EVENT
Accelerated degradation prediction
of Li-ion batteries using hybrid
simulations (Physics + ML)
13th December, 2023
Webinar
Accelerated degradation prediction of Li-ion batteries using hybrid simulations (Physics + ML)
Conventional methods for predicting battery degradation are often complex, time-consuming, and incomplete. These drawbacks can lead to unreliable predictions, issues in the on-road performance and over-engineering, increasing the cost of EVs.
To solve these challenges, oorja has pioneered an innovative hybrid approach (Physics + ML) to swiftly and reliably predict battery pack degradation across C rates, temperatures, and real-world drive cycles. Join us during the webinar to find out more
Key Highlights
Predict cell and pack level degradation on the drive cycles
Predict degradation for various C rates and temperatures
Reduce dependence on tedious battery cycler experiments
Upto 8X faster and reliable results using hybrid simulations
Webinar Agenda
Introduction to oorja
Demonstration of degradation prediction using oorja
Question and Answers
60 min / Webinar Duration
This webinar provides valuable insights into oorja’s hybrid approach to quickly and reliably predict li-ion battery degradation and its potential benefits for battery design and maintenance.The webinar is most suitable for battery design leaders.
Vineet Dravid
Vineet founded oorja to simplify design for complex engineering problems. Armed with a Ph.D. in Mechanical Engineering from Purdue University, Vineet has worked on cutting-edge simulation and mathematical modelling technologies for two decades.