Curriculum Overview
The Electrical Engineering program at Arni University Kangra follows a carefully structured curriculum designed to provide students with both foundational knowledge and specialized expertise. The program spans eight semesters, each building upon the previous one to create a comprehensive learning experience.
Semester-wise Course Structure
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| I | MAT101 | Calculus and Analytical Geometry | 3-1-0-4 | - |
| I | PHY101 | Physics for Engineers | 3-1-0-4 | - |
| I | CHM101 | Chemistry for Engineers | 3-1-0-4 | - |
| I | ENG101 | English Communication | 2-0-0-2 | - |
| I | ECE101 | Introduction to Electrical Engineering | 3-1-0-4 | - |
| I | IT101 | Programming and Problem Solving | 2-0-2-3 | - |
| I | LAW101 | Legal Aspects of Engineering | 2-0-0-2 | - |
| II | MAT201 | Differential Equations and Laplace Transforms | 3-1-0-4 | MAT101 |
| II | PHY201 | Electromagnetic Fields and Waves | 3-1-0-4 | PHY101 |
| II | ECE201 | Circuit Analysis and Design | 3-1-0-4 | ECE101 |
| II | IT201 | Data Structures and Algorithms | 3-1-0-4 | IT101 |
| II | ECE202 | Electromagnetic Fields and Waves Lab | 0-0-3-1.5 | - |
| III | MAT301 | Probability and Statistics | 3-1-0-4 | MAT201 |
| III | ECE301 | Analog Electronics | 3-1-0-4 | ECE201 |
| III | ECE302 | Digital Electronics and Logic Design | 3-1-0-4 | ECE201 |
| III | ECE303 | Electrical Machines I | 3-1-0-4 | ECE201 |
| III | ECE304 | Signals and Systems | 3-1-0-4 | MAT201 |
| III | ECE305 | Electronics Lab | 0-0-3-1.5 | - |
| IV | MAT401 | Numerical Methods and Optimization | 3-1-0-4 | MAT301 |
| IV | ECE401 | Power Electronics | 3-1-0-4 | ECE301 |
| IV | ECE402 | Control Systems | 3-1-0-4 | ECE304 |
| IV | ECE403 | Electrical Machines II | 3-1-0-4 | ECE303 |
| IV | ECE404 | Microprocessors and Microcontrollers | 3-1-0-4 | ECE302 |
| IV | ECE405 | Control Systems Lab | 0-0-3-1.5 | - |
| V | ECE501 | Communication Systems | 3-1-0-4 | ECE304 |
| V | ECE502 | Embedded Systems Design | 3-1-0-4 | ECE404 |
| V | ECE503 | Power System Analysis | 3-1-0-4 | ECE303 |
| V | ECE504 | Signal Processing | 3-1-0-4 | ECE304 |
| V | ECE505 | Communication Systems Lab | 0-0-3-1.5 | - |
| VI | ECE601 | Renewable Energy Systems | 3-1-0-4 | ECE503 |
| VI | ECE602 | Advanced Control Theory | 3-1-0-4 | ECE402 |
| VI | ECE603 | Robotics and Automation | 3-1-0-4 | ECE402 |
| VI | ECE604 | VLSI Design | 3-1-0-4 | ECE302 |
| VI | ECE605 | Electronics and Communication Lab | 0-0-3-1.5 | - |
| VII | ECE701 | Artificial Intelligence and Machine Learning | 3-1-0-4 | ECE504 |
| VII | ECE702 | Power System Protection | 3-1-0-4 | ECE503 |
| VII | ECE703 | Electromagnetic Compatibility | 3-1-0-4 | ECE201 |
| VII | ECE704 | Advanced Embedded Systems | 3-1-0-4 | ECE502 |
| VII | ECE705 | Capstone Project I | 0-0-6-3 | - |
| VIII | ECE801 | Power System Operation and Control | 3-1-0-4 | ECE503 |
| VIII | ECE802 | Advanced Signal Processing | 3-1-0-4 | ECE504 |
| VIII | ECE803 | Industrial Training | 0-0-6-3 | - |
| VIII | ECE804 | Capstone Project II | 0-0-6-3 | - |
Advanced Departmental Electives
The program offers several advanced departmental electives to allow students to specialize in emerging fields within electrical engineering:
- Advanced Power System Analysis: This course delves into complex power system models, stability analysis, and modern control strategies for grid management. Students learn to simulate large-scale systems using MATLAB and Simulink tools.
- Wireless Communication Networks: Focuses on modern wireless technologies including 5G, LTE, and satellite communications. The curriculum includes hands-on labs with software-defined radios and network simulators.
- Machine Learning Applications in Electrical Engineering: Explores how machine learning algorithms can be applied to solve problems in power systems, signal processing, and control systems. Students gain experience with TensorFlow and PyTorch frameworks.
- Advanced Embedded Systems: Covers advanced topics in microcontroller architecture, real-time operating systems, and embedded system design methodologies. Labs involve ARM-based development boards and embedded C programming.
- Renewable Energy Technologies: Studies solar, wind, hydroelectric, and geothermal energy systems with emphasis on integration into existing power grids. Students participate in designing hybrid renewable energy systems.
- Quantum Computing Fundamentals: Introduces quantum computing concepts and their potential impact on electrical engineering applications. Topics include qubit manipulation, quantum algorithms, and quantum error correction.
- Advanced Control Theory: Delves into nonlinear control theory, optimal control, and adaptive control techniques for complex systems. The course includes practical implementation of control strategies in MATLAB/Simulink environments.
- Signal Integrity and Electromagnetic Compatibility: Addresses issues related to signal degradation and electromagnetic interference in electronic systems. Students learn to use simulation tools like CST Studio Suite and ADS for EMI/EMC analysis.
- Power Electronics Applications: Explores advanced power electronics converters and their applications in renewable energy and electric vehicles. Labs include designing and testing DC-DC converters, inverters, and motor drives.
- Internet of Things (IoT) for Smart Cities: Examines how IoT technologies can be leveraged for urban infrastructure management and sustainability. Students work on real-world projects involving sensor networks and smart city applications.
Project-Based Learning Approach
The department places significant emphasis on project-based learning as a means of reinforcing theoretical knowledge with practical experience. The curriculum incorporates mandatory mini-projects in the second year, followed by a comprehensive capstone project in the final year.
Mini-projects are designed to introduce students to real-world engineering challenges and encourage creativity and innovation. These projects typically involve teams of 3-5 students working under faculty supervision on topics related to their interests or industry needs.
The final-year thesis/capstone project is a significant undertaking that spans the entire academic year. Students select a research topic in consultation with faculty mentors, conduct literature reviews, design experiments, analyze data, and present findings through technical reports and oral presentations.
Project selection criteria include feasibility, relevance to current industry trends, and potential for innovation or impact. Faculty mentors guide students throughout the project lifecycle, ensuring that they develop both technical and professional skills necessary for success in their careers.