NXP's eIQ Auto Machine Learning for Better Battery Management Systems Insights | NXP Semiconductors

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NXP's eIQ Auto Machine Learning for Better Battery Management Systems Insights

NXP's eIQ Auto Machine Learning for Better Battery Management Systems (BMS) Insights

About This Training

In video, co-created by NXP and oorja Energy, we will look at an example of a combined workflow for rapidly deploying edge AI on the NXP S32K3 family of automotive microcontrollers. The video will be helpful for engineering developers of battery packs and thermal management systems, edge ML practitioners and developers of battery management systems for electric vehicles.

Presentation

NXP's eIQ Auto Machine Learning for Better Battery Management Systems Insights

What You Will Learn

A glimpse into how edge AI can unlock new insights in electric vehicles (EV) applications such as BMS and motor control
An introduction to the NXP eIQ® Auto ML Software Development Environment
An introduction to the oorja HEAT application for battery pack thermal analysis and simulation

Presented by

Narsimh Kamath
Electrification Business Development Manager, NXP Semiconductors
Vineet Dravid

Co-founder & CEO, oorja

DURATION

51 min

LANGUAGE

English

SKILL LEVEL

Beginner

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