CHRIST (Deemed to University), Bangalore

DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING

School of Engineering and Technology

Syllabus for
Master of Technology (Power Systems)
Academic Year  (2024)

 
1 Semester - 2024 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
MTEE131 MODERN POWER SYSTEM ANALYSIS Core Courses 4 3 100
MTEE132 ADVANCED ELECTRICAL VEHICLE TECHNOLOGY Core Courses 3 3 100
MTEE143E01 ADVANCED AI AND MACHINE LEARNING Discipline Specific Elective Courses 3 3 100
MTEE144E03 POWER QUALITY AND STANDARDS Discipline Specific Elective Courses 4 3 100
MTEE151 POWER SYSTEMS AND RENEWABLE ENERGY LAB Core Courses 2 2 50
MTEE152 ELECTRIC VEHICLE LABORATORY Core Courses 2 2 50
MTEEAC121 RESEARCH WRITING USING LATEX Skill Enhancement Courses 1 0 0
MTMC123 RESEARCH METHODOLOGY AND IPR Core Courses 2 2 50
2 Semester - 2024 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
MTEE231 SMART GRID - 4 3 100
MTEE232 ADVANCES IN ELECTRIC VEHICULAR SYSTEMS - 3 3 100
MTEE241E03 CHARGING INFRASTRUCTURE AND GRID INTEGRATION - 3 3 100
MTEE242E2 DIGITAL SIGNAL PROCESSORS - 3 3 100
MTEE251 SMART GRID LABORATORY - 2 2 50
MTEE252 ELECTRIC VEHICLE ENERGY MANAGEMENT LABORATORY - 2 2 50
MTEE271 MINI PROJECT - 4 2 50
MTEEAC221 AUDIT COURSE -2 - 1 0 0
3 Semester - 2023 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
MTEE341E1 FACTS AND CUSTOM POWER DEVICES Discipline Specific Elective Courses 3 3 100
MTEE381 PROJECT WORK PHASE I Core Courses 16 8 100
MTEE382 INTERNSHIP Core Courses 2 2 50
MTEEOE1 BUSINESS ANALYTICS Interdisciplinary Elective Courses 3 3 100
4 Semester - 2023 - Batch
Course Code
Course
Type
Hours Per
Week
Credits
Marks
MTEE481 PROJECT WORK PHASE II AND DISSERTATION - 18 16 300
    

    

Introduction to Program:

Electrical energy is probably the cleanest form of energy that is suitable for easy, efficient and economical transmission, distribution and control. As a result the captive electrical powers system, viz. generation transmission and consumption are ubiquitous all over the world. Ensuring safe, reliable and quality power is hence a mandate for any company engaged in power industry. The MTech Power system, a two year, four semester course, offered by Christ University faculty of Engineering is designed to develop the needed knowledge and expertise in this area with emphasis on power system operation and practice. Our desire is provide the students with facilities and curriculum for a comprehensive learning and help them develop expertise in this area. With needs of energy growing day-by-day, demand for professional in the area of power will continue to rise.

Programme Outcome/Programme Learning Goals/Programme Learning Outcome:

PO1: Apply the enhanced knowledge in advanced technologies for modelling, analysing and solving contemporary issues in power sector with a global perspective.

PO2: Critically analyse and carry out detailed investigation on multifaceted complex Problems in area of Power Systems and envisage advanced research in thrust areas.

PO3: Identify, analyse and solve real-life engineering problems in the area of Power Systems

Assesment Pattern

Assessment of Project Work(Phase I)

§  Continuous Internal Assessment:100 Marks

¨       Presentation assessed by Panel Members

¨       Guide

¨       Assessment of Project Report

 

v  Assessment of Project Work(Phase II) and Dissertation

§  Continuous Internal Assessment:100 Marks

¨       Presentation assessed by Panel Members

Examination And Assesments

 

·         Continuous Internal Assessment (CIA) for Theory : 50% (50 marks)

Theory papers:

CIA II   :   Mid Semester Examination (Theory)                       : 25 marks       

CIA I  :  Assignments/  Quizzes/Seminar/Case Studies/Project Work /any othe                                                           : 10 marks

CIA III: Quizzes/Seminar/Case Studies/Project Work /any other             : 10 marks

Attendance                                                                  : 05 marks

End Semester exam: 50 marks

Laboratory / Practical Papers:

CIA will be given 50 % weightage( total 25 marks)

Assessed through observation and performance, viva,recording of results,midsemester exam

End semester exam: 25 marks

MTEE131 - MODERN POWER SYSTEM ANALYSIS (2024 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:4
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Students will be able to:
1. Study various methods of load flow and their advantages and disadvantages
2. Understand how to analyze various types of faults in power system
3. Understand power system security concepts and study the methods to rank the contingencies
4. Understand need of state estimation and study simple algorithms for state estimation
5. Study voltage instability phenomenon

Course Outcome

CO1: Analyze various methods of load flow and evaluate their advantages and disadvantages.

CO2: Investigate and diagnose various types of faults in power systems.

CO3: Assess power system security concepts and apply methods to rank contingencies.

CO4: Explain the need for state estimation and implement simple algorithms for state estimation.

CO5: Examine and interpret the voltage instability phenomenon.

Unit-1
Teaching Hours:9
Load Flow Analysis
 

Introduction - Solution of static load flow equations - Gauss Seidal method –

Newton Raphson method - Fast decoupled method - Flow charts and comparison of the three methods.

Unit-2
Teaching Hours:9
Short Circuit Analysis
 

Introduction – Balanced fault analysis, short circuit MVA, Unbalanced faults: sequence networks – single line to ground fault – line fault -

Double line to ground fault – Unbalanced fault analysis using bus impedance

Unit-3
Teaching Hours:9
Transient Stability Analysis
 

Introduction – Swing Equation, Equal Area Criteria (EAC), Applications of EAC: 3ph short circuit fault at sending side and middle of the transmission line, critical clearing time and angle, multi-machine transient stability analysis: classical approach. (uncertainty impact of renewable energy and electric vehicle fleet)

 

Unit-4
Teaching Hours:9
Voltage Stability Analysis
 

Introduction – Static voltage stability analysis V–Q sensitivity analysis, Q–V model analysis – bus participation factors – branch participation factors – generation participation factors - Continuous Power Flow (CPF)-(uncertainty impact of renewable energy and electric vehicle fleet)

Unit-5
Teaching Hours:9
Power System Security Analysis
 

DC load flow,Security state diagram, contingency analysis, generator shift distribution factors-line outage distribution factor, multiple line outages, overload index ranking, (AC analysis using ETAP/ MATPOWER)

Text Books And Reference Books:

1. HadiSaadat, Power System Analysis, 3rd Edition, PSA Publishing, 2011.
2. Allen J. Wood, Bruce F. Wollenberg, Gerald B. Sheblé, Power Generation, Operation, and Control, 3rd Edition, Wiley Publication, 2013.

Essential Reading / Recommended Reading

1. HadiSaadat, Power System Analysis, 3rd Edition, PSA Publishing, 2011.
2. Allen J. Wood, Bruce F. Wollenberg, Gerald B. Sheblé, Power Generation, Operation, and Control, 3rd Edition, Wiley Publication, 2013.
3. D P Kothari, J Nagrath ‘Modern Power System Analysis’, 4rd Edition, Tata McGraw-Hill Publishing Company Limited, New Delhi, 2011.
4. J. J. Grainger & W. D. Stevenson, “Power system analysis”, McGraw Hill, 2003.

Evaluation Pattern

DETAIL OF MARK FOR COURSES WITH THOERY AND PRACTICAL

THEORY

PRACTICAL

 

Component

Assessed for

Scaled down to

Min. marks to pass

Max. marks

Component

Assessed for

Scaled down to

Min. marks to pass

Maximum marks

1

CIA-1

20

10

-

10

Overall CIA

50

35

14

35

2

CIA-2

50

10

-

10

3

CIA-3

20

10

-

10

4

Attendance

05

05

-

05

Attendance

NA

NA

-

-

5

ESE

100

30

12

30

ESE

NA

NA

-

-

TOTAL

65

-

65

TOTAL

 

35

14

35

MTEE132 - ADVANCED ELECTRICAL VEHICLE TECHNOLOGY (2024 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The course aims to provide a comprehensive understanding of advanced concepts and subsystems in electric vehicle (EV) technology within the framework of power systems. The syllabus encompasses foundational aspects and diverse subsystems of electric vehicles, allowing students to comprehend, analyze, and innovate within the burgeoning field of E-Mobility.

Course Outcome

CO1: Analyze the development, types, and components of Electric Vehicles (EVs), including a comparison with hybrid and internal combustion engine vehicles, and understand their environmental and energy advantages. (L3)

CO2: Evaluate the subsystems of Electric Vehicles, including battery systems, electric motors, power electronics, and charging infrastructure, focusing on their types, working principles, and performance. (L4)

CO3: Describe the architecture of Electric Vehicle powertrains, including drivetrain configurations, transmission systems, regenerative braking, thermal management, and control systems integration. (L2)

CO4: Investigate advanced technologies in Electric Vehicles, covering autonomous and connected EVs, Vehicle-to-Grid technology, advanced sensors, AI integration, and future e-mobility trends. (L5)

CO5: Apply knowledge of EV testing procedures, standards, and safety protocols, assess environmental impacts, and explore maintenance, servicing, and industry applications in EV technology. (L3)

Unit-1
Teaching Hours:9
Introduction to Electric Vehicles
 

Overview of Electric Vehicles (EVs): Types and Classification, Historical Evolution and Advancements in EV Technology, Fundamentals of EV Components: Motors, Batteries, and Power Electronics Comparison between Electric, Hybrid, and Internal Combustion Engine Vehicles, Environmental and Energy Advantages of Electric Vehicles

Unit-2
Teaching Hours:9
Electric Vehicle Subsystems
 

Battery Systems in Electric Vehicles: Types, Chemistry, and Management, Electric Motors: Types, Working Principles, and Performance Analysis, Power Electronic Converters and Controllers in EVs, Charging Infrastructure: AC/DC Charging, Charging Standards, and Protocols, Energy Storage and Management Systems in Electric Vehicles

Unit-3
Teaching Hours:9
Electric Vehicle Powertrain
 

Powertrain Architecture: Understanding EV Drivetrains and Configurations, Electric Vehicle Transmission Systems and Gear Ratios, Regenerative Braking Systems and Energy Recovery, Thermal Management Systems in Electric Vehicles, Control Systems and Integration of Powertrain Components

Unit-4
Teaching Hours:9
Advanced Technologies in Electric Vehicles
 

Introduction to Autonomous and Connected Electric Vehicles, Vehicle-to-Grid (V2G) Technology and Smart Charging, Advanced Sensors and Automation in EVs, Integration of AI and Machine Learning in Electric Vehicle Control, Future Trends and Innovations in E-Mobility

Unit-5
Teaching Hours:9
EV Testing, Standards, and Safety
 

Testing Procedures and Standards for Electric Vehicles, Safety Protocols and Regulations in EV Design and Operation, Environmental Impact Assessment and Emission Reduction in E-Mobility, Maintenance and Servicing Considerations for Electric Vehicles, Case Studies and Industry Applications in Electric Vehicle Technology

Text Books And Reference Books:

1.      John M. Miller, "Electric Vehicle Technology Explained", John Wiley & Sons.

2.      Ali Emadi, "Modern Electric, Hybrid Electric, and Fuel Cell Vehicles", CRC Press.

3.      Chris Mi, "Electric Vehicle Machines and Drives: Design, Analysis and Application", John Wiley & Sons.

Essential Reading / Recommended Reading

1.      Joeri Van Mierlo, "Electric Vehicle Technology Explained", Academic Press.

2.      David A. H. Wilson, "Electric and Hybrid Vehicles: Design Fundamentals", CRC Press.

Evaluation Pattern

Assessment - Only for Theory Course (Without Practical Component)

Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

End Semester Examination (ESE) : 50% (50 marks out of 100 marks)

 

Components of the CIA

·       CIA I    :  Subject Assignments / Online Tests                              : 10 marks

·       CIA II  :   Mid Semester Examination (Theory)                             : 25 marks               

·       CIAIII: Quiz/Seminar/Case Studies/Project/

Innovative assignments/ presentations/ publications                     : 10 marks

·       Attendance                                                                                : 05 marks

            Total                                                                                        : 50 marks

 

Mid Semester Examination (MSE): Theory Papers:

·       The MSE is conducted for 50 marks of 2 hours duration.

·       Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks

End Semester Examination (ESE):

·       The ESE is conducted for 100 marks of 3 hours duration.

·       The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

·       Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions

MTEE143E01 - ADVANCED AI AND MACHINE LEARNING (2024 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The course aims to provide an advanced understanding of Artificial Intelligence (AI) and Machine Learning (ML) concepts, emphasizing their applications in power systems and E-Mobility. Through five comprehensive units, students will gain insights into advanced AI and ML techniques, algorithms, and their relevance in the context of evolving power systems.

Course Outcome

CO1: Understand the basic concepts of Artificial Intelligence and Machine Learning, including types of ML (Supervised, Unsupervised, Reinforcement Learning) and key algorithms (Regression, Classification, Clustering, Neural Networks).

CO2: Grasp advanced ML techniques including Deep Learning (CNNs, RNNs), Ensemble Learning (Bagging, Boosting, Random Forests, GBM), and Reinforcement Learning algorithms (Q-Learning, SARSA, Policy Gradient methods).

CO3: Analyze the applications of AI and ML in power systems for monitoring, control, fault detection, predictive maintenance, and energy forecasting.

CO4: Investigate the use of AI and ML in E-Mobility, focusing on EV battery management, intelligent charging strategies, and AI integration in autonomous and connected vehicles.

CO5: Evaluate the ethical implications of AI/ML, understand the importance of interpretable AI models, and explore emerging trends and future prospects of AI/ML in power systems and E-Mobility

Unit-1
Teaching Hours:9
Fundamentals of AI and ML
 

 Overview of Artificial Intelligence and Machine Learning concepts. Types of Machine Learning: Supervised, Unsupervised, and Reinforcement Learning. Algorithms: Regression, Classification, Clustering, and Neural Networks.

Unit-2
Teaching Hours:9
Advanced ML Techniques
 

Deep Learning: Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).

Ensemble Learning: Bagging, Boosting, Random Forests, and Gradient Boosting Machines (GBM).

Reinforcement Learning algorithms: Q-Learning, SARSA, and Policy Gradient methods.

Unit-3
Teaching Hours:9
AI and ML Applications in Power Systems
 

AI/ML applications in power system monitoring, control, and fault detection. Predictive maintenance and condition monitoring using AI/ML techniques. Energy forecasting and load prediction models in power systems.

Unit-4
Teaching Hours:9
AI and ML in E-Mobility
 

 AI/ML applications in Electric Vehicle (EV) battery management and optimization. Intelligent charging strategies and optimization techniques in EVs. Autonomous and connected vehicles: AI/ML integration in E-Mobility.

Unit-5
Teaching Hours:9
AI Ethics, Interpretability, and Future Trends
 

 Ethical considerations and challenges in AI/ML applications. Interpretable AI/ML models: Explainability and transparency. Emerging trends and future prospects in AI/ML for power systems and E-Mobility.

Text Books And Reference Books:

Ian Goodfellow, et al., "Deep Learning", MIT Press.

2.     Aurélien Géron, "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow", O'Reilly.

3.     Christopher M. Bishop, "Pattern Recognition and Machine Learning", Springer.

4.     Power System Journals and AI/ML Research Papers.

Essential Reading / Recommended Reading

NA

Evaluation Pattern

 Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

 End Semester Examination (ESE) : 50% (50 marks out of 100 marks)

Components of the CIA

·       CIA I:  Subject Assignments / Online Tests: 10 marks

·       CIA II:   Mid Semester Examination (Theory): 25 marks                    

          CIAIII: Quiz/Seminar/Case Studies/Project/

Innovative assignments/ presentations/ publications: 10 marks

·       Attendance: 05 marks

            Total                                                                                        : 50 marks

 

Mid Semester Examination (MSE): Theory Papers:

·       The MSE is conducted for 50 marks of 2 hours duration.

·       Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks

End Semester Examination (ESE):

·       The ESE is conducted for 100 marks of 3 hours duration.

·       The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

·       Question paper pattern is as follows.

         Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

 

 

 

 

MTEE144E03 - POWER QUALITY AND STANDARDS (2024 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:4
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Objective:

 

The course aims to provide a comprehensive understanding of power quality issues, standards, and their significance in power systems and E-Mobility. Through five units, students will explore power quality parameters, standards, mitigation techniques, and their implications in modern electric systems.

Course Outcome

CO1: Understand the definition and importance of power quality in electrical systems, comprehend power quality parameters like voltage sags, swells, harmonics, interruptions, and flicker, and recognize their causes and effects on electrical equipment. (L2)

CO2: Gain knowledge of international and national power quality standards (IEEE, IEC) and regulatory bodies, learn the compliance requirements for E-Mobility and grid-connected systems, and apply these standards to maintain acceptable power quality levels. (L3)

CO3: Learn about instruments and methodologies for power quality measurement, including power analyzers and oscilloscopes, and develop skills in monitoring, data analysis, and interpretation of power quality in real-time systems. (L3)

CO4: Understand active and passive power quality mitigation techniques, including filters, STATCOM, DVR, and UPQC, learn harmonic mitigation strategies, power factor correction, and apply these techniques in E-Mobility systems and grid integration. (L3)

CO5: Explore emerging challenges and trends in power quality, particularly with the integration of renewable energy sources, and assess research directions and advancements in enhancing power quality in electric systems. (L4)

Unit-1
Teaching Hours:9
Unit I: Introduction to Power Quality (9 Hours)
 

 

Definition and significance of power quality in electrical systems. Power quality parameters: voltage sags, swells, harmonics, interruptions, and flicker. Causes and effects of poor power quality on electrical equipment and systems.

Unit-2
Teaching Hours:9
Unit II: Power Quality Standards and Regulations (9 Hours
 

 

Overview of international and national standards: IEEE, IEC, and regulatory bodies. Compliance and adherence to power quality standards in E-Mobility and grid-connected systems. Interpretation and application of standards for maintaining acceptable power quality levels.

Unit-3
Teaching Hours:9
Unit III: Power Quality Monitoring and Measurement (9 Hours)
 

 

Instruments and devices for power quality measurement: power analyzers, oscilloscopes, and recorders. Methodologies and techniques for power quality monitoring in real-time systems. Data analysis and interpretation of power quality measurements.

Unit-4
Teaching Hours:9
Unit IV: Power Quality Mitigation Techniques (9 Hours)
 

 

Active and passive power quality mitigation devices: Filters, STATCOM, DVR, and UPQC. Harmonic mitigation techniques and power factor correction strategies. Application of mitigation devices in E-Mobility systems and grid integration.

Unit-5
Teaching Hours:9
Unit V: Emerging Trends and Future of Power Quality (9 Hours)
 

 

Emerging challenges and trends in power quality in evolving electrical systems. Integration of renewable energy sources and their impact on power quality. Research directions and advancements in enhancing power quality in electric systems.

Text Books And Reference Books:

1.       J.C. Das, "Power System Quality Assessment", McGraw-Hill Education.

2.       Roger C. Dugan, "Electrical Power Systems Quality", McGraw-Hill Education.

3.       IEEE and IEC Standards related to Power Quality.

4.       Power Quality Journals and Research Papers.

Essential Reading / Recommended Reading

Roger C. Dugan, "Electrical Power Systems Quality", McGraw-Hill Education.

Evaluation Pattern

Assessment - Only for Theory Course (Without Practical Component)

Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

End Semester Examination (ESE) : 50% (50 marks out of 100 marks)

 

Components of the CIA 

  • CIA I:  Subject Assignments / Online Tests: 10 marks 

  • CIA II:   Mid Semester Examination (Theory): 25 marks

  • CIAIII: Quiz/Seminar/Case Studies/Project/

Innovative assignments/ presentations/ publications: 10 marks

  • Attendance: 05 marks

Total: 50 marks

 

Mid Semester Examination (MSE): Theory Papers: 

  • The MSE is conducted for 50 marks of 2 hours duration. 

  • Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks

End Semester Examination (ESE): 

  • The ESE is conducted for 100 marks of 3 hours duration. 

  • The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution. 

  • Question paper pattern is as follows. 

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions 

25 % - Simple level questions 

25 % - Complex level questions 

 

 

MTEE151 - POWER SYSTEMS AND RENEWABLE ENERGY LAB (2024 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

The course aims to provide hands-on experience and practical exposure to power system simulations using MATLAB software and hardware-software integration for renewable energy systems. Through a series of ten experiments, students will gain practical insights into power system analysis and renewable energy technologies in the context of E-Mobility.

Course Outcome

CO1: Develop proficiency in using MATLAB for power system simulations, enabling the analysis of power curves, wind farm dynamics, and the capabilities of hydrogen fuel cells and capacitors, thereby gaining a deep understanding of the software's application in power systems analysis. (L3)

CO2: Gain hands-on experience in assessing the impact of environmental variables on renewable energy systems, including the effect of temperature and load on solar panel output and the performance of wind turbines under varying load conditions. (L3)

CO3: Acquire practical skills in evaluating and interpreting data from renewable energy experiments, such as testing the capabilities of solar panels and wind turbines, thereby understanding the operational aspects of these technologies in real-world scenarios. (L4)

CO4: Apply theoretical knowledge to practical situations, demonstrating the ability to integrate hardware and software for the analysis of renewable energy systems, and gain insights into their application in the context of E-Mobility. (L4)

Unit-1
Teaching Hours:9
List of Experiments
 

1.      Simulation experiments using MATLAB

1.      Power Curves

2.      Build a Wind Farm

3.      Test the Capabilities of Hydrogen Fuel Cells and Capacitors

4.      Effect of Temperature on Solar Panel Output

5.      Variables Affecting Solar Panel Output

6.      Effect of Load on Solar Panel Output

7.      Wind Turbine Output: The Effect of Load

8.      Test the Capabilities of Solar Panels and Wind Turbines

Text Books And Reference Books:

1.      Padiyar, K.R., "Power System Dynamics: Stability and Control", BS Publications.

2.      Grigsby, L.L., "Power Systems", CRC Press.

Essential Reading / Recommended Reading

1.      MathWorks Documentation for MATLAB Simulation in Power Systems.

2.      Renewable Energy Systems: Principles, Simulation, and Hardware Manuals.

Evaluation Pattern

50% CIA and 50% external examination

MTEE152 - ELECTRIC VEHICLE LABORATORY (2024 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

The course aims to provide practical hands-on experience and experimentation in electric vehicle (EV) technologies. Through a series of ten experiments, students will gain insights into the design, operation, and testing of various components in electric vehicles, aligning with the principles of E-Mobility.

Course Outcome

CO1: Acquire a comprehensive understanding of electric vehicle components including motors, batteries, power electronics, and control systems through hands-on experimentation, and develop skills in evaluating and testing battery performance parameters such as voltage, current, capacity, and internal resistance. (L3)

CO2: Gain practical experience in analyzing motor characteristics and performance, including efficiency, torque-speed characteristics, and power output under varying load conditions, and test the functionality and performance of power electronic converters and controllers in EVs. (L3)

CO3: Understand and test various aspects of electric vehicle charging infrastructure, including different charging modes, standards, and protocols, and evaluate the efficiency of regenerative braking systems and their energy recovery mechanisms. (L3)

CO4: Perform integration and testing of electric vehicle powertrain components, analyze and test Vehicle-to-Grid (V2G) technology, experiment with autonomous features in EVs, and conduct a comprehensive evaluation of overall EV performance and efficiency. (L4)

Unit-1
Teaching Hours:30
List of Experiments
 

1.      Experiment 1: Electric Vehicle Components Overview (2 Hours)

Introduction to various components of an electric vehicle: motors, batteries, power electronics, and control systems.

2.      Experiment 2: Battery Performance Testing (2 Hours)

Evaluation and testing of battery performance parameters such as voltage, current, capacity, and internal resistance.

3.      Experiment 3: Motor Characteristics and Performance Testing (2 Hours)

Analysis of motor efficiency, torque-speed characteristics, and power output under varying load conditions.

4.      Experiment 4: Power Electronics and Controller Testing (2 Hours)

Testing the functionality and performance of power electronic converters and controllers in electric vehicles.

5.      Experiment 5: Electric Vehicle Charging Infrastructure (2 Hours)

Understanding and testing different charging modes, standards, and protocols for electric vehicles.

6.      Experiment 6: Regenerative Braking System Testing (2 Hours)

Evaluation of regenerative braking efficiency and energy recovery in electric vehicles.

7.      Experiment 7: Electric Vehicle Powertrain Integration (2 Hours)

Integration and testing of powertrain components including motors, controllers, and transmission systems.

8.      Experiment 8: Vehicle-to-Grid (V2G) Testing (2 Hours)

Analysis and testing of V2G technology and its implications in smart charging and grid integration.

9.      Experiment 9: Autonomous Features Testing (2 Hours)

Experimentation and testing of autonomous features and sensors integration in electric vehicles.

10.   Experiment 10: EV Performance and Efficiency Evaluation (2 Hours)

Comprehensive testing and evaluation of overall electric vehicle performance and efficiency.

Text Books And Reference Books:

1.      Ali Emadi, "Modern Electric, Hybrid Electric, and Fuel Cell Vehicles", CRC Press.

2.      John M. Miller, "Electric Vehicle Technology Explained", John Wiley & Sons.

Essential Reading / Recommended Reading

1.      David A. H. Wilson, "Electric and Hybrid Vehicles: Design Fundamentals", CRC Press.

2.      Electric Vehicle Manufacturers' Manuals and Technical Documentation.

Evaluation Pattern

50% CIA and 50% External examination

MTEEAC121 - RESEARCH WRITING USING LATEX (2024 Batch)

Total Teaching Hours for Semester:15
No of Lecture Hours/Week:1
Max Marks:0
Credits:0

Course Objectives/Course Description

 

The course aims to equip students with the necessary skills to use LaTeX for scientific and research-oriented documentation, particularly focusing on technical report writing, research papers, and thesis preparation. Through 15 hours of instruction, students will gain proficiency in using LaTeX to produce high-quality documents for academic and professional purposes.

Course Outcome

CO1: -CO1: Understand the features, advantages, and applications of LaTeX in academic writing, and learn the basics of setting up LaTeX, including installation, choosing editors, and basic document structure. (L2) -CO2: Acquire skills in basic document formatting using LaTeX, including structuring documents with titles, abstracts, sections, and subsections, and inserting tables, figures, equations, and mathematical symbols. (L3) -CO3: Master advanced formatting techniques in LaTeX, such as managing bibliographies and citations using BibTeX and natbib packages, and customizing document layout, styles, fonts, and page formatting. (L3) -CO4: Learn to format academic theses and research papers in LaTeX, including structuring chapters and sections for theses, and manuscript preparation for journal and conference submissions. (L3)

Unit-1
Teaching Hours:15
Detailed syllabus
 

Unit I: Introduction to Entrepreneurship (3 Hours)

Understanding entrepreneurship: definition, significance, and characteristics. Overview of entrepreneurial mindset, traits, and identification of opportunities in E-Mobility.

Unit II: Business Models in E-Mobility (3 Hours)

Introduction to business models: types, canvas, and value proposition in E-Mobility. Case studies of successful E-Mobility startups and their business strategies.

Unit III: Innovation and Technology in E-Mobility (3 Hours)

Role of innovation and technology in shaping E-Mobility ventures. Intellectual Property Rights (IPR) considerations in E-Mobility startups.

Unit IV: Funding and Finance (3 Hours)

Understanding funding sources: bootstrapping, venture capital, and angel investors. Financial planning, budgeting, and risk management in E-Mobility ventures.

Unit V: Entrepreneurial Skills and Development (3 Hours)

Developing an entrepreneurial mindset: leadership, creativity, and problem-solving. Networking, team building, and effective communication in an entrepreneurial setup.

Text Books And Reference Books:

1.      Leslie Lamport, "LaTeX: A Document Preparation System", Addison-Wesley.

Essential Reading / Recommended Reading

1.      George Gratzer, "More Math into LaTeX", Springer.

2.      LaTeX documentation and online resources.

Evaluation Pattern

Audit course

MTMC123 - RESEARCH METHODOLOGY AND IPR (2024 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Objectives-

At the end of this course, students will be able to

1.      Understand research problem formulation.

2.      Analyze research related information

3.      Follow research ethics

4.      Understand that today’s world is controlled by Computer, Information Technology, but tomorrow world will be ruled by ideas, concept, and creativity.

5.      Understanding that when IPR would take such important place in growth of individuals & nation, it is needless to emphasis the need of information about Intellectual Property Right to be promoted among students in general & engineering in particular.

Understand that IPR protection provides an incentive to inventors for further research work and investment in R & D, which leads to creation of new and better products, and in turn brings about, economic growth and social benefits

Course Outcome

CO1: Formulate research problems effectively.

CO2: Analyze research-related information critically.

CO3: Adhere to research ethics consistently.

CO4: Evaluate the evolving importance of ideas, concepts, and creativity in a world increasingly controlled by Computer and Information Technology.

CO5: Recognize the significance of Intellectual Property Rights in the growth of individuals and the nation, and promote awareness about Intellectual Property Rights among students, particularly in engineering.

Unit-1
Teaching Hours:6
Identifying a Research Problem
 

Meaning of research problem, Sources of research problem, Criteria Characteristics of a good research problem, Errors in selecting a research problem, Scope and objectives of research problem. Approaches of investigation of solutions for research problem, data collection, analysis, interpretation, Necessary instrumentations.  

Unit-2
Teaching Hours:6
Literature Survey and Research Ethics
 

Effective literature studies approaches, analysis Plagiarism, Research ethics

Unit-3
Teaching Hours:6
Research Proposal and Report Writing
 

Effective technical writing, how to write report, Paper Developing a Research Proposal, Format of research proposal, a presentation and assessment by a review committee.

Unit-4
Teaching Hours:6
Intellectual Property Rights
 

Nature of Intellectual Property: Patents, Designs, Trade and Copyright. Process of Patenting and Development: technological research, innovation, patenting, development. International Scenario: International cooperation on Intellectual Property. Procedure for grants of patents, Patenting under PCT. Patent Rights: Scope of Patent Rights. Licensing and transfer of technology. Patent information and databases. Geographical Indications.

Unit-5
Teaching Hours:6
New Developments In IPR
 

New Developments in IPR: Administration of Patent System. New developments in IPR; IPR of Biological Systems, Computer Software etc. Traditional knowledge Case Studies, IPR and IITs.

Text Books And Reference Books:

1.      Stuart Melville and Wayne Goddard, “Research methodology: an introduction for science & engineering students’”

2.      Wayne Goddard and Stuart Melville, “Research Methodology: An Introduction”

3.      Ranjit Kumar, 2nd Edition , “Research Methodology: A Step by Step Guide for beginners”

4.      Halbert, “Resisting Intellectual Property”, Taylor & Francis Ltd ,2007.

5.      Mayall , “Industrial Design”, McGraw Hill, 1992.

Essential Reading / Recommended Reading

1.      Niebel , “Product Design”, McGraw Hill, 1974.

2.      Asimov , “Introduction to Design”, Prentice Hall, 1962.

3.      Robert P. Merges, Peter S. Menell, Mark A. Lemley, “ Intellectual Property in New Technological Age”, 2016.

T. Ramappa, “Intellectual Property Rights Under WTO”, S. Chand, 2008

Evaluation Pattern

Evaluation based on internal assessment

MTEE231 - SMART GRID (2024 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:4
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The course focus on the coverage of both technologies and power system operation in smart grid environment with the detail discussion of information and communication technologies.

  1. To Study about smartgrid technologies, different smart meters and advanced metering infrastructure.
  2. To get familiarized with the power quality management issues in smartgrid.
  3. To get familiarized with the high performance computing for smartgrid applications

 

Course Outcome

CO1: Appreciate the difference between smart grid & conventional grid

CO2: Apply smart metering concepts to industrial and commercial installations

CO3: Formulate solutions in the areas of smart substations, distributed generation and wide area measurements

CO4: Come up with smart grid solutions using modern communication technologies

Unit-1
Teaching Hours:9
Introduction
 

Evolution of Electric Grid - Definitions, Architecture and Concept of Smart Grid - Need of Smart Grid - Functions of Smart Grid - Opportunities & Barriers of Smart Grid - Difference between conventional & smart grid - Difference between smart grid and Microgrid - Present development & International policies in Smart Grid - Smart grid economic and environmental benefits - Case study of Smart Grid

Unit-2
Teaching Hours:9
Data Science
 

Data and information in electrical system – Database management system – Data acquisition – Big data analytics – AI techniques – Machine and deep learning - Cloud services – Fog computing – Enterprise mobility – Blockchain framework

Unit-3
Teaching Hours:9
Communication
 

Wired and Wireless communication technologies – Communication network requirement in smart grid – Cryptosystem –– Interoperability  - Remote terminal unit – VSAT -  Communication Protocols

Unit-4
Teaching Hours:9
Monitoring and Control
 

Smart sensors – Advance metering infrastructure – Intelligent electronic devices – Internet of Things – Digital twins - Phase measurement unit – Open source hardware and software for smart power grid  - Load dispatch center – Automated power dispatch and allocation – Wide Area Monitoring System

Unit-5
Teaching Hours:9
System Studies
 

Demand response -  Demand side integration – Distribution Intelligence and automation – Energy Efficiency - Outage management system – Plug in electric vehicles -  Smart substation - Home & Building Automation – Renewable energy integration – Smart grid simulator

Text Books And Reference Books:

T1.   Ali Keyhani, Mohammad N. Marwali, Min Dai “Integration of Green and Renewable Energy in Electric Power Systems”, Wiley

T2.   Clark W. Gellings, “The Smart Grid: Enabling Energy Efficiency and Demand Response”, CRC Press

T3.   Janaka Ekanayake, Nick Jenkins, Kithsiri Liyanage, Jianzhong Wu, Akihiko Yokoyama, “Smart Grid: Technology and Applications”, Wiley

T4.   Jean Claude Sabonnadière, Nouredine Hadjsaïd, “Smart Grids”, Wiley Blackwell

T5.   Peter S. Fox Penner, “Smart Power: Climate Changes, the Smart Grid, and the Future of Electric Utilities”, Island Press; 1 edition 8 Jun 2010

T6.   S. Chowdhury, S. P. Chowdhury, P. Crossley, “Microgrids and Active Distribution Networks.” Institution of Engineering and Technology, 30 Jun 2009

Stuart Borlase, “Smart Grids (Power Engineering)”, CRC Press

Essential Reading / Recommended Reading

R1.   Andres Carvallo, John Cooper, “The Advanced Smart Grid: Edge Power Driving Sustainability: 1”, Artech House Publishers July 2011

R2.   James Northcote, Green, Robert G. Wilson “Control and Automation of Electric Power Distribution Systems (Power Engineering)”, CRC Press

Mladen Kezunovic, Mark G. Adamiak, Alexander P. Apostolov, Jeffrey George Gilbert “Substation Automation (Power Electronics and Power Systems)”, Springer

Evaluation Pattern

Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks)

End Semester Examination(ESE)          : 50% (50 marks out of 100 marks)

Components of the CIA

CIA I  :  Subject Assignments / Online Tests             : 10 marks

CIA II:   Mid Semester Examination (Theory)                      : 25 marks                   

CIAIII: Quiz/Seminar/Case Studies/Project/

Innovative assignments/ presentations/ publications              : 10 marks

Attendance                                                                             : 05 marks

            Total                                                                            : 50 marks

Mid Semester Examination (MSE): Theory Papers:

The MSE is conducted for 50 marks of 2 hours duration.

Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks

End Semester Examination (ESE):

The ESE is conducted for 100 marks of 3 hours duration.

The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions

MTEE232 - ADVANCES IN ELECTRIC VEHICULAR SYSTEMS (2024 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

This course aims to provide an in-depth understanding of Electric Vehicular Systems, focusing on advanced components, technologies, and emerging trends. Through five units, each comprising nine hours of study, students will explore the specialized areas within electric vehicles, emphasizing advanced technologies, testing, standards, and safety protocols.

Course Outcome

CO1: Learn about advanced electric vehicle powertrains, including multi-motor configurations and powertrain optimization, understand high-performance battery technologies like solid-state batteries, and explore advanced electric motors and motor control systems for enhanced performance. (L3)

CO2: Understand advanced Vehicle-to-Grid (V2G) technology, including bi-directional power flow and grid support, learn smart charging protocols for grid optimization, and explore the integration of renewable energy in vehicle charging. (L3)

CO3: Gain insights into autonomous and connected electric vehicles, including Advanced Driver-Assistance Systems (ADAS), sensor fusion, and decision-making algorithms, and learn about Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication for traffic management. (L3)

CO4: Explore the integration of Artificial Intelligence (AI) and Machine Learning (ML) in electric vehicle control, predictive analytics for energy management and battery health, and AI-based innovations in navigation and route optimization. (L3)

CO5: Understand advanced testing methodologies for electric vehicles, including simulation and hardware-in-the-loop techniques, learn evolving safety standards and regulations, and assess the environmental impact and life-cycle analysis of electric vehicle technology. (L3)

Unit-1
Teaching Hours:9
Advanced Electric Vehicle Propulsion
 

Advanced electric vehicle powertrains: Multi-motor configurations, powertrain optimization, and efficiency enhancement. High-performance battery technologies: Solid-state batteries, next-gen chemistries, and their application in electric vehicles. Advanced electric motors and motor control systems for enhanced performance and energy efficiency.

Unit-2
Teaching Hours:9
Vehicle-to-Grid Integration and Smart Charging
 

Advanced Vehicle-to-Grid (V2G) technology: Bi-directional power flow, grid support, and dynamic charging strategies. Smart charging protocols: Demand response, time-of-use tariffs, and bidirectional communication for grid optimization. Integration of renewable energy sources in vehicle charging and grid interactions.

Unit-3
Teaching Hours:9
Autonomous and Connected Electric Vehicles
 

Advanced driver-assistance systems (ADAS) in electric vehicles: Sensor fusion, perception, and decision-making algorithms. Connected electric vehicles: Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and their impact on traffic management. Autonomous driving technologies and their role in the future of electric mobility.

Unit-4
Teaching Hours:9
AI and Machine Learning Applications in Electric Vehicles
 

Integration of Artificial Intelligence (AI) and Machine Learning (ML) in electric vehicle control and optimization. Predictive analytics for energy management, range prediction, and battery health monitoring in EVs. Innovations in AI-based navigation, route optimization, and adaptive cruise control.

Unit-5
Teaching Hours:9
Advanced Testing, Standards, and Safety
 

Advanced testing methodologies for electric vehicles: Simulation, virtual testing, and hardware-in-the-loop (HIL) techniques. Evolving safety standards and regulations for electric vehicles: Crash safety, high-voltage systems, and fire safety. Environmental impact assessment and life-cycle analysis for electric vehicle technology.

Text Books And Reference Books:

1.      Ali Emadi, "Electric Vehicle Technology Explained", Wiley-Blackwell.

2.      John M. Miller, "Advanced Electric Drive Vehicles", Academic Press.

Essential Reading / Recommended Reading

1.      Various technical papers, research articles, and international standards on Advanced Electric Vehicle Systems.

Evaluation Pattern

Assessment - Only for Theory Course (Without Practical Component)

Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

End Semester Examination (ESE) : 50% (50 marks out of 100 marks)

 

Components of the CIA

·       CIA I    :  Subject Assignments / Online Tests                              : 10 marks

·       CIA II  :   Mid Semester Examination (Theory)                             : 25 marks               

·       CIAIII: Quiz/Seminar/Case Studies/Project/

Innovative assignments/ presentations/ publications                     : 10 marks

·       Attendance                                                                                : 05 marks

            Total                                                                                        : 50 marks

 

Mid Semester Examination (MSE): Theory Papers:

·       The MSE is conducted for 50 marks of 2 hours duration.

·       Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks

End Semester Examination (ESE):

·       The ESE is conducted for 100 marks of 3 hours duration.

·       The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

·       Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions

MTEE241E03 - CHARGING INFRASTRUCTURE AND GRID INTEGRATION (2024 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The course aims to provide a comprehensive understanding of charging infrastructure, grid integration, and the associated challenges in the context of Electric Vehicular Systems. Through five units, each comprising nine hours of study, students will explore charging technologies, grid-to-vehicle integration, smart grid systems, and the impact of Electric Vehicle (EV) charging on power grids.

Course Outcome

CO1: Acquire knowledge about EV charging, including charging modes, standards, and protocols, understand charging station architectures, and explore emerging trends like wireless and ultra-fast charging technologies. (L2)

CO2: Understand grid integration and Vehicle-to-Grid (V2G) technology, including V2G communication protocols, applications in grid support, and identify challenges and opportunities in V2G implementation. (L3)

CO3: Learn about smart grid solutions for EV charging, including smart charging strategies, grid-friendly charging considerations, and advanced grid infrastructure for EV adoption. (L3)

CO4: Explore the interfacing of renewable energy with EV charging, including the integration of solar and wind power into charging infrastructure, and the role of energy storage and microgrid concepts in renewable energy-powered charging setups. (L3)

CO5: Understand policy and regulatory frameworks related to EV charging, examine global case studies of EV deployment and charging infrastructure, and assess future trends and outlook in EV charging technologies and business models. (L3)

Unit-1
Teaching Hours:9
Overview of EV Charging Infrastructure
 

Introduction to EV charging: Charging modes, standards, and protocols (AC and DC charging). Charging station architectures: Public charging stations, fast chargers, and depot charging facilities. Emerging trends: Wireless charging, ultra-fast charging technologies, and interoperability.

Unit-2
Teaching Hours:9
Grid Integration and Vehicle-to-Grid (V2G) Technology
 

Grid-to-vehicle integration: V2G communication protocols, bidirectional power flow, and grid support functions. V2G applications: Peak shaving, frequency regulation, and grid stability enhancement. Challenges and opportunities in V2G implementation: Technical, regulatory, and market-related aspects.

Unit-3
Teaching Hours:9
Smart Grid Solutions for EV Charging
 

Smart charging strategies: Time-based charging, demand response, and load management. Grid-friendly charging: Grid impact assessment, power quality considerations, and mitigation techniques. Advanced grid infrastructure: Distribution automation, substation upgrades, and grid capacity planning for EV adoption.

Unit-4
Teaching Hours:9
Interfacing Renewable Energy with EV Charging
 

Renewable energy sources in EV charging: Solar photovoltaics, wind power, and their integration into charging infrastructure. Energy storage solutions: Battery systems, ultra-capacitors, and their role in renewable energy-based charging stations. Microgrid concepts: Islanding, grid-tied operations, and their relevance in renewable energy-powered charging setups.

Unit-5
Teaching Hours:9
: Policy, Regulations, and Future Trends
 

Regulatory frameworks: Tariff structures, incentives, and government policies promoting EV adoption and charging infrastructure development. Global case studies: Successful EV deployment models, innovative charging infrastructure initiatives, and best practices. Future trends and outlook: Evolution of EV charging technologies, emerging business models, and sustainability considerations.

Text Books And Reference Books:

1.      John Voelcker, "Electric Cars and the Grid: Integration, Security, and Environmental Concerns."

2.      National Renewable Energy Laboratory (NREL) publications on EV charging infrastructure.

Essential Reading / Recommended Reading

1.      Various research papers, technical reports, and industry publications on EV charging and grid integration.

Evaluation Pattern

Assessment - Only for Theory Course (Without Practical Component)

Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

End Semester Examination (ESE) : 50% (50 marks out of 100 marks)

 

Components of the CIA

·       CIA I    :  Subject Assignments / Online Tests                              : 10 marks

·       CIA II  :   Mid Semester Examination (Theory)                             : 25 marks               

·       CIAIII: Quiz/Seminar/Case Studies/Project/

Innovative assignments/ presentations/ publications                     : 10 marks

·       Attendance                                                                                : 05 marks

            Total                                                                                        : 50 marks

 

Mid Semester Examination (MSE): Theory Papers:

·       The MSE is conducted for 50 marks of 2 hours duration.

·       Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks

End Semester Examination (ESE):

·       The ESE is conducted for 100 marks of 3 hours duration.

·       The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

·       Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions

MTEE242E2 - DIGITAL SIGNAL PROCESSORS (2024 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The course aims to equip students with an understanding of Digital Signal Processors (DSPs) and their applications in power systems and Electric Vehicular Systems. The syllabus is divided into five units, each comprising nine hours of study, focusing on DSP fundamentals, architectures, algorithms, and their practical implementations.

Course Outcome

CO1: Acquire foundational knowledge of Digital Signal Processing, including its overview, significance, and applications in power systems and signal processing, understand digital signals and systems, and learn about DSP architecture and hardware components. (L2)

CO2: Understand DSP algorithms and operations, including the principles and applications of DFT and FFT, design and implementation of FIR and IIR filters, and DSP techniques for power quality analysis and control. (L3)

CO3: Learn about DSP-based control algorithms in power converters, real-time control applications in renewable energy systems and electric vehicles, and DSP-based protection schemes for power systems. (L3)

CO4: Explore DSP-based motor control techniques for electric vehicular systems, including Field-Oriented Control and sensorless control, and understand DSP applications in battery management and EV communication networks. (L3)

CO5: Investigate advanced DSP applications, including adaptive signal processing, DSP in speech and image processing, and emerging trends like machine learning integration, IoT, and AI applications in DSP. (L4)

Unit-1
Teaching Hours:9
Introduction to Digital Signal Processing (DSP)
 

Basics of DSP: Overview, significance, and applications in power systems and signal processing. Digital signals and systems: Sampling theorem, discrete-time signals, and frequency domain analysis. DSP architecture and hardware components: Processor elements, memory, and peripherals.

Unit-2
Teaching Hours:9
DSP Algorithms and Operations
 

Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT): Principles, algorithms, and applications. Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters: Design, implementation, and characteristics. Digital signal processing techniques for power quality analysis and control.

Unit-3
Teaching Hours:9
DSP in Power Systems Applications
 

DSP-based control algorithms in power converters: PWM techniques, voltage and current control. Real-time control of power electronic converters: Applications in renewable energy systems and electric vehicles. DSP-based protection schemes for power systems: Fault detection, localization, and fault-tolerant control.

Unit-4
Teaching Hours:9
DSP for Electric Vehicular Systems
 

DSP-based motor control techniques: Field-Oriented Control (FOC), sensorless control, and torque ripple minimization. Battery management systems (BMS): DSP-based state estimation, balancing, and charge/discharge control. DSP applications in Electric Vehicle (EV) communication networks and smart charging systems.

Unit-5
Teaching Hours:9
Advanced DSP Applications
 

Adaptive signal processing: LMS, NLMS algorithms, and their applications in adaptive filtering. DSP in speech and image processing: Applications, algorithms, and implementation techniques. Emerging trends and future prospects in DSP: Machine learning integration, IoT, and AI applications.

Text Books And Reference Books:

1.      Proakis, J. G., & Manolakis, D. G. (2006). "Digital Signal Processing: Principles, Algorithms, and Applications."

Essential Reading / Recommended Reading

1.      Chassaing, R. (2016). "Digital Signal Processing and Applications."

Evaluation Pattern

Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

End Semester Examination (ESE) : 50% (50 marks out of 100 marks)

 

Components of the CIA

·       CIA I    :  Subject Assignments / Online Tests                              : 10 marks

·       CIA II  :   Mid Semester Examination (Theory)                             : 25 marks               

·       CIAIII: Quiz/Seminar/Case Studies/Project/

Innovative assignments/ presentations/ publications                     : 10 marks

·       Attendance                                                                                : 05 marks

            Total                                                                                        : 50 marks

MTEE251 - SMART GRID LABORATORY (2024 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Smart grid technologies lab

Course Outcome

CO1: Develop an understanding of smart grid components and their functionalities through practical exploration, and gain skills in smart meter data analysis, interpreting usage patterns and energy consumption behaviors. (L3)

CO2: Acquire practical experience in demand response simulation, understanding the mechanisms and implications for grid stability, and learn to assess grid stability through various testing and analysis techniques. (L3)

CO3: Understand and apply communication protocols in smart grid systems, design and operate microgrids, and manage energy effectively in smart buildings, leveraging hands-on experiments to comprehend the intricacies of these systems. (L3)

CO4: Perform cybersecurity assessments in smart grid environments, exploring vulnerabilities and protective measures, integrate smart grid solutions for electric vehicles, and conduct economic and cost-benefit analysis to understand the financial aspects of smart grid technologies. (L4)

Unit-1
Teaching Hours:30
List of Experiments
 

Experiment 1: Introduction to Smart Grid Components

Experiment 2: Smart Meter Data Analysis

Experiment 3: Demand Response Simulation

Experiment 4: Grid Stability Assessment

Experiment 5: Communication Protocols in Smart Grid

Experiment 6: Microgrid Design and Operation

Experiment 7: Energy Management in Smart Buildings

Experiment 8: Cybersecurity Assessment in Smart Grid

Experiment 9: Smart Grid Integration for Electric Vehicles

Experiment 10: Smart Grid Economics and Cost-Benefit Analysis

Text Books And Reference Books:

1.      Farret, Felix M., and M. Godoy Simoes. "Integration of Alternative Sources of Energy." John Wiley & Sons, 2010.

2.      Guerrero, Josep M., et al. "Microgrids: Architectures and Control." John Wiley & Sons, 2011.

Essential Reading / Recommended Reading

1.      Massoud Amin, et al. "Smart Grid: Overview, Issues, and Opportunities." IEEE Transactions on Smart Grid, vol. 5, no. 2, 2014, pp. 1905-1922.

Evaluation Pattern

50% CIA and 50% ESE

MTEE252 - ELECTRIC VEHICLE ENERGY MANAGEMENT LABORATORY (2024 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Experiments in electrical vehicles and systems

Course Outcome

CO1: Gain proficiency in testing and evaluating the performance of EV batteries, understand the intricacies of energy storage systems, and learn to optimize electric vehicle charging through practical experiments and analysis. (L3)

CO2: Acquire skills in simulating and analyzing Vehicle-to-Grid (V2G) interactions, understand the principles of thermal management in EVs, and apply techniques for range estimation and optimization in electric vehicles. (L3)

CO3: Explore energy harvesting methods in EVs, analyze drive cycles for performance assessment, and understand the integration of smart charging systems with the grid, focusing on practical applications and testing. (L3)

CO4: Develop capabilities in optimizing energy management systems for electric vehicles, applying learned concepts to enhance efficiency and performance in EV energy systems. (L4)

Unit-1
Teaching Hours:30
List of Experiments
 

1. Battery Performance Testing

2. Energy Storage System Analysis

3. Electric Vehicle Charging Optimization

4. Vehicle-to-Grid (V2G) Simulation

5. Thermal Management in EVs

6. Range Estimation and Optimization

7. Energy Harvesting in EVs

8. EV Drive Cycle Analysis

9. Smart Charging and Grid Integration

10. Energy Management System Optimization

Text Books And Reference Books:

1.      "Electric Vehicle Integration into Modern Power Networks" by Rodrigo Garcia-Valle and João A. Peças Lopes. 

2.     "Advanced Electric Drive Vehicles" by Ali Emadi.

Essential Reading / Recommended Reading

"Energy Management Strategies for Electric and Plug-in Hybrid Electric Vehicles" by Sheldon S. Williamson

Evaluation Pattern

50% CIA and 50% ESE

MTEE271 - MINI PROJECT (2024 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Survey of the project topic

Course Outcome

CO1: To identify a problem and develop a technical solution using a thorough literature survey

CO2: To test and verify the solution developed for the problem

Unit-1
Teaching Hours:60
Evaluation
 

§  Continuous Internal Assessment:100 Marks

¨      Presentation assessed by Panel Members

¨      Guide

¨      Assessment of Project Report

Text Books And Reference Books:

* IEEE digital Library

Essential Reading / Recommended Reading

* IEEE digital Library

Evaluation Pattern


§  Continuous Internal Assessment:100 Marks

¨       Presentation assessed by Panel Members

¨       Guide

 ¨       Assessment of  Report of phase-I

MTEEAC221 - AUDIT COURSE -2 (2024 Batch)

Total Teaching Hours for Semester:15
No of Lecture Hours/Week:1
Max Marks:0
Credits:0

Course Objectives/Course Description

 

Research Publication and Tools

Course Outcome

CO1: -CO1: Gain an understanding of the academic research landscape, the significance of scholarly publications, the research publication lifecycle, and the ethics and integrity in academic writing and publishing. (L2) -CO2: Learn about academic writing styles and structures, strategies for effective literature review and synthesis, and gain knowledge in citations, referencing, avoiding plagiarism, and tools for managing References. (L3) -CO3: Acquire skills in using statistical analysis software (SAS, R, or Python) for data analysis and visualization, including descriptive, inferential, and predictive analysis, and practical experience with data visualization tools. (L3) -CO4: Understand manuscript preparation for scholarly journals, including structure (IMRAD), journal selection, submission guidelines, and responding effectively to peer review comments. (L3)

Unit-1
Teaching Hours:15
Detailed syllabus
 

Unit I: Introduction to Academic Research and Publications (3 hours)

Understanding the Academic Research Landscape, Significance of Scholarly Publications, Overview of Research Publication Lifecycle, Ethics and Integrity in Academic Writing and Publishing,

Unit II: Effective Writing and Literature Review (3 hours)

Academic Writing Styles and Structures, Strategies for Literature Review and Synthesis, Citations, Referencing, and Avoiding Plagiarism, Tools for Organizing and Managing References,

Unit III: Research Tools for Data Analysis and Visualization (3 hours)

Introduction to Statistical Analysis Software (SAS), R, or Python, Data Analysis Techniques: Descriptive, Inferential, and Predictive, Data Visualization Tools: Graphs, Charts, and Infographics, Practical Hands-on Session Using Data Analysis Software

Unit IV: Manuscript Preparation and Journal Selection (3 hours)

Manuscript Structure: Abstract, Introduction, Methods, Results, Discussion (IMRAD), Selecting a Suitable Journal: Understanding Aims and Scope, Submission Guidelines and Manuscript Formatting, Peer Review Process and Responding to Reviewer Comments

Unit V: Publication Strategies and Academic Networking (3 hours)

Effective Strategies for Successful Publication, Building an Academic Profile: Networking, Collaboration, and Visibility, Utilizing Academic Platforms: ResearchGate, Google Scholar, etc., Open Access and Publishing in Predatory Journals: Pitfalls and Precautions

Text Books And Reference Books:

1.      "Writing Your Journal Article in Twelve Weeks" by Wendy Laura Belcher

Essential Reading / Recommended Reading

1.      "The Literature Review: A Step-by-Step Guide for Students" by Diana Ridley

Evaluation Pattern

audit course

MTEE341E1 - FACTS AND CUSTOM POWER DEVICES (2023 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Course Objectives:-Students will be able to:

1.  To learn the active and reactive power flow control in power system

2.  To understand the need for static compensators

To develop the different control strategies used for compensation

Course Outcome

CO1: To learn the active and reactive power flow control in power system

CO2: To understand the need for static compensators

CO3: To develop the different control strategies used for compensation

Unit-1
Teaching Hours:9
FACTS devices
 

Reactive power flow control in Power Systems - Control of dynamic power unbalances in Power System - Power flow control - Constraints of maximum transmission line loading - Benefits of FACTS Transmission line compensation - Uncompensated line -Shunt compensation, Series compensation - Phase angle control - Reactive power compensation - Shunt and Series compensation principles - Reactive compensation at transmission and distribution level

Unit-2
Teaching Hours:9
STATCOM
 

Static versus passive VAR compensator, Static shunt compensators: SVC and STATCOM Operation and control of TSC, TCR and STATCOM - Compensator control - Comparison between SVC and STATCOM

Unit-3
Teaching Hours:9
Compensators
 

Static series compensation: TSSC, SSSC -Static voltage and phase angle regulators - TCVR and TCPAR Operation and Control Applications, Static series compensation - GCSC,TSSC, TCSC and Static synchronous series compensators and their Control

Unit-4
Teaching Hours:9
UPFC
 

SSR and its damping Unified Power Flow Controller - Circuit Arrangement, Operation and control of UPFC, Basic Principle of P and Q control Independent real and reactive power flow control- Applications.

Unit-5
Teaching Hours:9
IPFC
 

Introduction to interline power flow controller. Modeling and analysis of FACTS Controllers - Simulation of FACTS controllers - Power quality problems in distribution systems, harmonics, loads that create harmonics modeling, harmonic propagation, series and parallel resonances mitigation of harmonics, passive filters, active filtering – shunt , series and hybrid and their control.

Text Books And Reference Books:

1.  K R Padiyar, “FACTS Controllers in Power Transmission and Distribution”, New Age InternationalPublishers, 2007

2.  X P Zhang, C Rehtanz, B Pal, “Flexible AC Transmission Systems- Modelling and Control”, SpringerVerlag, Berlin, 2006

Essential Reading / Recommended Reading

1.  N.G. Hingorani, L. Gyugyi, “Understanding FACTS: Concepts and Technology of Flexible

ACTransmission Systems”, IEEE Press Book, Standard Publishers and Distributors, Delhi, 2001.

2.  K.S.Sureshkumar ,S.Ashok , “FACTS Controllers & Applications”, E-book edition, Nalanda DigitalLibrary, NIT Calicut,2003

3.  G T Heydt , “Power Quality”, McGraw-Hill Professional, 2007

4.  T J E Miller, “Static Reactive Power Compensation”, John Wiley and Sons, Newyork, 1982.

Evaluation Pattern

ASSESSMENT - ONLY FOR THEORY COURSE (without practical component)

Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks)

End Semester Examination(ESE)          : 50% (50 marks out of 100 marks)

Components of the CIA

CIA I   :  Subject Assignments / Online Tests                        : 10 marks

CIA II  :   Mid Semester Examination (Theory)                     : 25 marks                       

CIAIII: Quiz/Seminar/Case Studies/Project/

Innovative assignments/ presentations/ publications             : 10 marks

Attendance                                                                              : 05 marks

            Total                                                                           : 50 marks

Mid Semester Examination (MSE): Theory Papers:

The MSE is conducted for 50 marks of 2 hours duration.

Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks

End Semester Examination (ESE):

The ESE is conducted for 100 marks of 3 hours duration.

The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions


 

MTEE381 - PROJECT WORK PHASE I (2023 Batch)

Total Teaching Hours for Semester:120
No of Lecture Hours/Week:16
Max Marks:100
Credits:8

Course Objectives/Course Description

 

Survey of the project topic

Course Outcome

CO1: To conduct detailed literature review

CO2: To develop a technical solution for the problem

CO3: Test and validate the solution

CO4: To prepare report on the project

Unit-1
Teaching Hours:60
Evaluation
 

§  Continuous Internal Assessment:100 Marks

¨      Presentation assessed by Panel Members

¨      Guide

¨      Assessment of Project Report

Text Books And Reference Books:

* IEEE digital Library

Essential Reading / Recommended Reading

* IEEE digital Library

Evaluation Pattern

v  Assessment of Project Work(Phase I)

§  Continuous Internal Assessment:100 Marks

¨       Presentation assessed by Panel Members

¨       Guide

 ¨       Assessment of  Report of phase-I

MTEE382 - INTERNSHIP (2023 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Internships are short-term work experiences that will allow  a student to observe and participate in professional work environments and explore how his interests relate to possible careers. They are important learning opportunities through industry exposure and practices.   More specifically, doing internships is beneficial because they provide the opportunity to:

  • Get an inside view of an industry and organization/company
  • Gain valuable skills and knowledge
  • Make professional connections and enhance student's network
  • Get experience in a field to allow the student  to make a career transition

Course Outcome

CO1: Get an inside view of an industry and organization/company

CO2: Gain valuable skills and knowledge

CO3: Make professional connections and enhance student's network

CO4: Get experience in a field to allow the student to make a career transition

Unit-1
Teaching Hours:30
Internship
 

REGULATIONS

1.The student shall undergo an Internship for 60 days  starting from the end of 2nd semester examination and completing it during the initial period of 7th semester.

2.The department shall nominate a faculty as a mentor for a group of students to prepare and monitor the progress of  the students

3. The students shall report the progress of the internship to the mentor/guide at regular intervals and may seek his/her advise.

Text Books And Reference Books:

The students can refer relevent standard text books or journal papers 

Essential Reading / Recommended Reading

The students can refer relevent standard text books or journal papers 

Evaluation Pattern

v   Assessment of Internship (M.Tech)

All students should complete internship either in Industry/Research labs before 3rd semester. This component carries 2 credits.

§  Continuous Internal Assessment:2 credits

 

o   Presentation assessed by Panel Members 

MTEEOE1 - BUSINESS ANALYTICS (2023 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 
  • Understand the role of business analytics within an organization.
  • Analyze data using statistical and data mining techniques and understand relationships between the underlying business processes of an organization.
  • To gain an understanding of how managers use business analytics to formulate and solve business problems and to support managerial decision making.
  • To become familiar with processes needed to develop, report, and analyze business data.
  • Use decision-making tools/Operations research techniques.
  • Mange business process using analytical and management tools.
  • Analyze and solve problems from different industries such as manufacturing, service, retail, software, banking and finance, sports, pharmaceutical, aerospace etc.

Course Outcome

CO1: Demonstrate knowledge of data analytics

CO2: Demonstrate the ability of think critically in making decisions based on data and deep analytics

CO3: Demonstrate the ability to use technical skills in predicative and prescriptive modeling to support business decision-making

CO4: Demonstrate the ability to translate data into clear, actionable insights

CO5: Practice software tools in data analytics

Unit-1
Teaching Hours:9
Business analytics
 

Overview of Business analytics, Scope of Business analytics, Business Analytics Process, Relationship of Business Analytics Process and organisation, competitive advantages of Business Analytics. Statistical Tools: Statistical Notation, Descriptive Statistical methods, Review of probability distribution and data modelling, sampling and estimation methods overview.

Unit-2
Teaching Hours:9
Trendiness and Regression Analysis
 

Modelling Relationships and Trends in Data, simple Linear Regression. Important Resources, Business Analytics Personnel, Data and models for Business analytics, problem solving, Visualizing and Exploring Data, Business Analytics Technology

Unit-3
Teaching Hours:9
Data analytics types
 

Organization Structures of Business analytics, Team management, Management Issues, Designing Information Policy, Outsourcing,  Ensuring Data Quality, Measuring contribution of Business analytics, Managing Changes. Descriptive Analytics, predictive analytics, predicative Modelling, Predictive analytics analysis, Data Mining, Data Mining Methodologies, Prescriptive analytics and its step in the business analytics Process, Prescriptive Modelling, nonlinear Optimization.

Unit-4
Teaching Hours:9
Forecasting Techniques
 

Qualitative and Judgmental Forecasting, Statistical Forecasting Models, Forecasting Models for Stationary Time Series, Forecasting Models for Time Series with a Linear Trend, Forecasting Time Series with Seasonality, Regression Forecasting with Casual Variables, Selecting Appropriate Forecasting Models. Monte Carlo Simulation and Risk Analysis: Monte Carle Simulation Using Analytic Solver Platform, New-Product Development Model, Newsvendor Model, Overbooking Model, Cash Budget Model.

Unit-5
Teaching Hours:9
Decision Analysis and Recent Trends
 

Formulating Decision Problems, Decision Strategies with the without Outcome Probabilities, Decision Trees, The Value of Information, Utility and Decision Making. Embedded and collaborative business intelligence, Visual data recovery, Data Storytelling and Data journalism.

Text Books And Reference Books:


Business Analytics by James Evans, persons Education.

Essential Reading / Recommended Reading


Business analytics Principles, Concepts, and Applications by Marc J. Schniederjans, Dara G. Schniederjans, Christopher M. Starkey, Pearson FT Press.

Evaluation Pattern

Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks)
End Semester Examination(ESE): 50% (50 marks out of 100 marks)
Components of the CIA
CIA I  :  Subject Assignments / Online Tests: 10 marks
CIA II:   Mid Semester Examination (Theory): 25 marks                  
CIAIII: Quiz/Seminar/Case Studies/Project/
Innovative assignments/ presentations/ publications: 10 marks
Attendance : 05 marks
Total  : 50 marks

Mid Semester Examination (MSE): Theory Papers:
The MSE is conducted for 50 marks of 2 hours duration.
Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks
End Semester Examination (ESE):
The ESE is conducted for 100 marks of 3 hours duration.
The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.
Question paper pattern is as follows.
Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year
The criteria for drawing the questions from the Question Bank are as follows
50 % - Medium Level questions
25 % - Simple level questions
25 % - Complex level questions

MTEE481 - PROJECT WORK PHASE II AND DISSERTATION (2023 Batch)

Total Teaching Hours for Semester:270
No of Lecture Hours/Week:18
Max Marks:300
Credits:16

Course Objectives/Course Description

 

To enable the student to convert  theory and concepts into application

Course Outcome

CO1: To identify a technical problem from industry or from the field

CO2: To conduct detailed literature survey

CO3: To develop solution for the problem

CO4: To test and validate the results

CO5: To write a report on the work

Unit-1
Teaching Hours:270
Project execution, presentation and publication of results
 

v  Assessment of Project Work(Phase II) and Dissertation

§  Continuous Internal Assessment:100 Marks

¨       Presentation assessed by Panel Members

¨       Guide

¨       Assessment of Project Report

§  End Semester Examination:100 Marks

¨       Viva Voce

¨       Demo

¨       Project Report

§  Dissertation (Exclusive assessment of Project Report): 100 Marks

¨       Internal Review : 50 Marks

 

¨       External review : 50 Marks

Text Books And Reference Books:

* IEEE digital Library

* Latex tutorial Manual

Essential Reading / Recommended Reading

* Latex Project tutorial Manual

Evaluation Pattern

     v  Assessment of Project Work(Phase II) and Dissertation

§  Continuous Internal Assessment:100 Marks

¨       Presentation assessed by Panel Members

¨       Guide

¨       Assessment of Project Report

§  End Semester Examination:100 Marks

¨       Viva Voce

¨       Demo

¨       Project Report

§  Dissertation (Exclusive assessment of Project Report): 100 Marks

¨       Internal Review : 50 Marks

¨       External review : 50 Marks