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    support@collegese.com
    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Electrical Engineering

    Lakshmi Narayan College of Technology, Bhopal - Indore Campus
    Duration
    4 Years
    Electrical Engineering UG OFFLINE

    Duration

    4 Years

    Electrical Engineering

    Lakshmi Narayan College of Technology, Bhopal - Indore Campus
    Duration
    Apply

    Fees

    ₹5,00,000

    Placement

    92.0%

    Avg Package

    ₹7,80,000

    Highest Package

    ₹18,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Electrical Engineering
    UG
    OFFLINE

    Fees

    ₹5,00,000

    Placement

    92.0%

    Avg Package

    ₹7,80,000

    Highest Package

    ₹18,00,000

    Seats

    120

    Students

    300

    ApplyCollege

    Seats

    120

    Students

    300

    Curriculum

    Comprehensive Course Structure Overview

    The Electrical Engineering curriculum at LNCT BHOPAL INDORE CAMPUS is meticulously designed to provide a balanced mix of foundational knowledge, advanced concepts, and practical applications. The program spans eight semesters, with each semester containing core courses, departmental electives, science electives, and laboratory sessions.

    Semester Course Code Course Title Credits (L-T-P-C) Prerequisites
    I ENG101 English for Engineers 3-0-0-3 -
    I MAT101 Mathematics I 4-0-0-4 -
    I PHY101 Physics for Engineers 3-0-0-3 -
    I CHE101 Chemistry for Engineers 3-0-0-3 -
    I EEE101 Introduction to Electrical Engineering 3-0-0-3 -
    I CSE101 Programming for Engineers 3-0-0-3 -
    I ECL101 Engineering Drawing & Graphics 2-0-0-2 -
    II MAT201 Mathematics II 4-0-0-4 MAT101
    II PHY201 Physics II 3-0-0-3 PHY101
    II EEE201 Circuit Analysis 3-0-0-3 EEE101
    II EEE202 Electronics Devices & Circuits 3-0-0-3 EEE101
    II CSE201 Data Structures & Algorithms 3-0-0-3 CSE101
    II EEE203 Digital Logic Design 3-0-0-3 EEE101
    III MAT301 Mathematics III 4-0-0-4 MAT201
    III EEE301 Electromagnetic Fields 3-0-0-3 PHY201, MAT201
    III EEE302 Signals & Systems 3-0-0-3 MAT201, EEE201
    III EEE303 Power Electronics 3-0-0-3 EEE202
    III EEE304 Control Systems 3-0-0-3 EEE201, MAT301
    III EEE305 Communication Engineering 3-0-0-3 EEE201, EEE302
    IV EEE401 Microprocessors & Microcontrollers 3-0-0-3 EEE203, CSE201
    IV EEE402 Power Systems Analysis 3-0-0-3 EEE301, EEE303
    IV EEE403 Advanced Control Systems 3-0-0-3 EEE304
    IV EEE404 Digital Signal Processing 3-0-0-3 EEE302
    V EEE501 Renewable Energy Systems 3-0-0-3 EEE302, EEE402
    V EEE502 Embedded Systems 3-0-0-3 EEE401
    V EEE503 Smart Grid Technologies 3-0-0-3 EEE402
    V EEE504 AI & Machine Learning in Electrical Engineering 3-0-0-3 EEE404
    V EEE505 Antenna & Microwave Engineering 3-0-0-3 EEE301
    V EEE506 Industrial Robotics 3-0-0-3 EEE304
    VI EEE601 Advanced Power Electronics 3-0-0-3 EEE303
    VI EEE602 Power System Protection 3-0-0-3 EEE402
    VI EEE603 Wireless Communication Systems 3-0-0-3 EEE501, EEE503
    VI EEE604 Sustainable Energy Technologies 3-0-0-3 EEE501
    VII EEE701 Research Methodology 2-0-0-2 -
    VII EEE702 Capstone Project I 4-0-0-4 -
    VIII EEE801 Capstone Project II 6-0-0-6 EEE702

    Detailed Course Descriptions for Advanced Departmental Electives

    These advanced elective courses form the core of specialization tracks and are designed to provide in-depth exposure to cutting-edge areas in electrical engineering:

    • Renewable Energy Systems: This course explores the design, modeling, and optimization of solar photovoltaic systems, wind turbines, hydroelectric plants, and hybrid renewable energy systems. Students learn about grid integration, energy storage solutions, and policy frameworks supporting clean energy adoption.
    • Embedded Systems: Focused on microcontroller architectures, embedded C programming, real-time operating systems (RTOS), sensor interfacing, and IoT applications. The course emphasizes hands-on development of autonomous systems using ARM Cortex-M and ESP32 platforms.
    • Smart Grid Technologies: Covers the evolution from traditional power grids to smart grids, focusing on smart meters, demand response systems, grid stability, and cyber security in electrical networks. Students engage in simulations using MATLAB/Simulink and real-time testing environments.
    • AI & Machine Learning in Electrical Engineering: Integrates AI principles with practical applications in signal processing, control systems, power electronics, and automation. Topics include neural networks, deep learning architectures, and algorithmic optimization for electrical systems.
    • Antenna & Microwave Engineering: Provides a comprehensive study of electromagnetic wave propagation, antenna design techniques, microwave circuits, and radar systems. Students design and test various types of antennas and analyze their performance in different environments.
    • Industrial Robotics: Explores the fundamentals of robotics, robot kinematics, motion control, sensor integration, and automation in manufacturing processes. Includes programming exercises using ROS (Robot Operating System) and simulation tools like Gazebo.
    • Advanced Power Electronics: Delves into high-frequency switching, resonant converters, power factor correction, and grid-connected inverters. Students build and test advanced power conversion circuits for renewable energy applications.
    • Power System Protection: Studies fault analysis, protective relaying, circuit breakers, and system stability in modern power grids. The course includes practical exercises using digital protection relays and simulation software like ETAP.
    • Wireless Communication Systems: Examines modulation techniques, wireless channel modeling, mobile communication standards (5G, LTE), and network protocols. Students implement communication algorithms and analyze signal quality in noisy environments.
    • Sustainable Energy Technologies: Focuses on innovative approaches to sustainable power generation, including fuel cells, geothermal energy, tidal power, and carbon capture technologies. Emphasizes environmental impact assessments and policy considerations.

    Project-Based Learning Philosophy

    The department strongly believes in project-based learning as a means of bridging the gap between theory and practice. The program incorporates two mandatory projects: a mini-project in the third year and a final-year thesis or capstone project.

    Mini-Projects (Semester III & IV):

    • Students form teams of 3-5 members to work on open-ended problems related to their specialization.
    • Each team selects a project from a list provided by faculty mentors or proposes an idea after consultation with advisors.
    • The mini-project spans two semesters and involves literature review, design, simulation, prototyping, and documentation.
    • Evaluation includes progress reports, mid-term presentations, and final demonstration sessions.

    Final-Year Capstone Project (Semester VII & VIII):

    • This project is the culmination of the student's engineering education, requiring them to apply integrated knowledge across multiple domains.
    • Students can choose from industry-sponsored projects or pursue independent research under faculty supervision.
    • The final project involves extensive experimentation, data analysis, and technical writing.
    • Projects are evaluated based on innovation, feasibility, technical depth, and presentation quality.

    Faculty mentors play a crucial role in guiding students throughout the process. Regular meetings, workshops, and feedback sessions ensure that projects meet academic standards while remaining relevant to industry needs.