CN113859053A - Fuel cell management method, system, device, and medium based on travel demand - Google Patents
Fuel cell management method, system, device, and medium based on travel demand Download PDFInfo
- Publication number
- CN113859053A CN113859053A CN202111332965.7A CN202111332965A CN113859053A CN 113859053 A CN113859053 A CN 113859053A CN 202111332965 A CN202111332965 A CN 202111332965A CN 113859053 A CN113859053 A CN 113859053A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- fuel cell
- predicted
- feasible
- traffic
- 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.)
- Pending
Links
- 239000000446 fuel Substances 0.000 title claims abstract description 66
- 238000007726 management method Methods 0.000 title claims abstract description 32
- 238000000034 method Methods 0.000 claims abstract description 6
- 238000001228 spectrum Methods 0.000 claims description 8
- 238000004891 communication Methods 0.000 description 9
- 238000004364 calculation method Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000005265 energy consumption Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 238000013500 data storage Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 229910052739 hydrogen Inorganic materials 0.000 description 2
- 239000001257 hydrogen Substances 0.000 description 2
- 230000002035 prolonged effect Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
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
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/30—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling fuel cells
-
- 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
- B60L2250/00—Driver interactions
- B60L2250/16—Driver interactions by display
-
- 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
- Y02T90/40—Application of hydrogen technology to transportation, e.g. using fuel cells
Landscapes
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Sustainable Development (AREA)
- Sustainable Energy (AREA)
- Power Engineering (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
- Fuel Cell (AREA)
Abstract
The invention discloses a fuel cell management method, a system, equipment and a medium based on driving requirements. A method of fuel cell management based on driving demand, comprising: receiving driving demand information input by a driver; acquiring feasible paths and predicted vehicle passing data according to the driving demand information; predicting to obtain a vehicle predicted running state based on vehicle predicted traffic data and vehicle power parameters; the power output of the fuel cell is controlled in accordance with the predicted running state of the vehicle. A fuel cell management system based on driving demand, comprising: the information transceiving module is used for receiving driving demand information input by a driver; the operation module is used for obtaining a feasible path and predicted vehicle passing data according to the driving demand information; predicting to obtain the predicted running state of the vehicle based on the predicted passing data of the vehicle and the power parameters of the vehicle; and a control module. The invention also provides equipment and a medium for realizing the fuel cell management method based on the driving requirement.
Description
Technical Field
The invention relates to the technical field of fuel cell vehicles, in particular to a fuel cell management method, a fuel cell management system, fuel cell management equipment and a fuel cell management medium based on driving requirements.
Background
The difficulty of the wide application of fuel cell vehicles lies in that the cost of the fuel cell and hydrogen is high, the improvement of the service life and the efficiency of the fuel cell is a key factor of the development of the fuel cell vehicle, and the energy management technology is the most effective and practical technical means at present under the condition that the fuel cell technology is difficult to have major breakthrough in a short time.
The energy management technology can effectively reduce the load change requirement of the driving working condition on the fuel cell and prolong the service life of the fuel cell; meanwhile, under the condition of meeting the requirement of a single running working condition, the instantaneous power of the working point of the fuel cell is reduced, the overall efficiency is improved, and the hydrogen consumption is reduced. Therefore, the use cost of the fuel cell automobile is reduced in the whole life cycle.
At present, the power control of the fuel cell is an optimized result obtained according to instantaneous driving requirements and the characteristics of a vehicle and parts thereof. In the prior art, the driving requirement of a driver, the road traffic condition and the vehicle are not considered as a whole, so that the current fuel cell vehicle has high energy consumption and short service life.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a method, system, device and medium for managing a fuel cell based on a driving demand.
In a first aspect, the present invention provides a fuel cell management method based on a travel demand, comprising:
receiving driving demand information input by a driver;
acquiring feasible paths and predicted vehicle passing data according to the driving demand information;
predicting to obtain a vehicle predicted running state based on vehicle predicted traffic data and vehicle power parameters;
the power output of the fuel cell is controlled in accordance with the predicted running state of the vehicle.
In one embodiment of the above technical solution, the driving demand information includes: a transport destination, and a desired arrival time and/or a desired transit path.
In one embodiment, the receiving of the driving demand information input by the driver includes: and receiving driving demand information input by a driver through the HMI.
In one embodiment, the vehicle predicted traffic data includes a vehicle predicted traffic average speed and a vehicle predicted traffic time.
In one embodiment of the foregoing technical solution, the obtaining the feasible route and the predicted vehicle passing data according to the driving demand information includes:
planning to obtain a feasible path according to the driving demand information;
acquiring traffic state information, matching the traffic state information to corresponding feasible paths, and selecting a better feasible path from the feasible paths;
and calculating the vehicle predicted traffic data of the better feasible path.
In an embodiment of the foregoing technical solution, the traffic status information includes: one or more of traffic flow speed, passing time, intersection distance, traffic light time, weather conditions, time intervals and sudden accidents on the road section;
the selecting a better feasible path from the feasible paths includes: and selecting the feasible path with the shortest transit time and/or the shortest jam time from the feasible paths as the better feasible path.
In one embodiment, the predicting and obtaining the predicted driving state of the vehicle based on the predicted traffic data of the vehicle and the dynamic parameters of the vehicle itself includes:
and calculating the running speed spectrum and the running power of the vehicle on a better feasible path based on the vehicle predicted traffic data and the vehicle power parameters, namely predicting to obtain the vehicle predicted running state.
In a second aspect, the present invention provides a fuel cell management system based on a travel demand, comprising:
the information transceiving module is used for receiving driving demand information input by a driver;
the operation module is used for obtaining a feasible path and predicted vehicle passing data according to the driving demand information; predicting to obtain the predicted running state of the vehicle based on the predicted passing data of the vehicle and the power parameters of the vehicle;
and the control module is used for controlling the power output of the fuel cell according to the predicted running state of the vehicle.
In a third aspect, the present invention provides an apparatus comprising:
a memory for storing one or more programs;
a processor for executing the program stored in the memory to implement the fuel cell management method based on travel demand according to any one of the above.
In a fourth aspect, the present invention also provides a computer-readable storage medium storing at least one program, wherein the program, when executed by a processor, implements a fuel cell management method based on travel needs as in any one of the above.
Compared with the prior art, the method and the device have the advantages that the feasible path and the predicted vehicle running data are obtained according to the running demand information input by the driver, the predicted vehicle running state is obtained through prediction based on the predicted vehicle running data and the power parameters of the vehicle, the power output of the fuel cell is controlled according to the predicted vehicle running state, the analysis of the feasible path, the predicted vehicle running data and the predicted vehicle running state based on the running demand of the driver is realized, the basis is provided for the power output control of the fuel cell, the scientific effectiveness of the power control of the fuel cell is effectively improved, the optimal energy consumption effect is achieved, and the service lives of the fuel cell and the vehicle are prolonged.
For a better understanding and practice, the invention is described in detail below with reference to the accompanying drawings.
Drawings
Fig. 1 is an exemplary flow chart diagram of a fuel cell management method based on travel demand according to the present invention.
Fig. 2 is an exemplary block diagram of a fuel cell management system based on travel demand of the present invention.
Detailed Description
The terms of orientation of up, down, left, right, front, back, top, bottom, and the like, referred to or may be referred to in this specification, are defined relative to their configuration, and are relative concepts. Therefore, it may be changed according to different positions and different use states. Therefore, these and other directional terms should not be construed as limiting terms.
The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of implementations consistent with certain aspects of the present disclosure.
The terminology used in the present disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this disclosure, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, fig. 1 is a block diagram illustrating an exemplary flow of a fuel cell management method based on driving demand according to the present invention.
In a first aspect, the present invention provides a fuel cell management method based on a travel demand, comprising:
Optionally, the driving demand information includes: a transport destination, and a desired arrival time and/or a desired transit path.
Preferably, the receiving of the driving demand information input by the driver includes: and receiving driving demand information input by a driver through the HMI.
For example, the driver may input the transportation destination and the desired arrival time, or the transportation destination and the desired passing route, or the transportation destination, the desired arrival time, and the desired passing route through the HMI.
In specific implementation, the specific receiving mode of the HMI may be through a vehicle display screen, or through a terminal such as a mobile phone in communication connection with a vehicle center console.
And 102, acquiring feasible paths and predicted vehicle passing data according to the driving demand information.
Optionally, the vehicle expected traffic data includes an average speed of vehicle expected traffic and an expected traffic time of the vehicle. The obtained vehicle predicted passing average speed and the vehicle predicted passing time can provide basis for obtaining the vehicle predicted running state in a prediction mode.
Preferably, in step 102, the obtaining the feasible route and the predicted vehicle passing data according to the driving demand information includes:
and step 1021, planning to obtain a feasible path according to the driving demand information.
This step can be implemented by existing map software or the like.
Step 1022, acquiring the traffic status information, matching the traffic status information to the corresponding feasible routes, and selecting a better feasible route from the feasible routes.
Optionally, the traffic status information includes: the road section traffic flow speed, the passing time, the intersection distance, the traffic light time, the weather condition, the time period and one or more of sudden accidents.
In the step 1022, the selecting a better feasible path from the feasible paths includes: and selecting the feasible path with the shortest transit time and/or the shortest jam time from the feasible paths as the better feasible path.
Illustratively, the obtained traffic state information is matched with the planned and obtained feasible paths, and whether the feasible paths have the problems of slow traffic speed of the traffic flow in the road section, sudden accidents, overlong waiting time of traffic lights and the like is judged, so that a better feasible path is selected from the feasible paths.
Preferably, if the preferred feasible path includes a desired pass-through path entered by the driver, the desired pass-through path may preferably be selected.
If the preferred feasible route does not include the expected passing route input by the driver, the driver can be reminded through voice and the like, the expected passing route is not the preferred feasible route at present, the preferred feasible route obtained through calculation is recommended to be modified, and whether the preferred feasible route is changed or not is selected through the operation of the driver.
At step 1023, vehicle estimated traffic data for the preferred feasible route is calculated.
After a preferred feasible route is obtained, the average speed of the vehicle predicted to pass and the time of the vehicle predicted to pass in the preferred feasible route can be calculated.
And 103, predicting to obtain the predicted running state of the vehicle based on the predicted passing data of the vehicle and the power parameters of the vehicle.
The step 103 of predicting and obtaining the predicted running state of the vehicle based on the predicted traffic data of the vehicle and the power parameter of the vehicle includes:
and calculating the running speed spectrum and the running power of the vehicle on a better feasible path based on the vehicle predicted traffic data and the vehicle power parameters, namely predicting to obtain the vehicle predicted running state.
In the implementation, the information obtained by the V2X can be compared with historical initial speed data on a preferred optional path to predict the running vehicle speed spectrum of the vehicle on the preferred feasible path, that is, the variation curve of the vehicle speed with time or distance, and further obtain the variation curve of the running power with time or distance.
And 104, controlling the power output of the fuel cell according to the predicted running state of the vehicle.
According to the running speed spectrum and the running power of the vehicle on a better feasible path, which are obtained by calculation, a basis can be provided for the power output of the fuel cell, and a change curve of the power output of the fuel cell along with time or distance is planned, so that the effectiveness of the power output of the fuel cell is further improved, and energy is saved.
Referring to fig. 2, fig. 2 is an exemplary block diagram of a fuel cell management system based on driving demand according to the present invention.
In a second aspect, based on the same inventive concept, the present invention provides a fuel cell management system based on a driving demand, comprising:
the information transceiving module S1 is used for receiving the driving demand information input by the driver;
the operation module S2 is used for obtaining the feasible path and the predicted passing data of the vehicle according to the running demand information; predicting to obtain the predicted running state of the vehicle based on the predicted passing data of the vehicle and the power parameters of the vehicle;
and a control module S3 for controlling the power output of the fuel cell based on the predicted driving state of the vehicle.
In particular implementation, the information transceiver module S1 may be an HMI.
Optionally, the driving demand information includes: a transport destination, and a desired arrival time and/or a desired transit path.
For example, the driver may input the transportation destination and the desired arrival time, or the transportation destination and the desired passing route, or the transportation destination, the desired arrival time, and the desired passing route through the HMI.
In specific implementation, the specific receiving mode of the HMI may be through a vehicle display screen, or through a terminal such as a mobile phone in communication connection with a vehicle center console.
In a specific implementation, the computing module S2 may be a computing platform communicatively connected to a console of a vehicle.
Optionally, the vehicle expected traffic data includes an average speed of vehicle expected traffic and an expected traffic time of the vehicle. The obtained vehicle predicted passing average speed and the vehicle predicted passing time can provide basis for obtaining the vehicle predicted running state in a prediction mode.
In a specific implementation, the operation module S2 may be configured to implement:
a. and planning to obtain a feasible path according to the driving demand information.
This step can be implemented by existing map software or the like.
b. And acquiring traffic state information, matching the traffic state information to corresponding feasible paths, and selecting a better feasible path from the feasible paths.
Optionally, the traffic status information includes: the road section traffic flow speed, the passing time, the intersection distance, the traffic light time, the weather condition, the time period and one or more of sudden accidents.
The selecting a better feasible path from the feasible paths includes: and selecting the feasible path with the shortest transit time and/or the shortest jam time from the feasible paths as the better feasible path.
Illustratively, the obtained traffic state information is matched with the planned and obtained feasible paths, and whether the feasible paths have the problems of slow traffic speed of the traffic flow in the road section, sudden accidents, overlong waiting time of traffic lights and the like is judged, so that a better feasible path is selected from the feasible paths.
For example, the shortest transit time and the shortest congestion time may occur in the same feasible route or different feasible routes, and if the shortest transit time and the shortest congestion time occur in different feasible routes, the shortest transit time and the shortest congestion time may be both used as a better feasible route, and may be pushed to the driver for self-selection.
Preferably, if the preferred feasible path includes a desired pass-through path entered by the driver, the desired pass-through path may preferably be selected.
If the preferred feasible route does not include the expected passing route input by the driver, the driver can be reminded through voice and the like, the expected passing route is not the preferred feasible route at present, the preferred feasible route obtained through calculation is recommended to be modified, and whether the preferred feasible route is changed or not is selected through the operation of the driver.
c. And calculating the vehicle predicted traffic data of the better feasible path.
After a preferred feasible route is obtained, the average speed of the vehicle predicted to pass and the time of the vehicle predicted to pass in the preferred feasible route can be calculated.
In a specific implementation, the operation module S2 may be further configured to implement:
and calculating the running speed spectrum and the running power of the vehicle on a better feasible path based on the vehicle predicted traffic data and the vehicle power parameters, namely predicting to obtain the vehicle predicted running state.
In the implementation, the information obtained by the V2X can be compared with historical initial speed data on a preferred optional path to predict the running vehicle speed spectrum of the vehicle on the preferred feasible path, that is, the variation curve of the vehicle speed with time or distance, and further obtain the variation curve of the running power with time or distance.
In particular implementations, the control module S3 may be a center console of a vehicle.
According to the running speed spectrum and the running power of the vehicle on a better feasible path, which are obtained by calculation, a basis can be provided for the power output of the fuel cell, and a change curve of the power output of the fuel cell along with time or distance is planned, so that the effectiveness of the power output of the fuel cell is further improved, and energy is saved.
In a third aspect, based on the same inventive concept, the present invention provides an apparatus comprising:
a memory for storing one or more programs;
a processor for executing the program stored in the memory to implement the fuel cell management method based on the driving demand as described.
The device may also preferably include a communication interface for communicating with external devices and for interactive transmission of data.
It should be noted that the memory may include a high-speed RAM memory, and may also include a nonvolatile memory (nonvolatile memory), such as at least one disk memory.
In a specific implementation, if the memory, the processor and the communication interface are integrated on a chip, the memory, the processor and the communication interface can complete mutual communication through the internal interface. If the memory, the processor and the communication interface are implemented independently, the memory, the processor and the communication interface may be connected to each other through a bus and perform communication with each other.
In a fourth aspect, based on the same inventive concept, the invention also provides a computer-readable storage medium storing at least one program, characterized in that when the program is executed by a processor, the fuel cell management method based on driving demand as described is implemented.
It should be appreciated that the computer-readable storage medium is any data storage device that can store data or programs which can thereafter be read by a computer system. Examples of the computer readable storage medium include read-only memory, random-access memory, CD-ROMs, HDDs, DVDs, magnetic tapes, optical data storage devices, and the like. The computer readable storage medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion.
Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, Radio Frequency (RF), etc., or any suitable combination of the foregoing.
In some embodiments, the computer-readable storage medium may be non-transitory.
Compared with the prior art, the method and the device have the advantages that the feasible path and the predicted vehicle running data are obtained according to the running demand information input by the driver, the predicted vehicle running state is obtained through prediction based on the predicted vehicle running data and the power parameters of the vehicle, the power output of the fuel cell is controlled according to the predicted vehicle running state, the analysis of the feasible path, the predicted vehicle running data and the predicted vehicle running state based on the running demand of the driver is realized, the basis is provided for the power output control of the fuel cell, the scientific effectiveness of the power control of the fuel cell is effectively improved, the optimal energy consumption effect is achieved, and the service lives of the fuel cell and the vehicle are prolonged.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention.
Claims (10)
1. A method for managing a fuel cell based on a driving demand, comprising:
receiving driving demand information input by a driver;
acquiring feasible paths and predicted vehicle passing data according to the driving demand information;
predicting to obtain a vehicle predicted running state based on vehicle predicted traffic data and vehicle power parameters;
the power output of the fuel cell is controlled in accordance with the predicted running state of the vehicle.
2. The travel demand-based fuel cell management method according to claim 1, wherein the travel demand information includes: a transport destination, and a desired arrival time and/or a desired transit path.
3. The running demand-based fuel cell management method according to claim 2, wherein the receiving of the running demand information input by the driver includes: and receiving driving demand information input by a driver through the HMI.
4. The driving demand-based fuel cell management method according to claim 2, wherein the vehicle expected traffic data includes a vehicle expected traffic average speed and a vehicle expected traffic time.
5. The method for managing a fuel cell according to claim 4, wherein the obtaining of the feasible route and the predicted traffic data of the vehicle according to the information of the driving demand comprises:
planning to obtain a feasible path according to the driving demand information;
acquiring traffic state information, matching the traffic state information to corresponding feasible paths, and selecting a better feasible path from the feasible paths;
and calculating the vehicle predicted traffic data of the better feasible path.
6. The driving demand-based fuel cell management method according to claim 5, wherein the traffic state information includes: one or more of traffic flow speed, passing time, intersection distance, traffic light time, weather conditions, time intervals and sudden accidents on the road section;
the selecting a better feasible path from the feasible paths includes: and selecting the feasible path with the shortest transit time and/or the shortest jam time from the feasible paths as the better feasible path.
7. The fuel cell management method based on travel demand according to claim 6, wherein the predicting to obtain the vehicle predicted travel state based on the vehicle predicted traffic data and the vehicle own power parameter includes:
and calculating the running speed spectrum and the running power of the vehicle on a better feasible path based on the vehicle predicted traffic data and the vehicle power parameters, namely predicting to obtain the vehicle predicted running state.
8. A fuel cell management system based on travel demand, comprising:
the information transceiving module is used for receiving driving demand information input by a driver;
the operation module is used for obtaining a feasible path and predicted vehicle passing data according to the driving demand information; predicting to obtain the predicted running state of the vehicle based on the predicted passing data of the vehicle and the power parameters of the vehicle;
and the control module is used for controlling the power output of the fuel cell according to the predicted running state of the vehicle.
9. An apparatus, comprising:
a memory for storing one or more programs;
a processor for executing the program stored in the memory to implement the fuel cell management method based on travel demand according to any one of claims 1 to 7.
10. A computer-readable storage medium storing at least one program, characterized in that when the program is executed by a processor, it implements the fuel cell management method based on travel needs according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111332965.7A CN113859053A (en) | 2021-11-11 | 2021-11-11 | Fuel cell management method, system, device, and medium based on travel demand |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111332965.7A CN113859053A (en) | 2021-11-11 | 2021-11-11 | Fuel cell management method, system, device, and medium based on travel demand |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113859053A true CN113859053A (en) | 2021-12-31 |
Family
ID=78987769
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111332965.7A Pending CN113859053A (en) | 2021-11-11 | 2021-11-11 | Fuel cell management method, system, device, and medium based on travel demand |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113859053A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114475366A (en) * | 2022-03-18 | 2022-05-13 | 湖南精准信息科技有限公司 | Fuel cell automobile energy-saving driving method and system based on convex optimization |
| WO2024124609A1 (en) * | 2022-12-12 | 2024-06-20 | 北汽福田汽车股份有限公司 | Method and apparatus for increasing endurance mileage of vehicle, medium, and vehicle |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070112475A1 (en) * | 2005-11-17 | 2007-05-17 | Motility Systems, Inc. | Power management systems and devices |
| CN102509470A (en) * | 2011-10-14 | 2012-06-20 | 北京掌城科技有限公司 | System and method for realizing energy conservation and emission reduction of vehicle based on dynamic path planning |
| CN107782327A (en) * | 2016-08-25 | 2018-03-09 | 通用汽车环球科技运作有限责任公司 | The vehicle routing problem of energetic optimum |
| CN109960255A (en) * | 2017-12-26 | 2019-07-02 | 郑州宇通客车股份有限公司 | A kind of control method and device of optimal objective speed prediction, fuel cell system |
| CN112185147A (en) * | 2020-10-14 | 2021-01-05 | 安徽江淮汽车集团股份有限公司 | Vehicle driving process optimization method, device, equipment and storage medium |
| CN112959922A (en) * | 2021-02-05 | 2021-06-15 | 浙江吉利控股集团有限公司 | Control method, control device and computer storage medium |
| CN113085666A (en) * | 2021-05-18 | 2021-07-09 | 北京理工大学 | Energy-saving driving method for layered fuel cell automobile |
-
2021
- 2021-11-11 CN CN202111332965.7A patent/CN113859053A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070112475A1 (en) * | 2005-11-17 | 2007-05-17 | Motility Systems, Inc. | Power management systems and devices |
| CN102509470A (en) * | 2011-10-14 | 2012-06-20 | 北京掌城科技有限公司 | System and method for realizing energy conservation and emission reduction of vehicle based on dynamic path planning |
| CN107782327A (en) * | 2016-08-25 | 2018-03-09 | 通用汽车环球科技运作有限责任公司 | The vehicle routing problem of energetic optimum |
| CN109960255A (en) * | 2017-12-26 | 2019-07-02 | 郑州宇通客车股份有限公司 | A kind of control method and device of optimal objective speed prediction, fuel cell system |
| CN112185147A (en) * | 2020-10-14 | 2021-01-05 | 安徽江淮汽车集团股份有限公司 | Vehicle driving process optimization method, device, equipment and storage medium |
| CN112959922A (en) * | 2021-02-05 | 2021-06-15 | 浙江吉利控股集团有限公司 | Control method, control device and computer storage medium |
| CN113085666A (en) * | 2021-05-18 | 2021-07-09 | 北京理工大学 | Energy-saving driving method for layered fuel cell automobile |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114475366A (en) * | 2022-03-18 | 2022-05-13 | 湖南精准信息科技有限公司 | Fuel cell automobile energy-saving driving method and system based on convex optimization |
| WO2024124609A1 (en) * | 2022-12-12 | 2024-06-20 | 北汽福田汽车股份有限公司 | Method and apparatus for increasing endurance mileage of vehicle, medium, and vehicle |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9604633B2 (en) | Travel support device, travel support method, and drive support system | |
| CN101916509B (en) | User self-help real-time traffic condition sharing method | |
| CN110187901A (en) | The dynamic optimization based on cloud that vehicle software updates | |
| CN102916462B (en) | Batter-charghing system and method | |
| KR101560957B1 (en) | Charger arrangement planning supporting apparatus, charger arrangement planning supporting method, and program | |
| US20180098227A1 (en) | Moving Mobile Wireless Vehicle Network Infrastructure System and Method | |
| CN113859053A (en) | Fuel cell management method, system, device, and medium based on travel demand | |
| US11987270B2 (en) | Vehicle dispatch management device and vehicle dispatch management method | |
| CN105424052A (en) | Stochastic range | |
| EP3119112B1 (en) | Method and system for minimizing the required bandwidth for a cloud based unicast communication with a vehicle | |
| CN108592932A (en) | Unmanned vehicle scheduling method, system, equipment and storage medium | |
| CN105489001A (en) | Taxi scheduling optimization method and system | |
| KR101063656B1 (en) | Information providing system of charging station for electric vehicle | |
| CN105070044A (en) | Dynamic scheduling method for customized buses and car pooling based on passenger appointments | |
| US9222793B2 (en) | Communication-based navigation system | |
| CN104864881A (en) | Method and apparatus for providing a navigation route with recommended charging | |
| CN103218769A (en) | Taxi order allocation method | |
| EP4184120A1 (en) | Path determination method and apparatus, and device and medium | |
| EP3091758B1 (en) | Low latency method and system for sending cloud data to a vehicle | |
| US10154419B2 (en) | Control of data connections and/or data transmissions in a mobile radio device | |
| US10801848B2 (en) | Crowd sourcing to predict vehicle energy consumption | |
| CN103884344A (en) | Intelligent navigation method and system based on mass vehicle data | |
| CN107845255A (en) | A kind of trick car system of pilotless automobile with route | |
| CN108827332A (en) | Combination of paths planing method, system, equipment and the storage medium driven with subway | |
| CN103175533A (en) | Method and apparatus for vehicle routing |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20211231 |
|
| RJ01 | Rejection of invention patent application after publication |