Idea Details

Team and Contact Details

SNo Student Name School Degree Year Email
1Rida ArshadPNECUndergraduateFourthridaarshad97@gmail.com

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

Idea Name: BatteryGuard
Slogan: Empowering Batteries
Supervisor Name: Dr. Sajjad Haider Zaidi
Supervisor Designation: Project Supervisor (Director Research)
Supervisor School: PNEC
Supervisor Department: Electrical
Contact number: 0321-3888853
Email ID: sajjadzaidi@pnec.nust.edu.pk
Abstract:
    Our aim is to develop a smart and robust hardware that is efficiently able to identify faulty batteries and analyze the State of Health, since its essential in prevention of system failure .
What is the unmet need in society that your idea will fulfill ?
    When dealing with batteries, accidents and catastrophe often occur and there is always a risk of system failure due to even a minor fault in the battery. Hence there is a need for a robust monitoring system to prevent such incidents, and minimize the chances of failure.
Who needs it ? How many would benefit ?
   Smart Battery Health Monitoring System is the need of the time for organizations and consumers alike. More specifically in UPS, Electric/Hybrid Vehicles, and Solar Power Plants, batteries are needed to be monitored properly. We would be catering to majority of the power and automotive sector.
How will the solution works
    Deep Learning is an evolving research area with diverse application domains and is the chosen method for our project. Proceeding with the technique, we will first prepare a test bench circuitry which will help us to have some samples of battery Voltage, Temperature and Current. Then various deep learning classification algorithms would be implemented on chosen dataset to train the data. Testing would be done on some samples for classification accuracy, then it would predict the results needed.
Who are your competitors ? How is your solution different
    We have no competitors locally, since no BHMS manufacturers in Pakistan. Our solution is based on deep learning, different in a way that once the relevant data set is trained, the logic for data processing can be embedded on-board controllers whilst enabling real-time health assessment.
Status: Approved
Entry Date & Time: 2018-12-23 (1759)