CN117232535B - Vehicle navigation system based on Internet of things - Google Patents
Vehicle navigation system based on Internet of things Download PDFInfo
- Publication number
- CN117232535B CN117232535B CN202311362859.2A CN202311362859A CN117232535B CN 117232535 B CN117232535 B CN 117232535B CN 202311362859 A CN202311362859 A CN 202311362859A CN 117232535 B CN117232535 B CN 117232535B
- Authority
- CN
- China
- Prior art keywords
- charging
- route
- planned
- vehicle
- module
- 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.)
- Active
Links
- 238000011156 evaluation Methods 0.000 claims abstract description 14
- 238000012544 monitoring process Methods 0.000 claims abstract description 4
- 238000012216 screening Methods 0.000 claims abstract description 4
- 238000005070 sampling Methods 0.000 claims description 18
- 238000012795 verification Methods 0.000 claims description 12
- 238000012937 correction Methods 0.000 claims description 6
- 238000000034 method Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 5
- 230000003247 decreasing effect Effects 0.000 claims description 3
- 230000006855 networking Effects 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
Landscapes
- Navigation (AREA)
Abstract
The invention relates to the technical field of vehicle navigation, in particular to a vehicle navigation system based on the Internet of things, which comprises: vehicle monitoring module: acquiring current vehicle related information; the map grabbing module is used for: acquiring a driving route and charging station information; a charging route generation module: generating a planned charging route for the vehicle to the charging station; the charging station information synchronization module: acquiring operation information of the charging station; and a route planning module: calculating a safe driving mileage; acquiring the length L of each planned charging route, and screening out the planned charging routes meeting the conditions; calculating an evaluation coefficient of a planned charging route conforming to the constraint condition; and selecting a planned charging route corresponding to the maximum value in the evaluation coefficients as a target charging route, and charging the vehicle to a charging station according to the target charging route. The invention can be used for selecting the position of the charging station without deviating from the planned route and the actual driving requirement.
Description
Technical Field
The invention relates to the technical field of vehicle navigation, in particular to a vehicle navigation system based on the Internet of things.
Background
The internet of things refers to a network in which various physical devices, sensors, software, etc. are connected through the internet so that they can communicate with each other and share data. The basic principle is that objects are connected to the internet through various sensors and connection technologies such as Wi-Fi, bluetooth, NFC and the like, and then data is transmitted through a network, so that the objects can communicate and share information with each other. This enables the object to perform intelligent, automated, remote control, etc. And these physical devices may be any object having a unique identifier and capable of network connection, including sensors, automobiles, home appliances, industrial machines, etc.
The vehicle navigation system is intelligent electronic equipment integrated in the automobile, can accurately determine the position of the automobile through a Global Positioning System (GPS) technology, and provides functions of navigation, route planning and the like for a driver. The digital map database is built in, and the digital map database comprises information of roads, streets, landmarks and the like, can monitor traffic conditions in real time, provides real-time navigation suggestions, avoids traffic jams and selects an optimal driving route. It also provides intersection and exit indications, clearly showing how it should be operated at an intersection or highway exit.
The electric energy is used as a power source, the electric energy is stored by the battery pack, and then the electric energy is converted into power by the motor to drive the automobile, so that the automobile is the most common new energy automobile in the prior art. Is popular because it is more environmentally friendly and saves fuel costs. However, the cruising of the electric energy trolley is still an unresolved problem, and the electric energy trolley needs to be frequently carried to a charging station for charging. In the conventional car navigation system, when a driver wants to go to a charging station, the driver merely sets the nearest charging station as the destination to perform route planning, and the situation such as departure from the original route and the running state of the charging station is not considered.
Disclosure of Invention
The invention aims to provide a vehicle navigation system based on the Internet of things, which solves the technical problems.
The aim of the invention can be achieved by the following technical scheme:
Vehicle navigation system based on thing networking includes:
vehicle monitoring module: acquiring the residual electric quantity E re of the current vehicle, the apparent driving range S ba, the total driving range S all of the vehicle and the average driving speed V of the vehicle;
The map grabbing module is used for: acquiring a planned travel route, position information of charging stations around the planned travel route, and a shortest charging route, wherein the planned travel route represents a travel route preselected according to a destination when a vehicle starts, and the shortest charging route represents a shortest route from a charging station to the travel route;
A charging route generation module: acquiring an intersection point between the shortest charging route and the planned traveling route, intercepting a corresponding pre-traveling route from the planned traveling route by taking the current position of the vehicle and the intersection point as end points, and generating a planned charging route by combining the pre-traveling route and the shortest charging route;
The charging station information synchronization module: acquiring operation information of the charging station, wherein the operation information comprises the number n of the spare charging piles, the average use frequency f of the charging piles and the average use time t of the charging piles;
and a route planning module: the safe driving mileage is calculated, and the calculation formula is as follows:
；
E min is a preset safe reserved electric quantity;
The length L of each planned charging route is obtained, the planned charging route meeting the conditions is screened out, and the constraint conditions are as follows:
0.75S≤L≤S；
Calculating an evaluation coefficient K i of a planned charging route which accords with constraint conditions, wherein the calculation formula is as follows:
；
Wherein K i represents an evaluation coefficient of the i-th planned charging route conforming to the constraint condition, and L i represents a length of the i-th planned charging route conforming to the constraint condition;
And selecting a planned charging route corresponding to the maximum value MAX (K i) in the evaluation coefficient K i as a target charging route, and charging the vehicle to a charging station according to the target charging route.
As a further scheme of the invention: the system also comprises a mileage correction module, wherein in the mileage correction module, a verification period T is set, and after the verification period T is passed, the mileage deviation proportion delta S is calculated, and the calculation formula is as follows:
；
Wherein S all 'represents the total driving range of the vehicle after the verification period T, and S ba' represents the apparent driving range of the meter after the verification period T;
And correcting the safety driving mileage to be S' =delta S.S.
As a further scheme of the invention: in the route planning module, after the vehicle is charged in the charging station, the vehicle returns to the planned driving route along the shortest charging route.
As a further scheme of the invention: in the route planning module, when two or more planned charging routes have equal evaluation coefficients, a planned charging route with the largest length is selected as a target charging route.
As a further scheme of the invention: in the map capturing module, the specific step of obtaining the position information of the charging station includes:
Selecting sampling points according to preset intervals in the planned driving route;
selecting a sampling area by taking the sampling point as a circle center and a preset sampling radius r;
and acquiring the position information of all charging stations in the sampling area.
As a further scheme of the invention: in the process of collecting the position information of the charging station, the linear distance d between adjacent sampling points meets the constraint condition: and r is more than or equal to d and less than or equal to 1.25r.
As a further scheme of the invention: in the route planning module, when the number of planned charging routes meeting the constraint conditions is smaller than the preset number, the lower limit value of the length L in the constraint conditions is reduced until the number of planned charging routes meeting the constraint conditions is larger than or equal to the preset number.
As a further scheme of the invention: in the process of reducing the lower limit value of the length L in the constraint condition, the value of each reduction is a preset value A, wherein A epsilon (0.1S, 0.125S).
The invention has the beneficial effects that: in the invention, in the charging planning of the automobile, the normal running requirement is fully considered, and the planned running route is taken as a standard to acquire the position information and the route information of surrounding charging stations; under the premise of considering the residual electric quantity and the driving mileage of the vehicle, calculating the predicted value of the driving mileage of the vehicle when the electric quantity is safely reserved under the condition of the current electric quantity; screening the charging stations by taking the predicted value as a standard, so as to obtain the information of the charging stations meeting the constraint conditions; and finally, according to the actual running condition of each charging station, selecting the charging station with higher priority as a target charging station, thereby selecting the position of the charging station under the condition of not deviating from a route and actual running requirements.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of the vehicle navigation system based on the internet of things.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention is a vehicle navigation system based on internet of things, comprising:
vehicle monitoring module: acquiring the residual electric quantity E re of the current vehicle, the apparent driving range S ba, the total driving range S all of the vehicle and the average driving speed V of the vehicle;
The map grabbing module is used for: acquiring a planned travel route, position information of charging stations around the planned travel route, and a shortest charging route, wherein the planned travel route represents a travel route preselected according to a destination when a vehicle starts, and the shortest charging route represents a shortest route from a charging station to the travel route;
A charging route generation module: acquiring an intersection point between the shortest charging route and the planned traveling route, intercepting a corresponding pre-traveling route from the planned traveling route by taking the current position of the vehicle and the intersection point as end points, and generating a planned charging route by combining the pre-traveling route and the shortest charging route;
The charging station information synchronization module: acquiring operation information of the charging station, wherein the operation information comprises the number n of the spare charging piles, the average use frequency f of the charging piles and the average use time t of the charging piles;
and a route planning module: the safe driving mileage is calculated, and the calculation formula is as follows:
；
E min is a preset safe reserved electric quantity;
The length L of each planned charging route is obtained, the planned charging route meeting the conditions is screened out, and the constraint conditions are as follows:
0.75S≤L≤S；
Calculating an evaluation coefficient K i of a planned charging route which accords with constraint conditions, wherein the calculation formula is as follows:
；
Wherein K i represents an evaluation coefficient of the i-th planned charging route conforming to the constraint condition, and L i represents a length of the i-th planned charging route conforming to the constraint condition;
And selecting a planned charging route corresponding to the maximum value MAX (K i) in the evaluation coefficient K i as a target charging route, and charging the vehicle to a charging station according to the target charging route.
It is noted that, for the existing driving navigation process, the user inputs the destination when the vehicle starts, and selects a proper driving route, that is, the planned driving route in the present scheme, and the acquisition of the route belongs to the prior art, which is not described herein;
In the invention, in the charging planning of the automobile, the normal running requirement is fully considered, and the planned running route is taken as a standard to acquire the position information and the route information of surrounding charging stations; under the premise of considering the residual electric quantity and the driving mileage of the vehicle, calculating the predicted value of the driving mileage of the vehicle when the electric quantity is safely reserved under the condition of the current electric quantity; screening the charging stations by taking the predicted value as a standard, so as to obtain the information of the charging stations meeting the constraint conditions; and finally, according to the actual running condition of each charging station, selecting the charging station with higher priority as a target charging station, thereby selecting the position of the charging station under the condition of not deviating from a route and actual running requirements.
It can be understood that, in the operation information of the charging station in this embodiment, the average usage frequency f of the charging post refers to the number of vehicles that need to be charged when entering the charging station in unit time, and the average usage time t of the charging post refers to the average occupation time of the charging station when the vehicle is charged.
In a preferred embodiment of the present invention, the system further includes a mileage correction module, wherein a verification period T is set in the mileage correction module, and after the verification period T passes, a mileage deviation ratio Δs is calculated, and a calculation formula thereof is as follows:
；
Wherein S all 'represents the total driving range of the vehicle after the verification period T, and S ba' represents the apparent driving range of the meter after the verification period T;
And correcting the safety driving mileage to be S' =delta S.S.
In a preferred embodiment of the invention, in the route planning module, after the vehicle has been charged in the charging station, the planned travel route is returned along the shortest charging route.
In a preferred embodiment of the present invention, in the route planning module, when there are two or more planned charging routes with equal evaluation coefficients, the planned charging route with the largest length is selected as the target charging route.
In a preferred embodiment of the present invention, in the map capturing module, the specific step of obtaining the location information of the charging station includes:
Selecting sampling points according to preset intervals in the planned driving route;
selecting a sampling area by taking the sampling point as a circle center and a preset sampling radius r;
and acquiring the position information of all charging stations in the sampling area.
In a preferred embodiment of the present invention, in the process of collecting the position information of the charging station, the linear distance d between adjacent sampling points satisfies the constraint condition: and r is more than or equal to d and less than or equal to 1.25r.
In a preferred embodiment of the present invention, in the route planning module, when the number of planned charging routes that meet the constraint condition is smaller than the preset number, the lower limit value of the length L in the constraint condition is reduced until the number of planned charging routes that meet the constraint condition is greater than or equal to the preset number.
In a preferred embodiment of the invention, in decreasing the lower limit value of the length L in the constraint, the value of each decrease is a preset value a, where a e (0.1 s,0.125 s).
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (8)
1. Vehicle navigation based on thing networking, its characterized in that includes:
vehicle monitoring module: acquiring the residual electric quantity E re of the current vehicle, the apparent driving range S ba, the total driving range S all of the vehicle and the average driving speed V of the vehicle;
The map grabbing module is used for: acquiring a planned travel route, position information of charging stations around the planned travel route, and a shortest charging route, wherein the planned travel route represents a travel route preselected according to a destination when a vehicle starts, and the shortest charging route represents a shortest route from a charging station to the planned travel route;
A charging route generation module: acquiring an intersection point between the shortest charging route and the planned traveling route, intercepting a corresponding pre-traveling route from the planned traveling route by taking the current position of the vehicle and the intersection point as end points, and generating a planned charging route by combining the pre-traveling route and the shortest charging route;
The charging station information synchronization module: acquiring operation information of the charging station, wherein the operation information comprises the number n of the spare charging piles, the average use frequency f of the charging piles and the average use time t of the charging piles;
and a route planning module: the safe driving mileage is calculated, and the calculation formula is as follows:
E min is a preset safe reserved electric quantity;
The method comprises the steps of obtaining the length L of each planned charging route, and screening out the planned charging routes meeting constraint conditions, wherein the constraint conditions are as follows:
0.75S≤L≤S；
Calculating an evaluation coefficient K i of a planned charging route which accords with constraint conditions, wherein the calculation formula is as follows:
Wherein K i represents an evaluation coefficient of the i-th planned charging route conforming to the constraint condition, and L i represents a length of the i-th planned charging route conforming to the constraint condition;
and selecting a planned charging route corresponding to the maximum value MAX (K i) in the evaluation coefficient K i as a target charging route, and charging the vehicle to a charging station according to the target charging route.
2. The internet of things-based vehicle navigation system according to claim 1, further comprising a mileage correction module, wherein the mileage correction module sets a verification period T, and calculates a mileage deviation ratio Δs after the verification period T passes, wherein the calculation formula is as follows:
Wherein S all 'represents the total driving range of the vehicle after the verification period T, and S ba' represents the apparent driving range of the meter after the verification period T;
and correcting the safety driving mileage to be S' =delta S.S.
3. The internet of things-based vehicle navigation system of claim 1, wherein in the route planning module, the planned travel route is returned along the shortest charging route after the vehicle is charged in the charging station.
4. The internet of things-based car navigation system according to claim 1, wherein in the route planning module, when two or more planned charging routes have equal evaluation coefficients, a planned charging route with the largest length is selected as the target charging route.
5. The internet of things-based vehicle navigation system according to claim 1, wherein the specific step of acquiring the location information of the charging station in the map capturing module includes:
Selecting sampling points according to preset intervals in the planned driving route;
selecting a sampling area by taking the sampling point as a circle center and a preset sampling radius r;
and acquiring the position information of all charging stations in the sampling area.
6. The internet of things-based vehicle navigation system of claim 5, wherein in the process of collecting the position information of the charging station, the linear distance d between adjacent sampling points satisfies a constraint condition: and r is more than or equal to d and less than or equal to 1.25r.
7. The internet of things-based vehicle navigation system according to claim 1, wherein in the route planning module, when the number of planned charging routes satisfying the constraint condition is smaller than a preset number, the lower limit value of the length L in the constraint condition is reduced until the number of planned charging routes satisfying the constraint condition is greater than or equal to the preset number.
8. The internet of things-based car navigation system of claim 7, wherein in decreasing the lower limit value of the length L in the constraint condition, the value decreased each time is a preset value a, where a e (0.1 s,0.125 s).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311362859.2A CN117232535B (en) | 2023-10-20 | 2023-10-20 | Vehicle navigation system based on Internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311362859.2A CN117232535B (en) | 2023-10-20 | 2023-10-20 | Vehicle navigation system based on Internet of things |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117232535A CN117232535A (en) | 2023-12-15 |
| CN117232535B true CN117232535B (en) | 2024-05-17 |
Family
ID=89091220
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311362859.2A Active CN117232535B (en) | 2023-10-20 | 2023-10-20 | Vehicle navigation system based on Internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117232535B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20210149972A (en) * | 2020-06-02 | 2021-12-10 | 현대모비스 주식회사 | Autonomous driving control system and method of vehicle |
| DE102021205559A1 (en) * | 2021-06-01 | 2022-06-30 | Continental Automotive Gmbh | Navigation management system for route planning of a vehicle |
| CN116007648A (en) * | 2023-01-04 | 2023-04-25 | 奇瑞汽车股份有限公司 | Method and system for planning and navigating charging path of pure electric vehicle |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130158868A1 (en) * | 2011-12-14 | 2013-06-20 | Automotive Research & Testing Center | Recursive route planning method for electric vehicle |
| JP6081899B2 (en) * | 2013-11-13 | 2017-02-15 | 三菱重工業株式会社 | Rechargeable vehicle route search device, rechargeable vehicle route search method, rechargeable vehicle management system, and program |
| DE102018214986A1 (en) * | 2018-09-04 | 2020-03-05 | Zf Friedrichshafen Ag | Device, method and system for route planning of an electric vehicle |
| EP3772429A1 (en) * | 2019-08-08 | 2021-02-10 | Ningbo Geely Automobile Research & Development Co., Ltd. | Method for controlling a low fuel or low charge warning system in a vehicle |
-
2023
- 2023-10-20 CN CN202311362859.2A patent/CN117232535B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20210149972A (en) * | 2020-06-02 | 2021-12-10 | 현대모비스 주식회사 | Autonomous driving control system and method of vehicle |
| DE102021205559A1 (en) * | 2021-06-01 | 2022-06-30 | Continental Automotive Gmbh | Navigation management system for route planning of a vehicle |
| CN116007648A (en) * | 2023-01-04 | 2023-04-25 | 奇瑞汽车股份有限公司 | Method and system for planning and navigating charging path of pure electric vehicle |
Non-Patent Citations (3)
| Title |
|---|
| Electric vehicle charging path planning considering the state of EV pile-road-grid;He, Z 等;Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022);20220528;第1-8页 * |
| 基于改进A*算法的电动车能耗最优路径规划;顾青 等;农业机械学报;20151231;第46卷(第12期);第316-322页 * |
| 多信息融合下电动汽车充电路径规划;夏冬 等;电测与仪表;20201216(第22期);第24-32页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117232535A (en) | 2023-12-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111055850B (en) | Intelligent motor vehicle, system and control logic for driver behavior coaching and on-demand mobile charging | |
| CN113135100B (en) | Vehicle charging reminding method and device, storage medium and vehicle | |
| CN110686689B (en) | Vehicle energy usage tracking | |
| US20220178704A1 (en) | Method for predicting future driving conditions for a vehicle | |
| CN106908075B (en) | Big data acquisition and processing system and electric vehicle endurance estimation method based on big data acquisition and processing system | |
| US8949028B1 (en) | Multi-modal route planning | |
| CN110174117B (en) | Electric vehicle charging route planning method | |
| CN103175534B (en) | The system that vehicle route is determined | |
| CN105946857B (en) | Parallel plug-in hybrid electric vehicle (PHEV) energy management method based on intelligent transportation system | |
| EP2343226A1 (en) | Method, system, and apparatus for operating a vehicle | |
| CN101780774B (en) | Route guidance device, route guidance method | |
| US8996213B2 (en) | Charge control system for electric motor vehicle | |
| US8190318B2 (en) | Power management systems and methods in a hybrid vehicle | |
| US11142089B2 (en) | Determining a minimum state of charge for an energy storage means of a vehicle | |
| CN105074387B (en) | Travel assist system, traveling householder method and computer program | |
| US10668824B2 (en) | Method for calculating a setpoint for managing the fuel and electricity consumption of a hybrid motor vehicle | |
| CN108515963B (en) | Energy management method of plug-in hybrid electric vehicle based on ITS system | |
| US11443563B2 (en) | Driving range based on past and future data | |
| JP5683722B2 (en) | Center side system and vehicle side system | |
| CN104044462A (en) | User interface system and method based on calendar event | |
| EP2683574B1 (en) | Method and electronic system for the automatic management of the energy autonomy of a vehicle particularly of electric vehicles | |
| CN110641397A (en) | Electric automobile driving feedback system based on combination of driving data and map prediction | |
| CN114604250A (en) | Electric vehicle control for dynamic road segment-based distance to empty | |
| JP5697761B2 (en) | Center side system and vehicle side system | |
| CN117232535B (en) | Vehicle navigation system based on Internet of things |
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 |