Monitoring, Analyzing, and Mitigating Electrical Vehicle (EV) Anomalies and Failures

This project is designed to build a system and software that will monitor and analyze the Electrical Vehicle (EV) bearing anomalies and failures. We will develop a framework that will address the EV bearing failure modes, its effect, and the key features of each failure mode. Later, we will collect the bearing data at “Solution Serafin”, and ingest it in an AI tool for the diagnosis and prognosis of the EV bearing failure. This tool will provide the EV driver and our partner the remaining useful bearing life, and consequently an enhanced maintenance planning strategy. Moreover, we will define the suitable actions to be taken to avoid the EV bearing breakdowns, and we will extend its functionality to reach the nearest suitable replacement time. The proposed system will help our partner to be in control of the EV performance and to find enhanced maintenance actions.

Intern: 
Hussein Adel Taha
Superviseur universitaire: 
Soumaya Yacout
Province: 
Quebec
Partenaire: 
Partner University: 
Discipline: 
Programme: