VERIM PURE Project Predicting the state of health of electric vehicle batteries - Group 1

Term: 
2020-2021 Fall
Faculty Department of Project Supervisor: 
Faculty of Arts & Social Sciences
Number of Students: 
5

 

Li-ion batteries are currently the mainstream technology used in electric vehicles. Predicting the state of health (i.e., the remaining life) of

batteries is necessary for reliable operations. Students are expected to build machine learning models to predict

the degree of degradation based on different stress factors in this data science project. 

 

Student sare expected to take CS210 or CS412.

 

Please contact the supervisors with your CV and transcript.

Related Areas of Project: 
Computer Science and Engineering
Electronics Engineering
Mechatronics Engineering
Industrial Engineering
Physics

About Project Supervisors