Ecological Adaptive Cruise Control of Plug-In Hybrid Electric Vehicle With Connected Infrastructure and On-Road Experiments

被引：10

作者：

Bae, Sangjae ^{[1
]}

Kim, Yeojun ^{[2
]}

Choi, Yongkeun ^{[2
]}

Guanetti, Jacopo ^{[2
]}

Gill, Preet ^{[1
]}

Borrelli, Francesco ^{[2
]}

Moura, Scott J. ^{[1
]}

机构：

[1] Univ Calif Berkeley, Civil & Environm Engn, Berkeley, CA 94704 USA

[2] Univ Calif Berkeley, Mech Engn, Berkeley, CA 94704 USA

来源：

JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME | 2022年 / 144卷 / 01期

关键词：

ENERGY MANAGEMENT STRATEGY; FUEL-ECONOMY;

D O I：

10.1115/1.4053187

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper examines both mathematical formulation and practical implementation of an ecological adaptive cruise controller (ECO-ACC) with connected infrastructure. Human errors are typical sources of accidents in urban driving, which can be remedied by rigorous control theories. Designing an ECO-ACC is, therefore, a classical research problem to improve safety and energy efficiency. We add two main contributions to the literature. First, we propose a mathematical framework of an online ECO-ACC for plug-in hybrid electric vehicle (PHEV). Second, we demonstrate ECO-ACC in a real world, which includes other human drivers and uncertain traffic signals on a 2.6 (km) length of the corridor with eight signalized intersections in Southern California. The demonstration results show, on average, 30.98% of energy efficiency improvement and 8.51% additional travel time.

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