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University of Ontario Institute of Technology

Development of eco-driving control system for connected and automated hybrid electric vehicles

Abstract

dc:description.abstract

Hybrid electric vehicles (HEVs) were designed as a potential solution to the ever-increasing global problems of the energy crisis and global warming through flexibly utilizing both fuel and electrical energy. Besides, the emerging technologies of connected and automated vehicles (CAVs) have provided huge possibilities to push the boundaries of HEVs even further and thus have been extensively studied. In this study, a bi-level MPC-based eco-driving strategy for CAHEVs is proposed and designed to improve fuel economy, reduce exhaust emissions while ensuring driving safety under the most common driving scenarios. First, the HEV powertrain is modelled, and the real-time data sources are in the intelligent transportation system (ITS) are introduced. Next, the multi-objective problem is formulated with three goals, namely, driving safety, fuel economy and emission reduction. The simulation is carried out on a map with realistic driving conditions. The results demonstrate the effectiveness and robustness of the proposed eco-driving strategy for CAHEVs.

Degree

thesis:*
Name thesis:degree_name
Master of Applied Science (MASc)
Discipline thesis:degree_discipline
Automotive Engineering
Grantor
University of Ontario Institute of Technology
Year dc:date.issued
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Wang, Siyang
Advisor dc:contributor.advisor
  • Lin, Xianke

Subjects

dc:subject × 5

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10155/1186
OAI identifier oai:identifier
oai:ontariotechu.scholaris.ca:10155/1186

Chain of custody

source
Harvested from
Ontario Institute of Technology
Base URL
ontariotechu.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Wang, Siyang. Development of eco-driving control system for connected and automated hybrid electric vehicles. University of Ontario Institute of Technology, 2020. https://hdl.handle.net/10155/1186