车-路协同电动汽车动态无线充电的路权调度控制

doi:10.12263/DZXB.20200954

电子学报 ›› 2021, Vol. 49 ›› Issue (5): 904-911.DOI: 10.12263/DZXB.20200954

所属专题：面向自动驾驶和智慧交通协同的通信与控制

• 面向自动驾驶和智慧交通协同的通信与控制 • 上一篇下一篇

车-路协同电动汽车动态无线充电的路权调度控制

周熙炜, 汪贵平, 王会峰, 尚宵

长安大学电子与控制工程学院, 陕西西安 710064

收稿日期:2020-08-31 修回日期:2020-11-26 出版日期:2021-05-25
- 作者简介:
- 周熙炜 男,1975年生,陕西兴平人.博士,副教授.主要研究领域为电动汽车无线充电技术,多目标优化控制等.;汪贵平 男,1963年生,湖北麻城人.教授,博士生导师.主要研究领域为车路协同环境下智能车控制与测试、交通信息及控制技术等. E-mail:gpwang@chd.edu.cn;王会峰 男,1976年生,山西运城人.教授,博士生导师.主要研究领域为车路协同智能驾驶环境信息灵巧感知与协同控制等. E-mail:hfwang@chd.edu.cn;尚宵女,1995年生,陕西咸阳人.硕士研究生.主要研究领域为多目标优化控制、交通信息及控制技术等. E-mail:540208376@qq.com
- 基金资助:
- 国家重点研发计划 (No.2018YFB1600600）; 陕西省重点研发计划一般项目 (No.2018GY-065）; 西安市科技项目 (No.2020KJRC0123）

The Scheduling Control Strategy for In-motion EV Wireless Charging Based on Cooperative Vehicle Infrastructure System

ZHOU Xi-wei, WANG Gui-ping, WANG Hui-feng, SHANG Xiao

School of Electronics and Control Engineering, Chang'an University, Xi'an, Shaanxi 710064, China

Received:2020-08-31 Revised:2020-11-26 Online:2021-05-25 Published:2021-05-25

摘要/Abstract

摘要： 在高级公路中设置无线充电专用道路,对行驶中的电动车辆进行动态无线充电,引发了交通工程领域的深刻变革.然而在最大限度的保证电动车辆充电能效的前提下,如何对这类车辆进行调度和管理,以提高行车安全和道路的通行能力是一个无法回避的关键问题.为此,本文首先建立了系统的车辆调度模型.然后提出了一种新的精英反向变异粒子群算法(Reverse Elitist Mutation Particle Swarm Optimization,REMPSO),通过与传统的粒子群和遗传算法的比对,证明了该算法的稳定性和寻优能力.然后使用这一算法对系统模型进行求解,得出充电行驶中的优化移动隔离分区.通过车-路协同为电动汽车动态无线充电的路权调度提供了一种可行的控制策略.

关键词: 车路协同, 电动汽车, 动态无线充电, 粒子群算法, 路权调度

Abstract: Special roads set up in highway used to realize dynamic wireless charging for In-motion electric vehicles that leads to a profound change in the field of traffic engineering.However,on the premise of the maximum charging effect of EV,how to schedule and manage such vehicles to improve traffic safety and road capacity is a key issue that cannot be avoided.Therefore,this paper first establishes the vehicle scheduling model of the system.A new reverse elitist mutation particle swarm optimization (REMPSO) algorithm is proposed.And its rapidity,stability and optimization ability are proved by comparing with the traditional particle swarm optimization and genetic algorithm.Finally,this algorithm is used to solve the system model,and the optimal moving isolation partition is obtained.Based on cooperative vehicle infrastructure system,The paper provides a feasible control strategy for the right of way scheduling of dynamic wireless charging for In-motion EV.

Key words: cooperative vehicle infrastructure system, electric vehicles, dynamic wireless charging, particle swarm algorithm, scheduling

中图分类号:

TP11
U495

周熙炜, 汪贵平, 王会峰, 尚宵. 车-路协同电动汽车动态无线充电的路权调度控制[J]. 电子学报, 2021, 49(5): 904-911.

ZHOU Xi-wei, WANG Gui-ping, WANG Hui-feng, SHANG Xiao. The Scheduling Control Strategy for In-motion EV Wireless Charging Based on Cooperative Vehicle Infrastructure System[J]. Acta Electronica Sinica, 2021, 49(5): 904-911.

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车-路协同电动汽车动态无线充电的路权调度控制

The Scheduling Control Strategy for In-motion EV Wireless Charging Based on Cooperative Vehicle Infrastructure System

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