模糊逻辑
能源管理
区间(图论)
汽车工业
汽车工程
计算机科学
控制工程
控制器(灌溉)
能源消耗
智能控制
电动汽车
控制理论(社会学)
工程类
能量(信号处理)
控制(管理)
人工智能
电气工程
数学
功率(物理)
物理
航空航天工程
组合数学
统计
生物
量子力学
农学
作者
Duong Phan,Alireza Bab‐Hadiashar,Mojgan Fayyazi,Reza Hoseinnezhad,Reza N. Jazar,Hamid Khayyam
标识
DOI:10.1109/tiv.2020.3011954
摘要
Autonomous vehicles are aimed to reduce accidents and traffic congestion. Since hybrid electric vehicles offer feasible solutions to reduce energy consumption and emission to the environment, it is expected that autonomous vehicles will be powered through a hybrid electric system compared to other alternatives. In this paper, a hybrid electric autonomous vehicle is studied under significant amount of uncertainty and ambiguity in the road environment and driver behavior. A Type 1 fuzzy logic controller is constructed here to address the uncertainties of driving conditions. The design involves building an intelligent energy management system for the hybrid electric autonomous vehicle. We have also examined the potentials of the Interval Type 2 fuzzy logic control, especially for energy consumption management. Two simulations are implemented, to demonstrate that the intelligent system, proposed trough Type 1 and Interval Type 2 fuzzy logic control, decreases the fuel usage of the vehicle from 6.74 to 6.58 L/100km, respectively. It is also demonstrated that the Interval Type 2 fuzzy logic controller saves more battery life compared to the Type-1 when the vehicle works under uncertain and ambiguous road conditions. Finally, Interval Type-2 fuzzy logic controller facilitates a reduction of carbon footprint in the autonomous vehicle as desired by the automotive industry stakeholders.
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