CN105966390A - New energy vehicle based on cloud computing route planning - Google Patents
New energy vehicle based on cloud computing route planning Download PDFInfo
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- CN105966390A CN105966390A CN201610477443.9A CN201610477443A CN105966390A CN 105966390 A CN105966390 A CN 105966390A CN 201610477443 A CN201610477443 A CN 201610477443A CN 105966390 A CN105966390 A CN 105966390A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W20/00—Control systems specially adapted for hybrid vehicles
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
- B60W10/06—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
- B60W10/08—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/18—Conjoint control of vehicle sub-units of different type or different function including control of braking systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2530/00—Input parameters relating to vehicle conditions or values, not covered by groups B60W2510/00 or B60W2520/00
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2556/00—Input parameters relating to data
- B60W2556/45—External transmission of data to or from the vehicle
- B60W2556/50—External transmission of data to or from the vehicle of positioning data, e.g. GPS [Global Positioning System] data
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2720/00—Output or target parameters relating to overall vehicle dynamics
- B60W2720/10—Longitudinal speed
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- 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
- Y02T10/62—Hybrid vehicles
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Abstract
The invention discloses a new energy vehicle based on cloud computing route planning. A vehicle body is a gasoline-electric hybrid vehicle and comprises an instrument panel data monitoring module, a streetscape data acquisition module, a GPS positioning module, a terminal node module, a server cluster module and a steering and braking module, wherein the server cluster module contains a self-adaption objective function optimization genetic algorithm embedded in a server cluster processor. According to the self-adaption objective function optimization genetic algorithm, effective input data, except oil consumption data, uploaded from all terminal nodes are input; the effective data are serial 16-bit time data, 48-bit character data and 16-bit longitude and latitude positioning data, and the optimization objective of the self-adaption objective function optimization genetic algorithm is the minimum oil consumption; when the vehicle runs, steering, speed change and power switching of the vehicle body are controlled in real time by the terminal node module, energy consumption of the vehicle is greatly improved, the energy utilization rate is increased, and the new energy vehicle has higher economic benefits and also can produce higher environmental benefits.
Description
Technical field
The present invention relates to automotive automation field, particularly to a kind of new forms of energy car based on cloud computing path planning.
Background technology
In the face of diversified running environment, use computer technology to automobile self information and the excavation of external environmental information, the problems referred to above will be made to be readily solved.And the introducing of cloud computing, accuracy and the efficiency of calculating will be greatly improved.Cloud computing is a multi-field cross discipline, relates to the multi-door subjects such as theory of probability, statistics, game theory, algorithm complex theory.Cloud computing is parallel computation (Parallel Computing), Distributed Calculation (Distributed Computing) and the development of grid computing (Grid Computing), or perhaps the business of these computer science concepts realizes.Field of cloud calculation has emerged a large amount of new technology, and they become cloud computing collection, the powerful mean storing, process and presenting.Cloud computing is the concept mixing evolution such as virtualization (Virtualization), public calculating (Utility Computing), IaaS (infrastructure i.e. services), PaaS (platform i.e. services), SaaS (software i.e. services) the result risen to.Cloud computing processes key technology and generally comprises: cloud computing collection, cloud computing pretreatment, cloud computing storage and management, cloud computing analysis and excavation, cloud computing represent and apply (cloud computing retrieval, cloud computing visualization, cloud computing application, cloud computing safely etc.).And the most emerging and increasingly mature support vector machine is with self-organized learning is theoretical and technology plays key player day by day in field of intelligent control.As the one in many cloud computing algorithms, genetic algorithm (Genetic Algorithm) is the computation model of the biological evolution process of the simulation natural selection of Darwinian evolutionism and genetic mechanisms, is a kind of method by simulating natural evolution process searches optimal solution.Genetic algorithm is that a population from the possible potential disaggregation of the problem that represents starts, and a population is then made up of the individuality of the some through gene code.Each individuality is actually the chromosome entity with feature.Chromosome is as the main carriers of hereditary material, the set of the most multiple genes, and its internal performance is certain assortment of genes, which determines the external presentation of the shape of individuality, if the feature of dark hair is to be determined by certain assortment of genes controlling this feature in chromosome.Therefore, need to realize the mapping i.e. coding work from Phenotype to genotype at the beginning.Owing to the work copying gene code is the most complicated, we often simplify, such as binary coding, after just producing for population, according to survival of the fittest and the principle of the survival of the fittest, develop by generation and produce the approximate solution become better and better, in every generation, select individuality according to fitness size individual in Problem Areas, and the genetic operator by means of natural genetics is combined intersecting and variation, produces the population representing new disaggregation.This process will cause rear life that kind of images of a group of characters natural evolution is the same to be adaptive to environment for population than former generation, and the optimum individual in last reign of a dynasty population, can be as problem approximate optimal solution through decoding.
Summary of the invention
In order to solve the technical problem that prior art exists, the present invention provides a kind of new forms of energy car based on cloud computing path planning.
A kind of new forms of energy car based on cloud computing path planning, car body is oil and electricity hybrid vehicle, also include instrumental panel data monitoring module, streetscape data acquisition module, GPS locating module, terminal node module, server farm module, turn to and brake module, embed server farm processor adaptive targets function optimization genetic algorithm module.
Described instrumental panel data monitoring module, including the detachable imageing sensor being positioned at above fuel consumption data instrumental panel, oil consumption image data buffer, oil consumption character recognition computer, fuel consumption data bluetooth transmitters.Described detachable imageing sensor connects oil consumption image data buffer by wired mode, described oil consumption image data buffer core is ARM core 32-bit microprocessor, described character recognition computer is connected by the way of parallel interface, described oil consumption character recognition computer is digital signal processor, the fuel consumption data bluetooth transmitters described in connection.
Streetscape data acquisition module, including two-way street view image sensor, street view image buffer, street view image character recognition computer, street view image character data bluetooth transmitters；Described streetscape two-way imageing sensor be positioned at roof respectively for car both sides, by wired mode connect described in street view image buffer, described street view image buffer kernel is ARM core 32-bit microprocessor, described street view image character recognition computer is connected by the way of parallel interface, described street view image character recognition computer is digital signal processor, street view image character data bluetooth transmitters for obtaining the character that 3 credibilitys in street view image are the highest, described in connection.
Described GPS locating module, positions data acquisition module including GPS, positions bluetooth data emitter；Described GPS location data module be positioned at above roof with described street view image sensor place same position at, described GPS location data module by ISO7816-10 agreement connect described in location bluetooth data emitter；Described location bluetooth data emitter is launched with described street view image data source data simultaneously.
Described terminal node module, including Bluetooth data reception device, Data Integration computer, solid state medium memorizer, Wifi module, is positioned in car；Described Bluetooth data reception device, described fuel consumption data bluetooth transmitters is come from for receiving, described street view image character data bluetooth transmitters and described location bluetooth data emitter send the data of coming, and connect Data Integration computer by wired mode；The core of described Data Integration computer is low-power consumption X86 core, built-in real time of day enumerator, described built-in real time of day enumerator is for the timing synchronization time data with real world, described Data Integration computer is by real time of day data, with corresponding fuel consumption data, the data of 3 characters of street view image, location data are converted to the form of file, by wired mode connect described in Wifi module and described solid state medium memorizer, described Wifi module for being uploaded to described server farm module by file data.
Described turns to and brake module, including steering controller, speed controller, powershift controller, Capacitor apart device, front and back steering spindle, power engine, brake device；Described steering controller, speed controller, powershift controller is simultaneously connected with described Data Integration computer respectively；Before and after described, steering spindle is by the steering controller described in described Capacitor apart device connection, described steering controller is controlled by described Data Integration computer, according to turning to of car body described in the route planning output control returned by described server farm module；Described power engine and described brake device are by the speed controller described in described Capacitor apart device connection, described speed controller is controlled by described Data Integration computer, and the real-time results that described steering controller obtains according to described Data Integration computer provide brake signal to braking maneuver device；Described powershift controller, is controlled by described Data Integration computer, drives or electric power drive pattern according to the route planning module returned by described server farm module and real-time fuel consumption data exchange fuel power.
Described server farm module comprises the adaptive targets function optimization genetic algorithm embedding server farm processor；Described adaptive targets function optimization genetic algorithm, input be transmit on all terminal nodes in addition to fuel consumption data, effectively input data；Described valid data are 16 time data of series connection, and 48 character datas and 16 longitude and latitude location data, the optimization aim of described adaptive targets function optimization genetic algorithm is that oil consumption is minimum；The object function of described adaptive targets function optimization genetic algorithm is drawn by row literary composition Burger-Ma Kuaertefa matching with known corresponding fuel consumption data by 16 time data connected, 48 character datas and 16 longitude and latitude location data；The genetic factor of described adaptive targets function optimization genetic algorithm is encoded to 16 time data of series connection, 48 character datas and the binary numeral of 16 longitude and latitude location data.
Accompanying drawing explanation
Fig. 1 is data acquisition module topological diagram of the present invention；
Fig. 2 is terminal node of the present invention and topology server figure；
Fig. 3 is terminal node of the present invention and turns to and brake module structure chart；
Fig. 4 is fuel consumption data acquisition algorithm of the present invention；
Fig. 5 is street view image character data acquisition algorithm of the present invention；
Fig. 6 is adaptive targets function optimization genetic algorithm.
Detailed description of the invention
The present invention is illustrated below in conjunction with embodiment and accompanying drawing.
For the technical scheme being illustrated more clearly that in the embodiment of the present invention, in describing embodiment below, the required accompanying drawing used is briefly described, apparently, accompanying drawing in describing below is only some embodiments of the present invention, for those of ordinary skill in the art, on the premise of not paying creative work, it is also possible to obtain other accompanying drawing according to these accompanying drawings.
A kind of new forms of energy car based on cloud computing path planning, car body is oil and electricity hybrid vehicle, including instrumental panel data monitoring module, streetscape data acquisition module, GPS locating module, terminal node module, server farm module, turn to and brake module, embed server farm processor adaptive targets function optimization genetic algorithm module.
Described instrumental panel data monitoring module, including the detachable imageing sensor being positioned at above fuel consumption data instrumental panel (101) as shown in Figure 1, oil consumption image data buffer (102) as shown in Figure 1, oil consumption character recognition computer (103) as shown in Figure 1, fuel consumption data bluetooth transmitters (104) as shown in Figure 1.Described detachable imageing sensor connects oil consumption image data buffer by wired mode, described oil consumption image data buffer core is ARM core 32-bit microprocessor, described character recognition computer is connected by the way of parallel interface, described oil consumption character recognition computer is digital signal processor, the fuel consumption data bluetooth transmitters described in connection.The acquisition algorithm of fuel consumption data is concrete as shown in Figure 4.
Streetscape data acquisition module, including two-way street view image sensor (201) as shown in Figure 1, street view image buffer (202) as shown in Figure 1, street view image character recognition computer (203) as shown in Figure 1, street view image character data bluetooth transmitters (204) as shown in Figure 1；Described streetscape two-way imageing sensor be positioned at roof respectively for car both sides, by wired mode connect described in street view image buffer, described street view image buffer kernel is ARM core 32-bit microprocessor, described street view image character recognition computer is connected by the way of parallel interface, described street view image character recognition computer is digital signal processor, street view image character data bluetooth transmitters for obtaining the character that 3 credibilitys in street view image are the highest, described in connection.The acquisition algorithm specific algorithm of streetscape data is as shown in Figure 5.
Described GPS locating module, including GPS location data acquisition module (301) as shown in Figure 1, location bluetooth data emitter (302) as shown in Figure 1；Described GPS location data module be positioned at above roof with described street view image sensor place same position at, described GPS location data module by ISO7816-10 agreement connect described in location bluetooth data emitter；Described location bluetooth data emitter is launched with described street view image data source data simultaneously.
Described terminal node module, including Bluetooth data reception device (401) as shown in Figure 2, Data Integration computer (402) as shown in Figure 2, solid state medium memorizer (403) as shown in Figure 2, Wifi module (404) as shown in Figure 2, is positioned in car；Described Bluetooth data reception device, described fuel consumption data bluetooth transmitters is come from for receiving, described street view image character data bluetooth transmitters and described location bluetooth data emitter send the data of coming, and connect Data Integration computer by wired mode；The core of described Data Integration computer is low-power consumption X86 core, built-in real time of day enumerator, described built-in real time of day enumerator is for the timing synchronization time data with real world, described Data Integration computer is by real time of day data, with corresponding fuel consumption data, the data of 3 characters of street view image, location data are converted to the form of file, by wired mode connect described in Wifi module and described solid state medium memorizer, described Wifi module for being uploaded to described server farm module by file data.
Described turns to and brake module, including steering controller (601) as shown in Figure 2, speed controller (602) as shown in Figure 2, powershift controller (603) as shown in Figure 2, Capacitor apart device (606) (607) as shown in Figure 2, steering spindle (604) (605) as shown in Figure 2 front and back, power engine (608) as shown in Figure 2, brake device (609) as shown in Figure 2；Described steering controller, speed controller, powershift controller is simultaneously connected with described Data Integration computer respectively；Before and after described, steering spindle is by the steering controller described in described Capacitor apart device connection, described steering controller is controlled by described Data Integration computer, according to turning to of car body described in the route planning output control returned by described server farm module；Described power engine and described brake device are by the speed controller described in described Capacitor apart device connection, described speed controller is controlled by described Data Integration computer, and the real-time results that described steering controller obtains according to described Data Integration computer provide brake signal to braking maneuver device；Described powershift controller, is controlled by described Data Integration computer, drives or electric power drive pattern according to the route planning module returned by described server farm module and real-time fuel consumption data exchange fuel power；When car in motion, described Data Integration computer detects when fuel consumption data is higher, sends a signal to described powershift controller, by described powershift controller, power source switches to electric power pattern；When car in motion, described Data Integration computer detects when fuel consumption data is relatively low, sends a signal to described powershift controller, by described powershift controller, power source switches to fuel power pattern.Described turns to the structure chart with brake module and described terminal node module as shown in Figure 3.
Described server farm module comprises the adaptive targets function optimization genetic algorithm embedding server farm processor (501) as shown in Figure 2；Described adaptive targets function optimization genetic algorithm, input be transmit on all terminal nodes in addition to fuel consumption data, effectively input data；Described valid data are 16 time data of series connection, and 48 character datas and 16 longitude and latitude location data, the optimization aim of described adaptive targets function optimization genetic algorithm is that oil consumption is minimum；The object function of described adaptive targets function optimization genetic algorithm is drawn by row literary composition Burger-Ma Kuaertefa matching with known corresponding fuel consumption data by 16 time data connected, 48 character datas and 16 longitude and latitude location data；The genetic factor of described adaptive targets function optimization genetic algorithm is encoded to 16 time data of series connection, 48 character datas and the binary numeral of 16 longitude and latitude location data.Specific algorithm is as shown in Figure 6.
Claims (8)
1. a new forms of energy car based on cloud computing path planning, car body is oil and electricity hybrid vehicle, including instrumental panel data monitoring module, streetscape data acquisition module, GPS locating module, terminal node module, server farm module, turn to and brake module, embed server farm processor adaptive targets function optimization genetic algorithm module.
2. the instrumental panel data monitoring module described in, including the detachable imageing sensor being positioned at above fuel consumption data instrumental panel, oil consumption image data buffer, oil consumption character recognition computer, fuel consumption data bluetooth transmitters.
3. the detachable imageing sensor described in connects oil consumption image data buffer by wired mode, described oil consumption image data buffer core is ARM core 32-bit microprocessor, described character recognition computer is connected by the way of parallel interface, described oil consumption character recognition computer is digital signal processor, the fuel consumption data bluetooth transmitters described in connection.
4. streetscape data acquisition module, including two-way street view image sensor, street view image buffer, street view image character recognition computer, street view image character data bluetooth transmitters；Described streetscape two-way imageing sensor be positioned at roof respectively for car both sides, by wired mode connect described in street view image buffer, described street view image buffer kernel is ARM core 32-bit microprocessor, described street view image character recognition computer is connected by the way of parallel interface, described street view image character recognition computer is digital signal processor, street view image character data bluetooth transmitters for obtaining the character that 3 credibilitys in street view image are the highest, described in connection.
5. the GPS locating module described in, positions data acquisition module including GPS, positions bluetooth data emitter；Described GPS location data module be positioned at above roof with described street view image sensor place same position at, described GPS location data module by ISO7816-10 agreement connect described in location bluetooth data emitter；Described location bluetooth data emitter is launched with described street view image data source data simultaneously.
6. the terminal node module described in, including Bluetooth data reception device, Data Integration computer, solid state medium memorizer, Wifi module, is positioned in car；Described Bluetooth data reception device, described fuel consumption data bluetooth transmitters is come from for receiving, described street view image character data bluetooth transmitters and described location bluetooth data emitter send the data of coming, and connect Data Integration computer by wired mode；The core of described Data Integration computer is low-power consumption X86 core, built-in real time of day enumerator, described built-in real time of day enumerator is for the timing synchronization time data with real world, described Data Integration computer is by real time of day data, with corresponding fuel consumption data, the data of 3 characters of street view image, location data are converted to the form of file, by wired mode connect described in Wifi module and described solid state medium memorizer, described Wifi module for being uploaded to described server farm module by file data.
7. turning to and brake module described in, including steering controller, speed controller, powershift controller, Capacitor apart device, front and back steering spindle, power engine, brake device；Described steering controller, speed controller, powershift controller is simultaneously connected with described Data Integration computer respectively；Before and after described, steering spindle is by the steering controller described in described Capacitor apart device connection, described steering controller is controlled by described Data Integration computer, according to turning to of car body described in the route planning output control returned by described server farm module；Described power engine and described brake device are by the speed controller described in described Capacitor apart device connection, described speed controller is controlled by described Data Integration computer, and the real-time results that described steering controller obtains according to described Data Integration computer provide brake signal to braking maneuver device；Described powershift controller, is controlled by described Data Integration computer, drives or electric power drive pattern according to the route planning module returned by described server farm module and real-time fuel consumption data exchange fuel power.
8. the server farm module described in comprises the adaptive targets function optimization genetic algorithm embedding server farm processor；Described adaptive targets function optimization genetic algorithm, input be transmit on all terminal nodes in addition to fuel consumption data, effectively input data；Described valid data are 16 time data of series connection, and 48 character datas and 16 longitude and latitude location data, the optimization aim of described adaptive targets function optimization genetic algorithm is that oil consumption is minimum；The object function of described adaptive targets function optimization genetic algorithm is drawn by row literary composition Burger-Ma Kuaertefa matching with known corresponding fuel consumption data by 16 time data connected, 48 character datas and 16 longitude and latitude location data；The genetic factor of described adaptive targets function optimization genetic algorithm is encoded to 16 time data of series connection, 48 character datas and the binary numeral of 16 longitude and latitude location data.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103057393A (en) * | 2012-12-30 | 2013-04-24 | 徐工集团工程机械股份有限公司江苏徐州工程机械研究院 | Control strategy of fluid and power combination hybrid power system and method for optimizing control parameter |
| CN103324982A (en) * | 2013-06-07 | 2013-09-25 | 银江股份有限公司 | Path planning method based on genetic algorithm |
| CN104331746A (en) * | 2014-10-20 | 2015-02-04 | 江苏大学 | Separate-type dynamic path optimization system and method thereof |
| CN105046365A (en) * | 2015-07-29 | 2015-11-11 | 余意 | Method and device for route optimization of logistics delivery vehicle |
| US20160171366A1 (en) * | 2014-06-23 | 2016-06-16 | International Business Machines Corporation | Solving vehicle routing problems using evolutionary computing techniques |
-
2016
- 2016-06-28 CN CN201610477443.9A patent/CN105966390B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103057393A (en) * | 2012-12-30 | 2013-04-24 | 徐工集团工程机械股份有限公司江苏徐州工程机械研究院 | Control strategy of fluid and power combination hybrid power system and method for optimizing control parameter |
| CN103324982A (en) * | 2013-06-07 | 2013-09-25 | 银江股份有限公司 | Path planning method based on genetic algorithm |
| US20160171366A1 (en) * | 2014-06-23 | 2016-06-16 | International Business Machines Corporation | Solving vehicle routing problems using evolutionary computing techniques |
| CN104331746A (en) * | 2014-10-20 | 2015-02-04 | 江苏大学 | Separate-type dynamic path optimization system and method thereof |
| CN105046365A (en) * | 2015-07-29 | 2015-11-11 | 余意 | Method and device for route optimization of logistics delivery vehicle |
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| CN105966390B (en) | 2019-05-21 |
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