Multiobjective Optimization of Large-Scale EVs Charging Path Planning and Charging Pricing Strategy for Charging Station

Algorithm 3

The proposed EHBMA.

	Initialization
	Initialize the average velocity of each road link based on the traffic condition.
	Calculate the energy consumption and driving time of the road link based on the energy consumption model and average velocity.
	Calculate the shortest distance from each charging station to each node on the map and save the result as a dictionary in which the keys are charging station nodes and the values are all other nodes on the map.
	Initialize the location of the EV, .
	Charging Path Planning
	Select three charging stations closest to the current location by query the data .
(1)	For
(2)	Create a forward list and a backward list
(3)	The initial elements in and are the label of the starting point , , and the label of the end point ,
(4)	Create the path set
(5)	The initial search direction is forward
(6)	While is not dominated by the label in
(7)	If, Then get the minimum node label in
(8)	For the child adjacent node of ,
(9)	Calculate the heuristic items by query
(10)	Calculate the node label of the adjacent node,
(11)	If is not dominated by other node label of , Then put into
(12)	If, Then get the minimum node label in
(13)	For the parent adjacent node of ,
(14)	Calculate the heuristic items
(15)	Calculate the node label of the adjacent node,
(16)	If is not dominated by other node label of , Then put into
(17)	If the label of is in the list of reverse direction, Then get a path by return the previous node label in and, and add the path into
(18)	Change direction to the opposite
(19)	Pareto Path Selection
(20)	For, its end point is a charging station ,
(21)
(22)
(23)
(24)
(25)	Calculate the driver preference .
(26)	Select charging path and charging station of the smallest , which is the final planned path recommended to the EV users.