电气技术2025，Vol.26Issue(3)：36-41,48,7.
基于遗传算法的电动重卡充换电站充电策略优化
Optimization of charging strategy for electric heavy truck charging and swapping stations based on genetic algorithm
王博 1杨克南 1杨迎春 2王少鹏 2韩锦峰3
作者信息
- 1. 许继电气股份有限公司,河南 许昌 461000
- 2. 许昌许继软件技术有限公司,河南 许昌 461000
- 3. 郑州大学材料科学与工程学院,郑州 450001
- 折叠
摘要
Abstract
Electric heavy truck charging and swapping stations are developing rapidly,and battery charging strategies have an important impact on station-side operating costs and user battery swapping experience.How to meet the daily battery swapping needs of electric heavy trucks while minimizing station-side operating costs and shortening user battery swapping waiting time is a key research direction.First,a certain electric heavy truck charging and swapping station is taken as the experimental object,and statistical analysis methods are used to obtain user battery swapping needs at different times of the day.Secondly,a charging strategy optimization control model is proposed with the goal of reducing station-side battery charging costs and life loss costs.Combined with battery swapping demand and time-of-use electricity prices,a genetic algorithm is used to solve the charging rate matrix and charging cut-off voltage of the battery charging compartment at different times of the day.Finally,the effectiveness of the model is verified through experimental examples,which also provides reference for its wide application in actual charging and swapping stations.关键词
电动重卡/充换电站/换电需求/充电策略/遗传算法(GA)Key words
electric heavy truck/charging and swapping station/battery swapping demand/charging strategy/genetic algorithm(GA)引用本文复制引用
王博,杨克南,杨迎春,王少鹏,韩锦峰..基于遗传算法的电动重卡充换电站充电策略优化[J].电气技术,2025,26(3):36-41,48,7.
