PLANNING METHOD OF ELECTRIC VEHICLE FAST CHARGING STATIONS ON THE EXPRESSWAY

• US 20180240047A1
• Filed: 08/28/2015
• Published: 08/23/2018
• Est. Priority Date: 08/19/2015
• Status: Active Grant

• Current Assignee: Tianjin University
• Original Assignee: Tianjin University
• Inventors: MU, Yunfei, DONG, Xiaohong, JIA, Hongjie, YU, Xiaodan
• Granted Patent: US 10,360,519 B2
• Time in Patent Office: Days
• CPC Class Codes: B60L 2240/72 Charging station selection relying on external data
• CPC Class Codes: B60L 2240/80 Time limits
• CPC Class Codes: B60L 53/11 DC charging controlled by the charging station, e.g. mode 4
• CPC Class Codes: B60L 53/14 Conductive energy transfer
• CPC Class Codes: B60L 53/66 Data transfer between charging stations and vehicles
• CPC Class Codes: B60L 53/67 Controlling two or more charging stations
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: Y02T 10/70 Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 10/72 Electric energy management in electromobility
• CPC Class Codes: Y02T 90/12 Electric charging stations
• CPC Class Codes: Y02T 90/14 Plug-in electric vehicles
• CPC Class Codes: Y02T 90/16 Information or communication technologies improving the operation of electric vehicles

Abstract

A planning method of EV fast charging stations on the expressway, comprising the following steps: Step 1: forecasting the spatial and temporal distribution of EV charging load, that is to determine the time and location of each EV needing charging on the expressway; Step 2: based on the forecast result achieved by Step 1, determining the locations of the fast charging stations on the expressway by the nearest neighbor clustering algorithm; Step 3: according to the spatial and temporal forecast result of the EV charging load and the locations of the fast charging stations, determining the number c of the chargers in each fast charging station by queuing theory. Due to battery characteristics, traditional gas stations do not completely match the fast charging stations. In the planning method, the locations and times for charging of the EVs are considered to determine the capacities and locations of the fast charging stations, which can meet the charging needs of the EVs more than the traditional gas station, and thus promote the development of EVs.

Claims

1. A planning method of EV fast charging stations on the expressway, comprising forecasting the spatial and temporal distribution of EV charging load, determining the locations of the EV fast charging stations and determining the number of the chargers in each fast charging station;

the detailed steps of the planning method are as follows;

Step 1;

forecasting the spatial and temporal distribution of EV charging load, that is to determine the time and location of each EV needing charging on the expressway;

Step 2;

based on the forecast result achieved by Step 1, determining the locations of the fast charging stations on the expressway by the nearest neighbor clustering algorithm, which further includes the following steps;

Step 2-1;

calculating the maximum travel range Ran_sc after the EVs need charging;

based on the central limit theorem, determining the travel distance of 99% EVs under the remaining capacity of batteries by fitted normal distribution, wherein the travel distance is defined as the service radius SR of the fast charging stations;

Step 2-2;

determining the distance matrix D, where d_ij represents the distance between the EV location needing charging P_i to the EV location needing charging P_j, i and j belongs to 1˜

n, and n represents the total number of the EVs needing charging;

Step 2-3;

determining the similarity matrix S;

based on the distance matrix D, determining the number of the EV locations needing charging within the service radius SR of each EV location needing charging;

the similarity s_ij of the EV location needing charging P_i and the EV location needing charging P_j is defined in the equation (5);

s_ij=size(NN(i)∩

NN(j))  

 

(5)

Wherein, NN(i) and NN(j) are the sets of the EV locations needing charging within the service radius SR of the EV location needing charging P_i and P_i, respectively;

the “

size”

means the shared number of the EV locations needing charging in the intersection set of NN(i) and NN(j);

Step 2-4;

calculating the EV charging demand l_1,j of each location needing charging according to the sum of the rows of the similarity matrix S by the following equation;

2. The planning method of EV fast charging stations on the expressway according to claim 1, wherein the Step 1 further includes the following steps:

Step 1-1;

obtaining the following basic data;

EV data;

including the EV types, the probability density function of battery capacity for each EV type, the upper and lower boundary of the battery capacity for each EV type and the mathematical relationship between battery capacity and EV maximum travel range thereof;

Traffic data;

including the probability matrix P<sub>m×

m</sub> of traffic origin and destination point and the probability distribution of the time t_s when the car entered the expressway;

Obtaining the traffic origin-destination matrix A<sub>m×

m</sub> of the expressway entrance &

exit through the investigation data of traffic origin and destination points, and obtaining the matrix P<sub>m×

m</sub> according to the equation (1) by using the matrix A<sub>m×

m</sub>;

p_ij=a_ij/B_i(1≤

i≤

m,1≤

j≤

m)  

 

(1)

In the equation (1), m is the number of the expressway entrance &

exit;

a_ij is the daily average EV number passing through the expressway entrance &

exit i to the expressway entrance &

exit j;

p_ij is the daily probability of a vehicle passing through the expressway entrance &

exit i to the expressway entrance &

exit j, B_i is the daily average vehicle number entering the expressway via the expressway entrance &

exit i;

3. The planning method of EV fast charging stations on the expressway according to claim 1 or 2, wherein the Step 3 further includes the following steps:

Step 3-1;

determining the peak value of EVs arrived at each fast charging station per hour by using the time of each EV needing charging achieved by the Step 1 and the locations of the fast charging stations achieved by the Step 2;

setting the peak value as the number λ

, of reaching the fast charging station per hour for EVs;

Step 3-2;

determining the chargers'"'"' number of each fast charging station c;

Calculating the average length L_s of waiting queue and the waiting time W_q by the following equations;