Certification Course in Advanced Driver Assistance Systems (ADAS) for EVs

Curriculum
Description

Module 1: Electric Vehicle Technology I

Topic 1: Starting with EV Technology

Topic 2: Understanding ICE to EV Transition

Topic 3: Electric Vehicle Engineering

Topic 4: Battery Technology for EV Systems
Module 2: Electric Vehicle Technology II

Topic 1: Power Electronics for EV Systems

Topic 2: Motor Systems for Electric Vehicles

Topic 3: Vehicle Electrification Systems

Topic 4: Electric Vehicle Charging Technology
Module : ADAS Fundamentals & Prerequisites

Topic 1: ADAS Prerequisites 1 – Vehicle Fundamentals & Electronics

14m 15s

Topic 2: ADAS Prerequisites 2 – Embedded Systems, Programming & Control

17m 14s

Topic 3: ADAS Prerequisites 3 – AI & ML, Safety Standards & Testing

19m 47s

Topic 4: ADAS Overview – Sensors, Features & Automation
Module :

Topic 1: Overview of Development Models, Testing, and Simulation

Topic 2: LDW & LKA – Sensor Based Implementation & Validation in MATLAB

Topic 3: MATLAB and Simulink Overview for ADAS Applications
Module 3: Introduction to ADAS and MATLAB

Topic 1: Overview of ADAS – Definition, Components, History, and Significance

Topic 2: MATLAB overview – Key features, relevant toolboxes (Signal Processing, Image Processing, Automated Driving)

Topic 3: Benefits of Simulation & Model Based Design

Topic 4: Activity – Explore MATLAB Environment & Basic Functions
Module 4: MATLAB Basics

Topic 1: MATLAB Syntax, Operations, Variables, Arrays, & Matrices

Topic 2: Writing Scripts and Functions, including Loops & Control Structures

Topic 3: Activity – Solve Linear Equations using MATLAB scripts & functions
Module 5: Data Analysis and Visualization

Topic 1: Importing, Exporting, & Pre-Processing Data in MATLAB

Topic 2: Basic Statistical Analysis & Filtering Techniques

Topic 3: Plotting & Visualizing Data, including 3D plots

Topic 4: Activity – Analyze and Visualize ADAS Sensor Data
Module 6: ADAS Sensors Overview

Topic 1: Overview of Camera, RADAR, LIDAR, and Ultrasonic Sensors – Working Principles, Advantages, Limitations, & Data Types

Topic 2: Sensor Data Formats & Pre Processing

Topic 3: Introduction to Sensor Fusion

Topic 4: Activity – Simulate and Visualize Sensor Data in MATLAB.
Module 7: Signal Processing for ADAS

Topic 1: Basics of Digital Signal Processing: Sampling, Fourier Transforms, & Filtering

Topic 2: Noise Reduction & Feature Extraction from Sensor Data

Topic 3: Activity – Implement Noise Reduction Filters on Sensor Data using MATLAB
Module 8: ADAS Algorithms

Topic 1: Algorithms for Lane Detection, Object Detection, and Tracking

Topic 2: Implementing ADAS Algorithms in MATLAB using Image Processing & Computer Vision Techniques

Topic 3: Activity – Develop a Lane Detection Algorithm using MATLAB
Module 9: Simulating ADAS Systems

Topic 1: Setting up ADAS Simulations in MATLAB – Environment & Scenario Setup

Topic 2: Using MATLAB’s ADAS Toolbox for Simulation

Topic 3: Evaluating Simulation Performance

Topic 4: Activity – Run an ADAS Simulation Scenario & Evaluate Its Performance
Module 10: Case Study and Project Introduction

Topic 1: Review of Key Concepts & Introduction to a Comprehensive ADAS Project

Topic 2: Project Planning, Task Division, and Timeline Creation

Topic 3: Activity – Begin Project Planning & Role Assignments
DIY Projects:

Project: Lane Departure Warning System ADAS Design and Simulation

Congratulations on Successfully Completing the Course!

The Certification Program in ADAS for Electric Vehicles combines theoretical insights and hands-on training to provide a comprehensive understanding of designing, developing, and simulating Advanced Driver Assistance Systems (ADAS) using MATLAB. With a focus on key sensors, algorithms, and simulation tools, this program equips participants with the skills to create safe, efficient, and scalable ADAS solutions tailored for electric vehicles.

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What's included

-10 Modules
-36 Lessons
-25 Hours of Video Content
-Certificate of Completion
-1 Project Assignment

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