Reserving Charging Decision-Making Model and Route Plan for Electric Vehicles Considering Information of Traffic and Charging Station
Abstract
:1. Introduction
- (1)
- The proposed reserving charging decision-making model simultaneously involves the information of traffic conditions, charging resources and charging prices, as well as charging and moving performance of electric vehicles, so that charging reservations and route plans are more feasible.
- (2)
- Considering both energy consumption and time consumption from the initial position to the destination passing by a charging station, an optimization model with two objective functions is established. In this way, to obtain feasible solution set of optimizations, the weight of each graph edge of traffic network is respectively set as driving time and driving distance.
2. Background
3. Characteristics of Transportation Network, Charging Stations and Electric Vehicles
3.1. Transportation Network Model
3.2. Charging Station Model
3.2.1. Available Charging Piles
3.2.2. Minimal Waiting Time at Charging Stations
3.2.3. Charging Prices
3.3. Electric Vehicle Model
3.3.1. Charging Characteristics of EV
3.3.2. Moving Characteristics of EV
4. Information Interactive Mechanism and Credit Mechanism
4.1. Information Interactive Mechanism Involving Vehicle Navigation, Charging Stations and EV
4.1.1. EV Battery Energy Management System
4.1.2. Operation Management System of Charging Station
4.1.3. Vehicle Navigation System
4.1.4. Information Interactive Mechanism
- (1)
- The information interaction between every involved part is reliable and safe.
- (2)
- Time delay during the process of information transmission and information processing is small enough and can be ignored.
4.2. Credit Mechanism
5. Reserving Charging Decision-Making Model
5.1. Objective Functions
5.1.1. Objective of Minimizing Driving Time
5.1.2. Objective of Minimizing Charging Expenses
5.2. Constraint Conditions
6. Solution Procedure
6.1. Weighted Directed Graph Based K Shortest Paths Algorithm
6.2. Solving Procedure
- (1)
- When charging request is proposed, the reserving charging system obtains information of the EV (including position, destination, remaining SOC and expected SOC when arriving at destination), information of traffic conditions (including topology, traffic volume and maximum speed limit), and information of charging resources (including positions of charging stations, available charging piles and charging prices).
- (2)
- For charging station i, the reserving charging system searches for K shortest routes from initial position to the charging station using K shortest paths algorithm and calculates the driving distances. If station i is out of remaining mileage range of the EV, it is out of option.
- (3)
- Reserving charging system calculates driving distances, driving time and energy consumptions of K routes from i-th charging station to destination based on K shortest paths algorithm.
- (4)
- Reserving charging system calculates needed charging power, charging time and waiting time at i-th charging station. If waiting time at station i is longer than a given value, i-th charging station is out of option.
- (5)
- Reserving charging system calculates charging fees C and total time consumption T for choosing charging station i and corresponding routes.
- (6)
- Reserving charging system respectively obtains results with minimal time consumption and minimal charging expense among all possible routes obtained through K shortest paths algorithm.
- (7)
- The EV user chooses reserving charging strategy and route according to his/her preference for time consumption and expenses, and submits the reservation, including starting time and finishing time of charging.
- (8)
- Charging stations check reservation information. If reservation request is not accepted by selected charging station, the EV user has to turn to the suboptimal charging station, until charging reservation is accepted by a certain charging station.
7. Case Studies
7.1. Data Information
7.2. Reserving Charging Strategy and Route Selection With Minimal Time Consumption
7.3. Reserving Charging Strategy and Route Selection with Minimal Expense
7.4. Analysis of Optimal Results with Different Weights for Two Objectives
8. Conclusions
Author Contributions
Acknowledgments
Conflicts of Interest
Appendix A
Road (p,q) | Road Length lpq (km) | Average Speed vpq (km/hour) | Road (p,q) | Road Length lpq (km) | Average Speed vpq (km/hour) | Road (p,q) | Road Length lpq (km) | Average Speed vpq (km/hour) |
---|---|---|---|---|---|---|---|---|
(1,2) | 3.5 | 40 | (18,11) | 4.7 | 60 | (35,26) | 5.4 | 70 |
(1,5) | 6.8 | 60 | (18,19 | 2 | 60 | (35,34) | 3.4 | 50 |
(1,10) | 10.5 | 60 | (18,26) | 2 | 60 | (35,36) | 2.2 | 40 |
(2,1) | 3.5 | 40 | (19,12) | 4 | 40 | (35,39) | 2.9 | 50 |
(2.3) | 3.3 | 40 | (19,18) | 2 | 60 | (36,27) | 4.4 | 40 |
(2,6) | 5.4 | 60 | (19,20) | 2.8 | 60 | (36,35) | 2.2 | 40 |
(3,2) | 3.3 | 40 | (19,27) | 2 | 50 | (36,40) | 2.3 | 40 |
(3,4) | 5.8 | 50 | (20,13) | 4 | 50 | (37,28) | 5 | 40 |
(3,7) | 5.4 | 50 | (20,19) | 2.8 | 70 | (37,38) | 5.1 | 40 |
(4,3) | 5.8 | 50 | (20,21) | 5.5 | 50 | (37,40) | 2.1 | 60 |
(4,8) | 8.5 | 40 | (20,28) | 2.2 | 40 | (38,29) | 7.4 | 40 |
(4,25) | 15 | 40 | (21,20) | 5.5 | 70 | (38,37) | 5.1 | 40 |
(5,1) | 6.8 | 60 | (21,22) | 3.2 | 60 | (38,41) | 2.1 | 50 |
(5,6) | 2.6 | 40 | (22,16) | 3.1 | 40 | (39,35) | 2.9 | 70 |
(5,11) | 5.4 | 70 | (22,21) | 3.2 | 70 | (39,40) | 2 | 60 |
(6,2) | 5.4 | 60 | (22,23) | 2 | 60 | (39,43) | 7.7 | 30 |
(6,5) | 2.6 | 60 | (22,29) | 4.3 | 40 | (39,47) | 4.1 | 60 |
(6,7) | 3 | 50 | (23,16) | 4 | 40 | (40,36) | 2.3 | 40 |
(7,3) | 5.4 | 50 | (23,22) | 2 | 60 | (40,37) | 2.1 | 60 |
(7,6) | 3 | 70 | (23,24) | 2 | 60 | (40,39) | 2 | 60 |
(7,8) | 2.5 | 50 | (23,30) | 4.7 | 40 | (40,41) | 6.3 | 50 |
(7,14) | 3 | 40 | (24,9) | 8.7 | 60 | (41,38) | 2.1 | 50 |
(8,4) | 8.5 | 40 | (24,23) | 2 | 60 | (41,40) | 6.3 | 50 |
(8,7) | 2.5 | 70 | (24,25) | 6 | 50 | (41,42) | 4.8 | 60 |
(8,9) | 1.2 | 40 | (24,31) | 4.6 | 50 | (41,43) * | 2.4 | 40 |
(8,15) | 3 | 60 | (25,4) | 15 | 40 | (42,30) | 4.8 | 50 |
(9,8) | 1.2 | 60 | (25,24) | 6 | 50 | (42,41) | 4.8 | 60 |
(9,16) | 2.6 | 50 | (25,33) | 10.4 | 60 | (42,46) | 3 | 50 |
(9,24) | 8.7 | 60 | (26,17) | 4.4 | 40 | (43,39) | 7.7 | 30 |
(10,1) | 10.5 | 60 | (26,18) | 2 | 70 | (43,44) | 1.6 | 60 |
(10,11) | 3.4 | 50 | (26,27) | 2.2 | 60 | (43,48) | 4.8 | 60 |
(10,17) | 5.8 | 40 | (26,35) | 5.4 | 50 | (44,43) | 1.6 | 60 |
(11,5) | 5.4 | 40 | (27,19) | 2 | 40 | (44,45) | 2.4 | 50 |
(11,10) | 3.4 | 50 | (27,26) | 2.2 | 60 | (44,49) | 4.8 | 40 |
(11,12) | 2.8 | 40 | (27,28) * | 2.1 | 40 | (45,44) | 2.4 | 50 |
(11,18) | 4.7 | 60 | (27,36) | 4.4 | 40 | (45,46) | 3.5 | 40 |
(12,11) | 2.8 | 30 | (28,20) | 2.2 | 40 | (45,50) | 5 | 50 |
(12,13) | 2.2 | 30 | (28,37) | 5 | 40 | (46,32) | 5 | 40 |
(12,19) | 4 | 40 | (29,22) | 4.3 | 40 | (46,42) | 3 | 50 |
(13,12) | 2.2 | 30 | (29,30) | 1.7 | 60 | (46,45) | 3.5 | 40 |
(13,14) | 5 | 30 | (29,38) | 7.4 | 40 | (46,51) | 3.3 | 40 |
(13,20) | 4 | 50 | (30,23) | 4.7 | 40 | (47,34) | 4.5 | 40 |
(14,7) | 3 | 40 | (30,29) | 1.7 | 60 | (47,39) | 4.1 | 60 |
(14,13) | 5 | 30 | (30,31) * | 2.8 | 50 | (47,48) | 10.8 | 50 |
(14,15) | 1.4 | 60 | (30,42) | 4.8 | 50 | (48,43) | 4.8 | 60 |
(14,21) * | 3.3 | 40 | (31,24) | 4.6 | 50 | (48,47) | 10.8 | 50 |
(15,8) | 3 | 60 | (31,32) | 1.8 | 40 | (48,49) | 1.8 | 40 |
(15,14) | 1.4 | 30 | (32,31) | 1.8 | 40 | (49,44) | 4.8 | 40 |
(15,16) | 2 | 40 | (32,33) | 5.5 | 50 | (49,48) | 1.8 | 40 |
(16,9) | 2.6 | 50 | (32,46) | 5 | 40 | (49,50) | 2.7 | 60 |
(16,15) | 2 | 30 | (33,25) | 10.4 | 60 | (50,45) | 5 | 50 |
(16,22) | 3.1 | 40 | (33,32) | 5.5 | 50 | (50,49) | 2.7 | 60 |
(16,23) | 4 | 40 | (33,51) | 7.7 | 40 | (50,51) | 7.2 | 40 |
(17,10) | 5.8 | 40 | (34,17) | 8.8 | 50 | (51,33) | 7.7 | 40 |
(17,26) | 4.4 | 40 | (34,35) | 3.4 | 50 | (51,46) | 3.3 | 40 |
(17,34) | 8.8 | 50 | (34,47) | 4.5 | 40 | (51,50) | 7.2 | 40 |
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Charging Station | Nearest Node | Distance from Node (km) | Number of Piles |
---|---|---|---|
#1 | 12 | 0 | 4 |
#2 | 40 | 0 | 4 |
#3 | 9 | 1 | 5 |
#4 | 46 | 1 | 6 |
#5 | 30 | 0 | 4 |
#6 | 36 | 0 | 4 |
Weight for Time Consumption | Preferred Charging Station | Time Consumption (min) | Total Expense (RMB) |
---|---|---|---|
Case 1: ω1 ≤ 0.68 | #2 | 87.6 | 17.9 |
Case 2: ω1 > 0.68 | #2 | 70.6 | 22.0 |
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Liu, H.; Yin, W.; Yuan, X.; Niu, M. Reserving Charging Decision-Making Model and Route Plan for Electric Vehicles Considering Information of Traffic and Charging Station. Sustainability 2018, 10, 1324. https://doi.org/10.3390/su10051324
Liu H, Yin W, Yuan X, Niu M. Reserving Charging Decision-Making Model and Route Plan for Electric Vehicles Considering Information of Traffic and Charging Station. Sustainability. 2018; 10(5):1324. https://doi.org/10.3390/su10051324
Chicago/Turabian StyleLiu, Haoming, Wenqian Yin, Xiaoling Yuan, and Man Niu. 2018. "Reserving Charging Decision-Making Model and Route Plan for Electric Vehicles Considering Information of Traffic and Charging Station" Sustainability 10, no. 5: 1324. https://doi.org/10.3390/su10051324