CN106682759A - Battery supply system for electric taxi, and network optimization method - Google Patents

Abstract

The invention discloses a battery supply system for an electric taxi, and a network optimization method. The battery supply system is especially designed for the electric taxi through the big data technology, and the economical strategy of centralized charging is employed for meeting the demands of the electric taxi in a city. An existing gasoline station can meet the gasoline demands of all vehicles in the city, and also can meet the demands of taxies in the city definitely. A mode of cooperating with the existing gasoline state (taking the existing gasoline state as an alternative point) can avoid a condition that a selected region is not feasible (because of geographical or law factors), thereby saving a large amount of money. When the taxi changes an electric changing station, the road congestion, the service level of the electric changing station, the queuing length and the driving habits of a driver are considered through a logit model, so the system is more suitable for the actual conditions.

Description

For the battery supplied system and network optimized approach of electric taxi

Technical field

The present invention relates to the planing method that a kind of abandoned car is reclaimed, it is fixed that this planing method is particularly based on balanced returned enterprise Valency and cost recovery.It is related to Patent classificating number G06 calculating；Calculate；Count G06Q and be specially adapted for administration, business, finance, pipe The data handling system or method of reason, supervision or prediction purpose；What other classifications did not included is specially adapted for administration, business, gold Melt, manage, supervise or predict purpose processing system or method G06Q50/00 be specially adapted for specific operating division system or Method, such as public utilities or tourism G06Q50/06 electric power, natural gas or water supply.

Background technology

Economic fast development, what is on the one hand brought is the improvement of people's living standards, on the other hand also makes energy problem Acid test is obtained.Electric automobile is a kind of new forms of energy vehicles, and it has, and energy consumption is low, use cost is low, pollutant is few The features such as, Pollution of City Traffic problem can be efficiently solved, nowadays have become the emerging strategic product that China's emphasis is supported One of industry, is following development trend.

However, imperfect service auxiliary facility, electric automobile is impossible to be used by large-scale popularization.Strengthen electronic vapour Car electrically-charging equipment capital construction, is to promote low-carbon economy, build with advanced adequate and systematic service level guiding electric automobile consumption demand If the Important Action of resource-conserving and environment-friendly society.

Electrically-charging equipment includes charging pile and changes battery station, as shown in the table, changes battery technology in time with definitely excellent Gesture.It is in fact external just it has been proposed that change the idea at battery station and put into practice early in 2007, but because huge base cannot be undertaken Infrastructure is invested and most cars are looked forward to not the actively attitude of cooperation and counted out.Really, batteries of electric automobile picture shows The engine for having automobile equally belongs to core technology, and each big Automobile Enterprises are difficult to share, so for private car, changing The foundation at battery station there may be obstruction.The public transports such as taxi are very different with private car, taxi bus Easily realize that model is unified, there is no above-mentioned core technology sharing problem.And, the distance travelled of private car is relatively short after all, Perhaps charge several hours after driving a period of time can be tolerated, but taxi is not all right.

The electric power of table 1 supplements type list

The content of the invention

Proposition for problem above of the invention, and a kind of battery supplied system and net for electric taxi developed Network optimization method, with following steps：

- by the GPS historical datas of analysis record taxi, obtain location distribution of the taxi in charge period；

- set up the selection scheme that taxi exchange power station is determined based on the selection scheme model of multinomial Logit mode；

- according to described selection scheme, determine that taxi reaches target and changes an expense at station；Set up comprising the expense Electrical changing station site selection model；The optimum for meeting each item constraint is selected from multiple alternative electrical changing station addressing schemes by the site selection model Electrical changing station addressing scheme；

- the selection scheme according to the optimum electrical changing station selection scheme and taxi for obtaining to electrical changing station, sets up and is based on Tyson Polygonal charging center position model；Alternative charging center placement scheme is input into the model, obtain charging center and its The cluster of attached electrical changing station composition；

- expense of each cluster is traveled through, the charging center position model that expense min cluster is represented is exported, complete The optimization of grid.

Used as preferred embodiment, the described selection scheme model based on multinomial Logit mode is including at least taxi Car is to bustling area's tendentiousness and described location distribution away from gas station's distance and electrical changing station service level and electrical changing station row Team's penalty；The weight coefficient of described each influence factor is respectively θ₁、θ₂、θ₃And θ₄。

Further, described electrical changing station penalty is：

The function is the relation function of electrical changing station queuing duration and CSAT.

Used as preferred embodiment, the described selection scheme model based on multinomial Logit mode is as follows：

Endurance is constrained, and determines the electrical changing station in the range of each taxi endurance, that is, Bg；

Utility function, determines each taxi to the value of utility of each electrical changing station in its endurance；

Probability function, determines each taxi to the probability of each electrical changing station in its endurance；

Wherein γ_gbrRepresent r-th variable for affecting taxi g to select u-th electrical changing station；θ_rRepresent the power of r-th variable Weight coefficient；V_gbRepresent that electric taxi g selects the utility function of electrical changing station u；P_gbRepresent that electric taxi g selects electrical changing station u's Probability；E⁰Represent electric taxi initial residual electricity；E represents the average power consumption of electric taxi unit interval；B represents quilt The electrical changing station chosen set B=u | w_u=1 }；B_gThe set G for representing the electrical changing station in the range of taxi g endurances is represented The set of taxi.

Further, described electrical changing station site selection model is：

Subject to:

Limited fund so that the total fund of input coefficient is less than certain limit；

Amount of batteries is constrained, represent daily to u-th electrical changing station battery requirements less than u-th electrical changing station amount of batteries；

Service rate is constrained, it is ensured that more than 90% taxi changes battery behavior and is satisfied；

Variable-value is constrained；

Wherein, a represents that electric taxi travels the average unit cost of unit interval；h_uRepresent that establishment builds the u's of electrical changing station Constant expense；Qb represents the battery capacity of electrical changing station u；U represents the set of electrical changing station.

It is described to select full from multiple alternative electrical changing station addressing schemes by the site selection model as preferred embodiment The optimum electrical changing station addressing scheme process of each item constraint of foot is specific as follows：

- a series of electrical changing station placement scheme set { M are produced from candidate's electrical changing station₁,M₂,,,,,,M_n, wherein, M₁It is Alternative electrical changing station 1, M₂It is alternative electrical changing station 2, by that analogy, M_nIt is alternative electrical changing station n；Alternative electrical changing station combination sum

- scheme is taken out from described scheme set；

- described number of batteries constraint, limited fund, service rate constraint are checked respectively；Calculate the cost of charging center；

Expense, the construction cost of electrical changing station and the expense with regard to charging center of electrical changing station are reached to program taxi Sued for peace；

- each scheme is traveled through, the minimum scheme of cost is drawn, as optimum electrical changing station addressing scheme.

Used as preferred embodiment, described charging center position model is as follows：

Subject to：

BPR functions：

Guarantee between charging center without Distribution path：

Guarantee necessarily there is Distribution path between charging center and electrical changing station：

Dispensing vehicle quantity used in computing system：

0/1 variable-value, W_vRepresent whether charging center v is established, x_ijkRepresent whether dispensed by dispensing vehicle k between (i, j) Battery；

Wherein, A represents the distribution cost of battery dispensing vehicle unit interval；M represents the number of battery dispensing vehicle；M is represented and matched somebody with somebody Send the cost of car；α represents BPR function undetermined parameters, it is proposed that value is 0.15；β represents BPR function undetermined parameters, it is proposed that value For 4；t_ijRepresent the actual transit time of charging center i to electrical changing station j；t_ijRepresent the free walker of charging center i to electrical changing station j Sail the time；H_vRepresent the constant expense for building charging center v；Q_ijRepresent the actual traffic amount of charging center i to electrical changing station j；C_ij Represent the traffic capacity of charging center i to electrical changing station j；K represents the set of battery dispensing vehicle；V represents the set of charging center；O Represent selected charging center set O=v | W_v=1 }.

The main contributions of the present invention are to aim at electric taxi with big data technology to devise battery supplied system and adopt With the demand for concentrating this economical strategy that charges to meet electric taxi in a city.The gas station for having existed Disclosure satisfy that the oiling demand of all cars in an a city also demand for surely meeting taxi.With the gas station for having existed The mode (with the gas station that existed as alternative point) of cooperation not only can avoid infeasible (the geographical, law in the region chosen Etc. reason) a large number of investment cost can also be saved.Road crowding, electrical changing station are serviced into water when taxi selects electrical changing station The many factors such as flat, queuing duration, driver driving custom are taken into account by logit models, more tally with the actual situation.To sum up, The present invention carries out master-plan and optimization from the visual angle of taxi company (or government) to whole city battery supplied network, Find preferably charging center and electrical changing station addressing scheme.In view of above reason, present invention can be widely used to electric taxi Field.

Description of the drawings

For clearer explanation embodiments of the invention or the technical scheme of prior art, below will be to embodiment or existing The accompanying drawing to be used needed for having technology description does one and simply introduces, it should be apparent that, drawings in the following description are only Some embodiments of the present invention, for those of ordinary skill in the art, on the premise of not paying creative work, may be used also To obtain other accompanying drawings according to these accompanying drawings.

Fig. 1 is the system operation figure of the present invention

Fig. 2 is the schematic flow sheet of the present invention

Fig. 3 is the dendrogram in calculating process of the present invention

Specific embodiment

To make purpose, technical scheme and the advantage of embodiments of the invention clearer, with reference to the embodiment of the present invention In accompanying drawing, clearly complete description is carried out to the technical scheme in the embodiment of the present invention：

As Figure 1-3：

Then we obtain the selection scheme of taxi, its suboptimum firstly the need of the data message for collecting charge requirement point Change the position of electrical changing station, finally optimize the position of charging center.The position optimization of charging center is both one needs independent decision-making Problem be again to affect the subproblem of electrical changing station position below in conjunction with the accompanying drawings and specific embodiment, further elucidate the present invention：

1) charge requirement point, that is, the position of taxi are determined.

The first step of addressing optimization is to determine the position of client's point, that is, the position of taxi driver.As one not The dynamic vehicles of offset, taxi is generally identified as trip demands.Although it is considered that the position of taxi is dynamic change Change, but in certain period of time, dynamic equilibrium has been reached to a certain extent.In other words, certain specific taxi Position is really being constantly occurring change, but the taxi number in certain area is constant within a period of time.By big number GPS analyses are carried out according to technology, the position distribution situation of taxi charging interval section can be obtained.

2) selection scheme of the taxi to electrical changing station is obtained.

There are multiple electrical changing stations in the range of the endurance of one taxi, it is generally recognized that taxi understands chosen distance, and it is nearest That electrical changing station change electrical changing station service level in battery, but real life, queue length, driver driving custom etc. all can be right Selection result produces impact, and we affect to represent that model is concrete with the selection scheme model based on multinomial Logit mode by this It is as follows：

The electrical changing station of table 2 selects influence factor table

γ_gbrRepresent r-th variable for affecting taxi g to select u-th electrical changing station；θ_rRepresent the weight system of r-th variable Number；V_gbRepresent that electric taxi g selects the utility function of electrical changing station u；P_gbRepresent that electric taxi g selection electrical changing station u's is general Rate；E⁰Represent electric taxi initial residual electricity；E represents the average power consumption of electric taxi unit interval；B represents selected In electrical changing station set B=u | w_u=1 }；B_gThe set G for representing the electrical changing station in the range of taxi g endurances is represented The set hired a car

It is as follows to the selection course calculation procedure of electrical changing station to taxi using logit models：

Step 1:For each taxi, all electrical changing stations in the range of its endurance are found.

Step 2:First pass through distance, service level, three indexs of tendentiousness to bustling area and calculate electrical changing station to taxi Value of utility, and determine that each taxi selects the initial scheme of electrical changing station by probability function.

Step 3:Again the 4th index crowding is weighed with the initial scheme for obtaining, final four indexs are weighed simultaneously Obtain the plan of taxi electricity supplement.

3) electrical changing station site selection model

Final addressing is as follows, and the target of model is that logistics system total cost is minimum, including taxi is reached and changes electricity The expense stood, the construction cost of electrical changing station, with regard to the expense of charging center.Service rate ensured by hard constraint, it is so low into This and high service rate just can be guaranteed simultaneously.

Subject to:

A represents that electric taxi travels the average unit cost of unit interval；h_uRepresent the fixed charge for setting up the u for building electrical changing station With；q_bRepresent the battery capacity of electrical changing station u；U represents the set of electrical changing station.

Formula (5) is limited fund so that the total fund of input coefficient is less than certain limit.

Formula (6) is amount of batteries constraint, is represented daily to u-th electrical changing station battery requirements less than u-th electrical changing station Amount of batteries.

Formula (7) is service rate constraint, it is ensured that more than 90% taxi changes battery behavior and is satisfied.

Formula (8) is variable-value constraint.

The addressing optimization process calculation procedure of electrical changing station is as follows：

Step 1:A series of electrical changing station placement scheme { M are produced from candidate's electrical changing station₁,M₂,,,,,,M_n, wherein, M₁It is Alternative electrical changing station 1, M₂It is alternative electrical changing station 2, by that analogy, M_nIt is alternative electrical changing station n；Alternative electrical changing station combination sum

Step 2:A scheme is taken out from the scheme set of step 1.

Step 3:Inspection number of batteries constraint (constraint (6)), and obtain final electricity additional project.Go out if n Hire a car more than the service limit of certain electrical changing station, whether inspection can again reach it apart from n nearest taxi of the electrical changing station His electrical changing station.If endurance is allowed and other electrical changing stations there remains battery, these electrical changing stations is arranged into and newly change electricity Stand, otherwise these electrical changing stations will not being serviced, that is, final electricity additional project.

Step 4:Inspection limited fund (constraint (5)).If the cost that this scheme is produced is carried out in the range of fund Step5.Otherwise, give up this scheme and carry out Step 8.

Step 5:Inspection service rate constraint (constraint (7)).If the service rate of this scheme is more than 90%, step8 is carried out. Otherwise, give up this scheme and carry out Step8.

Step 6:Calculate the cost (being discussed in detail in next part) with regard to charging center.

Step 7:By each several part cost summation of the program, (taxi reaches the expense of electrical changing station, the cost of erection of electrical changing station With with regard to the expense of charging center).If totle drilling cost records and carries out step8 less than upper one record.Otherwise, do not remember Record directly carries out step8.

Step 8:If all schemes are all tested crossed, step9 is carried out.Otherwise, select down from the set of step 1 One scheme simultaneously returns step3.

Step 9:Terminate and export final result.

4) charging center position optimization model

Charging center number problem needs to be leveraged, if only selecting a charging center, although construction cost can be saved, But freight can increase.If selecting multiple charging centers, in turn freight can be reduced, and construction cost can increase.Institute Where to build charging center, building several charging centers needs to be determined.

We are carried out based on the cluster (Fig. 3) of distance using Thiessen polygon, and such a polycentric scheme is just divided Solution is into multiple single centre VRP problems.

The model of battery dispensing problem is as follows, and object function is intended to minimize the cost of three parts, is respectively：

Vehicle delivery cost；

Charging center construction cost；

Vehicle use cost；

Vehicle delivery cost is exactly with the related part cost of operating range；

Vehicle use cost is exactly with the related part cost of vehicle fleet size.

Because battery dispensing vehicle lifting capacity is limited, point-to-point means of distribution is adopted according to present battery weight, such as Technique variation can be saving distribution cost by the way of transporting using closed loop after fruit.Vehicle dispenses daily τ primary cells, so battery Distribution cost has been multiplied by a τ.τ is the value made by oneself, and with the increase of taxi charging behavior, τ values increase.

Subject to：

A represents the distribution cost of battery dispensing vehicle unit interval；M represents the number of battery dispensing vehicle；M represents dispensing vehicle Cost；α represents BPR function undetermined parameters, it is proposed that value is 0.15；β represents BPR function undetermined parameters, it is proposed that value is 4；t_ij Represent the actual transit time of charging center i to electrical changing station j；t_ijRepresent the free running time of charging center i to electrical changing station j； H_vRepresent the constant expense for building charging center v；Q_ijRepresent the actual traffic amount of charging center i to electrical changing station j；C_ijRepresent and charge The traffic capacitys of the center i to electrical changing station j；K represents the set of battery dispensing vehicle；V represents the set of charging center；O represents selected In charging center set O=v | W_v=1 }.

Formula (10) is BPR functions.

Formula (11) is guaranteed between charging center without Distribution path.

Formula (12) guarantees necessarily there is Distribution path between charging center and electrical changing station.

Formula (13) is the dispensing vehicle quantity for using in computing systems

Formula (14) is 0/1 variable-value, W_vRepresent whether charging center v is established, x_ijkRepresent between (i, j) whether by Dispensing vehicle k dispenses battery.

The addressing optimization process calculation procedure of electrical changing station is as follows：

Step 1:A series of charging center placement schemes are produced from candidate's charging center.

Step 2:Cross if all of scheme is all tested, turn to step 7.Otherwise, the set from step1 Take out a scheme and turn to step 3.

Step3:For each electrical changing station is found apart from its nearest charging center, then each charging center and " it Electrical changing station " constitutes a class.Each scheme is made up of several clusters, that is, the cluster based on Thiessen polygon.

Step4:Calculate the totle drilling cost of each class.(vehicle delivery cost, charging center construction cost, vehicle are used into This).

Step5：The expense of all classes in scheme is added and.If total cost is less than Last record, records and turn to Step 6. otherwise, is not recorded directly to step6.

Step6:Next charging center scheme is taken out from the set of step1 and Step2 is returned to.

Step7:Terminate and export final result.

The above, the only present invention preferably specific embodiment, but protection scope of the present invention is not limited thereto, Any those familiar with the art the invention discloses technical scope in, technology according to the present invention scheme and its Inventive concept equivalent or change in addition, all should be included within the scope of the present invention.

Claims (7)

1. a kind of battery supplied system and network optimized approach for electric taxi, it is adaptable to comprising electrical changing station and charge The battery supplied system of the heart, charging center is responsible for battery concentration charging in system, and battery dispensing vehicle is sent to full battery respectively Individual electrical changing station simultaneously takes back on empty battery, it is characterised in that with following steps：

- by the GPS historical datas of analysis record taxi, obtain location distribution of the taxi in charge period；

- set up based on the selection scheme model of multinomial Logit mode, determine that taxi exchanges the selection scheme in power station；

- according to described selection scheme, determine that taxi reaches target and changes an expense at station；Set up and change electricity comprising the expense Stand site selection model；Selected from multiple alternative electrical changing station addressing schemes by the site selection model and meet the optimum of each item constraint and change electricity Stand addressing scheme；

- the selection scheme according to the optimum electrical changing station selection scheme and taxi for obtaining to electrical changing station, sets up polygon based on Tyson The charging center position model of shape；Alternative charging center placement scheme is input into the model, charging center is obtained and its is attached The cluster of electrical changing station composition；

- expense of each cluster is traveled through, export the charging center position model that expense min cluster is represented, completion system The optimization of network.

2. the battery supplied system and network optimized approach for electric taxi according to claim 1, its feature is also It is the described selection scheme model based on multinomial Logit mode including at least taxi to bustling area's tendentiousness and described Location distribution is away from gas station's distance and electrical changing station service level and electrical changing station queuing penalty；Described each impact because The weight coefficient of element is respectively θ₁、θ₂、θ₃And θ₄。

3. the battery supplied system and network optimized approach for electric taxi according to claim 2, its feature is also It is that described electrical changing station penalty is：

$\begin{array}{cc}{\mathrm{\γ}}_{gb4}=\frac{1}{\underset{g\∈G}{\mathrm{\Σ}}{y}_{gb}}& \∀b\∈B\end{array}$

The function is the relation function of electrical changing station queuing duration and CSAT.

4. the battery supplied system and network optimized approach for electric taxi according to claim 2, its feature is also It is that the described selection scheme model based on multinomial Logit mode is as follows：

Endurance is constrained, and determines the electrical changing station in the range of each taxi endurance, that is, Bg；

$\begin{array}{cc}{E}^0-e\×t_{gb}\≥0& \∀g\∈G,b\∈B\end{array}---\left(1\right)$

Utility function, determines each taxi to the value of utility of each electrical changing station in its endurance；

$\begin{array}{ccc}{V}_{gb}=\underset{r=1}{\overset{4}{\Σ}}{\mathrm{\θ}}_r\×{\mathrm{\γ}}_{gbr}& \∀g\∈G& b\∈B_g\end{array}---\left(2\right)$

Probability function, determines each taxi to the probability of each electrical changing station in its endurance；

$\begin{array}{ccc}{P}_{gb}=\frac{{\mathrm{expV}}_{gb}}{\underset{b\∈B}{\mathrm{\Σ}}{\mathrm{expV}}_{gb}}& \∀g\∈G& b\∈B_g\end{array}---\left(3\right)$

Wherein γ_gbrRepresent r-th variable for affecting taxi g to select u-th electrical changing station；θ_rRepresent the weight system of r-th variable Number；V_gbRepresent that electric taxi g selects the utility function of electrical changing station u；P_gbRepresent that electric taxi g selection electrical changing station u's is general Rate；E⁰Represent electric taxi initial residual electricity；E represents the average power consumption of electric taxi unit interval；B represents selected In electrical changing station set B=u | w_u=1 }；B_gThe set G for representing the electrical changing station in the range of taxi g endurances is represented The set hired a car.

5. the battery supplied system and network optimized approach for electric taxi according to claim 4, its feature is also It is that described electrical changing station site selection model is：

Subject to： Limited fund so that the total fund of input coefficient is less than certain limit；

$\begin{array}{ccc}\underset{u\∈U}{\mathrm{\Σ}}{h}_u{w}_u+\underset{v\∈V}{\mathrm{\Σ}}{H}_v{W}_v+m\×M\≤S& \∀g\∈G& b\∈B\end{array}---\left(5\right)$

Amount of batteries is constrained, represent daily to u-th electrical changing station battery requirements less than u-th electrical changing station amount of batteries；

$\begin{array}{cc}\underset{g\∈G}{\Σ}{y}_{gb}\≤{\mathrm{\τq}}_b& \∀b\∈B\end{array}---\left(6\right)$

Service rate is constrained, it is ensured that more than 90% taxi changes battery behavior and is satisfied；

$\underset{b\∈B}{\Σ}\underset{g\∈G}{\Σ}{y}_{gb}/\left|G\right|\≥0.9---\left(7\right)$

Variable-value is constrained；

$\begin{array}{ccc}{W}_u,y_{gb}\∈\{0,1\}& \∀g\∈G& b\∈B\end{array}---\left(8\right)$

Wherein, a represents that electric taxi travels the average unit cost of unit interval；h_uRepresent the fixed charge for setting up the u for building electrical changing station With；Qb represents the battery capacity of electrical changing station u；U represents the set of electrical changing station.

6. the battery supplied system and network optimized approach for electric taxi according to claim 5, its feature is also The optimum electrical changing station for meeting each item constraint is selected from multiple alternative electrical changing station addressing schemes by the site selection model described in being Addressing scheme process is specific as follows：

- a series of electrical changing station placement scheme set { M are produced from candidate's electrical changing station₁,M₂,,,,,,M_n, wherein, M₁It is standby Select electrical changing station 1, M₂It is alternative electrical changing station 2, by that analogy, M_nIt is alternative electrical changing station n；Alternative electrical changing station combination sum

- scheme is taken out from described scheme set；

- described number of batteries constraint, limited fund, service rate constraint are checked respectively；Calculate the cost of charging center；

Expense, the construction cost of electrical changing station and the expense with regard to charging center of electrical changing station are reached to program taxi to be carried out Summation；

- each scheme is traveled through, the minimum scheme of cost is drawn, as optimum electrical changing station addressing scheme.

7. the battery supplied system and network optimized approach for electric taxi according to claim 1, its feature is also It is that described charging center position model is as follows：

Subject to： BPR functions：

$t_{ij}=t_{ij}^0\[1+\mathrm{\α}{\left(\frac{Q_{ij}}{C_{ij}}\right)}^{\mathrm{\β}}\]---\left(10\right)$

Guarantee between charging center without Distribution path：

$\begin{array}{cc}\underset{i\∈0}{\Σ}\underset{j\∈0}{\Σ}{x}_{ijk}=0& \∀k\∈K\end{array}---\left(11\right)$

Guarantee necessarily there is Distribution path between charging center and electrical changing station：

$\begin{array}{cc}\underset{j\∈B}{\Σ}\underset{k\∈K}{\Σ}{x}_{ijk}=1& \∀i\∈0\end{array}---\left(12\right)$

Dispensing vehicle quantity used in computing system：

$\underset{i\∈0}{\Σ}\underset{j\∈B}{\Σ}\underset{k\∈K}{\Σ}{x}_{ijk}=m---\left(13\right)$

0/1 variable-value, W_vRepresent whether charging center v is established, x_ijkRepresent and whether battery is dispensed by dispensing vehicle k between (i, j)；

$\begin{array}{ccccc}{W}_v,x_{ijk}\∈\{0,1\}& \∀v\∈V& i\∈I& j\∈I& k\∈K\end{array}---\left(14\right)$

Wherein, A represents the distribution cost of battery dispensing vehicle unit interval；M represents the number of battery dispensing vehicle；M represents dispensing vehicle Cost；α represents BPR function undetermined parameters, it is proposed that value is 0.15；β represents BPR function undetermined parameters, it is proposed that value is 4； t_ijRepresent the actual transit time of charging center i to electrical changing station j；t_ijRepresent charging center i to electrical changing station j when freely travelling Between；H_vRepresent the constant expense for building charging center v；Q_ijRepresent the actual traffic amount of charging center i to electrical changing station j；C_ijRepresent The traffic capacitys of the charging center i to electrical changing station j；K represents the set of battery dispensing vehicle；V represents the set of charging center；O is represented Selected charging center set O=v | W_v=1 }.