Fuel Saving Potential of Optimal Route-Based Control for Plug-in Hybrid Electric Vehicle

被引：4

作者：

Karbowski, Dominik ^{[1
]}

Sokolov, Vadim ^{[1
]}

Jongryeol, Jeong ^{[1
]}

机构：

[1] Argonne Natl Lab, Ctr Transportat Res, 9700 S Cass Ave, Argonne, IL 60439 USA

来源：

IFAC PAPERSONLINE | 2016年 / 49卷 / 11期

关键词：

hybrid vehicle; energy management; optimization; ENERGY-MANAGEMENT; STRATEGY; ECMS;

D O I：

10.1016/j.ifacol.2016.08.020

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we evaluate the fuel savings of a plug-in hybrid electric vehicle (PREV) that uses an optimal controller, itself based on the Pontryagin Minimum Principle (PMP). A process was developed to synthesize speed profiles through a combination of Markov chains and information from a digital map about the future route. In a potential real-world scenario, the future trip (speed, grade, stops, etc.) can be estimated, but not deterministically known. The stochastic trip prediction process models such uncertainty. A PMP strategy was implemented in a Simulink controller for a model of Prius-like PHEV and compared to a baseline strategy using Autonomie, an automotive modeling environment. Multiple real-world itineraries were defined in urban areas with various environments, and for each of them multiple speed profiles were synthesized so as to provide a statistically representative dataset, and finally fuel savings were evaluated with the optimal control. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：128 / 133

页数：6

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