CN108422886B - Electric vehicle charging control device and control method based on route planning - Google Patents

Electric vehicle charging control device and control method based on route planning Download PDF

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CN108422886B
CN108422886B CN201810375576.4A CN201810375576A CN108422886B CN 108422886 B CN108422886 B CN 108422886B CN 201810375576 A CN201810375576 A CN 201810375576A CN 108422886 B CN108422886 B CN 108422886B
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charging pile
charged
charging
electric
electric automobile
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CN108422886A (en
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闵海涛
宋琪
李成宏
于远彬
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Jilin University
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Jilin University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/30—Constructional details of charging stations
    • B60L53/31—Charging columns specially adapted for electric vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/70—Interactions with external data bases, e.g. traffic centres
    • B60L2240/72—Charging station selection relying on external data
    • 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
    • B60L2260/00—Operating Modes
    • B60L2260/40—Control modes
    • B60L2260/50—Control modes by future state prediction
    • B60L2260/52—Control modes by future state prediction drive range estimation, e.g. of estimation of available travel distance
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/12—Electric charging stations

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

The invention provides an electric vehicle charging control device and a control method based on route planning, wherein the device comprises a charging pile monitoring module arranged on a charging pile and an electric vehicle module arranged on an electric vehicle, and the method comprises the following steps: the method comprises the steps of inputting whole vehicle parameters and battery pack parameters of an electric vehicle to be charged into a central control console; monitoring states of the charging pile and the parking space, and transmitting position and state information of the charging pile and the parking space to the electric automobile module; calculating the remaining driving mileage of the electric automobile; screening the charging piles according to the number of remaining driving ranges, the positions and the state information of the charging piles to obtain candidate charging piles, and planning paths of the final candidate charging piles; according to the invention, the charging pile of the electric automobile is monitored in real time, so that the problems of occupied charging parking spaces and the like are avoided, and the charging pile is ensured to be in an available state all the time; and providing a road for charging the electric automobile in time for a driver based on the route planning.

Description

Electric vehicle charging control device and control method based on route planning
Technical Field
The invention belongs to the field of electric automobiles, and relates to an electric automobile charging control device and method based on route planning
Background
With the continuous deepening of global energy crisis, petroleum resources are exhausted gradually, the hazards of atmospheric pollution and global temperature rise are aggravated, and an electric automobile is used as a new generation of transportation means, and has incomparable advantages compared with the traditional automobile in the aspects of energy conservation, emission reduction and human dependence on traditional fossil energy sources. Therefore, in the environment situation, people put out corresponding policies in various countries around the world, and development and application of electric automobiles are promoted.
At present, an electric automobile is in an demonstration popularization period, but because various types of storage batteries in the electric automobile have serious defects of high price, short service life, large external dimension and weight, long charging time and the like, the electric automobile often has the problems that the electric quantity of the battery is exhausted and cannot reach a destination or a charging place so as not to continue driving, namely, the driving range of the battery cannot meet the requirements of a driver to the greatest extent; meanwhile, at present, electric vehicle charging equipment (such as an electric vehicle charging station, a charging pile and the like) is not widely popularized, which also hinders popularization and use of electric vehicles.
Meanwhile, the charging of electric vehicles at present often faces such a problem: the electric automobile charges the parking stall and is taken up, and current device does not put forward effective solution to this kind of problem yet.
As described in patent No. 201510680905.2, a method, a device and a system for displaying driving range of an electric vehicle are disclosed, wherein the method, the device and the system are used for obtaining the maximum driving range parameter of the electric vehicle and determining factors influencing the driving range of the electric vehicle, calculating the remaining driving range parameter of the electric vehicle, and displaying the parameters influencing the driving range factors and the remaining driving range parameters of the electric vehicle. Only the calculation of the remaining range is performed, but no corresponding method measures are continuously proposed to solve the problem generated when the remaining range is insufficient.
Disclosure of Invention
The invention provides an electric vehicle charging control device and method based on route planning. The invention has the following purposes: 1. the electric vehicle charging pile is monitored in real time, so that the problems of occupied charging parking spaces and the like are avoided, and the charging pile is ensured to be in an available state all the time; 2. another important objective of the present invention is to provide a device and a method for controlling electric vehicle charging based on route planning, which provides a road for a driver to charge an electric vehicle in time based on route planning when the electric quantity is about to be exhausted, so as to reasonably solve the problem that the remaining driving range cannot enable the electric vehicle to reach the destination due to the about to be exhausted electric quantity of the battery, and finally achieve the purpose of prolonging the driving range of the electric vehicle.
The invention is realized by adopting the following technical scheme:
the invention provides an electric vehicle charging control device based on route planning, which is characterized by comprising a charging pile monitoring module and an electric vehicle module, wherein the electric vehicle module is arranged on an electric vehicle to be charged;
the utility model provides a fill electric pile monitoring module includes parking stall detection device and electric quantity detection device, wherein, parking stall detection device includes a wireless communication module, an infrared scanner, a voice broadcast ware, four pressure sensor, two obstacle pieces that have elevating gear, a time-recorder and a control circuit, infrared scanner and voice broadcast ware are integrated in an integrated box and install on the surface towards the parking stall at the fill electric pile, an obstacle piece and elevating gear establishes in the hole that is located underground at parking stall left boundary line middle part, another obstacle piece is established in the hole that is located underground at parking stall right boundary line middle part, two obstacle piece symmetrical arrangement and hole top all are equipped with automatic baffle, automatic baffle is by a small-size motor drive horizontal migration in order to open or close the hole that holds the obstacle piece, four pressure sensor establish respectively at four angles in the parking stall, two pressure sensor who sets up two angles that keep away from the fill electric pile at the parking stall are front pressure sensor, two pressure sensor who sets up two angles that are close to the fill electric pile at the parking stall are rear pressure sensor, one of them, but electric pile type of connection wireless communication device is connected with wireless communication device in wireless communication pile, but wireless communication device is connected with wireless communication device in the wireless communication pile, the wireless communication device is connected with the wireless communication device in the wireless communication pile, the wireless communication device of the wireless communication pile, the wireless communication device is connected with the wireless communication device.
The electric automobile module comprises a driving mileage statistics system, a vehicle-mounted navigator, a central control console and a small display, wherein the driving mileage statistics system comprises an electric quantity display device connected with a storage battery of the electric automobile to be charged and a speed sensor of the electric automobile to be charged; the small display comprises a display screen and a voice broadcasting device, and the electric quantity display device, the speed sensor, the display screen and the voice broadcasting device are all connected with a central control console of the electric automobile to be charged.
The invention also provides an electric vehicle charging control method based on route planning, which is characterized by comprising the following specific steps:
step one, inputting the whole vehicle parameters and the battery pack parameters of the electric vehicle to be charged into a central control console;
the charging pile monitoring module monitors the states of the charging pile and the parking space, and transmits the position and state information of the charging pile and the parking space to the electric automobile module;
step three, acquiring speed information of the running working condition of the electric vehicle to be charged by a driving mileage statistics system; establishing a fuzzy model between characteristic parameters of typical standard working conditions and energy consumption; substituting the speed information of the running working condition of the charged electric automobile into a fuzzy model between the characteristic parameters of the typical standard working condition and the energy consumption by the central control console to calculate the remaining continuous mileage of the electric automobile to be charged;
the central control console performs three-time screening on the charging piles according to the remaining driving mileage of the electric vehicle to be charged, the position and state information of the charging piles to obtain final candidate charging piles, and the vehicle-mounted navigator performs path planning on the final candidate charging piles;
wherein ,
the specific process of the step (II) is as follows:
when the front pressure sensor detects that the pressure is gradually increased and the pressure direction is from the outside of the parking space to the inside of the parking space, namely when a car starts to park, an infrared scanner is triggered, the infrared scanner scans the license plate of the car which is parked, and the scanned license plate is accessed into a vehicle type information database of the Internet through a wireless communication module to determine the type of the car which parks:
a. if the type of the automobile for parking is determined to be an electric automobile, the voice broadcasting device broadcasts that the parked automobile is the electric automobile, charging is requested, the parking is completed when the four pressure sensors detect that the pressure is not increased any more, the pressure sensors trigger the timer to start timing when the automobile just completes the parking, and the timer detects the parking time t of the automobile 1 In addition, a time threshold t is set 0 Taking t 0 =10 to 30s; if t 1 ＞t 0 When the electric quantity detection device in the charging pile monitoring module does not detect that the charging pile has corresponding charging action, an alarm is triggered, and the voice broadcasting device plays a voice warning to prohibit the occupied chargingElectric parking space ";
if the electric automobile is at time t 0 In-charging operation, the electric quantity detection device detects the electric quantity s of the electric automobile storage battery being charged in real time 1 When s is 1 When the vehicle is in 100 percent or the vehicle owner stops the charging work of the charging pile, the voice broadcasting device plays a voice prompt that the charged vehicle is timely away, the timer starts to count, and the timer starts to detect the parking time t of the vehicle after the charging is completed 2 If t 2 ＞t 0 When the automobile is still parked at the parking space, triggering an alarm, and carrying out voice warning on the fact that the automobile is prohibited to occupy the charging parking space by the voice broadcasting device;
after the automobile finishes the parking action, if the front pressure sensor and the rear pressure sensor do not detect the pressure change, the parking space is in a used state, and the use state value a=0 of the charging pile; if the front pressure sensor and the rear pressure sensor detect that the pressure value is zero, namely the automobile is driven out of the parking space, the service state value a=1 of the charging pile;
meanwhile, the charging pile monitoring module transmits a and s through the wireless communication device 1 The numerical value of (2) is sent to the electric automobile module;
b. if the type of the automobile for stopping is determined to be a traditional automobile, the control circuit controls the automatic partition board to open, controls the lifting mechanism of the obstacle block to drive the obstacle block to ascend, and simultaneously the voice broadcasting device carries out voice warning to prevent the traditional automobile from stopping into a parking space.
The specific process of the step (III) is as follows:
firstly, characteristic parameter information of each segment under typical standard working conditions is obtained: establishing a whole electric vehicle energy consumption model in MATLAB, wherein the input working conditions are 10 typical standard working conditions, each typical standard working condition is 1200s, each typical standard working condition is divided into 12 groups of segments in sequence, each typical standard working condition is operated, and each typical standard working condition segment is provided with four characteristic parameters: the average speed v, the uniform speed proportion P, the deceleration proportion R and the total energy consumption E can obtain 120 groups of data;
secondly, establishing a fuzzy model between characteristic parameters of typical standard working conditions and energy consumption:
constructing a vector x composed of N groups of L dimensions j A composed data set X, each L-dimensional vector X j Four characteristic parameters for each segment are included, where n=120, l=4, x= (x) 1 ,x 2 ,…,x j )j＝1,2,…,N
And extracting the trust degree of the data set X by adopting a fuzzy C clustering algorithm added with the trust degree, namely a BFCM algorithm.
Let u ij For fuzzy membership, i.e. x j The degree belonging to class i, c is the number of clustering classes, bel j For confidence of data in clustering process, namely x j Trust level, v i I=1, 2, …, c, d for class i cluster center ij ＝d(v i ,x j ) For data x j And a cluster center v i M is a flexibility coefficient, controlling the sharing degree between categories, and it is generally preferable to take m as 2.0, so that m=2.0 is taken.
Initializing: the number of the characteristic parameters is four, so the number of the categories is 4, the clustering category number c=4 is set, the iteration termination value epsilon and the maximum iteration number b are set max The method can be determined according to specific precision requirements;
initializing fuzzy membership u ij Make it satisfy u ij ∈(0,1)
Updating confidence bel j ：
Order the
Figure GDA0004159098840000041
Figure GDA0004159098840000042
Updating cluster center v i ；
Figure GDA0004159098840000043
in the formula ,
Figure GDA0004159098840000044
representing the updated cluster center.
According to the updated clustering center
Figure GDA0004159098840000045
Updating fuzzy membership u ij ：
(d ij ) 2 ＝(x j -v i (b) ) T A(x j -v i (b) )
Figure GDA0004159098840000051
in the formula ,
Figure GDA0004159098840000052
representing updated fuzzy membership, A is a unity symmetry matrix, d when k=i kj ＝d ij
If it is
Figure GDA0004159098840000053
Ending the iteration to obtain the confidence level bel j . Otherwise, let->
Figure GDA0004159098840000054
Re-updating confidence bel j 。
Extracting fuzzy rules by using a iWM method, and establishing a fuzzy model between characteristic parameters and energy consumption according to a fuzzy rule base:
first, a sample T with N pairs of N input single outputs is constructed, T= { (x' (p) ；y (p) ) P=1, 2, …, N, average speed for each typical standard condition segment
Figure GDA0004159098840000055
The constant speed proportion P and the deceleration proportion R are used as a group of sample input, and the total energy consumption E of each typical standard working condition segment is used as a sample output of the group.
Wherein, n=3,
Figure GDA0004159098840000056
representing the p-th group of input data, y (p) E R represents the output of group p, +.>
Figure GDA0004159098840000057
Represents the average speed of group p, respectively>
Figure GDA0004159098840000058
Constant speed ratio P, and deceleration ratio R.
Dividing the interval of the input variable into d q A fuzzy subset, wherein q is the fuzzy rule number, dividing the value range of the output variable into d 0 A fuzzy subset, A and B are respectively expressed as input variable x' (p) And output variable y (p) Is a fuzzy set of (a) and (b).
And calculating a membership value by adopting a Gaussian function as a membership function:
Figure GDA0004159098840000059
Figure GDA00041590988400000510
wherein ,μA (x′ (p)) and μB (y (p) ) The membership function values of the input value and the output value of the p-th group of sample data are respectively represented, and the values of b and sigma can be determined according to the needs.
Calculating the weight w multiplied by the membership degree of each group of sample data (p) ：
Figure GDA00041590988400000511
Creating a complete fuzzy rule base, wherein the specific description form is as follows:
if
Figure GDA0004159098840000061
is/>
Figure GDA0004159098840000062
is/>
Figure GDA0004159098840000063
and/>
Figure GDA0004159098840000064
is/>
Figure GDA0004159098840000065
then y (p) is
Figure GDA0004159098840000066
after the above fuzzy rule is established, the product operation and weighted average defuzzification are adopted to obtain the following fuzzy model y (x), and the sample trust degree bel obtained by BFCM algorithm is obtained j The trust degree as the fuzzy rule is substituted into the fuzzy model:
Figure GDA0004159098840000067
wherein ,
Figure GDA0004159098840000068
is the q-th rule in the fuzzy membership function mu B Points corresponding to (y) =1.
After the fuzzy model between the characteristic parameters and the energy consumption is established, a speed sensor in a driving mileage statistics system acquires speed information of a driving working condition in the driving process of the electric vehicle to be charged, the driving working condition is divided into a plurality of segments according to time average, and the characteristic parameters of each segment are obtained: average speed of
Figure GDA0004159098840000069
The characteristic parameters are controlled by the central control console according to the speed of the electric automobile transmitted by the speed sensor at a constant speed ratio P' and a deceleration ratio NAcceleration information is obtained, average speed +.>
Figure GDA00041590988400000610
The constant speed ratio P 'and the deceleration ratio N' are input into a fuzzy model, so that the energy consumption of each segment can be obtained;
the central control console further calculates the remaining driving range of the electric automobile through the following calculation process:
E cost ＝∑E′
E rest ＝E total -E cost
Figure GDA00041590988400000611
S rest ＝lE rest
wherein E' is the energy consumption of each segment of the running working condition of the electric automobile to be charged; e (E) cost The total energy consumption of the electric automobile to be charged is; e (E) total The total energy of the electric automobile to be charged is obtained by parameters of the electric automobile to be charged; e (E) rest The remaining energy of the electric automobile to be charged; s is S cost The mileage of the electric vehicle to be charged is obtained by an odometer of the electric vehicle to be charged; l is the mileage of unit energy consumption; s is S rest Is the remaining driving mileage;
according to the obtained remaining mileage of the electric vehicle, the central control console uses the remaining mileage S of the electric vehicle rest Distance from remaining travel S need Comparing the sizes, if S rest -S need ＞S y The small display displays the remaining driving mileage of the electric automobile and the voice prompt that the electric automobile can successfully reach the target place; if S rest -S need ≤S y Starting a route planning system and prompting 'insufficient remaining driving range' by voice;
wherein ,Sy For mileage threshold, take S y ＝1～2km。
The specific process of the step (IV) is as follows:
through waiting for fillingThe wireless communication module in the electric automobile is connected with the wireless communication module of the charging piles to obtain the position information of each charging pile, and the remaining driving mileage S of the electric automobile to be charged is reserved by taking the current position of the electric automobile to be charged as the circle center rest Taking all charging piles within the radius range as primary candidate charging piles, and reserving position information of the primary candidate charging piles;
then planning an optimal driving path from the current position of the electric vehicle to be charged to each candidate charging pile by using a vehicle-mounted navigator, and keeping the optimal driving path course smaller than the residual continuous mileage S of the electric vehicle to be charged res t, taking the candidate charging pile as a secondary candidate charging pile, and reserving position information of the secondary candidate charging pile;
finally, the using state value a of the secondary candidate charging pile is read, the secondary candidate charging pile with a=0 is removed, the secondary candidate charging pile with a=1 is reserved as a final candidate charging pile, finally, the optimal driving path of each final candidate charging pile planned by the vehicle navigator is displayed on a display screen of a small display, and the electric quantity s of the corresponding electric vehicle storage battery which is being charged is marked beside each final candidate charging pile 1 。
Compared with the prior art, the invention has the beneficial effects that:
1. the charging pile monitoring module is arranged, so that the working state of the charging pile can be monitored in real time, the charging pile can be guaranteed to be in an available state all the time, the problem that a charging parking space is occupied is solved, and the charging pile position information and the available information are transmitted to the electric automobile module through the wireless communication device, so that a correct and feasible charging road is conveniently planned by the route planning system;
2. according to the invention, the charging pile monitoring module is connected with the electric automobile module through the wireless communication device, so that the information intercommunication between the charging pile and the electric automobile is realized, and the feasibility and the practicability of route planning are improved;
3. according to the invention, the infrared scanner and the obstacle speed are arranged in the charging pile monitoring module, so that the type of parked vehicles can be judged, the parking of the traditional vehicles is prevented when the vehicles are not parked in the parking space, the social phenomenon that the parking spaces of the charging piles are occupied can be effectively avoided, the effect which cannot be achieved by other control devices is achieved, the charging piles with insufficient quantity can be effectively utilized, and the resource waste is avoided;
4. the invention adopts the fuzzy control algorithm combining the BFCM algorithm and the iWM algorithm to construct the fuzzy model, calculates the remaining driving range of the electric automobile, is more accurate and reliable than the existing calculation method, and carries out preliminary judgment on the remaining driving range at the moment, namely judges whether the remaining driving range at the moment can enable the electric automobile to safely reach the destination, can help a driver to accurately judge the driving condition of the electric automobile at the moment, is convenient and trouble-free, and is an innovation point;
5. the invention provides a route planning and identifying system, which carries out corresponding route planning for a driver after the residual driving range is insufficient to reach a destination point, so as to obtain a convenient and quick route containing an electric vehicle charging station or a charging pile, so that an electric vehicle can charge in the residual driving range, and the problem of insufficient driving range of the electric vehicle is solved;
6. the route planning system performs three times of deleting on the charging piles, so that the unavailable charging piles and charging piles which cannot be reached by the residual driving mileage are removed, a good foundation is laid for final route planning, and the efficiency, accuracy and practicability of the route planning are improved;
7. the route planning system obtains the paths of the final candidate charging piles, marks the charging electric quantity of the electric vehicle which is being charged on each final candidate charging pile, can be used for a driver to carry out further screening according to the actual situation, realizes man-machine interaction, ensures that the route planning is more humanized and scientific, and avoids the defects caused by machine processing.
Drawings
The invention is further described below with reference to the accompanying drawings:
fig. 1 is a schematic structural diagram of an electric vehicle charging control device based on route planning according to the present invention;
fig. 2 is a schematic structural diagram of a charging pile monitoring module of the electric vehicle charging control device based on route planning according to the present invention;
fig. 3 is a flowchart of an electric vehicle charging control method based on route planning according to the present invention;
FIG. 4 schematic diagram of primary candidate charging pile
FIG. 5 schematic diagram of final candidate charging pile
In the figure: 1. charging pile, 2, integrated box, 3, rear pressure sensor, 4, parking stall, 5, obstacle piece, 6, front pressure sensor, 7, baffle, 8, the time-recorder, 9, infrared scanner, 10, voice broadcast ware.
Detailed Description
The invention is described in detail below with reference to the attached drawing figures:
the electric vehicle charging control device based on the route planning is characterized by comprising a charging pile monitoring module and an electric vehicle module, wherein the charging pile monitoring module is used for comprehensively judging the available state of a charging pile and carrying out corresponding warning; the electric automobile module is arranged on the electric automobile to be charged and is used for calculating the remaining driving range of the electric automobile to be charged and carrying out corresponding route planning. The device structure is schematically shown in fig. 1.
The charging pile monitoring module comprises a parking space detection device and an electric quantity detection device, wherein the parking space detection device and the electric quantity detection device are connected with a central control console through wireless communication for information transmission, the parking space detection device comprises an infrared scanner 9, a voice broadcasting device 10, four pressure sensors, two barrier blocks 5 with lifting devices, a timer 8 and a partition plate 7, the infrared scanner 9 and the voice broadcasting device 10 are integrated in an integrated box 2 and are arranged on the surface of a charging pile 1 facing a parking space 4, the infrared scanner 9 is used for judging the type of parked automobile, the voice broadcasting device 10 is used for prompting the charged electric automobile and the traditional automobile occupying the parking space to leave in time, the pressure sensors are used for detecting whether the automobile is parked at the charging parking space, one barrier block 5 and a lifting device thereof are arranged in a hole in the middle of the left boundary line of the parking space 4, the other barrier block 5 is arranged in a hole in the middle of the right boundary line of the parking space 4, the two barrier blocks 5 are symmetrically arranged and are respectively provided with an automatic partition 7 above the hole, the automatic partition 7 is driven by a small motor to horizontally move so as to open or close the hole for accommodating the barrier block 5, four pressure sensors are respectively arranged at four corners of the parking space 4, two pressure sensors arranged at two corners of the parking space 4 far away from the charging pile 1 are respectively a front pressure sensor 6, two pressure sensors arranged at two corners of the parking space 4 close to the charging pile 1 are respectively a rear pressure sensor 3, a timer 8 is connected with one of the rear pressure sensors 3, a wireless communication module can be connected with a wireless communication module in a central console of an electric automobile in a wireless communication manner, and also can be connected with a vehicle type information database of the Internet, the lifting mechanism of the pressure sensor, the infrared scanner 9, the voice broadcasting device 10, the wireless communication module, the small motor and the obstacle block 5 is connected with the control circuit, and the electric quantity detection device is arranged on the charging pile and used for detecting the charging state of the automobile at the moment. The electric quantity detection device is connected with a control circuit of the charging pile, and the control circuit of the charging pile stores position information of the charging pile.
The structure of the charging pile monitoring module is shown in fig. 2.
The electric automobile module comprises a driving mileage statistics system, a vehicle-mounted navigator, a central control console and a small display, wherein the driving mileage statistics system comprises an electric quantity display device connected with a storage battery of the electric automobile to be charged and a speed sensor of the electric automobile to be charged; the small display comprises a display screen and a voice broadcasting device, and the electric quantity display device, the speed sensor, the display screen and the voice broadcasting device are all connected with a central control console of the electric automobile to be charged.
The electric vehicle charging control method based on route planning is characterized by comprising the following specific steps:
the device flow is shown in fig. 3.
Step one, inputting the whole vehicle parameters and the battery pack parameters of the electric vehicle to be charged into a central control console;
the charging pile monitoring module monitors the states of the charging pile and the parking space, and transmits the position and state information of the charging pile and the parking space to the electric automobile module;
step three, acquiring speed information of the running working condition of the electric vehicle to be charged by a driving mileage statistics system; establishing a fuzzy model between characteristic parameters of typical standard working conditions and energy consumption; substituting the speed information of the running working condition of the charged electric automobile into a fuzzy model between the characteristic parameters of the typical standard working condition and the energy consumption by the central control console to calculate the remaining continuous mileage of the electric automobile to be charged;
the central control console performs three-time screening on the charging piles according to the remaining driving mileage of the electric vehicle to be charged, the position and state information of the charging piles to obtain final candidate charging piles, and the vehicle-mounted navigator performs path planning on the final candidate charging piles;
wherein ,
the specific process of the step (II) is as follows:
when the front pressure sensor 6 detects that the pressure is gradually increased and the pressure direction is from the outside of the parking space to the inside of the parking space, namely, when a car starts to park, the infrared scanner 9 is triggered, the infrared scanner 9 scans the license plate of the car which is parked, and the scanned license plate number is accessed to a vehicle type information database of the Internet through the wireless communication module to determine the type of the car which parks:
if the type of the automobile for parking is determined to be an electric automobile, the voice broadcasting device 10 broadcasts that the parked electric automobile is "please charge", the parking action is completed when the four pressure sensors detect that the pressure is no longer increased, the pressure sensors trigger the timer 8 to start timing when the automobile just completes the parking action, and the timer 8 detects the parking time t of the automobile 1 In addition, a time threshold t is set 0 General t 0 =10 to 30s; if t 1 ＞t 0 When the electric quantity detection device in the charging pile monitoring module does not detect that the charging pile has corresponding charging action, an alarm is triggered, and the voice broadcasting device 10 plays a voice warning 'prohibit occupying a charging parking space';
if the electric automobile is at time t 0 The charging operation is performed in the battery charger, and the electric quantity detection device detects that the battery charger is being charged in real timeElectric quantity s of electric automobile storage battery 1 When s is 1 When the vehicle owner stops the charging operation of the charging pile, the voice broadcasting device 10 plays a voice prompt of "the vehicle which has completed charging is timely away", the timer 8 starts to count, and the timer 8 starts to detect the vehicle parking time t after the completion of charging 2 If t 2 ＞t 0 When the automobile is still parked at the parking space, an alarm is triggered, and the voice broadcasting device 10 carries out voice warning on 'forbidden to occupy the charging parking space';
when the automobile finishes the parking action, if the front pressure sensor 6 and the rear pressure sensor 3 do not detect the pressure change, the parking space is in a used state, and the use state value a=0 of the charging pile; if the front pressure sensor 6 and the rear pressure sensor 3 detect that the pressure value is zero, namely the automobile is driven out of the parking space, the charging pile use state value a=1;
meanwhile, the charging pile monitoring module transmits a and s through the wireless communication device 1 The numerical value of (2) is sent to the electric automobile module;
b. if the type of the automobile for stopping is determined to be a traditional automobile, the control circuit controls the automatic partition 7 to open and controls the lifting mechanism of the obstacle block 5 to drive the obstacle block 5 to ascend, and meanwhile the voice broadcasting device 10 carries out voice warning to prevent the traditional automobile from stopping into a parking space.
The specific process of the step (III) is as follows:
firstly, characteristic parameter information of each segment under typical standard working conditions is obtained: establishing a whole electric vehicle energy consumption model in MATLAB, wherein the input working conditions are 10 typical standard working conditions, each typical standard working condition is 1200s, each typical standard working condition is divided into 12 groups of segments in sequence, each typical standard working condition is operated, and each typical standard working condition segment is provided with four characteristic parameters: average speed of
Figure GDA0004159098840000101
The constant speed proportion P, the deceleration proportion R and the total energy consumption E can obtain 120 groups of data;
secondly, establishing a fuzzy model between characteristic parameters of typical standard working conditions and energy consumption:
constructing a vector x composed of N groups of L dimensions j A composed data set X, each L-dimensional vector X j Four characteristic parameters for each segment are included, where n=120, l=4, x= (x) 1 ,x 2 ,…,x j )j＝1,2,…,N
The confidence level of the data set X is extracted by adopting a fuzzy C clustering algorithm added with the confidence level, namely a BFCM algorithm, the collected standard working condition data is processed by the BFCM algorithm, and the confidence level of the sample data is extracted in the clustering process, so that the assurance can be provided for obtaining a good fuzzy rule base.
Let u ij For fuzzy membership, i.e. x j The degree belonging to class i, c is the number of clustering classes, bel j For confidence of data in clustering process, namely x j Trust level, v i I=1, 2, …, c, d for class i cluster center ij ＝d(v i ,x j ) For data x j And a cluster center v i M is a flexibility coefficient, controlling the sharing degree between categories, and it is generally preferable to take m as 2.0, so that m=2.0 is taken.
Initializing: the number of the characteristic parameters is four, so the number of the categories is 4, the clustering category number c=4 is set, the iteration termination value epsilon and the maximum iteration number b are set max The method can be determined according to specific precision requirements;
initializing fuzzy membership u ij Make it satisfy u ij ∈(0,1)
Updating confidence bel j ：
Order the
Figure GDA0004159098840000111
Figure GDA0004159098840000112
Updating cluster center v i ；
Figure GDA0004159098840000113
in the formula ,
Figure GDA0004159098840000114
representing the updated cluster center.
According to the updated clustering center
Figure GDA0004159098840000115
Updating fuzzy membership u ij ：
(d ij ) 2 ＝(x j -v i (b) ) T A(x j -v i (b) )
Figure GDA0004159098840000116
in the formula ,
Figure GDA0004159098840000117
representing updated fuzzy membership, A is a unity symmetry matrix, d when k=i kj ＝d ij
If it is
Figure GDA0004159098840000118
Ending the iteration to obtain the confidence level bel j . Otherwise, let->
Figure GDA0004159098840000119
Re-updating confidence bel j 。
Extracting fuzzy rules by using a iWM method, and establishing a fuzzy model between characteristic parameters and energy consumption according to a fuzzy rule base:
first, a sample T with N pairs of N input single outputs is constructed, T= { (x' (p) ；y (p) ) P=1, 2, …, N, average speed for each typical standard condition segment
Figure GDA0004159098840000121
The constant speed ratio P and the deceleration ratio R are taken as a group of samples to be input, and each typical standard working condition is calculatedThe total energy consumption E of the segment is output as a sample of the group.
Wherein, n=3,
Figure GDA0004159098840000122
representing the p-th group of input data, y (p) E R represents the output of group p, +.>
Figure GDA0004159098840000123
Represents the average speed of group p, respectively>
Figure GDA0004159098840000124
Constant speed ratio P, and deceleration ratio R.
Dividing the interval of the input variable into d q A fuzzy subset, wherein q is the fuzzy rule number, dividing the value range of the output variable into d 0 A fuzzy subset, A and B are respectively expressed as input variable x' (p) And output variable y (p) Is a fuzzy set of (a) and (b).
And calculating a membership value by adopting a Gaussian function as a membership function:
Figure GDA0004159098840000125
Figure GDA0004159098840000126
wherein ,μA (x′ (p)) and μB (y (p) ) The membership function values of the input value and the output value of the p-th group of sample data are respectively represented, and the values of b and sigma can be determined according to the needs.
Calculating the weight w multiplied by the membership degree of each group of sample data (p) ：
Figure GDA0004159098840000127
Creating a complete fuzzy rule base, wherein the specific description form is as follows:
if
Figure GDA0004159098840000128
is/>
Figure GDA0004159098840000129
is/>
Figure GDA00041590988400001210
and/>
Figure GDA00041590988400001211
is/>
Figure GDA00041590988400001212
then y (p) is
Figure GDA00041590988400001213
after the above fuzzy rule is established, the product operation and weighted average defuzzification are adopted to obtain the following fuzzy model y (x), and the sample trust degree bel obtained by BFCM algorithm is obtained j The trust degree as the fuzzy rule is substituted into the fuzzy model:
Figure GDA00041590988400001214
wherein ,
Figure GDA00041590988400001215
is the q-th rule in the fuzzy membership function mu B Points corresponding to (y) =1.
After the fuzzy model between the characteristic parameters and the energy consumption is established, a speed sensor in a driving mileage statistics system acquires speed information of a driving working condition in the driving process of the electric vehicle to be charged, the driving working condition is divided into a plurality of segments according to time average, and the characteristic parameters of each segment are obtained: average speed of
Figure GDA0004159098840000131
The characteristic parameters of the constant speed ratio P 'and the deceleration ratio N' are obtained by a central control console according to the speed and acceleration information of the electric automobile transmitted by a speed sensor, and the average speed is +.>
Figure GDA0004159098840000132
The constant speed proportion P ' and the deceleration proportion N ' are input into a fuzzy model to obtain the energy consumption E ' of each segment;
the central control console further calculates the remaining driving range of the electric automobile through the following calculation process:
E cost ＝∑E′
E rest ＝E total -E cost
Figure GDA0004159098840000133
S rest ＝lE rest
wherein E' is the energy consumption of each segment of the running working condition of the electric automobile to be charged; e (E) cost The total energy consumption of the electric automobile to be charged is; e (E) total The total energy of the electric automobile to be charged is obtained by parameters of the electric automobile to be charged; e (E) rest The remaining energy of the electric automobile to be charged; s is S cost The mileage of the electric vehicle to be charged is obtained by an odometer of the electric vehicle to be charged; l is the mileage of unit energy consumption; s is S rest The remaining driving range;
according to the obtained remaining mileage of the electric vehicle, the central control console uses the remaining mileage S of the electric vehicle rest Distance from remaining travel S need Comparing the sizes, if S rest -S need ＞S y The small display displays the remaining driving mileage of the electric automobile and the voice prompt that the electric automobile can successfully reach the target place; if S rest -S need ≤S y Starting a route planning system and prompting 'insufficient remaining driving range' by voice;
wherein ,Sy Is taken as the insideThe threshold value is generally S y ＝1～2km。
The specific process of the step (IV) is as follows:
the method comprises the steps of obtaining position information of each charging pile through connection of a wireless communication module in an electric automobile to be charged and a wireless communication module of each charging pile, and reserving the remaining driving range S of the electric automobile to be charged by taking the current position of the electric automobile to be charged as the circle center rest Taking all charging piles within the radius range as primary candidate charging piles, as shown in fig. 4, and reserving position information of the primary candidate charging piles;
then planning an optimal driving path from the current position of the electric vehicle to be charged to each candidate charging pile by using a vehicle-mounted navigator, and keeping the optimal driving path course smaller than the remaining driving mileage S of the electric vehicle to be charged rest The candidate charging pile of the (2) is used as a secondary candidate charging pile, and the position information of the secondary candidate charging pile is reserved;
finally, the using state value a of the secondary candidate charging pile is read, the secondary candidate charging pile with a=0 is removed, the secondary candidate charging pile with a=1 is reserved as a final candidate charging pile, finally, the optimal driving path of each final candidate charging pile planned by the vehicle navigator is displayed on a display screen of a small display, and the electric quantity s of the corresponding electric vehicle storage battery which is being charged is marked beside each final candidate charging pile 1 As shown in fig. 5. Labeled s 1 The driver can further screen according to the actual situation, for example, there are two final candidate charging piles a and b: charging pile a is 2km and s away from current position of electric automobile to be charged 1a =100%, and the distance between the charging pile b and the current position of the electric car to be charged is 1km and s 1b The driver can determine the waiting time required by himself according to the time required for reaching each charging pile, and determine the choice of selecting the charging pile according to his actual situation.

Claims (1)

1. An electric vehicle charging control method based on route planning uses an electric vehicle charging control device based on route planning, which comprises a charging pile monitoring module and an electric vehicle module, wherein the electric vehicle module is arranged on an electric vehicle to be charged;
the charging pile monitoring module comprises a parking space detection device and an electric quantity detection device, wherein the parking space detection device comprises a wireless communication module, an infrared scanner (9), a voice broadcasting device (10), four pressure sensors, two barrier blocks (5) with lifting devices, a timer (8) and a control circuit, the infrared scanner (9) and the voice broadcasting device (10) are integrated in an integrated box (2) and are arranged on the surface of a charging pile (1) facing a parking space (4), one barrier block (5) and the lifting devices thereof are arranged in a hole in the middle of a left boundary line of the parking space (4), one barrier block (5) is arranged in a hole in the middle of a right boundary line of the parking space (4), the other barrier block (5) is symmetrically arranged in the hole, automatic partition plates (7) are respectively arranged above the hole, the automatic partition plates (7) are driven by a small motor to horizontally move so as to open or close the hole containing the barrier blocks (5), four pressure sensors are respectively arranged at four corners (4), the four corners of the parking space (4) are respectively arranged at two pressure sensors (1) which are arranged at the front two pressure sensors (4) of the two pressure sensors (4) near the parking space (1), the timer (8) is connected with one of the rear pressure sensors (3), the wireless communication module can be connected with the wireless communication module in the central control console of the electric automobile in a wireless communication manner, and can be connected with the vehicle type information database of the Internet, the pressure sensor, the infrared scanner (9), the voice broadcasting device (10), the wireless communication module, the small motor and the lifting mechanism of the barrier block (5) are all connected with the control circuit, the electric quantity detection device is arranged on the charging pile, the electric quantity detection device is connected with the control circuit of the charging pile, and the position information of the charging pile is stored in the control circuit of the charging pile;
the electric automobile module comprises a driving mileage statistics system, a vehicle-mounted navigator, a central control console and a small display, wherein the driving mileage statistics system comprises an electric quantity display device connected with a storage battery of the electric automobile to be charged and a speed sensor of the electric automobile to be charged; the small display comprises a display screen and a voice broadcasting device, and the electric quantity display device, the speed sensor, the display screen and the voice broadcasting device are all connected with a central control console of the electric automobile to be charged;
the method is characterized by comprising the following specific steps:
step one, inputting the whole vehicle parameters and the battery pack parameters of the electric vehicle to be charged into a central control console;
the charging pile monitoring module monitors the states of the charging pile and the parking space, and transmits the position and state information of the charging pile and the parking space to the electric automobile module;
step three, acquiring speed information of the running working condition of the electric vehicle to be charged by a driving mileage statistics system; establishing a fuzzy model between characteristic parameters of typical standard working conditions and energy consumption; substituting the speed information of the running working condition of the charged electric automobile into a fuzzy model between the characteristic parameters of the typical standard working condition and the energy consumption by the central control console to calculate the remaining driving mileage of the electric automobile to be charged;
the central control console performs three-time screening on the charging piles according to the remaining driving mileage of the electric vehicle to be charged, the position and state information of the charging piles to obtain final candidate charging piles, and the vehicle-mounted navigator performs path planning on the final candidate charging piles;
wherein ,
the specific process of the step (II) is as follows:
when the front pressure sensor (6) detects that the pressure is gradually increased and the pressure direction is from the outside of the parking space to the inside of the parking space, namely, when a car starts to park, the infrared scanner (9) is triggered, the infrared scanner (9) scans the license plate of the car which is parked, and the scanned license plate is accessed into a vehicle type information database of the Internet through the wireless communication module to determine the type of the car which parks:
a. if the type of the automobile for parking is determined to be an electric automobile, a voice broadcasting device (10) broadcasts that the parked automobile is the electric automobile, charging is requested, the parking is completed when four pressure sensors detect that the pressure is not increased any more, a timer (8) is triggered by the pressure sensors to start timing when the automobile just completes the parking, and the timer (8) detects the automobileTime t of parking 1 In addition, a time threshold t is set 0 Taking t 0 =10 to 30s; if t 1 ＞t 0 When the electric quantity detection device in the charging pile monitoring module does not detect that the charging pile has corresponding charging action, triggering an alarm, and playing a voice warning 'forbidden to occupy a charging parking space' by the voice broadcasting device (10);
if the electric automobile is at time t 0 In-charging operation, the electric quantity detection device detects the electric quantity s of the electric automobile storage battery being charged in real time 1 When s is 1 When the vehicle is in 100 percent or the vehicle is in stop of the charging operation of the charging pile, the voice broadcasting device (10) plays a voice prompt that the charged vehicle is timely away, the timer (8) starts to count, and the timer (8) starts to detect the parking time t of the vehicle after the charging is finished 2 If t 2 ＞t 0 When the automobile is still parked at the parking space, an alarm is triggered, and the voice broadcasting device (10) carries out voice warning on 'the occupied charging parking space is forbidden';
when the automobile finishes the parking action, if the front pressure sensor (6) and the rear pressure sensor (3) do not detect the pressure change, the parking space is in a used state, and the use state value a=0 of the charging pile; if the front pressure sensor (6) and the rear pressure sensor (3) detect that the pressure value is zero, namely the automobile is driven out of the parking space, the charging pile use state value a=1;
meanwhile, the charging pile monitoring module transmits a and s through the wireless communication device 1 The numerical value of (2) is sent to the electric automobile module;
b. if the type of the automobile for stopping is determined to be a traditional automobile, the control circuit controls the automatic partition board (7) to be opened, controls the lifting mechanism of the obstacle block (5) to drive the obstacle block (5) to ascend, and simultaneously the voice broadcasting device (10) carries out voice warning to prevent the traditional automobile from stopping into a parking space;
the specific process of the step (III) is as follows:
firstly, characteristic parameter information of each segment under typical standard working conditions is obtained: establishing a whole electric vehicle energy consumption model in MATLAB, wherein the input working conditions are 10 typical standard working conditions, each typical standard working condition takes 1200s, and the following steps are sequentially carried outEach typical standard working condition is equally divided into 12 groups of segments, each typical standard working condition is operated, and each typical standard working condition segment takes four characteristic parameters: average speed of
Figure FDA0004159098830000031
The constant speed proportion P, the deceleration proportion R and the total energy consumption E can obtain 120 groups of data;
secondly, establishing a fuzzy model between characteristic parameters of typical standard working conditions and energy consumption:
constructing a vector x composed of N groups of L dimensions j A composed data set X, each L-dimensional vector X j Four characteristic parameters for each segment are included, where n=120, l=4, x= (x) 1 ,x 2 ,…,x j )j＝1,2,…,N
Extracting the trust degree of the data set X by adopting a fuzzy C clustering algorithm added with the trust degree, namely a BFCM algorithm;
let u ij For fuzzy membership, i.e. x j The degree belonging to class i, c is the number of clustering classes, bel j For confidence of data in clustering process, namely x j Trust level, v i I=1, 2, …, c, d for class i cluster center ij ＝d(v i ,x j ) For data x j And a cluster center v i M is a flexibility coefficient, controlling the sharing degree among categories, and generally, m is more ideal to be 2.0, so that m=2.0;
initializing: the number of the characteristic parameters is four, so the number of the categories is 4, the clustering category number c=4 is set, the iteration termination value epsilon and the maximum iteration number b are set max The method can be determined according to specific precision requirements;
initializing fuzzy membership u ij Make it satisfy u ij ∈(0,1)
Updating confidence bel j ：
Order the
Figure FDA0004159098830000032
Figure FDA0004159098830000033
Updating cluster center v i ；
Figure FDA0004159098830000034
in the formula ,
Figure FDA0004159098830000041
representing the updated cluster center;
according to the updated clustering center
Figure FDA0004159098830000042
Updating fuzzy membership u ij ：
(d ij ) 2 ＝(x j -v i (b) ) T A(x j -v i (b) )
Figure FDA0004159098830000043
in the formula ,
Figure FDA0004159098830000044
representing updated fuzzy membership, A is a unity symmetry matrix, d when k=i kj ＝d ij
If it is
Figure FDA0004159098830000045
Ending the iteration to obtain the confidence level bel j The method comprises the steps of carrying out a first treatment on the surface of the Otherwise, let->
Figure FDA0004159098830000046
Re-updating confidence bel j ；
Extracting fuzzy rules by using a iWM method, and establishing a fuzzy model between characteristic parameters and energy consumption according to a fuzzy rule base:
first, a sample T with N pairs of N input single outputs is constructed, T= { (x' (p) ；y (p) ) P=1, 2, …, N, average speed for each typical standard condition segment
Figure FDA0004159098830000047
The constant speed ratio P and the deceleration ratio R are used as a group of sample input, and the total energy consumption E of each typical standard working condition segment is used as a sample output of the group;
wherein, n=3,
Figure FDA0004159098830000048
representing the p-th group of input data, y (p) E R represents the output of the p-th group,
Figure FDA0004159098830000049
represents the average speed of group p, respectively>
Figure FDA00041590988300000410
Constant speed ratio P, and deceleration ratio R;
dividing the interval of the input variable into d q A fuzzy subset, wherein q is the fuzzy rule number, dividing the value range of the output variable into d 0 A fuzzy subset, A and B are respectively expressed as input variable x' (p) And output variable y (p) Is a fuzzy set of (2);
and calculating a membership value by adopting a Gaussian function as a membership function:
Figure FDA00041590988300000411
Figure FDA00041590988300000412
wherein ,μA (x′ (p)) and μB (y (p) ) Respectively represent the number of the p-th group samplesAccording to membership function values of the input value and the output value, the values of b and sigma can be determined according to the needs;
calculating the weight w multiplied by the membership degree of each group of sample data (p) ：
Figure FDA0004159098830000051
Creating a complete fuzzy rule base, wherein the specific description form is as follows:
Figure FDA0004159098830000052
Figure FDA0004159098830000053
after the above fuzzy rule is established, the product operation and weighted average defuzzification are adopted to obtain the following fuzzy model y (x), and the sample trust degree bel obtained by BFCM algorithm is obtained j The trust degree as the fuzzy rule is substituted into the fuzzy model:
Figure FDA0004159098830000054
wherein ,
Figure FDA0004159098830000055
is the q-th rule in the fuzzy membership function mu B Points corresponding to (y) =1;
after the fuzzy model between the characteristic parameters and the energy consumption is established, a speed sensor in a driving mileage statistics system acquires speed information of a driving working condition in the driving process of the electric vehicle to be charged, the driving working condition is divided into a plurality of segments according to time average, and the characteristic parameters of each segment are obtained: average speed of
Figure FDA0004159098830000056
The characteristic parameters of the constant speed ratio P 'and the deceleration ratio N' are obtained by a central control console according to the speed and acceleration information of the electric automobile transmitted by a speed sensor, and the average speed is +.>
Figure FDA0004159098830000057
The constant speed ratio P 'and the deceleration ratio N' are input into a fuzzy model, so that the energy consumption of each segment can be obtained;
the central control console further calculates the remaining driving range of the electric automobile through the following calculation process:
E cost ＝∑E′
E rest ＝E total -E cost
Figure FDA0004159098830000058
S rest ＝lE rest
wherein E' is the energy consumption of each segment of the running working condition of the electric automobile to be charged; e (E) cost The total energy consumption of the electric automobile to be charged is; e (E) total The total energy of the electric automobile to be charged is obtained by parameters of the electric automobile to be charged; e (E) rest The remaining energy of the electric automobile to be charged; s is S cost The mileage of the electric vehicle to be charged is obtained by an odometer of the electric vehicle to be charged; l is the mileage of unit energy consumption; s is S rest Is the remaining driving mileage;
according to the obtained remaining mileage of the electric vehicle, the central control console uses the remaining mileage S of the electric vehicle rest Distance from remaining travel S need Comparing the sizes, if S rest -S need ＞S y The small display displays the remaining driving mileage of the electric automobile and the voice prompt that the electric automobile can successfully reach the target place; if S rest -S need ≤S y Starting a route planning system and prompting 'insufficient remaining driving range' by voice;
wherein ,Sy For mileage threshold, take S y ＝1～2km；
The specific process of the step (IV) is as follows:
the position information of each charging pile is obtained through connection of a wireless communication module in the electric automobile to be charged and a wireless communication module of each charging pile, and the remaining driving mileage S of the electric automobile to be charged with the current position of the electric automobile to be charged as the circle center is reserved rest Taking all charging piles within the radius range as primary candidate charging piles, and reserving position information of the primary candidate charging piles;
then planning an optimal driving path from the current position of the electric vehicle to be charged to each candidate charging pile by using a vehicle-mounted navigator, and keeping the optimal driving path course smaller than the residual continuous mileage S of the electric vehicle to be charged rest The candidate charging pile of the (2) is used as a secondary candidate charging pile, and the position information of the secondary candidate charging pile is reserved;
finally, the using state value a of the secondary candidate charging pile is read, the secondary candidate charging pile with a=0 is removed, the secondary candidate charging pile with a=1 is reserved as a final candidate charging pile, finally, the optimal driving path of each final candidate charging pile planned by the vehicle navigator is displayed on a display screen of a small display, and the electric quantity s of the corresponding electric vehicle storage battery which is being charged is marked beside each final candidate charging pile 1 。
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