Grant: Idea to Innovation
University of Ontario Institute of Technology
$20,000.00
L2M NSERC - Next-gen EV Battery Safety Framework using a Digital Twin-based Smart Battery Management System (BMS)
EF 2022-23
Résumé
Safety concerns arising from the frequent incidents of fire and catastrophic failure of electric vehicle (EVs) batteries are primarily bottlenecking the wide adoption of EVs. This is primarily because all existing practical battery management system (BMS) controls the battery thermal management system based on the measured temperatures at a few different points of the battery pack instead of cell core temperature. However, experimental studies revealed that the core temperate of the battery cell differs 50-60°F compared to the measured temperature at certain points of the battery pack. The difference is even more alarming in the case of EVs due to very high discharging and regenerative charging current during rapid acceleration and deceleration. Installing a physical sensor at the core of each cell is impractical due to system cost and manufacturing challenges. Now estimating thermal states needs a large volume of current as well as historical battery operational data as thermal parameters are subject to charge with battery aging, driving pattern, and other external parameters. Further real-time thermal state estimation by processing the current and historical data is also not feasible due to low processing power and the low data storage capacity of the onboard BMS.
Programme
Idea to Innovation
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
576716-2022
Name nom
Williamson, Sheldon S
Department département
Electrical, Computer and Software Engineering
Organization id
19222
Institution établissement
University of Ontario Institute of Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2022
Award amount
20000
Program id
I2IPJ
Program name en
Idea to Innovation
Program name fr
De l'idée à l'innovation
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
305
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Energy storage and conversion
Area of application fr
Stockage et transformation de l'énergie
Research subject code
2500
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Electrical and electronic engineering
Research subject fr
Génie électrique et électronique
Installment
inst:1
Partie
1
Nb partie
1
Application title
L2M NSERC - Next-gen EV Battery Safety Framework using a Digital Twin-based Smart Battery Management System (BMS)
Application summary
Safety concerns arising from the frequent incidents of fire and catastrophic failure of electric vehicle (EVs) batteries are primarily bottlenecking the wide adoption of EVs. This is primarily because all existing practical battery management system (BMS) controls the battery thermal management system based on the measured temperatures at a few different points of the battery pack instead of cell core temperature. However, experimental studies revealed that the core temperate of the battery cell differs 50-60°F compared to the measured temperature at certain points of the battery pack. The difference is even more alarming in the case of EVs due to very high discharging and regenerative charging current during rapid acceleration and deceleration. Installing a physical sensor at the core of each cell is impractical due to system cost and manufacturing challenges. Now estimating thermal states needs a large volume of current as well as historical battery operational data as thermal parameters are subject to charge with battery aging, driving pattern, and other external parameters. Further real-time thermal state estimation by processing the current and historical data is also not feasible due to low processing power and the low data storage capacity of the onboard BMS.