Predicting RUL of EV batteries using AI and ML algorithms.

We are team technophiles and participated in hackathon organized by PDEU and PDPU IIC.

PS no.: 01

Problem Statement : Prediction of Remaining Useful Live of EV Batteries using AI and ML algorithm

Our college name: Pandit Deendayal Energy University(PDEU)

Team Members: Rushabh Thakkar, Divy Patel, Denish Kalariya, Yug Thakkar and Shubham Vyas

Most electric vehicles use lithium-ion batteries as energy storage system. As this battery technology shows degradation during service life, lifetime analyses are of interest to understand aging phenomena and to optimize batteries and their operation.

Remaining Useful Life(RUL) of EV batteries is predicted so that we can replace these batteries before total breakdown and hence increasing the reliability of vehicle.

 Website:
          1. Load saved models in django website.
          2. Get values from users.
          3. Select model accordingly.
          4. Predict and return remaining useful life.  

It first ask user to select battery type followed by the no. of cycle consumed (between 0 to 120) and at last the minimum voltage required

It gives user the predicted battery capacity in Ah and also the Remaining Useful Life(RUL) cycles.

Visual Representation of NASA PROGNOSTIC DATASET

Presentation: T40

Profiles of team member:

• Rushabh Thakkar

Linkedin Github Resume

• Divy Patel

Linkedin Github Resume

• Denish Kalariya

Linkedin Github Resume

• Yug Thakkar

Linkedin Github

• Shubham Vyas

Linkedin Github