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Intelligent Driver Assistance and Energy Management Systems of Hybrid Electric Autonomous Vehicles

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 31 Jul 2022Publisher:MDPI AGJournal:Sustainability, volume 14, page 9,378 (eissn: 2071-1050,

Authors: Ziad Al-Saadi; Duong Phan Van; Ali Moradi Amani; Mojgan Fayyazi; Samaneh Sadat Sajjadi; Dinh Ba Pham; Reza Jazar; +1 Authors

doi: 10.3390/su14159378

Intelligent Driver Assistance and Energy Management Systems of Hybrid Electric Autonomous Vehicles

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Abstract

Automotive companies continue to develop integrated safety, sustainability, and reliability features that can help mitigate some of the most common driving risks associated with autonomous vehicles (AVs). Hybrid electric vehicles (HEVs) offer practical solutions to use control strategies to cut down fuel usage and emissions. AVs and HEVs are combined to take the advantages of each kind to solve the problem of wasting energy. This paper presents an intelligent driver assistance system, including adaptive cruise control (ACC) and an energy management system (EMS), for HEVs. Our proposed ACC determines the desired acceleration and safe distance with the lead car through a switched model predictive control (MPC) and a neuro-fuzzy (NF) system. The performance criteria of the switched MPC toggles between speed and distance control appropriately and its stability is mathematically proven. The EMS intelligently control the energy consumption based on ACC commands. The results show that the driving risk is extremely reduced by using ACC-MPC and ACC-NF, and the vehicle energy consumption by driver assistance system based on ACC-NF is improved by 2.6%.

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Keywords

Environmental effects of industries and plants, model predictive control, adaptive cruise control, autonomous vehicle, TJ807-830, intelligent energy management; adaptive cruise control; autonomous vehicle; model predictive control; artificial intelligence; complex systems, artificial intelligence, TD194-195, Renewable energy sources, Environmental sciences, GE1-350, complex systems, intelligent energy management

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	13
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%