CN111216571A - Battery-replacement type electric automobile navigation method participating in real-time logistics distribution - Google Patents

Battery-replacement type electric automobile navigation method participating in real-time logistics distribution Download PDF

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CN111216571A
CN111216571A CN201911148275.9A CN201911148275A CN111216571A CN 111216571 A CN111216571 A CN 111216571A CN 201911148275 A CN201911148275 A CN 201911148275A CN 111216571 A CN111216571 A CN 111216571A
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path
distribution
battery
time
station
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杨洪明
侯佳伟
姜贻哲
廖圣桃
王懂
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Changsha University of Science and Technology
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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
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • 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
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • 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
    • Y02T90/14—Plug-in electric vehicles
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention discloses a battery-replacement type electric vehicle navigation method participating in real-time logistics distribution, which comprises the following steps: step S1: acquiring the farthest driving distance d of the residual electric quantity of the electric automobile; step S2: acquiring the position information of the power swapping station, the position information of the commercial tenant and the distribution sequence position information of the commercial tenant, and screening out a distribution power swapping mode meeting the requirement on the premise of meeting the farthest driving distance d; step S3: and calculating an optimal path of each distribution battery changing mode, and screening out the distribution battery changing path with the lowest grade by taking the time of the commercial tenant arriving at the battery changing station after the commercial tenant performs the preferential distribution, the energy consumption cost of arriving at the battery changing station and the total battery changing time as evaluation factors of the distribution battery changing path of the electric automobile. The invention has the advantages of effectively increasing the income of logistics distributors, reducing the operation cost of the logistics distributors and the like.

Description

Battery-replacement type electric automobile navigation method participating in real-time logistics distribution
Technical Field
The invention mainly relates to the technical field of navigation planning of electric vehicles for logistics, in particular to a battery-swapping type electric vehicle navigation method participating in real-time logistics distribution.
Background
At present, billions of consumers of electric power merchants in China each year drive the explosive growth of the urban logistics distribution industry, the number of logistics distribution automobiles is higher and higher, the exhaust emission of the logistics distribution automobiles aggravates the deterioration of urban living environment, and aggravates urban congestion and traffic violation to a certain extent, and more pressure is brought to the urban environment and traffic. The battery-replaceable electric automobile has the characteristics of high energy conversion rate, low unit mileage travel cost, no pollution in the use process and the like; and the charging time of the battery replacement type electric automobile is short, the timeliness of logistics distribution can be met, the goods are guaranteed to arrive on time, and the battery replacement type electric automobile is the first choice for replacing the traditional fuel logistics distribution vehicle.
Most of the existing vehicle navigation technologies, such as gold, Baidu, etc., perform travel planning of the electric vehicle by collecting road and location information according to a GPS, for example: the shortest time route to the destination and the shortest distance to the destination. However, this navigation strategy is not suitable for the demand of the battery-replaceable electric vehicle in the field of logistics distribution. The power-change electric vehicle participates in logistics distribution, and various factors such as the requirements of merchants, power-change station reservation information, distribution path energy consumption and the like need to be considered. The reasonable planning and pushing of the power switching path matched with the power switching type electric automobile distribution path can maximize the benefits of logistics distribution merchants.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the technical problems in the prior art, the invention provides the battery-swapping type electric vehicle navigation method which can participate in real-time logistics distribution and can effectively increase the benefits of logistics distributors and reduce the operation cost of the logistics distributors.
In order to solve the technical problems, the invention adopts the following technical scheme:
a battery-swapping electric vehicle navigation method participating in real-time logistics distribution comprises the following steps:
step S1: acquiring the farthest driving distance d of the residual electric quantity of the electric automobile;
step S2: acquiring the position information of the power swapping station, the position information of the commercial tenant and the distribution sequence position information of the commercial tenant, and screening out a distribution power swapping mode meeting the requirement on the premise of meeting the farthest driving distance d;
step S3: and calculating an optimal path of each distribution battery changing mode, and screening out the distribution battery changing path with the lowest grade by taking the time of the commercial tenant arriving at the battery changing station after the commercial tenant performs the preferential distribution, the energy consumption cost of arriving at the battery changing station and the total battery changing time as evaluation factors of the distribution path of the electric automobile.
As a further improvement of the method of the present invention, in step S1, the battery manager of the electric vehicle outputs a current battery power E signal to compare with the set threshold, and when E is smaller than the set threshold, a charging requirement is generated, and the farthest driving distance of the remaining power is calculated as d.
As a further improvement of the method of the present invention, in step S2, the on-board wireless signal receiver receives the battery replacement station position information B1,B2…BmThe merchant position information and the merchant cargo demand information are matched and then sorted according to the cargo demand from large to small to obtain the distribution sequence position information of the merchant and record the distribution sequence position information as A1,A2…An(ii) a Screening out the delivery power changing mode S meeting the requirement on the premise of meeting the farthest driving distance dN。
As a further improvement of the method of the present invention, in step S3, the optimal path of the power distribution and swapping manner obtained by adding the optimal path for distribution between the merchants and the optimal path of the merchant-power swapping station is recorded as the optimal path of the power distribution and swapping manner
Figure BDA0002282828860000021
As a further improvement of the method, the vehicle-mounted GPS outputs the effective path with the shortest time between the merchants and the battery replacement station, if the effective path with the shortest time is only one, the effective path is used as the optimal path of the order, if the effective path with the shortest time is two or more, the energy consumption calculation is carried out on the shortest time path, and the effective path with the lowest path energy consumption is used as the optimal path between the merchants and the battery replacement station.
As a further improvement of the method, in the path evaluation and optimization process, the current distribution and battery replacement path is calculated
Figure BDA0002282828860000022
Energy consumption reaching the battery replacement station
Figure BDA0002282828860000023
Performing path evaluation; shortest time t between vehicle-mounted GPS output merchantsmixA-AShortest time t of merchant-power change station pathmixA-BAdding to obtain a current-switching electric automobile through the current distribution and current-switching path
Figure BDA0002282828860000024
Time of arrival at the battery replacement station
Figure BDA0002282828860000025
Performing path evaluation; electric automobile reservation battery replacement queuing time output by wireless signal receiver
Figure BDA0002282828860000026
And battery replacement time t of power stationmc，
Figure BDA0002282828860000027
And
Figure BDA0002282828860000028
the difference between the two is summed with tmcAdding to obtain the total battery replacement time
Figure BDA0002282828860000029
Performing path evaluation;
when receiving the current distribution and switching path of the electric automobile
Figure BDA00022828288600000210
Time of arrival at the battery replacement station
Figure BDA00022828288600000211
Cost of energy consumption to a power change station
Figure BDA00022828288600000212
And total battery replacement time tdAnd then, evaluating the current power switching delivery path, comparing the current power switching delivery path with other power switching delivery paths, outputting the power switching delivery path with the lowest score, and further determining the optimal power switching navigation path.
Compared with the prior art, the invention has the advantages that:
the invention relates to a battery replacement type electric vehicle navigation method participating in real-time logistics distribution, which aims at the situation that distribution cost is increased due to the fact that a battery replacement path of a battery replacement type electric vehicle is not matched with a distribution path. The invention can effectively increase the benefits of logistics distributors and reduce the operation cost of the logistics distributors by realizing the matching of the distribution path and the charging path.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention.
Fig. 2 is a schematic diagram of distances between merchants and between merchant swapping stations in a specific application example of the present invention.
FIG. 3 is a schematic diagram illustrating a comparison of distribution-change point path distances in an embodiment of the present invention.
FIG. 4 is a diagram of a distribution-swapping path S in an embodiment of the present invention3The path optimization diagram of (1).
Fig. 5 is a diagram illustrating the evaluation of distribution routes in an exemplary embodiment of the present invention.
Detailed Description
The invention will be described in further detail below with reference to the drawings and specific examples.
As shown in fig. 1-5, the battery-swapping electric vehicle navigation method participating in real-time logistics distribution according to the present invention comprises the steps of:
step S1: acquiring the farthest driving distance d of the residual electric quantity of the electric automobile;
step S2: acquiring the position information of the battery changing station, the position information of the commercial tenant and the distribution sequence position information of the commercial tenant; screening out a distribution power changing mode meeting the requirement on the premise of meeting the farthest driving distance d;
step S3: and calculating an optimal path of each distribution battery changing mode, and screening out the distribution battery changing path with the lowest grade by taking the time of the commercial tenant arriving at the battery changing station after the commercial tenant performs the preferential distribution, the energy consumption cost of arriving at the battery changing station and the total battery changing time as evaluation factors of the distribution path of the electric automobile.
In an embodiment, in step S1, the battery manager of the electric vehicle outputs a current battery power E signal to compare with a set threshold, and when E is smaller than the set threshold, a charging requirement is generated, and a remaining power farthest driving distance is calculated as d.
In a specific embodiment, in step S2, the on-board wireless signal receiver receives the battery replacement station location information B1,B2…BmThe merchant position information and the merchant cargo demand information are matched and then sorted according to the cargo demand from large to small to obtain the distribution sequence position information of the merchant and record the distribution sequence position information as A1,A2…An(ii) a Screening out the delivery power changing mode S meeting the requirement on the premise of meeting the farthest driving distance dN。
In a specific embodiment, in step S3, the optimal path of the power distribution and exchange manner obtained by adding the optimal path of the distribution between the merchants and the optimal path of the merchant power exchange station is recorded as the optimal path of the power distribution and exchange manner
Figure BDA0002282828860000041
In a specific embodiment, the vehicle-mounted GPS outputs the effective path with the shortest time between merchants and between the merchants and the battery replacement station, if the effective path with the shortest time is only one, the effective path is used as the optimal path of the order, if the effective path with the shortest time is two or more, the energy consumption calculation is carried out on the shortest time path, and the effective path with the smallest path energy consumption is used as the optimal path between the merchants and the battery replacement station.
In a specific embodiment, energy consumption of a path from a battery replacement type electric vehicle to a battery replacement station
Figure BDA0002282828860000042
The calculation formula is as follows:
a. when the electric automobile is in a constant speed or acceleration running state, neglecting the influence of the gradient, the driving consumed energy is as follows:
Figure BDA0002282828860000043
b. when the electric automobile is in a deceleration state, the brake energy consumption is as follows:
Figure BDA0002282828860000044
total energy consumption:
Figure BDA0002282828860000045
wherein m is the automobile mass, g is the gravity acceleration, f is the rolling resistance coefficient, delta is the rotating mass conversion coefficient, rho is the air density, CDIs the air resistance coefficient, A is the windward area,
Figure BDA0002282828860000051
in order to obtain the running speed of the automobile,
Figure BDA0002282828860000052
in order to drive the energy consumed by the motor,
Figure BDA0002282828860000053
energy expended for braking, ηbGamma is the proportion of accessory energy consumption to total energy consumption for the braking energy recovery efficiency of the electric automobile, ηmFor electric vehicle motor and controller efficiency, η is electric vehicle electric efficiency.
In the specific embodiment, in the path evaluation and optimization process, the current distribution power switching path is calculated
Figure BDA0002282828860000054
Energy consumption reaching the battery replacement station
Figure BDA0002282828860000055
Performing path evaluation; shortest time t between vehicle-mounted GPS output merchantsmixA-AShortest time t of merchant-power change station pathmixA-BAdding to obtain a current-switching electric automobile through the current distribution and current-switching path
Figure BDA0002282828860000056
Time of arrival at the battery replacement station
Figure BDA0002282828860000057
Performing path evaluation; electric automobile reservation battery replacement queuing time output by wireless signal receiver
Figure BDA0002282828860000058
And battery replacement time t of power stationmc，
Figure BDA0002282828860000059
And
Figure BDA00022828288600000510
the difference between the two is summed with tmcAdding to obtain the total battery replacement time
Figure BDA00022828288600000511
Performing path evaluation;
when receiving the current distribution and switching path of the electric automobile
Figure BDA00022828288600000512
Time of arrival at the battery replacement station
Figure BDA00022828288600000513
Cost of energy consumption to a power change station
Figure BDA00022828288600000514
And total battery replacement time tdAnd then, evaluating the current power switching delivery path, comparing the current power switching delivery path with other power switching delivery paths, and outputting the power switching delivery path with the lowest score, thereby determining the optimal power switching navigation path.
In a specific embodiment, the electric vehicle power distribution and replacement path evaluation calculation formula is as follows:
Figure BDA00022828288600000515
wherein the content of the first and second substances,
Figure BDA00022828288600000516
for the comprehensive scoring of the battery replacement type electric automobile reaching the battery replacement station through the current distribution battery replacement path, αβ is a weight coefficient, epsilon is a time sensitive factor, epsilon is set by a user,
Figure BDA00022828288600000517
for the driving time of the battery replacement type electric automobile reaching the battery replacement station through the optimal path,
Figure BDA00022828288600000518
energy consumption cost t for the battery-replacing type electric automobile to reach the battery-replacing station through the optimal pathdIs the total battery replacement time.
Taking a specific application as an example, and taking east wind, retta EM30-RTT with a battery capacity of 65.5kW/h as an example, the battery-replaceable electric vehicle navigation method participating in real-time logistics distribution of the invention is shown in fig. 1 and includes the steps of:
step S1: the battery manager outputs a current battery electric quantity E signal to be compared with a set threshold, when the E is smaller than the set threshold by 15 percent and the charging requirement is generated, the driving range d is 48km when the battery electric quantity is calculated to be 9.825 kW/h.
Step S2: the wireless signal receiver receives the position information B of the power changing station1,B2,B3,B4The merchant position information and the merchant cargo demand information are matched and then sorted according to the cargo demand from large to small to obtain the distribution sequence position information of the merchant and record the distribution sequence position information as A1,A2,A3,A4And the current electric vehicle distribution power exchange mode is obtained by outputting the current electric vehicle distribution power exchange mode to a vehicle-mounted GPS (global positioning system)1,S2,S3…S12In which S is1:A1-A2-B1；S2:A1-A2-B2；S3:A1-A2-B3；S4:A1-A2-B4；S5:A1-A2-A3-B1；S6:A1-A2-A3-B2；S7:A1-A2-A3-B3；S8:A1-A2-A3-B4；S9:A1-A2-A3-A4-B1；S10:A1-A2-A3-A4-B2；S11:A1-A2-A3-A4-B3；S12:A1-A2-A3-A4-B4。
The vehicle-mounted GPS obtains the distance between the merchants and the distance from the merchants to the battery changing station according to the received position information
Figure BDA0002282828860000061
See FIG. 2;
Figure BDA0002282828860000062
comparing with the maximum driving distance d of the electric automobile as shown in fig. 3, it is calculated that the current satisfied distribution power change mode has S1,S5,S7,S8,S12。
Step S3: to distribute and change the batteryMode S8For example, calculate A1-A2-A3-B4The optimal path between, the vehicle-mounted GPS outputs A1-A2-A3-B4Are the same distance from each other
Figure BDA0002282828860000063
Figure BDA0002282828860000064
Wherein
Figure BDA0002282828860000065
Vehicle-mounted GPS outputs each path time
Figure BDA0002282828860000066
Figure BDA0002282828860000067
Get the shortest path of time
Figure BDA0002282828860000068
Calculating the energy consumption
Figure BDA0002282828860000069
Figure BDA00022828288600000610
Figure BDA00022828288600000611
Is S8Optimal distribution and battery replacement path S8mixFIG. 4 is S8Path optimization map of (1). Distribution battery replacement mode S calculated by the same principle1,S5,S7,S12Is optimized path S1mix、S5mix、S7mix、S12mixAre respectively as
Figure BDA00022828288600000612
M in the energy consumption calculating module is 2.6 multiplied by 103，f＝0.018，δ＝1.1，ρ＝1.2208kg/m3，CD＝0.3，A＝4.7082m2，
Figure BDA00022828288600000613
ηbCalculated as S, 0.2, and γ 0.21,S5,S7,S8,S12Respectively, the optimal energy consumption is
Figure BDA00022828288600000614
Figure BDA00022828288600000615
Will be provided with
Figure BDA00022828288600000616
And outputting the data to a distribution path evaluation module.
Vehicle-mounted GPS (global positioning system) for outputting shortest time t of distribution path of commercial tenantmixA-AShortest time t from commercial tenant to power change stationmixA-BAdding to obtain the current path S of the battery-replacing electric automobileNTime of arrival at the battery replacement station
Figure BDA0002282828860000071
Is calculated to
Figure BDA0002282828860000072
Figure BDA0002282828860000073
Will be provided with
Figure BDA0002282828860000074
And outputting the data to a distribution path evaluation module.
Electric automobile reservation battery replacement queuing time output by wireless signal receiver
Figure BDA0002282828860000075
Figure BDA0002282828860000076
And battery replacement time t of power stationmc＝300p，
Figure BDA0002282828860000077
And
Figure BDA0002282828860000078
the difference between the two is summed with tmcAdding to obtain the total battery change time
Figure BDA0002282828860000079
Figure BDA00022828288600000710
Will be provided with
Figure BDA00022828288600000711
Outputting the data to a distribution path evaluation module;
the distribution path evaluation module receives the time when the battery replacement type electric automobile reaches the battery replacement station through the current distribution battery replacement path
Figure BDA00022828288600000712
Time required for completing battery replacement after reaching the battery replacement station
Figure BDA00022828288600000713
And energy cost to reach the power change station
Figure BDA00022828288600000714
The distribution route evaluation was performed, wherein α ═ 0.3, β ═ 0.4, and ε ═ 0.3, and the evaluation was calculated as shown in FIG. 5, and the distribution route evaluation was performed as follows
Figure BDA00022828288600000715
Figure BDA00022828288600000716
Path to be scored lowest
Figure BDA00022828288600000717
Outputting to determine the optimal path of the commercial tenant and the power change station
Figure BDA00022828288600000718
And providing an optimal battery replacement navigation path for the battery replacement electric automobile.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.

Claims (6)

1. The battery-swapping type electric vehicle navigation method participating in real-time logistics distribution is characterized by comprising the following steps of:
step S1: acquiring the farthest driving distance d of the residual electric quantity of the electric automobile;
step S2: acquiring the position information of the power swapping station, the position information of the commercial tenant and the distribution sequence position information of the commercial tenant, and screening out a distribution power swapping mode meeting the requirement on the premise of meeting the farthest driving distance d;
step S3: and calculating an optimal path of each distribution battery changing mode, and screening out the distribution battery changing path with the lowest grade by taking the time of the commercial tenant arriving at the battery changing station after the commercial tenant performs the preferential distribution, the energy consumption cost of arriving at the battery changing station and the total battery changing time as evaluation factors of the distribution path of the electric automobile.
2. The method as claimed in claim 1, wherein in step S1, the battery manager of the electric vehicle outputs a current battery power E signal to compare with a set threshold, and when E is smaller than the set threshold, a charging requirement is generated, and a distance d of the electric vehicle is calculated as the maximum driving distance of the remaining power.
3. The method for battery replacement type electric vehicle navigation participating in real-time logistics distribution as claimed in claim 1, wherein in step S2, the wireless signal receiver on the vehicle receives the battery replacement station location information B1,B2…BmThe merchant position information and the merchant cargo demand information are matched and then sorted according to the cargo demand from large to small to obtain the merchant allocationSending sequence position information is recorded as A1,A2…An(ii) a Screening out the delivery power changing mode S meeting the requirement on the premise of meeting the farthest driving distance dN。
4. The battery-swapping type electric vehicle navigation method participating in real-time logistics distribution as claimed in claim 1, wherein in step S3, the optimal path of the battery swapping mode for distribution obtained by adding the optimal path for distribution among the merchants to the optimal path for the merchant-battery swapping station is recorded as the optimal path of the battery swapping mode for distribution
Figure FDA0002282828850000011
5. The battery replacement type electric vehicle navigation method participating in real-time logistics distribution according to claim 4, wherein the vehicle-mounted GPS outputs the shortest effective path between the merchants and the battery replacement station, if the shortest effective path has only one effective path, the effective path is used as the optimal path of the order, if the shortest effective path has two or more effective paths, the energy consumption calculation is performed on the shortest time path, and the effective path with the lowest path energy consumption is used as the optimal path between the merchants and the battery replacement station.
6. The electric vehicle navigation method for participating in real-time logistics distribution of any one of claims 2-5, wherein in the path evaluation and optimization process, the current distribution and battery replacement path is calculated
Figure FDA0002282828850000021
Energy consumption reaching the battery replacement station
Figure FDA0002282828850000022
Performing path evaluation; shortest time t between vehicle-mounted GPS output merchantsmixA-AShortest time t of merchant-power change station pathmixA-BAdding to obtain a current-switching electric automobile through the current distribution and current-switching path
Figure FDA0002282828850000023
Time of arrival at the battery replacement station
Figure FDA0002282828850000024
Performing path evaluation; electric automobile reservation battery replacement queuing time output by wireless signal receiver
Figure FDA0002282828850000025
And battery replacement time t of power stationmc，
Figure FDA0002282828850000026
And
Figure FDA0002282828850000027
the difference between the two is summed with tmcAdding to obtain the total battery replacement time
Figure FDA0002282828850000028
Performing path evaluation;
when receiving the current distribution and switching path of the electric automobile
Figure FDA0002282828850000029
Time of arrival at the battery replacement station
Figure FDA00022828288500000210
Cost of energy consumption to a power change station
Figure FDA00022828288500000211
And total battery replacement time tdAnd then, evaluating the current power switching delivery path, comparing the current power switching delivery path with other power switching delivery paths, outputting the power switching delivery path with the lowest score, and further determining the optimal power switching navigation path.
CN201911148275.9A 2019-11-21 2019-11-21 Battery-replacement type electric automobile navigation method participating in real-time logistics distribution Pending CN111216571A (en)

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