A charging path optimization method for electric vehicles based on user travel rules

Abstract

The invention discloses a method for optimizing a charging path of an electric automobile based on user travel rules. The method comprises the following steps: (1) counting the owner travel characteristic; (2) performing data acquisition, wherein the data comprises data related to the electric automobile travel characteristic as well as data of charging stations and road congestion conditions; (3)establishing a traffic network, namely establishing a regional traffic network comprising nodes and two-way edges; (4) performing data analysis and processing, namely counting habitual charging stations and charging time of the owner, generating corresponding travel links, and correcting the analytical result according to the survey results in the (1); (5) establishing an electric automobile charging path optimization model; and (6) selecting the optimal charging requirement guided traveling path integrating the charging time, traveling path and cost for owner preference from the multiple travel links by utilizing the electric automobile charging path optimization model. According to the method disclosed by the invention, the travel path corresponding to the travel requirements is provided for the user by fully considering the regional historical circumstances and user charging habits, the defect that the real-time path planning system has harsh requirements on communication hardwarefacilities is overcome, and the charging path is personalized.

Description

technical field [0001] The invention relates to the technical field of electric vehicle charging and navigation, in particular to an electric vehicle charging path optimization method based on user travel rules. Background technique [0002] With the rapid promotion of new energy vehicles and the construction and improvement of charging infrastructure, electric vehicles have been popularized in my country on a large scale. How to ensure the enthusiasm of electric vehicle owners is crucial to the accelerated development of electric vehicles. [0003] As a mobile load, electric vehicles will inevitably bring impact to the power grid and aggravate traffic congestion if there is no reasonable charging control strategy. The decline will ultimately affect the promotion and use of electric vehicles. Existing charging control strategies are mainly aimed at a large number of electric vehicles, with the goal of ensuring global optimality, but rarely consider the charging path and cha...

AI Technical Summary

Problems solved by technology

[0003] As a mobile load, electric vehicles will inevitably bring impact to the power grid and aggravate traffic congestion if there is no reasonable charging control strategy. decline, which will ultimately affect the promotion and use of electric vehicles

Existing charging control strategies are mainly aimed at a large number of electric vehicles, with the goal of ensuring global optimality, but rarely consider the charging path and charging power of a single electric vehicle, and lack personalized charging navigation proliferation services for individual users

At the same time, most of the existing route optimization is real-time optimization, which requires users to manually input the starting and ending positions, and needs to obtain real-time traffic conditions and real-time conditions in the charging station. It has high requirements for communication systems and hardware facilities. If it is damaged, the planning result will have problems or even fail to proceed

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