the influence of the power grid: (1) in urban areas with dense population, the power consumption is limited to a certain extent, electric vehicles are charged in a centralized manner, the whole power grid is a large load, and the power balance of the electric power needs to be considered in large-scale charging. (2) For the part with more electric end loads, certain harmonic wave influence can be produced in the power supply alternation between the three phases, and large-scale charging pile access to the power grid is relatively large dynamic pollution to the whole power grid. As described above, it is necessary to obtain data feedback of charging of the charging pile, so as to effectively adjust the distribution of the power grid.
In the initial charging stage of the charging pile, the current-limiting charging is generally performed by using the optimal charging rate, and in this stage, because the electromotive force of the battery is low, although the charging voltage of the battery is not high, the charging current of the battery is also large, and the charging current needs to be limited. As the charging voltage continues, the battery electromotive force rises, and the charging voltage of the battery also rises. When the battery voltage reaches the best allowable charging voltage, constant voltage charging is maintained. At this stage, since the battery electromotive force is continuously increased while the battery voltage is kept constant, the charging current of the battery decreases in a hyperbolic curve until it decreases to 0. In the actual charging process, the charging may be stopped when the charging current is less than 0.015 CA. The specific charging process is shown in fig. 1.
The existing electric vehicle charging pile monitoring system is generally as shown in fig. 2, a charging pile transmits data to a background server, a user mobile terminal transmits data to a database server, and the background server and the database server are in data communication. At the charging post end, the available charging parameters are voltage, current and power parameters. The voltage parameters mainly comprise voltage out-of-limit, sensitivity index and stability margin index. The charging power parameters comprise complex power and power factor, the power factor is a key influencing the power utilization efficiency of the electrical equipment, the power factor is small, and the fact that most electric energy is consumed means that active power and reactive power are effectively monitored, and distributive power coordination is carried out on the active power and the reactive power, so that the power factor can be improved, the electric energy loss of a power grid is reduced, and the electric energy utilization rate is improved. The data that the user removes the end acquireed has data such as charging time, the stake number of charging of connecting, charging fee.
The safety design of the electric automobile charging pile monitoring system mainly exists in the data transmission process, and as the charging pile and the user mobile terminal are often in the external network environment, extremely high potential safety hazards exist, and particularly, charging parameters fed back in the charging process of an electric automobile are maliciously tampered, so that the power grid can be mistakenly adjusted, and therefore the safety of the system is necessarily improved by improving the safety of the link.
Disclosure of Invention
The invention aims to verify the correctness of feedback data through an electric vehicle charging pile service logic consistency analysis technology based on time sequence logic, so that power grid distribution is effectively adjusted according to the data.
The invention provides a method for analyzing service logic consistency of an electric vehicle charging pile based on sequential logic, and provides a method for verifying data reliability of a server side aiming at potential safety hazards in a data transmission process of an electric vehicle charging pile monitoring system, so that malicious attacks of error adjustment of a power grid caused by transmission of wrong charging parameters are effectively prevented. The method mainly comprises the steps of carrying out time sequence correlation on charging pile feedback data and user mobile terminal feedback data, and carrying out combined verification on multi-mode data, so that whether data abnormity caused by hacker intrusion occurs or not is judged, and the safety detection of service logic consistency of a charging pile monitoring system based on time sequence logic is realized.
The method comprises the following specific steps:
step 1: data acquisition is carried out on the electric vehicle charging pile terminal and the user mobile terminal, the charging pile terminal acquires the charging pile number, time and charging parameters, the charging parameters comprise voltage, current and power parameters, and the user mobile terminal acquires the charging time, the connected charging pile number and the charging expense; acquiring real-time electricity price of the charging pile from a database;
step 2: preprocessing the obtained data of each index, wherein the specific mode is as follows:
step 2.1: converting all data with the same physical meaning to values in uniform units, e.g., 20 minutes 15 seconds at 12 hours for 122015, voltage for all in V, current for a in kW, power for kW, and time for h;
step 2.2: the data are subjected to preliminary rationality judgment, the data comprise non-null data and numerical value rationality, parameter numerical values cannot be null if the data are not null, and the numerical value rationality, namely the size of the index numerical values, is within a reasonable range, so that obviously abnormal data are rejected.
And step 3: according to the service cycle and the service logic of the charging pile, the multi-mode data of the charging pile terminal and the user terminal are subjected to correlation processing, and the charging process analysis of the charging pile with a certain number specifically comprises the following steps:
step 3.1: judging the current charging state according to the time t0 when the user side starts to charge and the current time t; if T0 is equal to 0, the constant-current charging process of the electric vehicle is 0-T1, and the constant-voltage charging stage is T1-T, if T < T1 is in the constant-current charging stage, the charging current I is equal to the constant current I0, and the charging voltage U is equal to U0+ (U1-U0) T/T1, wherein U0 is the initial charging voltage, and U1 is the constant voltage of the constant-voltage charging stage; if T1< T, the charging voltage U is equal to U1 in the constant voltage charging phase, and the charging current may be approximated according to a charging curve, or approximated by an exponential curve to replace a decay curve of the current, and an expression is obtained and substituted to obtain the charging current at time T.
Step 3.2: after the charging voltage U and the charging current I at the moment are obtained through the user side, the charging voltage U and the charging current I are compared with the charging parameters of the charging pile terminal, the charging voltage U ', the charging current I' and the threshold value are set in feedback data obtained by the charging pile terminal1And2can be set according to the voltage and current fluctuation condition during normal charging if | U' -U-<1And | I' -I-<2The charging voltage and charging current data are reasonable; if | U' -U->1If the charging voltage data is maliciously tampered, the steps 3.1 and 3.2 are repeated to verify, and if | I ' -I |, ' I |, ' is not calculation>2If the charging current data is tampered maliciously, the steps 3.1 and 3.2 are repeated to verify. If the rationality is not determined after multiple verifications, the data source is not trusted.
Step 3.3: calculating the electric energy W consumed by the charging according to the charging electric charge of the user side and the electricity price during the charging;
step 3.4: acquiring charging power and time data in the charging process of the charging pile, integrating the charging power with respect to time to obtain electric energy output W' of the charging pile, and setting a threshold value3Can be set according to the historical charging data if | W' -W tint<3The charging power data is reasonable if | W' -W tint>3If the charging power data is maliciously tampered, the step 3.3 and the step 3.4 are repeatedly performed for verification; if the rationality is not determined after multiple verifications, the data source is not trusted.
Step 3.5: when no user of the charging pile charges, the charging output power and the charging current of the charging pile are 0, otherwise, the charging output power and the charging current of the charging pile can be maliciously tampered, and the data source is not trusted.
Step 3, analyzing the charging process of a certain charging pile, randomly selecting the charging piles from all the charging piles for analysis and detection in order to reduce the calculation cost and the communication cost, trusting data returned by the charging pile terminal if malicious attacks are not detected, and effectively adjusting the distribution of the power grid according to the data; and if the malicious attack is detected, the corresponding data source is kept untrusted, the part of data is ignored when the power grid distribution is adjusted, and the data source equipment is output.
The invention has the beneficial effects that:
the invention provides a method for analyzing service logic consistency of an electric vehicle charging pile based on time sequence logic, aiming at the problem of potential safety hazard in the communication link of an electric vehicle charging pile monitoring system. By performing multi-mode data combined analysis on charging parameters fed back by the charging pile and charging information fed back by the user mobile terminal and verifying data reliability through multiple data sources, the method can monitor whether the feedback data is possible to be tampered, output a monitoring result, and simultaneously output abnormal equipment and abnormal indexes if the feedback data is abnormal.
Drawings
FIG. 1 is a schematic view of a charging curve of a charging post of an electric vehicle;
FIG. 2 is an electric vehicle charging pile monitoring system;
fig. 3 is a flow chart of electric vehicle charging pile business logic consistency analysis based on sequential logic.
Detailed Description
The method of the present invention will be further described with reference to the accompanying drawings.
The electric vehicle charging pile business logic consistency analysis method based on the time sequence logic is as shown in fig. 3, and specifically comprises the following steps:
step 1: data acquisition is carried out on the electric vehicle charging pile terminal and the user mobile terminal, the charging pile terminal acquires the charging pile number, time and charging parameters, the charging parameters comprise voltage, current and power parameters, and the user mobile terminal acquires the charging time, the connected charging pile number and the charging expense; acquiring real-time electricity price of the charging pile from a database;
step 2: preprocessing the obtained data of each index, wherein the specific mode is as follows:
step 2.1: converting all data with the same physical meaning to values in uniform units, e.g., 20 minutes 15 seconds at 12 hours for 122015, voltage for all in V, current for a in kW, power for kW, and time for h;
step 2.2: the data are subjected to preliminary rationality judgment, the data comprise non-null data and numerical value rationality, parameter numerical values cannot be null if the data are not null, and the numerical value rationality, namely the size of the index numerical values, is within a reasonable range, so that obviously abnormal data are rejected.
And step 3: according to the service cycle and the service logic of the charging pile, the multi-mode data of the charging pile terminal and the user terminal are subjected to correlation processing, and the charging process analysis of the charging pile with a certain number specifically comprises the following steps:
step 3.1: judging the current charging state according to the time t0 when the user side starts to charge and the current time t; if T0 is equal to 0, the constant-current charging process of the electric vehicle is 0-T1, and the constant-voltage charging stage is T1-T, if T < T1 is in the constant-current charging stage, the charging current I is equal to the constant current I0, and the charging voltage U is equal to U0+ (U1-U0) T/T1, wherein U0 is the initial charging voltage, and U1 is the constant voltage of the constant-voltage charging stage; if T1< T, the charging voltage U is equal to U1 in the constant voltage charging phase, and the charging current may be approximated according to a charging curve, or approximated by an exponential curve to replace a decay curve of the current, and an expression is obtained and substituted to obtain the charging current at time T.
Step 3.2: after the charging voltage U and the charging current I at the moment are obtained through the user side, the charging voltage U and the charging current I are compared with the charging parameters of the charging pile terminal, the charging voltage U ', the charging current I' and the threshold value are set in feedback data obtained by the charging pile terminal1And2can be charged according to normal conditionsThe time voltage and current fluctuation condition is set, if | U' -U-<1And | I' -I-<2The charging voltage and charging current data are reasonable; if | U' -U->1If the charging voltage data is maliciously tampered, the steps 3.1 and 3.2 are repeated to verify, and if | I ' -I |, ' I |, ' is not calculation>2If the charging current data is tampered maliciously, the steps 3.1 and 3.2 are repeated to verify. If the rationality is not determined after multiple verifications, the data source is not trusted.
Step 3.3: calculating the electric energy W consumed by the charging according to the charging electric charge of the user side and the electricity price during the charging;
step 3.4: acquiring charging power and time data in the charging process of the charging pile, integrating the charging power with respect to time to obtain electric energy output W' of the charging pile, and setting a threshold value3Can be set according to the historical charging data if | W' -W tint<3The charging power data is reasonable if | W' -W tint>3If the charging power data is maliciously tampered, the step 3.3 and the step 3.4 are repeatedly performed for verification; if the rationality is not determined after multiple verifications, the data source is not trusted.
Step 3.5: when no user of the charging pile charges, the charging output power and the charging current of the charging pile are 0, otherwise, the charging output power and the charging current of the charging pile can be maliciously tampered, and the data source is not trusted.
Step 3, analyzing the charging process of a certain charging pile, randomly selecting the charging piles from all the charging piles for analysis and detection in order to reduce the calculation cost and the communication cost, trusting data returned by the charging pile terminal if malicious attacks are not detected, and effectively adjusting the distribution of the power grid according to the data; and if the malicious attack is detected, the corresponding data source is kept untrusted, the part of data is ignored when the power grid distribution is adjusted, and the data source equipment is output.

Claims (4)

1. The method is characterized in that sequential correlation is carried out on charging pile feedback data and user mobile terminal feedback data, and multi-mode data are jointly verified, so that whether data abnormity caused by hacker invasion occurs or not is judged, and safety detection of service logic consistency of a charging pile monitoring system based on sequential logic is realized; the method comprises the following specific steps:
step 1: data acquisition is carried out on the electric vehicle charging pile terminal and the user mobile terminal;
step 2: preprocessing the obtained data of each index, wherein the specific mode is as follows:
step 2.1: converting all data with the same physical meaning into numerical values in a unified unit;
step 2.2: carrying out preliminary rationality judgment on the data, wherein the preliminary rationality judgment comprises non-null and numerical rationality, the non-null is that the parameter numerical value cannot be null, the numerical rationality is that the index numerical value is within a reasonable range, and obviously abnormal data are removed;
and step 3: according to the service cycle and the service logic of the charging pile, the multi-mode data of the charging pile terminal and the user terminal are subjected to correlation processing, and the charging process analysis of the charging pile with a certain number specifically comprises the following steps:
step 3.1: judging the current charging state according to the time t0 when the user side starts to charge and the current time t;
step 3.2: after the charging voltage U and the charging current I at the moment are obtained through the user side, the charging voltage U and the charging current I are compared with the charging parameters of the charging pile terminal, the charging voltage U ', the charging current I' and the threshold value are set in feedback data obtained by the charging pile terminal1And2if | U' -U tint<1And | I' -I-<2The charging voltage and charging current data are reasonable; if | U' -U->1If the charging voltage data is maliciously tampered, the steps 3.1 and 3.2 are repeated to verify, and if | I ' -I |, ' I |, ' is not calculation>2If the charging current data is maliciously tampered, the step 3.1 and the step 3.2 are repeatedly performed for verification; if the rationality of the data is not determined after multiple times of verification, the data source is not trusted;
step 3.3: calculating the electric energy W consumed by the charging according to the charging electric charge of the user side and the electricity price during the charging;
step 3.4: acquiring charging power and time data in the charging process of the charging pile, integrating the charging power with respect to time to obtain electric energy output W' of the charging pile, and setting a threshold value3If | W' -W tint<3The charging power data is reasonable if | W' -W tint>3If the charging power data is maliciously tampered, the step 3.3 and the step 3.4 are repeatedly performed for verification; if the rationality of the data is not determined after multiple times of verification, the data source is not trusted;
step 3.5: when no user charges the charging pile, the charging output power and the charging current of the charging pile are 0, otherwise, the charging output power and the charging current of the charging pile can be maliciously tampered, and the data source is not trusted;
if the malicious attack is not detected, the data returned by the charging pile terminal can be trusted, and the power grid distribution is effectively adjusted according to the data; and if the malicious attack is detected, the corresponding data source is kept untrusted, and the part of data is ignored when the power grid distribution is adjusted.
2. The method for analyzing business logic consistency of electric vehicle charging piles based on sequential logic according to claim 1, wherein the data collected in the step 1 comprises: the charging pile terminal acquires a charging pile number, time and charging parameters, wherein the charging parameters comprise voltage, current and power parameters, and the user mobile terminal acquires charging time, the connected charging pile number and charging cost; and acquiring the real-time electricity price of the charging pile from the database.
3. The electric vehicle charging pile business logic consistency analysis method based on the sequential logic, according to claim 1, is characterized in that the specific judgment method in the step 3.1 is as follows:
let T0=0, the constant-current charging process of the electric vehicle is 0-T1, and the constant-voltage charging stage is T1-T, if T < T1, the electric vehicle is in the constant-current charging stage, the charging current I should be a constant current I0, and the charging voltage U = U0+ (U1-U0) T/T1, where U0 is the initial charging voltage, and U1 is the constant voltage of the constant-voltage charging stage; if T1< T, and the charging voltage is in a constant voltage charging stage, the charging voltage is U = U1, and the charging current can obtain an approximate value according to a charging curve, or obtain an expression by approximating a decay curve of the substitute current with an exponential curve, and then obtain the charging current at the time T.
4. The electric vehicle charging pile business logic consistency analysis method based on the sequential logic is characterized in that the charging piles can be randomly selected from all the charging piles to perform the analysis and detection in the step 3, if no malicious attack is detected, data returned by a charging pile terminal can be trusted, and the power grid distribution can be effectively adjusted according to the data; and if the malicious attack is detected, the corresponding data source is kept untrusted, the part of data is ignored when the power grid distribution is adjusted, and the data source equipment is output.
CN201910690107.6A 2019-07-29 2019-07-29 Electric vehicle charging pile service logic consistency analysis method based on time sequence logic Active CN110401191B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910690107.6A CN110401191B (en) 2019-07-29 2019-07-29 Electric vehicle charging pile service logic consistency analysis method based on time sequence logic

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910690107.6A CN110401191B (en) 2019-07-29 2019-07-29 Electric vehicle charging pile service logic consistency analysis method based on time sequence logic

Publications (2)

Publication Number Publication Date
CN110401191A CN110401191A (en) 2019-11-01
CN110401191B true CN110401191B (en) 2020-12-08

Family

ID=68326366

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910690107.6A Active CN110401191B (en) 2019-07-29 2019-07-29 Electric vehicle charging pile service logic consistency analysis method based on time sequence logic

Country Status (1)

Country Link
CN (1) CN110401191B (en)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111049830B (en) * 2019-12-13 2021-12-07 重庆国翰能源发展有限公司 Data information leakage prevention method for charging pile
CN111797436B (en) * 2020-09-10 2020-12-25 深圳华工能源技术有限公司 Energy-saving data counterfeiting identification method for energy-saving equipment of power distribution and utilization system
CN113541317B (en) * 2021-07-26 2022-06-28 国网吉林省电力有限公司 Real-time remote monitoring method for mass charging piles
CN117096877B (en) * 2023-10-19 2024-02-13 国网山西省电力公司营销服务中心 Multi-view-based regional dynamic electricity-carbon data electricity analysis method and system

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5900718A (en) * 1996-08-16 1999-05-04 Total Battery Management, Battery charger and method of charging batteries
JP5490473B2 (en) * 2009-09-15 2014-05-14 ルネサスエレクトロニクス株式会社 Data processing system, electric vehicle and maintenance service system
WO2011074095A1 (en) * 2009-12-17 2011-06-23 トヨタ自動車株式会社 Information transmission device of vehicle and electrically-driven vehicle provided with the same
CN102291416B (en) * 2011-09-14 2015-09-30 成都软智科技有限公司 A kind of method and system of client and server bi-directional synchronization
CN103679348A (en) * 2013-11-28 2014-03-26 国家电网公司 Operation-maintenance-integrated on-site data collection and feedback tour-inspection management system
CN104300604B (en) * 2014-09-28 2018-01-05 国家电网公司 A kind of electric automobile electric charging station monitoring system
CN105553771A (en) * 2015-12-16 2016-05-04 国网北京市电力公司 Message detection method and apparatus
CN108181530A (en) * 2018-01-11 2018-06-19 广东电网有限责任公司电力科学研究院 A kind of alternating-current charging pile interoperability detecting system and method
CN109118075B (en) * 2018-08-03 2020-08-04 浙江大学华南工业技术研究院 Electric power industrial control terminal safety monitoring method based on business logic consistency
CN109922038A (en) * 2018-12-29 2019-06-21 中国电力科学研究院有限公司 A kind of detection method and device of the abnormal data for electric power terminal

Also Published As

Publication number Publication date
CN110401191A (en) 2019-11-01

Similar Documents

Publication Publication Date Title
CN110401191B (en) Electric vehicle charging pile service logic consistency analysis method based on time sequence logic
CN115498640B (en) Micro-grid energy control method and system based on virtual power plant
CN105529789A (en) Electric vehicle intelligent charging system
CN109813982A (en) Charging pile down Monitor Unit method, apparatus and charging pile manage platform, storage medium
CN104767242A (en) Charging method of lithium battery for electric vehicle
CN115042660A (en) Intelligent collaborative management and control new energy charging pile power control system and method
CN111942186A (en) Safety risk early warning method and system for electric vehicle charging process
CN112258804A (en) Comprehensive analysis fault alarm system based on data packet data comparison
CN113541317A (en) Real-time remote monitoring method for mass charging piles
CN115986797A (en) New energy station electrochemical energy storage system grid-connection performance detection method, device and system based on multipoint synchronous test
CN105572623A (en) Remote electricity stealing inspection device
CN108482136A (en) Direct-current charging post based on Internet of Things
Gandhi et al. Impact of the open charge point protocol between the electric vehicle and the fast charging station on the cybersecurity of the smart grid
CN106384436A (en) Intelligent charging system and intelligent charging method
CN111934579B (en) Intelligent capacitor and power equipment control system based on big data
CN108183515B (en) Electric vehicle charging monitoring system without capacity increase
CN111813824B (en) Method and system for automatically detecting missing report of power failure event of 10kV line outgoing line
CN107979324A (en) Solar recharging system and its control method
Liu et al. Key security challenges for electric vehicle charging system
CN109697219B (en) Block chain-based electric power distributed system and block chain recording method thereof
Li et al. High-accuracy parameters identification of non-linear electrical model for high-energy lithium-ion capacitor
Nie et al. Online monitoring and integrated analysis system for EV charging station
CN110601261B (en) Microgrid controller service logic consistency analysis method based on sensing control logic
CN207481697U (en) direct-current charging post based on internet of things
Xu et al. The security of charging protocol between charging piles and electric vehicles

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant