{"title":"基于 SDP 的混合动力电动汽车电池充电控制器,为零排放区驾驶做准备","authors":"Jemin Woo, Seohee Han, Changsun Ahn","doi":"10.1007/s40684-024-00609-9","DOIUrl":null,"url":null,"abstract":"<p>The zero-emission zone (ZEZ) is a recent environmental regulation that restricts the entry of internal combustion engine vehicles. In a ZEZ, hybrid electric vehicles (HEVs) are allowed but must operate in full-electric mode. Therefore, it is important for HEVs entering a ZEZ to have a sufficiently charged battery. This study presents a stochastic dynamic programming-based power management strategy for optimizing HEV charging in preparation for ZEZ drives. Stochastic dynamic programming models the driver's intentions as a Markov chain and designs optimal controllers by incorporating future probabilistic information up to an infinite time horizon. Furthermore, the proposed controller takes into account the remaining distance to the zero-emission zone, enabling efficient charging. Compared to stochastic dynamic programming strategies that do not consider the remaining distance, the proposed power management strategy improves the equivalent fuel efficiency by up to about 21%.</p>","PeriodicalId":14238,"journal":{"name":"International Journal of Precision Engineering and Manufacturing-Green Technology","volume":"6 1","pages":""},"PeriodicalIF":5.3000,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SDP-Based Battery Charging Controller for Hybrid Electric Vehicles in Preparation for Zero-Emission Zone Drives\",\"authors\":\"Jemin Woo, Seohee Han, Changsun Ahn\",\"doi\":\"10.1007/s40684-024-00609-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The zero-emission zone (ZEZ) is a recent environmental regulation that restricts the entry of internal combustion engine vehicles. In a ZEZ, hybrid electric vehicles (HEVs) are allowed but must operate in full-electric mode. Therefore, it is important for HEVs entering a ZEZ to have a sufficiently charged battery. This study presents a stochastic dynamic programming-based power management strategy for optimizing HEV charging in preparation for ZEZ drives. Stochastic dynamic programming models the driver's intentions as a Markov chain and designs optimal controllers by incorporating future probabilistic information up to an infinite time horizon. Furthermore, the proposed controller takes into account the remaining distance to the zero-emission zone, enabling efficient charging. Compared to stochastic dynamic programming strategies that do not consider the remaining distance, the proposed power management strategy improves the equivalent fuel efficiency by up to about 21%.</p>\",\"PeriodicalId\":14238,\"journal\":{\"name\":\"International Journal of Precision Engineering and Manufacturing-Green Technology\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Precision Engineering and Manufacturing-Green Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s40684-024-00609-9\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Precision Engineering and Manufacturing-Green Technology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s40684-024-00609-9","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
摘要
零排放区(ZEZ)是最近出台的一项限制内燃机汽车进入的环境法规。在零排放区内,混合动力电动汽车(HEV)是允许的,但必须以全电动模式运行。因此,对于进入 ZEZ 的混合动力汽车来说,电池电量充足非常重要。本研究提出了一种基于随机动态编程的电源管理策略,用于优化 HEV 充电,为 ZEZ 驾驶做好准备。随机动态编程将驾驶员的意图建模为马尔科夫链,并通过将未来的概率信息纳入无限时间跨度来设计最优控制器。此外,建议的控制器还考虑了到零排放区的剩余距离,从而实现了高效充电。与不考虑剩余距离的随机动态编程策略相比,所提出的电源管理策略最多可将等效燃油效率提高约 21%。
SDP-Based Battery Charging Controller for Hybrid Electric Vehicles in Preparation for Zero-Emission Zone Drives
The zero-emission zone (ZEZ) is a recent environmental regulation that restricts the entry of internal combustion engine vehicles. In a ZEZ, hybrid electric vehicles (HEVs) are allowed but must operate in full-electric mode. Therefore, it is important for HEVs entering a ZEZ to have a sufficiently charged battery. This study presents a stochastic dynamic programming-based power management strategy for optimizing HEV charging in preparation for ZEZ drives. Stochastic dynamic programming models the driver's intentions as a Markov chain and designs optimal controllers by incorporating future probabilistic information up to an infinite time horizon. Furthermore, the proposed controller takes into account the remaining distance to the zero-emission zone, enabling efficient charging. Compared to stochastic dynamic programming strategies that do not consider the remaining distance, the proposed power management strategy improves the equivalent fuel efficiency by up to about 21%.
期刊介绍:
Green Technology aspects of precision engineering and manufacturing are becoming ever more important in current and future technologies. New knowledge in this field will aid in the advancement of various technologies that are needed to gain industrial competitiveness. To this end IJPEM - Green Technology aims to disseminate relevant developments and applied research works of high quality to the international community through efficient and rapid publication. IJPEM - Green Technology covers novel research contributions in all aspects of "Green" precision engineering and manufacturing.