CN114692082A - Method, system, device and medium for identifying battery swapping user - Google Patents
Method, system, device and medium for identifying battery swapping user Download PDFInfo
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Abstract
The invention discloses a method, a system, equipment and a medium for identifying a battery swapping user. The identification method of the battery swapping user comprises the following steps: acquiring a power change record mileage of a power change user and a driving track fitting mileage corresponding to a power change vehicle of the power change user; and identifying whether the battery swapping user is a suspected abnormal user or not according to the battery swapping recorded mileage and the driving track fitting mileage. According to the battery replacement recording mileage and the driving track fitting mileage, whether the battery replacement user is a suspected abnormal user or not is identified, the accuracy of identifying the abnormal user can be improved, cheating situations of the user are reduced, and the management and maintenance efficiency of the battery pack is improved.
Description
Technical Field
The invention belongs to the technical field of battery replacement user identification, and particularly relates to a battery replacement user identification method, a battery replacement user identification system, battery replacement user identification equipment and a battery replacement user identification medium.
Background
In the process of battery swapping operation, part of users may have abnormal behaviors, and the abnormal behaviors may cause adverse effects on operation and management of the battery swapping station. In order to reduce the occurrence of abnormal behaviors of abnormal users and efficiently and quickly identify the abnormal users, the method is very necessary. In the prior art, the identification of the abnormal user is mainly performed in a manual mode, so that the workload is large, and the identification efficiency is low.
Disclosure of Invention
The technical problem to be solved by the present invention is to overcome the defects in the prior art, and provide a method, a system, a device and a medium for identifying a battery swapping user.
The invention solves the technical problems through the following technical scheme:
the invention provides a method for identifying a battery swapping user, which comprises the following steps:
acquiring a power change record mileage of a power change user and a driving track fitting mileage corresponding to a power change vehicle of the power change user;
and identifying whether the battery swapping user is a suspected abnormal user or not according to the battery swapping recorded mileage and the driving track fitting mileage.
In the technical scheme, based on prior knowledge that battery replacement of the electric vehicle is closely related to the driving mileage of the electric vehicle, from the perspective of mileage data, whether a battery replacement user is a suspected abnormal user or not is automatically identified according to mileage data of two different sources, namely a battery replacement record mileage and a driving track fitting mileage, so that the efficiency of identifying the abnormal user can be improved, and meanwhile, the reliability of an identification result of the abnormal user can also be improved.
Preferably, the obtaining of the power swapping record mileage of the power swapping user and the driving track fitting mileage corresponding to the power swapping vehicle of the power swapping user includes:
acquiring a battery swapping record of a battery swapping user;
acquiring a power swapping record mileage of a power swapping user according to the power swapping record;
acquiring positioning information of a battery replacement vehicle of a battery replacement user in a running process;
and fitting according to the positioning information to obtain the driving track fitting mileage corresponding to the battery replacing vehicle.
In the technical scheme, an obtaining way of the power conversion record mileage and the driving track fitting mileage is provided, and authenticity and reliability of a data source of the power conversion record mileage and the driving track fitting mileage are guaranteed.
Preferably, the power change recorded mileage is an average power change recorded mileage, and the driving track fitting mileage is an average driving track fitting mileage; acquiring a power swapping record mileage of a power swapping user according to the power swapping record, comprising:
acquiring single battery replacement mileage recorded in each battery replacement record;
obtaining the number average power switching record mileage of the power switching user according to the multiple single power switching mileage;
obtaining a driving track fitting mileage corresponding to the battery replacing vehicle according to the positioning information fitting, comprising:
dividing the positioning information into local positioning information respectively corresponding to each battery replacement record according to the battery replacement time recorded in each battery replacement record;
fitting according to each piece of local positioning information to obtain a local running track fitting mileage corresponding to the battery replacement vehicle;
and fitting the mileage according to the plurality of local running tracks to obtain the average running track fitting mileage corresponding to the battery replacing vehicle.
In the technical scheme, the data of a certain scale can better reflect the characteristics of the data, and then the subsequent data processing can be effectively carried out on the basis of the characteristics of the data, so that whether the battery swapping user is a suspected abnormal user or not is identified by using the secondary average battery swapping recorded mileage and the secondary average driving track fitted mileage as bases, and the accuracy of the identification result of the abnormal user can be improved.
Preferably, identifying whether the battery swapping user is a suspected abnormal user according to the battery swapping record mileage and the driving track fitting mileage includes:
acquiring the mileage difference between the battery replacement record mileage and the driving track fitting mileage;
and when the mileage difference reaches a first preset threshold value, identifying the battery swapping user as a suspected abnormal user.
In the technical scheme, the priori knowledge with small difference between the mileage data from two different sources is used as the identification basis, so that whether the battery swapping user is a suspected abnormal user or not can be effectively identified.
Preferably, the method for identifying a battery swapping user further includes:
acquiring the power mileage of a battery pack used by the battery replacement vehicle;
when the mileage difference reaches a first preset threshold, identifying the battery swapping user as a suspected abnormal user, including:
and when the electric mileage is smaller than a second preset threshold and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a suspected abnormal user.
In the technical scheme, the degree electric mileage and mileage difference are combined based on the priori knowledge that the degree electric mileage has an upper limit, and the abnormality recognition is performed on the power change user, so that the recognition accuracy can be improved.
Preferably, the method for identifying a battery swapping user further includes:
acquiring accumulated battery replacement times of a battery replacement user;
when the electric mileage is less than a second preset threshold and the mileage difference reaches a first preset threshold, identifying the battery replacement user as a suspected abnormal user, including:
and when the accumulated battery swapping times reach a third preset threshold, the degree electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a suspected abnormal user.
In the technical scheme, the characteristic that data can be better reflected only by considering data of a certain scale is taken into consideration, the accumulated battery change times, the degree electric mileage and the mileage difference are combined, and the battery change user is subjected to abnormal recognition based on the degree electric mileage and the mileage difference when the accumulated battery change times reach a certain amount, so that the recognition accuracy can be improved.
Preferably, the method for identifying a battery swapping user further includes:
acquiring single battery replacement mileage recorded in a battery replacement record of a battery replacement user;
determining the ratio of the times of the single battery replacement mileage being less than the preset mileage to the total times of battery replacement;
when the accumulated battery swapping frequency reaches a third preset threshold, the degree electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a suspected abnormal user, including:
and when the occupation ratio reaches a fourth preset threshold, the accumulated battery swapping times reaches a third preset threshold, the degree electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a suspected abnormal user.
In the technical scheme, the characteristic that data can be better reflected by data of a certain scale is considered, the proportion of the number of times that the single battery swapping mileage is less than the preset mileage to the total battery swapping times, the accumulated battery swapping times, the degree-to-electricity mileage and the mileage difference are combined, and when the proportion of the number of times that the single battery swapping mileage is less than the preset mileage to the total battery swapping times reaches a certain amount, the battery swapping user is subjected to abnormity identification based on the accumulated battery swapping times, the degree-to-electricity mileage and the mileage difference, so that the identification accuracy can be improved.
Preferably, the method for identifying a battery swapping user further includes:
after the battery replacement user is identified as a suspected abnormal user, acquiring the mileage difference as an abnormal mileage;
and executing the exception handling operation based on the exception mileage.
According to the technical scheme, a way of correcting the abnormal behavior of the abnormal user after the abnormal user is identified is provided, the abnormal processing operation is executed based on the abnormal mileage, and the adverse effect of the abnormal behavior on the operation and management of the power conversion station can be reduced in a reasonable range.
The invention also provides an identification system of the battery replacement user, which comprises an acquisition unit and an identification unit;
the acquisition unit is used for acquiring a power swapping record mileage of a power swapping user and a driving track fitting mileage corresponding to a power swapping vehicle of the power swapping user;
the identification unit is used for identifying whether the battery swapping user is a suspected abnormal user or not according to the battery swapping recorded mileage and the driving track fitting mileage.
In the technical scheme, based on prior knowledge that battery replacement of the electric vehicle is closely related to the driving mileage of the electric vehicle, from the perspective of mileage data, whether a battery replacement user is a suspected abnormal user or not is automatically identified according to mileage data of two different sources, namely a battery replacement record mileage and a driving track fitting mileage, so that the efficiency of identifying the abnormal user can be improved, and meanwhile, the reliability of an identification result of the abnormal user can also be improved.
Preferably, the obtaining unit obtains a battery replacement record of a battery replacement user;
the acquisition unit acquires a power swapping record mileage of a power swapping user according to the power swapping record;
the method comprises the steps that an acquisition unit acquires positioning information of a battery replacement vehicle of a battery replacement user in a driving process;
the obtaining unit obtains driving track fitting mileage corresponding to the battery replacement vehicle according to the positioning information fitting.
In the technical scheme, an obtaining way of the power conversion record mileage and the driving track fitting mileage is provided, and authenticity and reliability of a data source of the power conversion record mileage and the driving track fitting mileage are guaranteed.
Preferably, the obtaining unit obtains a single battery replacement mileage recorded in each battery replacement record;
the acquisition unit acquires the secondary average battery replacement record mileage of the battery replacement user according to the multiple single battery replacement mileage;
the acquisition unit divides the positioning information into local positioning information respectively corresponding to each battery replacement record according to the battery replacement time recorded in each battery replacement record;
according to each piece of local positioning information, the obtaining unit obtains a local running track fitting mileage corresponding to the battery replacement vehicle through fitting;
and obtaining the mean driving track fitting mileage corresponding to the battery replacement vehicle by the obtaining unit according to the plurality of local driving track fitting mileage.
In the technical scheme, the data of a certain scale can better reflect the characteristics of the data, and then the subsequent data processing can be effectively carried out on the basis of the characteristics of the data, so that whether the battery swapping user is a suspected abnormal user or not is identified by using the secondary average battery swapping recorded mileage and the secondary average driving track fitted mileage as bases, and the accuracy of the identification result of the abnormal user can be improved.
Preferably, the obtaining unit obtains a mileage difference between the battery replacement record mileage and the driving track fitting mileage;
when the mileage difference reaches a first preset threshold value, the identification unit identifies the battery replacement user as a suspected abnormal user.
In the technical scheme, the priori knowledge with small difference between the mileage data from two different sources is used as the identification basis, so that whether the battery swapping user is a suspected abnormal user or not can be effectively identified.
Preferably, the acquisition unit acquires the kilowatt-hour mileage of a battery pack used by the battery replacement vehicle;
when the electric mileage is smaller than a second preset threshold value and the mileage difference reaches a first preset threshold value, the identification unit identifies the battery replacement user as a suspected abnormal user.
According to the technical scheme, the degree electric mileage and the mileage difference are combined based on the priori knowledge that the degree electric mileage has the upper limit, the abnormality recognition is carried out on the power change user, and the recognition accuracy can be improved.
Preferably, the acquisition unit acquires the accumulated battery replacement times of the battery replacement user;
when the accumulated battery changing times reach a third preset threshold, the electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, the identification unit identifies the battery changing user as a suspected abnormal user.
According to the technical scheme, the characteristic that data can be better reflected only by data of a certain scale is considered, the accumulated battery change times, the degree electric mileage and the mileage difference are combined, and the battery change user is subjected to abnormal recognition based on the degree electric mileage and the mileage difference when the accumulated battery change times reach a certain amount, so that the recognition accuracy can be improved.
Preferably, the obtaining unit obtains a single battery replacement mileage recorded in a battery replacement record of a battery replacement user;
the acquisition unit determines the ratio of the number of times that the single power change mileage is less than the preset mileage to the total number of power change;
when the occupation ratio reaches a fourth preset threshold, the accumulated battery replacement times reaches a third preset threshold, the degree electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, the identification unit identifies the battery replacement user as a suspected abnormal user.
According to the technical scheme, the characteristic that data can be better reflected by data of a certain scale is considered, the proportion of the number of times that the single power exchange mileage is less than the preset mileage to the total number of power exchange is combined with the accumulated power exchange number, the degree electric mileage and the mileage difference, and when the proportion of the number of times that the single power exchange mileage is less than the preset mileage to the total number of power exchange reaches a certain amount, the power exchange user is subjected to abnormal recognition based on the accumulated power exchange number, the degree electric mileage and the mileage difference, so that the recognition accuracy can be improved.
Preferably, after the battery replacement user is identified as a suspected abnormal user, the identification unit acquires the mileage difference as an abnormal mileage;
the identification unit executes an abnormality processing operation based on the abnormal mileage.
According to the technical scheme, a way of correcting the abnormal behavior of the abnormal user after the abnormal user is identified is provided, the abnormal processing operation is executed based on the abnormal mileage, and the adverse effect of the abnormal behavior on the operation and management of the power conversion station can be reduced in a reasonable range.
The invention also provides electronic equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the computer program to realize the method for identifying the battery swapping user.
The invention also provides a computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method for identifying a battery swapping user of the invention.
The positive progress effects of the invention are as follows: based on prior knowledge which is closely related to battery replacement of the electric vehicle and the driving mileage of the electric vehicle, whether a battery replacement user is a suspected abnormal user or not is automatically identified according to mileage data of two different sources, namely battery replacement recorded mileage and driving track fitted mileage from the viewpoint of mileage data, the efficiency of identifying the abnormal user can be improved, and meanwhile the reliability of an identification result of the abnormal user can also be improved.
Drawings
Fig. 1 is a flowchart of an identification method for a battery swapping user according to embodiment 1 of the present invention.
Fig. 2 is a flowchart of step S1 of the method for identifying a battery swapping user according to embodiment 1 of the present invention.
Fig. 3 is a flowchart of step S2 of an implementation manner of the method for identifying a battery swapping user in embodiment 5 of the present invention.
Fig. 4 is a schematic structural diagram of an electronic device according to embodiment 6 of the present invention.
Fig. 5 is a schematic structural diagram of an identification system for a battery swapping user in embodiment 8 of the present invention.
Detailed Description
The invention is further illustrated by the following examples, which are not intended to limit the scope of the invention.
Example 1
The embodiment provides an identification method for a battery swapping user. Referring to fig. 1, the method for identifying a battery swapping user includes the following steps:
and S1, acquiring a power swapping record mileage of a power swapping user and a driving track fitting mileage corresponding to a power swapping vehicle of the power swapping user.
And step S2, identifying whether the battery swapping user is a suspected abnormal user or not according to the battery swapping recorded mileage and the driving track fitting mileage.
As an alternative embodiment, referring to fig. 2, step S1 includes the following steps:
and S101, obtaining a battery swapping record of a battery swapping user.
And S102, acquiring a power swapping record mileage of a power swapping user according to the power swapping record.
And S103, acquiring positioning information of the battery replacement vehicle of the battery replacement user in the driving process.
And S104, fitting according to the positioning information to obtain a driving track fitting mileage corresponding to the battery replacing vehicle.
When the method is specifically implemented, each time the battery swapping user carries out the battery swapping operation, the battery swapping platform or the related server stores the battery swapping record of the battery swapping user. Therefore, the battery swapping record of the battery swapping user can be acquired from the battery swapping platform or the related server. And storing the corresponding driving mileage from the battery pack to the battery pack in the battery replacement record, namely the single battery replacement mileage. And obtaining the power change record mileage of the power change user in a preset time period according to a plurality of single power change mileage of the power change user in the preset time period (set as T).
In an optional implementation manner, a GPS device is arranged on the battery replacement vehicle, and in the running process of the battery replacement vehicle, the GPS device acquires the positioning information of the battery replacement vehicle according to a preset time interval, and according to a plurality of positioning information acquired within a certain time interval, the fitted driving mileage of the battery replacement vehicle within the time interval can be obtained through fitting. In specific implementation, dividing the positioning information into local positioning information respectively corresponding to each battery replacement record according to the battery replacement time recorded in each battery replacement record; and fitting to obtain the fitted mileage of the local running track corresponding to the battery replacing vehicle according to each local positioning information. That is, according to the battery replacement time (set as t1) corresponding to the battery pack when the battery pack is replaced and the battery replacement time (set as t2) corresponding to the battery pack when the battery pack is replaced, the local driving track fitting mileage of the battery replacement vehicle in the time interval from t1 to t2, namely the fitting mileage of the driving track of the battery replacement vehicle in the process from the battery pack to the battery pack when the battery pack is replaced can be obtained by fitting according to the time sequence according to the positioning information acquired by the GPS device in the time interval from t1 to t 2. And obtaining the driving track fitting mileage of the battery replacement user in the preset time period T according to the multiple local driving track fitting mileage of the battery replacement user in the preset time period T.
Then, acquiring the mileage difference between the battery replacement record mileage and the driving track fitting mileage; and when the mileage difference reaches a first preset threshold value, identifying the battery swapping user as a suspected abnormal user.
In the technical scheme, the priori knowledge with small difference between the mileage data from two different sources is used as the identification basis, so that whether the battery swapping user is a suspected abnormal user or not can be effectively identified.
In specific implementation, the preset time period T and the first preset threshold value may be reasonably set as required.
When a difference exists between the power swapping recorded mileage and the driving track fitting mileage, a situation that the power swapping user implements suspicious behaviors may exist. When the mileage difference is smaller than a first preset threshold value, the difference between the power swapping recorded mileage and the driving track fitting mileage is small, and even if suspicious behaviors exist, the influence of the suspicious behaviors on power swapping operation and management is not large, so that the suspicious behaviors are not classified as suspected abnormal users. If the mileage difference reaches a first preset threshold value, the difference between the power swapping recorded mileage and the driving track fitting mileage is large, the probability of suspicious behaviors is high, and the influence on power swapping operation and management is large, so that the power swapping user is to be classified as a suspected abnormal user.
In an alternative embodiment, when the mileage difference reaches a first preset threshold, it may be considered that there is an abnormal behavior in which the mileage data is falsified. On one hand, the abnormal behavior can generate influence on resources, such as loss of charging for battery replacement operation; on the other hand, it also has a safety impact, such as affecting the evaluation of the normal life cycle and the life time of the battery.
In an optional implementation manner, after the battery swapping user is identified as a suspected abnormal user, the mileage difference is acquired as an abnormal mileage; and executing the exception handling operation based on the exception mileage.
In this embodiment, based on prior knowledge that battery swapping for an electric vehicle is related to travel mileage of the electric vehicle, from the perspective of mileage data, whether a swapping user is a suspected abnormal user is automatically identified according to mileage data of two different sources, namely, a swapping record mileage and a travel track fitting mileage, so that the efficiency of identifying the abnormal user can be improved, and the reliability of an identification result of the abnormal user can also be improved.
Example 2
The embodiment provides an identification method for a battery swapping user.
In this embodiment, after the single battery replacement mileage and the local travel track fitting mileage are obtained, the number average battery replacement recorded mileage of the battery replacement user is obtained according to the multiple single battery replacement mileage, and the number average travel track fitting mileage corresponding to the battery replacement vehicle is obtained according to the multiple local travel track fitting mileage.
And if the battery replacement vehicle is configured to replace the battery within the preset time period T for N times, the secondary average battery replacement recorded mileage is the average value of the N single battery replacement mileage, and the secondary average driving track fitting mileage is the average value of the N local driving track fitting mileage.
In this embodiment, it is considered that data of a certain scale can better reflect characteristics of the data, and then subsequent data processing can be effectively performed on the basis of the characteristics of the data, so that whether the swapping user is a suspected abnormal user or not is identified by using the secondary average swapping record mileage and the secondary average driving track fitting mileage as bases, and the accuracy of an abnormal user identification result can be improved.
Then, acquiring the mileage difference between the secondary average battery replacement recorded mileage and the secondary average driving track fitted mileage; and when the mileage difference reaches a preset threshold value, identifying the battery swapping user as a suspected abnormal user.
In an optional implementation manner, after the battery swapping user is identified as a suspected abnormal user, the mileage difference is acquired as an abnormal mileage; and executing the exception handling operation based on the exception mileage.
Example 3
The embodiment provides an identification method for a battery swapping user.
In this embodiment, the power conversion record mileage and the driving track fitting mileage are first obtained. The specific implementation can refer to embodiment 1, and details are not described here.
And then, acquiring the kilowatt-hour mileage of the battery pack used by the battery replacement vehicle. And the electricity-degree mileage is obtained according to the ratio of the electricity-changing recorded mileage obtained by the electricity-changing recorded data of the electricity-changing vehicle to the total consumed electric quantity.
The step of identifying suspected anomalous users comprises:
and when the electric mileage is smaller than a second preset threshold and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a suspected abnormal user.
The second preset threshold value can be set reasonably according to specific situations.
The power-measuring mileage and the mileage difference are combined, the power-change user is evaluated and identified, and the identification accuracy can be improved.
In the embodiment, based on the priori knowledge that the electric mileage has an upper limit, the electric mileage and the mileage difference are combined, the abnormality of the power change user is identified, and the identification accuracy can be improved.
In an optional implementation manner, after the battery swapping user is identified as a suspected abnormal user, the mileage difference is acquired as an abnormal mileage; and executing the exception handling operation based on the exception mileage.
Example 4
The embodiment provides an identification method for a battery swapping user.
In this embodiment, the power conversion record mileage and the driving track fitting mileage are first obtained. The specific implementation can refer to embodiment 1, and details are not described here.
And then, acquiring the kilowatt-hour mileage of the battery pack used by the battery replacement vehicle. And the electricity-degree mileage is obtained according to the ratio of the electricity-changing recorded mileage obtained by the electricity-changing recorded data of the electricity-changing vehicle to the total consumed electric quantity.
Then, the accumulated power change times of the power change user is obtained. As an optional implementation manner, the accumulated battery replacement frequency is within a preset time period T, and the battery replacement frequency of the battery replacement vehicle may be obtained through statistics according to a battery replacement record of the battery replacement vehicle.
The step of identifying suspected anomalous users comprises:
and when the accumulated battery swapping times reach a third preset threshold, the degree electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a suspected abnormal user.
The third preset threshold value can be reasonably set according to specific conditions.
The accumulated power change times, the power mileage and the mileage difference are combined, the power change user is evaluated and identified, and the identification accuracy can be improved.
In the embodiment, the characteristic that data can be better reflected only by data of a certain scale is considered, the accumulated battery swapping frequency, the degree electric mileage and the mileage difference are combined, and when the accumulated battery swapping frequency reaches a certain amount, the abnormality recognition is performed on the battery swapping user based on the degree electric mileage and the mileage difference, so that the recognition accuracy can be improved.
In an optional implementation manner, after the battery swapping user is identified as a suspected abnormal user, the mileage difference is acquired as an abnormal mileage; and executing an exception handling operation based on the exception mileage.
Example 5
The embodiment provides an identification method for a battery swapping user.
In this embodiment, first, a single battery swapping mileage recorded in a battery swapping record of a battery swapping user, a battery swapping record mileage, and a driving trajectory fitting mileage are obtained. The specific implementation manner can refer to embodiment 1, and details are not described here.
And then, acquiring the kilowatt-hour mileage of the battery pack used by the battery replacement vehicle. And the electricity-degree mileage is obtained according to the ratio of the electricity-changing recorded mileage obtained by the electricity-changing recorded data of the electricity-changing vehicle to the total consumed electric quantity.
And then, acquiring the accumulated battery replacement times of the battery replacement user. As an optional implementation manner, the accumulated battery replacement frequency is within a preset time period T, and the battery replacement frequency of the battery replacement vehicle may be obtained through statistics according to a battery replacement record of the battery replacement vehicle. Setting the accumulated power conversion times of the power conversion user within a preset time period T as N1.
And then, acquiring a target frequency N2, wherein the target frequency is the frequency that the single power switching mileage is less than the preset mileage in N1 power switching within the preset time period T by the power switching user.
And then determining the ratio of the times of the single power exchange mileage being less than the preset mileage to the total power exchange times. This ratio is N2/N1.
The step of identifying suspected anomalous users comprises:
and when the proportion reaches a fourth preset threshold, the accumulated battery replacement times reach a third preset threshold, the degree-to-electricity mileage is less than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the battery replacement user as a suspected abnormal user.
The preset mileage can be reasonably set according to the situation. In an alternative embodiment, the predetermined mileage is 100 km.
The fourth preset threshold value can be reasonably set according to the situation.
The proportion of times that the single power exchange mileage is smaller than the preset mileage to the total power exchange times, the accumulated power exchange times, the degree power mileage and the mileage difference are combined, the power exchange user is evaluated and identified, and the identification accuracy can be improved.
In an optional implementation manner, after the battery swapping user is identified as a suspected abnormal user, the mileage difference is acquired as an abnormal mileage; and executing the exception handling operation based on the exception mileage.
In an implementable mode, when the mileage difference reaches a first preset threshold value, the battery swapping user is identified as a first-level suspected abnormal user;
further, when the electric mileage is smaller than a second preset threshold and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a second-level suspected abnormal user;
furthermore, when the accumulated battery swapping times reach a third preset threshold, the degree electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a three-level suspected abnormal user;
and further, when the ratio of the number of times that the single battery swapping mileage is less than the preset mileage to the total number of battery swapping reaches a fourth preset threshold, the accumulated battery swapping frequency reaches a third preset threshold, the degree-to-electricity mileage is less than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the battery swapping user as an abnormal user.
The suspected degree of the third-level suspected abnormal user is higher than that of the second-level suspected abnormal user, and the suspected degree of the second-level suspected abnormal user is higher than that of the first-level suspected abnormal user. Whether the abnormal user is the abnormal user or not is jointly identified through the cascaded multiple constraint conditions, and the accuracy of identifying the abnormal user is improved.
In specific implementation, referring to fig. 3, step S2 includes the following steps:
step S201, determining whether the mileage difference reaches a first preset threshold, if yes, performing step S202, and if no, performing step S210.
Step S202, identifying the battery swapping user as a primary suspected abnormal user.
Step S203, determining whether the electric mileage is less than a second preset threshold, if so, executing step S204.
And S204, identifying the battery swapping user as a secondary suspected abnormal user.
Step S205, determining whether the accumulated battery change times reaches a third preset threshold, if yes, executing step S206.
And S206, identifying the battery swapping user as a three-level suspected abnormal user.
Step S207, determining whether the ratio of the number of times that the single power exchange mileage is less than the preset mileage to the total number of power exchanges reaches a fourth preset threshold, if yes, executing step S208.
And S208, identifying the battery swapping user as an abnormal user.
And step S210, identifying the battery swapping user as a normal user.
The suspected degree of the third-level suspected abnormal user is higher than that of the second-level suspected abnormal user, and the suspected degree of the second-level suspected abnormal user is higher than that of the first-level suspected abnormal user. Whether the abnormal user is the abnormal user or not is jointly identified through the cascaded multiple constraint conditions, and the accuracy of identifying the abnormal user is improved.
In this embodiment, in consideration of the characteristic that data of a certain scale can be reflected better, the proportion of the number of times that the single power exchange mileage is less than the preset mileage to the total number of power exchanges, the accumulated power exchange number of times, the degree electric mileage and the mileage difference are combined, and when the proportion of the number of times that the single power exchange mileage is less than the preset mileage to the total number of power exchanges reaches a certain amount, the power exchange user is subjected to abnormality recognition based on the accumulated power exchange number of times, the degree electric mileage and the mileage difference, so that the recognition accuracy can be improved.
Example 6
Fig. 4 is a schematic structural diagram of an electronic device provided in this embodiment. The electronic device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein when the processor executes the program, the method for identifying the battery swapping user in any one of the embodiments 1-5 is realized. The electronic device 30 shown in fig. 4 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiment of the present invention.
The electronic device 30 may be embodied in the form of a general purpose computing device, which may be, for example, a server device. The components of the electronic device 30 may include, but are not limited to: the at least one processor 31, the at least one memory 32, and a bus 33 that couples various system components including the memory 32 and the processor 31.
The bus 33 includes a data bus, an address bus, and a control bus.
The memory 32 may include volatile memory, such as Random Access Memory (RAM)321 and/or cache memory 322, and may further include Read Only Memory (ROM) 323.
The processor 31 executes various functional applications and data processing, such as the method for identifying a battery replacement user according to any one of embodiments 1 to 5 of the present invention, by running the computer program stored in the memory 32.
The electronic device 30 may also communicate with one or more external devices 34 (e.g., keyboard, pointing device, etc.). Such communication may be through input/output (I/O) interfaces 35. Also, model-generating device 30 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via network adapter 36. As shown, network adapter 36 communicates with the other modules of model-generating device 30 via bus 33. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the model-generating device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.
It should be noted that although in the above detailed description several units/modules or sub-units/modules of the electronic device are mentioned, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more of the units/modules described above may be embodied in one unit/module according to embodiments of the invention. Conversely, the features and functions of one unit/module described above may be further divided into embodiments by a plurality of units/modules.
Example 7
The present embodiment provides a computer-readable storage medium on which a computer program is stored, the program, when executed by a processor, implementing the steps of the method for identifying a battery swapping user according to any one of embodiments 1 to 5.
More specific examples, among others, that the readable storage medium may employ may include, but are not limited to: a portable disk, a hard disk, random access memory, read only memory, erasable programmable read only memory, optical storage device, magnetic storage device, or any suitable combination of the foregoing.
In a possible implementation manner, the present invention can also be implemented in a form of a program product, which includes a program code, and when the program product runs on a terminal device, the program code is configured to enable the terminal device to execute the steps of implementing the method for identifying a battery swapping user according to any one of embodiments 1 to 5.
Where program code for carrying out the invention is written in any combination of one or more programming languages, the program code may be executed entirely on the user device, partly on the user device, as a stand-alone software package, partly on the user device, partly on a remote device or entirely on the remote device.
Example 8
The embodiment provides an identification system for a battery swapping user. Referring to fig. 5, the identification system for the battery swapping user includes an acquisition unit 201 and an identification unit 202.
The obtaining unit 201 is configured to obtain a power swapping record mileage of a power swapping user and a driving track fitting mileage corresponding to a power swapping vehicle of the power swapping user; the identification unit 202 is configured to identify whether the battery swapping user is a suspected abnormal user according to the battery swapping record mileage and the driving trajectory fitting mileage.
As an optional implementation manner, the obtaining unit 201 obtains a battery swapping record of a battery swapping user. The obtaining unit 201 obtains a power swapping record mileage of the power swapping user according to the power swapping record. The obtaining unit 201 obtains positioning information of a battery replacement vehicle of a battery replacement user in a driving process. The obtaining unit 201 obtains a driving track fitting mileage corresponding to the battery replacement vehicle according to the positioning information fitting.
In specific implementation, each time the battery swapping user performs a battery swapping operation, the battery swapping platform or the related server stores a battery swapping record of the battery swapping user. Therefore, the obtaining unit 201 obtains the battery swapping record of the battery swapping user from the battery swapping platform or the related server. And storing the corresponding driving mileage from the battery pack to the battery pack in the battery replacement record, namely the single battery replacement mileage. The obtaining unit 201 obtains a power swapping record mileage of the power swapping user in a preset time period according to a plurality of single power swapping mileage of the power swapping user in the preset time period (set to T).
In an optional implementation manner, a GPS device is arranged on the battery replacement vehicle, and in the running process of the battery replacement vehicle, the GPS device acquires the positioning information of the battery replacement vehicle according to a preset time interval, and the acquisition unit 201 may obtain the fitted driving range of the battery replacement vehicle in a certain time interval by fitting according to a plurality of positioning information acquired in the certain time interval. In specific implementation, the obtaining unit 201 divides the positioning information into local positioning information corresponding to each battery replacement record according to the battery replacement time recorded in each battery replacement record; according to each piece of local positioning information, the obtaining unit 201 obtains a local driving track fitting mileage corresponding to the battery replacement vehicle through fitting. That is, according to the battery replacement time (set to t1) corresponding to a certain battery pack when the battery pack is replaced and the battery replacement time (set to t2) corresponding to a battery pack when the battery pack is replaced, the obtaining unit 201 fits according to the time sequence according to the positioning information obtained by the GPS device in the time interval from t1 to t2, and the local driving track fitted mileage of the battery replacement vehicle in the time interval from t1 to t2, that is, the fitted mileage of the driving track of the battery replacement vehicle during the process from the battery pack to the battery pack when the battery pack is replaced can be obtained. The obtaining unit 201 obtains the driving track fitted mileage of the battery swapping user in the preset time period T according to the multiple local driving track fitted mileage of the battery swapping user in the preset time period T.
Then, the obtaining unit 201 obtains a mileage difference between the battery replacement record mileage and the driving trajectory fitting mileage; when the mileage difference reaches a first preset threshold, the identification unit 202 identifies the battery swapping user as a suspected abnormal user.
In the technical scheme, the priori knowledge with small difference between the mileage data from two different sources is used as the identification basis, so that whether the battery swapping user is a suspected abnormal user or not can be effectively identified.
In specific implementation, the preset time period T and the first preset threshold value may be reasonably set as required.
When a difference exists between the power swapping recorded mileage and the driving track fitting mileage, a situation that the power swapping user implements suspicious behaviors may exist. When the mileage difference is smaller than a first preset threshold value, the difference between the power swapping recorded mileage and the driving track fitting mileage is small, and even if suspicious behaviors exist, the influence of the suspicious behaviors on power swapping operation and management is not large, so that the suspicious behaviors are not classified as suspected abnormal users. If the mileage difference reaches a first preset threshold value, the difference between the power swapping recorded mileage and the driving track fitting mileage is large, the probability of suspicious behaviors is high, and the influence on power swapping operation and management is large, so that the power swapping user is to be classified as a suspected abnormal user.
In an alternative embodiment, when the mileage difference reaches a first preset threshold, it can be considered that there is an abnormal behavior in which the mileage data is falsified. On one hand, the abnormal behavior can generate influence on resources, such as loss of charging for battery replacement operation; on the other hand, the evaluation of the normal service life and the health life cycle of the battery can be influenced in safety.
In an optional implementation manner, after the battery swapping user is identified as a suspected abnormal user, the identifying unit 202 obtains a mileage difference as an abnormal mileage; the recognition unit 202 performs an abnormality processing operation based on the abnormal mileage.
In this embodiment, based on prior knowledge that battery swapping for an electric vehicle is related to travel mileage of the electric vehicle, from the perspective of mileage data, whether a swapping user is a suspected abnormal user is automatically identified according to mileage data of two different sources, namely, a swapping record mileage and a travel track fitting mileage, so that the efficiency of identifying the abnormal user can be improved, and the reliability of an identification result of the abnormal user can also be improved.
Example 9
The embodiment provides an identification system for a battery swapping user.
In this embodiment, after obtaining the single power conversion mileage and the partial travel track fitting mileage, the obtaining unit 201 obtains a sub-average power conversion record mileage of the power conversion user according to the multiple single power conversion mileage, and obtains a sub-average travel track fitting mileage corresponding to the power conversion vehicle according to the multiple partial travel track fitting mileage.
And if the battery replacement vehicle is configured to replace the battery within the preset time period T for N times, the secondary average battery replacement recorded mileage is the average value of the N single battery replacement mileage, and the secondary average driving track fitting mileage is the average value of the N local driving track fitting mileage.
In this embodiment, it is considered that data of a certain scale can better reflect characteristics of the data, and then subsequent data processing can be effectively performed on the basis of the characteristics of the data, so that whether the swapping user is a suspected abnormal user or not is identified by using the secondary average swapping record mileage and the secondary average driving track fitting mileage as bases, and the accuracy of an abnormal user identification result can be improved.
Then, the obtaining unit 201 obtains a mileage difference between the secondary average battery replacement record mileage and the secondary average travel track fitting mileage; when the mileage difference reaches a preset threshold, the identification unit 202 identifies the battery swapping user as a suspected abnormal user.
In an optional implementation manner, after identifying that the battery swapping user is a suspected abnormal user, the obtaining unit 201 obtains the mileage difference as an abnormal mileage; the acquisition unit 201 performs an exception handling operation based on the exception mileage.
Example 10
The embodiment provides an identification system for a battery swapping user.
In this embodiment, first, the obtaining unit 201 obtains the battery replacement record mileage and the driving track fitting mileage. The specific implementation manner can refer to embodiment 8, and details are not described here.
Then, the acquisition unit 201 acquires the kilowatt-hour mileage of the battery pack used by the battery replacement vehicle. And the electricity-degree mileage is obtained according to the ratio of the electricity-changing recorded mileage obtained by the electricity-changing recorded data of the electricity-changing vehicle to the total consumed electric quantity.
When the electric mileage is less than the second preset threshold and the mileage difference reaches the first preset threshold, the identification unit 202 identifies the battery swapping user as a suspected abnormal user.
The second preset threshold value can be set reasonably according to specific situations.
The power-measuring mileage and the mileage difference are combined, the power-change user is evaluated and identified, and the identification accuracy can be improved.
In the embodiment, based on the priori knowledge that the electric mileage has an upper limit, the electric mileage and the mileage difference are combined, the abnormality of the power change user is identified, and the identification accuracy can be improved.
In an optional implementation manner, after the battery swapping user is identified as a suspected abnormal user, the identification unit 202 obtains a mileage difference as an abnormal mileage; the recognition unit 202 performs an abnormality processing operation based on the abnormal mileage.
Example 11
The embodiment provides an identification system for a battery swapping user.
In this embodiment, the obtaining unit 201 first obtains the battery replacement record mileage and the driving track fitting mileage. The specific implementation manner can refer to embodiment 8, and details are not described here.
Then, the acquisition unit 201 acquires the kilowatt-hour mileage of the battery pack used by the battery replacement vehicle. And the electricity-degree mileage is obtained according to the ratio of the electricity-changing recorded mileage obtained by the electricity-changing recorded data of the electricity-changing vehicle to the total consumed electric quantity.
Then, the acquisition unit 201 acquires the accumulated battery replacement frequency of the battery replacement user. As an optional implementation manner, the accumulated battery replacement frequency is within a preset time period T, and the battery replacement frequency of the battery replacement vehicle may be obtained through statistics according to a battery replacement record of the battery replacement vehicle.
When the accumulated battery swapping frequency reaches a third preset threshold, the degree electric mileage is less than a second preset threshold, and the mileage difference reaches a first preset threshold, the identification unit 202 identifies the battery swapping user as a suspected abnormal user.
The third preset threshold value can be reasonably set according to specific conditions.
The accumulated power change times, the power mileage and the mileage difference are combined, the power change user is evaluated and identified, and the identification accuracy can be improved.
In the embodiment, the characteristic that data can be better reflected only by data of a certain scale is considered, the accumulated battery swapping frequency, the degree electric mileage and the mileage difference are combined, and when the accumulated battery swapping frequency reaches a certain amount, the abnormality recognition is performed on the battery swapping user based on the degree electric mileage and the mileage difference, so that the recognition accuracy can be improved.
In an optional implementation manner, after the battery swapping user is identified as a suspected abnormal user, the identification unit 202 obtains a mileage difference as an abnormal mileage; the recognition unit 202 performs an abnormality processing operation based on the abnormal mileage.
Example 12
The embodiment provides an identification system for a battery swapping user.
In this embodiment, the obtaining unit 201 first obtains a single battery swapping mileage recorded in a battery swapping record of a battery swapping user, and obtains a battery swapping record mileage and a driving trajectory fitting mileage. The specific implementation manner can refer to embodiment 8, and details are not described here.
Then, the acquisition unit 201 acquires the kilowatt-hour mileage of the battery pack used by the battery replacement vehicle. And the electricity-degree mileage is obtained according to the ratio of the electricity-changing recorded mileage obtained by the electricity-changing recorded data of the electricity-changing vehicle to the total consumed electric quantity.
Then, the acquisition unit 201 acquires the accumulated battery swapping times of the battery swapping user. As an optional implementation manner, the accumulated battery replacement frequency is within a preset time period T, and the battery replacement frequency of the battery replacement vehicle may be obtained through statistics according to a battery replacement record of the battery replacement vehicle. Setting the accumulated power conversion times of the power conversion user within a preset time period T as N1.
Then, the obtaining unit 201 obtains a target number of times N2, where the target number of times is the number of times that a single power swapping mileage is less than a preset mileage in N1 power swaps of the power swapping user within a preset time period T.
Then, the obtaining unit 201 determines the ratio of the number of times that the single power exchange mileage is less than the preset mileage to the total number of power exchanges. This ratio is N2/N1.
When the percentage reaches a fourth preset threshold, the accumulated battery swapping times reaches a third preset threshold, the degree electric mileage is less than a second preset threshold, and the mileage difference reaches a first preset threshold, the identification unit 202 identifies the battery swapping user as a suspected abnormal user.
The preset mileage can be reasonably set according to the situation. In an alternative embodiment, the predetermined mileage is 100 km.
The fourth preset threshold value can be reasonably set according to the situation.
The proportion of times that the single power exchange mileage is smaller than the preset mileage to the total power exchange times, the accumulated power exchange times, the degree power mileage and the mileage difference are combined, the power exchange user is evaluated and identified, and the identification accuracy can be improved.
In an optional implementation manner, after the battery swapping user is identified as a suspected abnormal user, the identification unit 202 obtains a mileage difference as an abnormal mileage; the recognition unit 202 performs an abnormality processing operation based on the abnormal mileage.
In an implementable manner, when the mileage difference reaches a first preset threshold, identifying the battery swapping user as a first-level suspected abnormal user;
further, when the electric mileage is smaller than a second preset threshold and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a second-level suspected abnormal user;
furthermore, when the accumulated battery swapping times reach a third preset threshold, the degree electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a three-level suspected abnormal user;
and further, when the ratio of the number of times that the single power exchange mileage is less than the preset mileage to the total number of power exchange reaches a fourth preset threshold, the accumulated power exchange number reaches a third preset threshold, the degree power mileage is less than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the power exchange user as an abnormal user.
The suspected degree of the third-level suspected abnormal user is higher than that of the second-level suspected abnormal user, and the suspected degree of the second-level suspected abnormal user is higher than that of the first-level suspected abnormal user. Whether the abnormal user is the abnormal user or not is jointly identified through the cascaded multiple constraint conditions, and the accuracy of identifying the abnormal user is improved.
In this embodiment, in consideration of the characteristic that data of a certain scale can be reflected better, the proportion of the number of times that the single power exchange mileage is less than the preset mileage to the total number of power exchanges, the accumulated power exchange number of times, the degree electric mileage and the mileage difference are combined, and when the proportion of the number of times that the single power exchange mileage is less than the preset mileage to the total number of power exchanges reaches a certain amount, the power exchange user is subjected to abnormality recognition based on the accumulated power exchange number of times, the degree electric mileage and the mileage difference, so that the recognition accuracy can be improved.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that this is by way of example only, and that the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the spirit and scope of the invention, and these changes and modifications are within the scope of the invention.
Claims (11)
1. A method for identifying a battery swapping user is characterized by comprising the following steps:
acquiring a power swapping record mileage of a power swapping user and a driving track fitting mileage corresponding to a power swapping vehicle of the power swapping user;
and identifying whether the battery swapping user is a suspected abnormal user or not according to the battery swapping recorded mileage and the driving track fitting mileage.
2. The method for identifying a battery swapping user according to claim 1, wherein the obtaining of the battery swapping record mileage of the battery swapping user and the driving track fitting mileage corresponding to the battery swapping vehicle of the battery swapping user comprises:
acquiring a battery swapping record of a battery swapping user;
acquiring a power swapping record mileage of the power swapping user according to the power swapping record;
acquiring positioning information of a battery replacement vehicle of the battery replacement user in a running process;
and fitting according to the positioning information to obtain a driving track fitting mileage corresponding to the battery replacing vehicle.
3. The method for identifying a power swapping user according to claim 2, wherein the power swapping recorded mileage is an average power swapping recorded mileage, and the driving track fitting mileage is an average driving track fitting mileage; the obtaining of the power swapping record mileage of the power swapping user according to the power swapping record comprises:
acquiring single battery replacement mileage recorded in each battery replacement record;
obtaining the secondary average battery replacement record mileage of the battery replacement user according to the plurality of single battery replacement mileage;
the obtaining of the driving track fitting mileage corresponding to the battery replacement vehicle according to the positioning information fitting comprises:
dividing the positioning information into local positioning information respectively corresponding to each battery changing record according to the battery changing time recorded in each battery changing record;
fitting according to each piece of local positioning information to obtain a local driving track fitting mileage corresponding to the battery replacement vehicle;
and obtaining the sub-average driving track fitting mileage corresponding to the battery replacement vehicle according to the plurality of partial driving track fitting mileage.
4. The method for identifying a battery swapping user according to claim 1, wherein the identifying whether the battery swapping user is a suspected abnormal user according to the battery swapping record mileage and the driving track fitting mileage comprises:
acquiring the mileage difference between the battery swapping record mileage and the driving track fitting mileage;
and when the mileage difference reaches a first preset threshold value, identifying the battery swapping user as a suspected abnormal user.
5. The method for identifying a battery swapping user as claimed in claim 4, wherein the method for identifying a battery swapping user further comprises:
acquiring the kilowatt-hour mileage of a battery pack used by the battery replacement vehicle;
when the mileage difference reaches a first preset threshold, identifying that the battery swapping user is a suspected abnormal user includes:
and when the electric mileage is smaller than a second preset threshold value and the mileage difference reaches a first preset threshold value, identifying the battery swapping user as a suspected abnormal user.
6. The battery swapping user identification method of claim 5, wherein the battery swapping user identification method further comprises:
acquiring the accumulated battery swapping times of the battery swapping user;
when the electric mileage is smaller than a second preset threshold and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a suspected abnormal user includes:
and when the accumulated battery swapping times reach a third preset threshold, the degree electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a suspected abnormal user.
7. The method for identifying a battery swapping user as claimed in claim 6, wherein the method for identifying a battery swapping user further comprises:
acquiring single battery replacement mileage recorded in a battery replacement record of the battery replacement user;
determining the ratio of the times of the single battery replacement mileage being less than the preset mileage to the total times of battery replacement;
when the accumulated battery swapping frequency reaches a third preset threshold, the degree electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying that the battery swapping user is a suspected abnormal user includes:
and when the occupation ratio reaches a fourth preset threshold, the accumulated battery swapping times reaches a third preset threshold, the degree electric mileage is smaller than a second preset threshold, and the mileage difference reaches a first preset threshold, identifying the battery swapping user as a suspected abnormal user.
8. The method for identifying a battery swapping user as claimed in any one of claims 1 to 7, wherein the method for identifying a battery swapping user further comprises:
after the battery replacement user is identified as a suspected abnormal user, acquiring the mileage difference as abnormal mileage;
and executing an exception handling operation based on the exception mileage.
9. The identification system for the battery replacement user is characterized by comprising an acquisition unit and an identification unit;
the acquisition unit is used for acquiring a power swapping record mileage of a power swapping user and a driving track fitting mileage corresponding to a power swapping vehicle of the power swapping user;
the identification unit is used for identifying whether the battery swapping user is a suspected abnormal user or not according to the battery swapping recorded mileage and the driving track fitting mileage.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for identifying a battery swapping user according to any of claims 1-8 when executing the computer program.
11. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for identifying a battery swapping user of any of claims 1-8.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116662818A (en) * | 2023-08-01 | 2023-08-29 | 杭州宇谷科技股份有限公司 | Abnormal power change user identification method, system, equipment and readable storage medium |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000346670A (en) * | 1999-06-04 | 2000-12-15 | Yazaki Corp | Electronic odometer apparatus |
| CN104239737A (en) * | 2014-09-25 | 2014-12-24 | 许继电气股份有限公司 | Numerical value correction method of battery charging and changing station vehicle monitoring system |
| CN205075761U (en) * | 2015-09-28 | 2016-03-09 | 谢子聪 | Electronic passenger car trade electric controller |
| EP3070772A2 (en) * | 2015-03-16 | 2016-09-21 | Thunder Power Hong Kong Ltd. | Electric vehicle thermal management system |
| CN106054108A (en) * | 2016-05-27 | 2016-10-26 | 北京智芯微电子科技有限公司 | Electricity utilization anomaly detection method and electricity utilization anomaly detection device |
| CN107305372A (en) * | 2016-04-25 | 2017-10-31 | 韩磊 | The electric automobile energy monitoring of the remote monitoring of system for cloud computing framework and more draping |
| CN109313825A (en) * | 2018-08-27 | 2019-02-05 | 深圳市锐明技术股份有限公司 | Vehicle mileage calculation method, system and terminal device |
| CN109979103A (en) * | 2017-12-27 | 2019-07-05 | 奥动新能源汽车科技有限公司 | Electrical changing station server-side and change electric treatment method, electrical changing station changes method for electrically and system |
| CN110418173A (en) * | 2019-07-18 | 2019-11-05 | 北京达佳互联信息技术有限公司 | Determine method, apparatus, server and the storage medium of exception account |
| CN110672123A (en) * | 2019-09-27 | 2020-01-10 | 吉旗（成都）科技有限公司 | Deviation correcting method and device for mileage |
| CN110864704A (en) * | 2018-08-28 | 2020-03-06 | 百度在线网络技术（北京）有限公司 | Automatic driving mileage statistical method, device and equipment |
| CN111208445A (en) * | 2020-02-25 | 2020-05-29 | 中国第一汽车股份有限公司 | Power battery abnormal monomer identification method and system |
| CN111582856A (en) * | 2019-02-18 | 2020-08-25 | 奥动新能源汽车科技有限公司 | Processing method and processing system for power swapping cost of cloud and power swapping station |
| CN111654089A (en) * | 2020-06-24 | 2020-09-11 | 青岛铁骑网络科技有限公司 | Battery intelligent charging and replacing platform |
| CN111746336A (en) * | 2019-03-26 | 2020-10-09 | 奥动新能源汽车科技有限公司 | Intelligent battery replacement method and system for battery replacement station |
| CN111746339A (en) * | 2019-03-26 | 2020-10-09 | 奥动新能源汽车科技有限公司 | Intelligent battery replacement method and system for battery replacement station |
| CN111862387A (en) * | 2020-07-15 | 2020-10-30 | 广州智鹏车联网科技有限公司 | Method and device for storing total mileage of vehicle instrument |
-
2020
- 2020-12-31 CN CN202011623684.2A patent/CN114692082A/en active Pending
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000346670A (en) * | 1999-06-04 | 2000-12-15 | Yazaki Corp | Electronic odometer apparatus |
| CN104239737A (en) * | 2014-09-25 | 2014-12-24 | 许继电气股份有限公司 | Numerical value correction method of battery charging and changing station vehicle monitoring system |
| EP3070772A2 (en) * | 2015-03-16 | 2016-09-21 | Thunder Power Hong Kong Ltd. | Electric vehicle thermal management system |
| CN205075761U (en) * | 2015-09-28 | 2016-03-09 | 谢子聪 | Electronic passenger car trade electric controller |
| CN107305372A (en) * | 2016-04-25 | 2017-10-31 | 韩磊 | The electric automobile energy monitoring of the remote monitoring of system for cloud computing framework and more draping |
| CN106054108A (en) * | 2016-05-27 | 2016-10-26 | 北京智芯微电子科技有限公司 | Electricity utilization anomaly detection method and electricity utilization anomaly detection device |
| CN109979103A (en) * | 2017-12-27 | 2019-07-05 | 奥动新能源汽车科技有限公司 | Electrical changing station server-side and change electric treatment method, electrical changing station changes method for electrically and system |
| CN109313825A (en) * | 2018-08-27 | 2019-02-05 | 深圳市锐明技术股份有限公司 | Vehicle mileage calculation method, system and terminal device |
| CN110864704A (en) * | 2018-08-28 | 2020-03-06 | 百度在线网络技术（北京）有限公司 | Automatic driving mileage statistical method, device and equipment |
| CN111582856A (en) * | 2019-02-18 | 2020-08-25 | 奥动新能源汽车科技有限公司 | Processing method and processing system for power swapping cost of cloud and power swapping station |
| CN111746336A (en) * | 2019-03-26 | 2020-10-09 | 奥动新能源汽车科技有限公司 | Intelligent battery replacement method and system for battery replacement station |
| CN111746339A (en) * | 2019-03-26 | 2020-10-09 | 奥动新能源汽车科技有限公司 | Intelligent battery replacement method and system for battery replacement station |
| CN110418173A (en) * | 2019-07-18 | 2019-11-05 | 北京达佳互联信息技术有限公司 | Determine method, apparatus, server and the storage medium of exception account |
| CN110672123A (en) * | 2019-09-27 | 2020-01-10 | 吉旗（成都）科技有限公司 | Deviation correcting method and device for mileage |
| CN111208445A (en) * | 2020-02-25 | 2020-05-29 | 中国第一汽车股份有限公司 | Power battery abnormal monomer identification method and system |
| CN111654089A (en) * | 2020-06-24 | 2020-09-11 | 青岛铁骑网络科技有限公司 | Battery intelligent charging and replacing platform |
| CN111862387A (en) * | 2020-07-15 | 2020-10-30 | 广州智鹏车联网科技有限公司 | Method and device for storing total mileage of vehicle instrument |
Non-Patent Citations (1)
| Title |
|---|
| 房永强;: "换电式纯电动客车CAN网络方案设计", 客车技术与研究, no. 01, pages 41 - 43 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116662818A (en) * | 2023-08-01 | 2023-08-29 | 杭州宇谷科技股份有限公司 | Abnormal power change user identification method, system, equipment and readable storage medium |
| CN116662818B (en) * | 2023-08-01 | 2023-11-03 | 杭州宇谷科技股份有限公司 | Abnormal power change user identification method, system, equipment and readable storage medium |
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