Model predictive control for energy management of a plug-in hybrid electric bus

Hongwen He; Jieli Zhang; Gaopeng Li

doi:10.1016/j.egypro.2016.06.109

Model predictive control for energy management of a plug-in hybrid electric bus

Hongwen He^*, Jieli Zhang, Gaopeng Li

^*此作品的通讯作者

机械与车辆学院

科研成果: 期刊稿件 › 会议文章 › 同行评审

29 引用（Scopus）

摘要

In this paper, the model predictive control (MPC) method is researched for energy management problem of a plug-in hybrid electric vehicle (HEV). The multi-step Markov prediction method is used to predict the driving condition. Dynamic programming (DP) is used to solve the optimization problem within the prediction horizon. Through the comparison of MPC result with the results of DP strategy and a rule-based strategy, it is certified that the MPC strategy can be implemented to solve the optimization problem for PHEV with good fuel economy.

源语言	英语
页（从-至）	901-907
页数	7
期刊	Energy Procedia
卷	88
DOI	https://doi.org/10.1016/j.egypro.2016.06.109
出版状态	已出版 - 1 6月 2016
活动	Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015 - Fuzhou, 中国期限: 15 11月 2015 → 17 11月 2015

访问文件

10.1016/j.egypro.2016.06.109

其它文件与链接

链接到 Scopus 的出版物

引用此

@article{5c13c59428dc4587b8fe11983bfedba4,

title = "Model predictive control for energy management of a plug-in hybrid electric bus",

abstract = "In this paper, the model predictive control (MPC) method is researched for energy management problem of a plug-in hybrid electric vehicle (HEV). The multi-step Markov prediction method is used to predict the driving condition. Dynamic programming (DP) is used to solve the optimization problem within the prediction horizon. Through the comparison of MPC result with the results of DP strategy and a rule-based strategy, it is certified that the MPC strategy can be implemented to solve the optimization problem for PHEV with good fuel economy.",

keywords = "Energy management strategy, Markov, Model predictive control, Plug-in hybrid electric vehicles",

author = "Hongwen He and Jieli Zhang and Gaopeng Li",

note = "Publisher Copyright: {\textcopyright} 2016 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.; Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015 ; Conference date: 15-11-2015 Through 17-11-2015",

year = "2016",

month = jun,

day = "1",

doi = "10.1016/j.egypro.2016.06.109",

language = "English",

volume = "88",

pages = "901--907",

journal = "Energy Procedia",

issn = "1876-6102",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - Model predictive control for energy management of a plug-in hybrid electric bus

AU - He, Hongwen

AU - Zhang, Jieli

AU - Li, Gaopeng

PY - 2016/6/1

Y1 - 2016/6/1

N2 - In this paper, the model predictive control (MPC) method is researched for energy management problem of a plug-in hybrid electric vehicle (HEV). The multi-step Markov prediction method is used to predict the driving condition. Dynamic programming (DP) is used to solve the optimization problem within the prediction horizon. Through the comparison of MPC result with the results of DP strategy and a rule-based strategy, it is certified that the MPC strategy can be implemented to solve the optimization problem for PHEV with good fuel economy.

AB - In this paper, the model predictive control (MPC) method is researched for energy management problem of a plug-in hybrid electric vehicle (HEV). The multi-step Markov prediction method is used to predict the driving condition. Dynamic programming (DP) is used to solve the optimization problem within the prediction horizon. Through the comparison of MPC result with the results of DP strategy and a rule-based strategy, it is certified that the MPC strategy can be implemented to solve the optimization problem for PHEV with good fuel economy.

KW - Energy management strategy

KW - Markov

KW - Model predictive control

KW - Plug-in hybrid electric vehicles

UR - http://www.scopus.com/inward/record.url?scp=85007574078&partnerID=8YFLogxK

U2 - 10.1016/j.egypro.2016.06.109

DO - 10.1016/j.egypro.2016.06.109

M3 - Conference article

AN - SCOPUS:85007574078

SN - 1876-6102

VL - 88

SP - 901

EP - 907

JO - Energy Procedia

JF - Energy Procedia

T2 - Applied Energy Symposium and Summit on Low-Carbon Cities and Urban Energy Systems, CUE 2015

Y2 - 15 November 2015 through 17 November 2015

ER -

Model predictive control for energy management of a plug-in hybrid electric bus

摘要

访问文件

其它文件与链接

指纹

引用此