Decentralized Control of Electric Vehicle Smart Charging for Cost Minimization Considering Temperature and Battery Health

2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Pub Date : 2019-10-01 DOI:10.1109/SmartGridComm.2019.8909796

Yassir Dahmane, M. Ghanes, R. Chenouard, Mario Alvarado-Ruiz

{"title":"Decentralized Control of Electric Vehicle Smart Charging for Cost Minimization Considering Temperature and Battery Health","authors":"Yassir Dahmane, M. Ghanes, R. Chenouard, Mario Alvarado-Ruiz","doi":"10.1109/SmartGridComm.2019.8909796","DOIUrl":null,"url":null,"abstract":"A decentralized optimal control strategy for one electric vehicle is proposed to minimize the charging cost and maximize the customer’s profit while considering the temperature effect on lithium-ion batteries. To achieve this, we propose a smart bidirectional charging algorithm that exploits the grid to vehicle and vehicle to grid concepts. The decentralized smart charging algorithm takes into account the daily energy price, electric vehicle information, customer needs, the outside air temperature and the temperature of the battery, in order to formulate and solve a non-linear constrained optimization problem. The algorithm is tested over several different scenarios considering a daily energy price profile in France. The results obtained show a great efficiency of the decentralized algorithm and significant charging cost reduction compared to the uncontrolled charging.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SmartGridComm.2019.8909796","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 12

Abstract

A decentralized optimal control strategy for one electric vehicle is proposed to minimize the charging cost and maximize the customer’s profit while considering the temperature effect on lithium-ion batteries. To achieve this, we propose a smart bidirectional charging algorithm that exploits the grid to vehicle and vehicle to grid concepts. The decentralized smart charging algorithm takes into account the daily energy price, electric vehicle information, customer needs, the outside air temperature and the temperature of the battery, in order to formulate and solve a non-linear constrained optimization problem. The algorithm is tested over several different scenarios considering a daily energy price profile in France. The results obtained show a great efficiency of the decentralized algorithm and significant charging cost reduction compared to the uncontrolled charging.

查看原文本刊更多论文

考虑温度和电池健康的成本最小化电动汽车智能充电分散控制

考虑温度对锂离子电池的影响，提出了一种单辆电动汽车的分散最优控制策略，使充电成本最小，客户利润最大化。为了实现这一目标，我们提出了一种智能双向充电算法，该算法利用了电网对车辆和车辆对电网的概念。分布式智能充电算法考虑了日常能源价格、电动汽车信息、客户需求、外部空气温度和电池温度等因素，制定并求解了一个非线性约束优化问题。该算法在考虑法国每日能源价格概况的几个不同场景下进行了测试。结果表明，与不受控制的充电相比，分散充电算法效率高，充电成本显著降低。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)

自引率

0.00%

发文量