CN108776744A - Electric vehicle automatic identification running route planing method based on Computing - Google Patents
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Abstract
The invention belongs to electric vehicle engineering fields, disclose a kind of electric vehicle automatic identification running route planing method based on Computing, and the picture in monitoring camera is carried out target detection by the object detection unit integrated using photographing module；Vibration damping is carried out to electric automobile during traveling vehicle body using the partial derivative expression formula of the object function of construction；The running cost evaluation of estimate for calculating every circuit, the circuit for filtering out the minimum W values of running cost evaluation of estimate are optimal path；The traveling-position of positioning electric vehicle in real time.The present invention utilizes optimal method, designs optimal spring rate parameter and damperparameters so that electric car body effectiveness in vibration suppression reaches optimal state；Optimal path can be obtained by optimal path module simultaneously, greatly improve operational efficiency, bringing advantage to the user property promotes user experience.
Description
Technical field
The invention belongs to electric vehicle engineering field more particularly to a kind of electric vehicle automations based on Computing
Identify running route planing method.
Background technology
Currently, the prior art commonly used in the trade is such：
Electric vehicle refers to driving wheels travel using vehicle power supply as power with motor, meeting road traffic, security legislation
The vehicle of requirements.It is started using the electricity stored in the battery.Use 12 or 24 pieces of batteries sometimes when driving automobile,
Sometimes it then needs more.The composition of electric vehicle includes：It is the mechanical systems such as electric drive and control system, driving force transmission, complete
At the equipment etc. of assigned tasks.Electric drive and control system are the core of electric vehicle, and are different from I. C. engine steam
The maximum difference of vehicle.Electric drive and control system are by groups such as the speed-regulating control devices of drive motor, power supply and motor
At.Other devices of electric vehicle are substantially identical as internal-combustion engines vehicle.However, effectiveness in vibration suppression is inadequate in existing electric vehicle operation
It is ideal；Optimal path cannot be obtained simultaneously, operational efficiency is low.
Video Supervision Technique is ripe day by day at present, but to the demand of HD video, but still remain problems with：
1) high-resolution, the image quality of high quality need very large space to store video；
2) monitoring range is bigger, and monitoring way is more, be easy to cause the temporal confusion of video file；
3) for the correlation of similar event, do not accomplish effectively to be connected.
The key component that multi-channel video how is fast and accurately found in the HD video information of magnanimity, is one
Important topic,
Currently, the video image of monitoring camera acquisition is analyzed and identified on the basis of computer vision,
Realize the Detection and Extraction and tracking to suspicious object in DYNAMIC COMPLEX scene, and analysis is recognizable suspicious separated on this basis
The behavior of rule obtains the understanding to video image content, and obtained image information is analyzed and planned.
In conclusion problem of the existing technology is：
Effectiveness in vibration suppression is not ideal enough in existing electric vehicle operation；Optimal path cannot be obtained simultaneously, operational efficiency is low.
Existing shape similarity often with recognition methods have probability statistics algorithm, characteristic value least mean-square error and geometry
The Weighted Average Algorithm etc. of external appearance characteristic necessary condition.Although achieving certain efficiency, there is also some shortcomings：Algorithm
The matching of realization process and visual discrimination is not intuitive；Algorithm is complicated, causes data processing amount big, and operating cost is high；Algorithm
Evenness analysis causes the variation of important geometric properties in figure to the influence of overall similarity, and Stability and veracity is caused to be deposited
In certain deviation.
Invention content
In view of the problems of the existing technology, the electric vehicle automation based on Computing that the present invention provides a kind of
Identify running route planing method.
The invention is realized in this way a kind of electric vehicle automatic identification running route planning based on Computing
Method, including：
Picture in monitoring camera is carried out target detection by the object detection unit integrated using photographing module；Pass through mesh
Mark tracking cell tracks the realization of goal that detection obtains；To obtaining as a result, being divided target using target classification unit
Class, and based on the classification belonging to target, target is carried out abnormality detection by abnormality detection taxon, and it is different by what is detected
It is often included into corresponding anomaly classification；Database is established by Database Unit, set by abnormal attribute write-in database
In respective field, and create index；Travel is monitored；Field wherein in database is regarded including at least exception is affiliated
Frequency marking knowledge, abnormal generic；
Utilize the partial derivative expression formula w=6.5 of the object function of construction；B=K+i*w*C-w*w*M；F=
[110000]'；X=inv (B) * F；S=0.7*X (3)+0.3*X (4)；Provide four parameter k to be optimizedvf、cvf、kvrAnd cvr
Initial value, the value of calculating target function s is denoted as sa, enable：sa=abs (eval (s))；Electric automobile during traveling vehicle body is subtracted
It shakes；
The running cost evaluation of estimate W for calculating every circuit, the circuit for filtering out the minimum W values of running cost evaluation of estimate are
Optimal path；The traveling-position of positioning electric vehicle in real time；Wherein,
Display monitoring road video information.
Further, carrying out oscillation damping method to electric automobile during traveling vehicle body includes：
1) mass matrix M, the damping matrix C and stiffness matrix K of half vehicle model of electric vehicle are provided, it is specific as follows：
Wherein mtfAnd mtrIt is the quality of two front-wheels and two trailing wheels of electric vehicle, m respectivelycIt is electric car body matter
Amount, IcIt is rotary inertia of the electric car body for barycenter, mvfAnd mvrIt is the matter of front end battery pack and rear end battery group respectively
Amount；
Wherein csfAnd csrIt is the damper coefficient of the forward and backward suspension of electric vehicle, l respectivelyfAnd lrBefore being respectively electric vehicle
The horizontal distance of bridge, rear axle and barycenter, above four parameters are the preset parameter of electric vehicle, cvfIt is preceding end resistance to be optimized
The parameter of Buddhist nun's device, cvrIt is the parameter of rear end damper to be optimized；
Wherein ktfAnd ktrIt is the equivalent stiffness of the forward and backward tire of electric vehicle, k respectivelysfAnd ksrIt is electric vehicle respectively
Before,
The rigidity of rear suspension, kvfIt is the parameter of front springs to be optimized, kvrIt is the parameter of rear end spring to be optimized；
2) object function is constructed, partial derivative of the object function for four damping parameters to be optimized in step 1) is sought
Expression formula, specific instruction are as follows：
W=6.5；
B=K+i*w*C-w*w*M；
F=[110000] '；
X=inv (B) * F；
S=0.7*X (3)+0.3*X (4)；% object functions %；
s1=diff (s, kvf)；% object functions are for kvfPartial derivative %；
s2=diff (s, cvf)；% object functions are for cvfPartial derivative %；
s3=diff (s, kvr)；% object functions are for kvrPartial derivative %；
s4=diff (s, cvr)；% object functions are for cvrPartial derivative %；
Provide four parameter k to be optimized in step 1)vf、cvf、kvrAnd cvrInitial value, calculate object function s at this time
Value, is denoted as sa, specific instruction is：sa=abs (eval (s))；
4) the step-size in search h of iterative algorithm is provided, four variable k after iteration are calculatedvf、cvf、kvrAnd cvrValue, and count
The value for calculating object function s at this time, is denoted as sb, specific instruction is：kvf=kvf+abs(s1)*h；cvf=cvf+abs(s2)*h；kvr=
kvr+abs(s3)*h；cvr=cvr+abs(s4)*h；sb=abs (eval (s))；
5) compare saAnd sbThe size of value：If sa≥sb, then s is enableda=sb, return to step 4) and it continues cycling through；If sa<sb, terminate
It recycles, at this time k in step 4)vf、cvf、kvrAnd cvrValue be required spring and damper parameter.
Further, optimal path acquisition methods include：
First, be preset with a plurality of circuit between origin and destination, every circuit include the national highway that distance is S1,
The township highway for saving highway, the county road of S3, S4 of S2；
Then, the oil that vehicle travels in the national highway of every circuit, province's highway, county road, township highway is calculated separately
Consume evaluation index P1, P2, P3, P4 and Time evaluation index T1, T2, T3, T4；Wherein,
ρ is fuel density, and f is oil gas mixing ratio；
Finally, the running cost evaluation of estimate W for calculating every circuit filters out the minimum W values of running cost evaluation of estimate
Circuit is optimal path；Wherein,
Further, target following is carried out using polygonal profile similarity detection method；
The content of abnormality detection includes image interference, object identification, vehicle speed measurement, drive in the wrong direction warning, identification of crossing the border；Wherein scheme
As interference belonging to abnormal class be diagnostics classes, the affiliated abnormal class of object identification be identification class, and vehicle speed measurement, drive in the wrong direction warning,
It crosses the border and is identified as behavior class；
It is carried out abnormality detection using the method based on template matches.
Further, polygonal profile similarity detection method includes：Eliminate the strangeization part in figure；Establish two figures
Mathematical model establishes eigenmatrix corresponding with figure by the complete Vector Groups of description figure, calculates the angle on adjacent both sides；
Calculate the minimum distance between two figures；
The length of side of the mathematical model polygon of foundation and adjacent angle are by one vector S of construction counterclockwise1Indicate polygon：
S1=(l1,α1,l2, α2…lN-1,αN-1,lN,αN)；
S1There are mapping relations one by one with the polygon, indicates unrelated with corner initial order；
Complete Vector Groups have 2N vector S counterclockwise1、S2……S2N-1、S2NHave with polygon and reflects one by one
Relationship is penetrated, a complete Vector Groups of the polygon are constituted, is indicated as follows：
S1=(l1,α1,l2, α2…lN-1,αN-1,lN,αN)；
S2=(α1,l2,α2…lN-1,αN-1,lN,αN,l1)；
……
S2N-1=(lN,αN,l1,α1,l2, α2…lN-1,αN-1)；
S2N=(αN,l1,α1,l2, α2…lN-1,αN-1,lN)；
With matrix SEIt indicates complete vector, and defines SEFor the eigenmatrix of the polygon, SEIt indicates as follows：
Another object of the present invention is to provide the electric vehicle automatic identification based on Computing described in a kind of realize
The computer program of running route planing method.
Another object of the present invention is to provide the electric vehicle automatic identification based on Computing described in a kind of realize
The information data processing terminal of running route planing method.
Another object of the present invention is to provide a kind of computer readable storage medium, including instruction, when its on computers
When operation so that computer executes the electric vehicle automatic identification running route planning side based on Computing
Method.
Another object of the present invention is to provide the electric vehicle automatic identification based on Computing described in a kind of realize
The electric vehicle automatic identification running route planning system based on Computing of running route planing method, including：
Power supply module is connect with single chip control module, for being powered to electric vehicle；
Photographing module is connect with single chip control module, is monitored to travel for passing through camera；
Single chip control module, with power supply module, photographing module, Damping modules, optimal path module, locating module, aobvious
Show that module connects, for controlling modules normal work；
Damping modules are connect with single chip control module, for carrying out vibration damping to electric automobile during traveling vehicle body；
Optimal path module, connect with single chip control module, the optimal path for determining traveling；
Locating module is connect with single chip control module, the traveling for positioning electric vehicle in real time by positioning chip
Position；
Display module is connect with single chip control module, is used for display monitoring road video information.
Another object of the present invention is to provide a kind of electric vehicle automation knowledge equipped with described based on Computing
The information data processing terminal of other running route planning system.
Advantages of the present invention and good effect are：
The present invention utilizes dynamic vibration absorber thought by Damping modules, with spring and damper connecting electric automobile vehicle frame and
Battery pack take tuning quality as electric car body vibration damping of battery pack, before no excessively increase electric vehicle is improved quality
It puts, improves the effectiveness in vibration suppression of vehicle body；Using optimal method, optimal spring rate parameter and damper ginseng are designed
Number so that electric car body effectiveness in vibration suppression reaches optimal state；It can be obtained by optimal path module simultaneously optimal
Path greatly improves operational efficiency, bringing advantage to the user property, promotes user experience.
The present invention claps video camera by using computer vision, image procossing, video analysis and the method for pattern-recognition
The video sequence taken the photograph carries out Automatic analysis, include to the interesting target in monitoring scene be detected extraction, label and
Tracking, finally to the analysis of operative action of target and judgement, analysis result is preserved, when video recording is thumbed in return visit, saves the time,
Improve efficiency.
Polygonal profile similarity detection method of the present invention includes：Eliminate the strangeization part in figure；Establish two figures
Mathematical model establishes eigenmatrix corresponding with figure by the complete Vector Groups of description figure, calculates the angle on adjacent both sides；
Calculate the minimum distance between two figures；Visual discrimination effect of the machine to shape similarity is improved, especially to being manually not easy point
Distinguish that the difficult point of high similarity figure has very great help；Test pattern effect has stronger stability and reliability；Detection time is short,
Operation is efficient, and implementation result is at low cost.The present invention only inquires the side of figure, reduces data processing amount.The present invention is logical
The eigenmatrix for crossing constructing graphic chooses suitable decision criteria, and it is non-linear to carry out multiple enhancement to eigenmatrix element
Transformation establishes Measurement of Similarity with the weighted average of most values, multi-standard, has reached algorithm efficiently and had stronger stabilization
Property.
Description of the drawings
Fig. 1 is that the present invention implements the electric vehicle automatic identification running route planning side based on Computing provided
Method flow chart.
Fig. 2 is the electric vehicle automatic identification running route planning system based on Computing that the present invention implements to provide
System structure diagram.
In figure：1, power supply module；2, photographing module；3, single chip control module；4, Damping modules；5, optimal path mould
Block；6, locating module；7, display module.
Fig. 3 is that the present invention implements the camera-shooting module structure schematic diagram provided.
Specific implementation mode
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
As shown in Figure 1, the electric vehicle automatic identification provided in an embodiment of the present invention based on Computing runs road
Line planing method, includes the following steps：
S101 is powered electric vehicle by power supply module；Travel is monitored by photographing module；
S102, single chip control module dispatch Damping modules and carry out vibration damping to electric automobile during traveling vehicle body；
S103 determines the optimal path of traveling by optimal path module；Electric vehicle is positioned in real time by locating module
Traveling-position；
S104 passes through display module display monitoring road video information.
As shown in Fig. 2, the electric vehicle automatic identification running route planning provided by the invention based on Computing
System includes：Power supply module 1, photographing module 2, single chip control module 3, Damping modules 4, optimal path module 5, locating module
6, display module 7.
Power supply module 1 is connect with single chip control module 3, for being powered to electric vehicle；
Photographing module 2 is connect with single chip control module 3, is monitored to travel for passing through camera；
Single chip control module 3, with power supply module 1, photographing module 2, Damping modules 4, optimal path module 5, positioning mould
Block 6, display module 7 connect, for controlling modules normal work；
Damping modules 4 are connect with single chip control module 3, for carrying out vibration damping to electric automobile during traveling vehicle body；
Optimal path module 5 is connect with single chip control module 3, the optimal path for determining traveling；
Locating module 6 is connect with single chip control module 3, the row for positioning electric vehicle in real time by positioning chip
Sail position；
Display module 7 is connect with single chip control module 3, is used for display monitoring road video information.
With reference to concrete analysis, the invention will be further described.
Electric vehicle automatic identification running route planing method provided in an embodiment of the present invention based on Computing,
Including：
Picture in monitoring camera is carried out target detection by the object detection unit integrated using photographing module；Pass through mesh
Mark tracking cell tracks the realization of goal that detection obtains；To obtaining as a result, being divided target using target classification unit
Class, and based on the classification belonging to target, target is carried out abnormality detection by abnormality detection taxon, and it is different by what is detected
It is often included into corresponding anomaly classification；Database is established by Database Unit, set by abnormal attribute write-in database
In respective field, and create index；Travel is monitored；Field wherein in database is regarded including at least exception is affiliated
Frequency marking knowledge, abnormal generic；The integrated structure such as Fig. 3 of photographing module.
Utilize the partial derivative expression formula w=6.5 of the object function of construction；B=K+i*w*C-w*w*M；F=
[110000]'；X=inv (B) * F；S=0.7*X (3)+0.3*X (4)；Provide four parameter k to be optimizedvf、cvf、kvrAnd cvr
Initial value, the value of calculating target function s is denoted as sa, enable：sa=abs (eval (s))；Electric automobile during traveling vehicle body is subtracted
It shakes；
The running cost evaluation of estimate W for calculating every circuit, the circuit for filtering out the minimum W values of running cost evaluation of estimate are
Optimal path；The traveling-position of positioning electric vehicle in real time；Wherein,
Display monitoring road video information.
Carrying out oscillation damping method to electric automobile during traveling vehicle body includes：
1) mass matrix M, the damping matrix C and stiffness matrix K of half vehicle model of electric vehicle are provided, it is specific as follows：
Wherein mtfAnd mtrIt is the quality of two front-wheels and two trailing wheels of electric vehicle, m respectivelycIt is electric car body matter
Amount, IcIt is rotary inertia of the electric car body for barycenter, mvfAnd mvrIt is the matter of front end battery pack and rear end battery group respectively
Amount；
Wherein csfAnd csrIt is the damper coefficient of the forward and backward suspension of electric vehicle, l respectivelyfAnd lrBefore being respectively electric vehicle
The horizontal distance of bridge, rear axle and barycenter, above four parameters are the preset parameter of electric vehicle, cvfIt is preceding end resistance to be optimized
The parameter of Buddhist nun's device, cvrIt is the parameter of rear end damper to be optimized；
Wherein ktfAnd ktrIt is the equivalent stiffness of the forward and backward tire of electric vehicle, k respectivelysfAnd ksrIt is electric vehicle respectively
Before,
The rigidity of rear suspension, kvfIt is the parameter of front springs to be optimized, kvrIt is the parameter of rear end spring to be optimized；
2) object function is constructed, partial derivative of the object function for four damping parameters to be optimized in step 1) is sought
Expression formula, specific instruction are as follows：
W=6.5；
B=K+i*w*C-w*w*M；
F=[110000] '；
X=inv (B) * F；
S=0.7*X (3)+0.3*X (4)；% object functions %；
s1=diff (s, kvf)；% object functions are for kvfPartial derivative %；
s2=diff (s, cvf)；% object functions are for cvfPartial derivative %；
s3=diff (s, kvr)；% object functions are for kvrPartial derivative %；
s4=diff (s, cvr)；% object functions are for cvrPartial derivative %；
Provide four parameter k to be optimized in step 1)vf、cvf、kvrAnd cvrInitial value, calculate object function s at this time
Value, is denoted as sa, specific instruction is：sa=abs (eval (s))；
4) the step-size in search h of iterative algorithm is provided, four variable k after iteration are calculatedvf、cvf、kvrAnd cvrValue, and count
The value for calculating object function s at this time, is denoted as sb, specific instruction is：kvf=kvf+abs(s1)*h；cvf=cvf+abs(s2)*h；kvr=
kvr+abs(s3)*h；cvr=cvr+abs(s4)*h；sb=abs (eval (s))；
5) compare saAnd sbThe size of value：If sa≥sb, then s is enableda=sb, return to step 4) and it continues cycling through；If sa<sb, terminate
It recycles, at this time k in step 4)vf、cvf、kvrAnd cvrValue be required spring and damper parameter.
Optimal path acquisition methods include：
First, be preset with a plurality of circuit between origin and destination, every circuit include the national highway that distance is S1,
The township highway for saving highway, the county road of S3, S4 of S2；
Then, the oil that vehicle travels in the national highway of every circuit, province's highway, county road, township highway is calculated separately
Consume evaluation index P1, P2, P3, P4 and Time evaluation index T1, T2, T3, T4；Wherein,
ρ is fuel density, and f is oil gas mixing ratio；
Finally, the running cost evaluation of estimate W for calculating every circuit filters out the minimum W values of running cost evaluation of estimate
Circuit is optimal path；Wherein,
Target following is carried out using polygonal profile similarity detection method；
The content of abnormality detection includes image interference, object identification, vehicle speed measurement, drive in the wrong direction warning, identification of crossing the border；Wherein scheme
As interference belonging to abnormal class be diagnostics classes, the affiliated abnormal class of object identification be identification class, and vehicle speed measurement, drive in the wrong direction warning,
It crosses the border and is identified as behavior class；
It is carried out abnormality detection using the method based on template matches.
Polygonal profile similarity detection method includes：Eliminate the strangeization part in figure；Establish the mathematical modulo of two figures
Type establishes eigenmatrix corresponding with figure by the complete Vector Groups of description figure, calculates the angle on adjacent both sides；Calculate two
Minimum distance between figure；
The length of side of the mathematical model polygon of foundation and adjacent angle are by one vector S of construction counterclockwise1Indicate polygon：
S1=(l1,α1,l2,α2…lN-1,αN-1,lN,αN)；
S1There are mapping relations one by one with the polygon, indicates unrelated with corner initial order；
Complete Vector Groups have 2N vector S counterclockwise1、S2……S2N-1、S2NHave with polygon and reflects one by one
Relationship is penetrated, a complete Vector Groups of the polygon are constituted, is indicated as follows：
S1=(l1,α1,l2, α2…lN-1,αN-1,lN,αN)；
S2=(α1,l2, α2…lN-1,αN-1,lN,αN,l1)；
……
S2N-1=(lN,αN,l1,α1,l2, α2…lN-1,αN-1)；
S2N=(αN,l1,α1,l2, α2…lN-1,αN-1,lN)；
With matrix SEIt indicates complete vector, and defines SEFor the eigenmatrix of the polygon, SEIt indicates as follows：
In the above-described embodiments, can come wholly or partly by software, hardware, firmware or its arbitrary combination real
It is existing.When using entirely or partly realizing in the form of a computer program product, the computer program product include one or
Multiple computer instructions.When loading on computers or executing the computer program instructions, entirely or partly generate according to
Flow described in the embodiment of the present invention or function.The computer can be all-purpose computer, special purpose computer, computer network
Network or other programmable devices.The computer instruction can store in a computer-readable storage medium, or from one
Computer readable storage medium is transmitted to another computer readable storage medium, for example, the computer instruction can be from one
A web-site, computer, server or data center pass through wired (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)
Or wireless (such as infrared, wireless, microwave etc.) mode is carried out to another web-site, computer, server or data center
Transmission).The computer read/write memory medium can be that any usable medium that computer can access either includes one
The data storage devices such as a or multiple usable mediums integrated server, data center.The usable medium can be magnetic Jie
Matter, (for example, floppy disk, hard disk, tape), optical medium (for example, DVD) or semiconductor medium (such as solid state disk Solid
State Disk (SSD)) etc..
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement etc., should all be included in the protection scope of the present invention made by within refreshing and principle.
Claims (10)
1. a kind of electric vehicle automatic identification running route planing method based on Computing, which is characterized in that described
Electric vehicle automatic identification running route planing method based on Computing includes：
Picture in monitoring camera is carried out target detection by the object detection unit integrated using photographing module；By target with
Track unit tracks the realization of goal that detection obtains；To obtaining as a result, classified to target using target classification unit, and
Based on the classification belonging to target, target is carried out abnormality detection by abnormality detection taxon, and the exception detected is returned
Enter in corresponding anomaly classification；Database is established by Database Unit, it will be corresponding set by abnormal attribute write-in database
In field, and create index；Travel is monitored；Field wherein in database includes at least abnormal affiliated video mark
Know, abnormal generic；
Utilize the partial derivative expression formula w=6.5 of the object function of construction；B=K+i*w*C-w*w*M；F=[110000] '；X
=inv (B) * F；S=0.7*X (3)+0.3*X (4)；Provide four parameter k to be optimizedvf、cvf、kvrAnd cvrInitial value, calculate
The value of object function s, is denoted as sa, enable：sa=abs (eval (s))；Vibration damping is carried out to electric automobile during traveling vehicle body；
The running cost evaluation of estimate W for calculating every circuit, the circuit for filtering out the minimum W values of running cost evaluation of estimate are optimal
Path；The traveling-position of positioning electric vehicle in real time；Wherein,
Display monitoring road video information.
2. the electric vehicle automatic identification running route planing method based on Computing as described in claim 1,
It is characterized in that, carrying out oscillation damping method to electric automobile during traveling vehicle body includes：
1) mass matrix M, the damping matrix C and stiffness matrix K of half vehicle model of electric vehicle are provided, it is specific as follows：
Wherein mtfAnd mtrIt is the quality of two front-wheels and two trailing wheels of electric vehicle, m respectivelycIt is electric car body quality, Ic
It is rotary inertia of the electric car body for barycenter, mvfAnd mvrIt is the quality of front end battery pack and rear end battery group respectively；
Wherein csfAnd csrIt is the damper coefficient of the forward and backward suspension of electric vehicle, l respectivelyfAnd lrBe respectively electric vehicle Qian Qiao, after
The horizontal distance of bridge and barycenter, above four parameters are the preset parameter of electric vehicle, cvfIt is front end damper to be optimized
Parameter, cvrIt is the parameter of rear end damper to be optimized；
Wherein ktfAnd ktrIt is the equivalent stiffness of the forward and backward tire of electric vehicle, k respectivelysfAnd ksrBefore being respectively electric vehicle,
The rigidity of rear suspension, kvfIt is the parameter of front springs to be optimized, kvrIt is the parameter of rear end spring to be optimized；
2) object function is constructed, object function is sought and the partial derivative of four damping parameters to be optimized in step 1) is expressed
Formula, specific instruction are as follows：
W=6.5；
B=K+i*w*C-w*w*M；
F=[110000] '；
X=inv (B) * F；
S=0.7*X (3)+0.3*X (4)；% object functions %；
s1=diff (s, kvf)；% object functions are for kvfPartial derivative %；
s2=diff (s, cvf)；% object functions are for cvfPartial derivative %；
s3=diff (s, kvr)；% object functions are for kvrPartial derivative %；
s4=diff (s, cvr)；% object functions are for cvrPartial derivative %；
Provide four parameter k to be optimized in step 1)vf、cvf、kvrAnd cvrInitial value, calculate the value of object function s at this time, note
For sa, specific instruction is：sa=abs (eval (s))；
4) the step-size in search h of iterative algorithm is provided, four variable k after iteration are calculatedvf、cvf、kvrAnd cvrValue, and calculate this
When object function s value, be denoted as sb, specific instruction is：kvf=kvf+abs(s1)*h；cvf=cvf+abs(s2)*h；kvr=kvr+
abs(s3)*h；cvr=cvr+abs(s4)*h；sb=abs (eval (s))；
5) compare saAnd sbThe size of value：If sa≥sb, then s is enableda=sb, return to step 4) and it continues cycling through；If sa<sb, terminate to follow
Ring, at this time k in step 4)vf、cvf、kvrAnd cvrValue be required spring and damper parameter.
3. the electric vehicle automatic identification running route planing method based on Computing as described in claim 1,
It is characterized in that, optimal path acquisition methods include：
First, a plurality of circuit is preset between origin and destination, every circuit includes national highway, the S2 that distance is S1
Save the township highway of highway, the county road of S3, S4；
Then, the oil consumption that vehicle travels in the national highway of every circuit, province's highway, county road, township highway is calculated separately to comment
Valence index P1, P2, P3, P4 and Time evaluation index T1, T2, T3, T4；Wherein,
ρ is fuel density, and f is oil gas mixing ratio；
Finally, the running cost evaluation of estimate W for calculating every circuit, filters out the circuit of the minimum W values of running cost evaluation of estimate
As optimal path；Wherein,
4. the electric vehicle automatic identification running route planing method based on Computing as described in claim 1,
It is characterized in that, target following is carried out using polygonal profile similarity detection method；
The content of abnormality detection includes image interference, object identification, vehicle speed measurement, drive in the wrong direction warning, identification of crossing the border；Wherein image is dry
Abnormal class belonging to disturbing is diagnostics classes, and the affiliated abnormal class of object identification is identification class, and vehicle speed measurement, warning of driving in the wrong direction, is crossed the border
It is identified as behavior class；
It is carried out abnormality detection using the method based on template matches.
5. the electric vehicle automatic identification running route planing method based on Computing as described in claim 1,
It is characterized in that,
Polygonal profile similarity detection method includes：Eliminate the strangeization part in figure；The mathematical model for establishing two figures, by
The complete Vector Groups for describing figure establish eigenmatrix corresponding with figure, calculate the angle on adjacent both sides；Calculate two figures
Between minimum distance；
The length of side of the mathematical model polygon of foundation and adjacent angle are by one vector S of construction counterclockwise1Indicate polygon：
S1=(l1,α1,l2, α2…lN-1,αN-1,lN,αN)；
S1There are mapping relations one by one with the polygon, indicates unrelated with corner initial order；
Complete Vector Groups have 2N vector S counterclockwise1、S2……S2N-1、S2NThere is mapping one by one to close with polygon
System constitutes a complete Vector Groups of the polygon, indicates as follows：
S1=(l1,α1,l2, α2…lN-1,αN-1,lN,αN)；
S2=(α1,l2, α2…lN-1,αN-1,lN,αN,l1)；
……
S2N-1=(lN,αN,l1,α1,l2, α2…lN-1,αN-1)；
S2N=(αN,l1,α1,l2, α2…lN-1,αN-1,lN)；
With matrix SEIt indicates complete vector, and defines SEFor the eigenmatrix of the polygon, SEIt indicates as follows：
6. a kind of realizing the electric vehicle automatic identification operation based on Computing described in Claims 1 to 5 any one
The computer program of route planning method.
7. a kind of realizing the electric vehicle automatic identification operation based on Computing described in Claims 1 to 5 any one
The information data processing terminal of route planning method.
8. a kind of computer readable storage medium, including instruction, when run on a computer so that computer is executed as weighed
Profit requires the electric vehicle automatic identification running route planing method based on Computing described in 1-5 any one.
9. a kind of realizing the electric vehicle automatic identification running route planing method based on Computing described in claim 1
The electric vehicle automatic identification running route planning system based on Computing, which is characterized in that it is described based on calculate
The electric vehicle automatic identification running route planning system of machine operation includes：
Power supply module is connect with single chip control module, for being powered to electric vehicle；
Photographing module is connect with single chip control module, is monitored to travel for passing through camera；
Single chip control module, with power supply module, photographing module, Damping modules, optimal path module, locating module, display mould
Block connects, for controlling modules normal work；
Damping modules are connect with single chip control module, for carrying out vibration damping to electric automobile during traveling vehicle body；
Optimal path module, connect with single chip control module, the optimal path for determining traveling；
Locating module is connect with single chip control module, the traveling-position for positioning electric vehicle in real time by positioning chip；
Display module is connect with single chip control module, is used for display monitoring road video information.
10. a kind of electric vehicle automatic identification running route planning equipped with based on Computing described in claim 9
The information data processing terminal of system.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110082120A (en) * | 2019-04-24 | 2019-08-02 | 一汽-大众汽车有限公司 | The route planning method and device of accelerated durability test |
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| CN110082120A (en) * | 2019-04-24 | 2019-08-02 | 一汽-大众汽车有限公司 | The route planning method and device of accelerated durability test |
| CN110082120B (en) * | 2019-04-24 | 2021-01-26 | 一汽-大众汽车有限公司 | Route planning method and device for accelerated durability test |
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