CN106427635A - Electric automobile - Google Patents
Electric automobile Download PDFInfo
- Publication number
- CN106427635A CN106427635A CN201610953623.XA CN201610953623A CN106427635A CN 106427635 A CN106427635 A CN 106427635A CN 201610953623 A CN201610953623 A CN 201610953623A CN 106427635 A CN106427635 A CN 106427635A
- Authority
- CN
- China
- Prior art keywords
- charging
- charging station
- electric automobile
- information
- path
- 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
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/70—Interactions with external data bases, e.g. traffic centres
- B60L2240/72—Charging station selection relying on external data
-
- 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
- Y02T90/14—Plug-in electric vehicles
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention discloses an electric automobile. The electric automobile comprises a battery and a path optimization system. The path optimization system is communicated with a charging communication network through a wireless communication mode; the charging communication network is communicated with a plurality of automobile charging stations through a wireless communication mode; when the electric automobile is required to be charged, charging parameter information of the electric automobile is transmitted to the charging communication network by utilizing the path optimization system, the charging communication network transmits the information to the plurality of charging stations, and after the information is received by the charging stations, charging estimated information provided by the charging stations for the electric automobile is fed back and is transmitted to the electric automobile through the charging communication network. The electric automobile disclosed by the invention has the benefits that an optimal charging scheme can be reasonably selected by utilizing the path optimization system and in combination of self demands, and an optimal drive route and the best charging station are reasonably selected according to current automobile battery states and route conditions, so that the time can be saved, and the charging expense can also be reduced.
Description
Technical field
The present invention relates to a kind of electric automobile is and in particular to a kind of electric automobile comprising optimum path search system.
Background technology
Demand and consumption with fossil fuel constantly increase, and energy scarcity and environmental pollution have become countries in the world suddenly
The difficult problem that need to solve, and electric automobile (Electric Vehicle, EV) relies on driven by power, noise is low, and efficiency is high, and zero is dirty
Dye, more can directly solve energy dependence, exhaust emissions and problem of environmental pollution than traditional fuel-engined vehicle.Its large-scale application is
Alleviate energy scarcity, air environmental pollution and realize one of most effective mode of low-carbon economy.
However, comprising multiple charging stations on travel route when charging electric vehicle, and each charging station can be provided by
Charge power and the unit price that charges different, and a plurality of traffic route of corresponding same destination, every circuit all wraps
Containing multiple available charging stations, from the multiple charging stations a plurality of driving route, how to select the charging station of optimum, so that filling
The difficult problem in electricity univalent minimum or spent time the shortest always charging electric vehicle field.
Content of the invention
It is an object of the invention to overcoming the deficiencies in the prior art, invent a kind of electronic vapour comprising optimum path search system
Car, helps driver to select the optimum charging station on optimum traffic route and this route, helps driver to reduce money or time
Cost.
The present invention provide technical scheme be：A kind of electric automobile, electric automobile includes battery and optimum path search system, road
Footpath optimization system is communicated with charging communication network with communication, between charging communication network and multiple vehicle charging station with
Communication is communicated, when electric automobile needs to charge, using optimum path search system by the charge parameter of electric automobile
To the communication network that charges, charging communication network sends above- mentioned information to multiple charging stations to information transfer, after charging station receive information, instead
The charging prediction information that feedback charging station provides for this electric automobile is sent to electric automobile by charging communication network.
The charge parameter information of described electric automobile includes：The battery capacity of electric automobile, electric automobile internally-powered battery
Current SOC, allow charge power scope, expectation charge period.Charging prediction information includes：Charge period, charge power and
Charge univalent information.Optimum path search system includes：Charging instruction input module, available path determining module, charged state module,
Charging station selects and path selection module and display module.Charging instruction input module is used for obtaining electric automobile the need of filling
The information of electricity, this information can come from the charging instruction of user input or the charging instruction automatically generating according to battery electric quantity.
Automobile current geographic position information and destination geographical location information are inputted its internal map letter by available path determining module
Breath system, determines all ride travelling from current location to destination from cartographic information system, and will be defeated for this information
Enter and select and path selection module to charging station.Charged state module receives charging instruction at charging instruction input module
Afterwards, battery current SOC state is calculated according to battery status, and calculate power bracket, the charging institute needing to charge according to this SOC
The time needing and charge period, and enter this information into charging station selection and path selection module.
Charging station selects and path selection module comprises communication module, and it utilizes communication module to join the charging of electric automobile
Number information sends all charging stations to ride, and all charging stations on drive route select to charging station and path choosing
Select module feedback charge could, charge period and the corresponding univalent information that charges of charge period, charging station selects and Path selection
The power of the charging of electric automobile that ride that module sends according to available path determining module, charged state module send
Scope, charge required time, charge period information and the charging that charging station feeds back could, charge period and charge period corresponding
The univalent information that charges the ride of optimum and the charging that be located at this ride on are calculated and determined out according to optimizing mode
Stand, and the charging station by optimum ride and on this ride sends to display module.Display module is by optimum
Ride and be located at this ride on charge station information shown in the form of cartographic information, to facilitate driver to carry out
Select or confirm.
Optimizing mode comprises the steps：1）Determine optimization aim：Drive driving time required for destination and
Charging required time sum is minimum on the way；2）Determine optimization method：Tij=Si/Vi+Bij/CVij, wherein, Tij represents from current
Position travels to target ground, and j-th charging station charges on the i-th paths and the i-th paths, and completing above-mentioned task needs to spend altogether
The time taken, Si is the circuit distance of i-th driving path, and Vi is the road speed estimated for the i-th paths jam situation,
Bij is that automobile is travelled by the i-th paths to the electricity of j-th charging station moment automobile needs charging, and CVij is on the i-th paths
The charge rate that can be provided by of j-th charging station, it is that the charge power that this electric automobile can be provided by just becomes with charging station
Than, Vi is the speed estimating out according to history driving recording, by the corresponding Si of each available charging station of available planning driving path,
Vi, Bij and CVij information is brought above-mentioned formula respectively into and is calculated the corresponding Tij of each charging station, from multiple calculated Tij
Select minimum of a value Tijmin, Tijmin can be a numerical value can also be multiple numerical value, can just calculated be less than
The Tij of certain time threshold value is all set as Tijmin；3) by the charging station in planning driving path i corresponding to Tijmin and this path
J is defined as optimum planning driving path and its corresponding charging station.
Optimizing mode comprises the steps：1）Determine optimization aim：The unit price that charges is minimum；2）Determine optimization method：Cij=
Cj+Cj×（Sij-S0)/S0, wherein, Cij represents charging unit price after the conversion of j-th charging station charging on the i-th paths, Cj
Corresponding electric automobile travels the charging station forecast unit price of the charge period to this j-th charging station, Sij along the i-th paths
For selecting after on the i-th paths, j-th charging station is as charging station, automobile travels from it to the traveling of destination with being currently located
Distance, that is, the i-th paths travel to the distance of destination, S0 represents the air line distance being currently located ground distance objective ground；By S0
And each available charging station corresponding Cj, Sij of available planning driving path brings above-mentioned formula respectively into and calculates each charging station pair
The Cij answering, selects minimum of a value Cijmin, Cijmin can be a numerical value can also be many from multiple calculated Cij
Individual numerical value, can all be set as Cijmin by the just calculated Cij less than certain threshold value；3) by the row corresponding to Cijmin
Charging station j on bus or train route footpath i and this path is defined as optimum planning driving path and its corresponding charging station.
Implement the electric automobile charging station of the present invention, have the advantages that, using optimum path search system of the present invention
Electric automobile can be in conjunction with self-demand, and reasonable selection optimum charging scheme closes according to current automobile batteries state, line conditions
Reason selects optimum traffic route and optimal charge station, can save the time it is also possible to reduce charging expense.
Brief description
Charging station deployment scenarios figure around Fig. 1 road network and road network.
Schematic diagram is communicated between Fig. 2 charging station, charging communication network and charging station.
Optimum path search system layout in Fig. 3 electric automobile.
Specific embodiment
Fig. 1 is charging station deployment scenarios figure around the road network of the present invention and road network：To geographical position by the way of grid
Information is defined, on grid, the scale of abscissa is defined as A, B, C ... J, K, L, and ordinate is defined as 1,2,3 ... 9,10,11,
For example：Respective coordinates are C11, K2 respectively in figure square position, are respectively used to represent automobile present position and purpose
Position, the circle position charging station to the path of destination for the corresponding driving respectively, its coordinate definition is H10, J6,
G8, I6, D10, J3, D9, F6, I3, E5, H3, C6, D4 and H2, charging station H10, J6 of wherein being defined by geographical position are located at
Article first, in planning driving path S1, planning driving path correspondence travels from automobile present position to the vehicle line of destination locations,
Charging station G8, I6 are located in Article 2 planning driving path S2, and charging station D10, J3 are located in Article 3 planning driving path S3, charging station
D9, F6 and I3 are located in Article 4 planning driving path S4, and charging station E5, H3 are located in Article 5 planning driving path S5 respectively, charging station
C6, D4 and H2 are located in Article 6 planning driving path S6 respectively.Combine the selection that planning driving path determines optimum charging station for convenience,
Charging station position mirror image can be represented on the line, for example, in figure charging station H10, J6 are respectively positioned on first roadway
On footpath, respectively charging station H10 is defined as 11, J6 according to the direction of traffic to destination and is defined as 12,1 representing at this charging station
In first planning driving path, 2 represent second charging station running on this line direction, in the same manner, positioned at Article 2 driving
Charging station G8, I6 on path are respectively defined as 21,22.Around above-mentioned road network and road network, charging station deployment scenarios figure is stored in and fills
In the identification module of power station, during for selecting optimum planning driving path, input computing unit, asking in order to optimization method as parameter
Solution, and calculate and select the charging station on optimum planning driving path and this path accordingly.
Fig. 2 is to communicate schematic diagram between electric automobile, charging communication network and charging station, and electric automobile utilizes its in-car path
Optimization system or special communication system by the battery capacity of electric automobile, current SOC and allow the basic ginseng such as charge power scope
To the communication network that charges, above-mentioned parameter information is forwarded to electric automobile charging station, charging station root to number information transmission by charging communication network
Determine whether to be that this charging electric vehicle, charge period, charge power and the univalent information of charging send to charging according to above- mentioned information
Communication network, charging communication network forwards this information to the electric automobile needing to charge again.Electric automobile, charging communication network and fill
Communicated using mobile radio communication system between power station.
Fig. 3 is optimum path search system layout in the electric automobile of the present invention, and optimum path search system 300 includes charging instruction
Input module 310, available path determining module 320, charged state module 330, charging station selects and path selection module 340 He
Display module 350.Wherein, charging instruction input module is used for obtaining electric automobile the need of the information charging, and this information can
Since from the charging instruction of user input it is also possible to the charging instruction being automatically generated, for example：When automobile internally-powered battery electric quantity
State automatically generates charging instruction to charging instruction input module when being less than certain threshold value.When charging instruction input module determines
When receiving charging instruction, user is pointed out to input destination geographical location information further, charging instruction input module 310 will afterwards
Destination geographical location information inputs to available path determining module 320, and charging instruction is inputted to charged state module 330.
Automobile current geographic position information and destination geographical location information are inputted its internal map by available path determining module 320
Information system, determines all feasible ride from current location to destination or path from cartographic information system.Work as road
When footpath is more, it can be screened, select preferably path relatively.For example：If current location is apart from destination
The distance of short path is S, and the path that path distance can be more than 1.5s is rejected, or ought according to history driver information system
The path that the front period easily blocks up is rejected.Available path determining module 320 is by the mulitpath information input after screening to charging
Stand and select and path selection module 340.After charged state module 330 receives charging instruction, battery is calculated according to battery status and works as
Front SOC state, and the time according to needed for this SOC calculates the power bracket needing to charge and charges, and by this information input
Select and path selection module 340 to charging station.Charging station selects and path selection module 340 receives available path determining module
The mulitpath information of 320 transmissions and the SOC of electric automobile internally-powered battery, the power bracket of the charging and charging required time
After information, send, to all charging stations on all feasible paths, unit price consulting of charging, and according to routing information, battery status
The optimum charging station that information and the univalent information that charges calculate and select on optimum charge path and this path, charging station selection and
Path selection module will determine multiple schemes, and these schemes can be that path is identical, but charging station difference or path
Difference, but the technical scheme that charging station is identical or charging station is all different from path.Will be corresponding for each scheme in multiple schemes
Charge station information on driving path and path sends to display module 350, by display module 350 by path and charging thereon
Station is shown, to facilitate driver to be selected or to confirm.Wherein also include communication system and control system on display module,
When travelling driving path and the charging station in scheme and scheme when driver certifying, the communication system on display module needs charging
Ask information to send to selected charging station, examine whether this charging station can meet charge requirement in charge period.This charging needs
Ask information can include the information such as battery SOC, charge power and charging interval simultaneously.When this charging station can be expired at the appointed time
During the charge requirement of sufficient electric automobile, display module receives the confirmation charge information of charging station, is prompted to driver afterwards, and
Charging station on driving path and path is shown to driver with cartographic information, to facilitate driver to try to locate by following up a clue.When this fills
When power station can not meet the charge requirement of electric automobile at the appointed time, charge requirement is believed by the communication system on display module
Whether breath sends to the selected charging station of another program, carry out examining by step before and can charge in this charging station, if
Can charge and then charge path and charging station be shown, if repeat the above steps can not be continued, until selecting suitable scheme.Fill
Power station selects and path selection module 340 can optimum scheme comparison as follows：1）Determine optimization aim：Drive to destination
Required driving time and on the way charging required time sum minimum；2）Determine optimization method：Tij=Si/Vi+Bij/
CVij, wherein, Tij represents and travels to target ground from current location, and j-th charging station on the i-th paths and the i-th paths
Charge, complete the time that above-mentioned task need to spend altogether, Si is the circuit distance of i-th driving path, Vi is for the i-th paths
The road speed that jam situation is estimated, Bij is travelled by the i-th paths for automobile to be needed to charge to j-th charging station moment automobile
Electricity, CVij is the charge rate that j-th charging station on the i-th paths can be provided by, and it is this electronic vapour with charging station
The charge power that car can be provided by is directly proportional, and Vi is the speed estimating out according to history driving recording, by available planning driving path
Corresponding Si, Vi, the Bij and CVij information of each available charging station bring above-mentioned formula respectively into calculate each charging station corresponding
Tij, selects minimum of a value Tijmin, Tijmin can be a numerical value can also be many numbers from multiple calculated Tij
Value, can all be set as Tijmin by the just calculated Tij less than certain time threshold value；3) by the row corresponding to Tijmin
Charging station j on bus or train route footpath i and this path is defined as optimum planning driving path and its corresponding charging station.
Charging station selects and path selection module 340 also can optimum scheme comparison as follows：1）Determine optimization aim：
The unit price that charges is minimum；2）Determine optimization method：Cij=Cj+Cj×（Sij-S0)/S0, wherein, Cij represents jth on the i-th paths
Charge after the conversion that individual charging station charges unit price, and the corresponding electric automobile of Cj travels to this j-th charging station along the i-th paths
Charge period charging station forecast unit price, Sij be select the i-th paths on j-th charging station as charging station after, automobile from
It travels to the operating range of destination with being currently located, and that is, the i-th paths travel to the distance of destination, and S0 represents current institute
Air line distance on ground distance objective ground；By each available charging station corresponding Cj, Sij of S0 and available planning driving path respectively
Bring above-mentioned formula into and calculate the corresponding Cij of each charging station, from multiple calculated Cij, select minimum of a value Cijmin,
Cijmin can be a numerical value can also be multiple numerical value, can the just calculated Cij less than certain threshold value be all provided with
It is set to Cijmin；3) by the charging station j in planning driving path i corresponding to Cijmin and this path be defined as optimum planning driving path and
Its corresponding charging station.
The invention is not restricted to the disclosed embodiments and accompanying drawing and fall into each of spirit and scope of the present invention it is intended to cover
Plant change and deform.
Claims (10)
1. a kind of electric automobile, electric automobile include battery and optimum path search system it is characterised in that：Optimum path search system is with no
Line communication mode is communicated with charging communication network, is entered with communication between charging communication network and multiple vehicle charging station
Row communication, when electric automobile needs to charge, using optimum path search system by the charge parameter information transfer of electric automobile to charging
Communication network, charging communication network sends above- mentioned information to multiple charging stations, and after charging station receive information, feedback charging station is this electricity
The charging prediction information of electrical automobile offer is simultaneously sent to electric automobile by charging communication network.
2. electric automobile according to claim 1 it is characterised in that：The charge parameter information of described electric automobile includes：
When the battery capacity of electric automobile, the current SOC of electric automobile internally-powered battery, permission charge power scope and expectation are charged
Section.
3. electric automobile according to claim 2 it is characterised in that：Described charging prediction information includes：Charge period,
Charge power and the univalent information that charges.
4. electric automobile according to claim 1 it is characterised in that：Described optimum path search system includes：Charging instruction is defeated
Enter module, available path determining module, charged state module, charging station selects and path selection module and display module.
5. electric automobile according to claim 4 it is characterised in that：Described charging instruction input module is used for obtaining electronic
The need of the information charging, this information is derived from the charging instruction of user input or is automatically generated according to battery electric quantity automobile
Charging instruction.
6. electric automobile according to claim 4 it is characterised in that：Available path determining module is by automobile current geographic position
Confidence breath and destination geographical location information input its internal cartographic information system, determine from current from cartographic information system
Position travels to all ride of destination, and enters this information into charging station selection and path selection module.
7. electric automobile according to claim 4 it is characterised in that：Charged state module is at charging instruction input module
After receiving charging instruction, battery current SOC state is calculated according to battery status, and calculate what needs charged according to this SOC
Power bracket, charging required time and charge period, and enter this information into charging station selection and path selection module.
8. electric automobile according to claim 4 it is characterised in that：Charging station selects and path selection module comprises to communicate
Module, its all charging station being sent the charge parameter information of electric automobile to ride using communication module, drive
All charging stations on route select to charging station and path selection module feedback charging could, charge period and charge period pair
Answer charging unit price information, charging station select and path selection module sent according to available path determining module ride,
The power bracket of the charging of electric automobile of charged state module transmission, charge required time, charge period information and charging
The charging of feedback of standing could, charge period and the corresponding univalent information that charges of charge period is calculated and determined out according to optimizing mode
Optimum ride and the charging station being located on this ride, and by optimum ride and be located on this ride
Charging station send to display module, display module is by optimum ride and the charge station information that is located on this ride
Shown in the form of cartographic information, to facilitate driver to be selected or to confirm.
9. electric automobile according to claim 8 it is characterised in that：Optimizing mode comprises the steps：1）Determine and optimize
Target：Drive driving time required for destination and on the way charging required time sum minimum；2）Determine optimization method：
Tij=Si/Vi+Bij/CVij, wherein, Tij represents and travels to target ground from current location, and on the i-th paths JiiTiao road
On footpath, j-th charging station charges, and completes the time that above-mentioned task need to spend altogether, Si is the circuit distance of i-th driving path, Vi
It is the road speed estimated for the i-th paths jam situation, when Bij is travelled to j-th charging station by the i-th paths for automobile
Carve automobile need charge electricity, CVij is the charge rate that j-th charging station on the i-th paths can be provided by, its with fill
Power station is that the charge power that this electric automobile can be provided by is directly proportional, and Vi is the speed estimating out according to history driving recording,
By corresponding Si, Vi, the Bij and CVij information of each available charging station of available planning driving path bring into respectively above-mentioned formula calculate every
The corresponding Tij of individual charging station, selects minimum of a value Tijmin, Tijmin can be a numerical value from multiple calculated Tij
Can also be multiple numerical value, the calculated Tij less than certain time threshold value is all set as Tijmin；3) by Tijmin institute
Charging station j in corresponding planning driving path i and this path is defined as optimum planning driving path and its corresponding charging station.
10. electric automobile according to claim 8 it is characterised in that：Optimizing mode comprises the steps：1）Determine and optimize
Target：The unit price that charges is minimum；2）Determine optimization method：Cij=Cj+Cj×（Sij-S0)/S0, wherein, Cij represents the i-th paths
Charge after the conversion that upper j-th charging station charges unit price, and the corresponding electric automobile of Cj travels along the i-th paths and fills for j-th to this
Charge period behind power station charging station forecast unit price, Sij be select the i-th paths on j-th charging station as charging station after,
Automobile travels from it to the operating range of destination with being currently located, and that is, the i-th paths travel to the distance of destination, and S0 represents
It is currently located the air line distance on ground distance objective ground；By the corresponding Cj of each available charging station of S0 and available planning driving path,
Sij brings above-mentioned formula respectively into and calculates the corresponding Cij of each charging station, selects minimum of a value from multiple calculated Cij
Cijmin, Cijmin can be a numerical value can also be multiple numerical value, and the calculated Cij less than certain threshold value is all provided with
It is set to Cijmin；3) by the charging station j in planning driving path i corresponding to Cijmin and this path be defined as optimum planning driving path and
Its corresponding charging station.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610953623.XA CN106427635B (en) | 2016-11-03 | 2016-11-03 | A kind of electric car |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610953623.XA CN106427635B (en) | 2016-11-03 | 2016-11-03 | A kind of electric car |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106427635A true CN106427635A (en) | 2017-02-22 |
| CN106427635B CN106427635B (en) | 2019-03-26 |
Family
ID=58179986
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610953623.XA Active CN106427635B (en) | 2016-11-03 | 2016-11-03 | A kind of electric car |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106427635B (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108470224A (en) * | 2018-03-20 | 2018-08-31 | 李琰 | Charging station selection method, medium and equipment based on electric vehicle charging |
| CN108622038A (en) * | 2018-05-04 | 2018-10-09 | 佛山琴笙科技有限公司 | A kind of fuel cell new energy vehicle fuel delivery system |
| CN108973750A (en) * | 2018-08-13 | 2018-12-11 | 青岛特锐德电气股份有限公司 | A kind of Vehicular charging method and apparatus |
| CN109141458A (en) * | 2018-09-10 | 2019-01-04 | 威马智慧出行科技（上海）有限公司 | A kind of navigation route planning method and its system |
| CN109969038A (en) * | 2019-04-16 | 2019-07-05 | 爱驰汽车有限公司 | Energy management method, system, equipment and the storage medium of vehicle-mounted double source battery pack |
| CN110015127A (en) * | 2017-08-21 | 2019-07-16 | 大石祖耀 | The charging station method for searching of electric vehicle |
| CN110816320A (en) * | 2019-11-12 | 2020-02-21 | 华育昌(肇庆)智能科技研究有限公司 | Vehicle energy management system based on artificial intelligence |
| CN113942401A (en) * | 2021-10-29 | 2022-01-18 | 文远苏行(江苏)科技有限公司 | Charging station determination method, charging station determination apparatus, removable carrier, and storage medium |
| US11441917B2 (en) | 2019-08-14 | 2022-09-13 | Honda Motor Co., Ltd. | System and method for adjusting an electric vehicle charging speed |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140214321A1 (en) * | 2011-08-12 | 2014-07-31 | Toyota Jidosha Kabushiki Kaisha | Charging information-providing apparatus |
| CN104424511A (en) * | 2013-09-06 | 2015-03-18 | 现代自动车株式会社 | Method and system for providing driving route information of electric vehicle |
| CN104598988A (en) * | 2014-12-23 | 2015-05-06 | 北京交通大学 | Electric vehicle charging station selection method based on charging reservation |
| CN104821624A (en) * | 2015-05-07 | 2015-08-05 | 苏州天鸣信息科技有限公司 | Search and navigation method and search and navigation system based on electric vehicle fast charging stations |
| CN104864883A (en) * | 2015-05-22 | 2015-08-26 | 清华大学 | Cloud platform based electric automobile path planning method |
-
2016
- 2016-11-03 CN CN201610953623.XA patent/CN106427635B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140214321A1 (en) * | 2011-08-12 | 2014-07-31 | Toyota Jidosha Kabushiki Kaisha | Charging information-providing apparatus |
| CN104424511A (en) * | 2013-09-06 | 2015-03-18 | 现代自动车株式会社 | Method and system for providing driving route information of electric vehicle |
| CN104598988A (en) * | 2014-12-23 | 2015-05-06 | 北京交通大学 | Electric vehicle charging station selection method based on charging reservation |
| CN104821624A (en) * | 2015-05-07 | 2015-08-05 | 苏州天鸣信息科技有限公司 | Search and navigation method and search and navigation system based on electric vehicle fast charging stations |
| CN104864883A (en) * | 2015-05-22 | 2015-08-26 | 清华大学 | Cloud platform based electric automobile path planning method |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110015127A (en) * | 2017-08-21 | 2019-07-16 | 大石祖耀 | The charging station method for searching of electric vehicle |
| CN108470224A (en) * | 2018-03-20 | 2018-08-31 | 李琰 | Charging station selection method, medium and equipment based on electric vehicle charging |
| CN108622038A (en) * | 2018-05-04 | 2018-10-09 | 佛山琴笙科技有限公司 | A kind of fuel cell new energy vehicle fuel delivery system |
| CN108973750B (en) * | 2018-08-13 | 2020-07-17 | 青岛特来电新能源科技有限公司 | Vehicle charging method and device |
| CN108973750A (en) * | 2018-08-13 | 2018-12-11 | 青岛特锐德电气股份有限公司 | A kind of Vehicular charging method and apparatus |
| CN109141458A (en) * | 2018-09-10 | 2019-01-04 | 威马智慧出行科技（上海）有限公司 | A kind of navigation route planning method and its system |
| CN109969038A (en) * | 2019-04-16 | 2019-07-05 | 爱驰汽车有限公司 | Energy management method, system, equipment and the storage medium of vehicle-mounted double source battery pack |
| US11441917B2 (en) | 2019-08-14 | 2022-09-13 | Honda Motor Co., Ltd. | System and method for adjusting an electric vehicle charging speed |
| US11740098B2 (en) | 2019-08-14 | 2023-08-29 | Honda Motor Co., Ltd. | System and method for providing charging options based on electric vehicle operator activities |
| US11920940B2 (en) | 2019-08-14 | 2024-03-05 | Honda Motor Co., Ltd. | System and method for adjusting an electric vehicle charging speed |
| US12018955B2 (en) | 2019-08-14 | 2024-06-25 | Honda Motor Co., Ltd. | System and method for presenting electric vehicle charging options |
| CN110816320A (en) * | 2019-11-12 | 2020-02-21 | 华育昌(肇庆)智能科技研究有限公司 | Vehicle energy management system based on artificial intelligence |
| CN113942401A (en) * | 2021-10-29 | 2022-01-18 | 文远苏行(江苏)科技有限公司 | Charging station determination method, charging station determination apparatus, removable carrier, and storage medium |
| CN113942401B (en) * | 2021-10-29 | 2023-11-24 | 文远苏行(江苏)科技有限公司 | Charging station determining method, charging station determining device, movable carrier and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106427635B (en) | 2019-03-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106427635B (en) | A kind of electric car | |
| Shen et al. | Optimal energy management strategy for a plug-in hybrid electric commercial vehicle based on velocity prediction | |
| Guo et al. | Rapid-charging navigation of electric vehicles based on real-time power systems and traffic data | |
| CN110880054B (en) | Planning method for electric network car-booking charging and battery-swapping path | |
| Fotouhi et al. | A review on the applications of driving data and traffic information for vehicles׳ energy conservation | |
| CN106042963B (en) | The cooperative optimization method and system of electrified transportation network and electric system | |
| CN103236177B (en) | Control method of intelligent interactive system with vehicular network multi-system fusion | |
| CN107323300A (en) | A kind of electric automobile reservation charging method based on way station car conjunctive model | |
| CN108365986B (en) | Hybrid power fleet based on Model Predictive Control cooperates with energy management method | |
| CN103236179A (en) | Method for charging and navigating electric vehicles on basis of traffic information and power grid information | |
| CN108932561B (en) | Electric vehicle charging path selection method considering nonlinear charging function | |
| Li et al. | Electric vehicles network with nomadic portable charging stations | |
| EP2760696A2 (en) | Method and system for charging electric vehicles | |
| CN107818377A (en) | Vehicle global optimization control method, system, vehicle and cloud computing platform based on cloud computing platform | |
| CN103072572B (en) | Chargeable hybrid power vehicle remotely optimizes system | |
| CN103935259A (en) | Electric automobile optimal path finding method based on power consumption | |
| CN104184190A (en) | Dynamic charging path planning method for electric vehicle | |
| CN111347897A (en) | Mutual power borrowing system of unmanned vehicle and control method thereof | |
| JP2015211482A (en) | Smart grid system | |
| CN110422165A (en) | The control device of hybrid vehicle | |
| CN112389254A (en) | Intelligent coordination management system and control method for electric automobile and charging facility | |
| CN110293872A (en) | A kind of electric car intelligent charge navigation system and method | |
| CN114936666B (en) | Electric automobile charging navigation method and system based on vehicle-station-platform system | |
| Jung et al. | Shared-taxi operations with electric vehicles | |
| CN115510672A (en) | Electric micro-trip vehicle battery replacement demand prediction method under perception environment of Internet of things |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20221212 Address after: 102, East 1st Floor, Management Committee of Shandong Pingyi Economic Development Zone, West Section of Jinhua Road, Pingyi Street, Pingyi County, Linyi City, Shandong Province, 276000 Patentee after: Pingyi County Economic Development Enterprise Service Co.,Ltd. Address before: Room 001, Building B, Science and Technology Center, Lu'an City, Lu'an City, Anhui Province, 237000 (intersection of Jingsan Road and Gaocheng East Road) Patentee before: LU'AN KEYU PATENT TECHNOLOGY DEVELOPMENT SERVICE Co.,Ltd. |