CN113406557A - Remote verification method for propagation type charging pile - Google Patents
Remote verification method for propagation type charging pile Download PDFInfo
- Publication number
- CN113406557A CN113406557A CN202110701575.6A CN202110701575A CN113406557A CN 113406557 A CN113406557 A CN 113406557A CN 202110701575 A CN202110701575 A CN 202110701575A CN 113406557 A CN113406557 A CN 113406557A
- Authority
- CN
- China
- Prior art keywords
- charging
- pile
- measurement
- voltage
- error
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 83
- 238000012795 verification Methods 0.000 title claims abstract description 36
- 238000005259 measurement Methods 0.000 claims abstract description 92
- 238000004364 calculation method Methods 0.000 claims description 10
- 238000001514 detection method Methods 0.000 claims description 7
- XOFYZVNMUHMLCC-ZPOLXVRWSA-N prednisone Chemical compound O=C1C=C[C@]2(C)[C@H]3C(=O)C[C@](C)([C@@](CC4)(O)C(=O)CO)[C@@H]4[C@@H]3CCC2=C1 XOFYZVNMUHMLCC-ZPOLXVRWSA-N 0.000 claims description 3
- 238000012546 transfer Methods 0.000 claims description 3
- 238000011161 development Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 239000000295 fuel oil Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R35/00—Testing or calibrating of apparatus covered by the other groups of this subclass
- G01R35/04—Testing or calibrating of apparatus covered by the other groups of this subclass of instruments for measuring time integral of power or current
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- 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
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention provides a remote verification method for a propagation type charging pile, which is characterized by collecting charging process data, wherein the charging process data comprises a charging pile interface ID number, an electric vehicle VIN code, an electric vehicle BMS measured voltage, an electric vehicle BMS measured current, an electric vehicle BMS metered electric energy, a charging pile measured voltage, a charging pile measured current and a charging pile metered electric energy, subtracting the charging process data to obtain a measurement error, and completing remote pre-verification of the charging pile; the method has the advantages that the measurement accuracy of the plurality of charging piles with high use frequency is guaranteed, and the standard quantity value is transmitted to a network formed in the whole charging process by means of the charging behavior of the electric automobile, so that remote pre-verification of the charging piles is completed; the workload of verification personnel is greatly reduced, the verification efficiency is improved, and the cost consumed by the verification work is saved. Meanwhile, as an online remote verification system, the system can find problems at the first time, and real-time performance is guaranteed.
Description
Technical Field
The invention relates to the field of metering and verification of direct-current charging piles, in particular to a remote verification method of a propagation type charging pile.
Background
With the development of high social and economic level, environmental problems gradually come into the field of view of the public. The traditional fuel oil automobile has the problems of low energy utilization efficiency, environmental pollution caused by exhaust emission and the like. The new energy electric automobile consumes electric energy, has no tail gas emission, is low-carbon and environment-friendly, and develops rapidly in recent years. And the development of new energy automobiles cannot leave the support of charging facilities. In recent years, China actively promotes the construction of charging facilities, the number of the charging facilities is increased by geometric multiples, and meanwhile, the measuring workload of the charging pile is greatly increased. The electric automobile charging pile belongs to a metering device for trade settlement, whether the metering result of the charging pile is accurate or not is related to the fairness of transactions and the interest of both parties of the transactions, and the metering performance of a non-vehicle-mounted charger, such as working error, indicating value error, payment amount error and clock indicating value error, is required to be carried out in the longest one year period, so that regular detection is needed to ensure the accuracy and reliability of the metering result.
The traditional metering work of the charging facility depends on a detection mechanism, a metering person carries a standard device to arrive at the site, and the metering calibration work is carried out on the charging facility according to the experimental steps specified in the standard. But has the following disadvantages: on one hand, the metering work is completed by metering personnel, and the proficiency of the operation of the metering personnel determines the metering result, which has higher requirements on the self quality of the metering personnel; on the other hand, charging facilities are generally widely distributed in all regions of a city, and metering personnel need to carry a standard device to each site to carry out metering work, so that the detection cost is high, the period is long, and the efficiency is low.
Disclosure of Invention
In order to solve the problems, the invention provides a propagation type remote verification method for the charging pile, which is used for estimating the electric energy metering error of the charging pile by using the charging process data uploaded to a database by the charging pile and combining with a proper algorithm model.
A remote verification method for a propagation type charging pile comprises the following steps:
the data generated in the process of charging the electric automobile is called charging process data, remote pre-verification of the charging pile is completed by using the charging process data, and the charging process data comprises a charging pile interface ID number, an electric automobile VIN code, a measured value of an electric automobile BMS and a measured value of the charging pile;
the measured values of the electric automobile BMS comprise electric automobile BMS measured voltage, electric automobile BMS measured current and electric automobile BMS measured electric energy; the measurement values of the charging piles comprise charging pile measurement voltage, charging pile measurement current and charging pile measurement electric energy;
the measured value of the electric vehicle BMS and the measured value of the charging pile in the charging process data are subjected to difference to obtain the measurement error of one relative to the other; the current measurement error estimation method is the same as the voltage measurement error estimation method;
the pre-detection method specifically comprises the following steps:
the method comprises the following steps: the charging pile with high use frequency is calibrated, the calibrated charging pile is a standard pile, and the accuracy of a standard pile measurement value is ensured;
step two: in the charging process of the electric automobile and the standard pile, calculating measurement errors of standard pile measurement voltage, standard pile measurement current, electric automobile BMS measurement voltage and electric automobile BMS measurement current, namely transmitting a standard quantity value to the charged electric automobile through the standard pile to obtain calibration automobile BMS measurement voltage and calibration automobile BMS measurement current;
step three: the standard vehicle is charged by using an uncalibrated pile, and the metering error of the uncalibrated pile is estimated by using the error estimation of the uncalibrated pile measurement voltage, the uncalibrated pile measurement current, the standard vehicle BMS measurement voltage and the standard vehicle BMS measurement current in the charging process, namely the standard quantity value is transmitted to the uncalibrated pile by the calibration vehicle to obtain the calibrated pile measurement voltage and the calibrated pile measurement current;
step four: when the estimated uncertainty of the calibration vehicle or the calibration pile exceeds a certain threshold value, the accuracy is not enough to continue to be transmitted downwards, at the moment, the calibration vehicle or the calibration pile is changed into an uncalibrated state again, and the high-accuracy calibration system is waited to recalibrate the calibration vehicle or the calibration pile through a charging process;
step five: by utilizing the whole charging network, repeating the second step and the third step to obtain the error estimation results of the measured voltage and the measured current of all the uncertified charging piles in the charging network;
step six: and calculating the metering error of the charging pile according to an error transfer formula by using the error estimation results of the measured voltage and the measured current, and completing remote pre-verification.
Further, the voltage measurement error estimation method comprises the following steps:
(1) acquiring data of a charging process, acquiring a VIN (vehicle identification number) and an ID (identity) number of a charging pile interface in the charging process, and inquiring uncertainty of error estimation of the measured voltage of the automobile BMS and the measured voltage of the charging pile in a database; recording the charging voltage data for systems with higher uncertainty in voltage error estimation as Uh=(uh1,uh2,...,uhn) Charging voltage data U of a system with low uncertainty of voltage error estimationl=(ul1,ul2,...,uln);
(3) Calculating muhAndmean value of error mu by known lower uncertainty metrology systemlAnd uncertaintyObtaining the error mean value mu of a system with higher uncertaintyhAnd uncertainty
(4) The voltage error posterior estimation of a system with higher uncertainty is obtained by formula calculationAnd posterior estimation of uncertaintyWherein muh0Is a priori average value,Is a prior variance;
(5) estimating the posteriorAndas a priori estimate of the voltage measurement error estimation method.
Further, the electric energy metering error estimation method comprises the following steps:
the metering formula of the electric energy E is as follows: ec=UcIct;
Wherein, UcFor measuring voltage, IcTo measure current, t is the charging time;
according to the metering formula of the electric energy E, the voltage measurement error delta UcError of current measurement δ IcAnd time measurement error delta t is summed to obtain an electric energy error delta E calculation formula
δE=δUc·∫Ic·dt+δIc·∫Uc·dt+Uc·Ic·δt
The time error term can be ignored due to the small value of the time error, and the calculation formula for obtaining the electric energy error is as follows:
δE=δUc·∫Ic·dt+δIc·∫Uc·dt
wherein,for the purpose of estimating the uncertainty of the voltage,uncertainty is estimated for the current.
The invention has the beneficial effects
(1) According to the method, the charging process data uploaded to the database by the charging pile is combined with a proper algorithm model to estimate the electric energy metering error of the charging pile, so that the remote verification function of the charging pile of the electric automobile is completed, and the verification efficiency of the charging pile is improved as much as possible on the premise of ensuring the precision;
(2) according to the remote pre-verification method for the propagation type charging pile in the charging process of the electric automobile, the measurement accuracy of a plurality of charging piles with high use frequency is guaranteed, and the standard quantity value is transmitted to a network formed in the whole charging process by means of the charging behavior of the electric automobile, so that the remote pre-verification of the charging piles is completed; compared with the traditional on-site verification mode, the verification efficiency is high, and the labor, material and time costs required by verification are greatly reduced on the premise of ensuring accuracy;
(3) according to the invention, the standard quantity value is transmitted to each charging pile by using the BMS of the electric automobile, and the charging piles can be pre-verified only by ensuring the measurement precision of part of the charging piles, so that the workload of verification personnel is greatly reduced, the verification efficiency is improved, and the cost consumed by verification work is saved; meanwhile, as an online remote verification system, the system can find problems at the first time, and real-time performance is guaranteed.
Drawings
Fig. 1 is a verification network between an electric vehicle and a charging pile according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments; all other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Electric automobile fills electric pile when normal operating, and same electric automobile can use different electric pile that fills to charge, and same electric pile that fills also can provide charging service for many cars. A large network is formed in the charging process of the electric vehicle and the charging pile, as shown in fig. 1.
During the charging process, the BMS of the electric vehicle communicates and exchanges data with the charging post, and the data generated during the charging process is referred to as charging process data.
For the voltage, the current and the electric energy in the charging process, the charging process data simultaneously comprise a measured value of an automobile BMS system and a measured value of a charging pile, and the difference between the two measured values can estimate the measurement error of one relative to the other;
if a part of charging piles are calibrated, the metering accuracy of the charging piles is guaranteed, and the measurement error of the automobile BMS charged by using the standard piles can be estimated according to the charging process data; referring to fig. 1, a line segment with a direction represents a charging process of the charging pile and the electric vehicle, and a direction of an arrow represents a transmission direction of the standard value.
The charging piles used at present all adopt intelligent electric meters, and charging data can be transmitted to a cloud database, so that remote pre-verification of the charging piles can be completed remotely by using charging process data of electric vehicles and the charging piles.
A remote verification method for a propagation type charging pile comprises the following steps:
the data generated in the process of charging the electric automobile is called charging process data, and the charging process data is used for completing remote pre-verification of the charging pile and comprises a charging pile interface ID number (used for distinguishing different charging interfaces), an electric automobile VIN number (used for distinguishing different charging automobiles), a measurement value of an electric automobile BMS (battery management system) and a measurement value of the charging pile;
the measured values of the electric automobile BMS comprise electric automobile BMS measured voltage, electric automobile BMS measured current and electric automobile BMS measured electric energy; the measurement values of the charging piles comprise charging pile measurement voltage, charging pile measurement current and charging pile measurement electric energy;
the measured value of the electric vehicle BMS and the measured value of the charging pile in the charging process data are subjected to difference to obtain the measurement error of one relative to the other; the current measurement error estimation method is the same as the voltage measurement error estimation method;
the pre-detection method specifically comprises the following steps:
the method comprises the following steps: the charging pile with high use frequency is calibrated, the calibrated charging pile is a standard pile, and the accuracy of a standard pile measurement value is ensured;
step two: in the charging process of the electric automobile and the standard pile, calculating measurement errors of standard pile measurement voltage, standard pile measurement current, electric automobile BMS measurement voltage and electric automobile BMS measurement current, namely transmitting a standard quantity value to the charged electric automobile through the standard pile to obtain calibration automobile BMS measurement voltage and calibration automobile BMS measurement current;
step three: the standard vehicle is charged by using an uncalibrated pile, and the metering error of the uncalibrated pile is estimated by using the error estimation of the uncalibrated pile measurement voltage, the uncalibrated pile measurement current, the standard vehicle BMS measurement voltage and the standard vehicle BMS measurement current in the charging process, namely the standard quantity value is transmitted to the uncalibrated pile by the calibration vehicle to obtain the calibrated pile measurement voltage and the calibrated pile measurement current;
step four: when the estimated uncertainty of the calibration vehicle or the calibration pile exceeds a certain threshold value, the accuracy is not enough to continue to be transmitted downwards, at the moment, the calibration vehicle or the calibration pile is changed into an uncalibrated state again, and the high-accuracy calibration system is waited to recalibrate the calibration vehicle or the calibration pile through a charging process;
step five: by utilizing the whole charging network, repeating the second step and the third step to obtain the error estimation results of the measured voltage and the measured current of all the uncertified charging piles in the charging network;
step six: and calculating the metering error of the charging pile according to an error transfer formula by using the error estimation results of the measured voltage and the measured current, and completing remote pre-verification.
As shown in fig. 1, the left side is a standard pile after calibration, after the vehicle 1 is charged with the pile 1, the BMS system metering error of the vehicle 1 is estimated through charging process data, and a standard quantity value is transmitted to the vehicle 1 through the pile 1; when the vehicle 1 is charged by using the pile n +1, the BMS metering error model of the vehicle 1 is known, the metering error of the pile n +1 can be estimated by combining the charging process data of the vehicle 1 and the pile n +1, and by analogy, the standard quantity value can be transmitted to the whole charging network by using the charging process of the electric vehicle, so that the charging pile which is not identified in the network is subjected to online pre-verification.
The remote pre-detection content comprises the estimation of voltage measurement error, current measurement error and electric energy metering error of the charging pile, and the specific estimation method comprises the following steps:
the electric pile that fills that uses at present has all adopted smart electric meter, can transmit charging data to high in the clouds database.
The voltage measurement error estimation method comprises the following steps:
(1) acquiring data of a charging process, acquiring a VIN (vehicle identification number) and an ID (identity) number of a charging pile interface in the charging process, and inquiring uncertainty of error estimation of the measured voltage of the automobile BMS and the measured voltage of the charging pile in a database; the charging voltage data of a system (low-precision metering system) in which the uncertainty of the voltage error estimation is high is recorded as Uh=(uh1,uh2,...,uhn) Charging voltage data U of a system with low uncertainty of voltage error estimation (high-precision metering system)l=(ul1,ul2,...,uln);
(3) Calculating muhAndmean value of error mu by known lower uncertainty metrology systemlAnd uncertaintyObtaining the error mean value mu of a system with higher uncertaintyhAnd uncertainty
(4) The voltage error posterior estimation of a system with higher uncertainty is obtained by formula calculationAnd posterior estimation of uncertaintyWherein muh0Is a priori average value,Is a prior variance;
(5) estimating the posteriorAndas a priori estimate of the voltage measurement error estimation method.
The current error estimation is substantially the same as the voltage error estimation step, except that the current charge data is taken in the voltage error estimation step (1). The current measurement error and uncertainty obtained by the calculation of the steps are used for estimating the electric energy metering error
The electric energy metering error estimation method comprises the following steps:
the metering formula of the electric energy E is as follows: ec=UcIct;
Wherein, UcFor measuring voltage, IcTo measure current, t is the charging time;
according to the metering formula of the electric energy E, the voltage measurement error delta UcError of current measurement δ IcAnd time measurement error delta t is summed to obtain an electric energy error delta E calculation formula
δE=δUc·∫Ic·dt+δIc·∫Uc·dt+Uc·Ic·δt
The time error term can be ignored due to the small value of the time error, and the calculation formula for obtaining the electric energy error is as follows:
δE=δUc·∫Ic·dt+δIc·∫Uc·dt
wherein,for the purpose of estimating the uncertainty of the voltage,uncertainty is estimated for the current.
The propagation type charging pile remote verification method provided by the invention is introduced in detail, the principle and the implementation mode of the invention are explained, and the explanation of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (3)
1. A remote verification method for a propagation type charging pile is characterized by comprising the following steps:
the data generated in the process of charging the electric automobile is called charging process data, remote pre-verification of the charging pile is completed by using the charging process data, and the charging process data comprises a charging pile interface ID number, an electric automobile VIN code, a measured value of an electric automobile BMS and a measured value of the charging pile;
the measured values of the electric automobile BMS comprise electric automobile BMS measured voltage, electric automobile BMS measured current and electric automobile BMS measured electric energy; the measurement values of the charging piles comprise charging pile measurement voltage, charging pile measurement current and charging pile measurement electric energy;
the measured value of the electric vehicle BMS and the measured value of the charging pile in the charging process data are subjected to difference to obtain the measurement error of one relative to the other; the current measurement error estimation method is the same as the voltage measurement error estimation method;
the pre-detection method specifically comprises the following steps:
the method comprises the following steps: the charging pile with high use frequency is calibrated, the calibrated charging pile is a standard pile, and the accuracy of a standard pile measurement value is ensured;
step two: in the charging process of the electric automobile and the standard pile, calculating measurement errors of standard pile measurement voltage, standard pile measurement current, electric automobile BMS measurement voltage and electric automobile BMS measurement current, namely transmitting a standard quantity value to the charged electric automobile through the standard pile to obtain calibration automobile BMS measurement voltage and calibration automobile BMS measurement current;
step three: the standard vehicle is charged by using an uncalibrated pile, and the metering error of the uncalibrated pile is estimated by using the error estimation of the uncalibrated pile measurement voltage, the uncalibrated pile measurement current, the standard vehicle BMS measurement voltage and the standard vehicle BMS measurement current in the charging process, namely the standard quantity value is transmitted to the uncalibrated pile by the calibration vehicle to obtain the calibrated pile measurement voltage and the calibrated pile measurement current;
step four: when the estimated uncertainty of the calibration vehicle or the calibration pile exceeds a certain threshold value, the accuracy is not enough to continue to be transmitted downwards, at the moment, the calibration vehicle or the calibration pile is changed into an uncalibrated state again, and the high-accuracy calibration system is waited to recalibrate the calibration vehicle or the calibration pile through a charging process;
step five: by utilizing the whole charging network, repeating the second step and the third step to obtain the error estimation results of the measured voltage and the measured current of all the uncertified charging piles in the charging network;
step six: and calculating the metering error of the charging pile according to an error transfer formula by using the error estimation results of the measured voltage and the measured current, and completing remote pre-verification.
2. The method of claim 1, further comprising: the voltage measurement error estimation method comprises the following steps:
(1) acquiring data of a charging process, acquiring a VIN (vehicle identification number) and an ID (identity) number of a charging pile interface in the charging process, and inquiring uncertainty of error estimation of the measured voltage of the automobile BMS and the measured voltage of the charging pile in a database; recording the charging voltage data for systems with higher uncertainty in voltage error estimation as Uh=(uh1,uh2,...,uhn) Charging voltage data U of a system with low uncertainty of voltage error estimationl=(ul1,ul2,...,uln);
(3) Calculating muhAndmean value of error mu by known lower uncertainty metrology systemlAnd uncertaintyObtaining the error mean value mu of a system with higher uncertaintyhAnd uncertainty
(4) The voltage error posterior estimation of a system with higher uncertainty is obtained by formula calculationAnd posterior estimation of uncertaintyWherein muh0Is a priori average value,Is a prior variance;
3. The method of claim 1, further comprising: the electric energy metering error estimation method comprises the following steps:
the metering formula of the electric energy E is as follows: ec=UcIct;
Wherein, UcFor measuring voltage, IcTo measure current, t is the charging time;
according to the metering formula of the electric energy E, the voltage measurement error delta UcError of current measurement δ IcAnd time measurement error delta t is summed to obtain an electric energy error delta E calculation formula
δE=δUc·∫Ic·dt+δIc·∫Uc·dt+Uc·Ic·δt
The time error term can be ignored due to the small value of the time error, and the calculation formula for obtaining the electric energy error is as follows:
δE=δUc·∫Ic·dt+δIc·∫Uc·dt
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110701575.6A CN113406557A (en) | 2021-06-23 | 2021-06-23 | Remote verification method for propagation type charging pile |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110701575.6A CN113406557A (en) | 2021-06-23 | 2021-06-23 | Remote verification method for propagation type charging pile |
Publications (1)
Publication Number | Publication Date |
---|---|
CN113406557A true CN113406557A (en) | 2021-09-17 |
Family
ID=77682842
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110701575.6A Pending CN113406557A (en) | 2021-06-23 | 2021-06-23 | Remote verification method for propagation type charging pile |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113406557A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114485800A (en) * | 2022-02-14 | 2022-05-13 | 北京佳华智联科技有限公司 | Remote quality control method suitable for gas multi-parameter mobile monitor |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103439684A (en) * | 2013-08-05 | 2013-12-11 | 广西电网公司电力科学研究院 | System and method for detecting true shape electric energy metering errors of electric car battery charger/charging post |
CN103198223B (en) * | 2013-04-12 | 2015-12-09 | 电子科技大学 | A kind of Forecasting Methodology of electronic product reliability in time |
CN104682520B (en) * | 2015-03-17 | 2017-07-28 | 北京市计量检测科学研究院 | A kind of electric vehicle alternating-current charging attachment means with gauge check port |
CN109782097A (en) * | 2019-03-07 | 2019-05-21 | 深圳市计量质量检测研究院 | A kind of electrically-charging equipment remote meter system and its metering method |
CN111175689A (en) * | 2020-02-29 | 2020-05-19 | 国网河南省电力公司漯河供电公司 | Quick electric energy meter calibration device and use method |
CN108445435B (en) * | 2018-02-05 | 2020-08-25 | 国电南瑞科技股份有限公司 | Online error evaluation method for electric energy meter calibrating device |
CN109866648B (en) * | 2019-04-25 | 2021-03-26 | 上汽大众汽车有限公司 | Intelligent charging method and system for electric automobile |
CN112550029A (en) * | 2020-11-27 | 2021-03-26 | 中国电力科学研究院有限公司 | Electric energy metering device and method for electric automobile charging pile |
-
2021
- 2021-06-23 CN CN202110701575.6A patent/CN113406557A/en active Pending
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103198223B (en) * | 2013-04-12 | 2015-12-09 | 电子科技大学 | A kind of Forecasting Methodology of electronic product reliability in time |
CN103439684A (en) * | 2013-08-05 | 2013-12-11 | 广西电网公司电力科学研究院 | System and method for detecting true shape electric energy metering errors of electric car battery charger/charging post |
CN104682520B (en) * | 2015-03-17 | 2017-07-28 | 北京市计量检测科学研究院 | A kind of electric vehicle alternating-current charging attachment means with gauge check port |
CN108445435B (en) * | 2018-02-05 | 2020-08-25 | 国电南瑞科技股份有限公司 | Online error evaluation method for electric energy meter calibrating device |
CN109782097A (en) * | 2019-03-07 | 2019-05-21 | 深圳市计量质量检测研究院 | A kind of electrically-charging equipment remote meter system and its metering method |
CN109866648B (en) * | 2019-04-25 | 2021-03-26 | 上汽大众汽车有限公司 | Intelligent charging method and system for electric automobile |
CN111175689A (en) * | 2020-02-29 | 2020-05-19 | 国网河南省电力公司漯河供电公司 | Quick electric energy meter calibration device and use method |
CN112550029A (en) * | 2020-11-27 | 2021-03-26 | 中国电力科学研究院有限公司 | Electric energy metering device and method for electric automobile charging pile |
Non-Patent Citations (3)
Title |
---|
何静涵 等: "电动汽车交流充电桩测得值的不确定度分析", 《计量与测试技术》 * |
汪增福: "《模式识别》", 31 January 2010 * |
魏明晨: "电动汽车直流充电桩检定系统设计", 《中国优秀博硕士学位论文全文数据库(硕士)》 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114485800A (en) * | 2022-02-14 | 2022-05-13 | 北京佳华智联科技有限公司 | Remote quality control method suitable for gas multi-parameter mobile monitor |
CN114485800B (en) * | 2022-02-14 | 2023-10-27 | 北京佳华智联科技有限公司 | Remote quality control method suitable for gas multi-parameter mobile monitor |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN106443480B (en) | A kind of lithium-ion battery systems SOC estimation method | |
CN109061506A (en) | Lithium-ion-power cell SOC estimation method based on Neural Network Optimization EKF | |
CN105093114B (en) | The combined estimation method and system of a kind of battery line modeling and state-of-charge | |
CN101212071B (en) | Method for estimating charge state of power cell | |
CN101625397B (en) | Mixed rapid estimation method for residual energy of battery | |
CN104101838B (en) | Power cell system, and charge state and maximum charging and discharging power estimation methods thereof | |
CN102004226B (en) | Pure electrical vehicle battery pack state-of-charge (SOC) estimation device and method | |
CN105572596B (en) | Lithium battery SOC estimation method and system | |
CN106772072A (en) | A kind of SOC estimation method and device based on battery behavior curve | |
CN109633472B (en) | State of charge estimation algorithm of single lithium battery | |
CN102169168B (en) | Battery dump energy estimation method based on particle filtering | |
CN104617623A (en) | Balance control method for power battery pack of electric vehicle | |
CN106443492A (en) | Method for estimating SOC (State Of Charge) of lithium battery of low-velocity electronic vehicle | |
CN102608540A (en) | Coulomb efficiency measuring method used for SOC (system-on-chip) evaluation of power battery | |
CN107861074B (en) | Lithium battery SOC estimation method | |
CN103529400A (en) | Battery capacity forecasting method with self-adaptive temperature compensating function | |
CN106959420A (en) | A kind of power battery pack SOC and SOH adaptive estimation method | |
CN107831448A (en) | A kind of state-of-charge method of estimation of parallel connection type battery system | |
CN109633479A (en) | Lithium battery SOC estimation on line method based on built-in capacitor G-card Kalman Filtering | |
CN103267950A (en) | SOH (State Of Health) value evaluation method of electric car battery pack | |
CN106772104A (en) | A kind of electrokinetic cell SOC value evaluation method | |
CN104865533A (en) | High-precision display method for state of charge (SOC) of on-vehicle power supply | |
CN115839692A (en) | Array type displacement meter monitoring method and system for convergence and settlement monitoring | |
CN113406557A (en) | Remote verification method for propagation type charging pile | |
CN107748329A (en) | Charge states of lithium ion battery monitoring method, monitoring device and monitoring modular |
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 |