Eco-driving optimal control for electric vehicles with driver preferences

Q1 Engineering Transportation Engineering Pub Date : 2025-01-16 DOI:10.1016/j.treng.2025.100302

Roberto Lot , James Fleming , Boli Chen , Simos Evangelou

{"title":"Eco-driving optimal control for electric vehicles with driver preferences","authors":"Roberto Lot , James Fleming , Boli Chen , Simos Evangelou","doi":"10.1016/j.treng.2025.100302","DOIUrl":null,"url":null,"abstract":"<div><div>An optimal control formulation of an eco-driving system for front-wheel drive electric vehicles is proposed in this paper, demonstrating that including an optimal control model of driver preferences in such systems can successfully blend the objective of energy-efficiency with the subjective goals of human drivers, including desired following distances and time headways, a desired vehicle speed, smooth vehicle acceleration, and a comfortable corner negotiation speed. This builds on previous works that developed driver preference models for optimal control, but did not apply them to a realistic model of an EV powertrain to evaluate potential energy savings in practice. The resulting optimal control problem (OCP) is simplified for implementation by using a polynomial approximation of vehicle losses, and a relaxation of regenerative braking constraints that accurately accounts for required braking bias in a front-wheel drive vehicle. In testing, over a simulated 25km journey involving rural, motorway and urban sections, blending driver preferences with energy efficiency in this framework achieves energy savings of 21% with only a 7% decrease in average speed. For car-following scenarios, 10–15% energy savings are achievable with no decrease in average speed.</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"19 ","pages":"Article 100302"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666691X25000028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Engineering","Score":null,"Total":0}

引用次数: 0

Abstract

An optimal control formulation of an eco-driving system for front-wheel drive electric vehicles is proposed in this paper, demonstrating that including an optimal control model of driver preferences in such systems can successfully blend the objective of energy-efficiency with the subjective goals of human drivers, including desired following distances and time headways, a desired vehicle speed, smooth vehicle acceleration, and a comfortable corner negotiation speed. This builds on previous works that developed driver preference models for optimal control, but did not apply them to a realistic model of an EV powertrain to evaluate potential energy savings in practice. The resulting optimal control problem (OCP) is simplified for implementation by using a polynomial approximation of vehicle losses, and a relaxation of regenerative braking constraints that accurately accounts for required braking bias in a front-wheel drive vehicle. In testing, over a simulated 25km journey involving rural, motorway and urban sections, blending driver preferences with energy efficiency in this framework achieves energy savings of 21% with only a 7% decrease in average speed. For car-following scenarios, 10–15% energy savings are achievable with no decrease in average speed.

查看原文