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Grant: Collaborative Research and Development Grants

University of Waterloo

$75,539.00

Energy-optimal control of connected plug-in hybrid electric vehicles using traffic situation predictions in urban driving

EF 2019-20

Résumé
Toyota Motor Manufacturing Canada (TMMC) and other Canadian automobile manufacturers are under increasing pressure to produce cleaner and more fuel-efficient vehicles that also demonstrate improved drivability and safety. Meeting these broad and ambitious standards within a single vehicle is a major challenge for automobile companies which will require significant technological advances in vehicle control systems. The main purpose of this research proposal is to improve the performances of energy management system (EMS) and adaptive cruise controller (ACC) in terms of energy efficiency for hybrid electric vehicles and plug-in hybrids (HEV/PHEVs) by making them adaptable to individual traffic situations in urban driving. For HEV/PHEVs, EMS and ACC systems have significant effects on the vehicle's fuel economy and energy efficiency. These controllers can be significantly improved by using predictive control algorithms which require predictions of traffic participant motions in the near future. New advancements in vehicle communications and sensing systems can be used to obtain the required traffic situation predictions. We will use these predicted traffic participants motions information for development and industry-grade evaluation of novel energy-optimal EMS and ecological ACC (Eco-ACC) systems for HEV/PHEVs. In addition to the uncertainties of traffic situations as stochastic processes, the measurement uncertainties and inaccuracies associated with vehicle communications and sensing will be taken into account in the development of the proposed controllers through a systematic control design framework for systems with incomplete data.The resulting EMS and Eco-ACC control technologies, while initially designed for the Toyota Prius PHEV will be transferable to a broad range of Toyota vehicles, such as Lexus HEV and RAV4 HEV produced by TMMC.
Programme
Collaborative Research and Development Grants
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
522964-2017
Name nom
LashgarianAzad, Nasser
Department département
Systems Design Engineering
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2019
Competition year année de concours
2017
Award amount
75539
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
700
Area of application group en
Transportation systems and services
Area of application group fr
Services et systèmes de transport
Area of application en
Transportation systems and services
Area of application fr
Services et systèmes de transport
Research subject code
2108
Research subject group en
Mechanical engineering
Research subject group fr
Génie mécanique
Research subject en
Aerospace, aeronautical and automotive engineering
Research subject fr
Génie aérospatial, aéronautique et automobile
Installment
inst:2 - 2
Partie
2
Nb partie
2
Application title
Energy-optimal control of connected plug-in hybrid electric vehicles using traffic situation predictions in urban driving
Keyword
NSERC
Application summary
Toyota Motor Manufacturing Canada (TMMC) and other Canadian automobile manufacturers are under increasing pressure to produce cleaner and more fuel-efficient vehicles that also demonstrate improved drivability and safety. Meeting these broad and ambitious standards within a single vehicle is a major challenge for automobile companies which will require significant technological advances in vehicle control systems. The main purpose of this research proposal is to improve the performances of energy management system (EMS) and adaptive cruise controller (ACC) in terms of energy efficiency for hybrid electric vehicles and plug-in hybrids (HEV/PHEVs) by making them adaptable to individual traffic situations in urban driving. For HEV/PHEVs, EMS and ACC systems have significant effects on the vehicle's fuel economy and energy efficiency. These controllers can be significantly improved by using predictive control algorithms which require predictions of traffic participant motions in the near future. New advancements in vehicle communications and sensing systems can be used to obtain the required traffic situation predictions. We will use these predicted traffic participants motions information for development and industry-grade evaluation of novel energy-optimal EMS and ecological ACC (Eco-ACC) systems for HEV/PHEVs. In addition to the uncertainties of traffic situations as stochastic processes, the measurement uncertainties and inaccuracies associated with vehicle communications and sensing will be taken into account in the development of the proposed controllers through a systematic control design framework for systems with incomplete data.The resulting EMS and Eco-ACC control technologies, while initially designed for the Toyota Prius PHEV will be transferable to a broad range of Toyota vehicles, such as Lexus HEV and RAV4 HEV produced by TMMC.