Grant: Discovery Grants Program - Individual
University of Ontario Institute of Technology
$27,000.00
Degradation Analysis, Optimal Design, and Intelligent Management of Lithium Ion Batteries
EF 2019-20
Résumé
The increasing energy demands of a growing population and climate change challenges provide a strong driving force for renewable energy and transportation electrification. As one of the most promising energy storage systems, Li-ion batteries become widely used in the renewable energy systems and transportation electrification. However, there are still many issues facing Li-ion batteries. One of the most important issues is the degradation of the cells during operation, which becomes the limiting factor in battery cycle life. Longer cycle life is urgently needed to achieve the economic viability in electric vehicles and renewable energy infrastructure. In order to achieve longer cycle life, several key questions need to be addressed, including: (1) how do Li-ion batteries degrade over long-term cycling (degradation analysis); (2) how should we design Li-ion batteries that last longer (optimal design); (3) how should we manage Li-ion batteries in different applications to achieve longer cycle life (intelligent management). ***The proposed research will investigate the battery long term degradation and address these knowledge deficiencies. The long-term degradation process remains poorly understood due to its complexity. Preliminary results indicate different stages of degradation over long-term cycling. A high fidelity degradation model will be developed and experimentally validated to predict the long-term degradation. Through the insights provided by the degradation analysis, potential opportunities for cycle life improvement will be identified. Optimal design techniques will be developed to optimize the battery design parameters to achieve longer cycle life. The proposed program will also develop optimal battery formation protocol, intelligent charging and health conscious management based on the degradation model. The overall program is divided into 5 objectives: 1) Investigate the main degradation mechanisms and develop degradation models; 2) Optimize battery design; 3) Design optimal formation protocol and intelligent charging; 4) Develop advanced battery monitoring system; 5) Develop intelligent management strategies.***The results of this research will contribute to strengthening Canadian leadership in the area of renewable energy and transportation electrification. It will provide a deep understanding of battery long term degradation, specific recommendations of battery optimal design, and optimized battery management strategies. This will enable the industry to produce longer cycle-life battery cells and protect battery health during operation. It will significantly benefit the relevant products and services in a wide range of important applications in Canada. This program will also provide tremendous opportunities for training HQP for the fast growing transportation and energy industry in Canada.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2018-05471
Name nom
Lin, Xianke
Department département
Engineering and Applied Science, Faculty of
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
2019
Competition year année de concours
2018
Award amount
27000
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
1512
Committee name en
Mechanical Engineering
Committee name fr
Génie mécanique
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
2107
Research subject group en
Mechanical engineering
Research subject group fr
Génie mécanique
Research subject en
Modelling, simulation and finite element methods
Research subject fr
Modélisation, simulation et méthodes des éléments finis
Installment
inst:2 - 5
Partie
2
Nb partie
5
Application title
Degradation Analysis, Optimal Design, and Intelligent Management of Lithium Ion Batteries
Keyword
NSERC
Application summary
The increasing energy demands of a growing population and climate change challenges provide a strong driving force for renewable energy and transportation electrification. As one of the most promising energy storage systems, Li-ion batteries become widely used in the renewable energy systems and transportation electrification. However, there are still many issues facing Li-ion batteries. One of the most important issues is the degradation of the cells during operation, which becomes the limiting factor in battery cycle life. Longer cycle life is urgently needed to achieve the economic viability in electric vehicles and renewable energy infrastructure. In order to achieve longer cycle life, several key questions need to be addressed, including: (1) how do Li-ion batteries degrade over long-term cycling (degradation analysis); (2) how should we design Li-ion batteries that last longer (optimal design); (3) how should we manage Li-ion batteries in different applications to achieve longer cycle life (intelligent management). ***The proposed research will investigate the battery long term degradation and address these knowledge deficiencies. The long-term degradation process remains poorly understood due to its complexity. Preliminary results indicate different stages of degradation over long-term cycling. A high fidelity degradation model will be developed and experimentally validated to predict the long-term degradation. Through the insights provided by the degradation analysis, potential opportunities for cycle life improvement will be identified. Optimal design techniques will be developed to optimize the battery design parameters to achieve longer cycle life. The proposed program will also develop optimal battery formation protocol, intelligent charging and health conscious management based on the degradation model. The overall program is divided into 5 objectives: 1) Investigate the main degradation mechanisms and develop degradation models; 2) Optimize battery design; 3) Design optimal formation protocol and intelligent charging; 4) Develop advanced battery monitoring system; 5) Develop intelligent management strategies.***The results of this research will contribute to strengthening Canadian leadership in the area of renewable energy and transportation electrification. It will provide a deep understanding of battery long term degradation, specific recommendations of battery optimal design, and optimized battery management strategies. This will enable the industry to produce longer cycle-life battery cells and protect battery health during operation. It will significantly benefit the relevant products and services in a wide range of important applications in Canada. This program will also provide tremendous opportunities for training HQP for the fast growing transportation and energy industry in Canada.