CN107169605A - City electric car charging station site selecting method based on vehicle location information - Google Patents
City electric car charging station site selecting method based on vehicle location information Download PDFInfo
- Publication number
- CN107169605A CN107169605A CN201710351215.1A CN201710351215A CN107169605A CN 107169605 A CN107169605 A CN 107169605A CN 201710351215 A CN201710351215 A CN 201710351215A CN 107169605 A CN107169605 A CN 107169605A
- Authority
- CN
- China
- Prior art keywords
- location information
- msub
- charging station
- vehicle location
- mrow
- 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 22
- 238000005457 optimization Methods 0.000 claims abstract description 9
- 230000002068 genetic effect Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000013480 data collection Methods 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 230000000717 retained effect Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/043—Optimisation of two dimensional placement, e.g. cutting of clothes or wood
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Water Supply & Treatment (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Navigation (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention discloses a kind of city electric car charging station site selecting method based on vehicle location information, comprise the following steps：(A) collection vehicle location information；(B) charging station quantity M is determined；(C) vehicle location information obtained according to step (A), obtains rectangle running region Region (Lat of the vehicle in cityr,Lonr), Region is divided into Q sub-rectangular areas；(D) according to vehicle location information, calculating vehicle passes through each sub-rectangular areas regqFrequency countq；(E) optimization aim is to the maximum with the frequency sum of charging station setting area and builds restricted problem, solve the restricted problem, obtain characterizing the value whether each sub-rectangular areas sets charging station, and then determine the address of each charging station.The region most often passed through when this method by charging station by being arranged on electric automobile during traveling and stop, detouring when reducing its charging, realizes the more preferably location of charging station.
Description
Technical field
The invention belongs to Urban Traffic Planning and optimization field, and in particular to the electronic vapour in city based on vehicle location information
Car charging station site selecting method.
Background technology
Electric automobile refers to using vehicle power as power, is travelled with power wheel, meets road traffic, security legislation each
The vehicle that item is required.Because the relatively conventional automobile of effect on environment is smaller, the prospect of electric automobile is had an optimistic view of extensively, but current electricity
Electrical automobile is still within the starting stage in the development of China, and related technical standard is still immature.For at this stage, electronic vapour
Car course continuation mileage section, the shortcoming of charging interval length can not still overcome in a short time, and this is required must be appropriate in rational position
Arrangement charging station, to support the operation of electric automobile.
From the point of view of the practical development of China's electric automobile, since 2013, the recoverable amount of electric automobile increases notable, special
It is not in the coastal region in east China.On the one hand, it is the promotion of policies and regulations, is played an important role to promoting electric automobile, city
New-energy automobile recoverable amount in city has also obtained very big raising.On the other hand, it is a series of that there is China's independent intellectual production
The beautiful electric automobile of power, matter high price is also to promote one of major reason of electric automobile rapid growth.Joint conference is multiplied according to China's evidence
The data display of statistics, the pure electric vehicle of the 1-12 months in 2016 sells 240,000, increases by 116% on a year-on-year basis, accounts for new-energy automobile total
The 75% of sales volume.Wherein, BYD, lucky, Beijing Automobile Workshop are sure to occupy first three of new sales volume list.
Although the growth of electric automobile is very fast, however, during actual use, electrically-charging equipment (charging station, fills
Electric stake etc.) quantity and the layout of facility greatly limit the utilization rate of electric automobile, the owner of many electric automobiles makes
Before electric automobile, the facility situation of electrically-charging equipment can be considered.If charging and inconvenient, it often abandons using electronic vapour
Car transfers to go on a journey using other modes.
The content of the invention
Goal of the invention：To solve the above problems, the invention discloses a kind of electronic vapour in the city based on vehicle location information
Car charging station site selecting method, the region most often passed through when this method by charging station by being arranged on electric automobile during traveling and stop,
Detouring when reducing its charging, realizes the more preferably location of charging station.
Technical scheme：The present invention is adopted the following technical scheme that：
A kind of city electric car charging station site selecting method based on vehicle location information, comprises the following steps：
(A) collection vehicle location information；The location information includes the numbering P of vehiclei, vehicle location position longitude and latitude sit
Mark (Lati,Loni), the locating speed V of vehiclei；Wherein subscript i is the sequence number of vehicle location information, and 1≤i≤N, N is fixed for vehicle
The quantity of position information；
(B) charging station quantity M is determined；
(C) vehicle location information obtained according to step (A), obtains rectangle running region Region of the vehicle in city
(Latr,Lonr), wherein Rectangle is travelled into area
Domain Region is divided into Q sub-rectangular areas；
(D) according to vehicle location information, calculating vehicle passes through each sub-rectangular areas regqFrequency countq, 1≤q≤
Q；
(E) optimization aim is to the maximum with the frequency sum of charging station setting area and builds restricted problem, the optimization aim
Function is：
Wherein γqFor characterizing whether sub-rectangular areas q is provided with charging station, γq=1 expression sub-rectangular areas q is provided with
Charging station；dpqFor sub-rectangular areas q geometric centroid to the manhatton distance of sub-rectangular areas p geometric centroid, dminFor charging
Minimum allowable range between standing；
The restricted problem is solved, γ is obtainedqValue, and then determine the address of each charging station.
Preferably, charging station quantity M is determined by following formula：
Wherein PcFor the recoverable amount scale of the electric automobile in city, CcFor average daily charging times, the F of electric automobilecTo be electronic
The peak hour factor of automobile charging, the i.e. charge requirement of peak hour electric automobile accounts for the ratio of full-time total charge requirement, Ca
The maximum charge demand being met by for single charging station in unit hour.
Preferably, the equal decile of gridding is carried out in longitude and latitude direction to rectangle running region Region, by Region
It is divided into Q sub-rectangular areas.
As another preferred, gridding division, step are carried out with h × h unit grid to rectangle running region Region
For：
(C1) rectangle running region Region is extended, four summits of rectangle running region Region ' after extension
Respectively (minLati,minLoni)、(minLati,minLoni+Kh)、(minLati+Jh,minLoni)、(minLati+Jh,
minLoni+Kh)；
WhereinSubregion sum Q=JK；For to
Upper rounding operation；
(C2) to the rectangle running region Region ' carry out griddings after extension, it is divided into Q sub-rectangular areas, q-th of square
Shape subregion regqFour summits be respectively：
Wherein 1≤q≤Q.
Specifically, calculating vehicle passes through each sub-rectangular areas regqFrequency countqComprise the following steps：
(D1) frequency for initializing each sub-rectangular areas is 0, i.e. countq=0；
(D2) vehicle location information that step (A) is gathered is judged successively, when wherein i-th vehicle location information is full
During any one condition in following two conditions of foot, by the frequency count of q-th of sub-rectangular areasqIncrease by 1：
If position location (the Lat of condition one, i-th vehicle location informationi,Loni) in q-th of sub-rectangular areas,
And the locating speed V of vehiclei=0；
If position location (the Lat of condition two, i-th vehicle location informationi,Loni) in q-th of sub-rectangular areas,
And the locating speed V of vehiclei>0, and the numbering P of vehicleiCondition two is met into the i-th -1 article vehicle location information with the 1st article
The numbering P of vehiclejDiffer, 1≤j<i.
Preferably, application genetic algorithm for solving restricted problem in step (E), obtains γqValue, and then determine each charging station
Address.
Beneficial effect：Compared with prior art, the invention has the advantages that：(1) it is disclosed by the invention fixed based on vehicle
The city electric car charging station site selecting method of position information, it is excessively random to have abandoned conventional city charging station addressing, and charging station
It is located at the problem of city is from far-off regions more the position, is obtained by the inventive method and be respectively positioned on vehicle with the charging station position determined
Most often travel in the region with stopping, one side transport need is very big with charge requirement, on the other hand also reduces electric automobile
During charging around row distance；(2) charging station site selecting method disclosed by the invention is based primarily upon vehicle location information data.It is following with
The development and change in city, after the distribution of trip and the positional information of vehicle change, existing charging can retained
On the basis of facility, the new vehicle driving of region of variation and charge requirement are individually considered, and the addressing of charging station is synchronized
Update.
Brief description of the drawings
Fig. 1 is the flow chart of city electric car charging station site selecting method disclosed by the invention.
Embodiment
With reference to the accompanying drawings and detailed description, the present invention is furture elucidated.
As shown in figure 1, the city electric car charging station site selecting method of the invention based on vehicle location information, including it is following
Step：
(A) collection vehicle location information；
Step (A) collection vehicle location information, contains step A1), step A2) two sub-steps：
A1) determine that location information can be gathered in city, and the quantity T of the vehicle equipped with Vehicle Positioning Equipment, and it is right
These vehicles carry out exclusive number so that the numbering of any two cars is differed.The numbering of vehicle is to T's since 1
Positive integer.
A2) in units of bar, the vehicle location information of T car is gathered, wherein, i-th vehicle location information is included：Vehicle
Numbering Pi, vehicle position location latitude and longitude coordinates (Lati,Loni), the locating speed V of vehiclei.Wherein, subscript i is vehicle
The sequence number of location information, i is the total number that the integer and i≤N, N more than 0 are the vehicle location information collected, Pi∈[1,
T] and PiFor integer, LatiAnd LoniLatitude, the longitude of the position location of respectively i-th vehicle location information；
In step A, vehicle location information passes through location equipment automatic data collection.Location equipment is including but not limited to vehicle-mounted
GPS, external GPS, mobile phone, flat board, computer of built-in location equipment etc..Due to the position of location equipment meeting automatic data collection vehicle
With the information such as speed, while time when recording locating information acquisition, thus vehicle location information in step A is to be easy to
Collect.
For the ease of the management of data, collect after vehicle location information, be inputted in database, that is, build vehicle and determine
Position information database；
The N bars vehicle location information collected in step A is stored in vehicle location information database.Vehicle location is believed
The structure for ceasing database is as follows：
(B) charging station quantity M is determined；
According to the charge requirement in city, charging station quantity M is determined.Charging station quantity M can be determined by following formula：
Wherein, PcFor the recoverable amount scale of the electric automobile in city, CcFor average daily charging times, the F of electric automobilecFor electricity
The peak hour factor of electrical automobile charging, is that the charge requirement of peak hour electric automobile accounts for the ratio of full-time total charge requirement,
CaThe maximum charge demand being met by for single charging station in unit hour.
(C) vehicle location information obtained according to step (A), obtains rectangle running region Region of the vehicle in city
(Latr,Lonr), wherein Rectangle is travelled into area
Domain Region is divided into Q sub-rectangular areas；
Dividing for rectangle running region Region can be carried out by the way of equal decile in longitude and latitude direction
The equal decile of gridding, Q sub-rectangular areas is divided into by Region.
Can also be using the dividing mode for fixing unit grids size, to rectangle running region Region with h × h unit net
Lattice carry out gridding division, comprise the following steps：
(C1) rectangle running region Region is extended, four summits of rectangle running region Region ' after extension
Respectively (minLati,minLoni)、(minLati,minLoni+Kh)、(minLati+Jh,minLoni)、(minLati+Jh,
minLoni+Kh)；
WhereinSubregion sum Q=JK；For to
Upper rounding operation；
(C2) to the rectangle running region Region ' carry out griddings after extension, it is divided into Q sub-rectangular areas, q-th of square
Shape subregion regqFour summits be respectively：
Wherein 1≤q≤Q.
The size of h values has influence on the precision and amount of calculation of method, the present invention preferably h=0.005, according to earth radius
Value, can calculate the region that the unit grid that longitude and latitude is 0.005 × 0.005 is roughly equivalent to 500m × 500m, Ke Yiman
The required precision on full border, and amount of calculation is smaller.
(D) according to vehicle location information, calculating vehicle passes through each sub-rectangular areas regqFrequency countq, 1≤q≤
Q；Specifically include：
(D1) frequency for initializing each sub-rectangular areas is 0, i.e. countq=0；
(D2) vehicle location information that step (A) is gathered is judged successively, when wherein i-th vehicle location information is full
During any one condition in following two conditions of foot, by the frequency count of q-th of sub-rectangular areasqIncrease by 1：
If position location (the Lat of condition one, i-th vehicle location informationi,Loni) in q-th of sub-rectangular areas,
And the locating speed V of vehiclei=0；
If position location (the Lat of condition two, i-th vehicle location informationi,Loni) in q-th of sub-rectangular areas,
And the locating speed V of vehiclei>0, and the numbering P of vehicleiCondition two is met into the i-th -1 article vehicle location information with the 1st article
The numbering P of vehiclejDiffer, 1≤j<i.
(E) optimization aim is to the maximum with the frequency sum of charging station setting area and builds restricted problem, the optimization aim
Function is：
Wherein γqFor characterizing whether sub-rectangular areas q is provided with charging station, γq=1 expression sub-rectangular areas q is provided with
Charging station；dpqFor sub-rectangular areas q geometric centroid to the manhatton distance of sub-rectangular areas p geometric centroid, dminFor charging
Minimum allowable range between standing；
The restricted problem is solved, γ is obtainedqValue, and then determine the address of each charging station.
In the present embodiment, a main region in China city is chosen, method disclosed by the invention is verified.Including as follows
Step：
(A) collection vehicle location information；
The location information of 9126 vehicles, T=9126 can be gathered in the present embodiment；Vehicle location information is collected altogether
N=18668037 bars.
Collect 18668037 vehicle location informations are put into vehicle location information database.Vehicle location is believed
Cease database as follows：
(B) charging station quantity M is determined；
According to the charge requirement in city, charging station quantity is determinedBy calculating M=2.
(C) vehicle rectangle running region Region is divided；
The present embodiment is using the dividing mode for fixing unit grids size, to rectangle running region Region with h × h unit
Grid carries out gridding division, h=0.005.It is computed,
Rectangle running region Region is extended, four summits of rectangle running region Region ' after extension be respectively (31.23,
118.35), (31.23,119.24), (32.63,118.35), (32.63,119.24)；Subregion sum Q=49840；
(D) according to vehicle location information, calculating vehicle passes through each sub-rectangular areas regqFrequency countq, 1≤q≤
Q；
(E) optimization aim is to the maximum with the frequency sum of charging station setting area and builds restricted problem；The present embodiment application
Genetic algorithm for solving restricted problem, obtains characterizing the value whether each sub-rectangular areas sets charging station, and then determine each charging
The address stood.
It is final to determine that two electronic charging stations are located at sub-rectangular areas q=4589 and sub-rectangular areas q=by solving
In 12358.
Claims (7)
1. a kind of city electric car charging station site selecting method based on vehicle location information, it is characterised in that including following step
Suddenly：
(A) collection vehicle location information；The location information includes the numbering P of vehiclei, vehicle location position latitude and longitude coordinates
(Lati,Loni), the locating speed V of vehiclei；Wherein subscript i is the sequence number of vehicle location information, and 1≤i≤N, N is collected
The quantity of vehicle location information；
(B) charging station quantity M is determined；
(C) vehicle location information obtained according to step (A), obtains rectangle running region Region of the vehicle in city
(Latr,Lonr), wherein
Rectangle running region Region is divided into Q sub-rectangular areas；
(D) according to vehicle location information, calculating vehicle passes through each sub-rectangular areas regqFrequency countq, 1≤q≤Q；
(E) optimization aim is to the maximum with the frequency sum of charging station setting area and builds restricted problem, the optimization object function
For：
<mrow>
<mi>M</mi>
<mi>a</mi>
<mi>x</mi>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>q</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>Q</mi>
</munderover>
<msub>
<mi>&gamma;</mi>
<mi>q</mi>
</msub>
<msub>
<mi>count</mi>
<mi>q</mi>
</msub>
</mrow>
<mrow>
<mi>s</mi>
<mo>.</mo>
<mi>t</mi>
<mo>.</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<msub>
<mi>&gamma;</mi>
<mi>q</mi>
</msub>
<mo>,</mo>
<msub>
<mi>&gamma;</mi>
<mi>p</mi>
</msub>
<mo>&Element;</mo>
<mo>{</mo>
<mn>0</mn>
<mo>,</mo>
<mn>1</mn>
<mo>}</mo>
</mtd>
</mtr>
<mtr>
<mtd>
<mstyle>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>q</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>Q</mi>
</munderover>
</mstyle>
<msub>
<mi>&gamma;</mi>
<mi>q</mi>
</msub>
<mo>=</mo>
<mi>M</mi>
</mtd>
</mtr>
<mtr>
<mtd>
<mi>p</mi>
<mo>,</mo>
<mi>q</mi>
<mo>&Element;</mo>
<mo>{</mo>
<mn>1</mn>
<mo>,</mo>
<mn>2</mn>
<mo>,</mo>
<mo>...</mo>
<mo>,</mo>
<mi>Q</mi>
<mo>}</mo>
</mtd>
</mtr>
<mtr>
<mtd>
<msub>
<mi>d</mi>
<mrow>
<mi>p</mi>
<mi>q</mi>
</mrow>
</msub>
<mo>&GreaterEqual;</mo>
<msub>
<mi>&lambda;</mi>
<mrow>
<mi>p</mi>
<mi>q</mi>
</mrow>
</msub>
<msub>
<mi>d</mi>
<mi>min</mi>
</msub>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msub>
<mi>&lambda;</mi>
<mrow>
<mi>p</mi>
<mi>q</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>&gamma;</mi>
<mi>p</mi>
</msub>
<msub>
<mi>&gamma;</mi>
<mi>q</mi>
</msub>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
</mrow>
Wherein γqFor characterizing whether sub-rectangular areas q is provided with charging station, γq=1 expression sub-rectangular areas q is provided with charging
Stand；dpqFor sub-rectangular areas q geometric centroid to the manhatton distance of sub-rectangular areas p geometric centroid, dminFor charging station it
Between minimum allowable range；
The restricted problem is solved, γ is obtainedqValue, and then determine the address of each charging station.
2. the city electric car charging station site selecting method according to claim 1 based on vehicle location information, its feature
It is, charging station quantity M is determined by following formula：
<mrow>
<mi>M</mi>
<mo>=</mo>
<mfrac>
<mrow>
<msub>
<mi>P</mi>
<mi>c</mi>
</msub>
<msub>
<mi>C</mi>
<mi>c</mi>
</msub>
<msub>
<mi>F</mi>
<mi>c</mi>
</msub>
</mrow>
<msub>
<mi>C</mi>
<mi>a</mi>
</msub>
</mfrac>
</mrow>
Wherein PcFor the recoverable amount scale of the electric automobile in city, CcFor average daily charging times, the F of electric automobilecFor electric automobile
The peak hour factor of charging, CaThe maximum charge demand being met by for single charging station in unit hour.
3. the city electric car charging station site selecting method according to claim 1 based on vehicle location information, its feature
It is, the equal decile of gridding is carried out in longitude and latitude direction to rectangle running region Region, Region is divided into Q square
Shape subregion.
4. the city electric car charging station site selecting method according to claim 1 based on vehicle location information, its feature
It is, gridding division is carried out with h × h unit grid to rectangle running region Region, step is：
(C1) rectangle running region Region is extended, four summit difference of rectangle running region Region ' after extension
For (minLati,minLoni)、(minLati,minLoni+Kh)、(minLati+Jh,minLoni)、(minLati+Jh,
minLoni+Kh)；
WhereinSubregion sum Q=JK；To take upwards
Whole computing；
(C2) to the rectangle running region Region ' carry out griddings after extension, it is divided into Q sub-rectangular areas, q-th of rectangle
Region regqFour summits be respectively：
Wherein 1≤q≤Q.
5. the city electric car charging station site selecting method according to claim 1 based on vehicle location information, its feature
It is, calculating vehicle passes through each sub-rectangular areas regqFrequency countqComprise the following steps：
(D1) frequency for initializing each sub-rectangular areas is 0, i.e. countq=0；
(D2) vehicle location information that step (A) is gathered is judged successively, when wherein i-th vehicle location information is met such as
During any one condition in lower two conditions, by the frequency count of q-th of sub-rectangular areasqIncrease by 1：
If position location (the Lat of condition one, i-th vehicle location informationi,Loni) in q-th of sub-rectangular areas, and car
Locating speed Vi=0；
If position location (the Lat of condition two, i-th vehicle location informationi,Loni) in q-th of sub-rectangular areas, and car
Locating speed Vi>0, and the numbering P of vehicleiWith the 1st article of vehicle for meeting condition two into the i-th -1 article vehicle location information
Numbering PjDiffer, 1≤j<i.
6. the city electric car charging station site selecting method according to claim 1 based on vehicle location information, its feature
It is, application genetic algorithm for solving restricted problem, obtains γ in step (E)qValue, and then determine the address of each charging station.
7. the city electric car charging station site selecting method according to claim 1 based on vehicle location information, its feature
It is, collects after vehicle location information, by the vehicle location information input database, builds vehicle location information data
Storehouse.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710351215.1A CN107169605B (en) | 2017-05-18 | 2017-05-18 | Urban electric vehicle charging station site selection method based on vehicle positioning information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710351215.1A CN107169605B (en) | 2017-05-18 | 2017-05-18 | Urban electric vehicle charging station site selection method based on vehicle positioning information |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107169605A true CN107169605A (en) | 2017-09-15 |
| CN107169605B CN107169605B (en) | 2020-06-30 |
Family
ID=59816655
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710351215.1A Expired - Fee Related CN107169605B (en) | 2017-05-18 | 2017-05-18 | Urban electric vehicle charging station site selection method based on vehicle positioning information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107169605B (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108171386A (en) * | 2018-01-11 | 2018-06-15 | 成都雅骏新能源汽车科技股份有限公司 | A kind of charging station based on vehicle GPRS information builds optimization method |
| CN108182508A (en) * | 2017-12-07 | 2018-06-19 | 北京国网普瑞特高压输电技术有限公司 | A kind of method and system of electric automobile charging station planning |
| CN108288110A (en) * | 2018-01-18 | 2018-07-17 | 武汉理工大学 | A kind of charging pile Optimal Deployment Method based on the true running data of electric vehicle |
| CN109543888A (en) * | 2018-11-07 | 2019-03-29 | 中国联合网络通信集团有限公司 | Business hall position selecting method, device and storage medium |
| CN109858676A (en) * | 2018-12-29 | 2019-06-07 | 国网天津市电力公司电力科学研究院 | Electric car electric charging demand for services model prediction method based on clustering algorithm |
| CN109872070A (en) * | 2019-02-22 | 2019-06-11 | 中南大学 | Based on the static charging pile dispositions method divided |
| CN109902845A (en) * | 2017-12-08 | 2019-06-18 | 宝沃汽车（中国）有限公司 | Configuration method, the device and system of vehicle service point |
| CN110046753A (en) * | 2019-03-29 | 2019-07-23 | 江苏大学 | A kind of optimal Quantity of electric automobile charging station and addressing scheme planing method |
| CN110458589A (en) * | 2019-02-01 | 2019-11-15 | 吉林大学 | Trackside formula taxi bus stop addressing preferred method based on track big data |
| EP3644242A1 (en) | 2018-10-23 | 2020-04-29 | Honda Research Institute Europe GmbH | System and method for optimizing a service station layout |
| CN111860922A (en) * | 2019-04-30 | 2020-10-30 | 北京嘀嘀无限科技发展有限公司 | Service station deployment control method and device, electronic equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105447602A (en) * | 2016-01-01 | 2016-03-30 | 三峡大学 | Electric automobile power charging and converting station optimization arrangement system |
| KR20160068611A (en) * | 2014-12-05 | 2016-06-15 | 현대 아메리카 테크니컬 센타, 아이엔씨 | Method and system for aligning a vehicle with a wireless charging assembly |
| CN106355294A (en) * | 2016-09-26 | 2017-01-25 | 浙江工业大学 | Site selection and capacity determination method of electric vehicle (EV) charging station for large-scale complicated power distribution network |
| CN106845727A (en) * | 2017-02-15 | 2017-06-13 | 天津大学 | Consider the highway quick charge station heuristic programming algorithm of distribution trend constraint |
| CN106951978A (en) * | 2017-02-20 | 2017-07-14 | 国网天津市电力公司 | A kind of city concentrated charging station planing method based on improvement K means algorithms |
-
2017
- 2017-05-18 CN CN201710351215.1A patent/CN107169605B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20160068611A (en) * | 2014-12-05 | 2016-06-15 | 현대 아메리카 테크니컬 센타, 아이엔씨 | Method and system for aligning a vehicle with a wireless charging assembly |
| CN105447602A (en) * | 2016-01-01 | 2016-03-30 | 三峡大学 | Electric automobile power charging and converting station optimization arrangement system |
| CN106355294A (en) * | 2016-09-26 | 2017-01-25 | 浙江工业大学 | Site selection and capacity determination method of electric vehicle (EV) charging station for large-scale complicated power distribution network |
| CN106845727A (en) * | 2017-02-15 | 2017-06-13 | 天津大学 | Consider the highway quick charge station heuristic programming algorithm of distribution trend constraint |
| CN106951978A (en) * | 2017-02-20 | 2017-07-14 | 国网天津市电力公司 | A kind of city concentrated charging station planing method based on improvement K means algorithms |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108182508A (en) * | 2017-12-07 | 2018-06-19 | 北京国网普瑞特高压输电技术有限公司 | A kind of method and system of electric automobile charging station planning |
| CN109902845A (en) * | 2017-12-08 | 2019-06-18 | 宝沃汽车（中国）有限公司 | Configuration method, the device and system of vehicle service point |
| CN108171386A (en) * | 2018-01-11 | 2018-06-15 | 成都雅骏新能源汽车科技股份有限公司 | A kind of charging station based on vehicle GPRS information builds optimization method |
| CN108288110A (en) * | 2018-01-18 | 2018-07-17 | 武汉理工大学 | A kind of charging pile Optimal Deployment Method based on the true running data of electric vehicle |
| CN108288110B (en) * | 2018-01-18 | 2021-11-02 | 武汉理工大学 | Charging pile optimization layout method based on real driving data of electric vehicle |
| EP3644242A1 (en) | 2018-10-23 | 2020-04-29 | Honda Research Institute Europe GmbH | System and method for optimizing a service station layout |
| CN109543888A (en) * | 2018-11-07 | 2019-03-29 | 中国联合网络通信集团有限公司 | Business hall position selecting method, device and storage medium |
| CN109858676A (en) * | 2018-12-29 | 2019-06-07 | 国网天津市电力公司电力科学研究院 | Electric car electric charging demand for services model prediction method based on clustering algorithm |
| CN110458589A (en) * | 2019-02-01 | 2019-11-15 | 吉林大学 | Trackside formula taxi bus stop addressing preferred method based on track big data |
| CN109872070A (en) * | 2019-02-22 | 2019-06-11 | 中南大学 | Based on the static charging pile dispositions method divided |
| CN110046753A (en) * | 2019-03-29 | 2019-07-23 | 江苏大学 | A kind of optimal Quantity of electric automobile charging station and addressing scheme planing method |
| CN110046753B (en) * | 2019-03-29 | 2020-08-28 | 江苏大学 | Planning method for optimal construction quantity and site selection scheme of electric vehicle charging station |
| WO2020199558A1 (en) * | 2019-03-29 | 2020-10-08 | 江苏大学 | Method for planning optimal construction quantity and site selection scheme for electric vehicle charging stations |
| CN111860922A (en) * | 2019-04-30 | 2020-10-30 | 北京嘀嘀无限科技发展有限公司 | Service station deployment control method and device, electronic equipment and storage medium |
| CN111860922B (en) * | 2019-04-30 | 2024-05-03 | 北京嘀嘀无限科技发展有限公司 | Service station deployment control method and device, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107169605B (en) | 2020-06-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107169605A (en) | City electric car charging station site selecting method based on vehicle location information | |
| CN107153893B (en) | Electric vehicle charging station site selection planning method based on urban parking data | |
| CN102837697B (en) | A kind of electronlmobil course continuation mileage management system and method for work | |
| CN104200649B (en) | Based on the rush-hour path resource dispatching distribution System and method for of pre-first to file | |
| CN102509470B (en) | System and method for realizing energy conservation and emission reduction of vehicle based on dynamic path planning | |
| CN105679009B (en) | A kind of call a taxi/order POI commending systems and method excavated based on GPS data from taxi | |
| CN108537391B (en) | Taxi stop station setting optimization method based on taxi track data | |
| CN110174117A (en) | A kind of electric car charging route planning method | |
| CN105489056B (en) | A kind of parking facilities' forecasting method based on OD matrixes | |
| CN107871184A (en) | A kind of site selecting method of the electric automobile charging station of facing area electrically-charging equipment | |
| CN106599390A (en) | Method for calculating charging load considering time-space stochastic characteristics of electric taxi | |
| CN105303882A (en) | Parking management system and method based on space-time dimension dynamic parking charging strategy | |
| CN107067707A (en) | A kind of bus operation and passenger's trip optimization system | |
| CN102880921A (en) | Method for optimizing site selection of electric vehicle charging stations | |
| CN109703389B (en) | Vehicle pile network integrated charging scheduling device and method based on new energy bus | |
| Paffumi et al. | European-wide study on big data for supporting road transport policy | |
| CN105117595B (en) | A kind of private car trip data integrated approach based on floating car data | |
| CN106530180A (en) | High-cold region charging service network planning method | |
| CN105095993A (en) | System and method for predicting passenger flow volume of railway stations | |
| CN104778832B (en) | A kind of multimode Urban Road Cross-section resource coordination collocation method | |
| CN106373384B (en) | Outlying district regular bus circuit Real-time Generation | |
| WO2023040712A1 (en) | Map data processing method and apparatus | |
| CN102779406A (en) | Cloud computing intelligent transportation scheduling platform based on Beidou time service technology | |
| CN104240042A (en) | Carbon emission management system based on public bicycle system and accumulating method for carbon emission management system | |
| CN106130110B (en) | The electric taxi charging station constant volume method on trip ground is selected based on stratified probability |
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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20200630 |