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An analysis method for electric vehicle travel and charging demand considering charging feedback effect

A technology for electric vehicles and charging requirements, applied in data processing applications, instruments, calculations, etc., can solve the problems of travel demand changes in time and space distribution, without considering the impact of charging facilities, etc.

Active Publication Date: 2021-06-08
TIANJIN UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the analysis of charging demand, the existing research thinks that the charging facilities can fully meet any charging demand, and does not consider the influence of the distribution of charging facilities on the charging demand of electric vehicles. Changes due to the distribution of charging facilities

Method used

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  • An analysis method for electric vehicle travel and charging demand considering charging feedback effect
  • An analysis method for electric vehicle travel and charging demand considering charging feedback effect
  • An analysis method for electric vehicle travel and charging demand considering charging feedback effect

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[0117] The simulation is carried out in the destination mode, so the urban traffic network is reasonably simplified and the relevant information of the main parking lots (parking nodes) where users park in the simulated area is given. The specific information is shown in Table 2. There are a total of 4,000 electric vehicles in the simulation area. Referring to the technical parameters of Nissan Leaf, the lithium battery capacity of electric vehicles is C EV = 48kW·h, power consumption E for driving 100km 100 = 15kWh, cruising range X D =160km, charging power q=6kW, average driving speed v=40km / h. It is assumed that the initial state of charge of electric vehicles conforms to the normal distribution of N (0.51, 0.18). The constant c that reflects factors such as weather and road conditions is a random number of (1, 1.5]. The elastic coefficient m 1 = 1.2, fuzzy coefficient m 2 = 2, support factor n 1 =1.05, the time interval of time series interaction simulation dt=15min....

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Abstract

An analysis method of electric vehicle travel and charging demand considering the charging feedback effect: modeling of electric vehicle user travel demand in destination mode; time-series interactive analysis of travel and charging demand, and establishing power consumption based on travel demand when the user is in the driving state Model, establish a charging demand generation model based on fuzzy theory when the user is in the driving state, establish a power replenishment model considering the adequacy of charging facilities when the user is in the staying state, and make user difference decisions based on the charging feedback effect when the user is in the leaving state ; Time-series interactive simulation of user travel and charging demand. The invention can realize the time sequence interaction between the travel demand and the charging demand of the electric vehicle user, and analyze the change trend of the charging demand of the user and the hysteresis and recovery of the travel demand.

Description

technical field [0001] The invention relates to a method for predicting and analyzing the charging load of an electric vehicle. In particular, it relates to an electric vehicle travel and charging demand analysis method that considers the charging feedback effect and is applicable to the charging demand of private electric vehicle users in the destination mode. Background technique [0002] Facing the increasingly serious shortage of resources and environmental pollution, my country has launched a study on the timetable for banning the sale of fuel vehicles. Due to its huge advantages in energy consumption and environmental performance, electric vehicles have become the future development direction of new energy vehicles and have been vigorously developed. Private cars are the main targets for the popularization of electric vehicles in the future. Because of their travel characteristics of long staying time and short driving time, they tend to charge at destinations, that i...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06Q50/06
CPCG06Q10/06315G06Q50/06
Inventor 刘洪张旭葛少云
Owner TIANJIN UNIV
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