现代电子技术2026，Vol.49Issue(16)：48-53,61,7.DOI:10.16652/j.issn.1004-373X.2026.16.008
基于多任务动态优化的EV充电引导算法设计
Design of EV charging guidance algorithm based on multi-task dynamic optimization
摘要
Abstract
In order to improve the comprehensive performance of the vehicle-pile-network system,a charging guidance algorithm for electric vehicles(EV)is proposed based on the multi-task dynamic optimization.On the basis of the basic architecture and mathematical model of the vehicle-pile-network system,a deep learning algorithm is used to optimize the structure of the multi-task dynamic optimization algorithm,so as to obtain an improved multi-task dynamic optimization algorithm.The goals such as power grid load balance,charging demand and charging network energy efficiency are regarded as dynamic optimization tasks,and the improved algorithm is used to comprehensively analyze the multi-source data in the system,so as to realize accurate analysis of charging pile network operation and maintenance data and optimization of charging process,and improve the operation level of charging pile network and system energy efficiency.The testing experiments were conducted by using EV charging data as samples,and the horizontal comparisons with other similar algorithms were carried out.The results show that,in comparison with other comparison algorithms,the load volatility of the proposed algorithm is less than 0.3%,which provides a new technical scheme for the improvement of the energy efficiency of the EV charging pile and the development of intelligence.关键词
多任务动态优化/电动汽车/充电引导/车-桩-网系统/电网负荷平衡/深度学习/充电桩网络Key words
multi-task dynamic optimization/electric vehicle/charging guidance/vehicle-pile-network system/power grid load balancing/deep learning/charging pile network分类
信息技术与安全科学引用本文复制引用
朱延杰,高宇豆,李园..基于多任务动态优化的EV充电引导算法设计[J].现代电子技术,2026,49(16):48-53,61,7.基金项目
云南省科技厅基础研究面上项目(202301AT070172) （202301AT070172）
云南省中青年学术和技术带头人后备人才项目(202105AC160094) （202105AC160094）
云南电网有限责任公司信息中心科技项目(059300KK52170004,059300KK52190001) （059300KK52170004,059300KK52190001）
