Charging strategy and routing optimization of electric vehicles under dynamic load

被引：0
|
作者：
Huang J. [1 ]
Liu F. [1 ]
机构：
[1] School of Economics and Management, Fuzhou University, Fuzhou
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2023年 / 29卷 / 11期
关键词：
charging strategy; dynamic load; electric vehicles; hybrid genetic annealing algorithm; vehicle routing optimization;
D O I：
10.13196/j.cims.2021.0412
中图分类号：
学科分类号：
摘要：
In view of affection of load on power consumption rate in electric vehicle distribution process, a vehicle routing optimization model with soft time window was formulated to minimize the comprehensive cost, such as fixed cost, driving cost, power charging cost and time window penalty cost. An improved hybrid genetic annealing algorithm was designed to solve the problem, and then the power consumption rate and incomplete charging strategy of electric vehicles under dynamic load were discussed. The validity of the model and algorithm was verified by taking electric vehicle distribution service of fresh enterprise as an example. The results showed that an incomplete charging strategy had significant advantages over the complete charging strategy in case of charging time, driving distance and distribution cost under dynamic load of vehicles. Compared with the classical genetic algorithm, the improved hybrid genetic annealing algorithm could converge to optimal solutions quickly and effectively. © 2023 CIMS. All rights reserved.
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收藏
页码：3909 / 3921
页数：12
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