Description
In 1970s the Volvo
P1800E was the first vehicle to get an ECU to control the engine. Since after
that there has been a various way by which the integrated circuits and electronics
had been integrated into the vehicle, for various use such as transmission control,
safety, impact detection, etc.
With the coming
of electric vehicles, it has got a lot easier to control the drive unit, and
the performance optimization of the vehicle. The communication is set between
the powertrain communication, power unit, dashboard, vehicle control unit, etc.
is set by using the CAN connection and thus keeping them in sync with each
other and keeping the riders much safer.
In this
internship you learn about the basic domains of automotive systems, the CAN
protocols and software used in automobile. Learn about the model in loop,
hardware in loop and software in loop methods and how to perform them. Along
with this you also get to learn about Autosar – the basics and architecture, as
well as the various functional safety – ISO26262.
Program outcomes
-
Basics of Embedded System
-
CAN Communication and Protocol
-
Perform MIL, SIL and HIL test
-
Mathematical Model Based System
-
AUTOSAR Software and Components
-
Hardware and Diagnostics
-
Functional Safety
Requirements
- Mobile/Laptop/Tablet with good internet connectivity.
Syllabus
- 26 Lessons
- 20:24:30 Hours
- Introduction to Embedded Systems02:00:00
- Domains of Automotive Embedded Systems00:15:00
- What is CAN Communication?00:40:00
- CAN Protocol00:55:00
- IOT & Autonomous Vehicle 01:25:00
- Case study- Tesla Car00:44:00
- Assessment
- Introduction to Mathematical Model01:40:00
- Model Based Development using Mathematical Modelling01:09:00
- MBD Technology00:28:00
- Testing Automotive Control Systen00:53:00
- Introduction to Micro Controller00:07:00
- Micro Controller00:12:00
- Prerequisite of Python00:16:00
- Basics of Python00:19:00
- Coding on Python01:28:00
- Numpy00:56:00
- Regressions00:50:00
- Quick Recap of Course00:20:00
- Introduction of AI 00:20:00
- AI Applications00:52:00
- Introduction to Machine Learning00:40:00
- Classifications of Machine Learning00:42:30
- Data Processing & Acquisition00:13:00
About instructor
Reviews
Highly recommended. I learnt a lot. Presentation was very good. Excellent course. Liked the way you trained.