CN116910494A - Intelligent charging pile service method, system and storage medium for intelligent communities - Google Patents
Intelligent charging pile service method, system and storage medium for intelligent communities Download PDFInfo
- Publication number
- CN116910494A CN116910494A CN202311177100.7A CN202311177100A CN116910494A CN 116910494 A CN116910494 A CN 116910494A CN 202311177100 A CN202311177100 A CN 202311177100A CN 116910494 A CN116910494 A CN 116910494A
- Authority
- CN
- China
- Prior art keywords
- charging
- user
- charging pile
- screening
- sites
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000012216 screening Methods 0.000 claims abstract description 98
- 238000012417 linear regression Methods 0.000 claims abstract description 12
- 238000010586 diagram Methods 0.000 claims description 11
- 230000001419 dependent effect Effects 0.000 claims description 5
- 238000004590 computer program Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 claims description 3
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 230000006870 function Effects 0.000 description 3
- 238000010295 mobile communication Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/12—Electric charging stations
Landscapes
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention provides a smart community intelligent charging pile service method, a system and a storage medium, and relates to the technical field of intelligent charging piles, wherein the method comprises the steps of obtaining the residual electric quantity of a user vehicle and the driving data of a month; estimating the actual remaining mileage of the user vehicle according to the remaining electric quantity and the driving data of the user vehicle; receiving a charging reservation order sent by a user, wherein the charging reservation order comprises a user geographic position, a reserved charging pile brand and a reserved charging time point; through built-in screening logic, intelligent generation of a recommendation scheme is performed based on the charging reservation order; and generating a charging order and navigation information according to the recommended scheme selected by the user, and feeding back the charging order and the navigation information to the user. The invention has the advantages that: by providing a screening logic, several practicable charging schemes can be provided to the user quickly and efficiently. By constructing the linear regression model, the actual remaining mileage of the user vehicle and the number of idle charging piles can be estimated, and the rationality and accuracy of the recommended scheme are improved.
Description
Technical Field
The invention relates to the technical field of intelligent charging piles, in particular to a smart community intelligent charging pile service method, a smart community intelligent charging pile service system and a storage medium.
Background
The intelligent community is a new idea of community management and is a new mode of social management innovation under new situation. The intelligent community is an integrated application of new generation information technologies such as Internet of things, cloud computing and mobile Internet, and provides a safe, comfortable and convenient modern and intelligent living environment for community residents. Along with the increasing number of electric vehicles in recent years, intelligent charging piles also enter an intelligent community.
The existing intelligent charging pile service cannot be comprehensively analyzed based on the requirements of the vehicle owners and the operation data of the charging piles, and a recommended scheme cannot be intelligently planned, so that the available charging piles are difficult to conveniently and rapidly find when the vehicle owners need to perform the charging service.
Disclosure of Invention
Accordingly, the present invention is directed to a smart community intelligent charging pile service method, system and storage medium, which solve all or one of the above mentioned problems in the prior art.
Based on the above purpose, the invention provides an intelligent charging pile service method for an intelligent community, which comprises the following steps:
acquiring the residual electric quantity of a user vehicle and the running data of the last month;
estimating the actual remaining mileage of the user vehicle according to the remaining electric quantity and the driving data of the user vehicle;
receiving a charging reservation order sent by a user, wherein the charging reservation order comprises a user geographic position, a reserved charging pile brand and a reserved charging time point;
through built-in screening logic, intelligent generation of a recommendation scheme is performed based on the charging reservation order;
and generating a charging order and navigation information according to the recommended scheme selected by the user, and feeding back the charging order and the navigation information to the user.
Optionally, the estimating the operable time of the user vehicle according to the remaining power of the user vehicle and the driving data of the last month includes: acquiring driving data of a user vehicle for a month, wherein the driving data comprises a date, a driving mileage and a driving time; taking the driving mileage as an independent variable and the driving time as a dependent variable, and making a scatter diagram; performing linear fitting on the scatter diagram to obtain an electric quantity-mileage correlation linear equation; and carrying the endurance mileage of the user vehicle into a related linear equation, and calculating to obtain the operable time of the user vehicle.
Optionally, the intelligent generation recommendation scheme based on the charging reservation order through the built-in screening logic comprises the following steps:
step one: screening all charging pile sites with the distance not exceeding a preset range threshold value from the geographic position of the user based on the geographic position of the user, marking the charging pile sites as distance primary screening sites, and forming a primary screening charging pile site set U by all the distance primary screening sites, wherein U= { U 1 、u 2 、...、u n }，u i (i=1, 2., n) is the i-th distance prescreening station;
step two: screening out charging stake sites including at least one reservation charging stake brand from the primary screening sites based on reservation charging stake brands, marking the charging stake sites as brand screening sites, and forming a brand screening site set U by all brand screening sites p ，U p ={u p1 、u p2 、...、u pl }，u px (x=1, 2, a l) is the x brand screening site;
step three: based on historical operation data of the charging pile station, a charging pile idle number-moment linear regression model is established, and U is predicted at a reservation time point based on the charging pile idle number-moment linear regression model P The number of hollow charging piles in the charging pile stations is not zero, charging pile stations with the number of hollow charging piles being not zero in the product plate screening stations are screened out and are marked as time screening stations, and all the time screening stations form a time screening station set U ps ，U ps ={u ps1 、u ps2 、...、u psm }，u psy (y=1, 2,..m) is the y-th time screening site;
step four: based on the distance between the charging pile site and the user position, the method comprises the following steps of ps All charging pile sites are orderly sequenced from near to far, and the cloud server preferentially recommends the charging pile site closest to the user position to the vehicle owner mobile terminal.
Optionally, the pair sets U ps All charging pile stations are ordered from near to far, and the method comprises the following steps:
generating three range areas by taking the user position as the center according to a first preset distance, a second preset distance and a third preset distance, marking the range area with the distance from the user position smaller than the first preset distance as a first range area, marking the range area with the distance from the user position larger than the first preset distance smaller than the second preset distance as a second range area, and marking the range area with the distance from the user position larger than the second preset distance smaller than the third preset distance as a third range area;
adding special marks to the time screening sites when the user uses the overcharge pile sites to form special mark time screening sites;
all time screening sites falling into a first range zone are formed into a first range site set U ps 1 All time screening sites falling into a second range zone are formed into a second range site set U ps 2 All time screening sites falling into a third range zone are formed into a third range site set U ps 3 ；
Judging a first range site set U ps 1 Whether or not there is an element;
if the first range site is set U ps 1 If there is an element, judging a first range site set U ps 1 Screening whether the element has special mark time to screen sites, if so, collecting a first range site set U ps 1 The special mark time screening site in the list is recommended to the user, if not, a first range site set U is screened out ps 1 The time screening site with the maximum predicted number of idle charging piles in the elements is recommended to a user;
if the first range site is set U ps 1 Judging the second range site set U if no element exists ps 2 Whether or not there is an element;
if the second range site is set U ps 2 If there is an element, judging a second range site set U ps 2 Among the elements areScreening sites with special mark time, if yes, collecting sites in a second range U ps 2 The special mark time screening site in the list is recommended to the user, if not, a second range site set U is screened out ps 2 The time screening site with the maximum predicted number of idle charging piles in the elements is recommended to a user;
if the second range site is set U ps 2 Judging the third range site set U if no element exists ps 3 Whether or not there is an element;
if the third range site is set U ps 3 If there is an element, judging a third range site set U ps 3 Screening sites if the elements have special marked time, if so, collecting the sites in a third range U ps 3 The special mark time screening site in the list is recommended to the user, if not, a third range site set U is screened out ps 3 The time screening site with the maximum predicted number of idle charging piles in the elements is recommended to a user;
if the third range site is set U ps 3 And outputting a nearby non-recommended site signal to the user terminal if no element exists.
Optionally, the preset range threshold is 5 km, the first preset distance is 1 km, the second preset distance is 3 km, and the third preset distance is 5 km.
Optionally, the building of the charging pile idle number-moment linear regression model based on the historical operation data of the charging pile station includes the following steps: acquiring the number of idle charging piles at a charging pile station in a certain fixed time in the past 30 days; taking the idle number of the charging piles as a dependent variable, taking the date as the independent variable, and making a scatter diagram; and performing linear fitting on the scatter diagram to obtain an idle number-moment linear regression model.
Furthermore, an intelligent charging pile service system for the intelligent communities is provided, and the intelligent charging pile service method for the intelligent communities is realized, which comprises the following steps: the cloud server comprises a vehicle owner mobile terminal, a cloud server and a charging pile server.
The vehicle owner mobile terminal is used for sending a charging reservation order and paying the order;
the cloud server is in wireless connection with the vehicle owner mobile terminal and is used for processing the charging reservation order, calculating the running time of the user vehicle, generating an optimal scheme and generating navigation information;
the charging pile server is in wireless connection with the cloud server and is used for inquiring, storing and updating the basic information of the charging pile site.
Optionally, the vehicle owner mobile terminal includes: the system comprises a map module, a storage module, a payment module and a control module.
The map module acquires geographic position information by adopting a GPS system;
the storage module is used for collecting vehicle running information;
the payment module is used for being connected with payment software to realize remote payment;
the control module is used for controlling the charging pile to perform activities such as charging, reservation, stopping charging and the like.
Optionally, the charging pile server includes: management module, operation module and comprehensive inquiry.
The management module is used for carrying out centralized management on basic information of the charging pile station;
the operation module is used for charging and managing the user;
the comprehensive query is used for comprehensively analyzing and querying the data of the management module and the operation module.
Further, a computer readable storage medium is provided, and a computer program is stored on the storage medium, and the computer program is executed to execute the service method of the intelligent community intelligent charging pile.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides an intelligent charging pile service method for an intelligent community, which comprises screening logic, wherein the screening logic can rapidly and effectively screen all charging pile sites in a preset range according to user requirements, and provide several practicable charging schemes for users. Meanwhile, by constructing a linear regression model, the actual remaining mileage of the user vehicle and the number of idle charging piles of the charging pile station are estimated, so that the rationality and accuracy of the recommended scheme are improved. Still provide an intelligent electric pile service system that fills of wisdom community, this system contains multiple functional module, lets user experience more comfortable and convenient.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a schematic flow chart of a smart community intelligent charging pile service method provided by the embodiment of the invention;
fig. 2 is a schematic flow chart of step S400 of the intelligent charging pile service method in the intelligent community of fig. 1;
fig. 3 is a flowchart illustrating a step S440 of the intelligent charging pile service method in the intelligent community of fig. 2;
fig. 4 is a schematic structural diagram of an intelligent charging pile service system for an intelligent community according to an embodiment of the present invention.
Detailed Description
The following description is presented to enable one of ordinary skill in the art to make and use the invention. The preferred embodiments in the following description are by way of example only and other obvious variations will occur to those skilled in the art.
The present invention will be further described in detail below with reference to specific embodiments and with reference to the accompanying drawings, in order to make the objects, technical solutions and advantages of the present invention more apparent.
As shown in fig. 1, fig. 1 is a flowchart of a service method of an intelligent charging pile for an intelligent community, provided by the embodiment of the invention, including:
s100, acquiring the residual electric quantity of a user vehicle and the running data of the last month;
wherein, the driving data of the last month refers to the driving data of 30 days from the current beginning. The cloud server acquires the residual electric quantity of the user vehicle and the running data of the last month from the vehicle owner mobile terminal, and the vehicle owner mobile terminal acquires and stores the historical running records and the current running records of the vehicle machine system through wireless connection with the vehicle machine system.
S200, estimating the actual remaining mileage of the user vehicle according to the remaining electric quantity of the user vehicle and the running data of the last month;
the method comprises the specific steps of: acquiring driving data of a user vehicle for a month, wherein the driving data comprises a date, a driving mileage and a driving time; taking the driving mileage as an independent variable and the driving time as a dependent variable, and making a scatter diagram; performing linear fitting on the scatter diagram to obtain an electric quantity-mileage linear equation; and carrying the residual electric quantity of the user vehicle into a related linear equation, and calculating to obtain the actual residual mileage of the user vehicle.
S300, receiving a charging reservation order sent by a user, wherein the charging reservation order comprises a user geographic position, a reserved charging pile brand and a reserved charging time point;
s400, intelligently generating a recommendation scheme based on the charging reservation order through built-in screening logic;
the built-in screening logic takes brand information of the charging piles, reservation time information and distance information in a charging reservation order as input, and takes brand information of charging pile sites, position information of the charging pile sites, distance information between the charging pile sites and a mobile terminal of a vehicle owner, and number information of charging piles contained in the charging pile sites as output in a recommendation scheme, and referring to fig. 2, step 400 specifically includes:
s410, screening all charging pile sites with the distance not exceeding a preset range threshold value from the geographic position of the user based on the geographic position of the user, marking the charging pile sites as distance primary screening sites, and forming a primary screening charging pile site set U by all the distance primary screening sites, wherein U= { U 1 、u 2 、...、u n }，u i (i=1, 2, a n) is the i-th distance from the preliminary screening station.
S420, screening out that the distance primary screening site comprises at least one reserved charging based on the reserved charging pile brandThe charging stake station of the electric stake brand is marked as a brand screening station, and all the brand screening stations form a brand screening station set U p ，U p ={u p1 、u p2 、...、u pl }，u px (x=1, 2, a l) is the x brand screening site;
s430, based on historical operation data of the charging pile sites, establishing a charging pile idle number-moment linear regression model, and predicting U at a reservation time point based on the charging pile idle number-moment linear regression model P The number of hollow charging piles in the charging pile stations is not zero, charging pile stations with the number of hollow charging piles being not zero in the product plate screening stations are screened out and are marked as time screening stations, and all the time screening stations form a time screening station set U ps ，U ps ={u ps1 、u ps2 、...、u psm }，u psy (y=1, 2,..m) is the y-th time screening site;
s440, based on the distance between the charging pile site and the user position, collecting U ps And all the charging pile sites are orderly sequenced from near to far, and the cloud server recommends the charging pile sites to the vehicle owner mobile terminal according to the sequencing result.
As shown in fig. 3, step S440 further includes:
step one, taking the user position as the center, generating three range areas according to a first preset distance, a second preset distance and a third preset distance, marking the range area with the distance from the user position smaller than the first preset distance as a first range area, marking the range area with the distance from the user position larger than the first preset distance smaller than the second preset distance as a second range area, and marking the range area with the distance from the user position larger than the second preset distance smaller than the third preset distance as a third range area;
step two, adding special marks to the time screening site when the user uses the overcharge pile site to form a special mark time screening site;
step three, all time screening sites falling into the first range area are formed into a first range site set U ps 1 All falling within the second rangeTime screening sites forming a second range site set U ps 2 All time screening sites falling into a third range zone are formed into a third range site set U ps 3 ；
Step four, judging a first range site set U ps 1 Whether or not there is an element;
step five, if the first range site set U ps 1 If there is an element, judging a first range site set U ps 1 Screening whether the element has special mark time to screen sites, if so, collecting a first range site set U ps 1 The special mark time screening site in the list is recommended to the user, if not, a first range site set U is screened out ps 1 The time screening site with the maximum predicted number of idle charging piles in the elements is recommended to a user;
step six, if the first range site set U ps 1 Judging the second range site set U if no element exists ps 2 Whether or not there is an element;
step seven, if the second range site set U ps 2 If there is an element, judging a second range site set U ps 2 Screening whether the element has special mark time to screen sites, if so, collecting the sites in the second range U ps 2 The special mark time screening site in the list is recommended to the user, if not, a second range site set U is screened out ps 2 The time screening site with the maximum predicted number of idle charging piles in the elements is recommended to a user;
step eight, if the second range site set U ps 2 Judging the third range site set U if no element exists ps 3 Whether or not there is an element;
step nine, if the third range site set U ps 3 If there is an element, judging a third range site set U ps 3 Screening sites if the elements have special marked time, if so, collecting the sites in a third range U ps 3 The special mark time screening site in the list is recommended to the user, if not, a third range site set U is screened out ps 3 The time screening site with the maximum predicted number of idle charging piles in the elements is recommended to a user;
step ten, if the third range site set U ps 3 And outputting a nearby non-recommended site signal to the user terminal if no element exists.
Wherein the preset range threshold is 5 km, the first preset distance is 1 km, the second preset distance is 3 km, and the third preset distance is 5 km.
S500, generating a charging order and navigation information according to the recommended scheme selected by the user, and feeding back the charging order and the navigation information to the user.
The charging order comprises the brand of the charging piles, the site positions of the charging piles, the charging time, the charging voltage of the site, the charging current, the charge rate of each degree of electricity, the number of idle charging piles and the total number of charging piles.
The navigation information refers to a shortest route planned and generated by the cloud server by taking the position of a charging pile site in a recommended scheme selected by a user as a destination and the position of the user as a starting place.
As shown in fig. 3, fig. 3 is a smart community intelligent charging pile service system provided by the embodiment of the present invention, including: main mobile terminal, cloud server and charging pile server
The vehicle owner mobile terminal is mainly used for sending a charging reservation order and paying the order. The system comprises a map module, a storage module, a payment module and a control module. The map module acquires geographic position information by adopting a GPS system; the storage module is used for collecting vehicle running information; the payment module is used for being connected with the payment software to realize remote payment; the control module is used for controlling the charging pile to perform activities such as charging, reservation, stopping charging and the like. Vehicle owner mobile terminals exist in a variety of forms including, but not limited to: (1) a mobile communication device: the equipment is characterized by having a mobile communication function and mainly aims at providing voice and data communication. Such terminals include: smart phones, functional phones, etc. (2) ultra mobile personal computer device: such devices are in the category of personal computers, having computing and processing functions, and generally also having mobile internet access characteristics. Such terminals include: PDA, MID, and UMPC devices, etc. (3) portable entertainment device: such devices may display and play content. The device comprises: audio, video players, palm game players, electronic books, and smart toys. (4) other electronic devices with data interaction function.
The cloud server is in wireless connection with the vehicle owner mobile terminal, and the charging pile server is in wireless connection with the cloud server, and can be connected through a wireless network (such as 2G/3G/4G and the like). The cloud server is used for processing the charging reservation order, calculating the running time of the user vehicle, generating an optimal scheme and generating navigation information.
The charging pile server is used for inquiring, storing and updating basic information of the charging pile site and comprises a management module, an operation module and comprehensive inquiry. The management module is used for carrying out centralized management on the basic information of the charging pile station; the operation module is used for charging and managing the user; the comprehensive query is used for comprehensively analyzing and querying the managed and operated data.
The embodiment of the invention provides a non-volatile computer readable storage medium, on which a computer program is stored, which when called performs the intelligent community intelligent charging pile service method as described above. The storage medium may be a magnetic disk, an optical disk, a Read-0nly memory (rom), a random access memory (RandomAccessMemory, RAM), or the like.
Those of ordinary skill in the art will appreciate that: the discussion of any of the embodiments above is merely exemplary and is not intended to suggest that the scope of the disclosure, including the claims, is limited to these examples; the technical features of the above embodiments or in the different embodiments may also be combined within the idea of the invention, the steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.
The embodiments of the invention are intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Therefore, any omission, modification, equivalent replacement, improvement, etc. of the present invention should be included in the scope of the present invention.
Claims (10)
1. An intelligent charging pile service method for an intelligent community is characterized by comprising the following steps:
acquiring the residual electric quantity of a user vehicle and the running data of the last month;
estimating the actual remaining mileage of the user vehicle according to the remaining electric quantity and the driving data of the user vehicle;
receiving a charging reservation order sent by a user, wherein the charging reservation order comprises a user geographic position, a reserved charging pile brand and a reserved charging time point;
through built-in screening logic, intelligent generation of a recommendation scheme is performed based on the charging reservation order;
and generating a charging order and navigation information according to the recommended scheme selected by the user, and feeding back the charging order and the navigation information to the user.
2. The intelligent charging pile service method according to claim 1, wherein the estimating the actual remaining mileage of the user vehicle according to the remaining power and the driving data of the user vehicle comprises the steps of:
acquiring driving data of a user vehicle for a month from a vehicle machine system, wherein the driving data comprises a date, a driving mileage and an electric quantity used;
taking the electric quantity as an independent variable and the driving mileage as a dependent variable to form a scatter diagram;
performing linear fitting on the scatter diagram to obtain an electric quantity-mileage linear equation;
substituting the residual electric quantity of the user vehicle into a related linear equation, and calculating to obtain the actual residual mileage of the user vehicle.
3. The intelligent charging pile service method of claim 1, wherein the intelligent generation recommendation scheme based on the charging reservation order by the built-in screening logic comprises the following steps:
step one: screening all charging pile sites with the distance not exceeding a preset range threshold value from the geographic position of the user based on the geographic position of the user, marking the charging pile sites as distance primary screening sites, and forming a primary screening charging pile site set U by all the distance primary screening sites, wherein U= { U 1 、u 2 、…、u n }，u i (i=1, 2, …, n) is the i-th distance prescreening station;
step two: screening out charging stake sites including at least one reservation charging stake brand from the primary screening sites based on reservation charging stake brands, marking the charging stake sites as brand screening sites, and forming a brand screening site set U by all brand screening sites p ，U p ={u p1 、u p2 、...、u pl }，u px (x=1, 2, a l) is the x brand screening site;
step three: based on historical operation data of the charging pile station, a charging pile idle number-moment linear regression model is established, and U is predicted at a reservation time point based on the charging pile idle number-moment linear regression model P The number of idle charging piles in the charging pile station is obtained, and the predicted number of idle charging piles is obtained; screening out charging pile sites with non-zero number of charging piles in brand screening sites, marking the charging pile sites as time screening sites, and forming a time screening site set U by all time screening sites ps ，U ps ={u ps1 、u ps2 、...、u psm }，u psy (y=1, 2,..m) is the y-th time screening site;
step four: based on the distance between the charging pile site and the user position, the method comprises the following steps of ps And sequencing all the charging pile sites from near to far, and recommending the charging pile sites to the vehicle owner mobile terminal by the cloud server according to the sequencing result.
4. The intelligent charging pile service method for intelligent communities according to claim 3, wherein the intelligent charging pile service method for the intelligent communities is characterized in that the intelligent charging pile service method for the intelligent communities is realized by the aid of a set U ps All charging pile stations are ordered from near to far, and the method comprises the following steps:
generating three range areas by taking the user position as the center according to a first preset distance, a second preset distance and a third preset distance, marking the range area with the distance from the user position smaller than the first preset distance as a first range area, marking the range area with the distance from the user position larger than the first preset distance smaller than the second preset distance as a second range area, and marking the range area with the distance from the user position larger than the second preset distance smaller than the third preset distance as a third range area;
adding special marks to the time screening sites when the user uses the overcharge pile sites to form special mark time screening sites;
all time screening sites falling into a first range zone are formed into a first range site set U ps 1 All time screening sites falling into a second range zone are formed into a second range site set U ps 2 All time screening sites falling into a third range zone are formed into a third range site set U ps 3 ；
Judging a first range site set U ps 1 Whether or not there is an element;
if the first range site is set U ps 1 If there is an element, judging a first range site set U ps 1 Screening whether the element has special mark time to screen sites, if so, collecting a first range site set U ps 1 The special mark time screening site in the list is recommended to the user, if not, a first range site set U is screened out ps 1 The time screening site with the maximum predicted number of idle charging piles in the elements is recommended to a user;
if the first range site is set U ps 1 Judging the second range site set U if no element exists ps 2 Whether or not there is an element;
if the second range site is set U ps 2 If there is an element, judging a second range site set U ps 2 Screening whether the element has special mark time to screen sites, if so, collecting the sites in the second range U ps 2 The special mark time screening site in the list is recommended to the user, if not, a second range site set U is screened out ps 2 The time screening site with the maximum predicted number of idle charging piles in the elements is recommended to a user;
if the second range site is set U ps 2 Judging the third range site set U if no element exists ps 3 Whether or not there is an element;
if the third range site is set U ps 3 If there is an element, judging a third range site set U ps 3 Screening sites if the elements have special marked time, if so, collecting the sites in a third range U ps 3 The special mark time screening site in the list is recommended to the user, if not, a third range site set U is screened out ps 3 The time screening site with the maximum predicted number of idle charging piles in the elements is recommended to a user;
if the third range site is set U ps 3 And outputting a nearby non-recommended site signal to the user terminal if no element exists.
5. The intelligent charging pile service method according to claim 3, wherein the preset range threshold is 5 km, the first preset distance is 1 km, the second preset distance is 3 km, and the third preset distance is 5 km.
6. The intelligent charging pile service method for the intelligent community according to claim 3, wherein the building of the charging pile idle number-moment linear regression model based on the historical operation data of the charging pile site comprises the following steps:
acquiring the idle number of the charging piles corresponding to each whole point in 30 days;
taking the idle number of the charging piles as a dependent variable, taking time as the independent variable, and making a scatter diagram;
and performing linear fitting on the scatter diagram to obtain a linear regression model of the idle number-moment of the charging pile.
7. An intelligent charging pile service system for implementing the intelligent charging pile service method for intelligent communities according to any one of claims 1 to 6, comprising:
the vehicle owner mobile terminal is used for sending a charging reservation order and paying the order;
the cloud server is in wireless connection with the vehicle owner mobile terminal and is used for processing the charging reservation order, calculating the running time of the user vehicle, generating an optimal scheme and generating navigation information;
and the charging pile server is in wireless connection with the cloud server and is used for inquiring, storing and updating the basic information of the charging pile site.
8. The intelligent charging pile service system according to claim 7, wherein the vehicle owner mobile terminal comprises:
the map module is used for acquiring geographic position information by adopting a GPS system;
the storage module is in wireless connection with the vehicle-mounted system and acquires storage information in the vehicle-mounted system;
the payment module is used for being connected with the payment software to realize remote payment;
and the control module is used for controlling the charging pile to conduct activities such as reservation, charging, stopping charging and the like.
9. The intelligent charging pile service system according to claim 7, wherein the charging pile server comprises:
the management module is used for carrying out centralized management on the basic information of the charging pile station;
the operation module is used for charging and managing the user;
and the comprehensive query is used for comprehensively analyzing and querying the data of the management module and the operation module.
10. A computer readable storage medium having a computer readable computer program stored thereon, wherein the computer readable program when invoked performs the intelligent community charging pile service method of any one of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311177100.7A CN116910494B (en) | 2023-09-13 | 2023-09-13 | Intelligent charging pile service method, system and storage medium for intelligent communities |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311177100.7A CN116910494B (en) | 2023-09-13 | 2023-09-13 | Intelligent charging pile service method, system and storage medium for intelligent communities |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116910494A true CN116910494A (en) | 2023-10-20 |
| CN116910494B CN116910494B (en) | 2023-12-08 |
Family
ID=88358819
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311177100.7A Active CN116910494B (en) | 2023-09-13 | 2023-09-13 | Intelligent charging pile service method, system and storage medium for intelligent communities |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116910494B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117556971A (en) * | 2023-11-02 | 2024-02-13 | 江苏智融能源科技有限公司 | Ordered charging recommendation system and method based on artificial intelligence |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104864883A (en) * | 2015-05-22 | 2015-08-26 | 清华大学 | Cloud platform based electric automobile path planning method |
| CN105205919A (en) * | 2015-08-25 | 2015-12-30 | 国网北京市电力公司 | Charging settlement system for electric vehicle |
| CN105539185A (en) * | 2015-12-29 | 2016-05-04 | 戴姆勒股份公司 | Charging route planning and charging reserving method and system of electric automobile |
| CN105825282A (en) * | 2016-03-16 | 2016-08-03 | 上海翼锐汽车科技有限公司 | Cloud platform of charging piles |
| CN105844391A (en) * | 2016-03-21 | 2016-08-10 | 上海乐充新能源设备有限公司 | Intelligent charging-switching control device management method, system and electronic device |
| CN106515493A (en) * | 2016-12-01 | 2017-03-22 | 杭州快电新能源科技有限公司 | Electric automobile charging pile and system based on wireless network communication |
| CN107563531A (en) * | 2017-08-30 | 2018-01-09 | 安徽千里眼信息科技有限公司 | Charging electric vehicle long-distance management system based on internet |
| CN108327567A (en) * | 2018-03-28 | 2018-07-27 | 徐州市恒源电器有限公司 | A kind of intelligent electric vapour charging pile client connection system |
| CN108734485A (en) * | 2017-04-13 | 2018-11-02 | 宁波轩悦行电动汽车服务有限公司 | The terminal auxiliary information method for pushing of hiring a car estimated based on remaining capacity operating range |
| CN109159709A (en) * | 2018-11-13 | 2019-01-08 | 广州小鹏汽车科技有限公司 | The automatic localization charging method and system of electric car |
| CN110626209A (en) * | 2019-09-25 | 2019-12-31 | 苏州亿为新能源科技有限公司 | Charging method and system of charging pile |
| CN110782065A (en) * | 2019-09-09 | 2020-02-11 | 腾讯科技（深圳）有限公司 | Electric vehicle charging pile recommendation method, server, terminal and system |
| CN111415021A (en) * | 2020-04-02 | 2020-07-14 | 福建工程学院 | Charging pile optimal position recommendation management system and method based on intelligent vehicle-mounted terminal |
| CN111882096A (en) * | 2020-08-03 | 2020-11-03 | 上海博泰悦臻电子设备制造有限公司 | Method for information processing, electronic device, and storage medium |
| CN113379083A (en) * | 2021-05-26 | 2021-09-10 | 安徽工程大学 | Charging pile sharing system and method based on cloud platform |
| CN113947231A (en) * | 2020-07-17 | 2022-01-18 | 北京满电出行科技有限公司 | Charging station vacancy degree prediction method and device |
| CN116295506A (en) * | 2023-04-10 | 2023-06-23 | 章鱼博士智能技术(上海)有限公司 | Method, device, equipment and medium for predicting vehicle remaining mileage |
-
2023
- 2023-09-13 CN CN202311177100.7A patent/CN116910494B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104864883A (en) * | 2015-05-22 | 2015-08-26 | 清华大学 | Cloud platform based electric automobile path planning method |
| CN105205919A (en) * | 2015-08-25 | 2015-12-30 | 国网北京市电力公司 | Charging settlement system for electric vehicle |
| CN105539185A (en) * | 2015-12-29 | 2016-05-04 | 戴姆勒股份公司 | Charging route planning and charging reserving method and system of electric automobile |
| CN105825282A (en) * | 2016-03-16 | 2016-08-03 | 上海翼锐汽车科技有限公司 | Cloud platform of charging piles |
| CN105844391A (en) * | 2016-03-21 | 2016-08-10 | 上海乐充新能源设备有限公司 | Intelligent charging-switching control device management method, system and electronic device |
| CN106515493A (en) * | 2016-12-01 | 2017-03-22 | 杭州快电新能源科技有限公司 | Electric automobile charging pile and system based on wireless network communication |
| CN108734485A (en) * | 2017-04-13 | 2018-11-02 | 宁波轩悦行电动汽车服务有限公司 | The terminal auxiliary information method for pushing of hiring a car estimated based on remaining capacity operating range |
| CN107563531A (en) * | 2017-08-30 | 2018-01-09 | 安徽千里眼信息科技有限公司 | Charging electric vehicle long-distance management system based on internet |
| CN108327567A (en) * | 2018-03-28 | 2018-07-27 | 徐州市恒源电器有限公司 | A kind of intelligent electric vapour charging pile client connection system |
| CN109159709A (en) * | 2018-11-13 | 2019-01-08 | 广州小鹏汽车科技有限公司 | The automatic localization charging method and system of electric car |
| CN110782065A (en) * | 2019-09-09 | 2020-02-11 | 腾讯科技（深圳）有限公司 | Electric vehicle charging pile recommendation method, server, terminal and system |
| CN110626209A (en) * | 2019-09-25 | 2019-12-31 | 苏州亿为新能源科技有限公司 | Charging method and system of charging pile |
| CN111415021A (en) * | 2020-04-02 | 2020-07-14 | 福建工程学院 | Charging pile optimal position recommendation management system and method based on intelligent vehicle-mounted terminal |
| CN113947231A (en) * | 2020-07-17 | 2022-01-18 | 北京满电出行科技有限公司 | Charging station vacancy degree prediction method and device |
| CN111882096A (en) * | 2020-08-03 | 2020-11-03 | 上海博泰悦臻电子设备制造有限公司 | Method for information processing, electronic device, and storage medium |
| CN113379083A (en) * | 2021-05-26 | 2021-09-10 | 安徽工程大学 | Charging pile sharing system and method based on cloud platform |
| CN116295506A (en) * | 2023-04-10 | 2023-06-23 | 章鱼博士智能技术(上海)有限公司 | Method, device, equipment and medium for predicting vehicle remaining mileage |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117556971A (en) * | 2023-11-02 | 2024-02-13 | 江苏智融能源科技有限公司 | Ordered charging recommendation system and method based on artificial intelligence |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116910494B (en) | 2023-12-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104102638B (en) | Method for pushing, system and device based on positional information | |
| CN116910494B (en) | Intelligent charging pile service method, system and storage medium for intelligent communities | |
| CN109556612B (en) | Navigation information processing method, device, server, terminal and storage medium | |
| US20160109243A1 (en) | Suggestive mapping using relevance based drive information | |
| CN111127130B (en) | Energy site recommendation method based on user preference, storage medium and electronic equipment | |
| Austin et al. | Taxicabs as public transportation in Boston, Massachusetts | |
| CN105354214B (en) | A kind of generation method and device of memo information | |
| JP2019148928A (en) | Rental cycle management system and program | |
| CN102819550A (en) | Systems and methods for determining recommended media content for exchange between vehicles | |
| CN110750713A (en) | Vehicle-mounted service content recommendation method and device, vehicle and storage medium | |
| CN102607580A (en) | Methods and apparatus for navigation including vehicle recharging | |
| CN111428137B (en) | Recommendation method and recommendation device for electric vehicle charging facilities | |
| CN101751775A (en) | Hitchhiking request processing system and corresponding control method | |
| CN110782066B (en) | Driving route determination method, device and medium | |
| CN111739329B (en) | Travel route generation method, travel route generation device, storage medium, and server | |
| CN110126843A (en) | Driving service recommendation method, device, equipment and medium | |
| CN114298770A (en) | Charging station recommendation method, device, storage medium, and program product | |
| US20170213261A1 (en) | Method for detecting riders and managing and optimizing their shared transport | |
| CN107305666A (en) | Car operation route business analysis method and system | |
| CN111627239B (en) | Display method, device and equipment of public transport information and storage medium | |
| CN110826744A (en) | Power battery replacement reservation method, computer equipment and readable storage medium | |
| CN114676911A (en) | Method and device for determining driving route of transport vehicle | |
| CN111325436A (en) | Network appointment vehicle co-operation passenger matching method and system, storage medium and server | |
| CN107820108A (en) | Video recommendation method and system | |
| CN112129305B (en) | Vehicle navigation method, system, device and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right | ||
| PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: A smart community intelligent charging pile service method, system, and storage medium Granted publication date: 20231208 Pledgee: Zijin Branch of Nanjing Bank Co.,Ltd. Pledgor: Nanjing anchong Intelligent Technology Co.,Ltd. Registration number: Y2024980005053 |