- Program Highlights
Leverage the prestige of IIT Guwahati
- Admission Closes on 1st Nov
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- Career Opportunities
- Advanced Driver Assistance Systems (ADAS) Development
- AUTOSAR-based Embedded Software Development
- Model-Based Development (MBD) for Automotive Applications
- EV Powertrain & Battery Management Systems (BMS) Software Engineering
- Functional Safety (ISO 26262) & Cybersecurity (ISO 21434) Compliance
- Vehicle Communication (CAN, LIN, FlexRay, Ethernet) Engineering
- AI & Computer Vision for Autonomous Vehicles
- Real-Time Operating Systems (RTOS) & Multi-Core Processing
- HIL/SIL/MIL Testing for ADAS & EV Systems
- Integration of OTA Updates & Cloud Connectivity in EVs
- ADAS Software Engineer (Radar, LiDAR, Camera Sensor Fusion)
- AUTOSAR Embedded Software Engineer (Classic & Adaptive AUTOSAR)
- Model-Based Development Engineer (MATLAB, Simulink, Embedded C)
- Vehicle Communication Engineer (CAN, LIN, FlexRay, SOME/IP)
- Functional Safety Engineer (ISO 26262 Compliance)
- Cybersecurity Engineer (ISO 21434 & Secure Boot Implementation)
- Battery Management System (BMS) Engineer (EV Powertrain & Battery Control)
- HIL Validation Engineer (SIL, MIL, HIL Testing using dSPACE, CANoe)
- AI & Perception Engineer (Computer Vision & Sensor Fusion for ADAS)
- EV Software Architect (Over-the-Air Updates, Cloud Connectivity)
- AUTOSAR Classic & Adaptive (Architecture, RTE, MCAL, BSW, OS, COM)
- MATLAB/Simulink & Model-Based Development (MIL, SIL, HIL)
- AI & Machine Learning for ADAS (Python, OpenCV, TensorFlow)
- Vehicle Communication Protocols (CAN, LIN, FlexRay, SOME/IP, DDS)
- Embedded C & C++ for Automotive Software Development
- ADAS Sensor Integration (Radar, LiDAR, Camera, Ultrasonic Sensors)
- ISO 26262 Functional Safety & ISO 21434 Cybersecurity Implementation
- BMS, Power Electronics & Motor Control Strategies for EVs
- HIL Testing & Validation (Vector CANoe, dSPACE, NI LabVIEW)
- Real-Time Operating Systems (RTOS) for Automotive ECUs
- Tata Motors
- Mahindra Electric Mobility Limited
- Hero Electric
- Ather Energy
- Ola Electric
- TVS Motor Company
- Bajaj Auto
- MG Motor India
- Hyundai Motor India
- Ashok Leyland
- JBM Auto
- Kinetic Green Energy & Power Solutions
- FOR ENTERPRISE
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- Program Outcomes
- Program Curriculum
Module 1: EV Engineering Essentials Part I and II
- Module Description:
- In this foundational module, you’ll explore the essential components and technologies of electric vehicles, covering the transition from internal combustion engines (ICE) to EVs. This part covers EV design principles, key subsystems, and safety considerations, along with battery technologies, power electronics (inverters, converters), and motor systems, with a focus on control strategies and efficiency optimization. You’ll also gain insights into vehicle electrification, voltage distribution, and the latest charging technologies, including standards and fast-charging solutions.
- Module Details:
- Starting with EV Technology: Overview of Electric Vehicles, Components, Key Technologies.
- Understanding ICE to EV Transition: Key Differences, Benefits, Challenges.
- Electric Vehicle Engineering: EV Design Principles, Key Subsystems, Safety Considerations.
- Battery Technology for EV Systems: Battery Chemistries, Energy Density, Charging Cycles
- Power Electronics for EV Systems: Inverters, Converters, Power Management.
- Motor Systems for Electric Vehicles: Types of Motors, Control Strategies, Efficiency Optimization.
- Vehicle Electrification Systems: Vehicle Wiring, Voltage Distribution, High and Low Voltage Components.
- Electric Vehicle Charging Technology: Charging Infrastructure, Standards (CCS, CHAdeMO), Fast Charging Solutions.
Module 2: Advanced Certification in Electric Vehicle Design and Simulation using MATLAB, SIMULINK, and QSS
- Module Description:
- This module covers key aspects of electric vehicle (EV) development, including architecture modeling, powertrain design, and energy flow simulations. It analyzes road load factors like aerodynamic drag, rolling resistance, and gradient forces. The module also focuses on inverter design, efficiency, and thermal management, along with advanced Simscape modeling for electrical, mechanical, and thermal systems. Additionally, it integrates QSS and ADVISOR toolboxes for vehicle design, energy efficiency analysis, and battery performance modeling.
- Module Details:
- EV Architecture Modelling & Simulations: Vehicle Layout, Powertrain Architecture, Energy Flow Modeling
- Road Load Understanding: Forces Acting on Vehicles, Load Distribution
- Road Load Analysis: Modeling Aerodynamic Drag, Rolling Resistance, Gradient Forces
- Inverter Design and Modeling: Sizing, Efficiency, Thermal Management
- Advanced Simscape Modeling: Electrical, Mechanical, Thermal Modeling for EV Systems
- QSS and ADVISOR Toolbox Applications: Vehicle Design Simulations, Energy Efficiency Analysis
- BMS Modeling and Energy Analysis: Battery Performance Modeling, Energy Flow Simulations
Module 3: ESSENTIALS of ADAS & AUTOSAR
- Module Description:
- This module introduces Advanced Driver Assistance Systems (ADAS) and SAE Levels of Autonomous Driving (L0-L5). It explores ADAS technologies like radar, LiDAR, cameras, and ultrasonic sensors, and their role in Electric Vehicles (EVs). The course also covers AUTOSAR (Classic & Adaptive) with a focus on software architecture, layers, components, and ECU communication. Additionally, it highlights AUTOSAR’s role in EV Battery Management Systems (BMS), electric powertrain control, and vehicle dynamics, providing a comprehensive understanding of modern automotive systems.
- Module Details:
- Introduction to Advanced Driver Assistance Systems (ADAS)
- SAE Levels of Autonomous Driving (L0-L5)
- Role of ADAS in Electric Vehicles (EVs)
- Key ADAS Technologies:
- Radar, LiDAR, Camera, Ultrasonic Sensors
- Introduction to AUTOSAR (Classic & Adaptive)
- Software Architecture, Layers & Components
- ECU Communication & Configuration
- Role of AUTOSAR in EV Battery Management Systems (BMS)
- AUTOSAR for Electric Powertrain Control & Vehicle Dynamics
Module 4: Vehicle Communication & Model-Based Development (MBD)
- Module Description:
- This module covers communication protocols like CAN, LIN, FlexRay, and Ethernet in ADAS and EVs, along with the AUTOSAR communication stack (COM, PDU, DCM). It explores AUTOSAR’s Run-Time Environment (RTE) and OS. Practical labs include configuring CAN communication in AUTOSAR and integrating MATLAB/Simulink with AUTOSAR for Model-in-the-Loop (MIL), Software-in-the-Loop (SIL), and Hardware-in-the-Loop (HIL) testing. Additionally, students develop a Lane Keep Assist (LKA) algorithm using MATLAB/Simulink for hands-on experience.
- Module Details:
- CAN, LIN, FlexRay, Ethernet in ADAS & EVs
- AUTOSAR Communication Stack (COM, PDU, DCM)
- AUTOSAR RTE (Run-Time Environment) & OS
- Hands-on Lab: Configuring CAN Communication in AUTOSAR
- MATLAB/Simulink & AUTOSAR Integration
- Model-in-the-Loop (MIL), Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL) Testing
- Hands-on Lab: Developing Lane Keep Assist (LKA) Algorithm using MATLAB/Simulink
Module 5: Advanced ADAS Systems & AUTOSAR Implementation
- Module Description:
- This module focuses on integrating camera, radar, and LiDAR sensors for ADAS and EV applications, covering image processing, object detection (OpenCV, TensorFlow), sensor calibration, and data preprocessing. It includes AUTOSAR BSW, Microcontroller Abstraction Layer (MCAL), and complex device drivers. Key topics include memory management, diagnostics, ISO 26262 functional safety, and cybersecurity (ISO 21434). The module also explores Adaptive Cruise Control (ACC), Emergency Braking, Blind Spot Monitoring, and techniques like Model Predictive Control (MPC) and Kalman Filters.
- Module Details:
- Camera, Radar, LiDAR Sensor Integration
- Image Processing & Object Detection (OpenCV, TensorFlow)
- Sensor Calibration & Data Preprocessing
- AUTOSAR BSW & Microcontroller Abstraction Layer (MCAL)
- ECU Abstraction Layer & Complex Device Drivers
- Memory Management & Diagnostics
- ISO 26262 (ASIL Levels) & Functional Safety Concepts
- Cybersecurity (ISO 21434) in ADAS & EVs
- Threat Modeling & Secure Boot in AUTOSAR
- Adaptive Cruise Control (ACC), Emergency Braking, Blind Spot Monitoring
- Model Predictive Control (MPC) & Kalman Filters
Module 6: AUTOSAR Adaptive Platform
- Module Description:
- This module explores the differences between Classic and Adaptive AUTOSAR, focusing on communication protocols like ARA:COM, SOME/IP, and DDS. It covers the application of AUTOSAR Adaptive in EV software and Over-the-Air (OTA) updates. The integration of ADAS with EV powertrain and Battery Management Systems (BMS) is discussed, highlighting the impact of ADAS on battery management and energy efficiency. Students will gain insights into optimizing software for modern EV systems while enhancing vehicle performance and energy use.
- Module Details:
- Differences between Classic & Adaptive AUTOSAR
- ARA:COM, SOME/IP, DDS Communication
- AUTOSAR Adaptive in EV Software & Over-the-Air (OTA) Updates
- Integration of ADAS with EV Powertrain & BMS
- ADAS Impact on Battery Management & Energy Efficiency
Module 7: STM32 Microcontrollers and STM32CubeIDE
- Module Description:
- This module introduces STM32 microcontrollers, covering different STM32 families and their performance characteristics. It provides hands-on experience with STM32CubeIDE, guiding students through IDE setup, code writing, and debugging. The module also explores RTOS integration with FreeRTOS, focusing on task scheduling and advanced debugging techniques using JTAG/SWD and trace tools. Students will develop practical skills in embedded systems development, enhancing their ability to work with STM32 microcontrollers and real-time operating systems.
- Module Details:
- Introduction to STM32 Microcontrollers: STM32 Families, Performance Characteristics
- STM32CubeIDE Development: Setting Up IDE, Writing and Debugging Code
- RTOS Integration and Advanced Debugging: FreeRTOS, Task Scheduling, Debugging with JTAG/SWD, Trace Tools
Module 8: Advanced Peripheral Interfaces and Protocols
- Module Description:
- This module covers essential communication protocols like UART, I2C, SPI, and CAN Bus, focusing on interface design and protocol efficiency. It also explores wireless communication protocols such as Bluetooth, Zigbee, and Wi-Fi for embedded systems. Additionally, the module delves into advanced peripheral integration for EV systems, including sensor networks, battery management communication, and motor control interfaces. Students will gain practical insights into optimizing communication within embedded systems for efficient EV operation and performance.
- Module Details:
- UART, I2C, SPI, CAN Bus: Communication Protocols, Interface Design, Protocol Efficiency
- Wireless Communication Protocols: Bluetooth, Zigbee, Wi-Fi for Embedded Systems
- Advanced Peripheral Integration for EV Systems: Sensor Networks, Battery Management Communication, Motor Control Interfaces
Module 9: Digital Electronics and Logic Design
- Module Description:
- This module covers the fundamentals of digital electronics, including Boolean algebra and logic families like TTL and CMOS. It explores number systems (binary, octal, hexadecimal) and logic gates, with an emphasis on logic gate design. Students will learn to design logic circuits for embedded systems using tools like Karnaugh maps. The module also covers both combinational and sequential circuit design, providing hands-on experience in creating efficient digital systems for embedded applications.
- Module Details:
- Digital Electronics Basics: Boolean Algebra, Logic Families (TTL, CMOS)
- Number Systems, Boolean Algebra, and Logic Gates: Binary, Octal, Hexadecimal, Logic Gate Design
- Logic Circuit Design for Embedded Systems: Karnaugh Maps, Combinational/Sequential Circuit Design
Module 10: Control and Management Systems
- Module Description:
- This module covers motor controllers and Battery Management Systems (BMS) in electric vehicles (EVs), focusing on motor controller types, BMS role, and SOC/SOH estimation. It explores Electric Drive Unit (EDU) concepts, including motor drive electronics and torque control algorithms. The module also delves into regenerative braking principles and energy recovery mechanisms in EVs. Additionally, it addresses thermal management systems, covering cooling techniques and heat dissipation in power electronics to ensure optimal EV performance and efficiency.
- Module Details:
- Motor Controllers and BMS: Types of Motor Controllers, Role of BMS in EVs, SOC/SOH Estimation
- Electric Drive Unit (EDU): Motor Drive Electronics, Torque Control Algorithms
- Regenerative Braking: Principles, Energy Recovery Mechanisms in EVs
- Thermal Management Systems: Cooling Techniques, Heat Dissipation in Power Electronics
Module 11: Embedded Linux for Embedded Systems
- Module Description:
- This module introduces Embedded Linux, covering the Linux kernel and the differences between Embedded Linux and RTOS. It guides students through setting up Embedded Linux on ARM platforms, including bootloaders, cross-compiling kernels, and drivers. The module also explores integrating Real-Time Operating Systems (RTOS) with Linux, focusing on real-time kernel patches, RTOS scheduling, and preemptive multitasking. Additionally, it covers applications of Embedded Linux in networking, multimedia, and automation, providing hands-on experience with these technologies.
- Module Details:
- Introduction to Embedded Linux: Embedded Linux Kernel, Embedded Linux vs RTOS
- Setting Up Embedded Linux on ARM Platforms: Bootloaders, Cross-Compiling Kernels, Drivers
- Real-Time Operating Systems (RTOS) with Linux: Real-Time Kernel Patches, RTOS Scheduling, Preemptive Multitasking
- Applications in Linux: Embedded Linux in Networking, Multimedia, Automation
Module 12: Advanced Power Systems
- Module Description:
- This module covers HVDC (High Voltage Direct Current) systems and Power Factor Correction (PFC) techniques to improve power quality in embedded systems. It includes the design of auxiliary power modules, such as standby power modules and battery backup systems. Additionally, the module explores the use of supercapacitors in power systems, highlighting their applications and advantages, especially in enhancing energy storage and improving the performance of power systems in embedded and high-demand environments.
- Module Details:
- HVDC and Power Factor Correction (PFC): High Voltage Direct Current Systems, Improving Power Quality in Embedded Systems
- Auxiliary Power Modules: Design of Standby Power Modules, Battery Backup Systems
- Supercapacitors for Power Systems: Supercapacitor Applications, Advantages in Power Systems
Module 13: Embedded IoT Systems
- Module Description:
- This module focuses on the role of IoT in embedded systems, covering IoT architectures, sensor networks, and edge devices. It explores wireless communication protocols like Bluetooth, Zigbee, and Wi-Fi, emphasizing low power usage for embedded systems. The module also addresses IoT architecture and security, including the IoT stack, secure communication methods, and data encryption techniques for embedded devices, ensuring secure and efficient data exchange in IoT-enabled systems. Students will gain practical skills in designing and securing IoT solutions for embedded platforms.
- Module Details:
- IoT in Embedded Systems: IoT Architectures, Sensor Networks, Edge Devices
- Wireless Protocols (Bluetooth, Zigbee, Wi-Fi): Low Power Wireless Communication in Embedded Systems
- IoT Architecture and Security in Embedded Systems: IoT Stack, Secure Communication, Data Encryption for Embedded Devices
Module 14: Machine Learning and AI in Embedded Systems
- Module Description:
- This module introduces Machine Learning (ML) for embedded systems, focusing on edge AI and addressing resource constraints in embedded devices. It covers AI-specific hardware, such as AI accelerators, and neural network models designed for embedded platforms. The module explores practical ML and AI applications in embedded systems, including predictive maintenance, smart sensors, and autonomous systems. Students will gain insights into implementing efficient AI solutions on embedded platforms, optimizing performance while overcoming hardware limitations.
- Module Details:
- Introduction to Machine Learning for Embedded Systems: Edge AI, Resource Constraints in Embedded Devices
- AI Accelerators and Neural Networks: AI-Specific Hardware, Neural Network Models for Embedded Platforms
- ML and AI Applications in Embedded Systems: Predictive Maintenance, Smart Sensors, Autonomous Systems
Module 15: Advanced Security in Embedded Systems
- Module Description:
- This module covers cryptography for embedded systems, focusing on symmetric and asymmetric cryptography techniques and secure key management. It delves into secure boot and firmware updates, including secure bootloaders, code signing, and Over-the-Air (OTA) updates. The module also addresses security threats and countermeasures in automotive and IoT systems, highlighting attack vectors and intrusion detection methods. Students will gain practical knowledge in securing embedded devices against cyber threats, ensuring data protection and system integrity in automotive and IoT applications.
- Module Details:
- Cryptography for Embedded Systems: Symmetric/Asymmetric Cryptography, Secure Key Management
- Secure Boot and Firmware Updates: Secure Bootloader, Code Signing, Over-the-Air (OTA) Updates
- Security Threats and Countermeasures in Automotive/IoT Systems: Attack Vectors in IoT and Automotive Systems, Intrusion Detection
Module 16: Capstone Project & Industry Collaboration
- Module Description:
- This module offers an industry-linked capstone project focused on Embedded IoT or EV systems, allowing students to solve real-world problems. It includes project evaluation through peer and mentor feedback, as well as industry insights, providing a comprehensive learning experience and enhancing practical skills in IoT/EV system design.
- Module Details:
- Industry-Linked Capstone Project (Embedded IoT or EV Systems): Real-World Problem Solving in IoT/EV Systems
- Project Evaluation and Feedback: Peer and Mentor Evaluation, Industry Feedback
- Skills Covered
AUTOSAR Classic & Adaptive
MATLAB/Simulink
AI & Machine Learning for ADAS
Vehicle Communication Protocols
Embedded C & C++
ADAS Sensor Integration
BMS, Power Electronics & Motor Control
HIL Testing & Validation
Real-Time Operating Systems
ISO 26262 Functional Safety & ISO 21434 Cybersecurity Implementation
- Benefits
- Entry-Level Training in ADAS, AUTOSAR & EV Systems for Beginners.
- Industry-Oriented Curriculum to Bridge the College-to-Career Gap.
- Hands-on Projects & Real-World Simulations for Practical Learning.
- Job Readiness for Automotive, EV & Embedded Software Engineering Roles.
- Exposure to Cutting-Edge Automotive AI & Machine Learning Applications.
- Certification & Placement Support for Fresh Graduates in Automotive Industry.
- Upskilling for Experienced Automotive Engineers transitioning into ADAS & AUTOSAR.
- Bridging the Gap between Embedded Software & EV System Development.
- Certification & Industry Recognition to enhance career growth.
- Gaining Hands-on Experience with Industry-Standard Tools like Vector CANoe, MATLAB, Simulink.
- Understanding Functional Safety & Cybersecurity Compliance for regulatory adherence.
- Advanced Knowledge of AI in ADAS for future autonomous vehicle roles.
- Ability to design AUTOSAR-based software architectures for EVs and ADAS.
- Hands-on experience with CAN, LIN, and Ethernet-based communication in vehicles.
- Understanding of sensor fusion techniques for Radar, LiDAR, and Camera systems.
- Proficiency in model-based development (MBD) using MATLAB/Simulink.
- Knowledge of ISO 26262 (Functional Safety) and ISO 21434 (Cybersecurity) standards.
- Ability to configure and implement AUTOSAR Classic and Adaptive Platforms.
- Hands-on experience with HIL (Hardware-in-the-Loop) testing for ADAS applications.
- Proficiency in AI-based perception models using OpenCV and TensorFlow.
- Expertise in powertrain control and battery management in electric vehicles.
- Readiness for industry roles in ADAS, AUTOSAR, and EV software engineering.
- Projects
Automated Parking System
Design an AUTOSAR-based intelligent parking assistant using sensor fusion.
Adaptive Cruise Control (ACC)
Develop and test ACC algorithms using MATLAB/Simulink and AUTOSAR integration.
Lane Keep Assist (LKA)
Implement LKA with camera-based lane detection and vehicle control strategies.
Battery Management System (BMS) Simulation
Model and analyze EV BMS using MATLAB, Simulink, and AUTOSAR.
- Mode of Learning
Complete on-site
classroom program
Location: Mumbai
LIVE + Recorded + Onsite + Hardware + Workshop
LIVE + Weekend on-site sessions
Location: Pune, Delhi
LIVE + Recorded + Hardware + Workshop
Location: Global
- Tools Covered
Hardware Labs Access
Two-Wheeler Simulator & Test Bench
The 2 Wheeler Simulator & Testbench focuses on evaluating EV battery performance, including voltage, current, discharge profiles, and capacity testing under various load conditions. It also covers Battery Management System (BMS) testing and dynamic load analysis to optimize electric bike performance and safety.
LAB 1
Charging Station Simulator and Test Bench
The Charging Station Simulator and Test Bench covers experiments focusing on the efficiency, behavior, and safety features of EV charging systems. It includes the measurement of voltage, current, and power consumption during charging, and tests security features like RFID and OTP-based authentication. Key areas include energy efficiency analysis, protection unit testing, and charging behavior under different conditions
LAB 2
EV In-house manufacturing & Development KIT
The EV In-house Manufacturing & Development KIT provides all the essential tools and components for building and prototyping electric vehicles, supporting the entire development process from concept to production. It includes equipment for battery monitoring, motor control, system integration, and real-time data analysis, ensuring seamless development for EV projects​
LAB 5
Hardware Lab Attendees
Our Alumni: Shaping the Future of Innovation
The facilities at DIYguru, especially the testing equipment, were top-notch. Interacting with founders from other EV companies during sessions provided unique insights and added significant value to my educational journey.
Sunil Pareek
• Entrepreneur
The DIYguru course not only introduced me to the essentials of electric vehicles but also provided a highly supportive learning environment. The tutors were incredibly patient, always ready to explain complex concepts multiple times, which greatly enhanced my understanding and confidence
Ankit Kumar
• University Undergrad.
The training at DIYguru proved to be very useful, especially in my role as a deputy manager in R&D. The course provided me with insights that are directly applicable to my work in auto electrical systems, enhancing both my practical skills and theoretical knowledge.
Manoj Kumar
• Deputy Manager in R&D - Auto Ignition Ltd.
Dr. Gaurav Trivedi
Principal Investigator, IIT Guwahati
Chinmaya Chetan Biswal
BeepKart-2W | Spinny- 4W | Shuttl – EVs in Employee Logistics | MDI | TML
Dr. Bijaya Ketan Panigrahi
Professor, Department of Electrical Engineering, Founder Head, Centre for Automotive Research and Tribology (CART), IIT Delhi
Abhishek Dwivedi
Co-Founder EVeez
Arindam Lahiri
CEO of the Automotive Skills Development Council (ASDC)
Ms. Feroza Haque
Project Manager, EICT Academy, Indian Institute of Technology Guwahati
Ms. Pronamika Buragohain
Project Engineer at the E&ICT Academy, IIT Guwahati
Rahul Soni
Project Incharge – EVI Technologies
Jawaad Khan
CEO & Founder – Tadpole Projects
Prasad Kadam
Senior Technical Head – DIYguru COE Labs
Ankit Khatri
EIR – DIYguru | R&D Testing & validation Engineer at CREATARA | Ex- ICAT
Supratim Das
EIR – DIYguru | Hardware Generalist @ Google || Ex – Exponent Energy || Ex- Taqanal Energy || Ex- HCL Technology || E- Mobility, Energy Mentor
