Grant: Discovery Grants Program - Individual
Concordia University
$66,000.00
Intelligent Electric Motor Drives with Improved Performance and Reliability for Electrified Vehicles
EF 2024-25
Résumé
In an effort to improve the fuel economy of vehicles and to reduce greenhouse gas emissions, automotive companies are increasing the electrification of their vehicles including passenger cars, public transit vehicles, trucks and trains. The electric powertrain components, such as the energy source, traction electric machines and their drives are important subsystems providing the traction power for electrified vehicles. In the past decade, significant advances have been made to these traction electric powertrain components, such as low cost and lightweight batteries, more efficient electric motors and compact electric drives. However, the automotive industry and government still call for innovative research and developments to improve the electric powertrain efficiency, performance, reliability and durability. This research proposal focuses on developing the next-generation intelligent electric motor drives to improve the overall performance and reliability of the traction electric powertrain at a system level. The intelligence will make the proposed motor drive to be the "brain" instead of one component in the electric powertrain system. More specifically, through analyzing the inputs and observing the outputs of the powertrain system, the proposed intelligent electric motor drive is capable of self-learning and decision making during operation to achieve an improved performance and reliability. Among various traction electric machines, the permanent magnet synchronous machine (PMSM) is dominantly used in electrified vehicle applications, so the proposed research will be primarily focused on PMSM drives. The specific topics of the proposed research encompass comprehensive modeling, accurate machine and drive parameter identification, fault detection and fault tolerant control, and maximum efficiency/torque control strategies for the PMSM drives as well as a possible extension to other electric machine drives. More importantly, intelligent control theory will be investigated and applied in the proposed electric machine drive to exceed the current standard of technology. Therefore, the proposed research will help advance electrified vehicle technologies and provide the Canadian automotive original equipment manufacturers (OEM) and suppliers with product implementable solutions in the near-term with an ultimate aim of making transportation electrification widely acceptable to the consumers.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2019-05476
Name nom
Lai, Chunyan
Department département
Electrical and Computer Engineering
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2019
Award amount
66000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
512
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Transport equipment
Area of application fr
Matériel de transport
Research subject code
2516
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Energy conversion and distribution
Research subject fr
Conversion et distribution de l'énergie
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Intelligent Electric Motor Drives with Improved Performance and Reliability for Electrified Vehicles
Keywords
electric motor drives; permanent magnet machines; maximum torque/efficiency control; loss minimization; fault modeling and detection; fault tolerant control; electromagnetic torque modeling and analysis; condition monitoring; intelligent control algorithms; machine parameter estimation
Application summary
In an effort to improve the fuel economy of vehicles and to reduce greenhouse gas emissions, automotive companies are increasing the electrification of their vehicles including passenger cars, public transit vehicles, trucks and trains. The electric powertrain components, such as the energy source, traction electric machines and their drives are important subsystems providing the traction power for electrified vehicles. In the past decade, significant advances have been made to these traction electric powertrain components, such as low cost and lightweight batteries, more efficient electric motors and compact electric drives. However, the automotive industry and government still call for innovative research and developments to improve the electric powertrain efficiency, performance, reliability and durability. This research proposal focuses on developing the next-generation intelligent electric motor drives to improve the overall performance and reliability of the traction electric powertrain at a system level. The intelligence will make the proposed motor drive to be the "brain" instead of one component in the electric powertrain system. More specifically, through analyzing the inputs and observing the outputs of the powertrain system, the proposed intelligent electric motor drive is capable of self-learning and decision making during operation to achieve an improved performance and reliability. Among various traction electric machines, the permanent magnet synchronous machine (PMSM) is dominantly used in electrified vehicle applications, so the proposed research will be primarily focused on PMSM drives. The specific topics of the proposed research encompass comprehensive modeling, accurate machine and drive parameter identification, fault detection and fault tolerant control, and maximum efficiency/torque control strategies for the PMSM drives as well as a possible extension to other electric machine drives. More importantly, intelligent control theory will be investigated and applied in the proposed electric machine drive to exceed the current standard of technology. Therefore, the proposed research will help advance electrified vehicle technologies and provide the Canadian automotive original equipment manufacturers (OEM) and suppliers with product implementable solutions in the near-term with an ultimate aim of making transportation electrification widely acceptable to the consumers.