A control benchmark on the energy management of a plug-in hybrid electric vehicle

被引：90

作者：

Sciarretta, A. ^{[1
]}

Serrao, L. ^{[1
,3
]}

Dewangan, P. C. ^{[1
,5
]}

Tona, P. ^{[1
]}

Bergshoeff, E. N. D. ^{[8
,12
]}

Bordons, C. ^{[9
]}

Charmpa, L. ^{[5
,12
]}

Elbert, Ph. ^{[4
]}

Eriksson, L. ^{[6
]}

Hofman, T. ^{[8
]}

Hubacher, M. ^{[8
]}

Isenegger, R. ^{[8
]}

Lacandia, F. ^{[7
,13
]}

Laveau, A. ^{[5
]}

Li, H. ^{[5
,11
]}

Marcos, D. ^{[9
]}

Nueesch, T. ^{[4
]}

Onori, S. ^{[7
]}

Pisu, P. ^{[2
]}

Rios, J. ^{[2
]}

Silvas, E. ^{[8
]}

Sivertsson, M. ^{[6
]}

Tribioli, L. ^{[7
,10
]}

van der Hoeven, A. -J. ^{[8
]}

Wu, M. ^{[5
,11
]}

机构：

[1] IFP Energies Nouvelles, F-92852 Rueil Malmaison, France

[2] Clemson Univ, Clemson, SC 29631 USA

[3] Dana Corp, Trento, Italy

[4] Swiss Fed Inst Technol, Zurich, Switzerland

[5] IFP Sch, Rueil Malmaison, France

[6] Linkoping Univ, S-58183 Linkoping, Sweden

[7] Ohio State Univ, Columbus, OH 43210 USA

[8] TU Eindhoven, Eindhoven, Netherlands

[9] Univ Seville, Seville, Spain

[10] Univ Roma Tor Vergata, I-00173 Rome, Italy

[11] PSA, Paris, France

[12] Continental, Bordeaux, France

[13] Univ Lecce, I-73100 Lecce, Italy

来源：

CONTROL ENGINEERING PRACTICE | 2014年 / 29卷

关键词：

Supervisory control; Plug-in hybrid electric vehicles; Energy management; Optimal control; Rule-based control; CONTROL STRATEGIES; SUPERVISORY CONTROL; ECMS;

D O I：

10.1016/j.conengprac.2013.11.020

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A benchmark control problem was developed for a special session of the IFAC Workshop on Engine and Powertrain Control, Simulation and Modeling (E-COSM 12), held in Rueil-Malmaison, France, in October 2012. The online energy management of a plug-in hybrid-electric vehicle was to be developed by the benchmark participants. The simulator, provided by the benchmark organizers, implements a model of the GM Voltec powertrain. Each solution was evaluated according to several metrics, comprising of energy and fuel economy on two driving profiles unknown to the participants, acceleration and braking performance, computational performance. The nine solutions received are analyzed in terms of the control technique adopted (heuristic rule-based energy management vs. equivalent consumption minimization strategies, ECMS), battery discharge strategy (charge depleting-charge sustaining vs. blended mode), ECMS implementation (vector-based vs. map-based), ways to improve the implementation and improve the computational performance. The solution having achieved the best combined score is compared with a global optimal solution calculated offline using the Pontryagin's minimum principle-derived optimization tool HOT. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：287 / 298

页数：12

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