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.
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.
作者
周熙炜
汪贵平
王会峰
尚宵
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)
出处
《电子学报》
EI
CAS
CSCD
北大核心
2021年第5期904-911,共8页
Acta Electronica Sinica
基金
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)。
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
cooperative vehicle infrastructure system
electric vehicles
dynamic wireless charging
particle swarm algorithm
scheduling
