stability condition of a vehicle on a curved track and a banked road.To learn the structure of Vehicle , Electric Vehicles, Hybrid Electric Vehicle
To study about the EV conversion components
To know about the details and specifications for Electric Vehicles
To understand the concepts of Plug-in Hybrid Electric Vehicle
To model and simulate all types of DC motors
Course Outcomes:
After studying this course, students will be able to;
CO1: Summarize the History and Evolution of Vehicles, EVs, Hybrid and Plug-In Hybrid EVs CO2:Describe the various EV components
CO3: Describe the concepts related in the Plug-In Hybrid Electric Vehicles CO4: Analyze the details and Specifications for the various EVs developed. CO5: Describe the hybrid vehicle control strategy.
Vehicle mechanics- Roadway fundamentals, Laws of motion, Vehicle Kinetics, Dynamics of vehicle motion, propulsion power, velocity and acceleration, Tire –Road mechanics, Propulsion System Design.
Electric Vehicle History, and Evolution of Electric Vehicles. Series, Parallel and Series parallel Architecture, Micro and Mild architectures. Mountain Bike - Motorcycle- Electric Cars and Heavy Duty EVs. -Details and Specifications.
Power train Component sizing- Gears, Clutches, Differential, Transmission and Vehicle Brakes. EV power train sizing, HEV Powertrain sizing, Examples.
Vehicle supervisory controller, Mode selection strategy, Modal Control strategies.
Introduction-History-Comparison with electrical and hybrid electrical vehicle-Construction and working of PHEV-Block diagram and components-Charging mechanisms-Advantages of PHEVs.
Mehrdad Ehsani, YiminGao, Sebastian E. Gay, Ali Emadi, 'Modern Electric, Hybrid Electric and Fuel Cell Vehicles: Fundamentals, Theory and Design', CRC Press, 2004.
Build Your Own Electric Vehicle,Seth Leitman , Bob Brant, McGraw Hill, Third Edition 2013.
Advanced Electric Drive Vehicles, Ali Emadi, CRC Press, First edition 2017.
The Electric Vehicle Conversion Handbook: How to Convert Cars, Trucks, Motorcycles, and Bicycles
-- Includes EV Components, Kits, and Project Vehicles Mark Warner, HP Books, 2011.
Heavy-duty Electric Vehicles from Concept to Reality, Shashank Arora, Alireza Tashakori Abkenar, Shantha Gamini Jayasinghe, Kari Tammi, Elsevier Science, 2021
Electric Vehicles Modern Technologies and Trends, Nil Patel, Akash Kumar Bhoi, Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen Springer, 2020
Hybrid Electric Vehicles: A Review of Existing Configurations and Thermodynamic Cycles, Rogelio León , Christian Montaleza , José Luis Maldonado , MarCOs Tostado-Véliz and Francisco Jurado, Thermo, 2021, 1, 134–150. https://doi.org/10.3390/thermo10200
Course Outcomes:
After studying this course, students will be able to;
CO1: Understand the dynamics of the motor vehicle, modeling and simulation of the dynamic behavior of the vehicle.
CO2: Determine acceleration, tractive effort and reactions for different drives
CO3: Know about the gyroscopic effects and determine stability condition of a vehicle on a curved track and a banked road.
CO4: Design and analyze passive, semi-active, and active suspension using quarter-car, half car, and full car model
CO5: Understand vehicle aerodynamic and dynamic control system
History of road and off road vehicle system dynamics - dynamics of the motor vehicle, coordinate systems- vehicle fixed coordinates system, , details of vehicle systems, wheel angles, typical data of vehicles. Fundamental approaches to vehicle dynamics modeling lumped mass, vehicle fixed coordinate system, motion variables, earth fixed coordinate system, SAE coordinate system, Euler angles ,forces, Newton’s second law. Definitions- modeling and simulation of dynamic behavior of vehicle., motion analysis, force analysis, and energy analysis.
Introduction to longitudinal dynamics - Performance of road vehicles: forces and moments on vehicle, equation of motion, tire forces, rolling resistance, weight distribution, tractive effort/tractive resistance and power available from the engine/ power required for propulsion, road performance curves- acceleration, grade ability, drawbar pull and the problems related to these terms. Calculation of maximum acceleration braking torque, braking force, brake proportioning, braking efficiency, stopping distance, load distribution (three wheeled and four wheeled vehicles), calculation of acceleration, tractive effort and reactions for different drives, Stability of a vehicle on slope, (Problems related to these).
Introduction to lateral dynamics - Steering geometry, types of steering systems, fundamental condition for true rolling, development of lateral forces. slip angle, cornering force, cornering stiffness, pneumatic trail, self aligning torque, power consumed by tire, tire stiffness ,hysteresis effect in tires, steady state handling characteristics. yaw velocity, lateral acceleration, curvature response & directional stability. Stability of a vehicle on a curved track and a banked road. gyroscopic effects, weight transfer during acceleration,
cornering and braking, stability of a rigid vehicle and equations of motion of a rigid vehicle, cross wind handling, the problems related to these terms.
Introduction to vertical dynamics - Human response to vibrations, classification of vibration, specification and vibration , sources of vibration, suspension systems, Modal Analysis, One DOF, two DOF, free and forced vibration, damped vibration, magnification and transmissibility, vibration absorber, functions of suspension system. body vibrations: bouncing and pitching. doubly conjugate points (only basic idea). body rolling. roll center and roll axis, roll axis and the vehicle under the action of side forces, stability against body rolling. Vehicle dynamics and suspension design for stability, choice of suspension spring rate, chassis springs and theory of chassis springs, gas & and hydraulic dampers and choice of damper, damper characteristics, mechanics of an independent suspension system.. Design and analysis of passive, semi-active, and active suspension using quarter-car, half car, and full car model.
Road Loads: Air resistance-Mechanics of air flow around a vehicle, pressure distribution on a vehicle, factors affecting rolling resistance, aerodynamic forces – aerodynamic drag, drag components, drag coefficient, aerodynamic aids, aerodynamic side force, lift force, pitching moment, yawing moment, rolling moment, cross wind sensitivity . Vehicle dynamic Control, modelling of actuators, sensors for automobile control, sensors for detecting vehicle environment, central tyre inflation system. Prediction of vehicle performance. ABS, stability control, traction control.
Rajesh Rajamani, “Vehicle Dynamics and Control”, 1st edition, Springer, 2005
Singiresu S. Rao, “Mechanical Vibrations”, 5th Edition, Prentice Hall, 2010
Thomas D. Gillespie, “Fundamentals of Vehicle Dynamics”, Society of Automotive Engineers Inc, 1992
Wong. J. Y., “Theory of Ground Vehicles”, 3rd Edition, Wiley-Interscience, 2001 5. N.K. Giri, Automotive Mechanics, Kanna Publishers, 2007
Theory of Ground Vehicles - J. Y. Woung - John Willey & Sons, NY
Steering, Suspension & Tyres – J. G. Giles, Ilete Books Ltd., London
Mechanics of Road Vehicles – W. Steed, Ilete Books Ltd. London
Automotive Chassis – P. M. Heldt, Chilton Co. NK 5. Gillespie.T.D., “Fundamental of vehicle dynamic society of Automotive Engineers ",USA, 1992.
Vehicle dynamics and control by Rajesh Rajamani , Springer publication
Vehicle Dynamics : Theory and Application by Reza N Jazar, Springer publication.
Course Outcomes:
After studying this course, students will be able to; CO1: Understand basic concepts of Electric Drives
CO2: Perform Transient and steady-state analysis in DC Drives
CO3: Know the concepts used in Induction Motor Drives
CO4: Understand fundamentals used in Synchronous Motors Drives
CO5: Compare Switched reluctance motors, Stepper Motors, Permanent Magnet Motor.
Pillai S. K. "A first course on Electrical Drives", Second edition, Wiley Eastern.
Ned Mohan Electrical Machine Drive WILEY INDIA
Dubey G. K., "Power Semiconductor Controlled Drives", PHI,
Dubey G. K. , "Fundamentals of Electrical Drives". Narosa Publishing House.
Bose B. K., "Power Electronics and AC Drives", PHI Learning.
Murphy M. D., and Tumbuli F., "Power Electronic Control of AC Motors", Pergamon
Press, Oxford University Press.
P.V. Rao, "Power semiconductor Drives", BS Publications
S. Shiva Nagaraju power semiconductor drive PHI learning
After studying this course, students will be able to; CO1: Differentiate sensor, transmitter and transducer
CO2: Understand the Principle of operation of inductive & and capacitive transducer
CO3: Know about types, and selection criteria of Actuators
CO4: Compare principle of working of Micro Sensors and Micro Actuators CO5: Know about the Materials for sensors
Difference between sensor, transmitter and transducer - Primary measuring elements - selection and characteristics: Range; resolution, Sensitivity, error, repeatability, linearity and accuracy, impedance, backlash, Response time, Dead band. Signal transmission - Types of signal: Pneumatic signal; Hydraulic signal; Electronic Signal. Principle of operation, construction details, characteristics and applications of potentiometer, Proving Rings, Strain Gauges, Resistance thermometer, Thermistor, Hot-wire anemometer, Resistance Hygrometer, Photo-resistive sensor.
Inductive transducers: - Principle of operation, construction details, characteristics and applications of LVDT, Induction potentiometer, variable reluctance transducer, synchros, microsyn. Capacitive transducers: - Principle of operation, construction details, characteristics of Capacitive transducers – different types & signal conditioning- Applications:- capacitor microphone, capacitive pressure sensor, proximity sensor.
Definition, types, and selection of Actuators; linear; rotary; Logical and Continuous Actuators, Pneumatic actuator- Electro-Pneumatic actuator; cylinder, rotary actuators, Mechanical actuating system: Hydraulic actuator - Control valves; Construction, Characteristics and Types, Selection criteria. Electrical actuating systems: Solid-state switches, Solenoids, Electric Motors- Principle of operation and its application: D.C motors - AC motors - Single phase & 3 Phase Induction Motor; Synchronous Motor; Stepper motors - Piezoelectric Actuator.
Micro Sensors: Principles and examples, Force and pressure micro sensors, position and speed micro sensors, acceleration micro sensors, chemical sensors, biosensors, temperature micro sensors and flow micro sensors. Micro Actuators: Actuation principle, shape memory effects-one way, two way and pseudo elasticity. Types of micro actuators- Electrostatic, Magnetic, Fluidic, Inverse piezo effect, other principles.
Materials for sensors: Silicon, Plastics, metals, ceramics, glasses, nano materials Processing techniques: Vacuum deposition, sputtering, chemical vapour deposition, electro plating, photolithography, silicon micro machining, Bulk silicon micro machining, Surface silicon micro machining, LIGA process.
Patranabis.D, “Sensors and Transducers”, Wheeler publisher, 1994.
Sergej Fatikow and Ulrich Rembold, “ Microsystem Technology and Microbotics”, First edition, Springer –Verlag NEwyork, Inc, 1997.
Jacob Fraden, “Hand Book of Modern Sensors: Physics, Designs and Application” Fourth edition, Springer, 2010.
Robert H Bishop, “The Mechatronics Hand Book”, CRC Press, 2002.
Thomas. G. Bekwith and Lewis Buck.N, Mechanical Measurements, Oxford and IBH publishing Co. Pvt. Ltd.,
Massood Tabib and Azar, “Microactuators Electrical, Magnetic, thermal, optical, mechanical, chemical and smart structures”, First edition, Kluwer academic publishers, Springer, 1997.
Manfred Kohl, “Shape Memory Actuators”, first edition, Springer.
After completion of this course, students will be able to;
Know about comparative properties of alternate fuels, CNG, LPG, Alcohol, Vegetable oil and Bio-gas
Understand modifications required in SI and CI engines for CNG and LPG Engines
Compare the working principle of Hydrogen Cell and Fuel Cell
Understand about the Emission formation from SI & CI Engines and its Control
Measure Emission using Smokemeter
Estimate of petroleum reserve, need for alternate fuel, availability and comparative properties of alternate fuels, CNG, LPG, Alcohol, Vegetable oil and Bio-gas
Availability, properties, modifications required in SI and CI engines, performance and emission characteristics, storage, handling and dispensing, and safety aspects. Alcohol - Manufacture of alcohol, properties, blending of Methanol and Ethanol, engine design modifications required and effects of design parameters, performance and emission characteristics, durability. Types of vegetable oils for engine application, esterification, biogas, properties, engine performance and emission characteristics.
Production methods, properties, performance and emission characteristics, storage and handling, safety aspects, Working principle, classification, description of fuel cell systems, fuel cell components, properties of fuel cell, general performance characteristics, emission characteristics, merits and demerits, vehicle design and layout aspects.
Emission formation in S.I. engines – Hydrocarbons – Carbon monoxide – Nitric Oxide, Lead particulates – Polyneculear aromatic hydro carbon emission – Effects of design and operating variables on emission formation in spark ignition engines – Controlling of pollutant formation in engines – Thermal reactors –
Catalytic converters – Charcoal Canister Control for evaporative emission – Positive crank case ventilation system for UBHC emission reduction. Chemical delay – Significance – Intermediate compound formation – Pollutant formation on incomplete combustion – effect of operating variables on pollutant formation – Controlling of emissions – Driving behavior – Fumigation – Exhaust gas recirculation – Air injection – Cetane number effect.
Measurement of CO, CO2, by NDIR. Hydrocarbon by FID – Chemiluminescent detector for NOx measurement, Smoke meters – Dilution tunnel technique for particulate measurement. Procedures on Engine and Chassis Constant Volume Sampling procedures –Emission Test– Sampling probes and valves – Quantifying emissions – Dynamometers
Ganesan.V, Internal Combustion Engines, Tata McGraw Hill, 1994.
Crouse.W.M, Anglin.A.L., Automotive Emission Control, McGraw Hill 1995.
Springer.G.S, Patterson.D.J, Engine Emissions, pollutant formation, Plenum Press, 1986
Patterson, D.J, Henin.N.A, Emissions from Combustion engines and their Control, Anna Arbor Science, 1985. Linden.D, Handbook of Batteries and Fuel Cells, McGraw Hill, 1995.
Maxwell et al, Alternative Fuel : Emission, Economic and Performance, SAE, 1995
Watson, E.B., Alternative fuels for the combustion engine, ASME, 1990
Bechtold, R., Alternative fuels guidebook, 1998.
Joseph, N., Hydrogen fuel for structure transportation, SAE, 1996.
Holt and Danniel, Fuel cell powered vehicles: Automotive technology for the future, SAE, 2001.
This course aims to provide the required skill;
To introduce the fundamental concepts of machine learning and its applications
To learn the classification, clustering and regression based machine learning algorithms
To understand the deep learning architectures
To understand the methods of solving real life problems using the machine learning techniques
To understand the multiple learners, boosting and stacked generalization
After completion of this course, students will be able to;
Understand the basic concepts of Bayesian theory and normal densities
Implement different classification algorithms used in machine learning
Implement clustering and component analysis techniques
Design and implement deep learning architectures for solving real life problems
Combine the evidence from two or more models/methods for designing a system
Syllabus
- classification, clustering, linear and logistic regression – Types of learning - Bayesian decision theory - classifiers, discriminant functions, and decision surfaces -univariate and multivariate normal densities - Bayesian belief networks.
UNIT V – Combining Multiple Learners: Generating diverse learners - model combination schemes - voting - error-correcting output codes -bagging - boosting - mixture of experts revisited - stacked generalization - fine-tuning an ensemble –cascading
R. O. Duda, E. Hart, and D.G. Stork, “Pattern Classification”, Second Edition, John Wiley & Sons, Singapore, 2012.
Francois Chollet, “ Deep Learning with Python”, Manning Publications, Shelter Island, New York, 2018.
Ethem Alpaydin, “Introduction to Machine Learning”, 3rd Edition, MIT Press, 2014.
C. M. Bishop, “Pattern Recognition and Machine Learning”, Springer, 2006.
Kevin P. Murphy, “Machine Learning: A Probabilistic Perspective”, MIT Press, 2012.
Navin Kumar Manaswi, “Deep Learning with Applications using Python”, A press, New York, 2018.
Content Beyond Syllabus
1,Introduction to Genetic algorithm, Heuristic algorithms: A*, D*, Real-Time A*
This course aims at providing the required skill;
To apply the statistical tools in engineering problems
To introduce the basic concepts of probability and random variables
To introduce the basic concepts of two dimensional random variables
To acquaint the knowledge of testing of hypothesis for small and large samples which plays an important role in real life problems
To understand the basic concepts of statistical quality control
After completion of this course, students will be able to;
Understand the fundamental knowledge of the concepts of probability and have knowledge of standard distributions which can describe real life phenomenon
Understand the basic concepts of one and two dimensional random variables and apply in engineering applications
Apply the concept of testing of hypothesis for small and large samples in real life problems
Apply the basic concepts of classifications of design of experiments in the field of agriculture and statistical quality control
Have the notion of sampling distributions and statistical techniques used in engineering and management problems
Johnson, R.A., Miller, I and Freund J., "Miller and Freund’s Probability and Statistics for Engineers", Pearson Education, Asia, 8th Edition, 2015.
Milton. J. S. and Arnold. J.C., "Introduction to Probability and Statistics", Tata McGraw Hill, 4th Edition, 2007.
Devore. J.L., "Probability and Statistics for Engineering and the Sciences”, Cengage Learning, New Delhi, 8th Edition, 2014.
Papoulis, A. and Unnikrishnapillai, S., "Probability, Random Variables and Stochastic Processes", McGraw Hill Education India, 4th Edition, New Delhi, 2010.
Ross, S.M., "Introduction to Probability and Statistics for Engineers and Scientists", 3rd Edition, Elsevier, 2004.
Spiegel. M.R., Schiller. J. and Srinivasan, R.A., "Schaum’s Outline of Theory and Problems of Probability and Statistics", Tata McGraw Hill Edition, 2004.
Walpole. R.E., Myers. R.H., Myers. S.L. and Ye. K., "Probability and Statistics for Engineers and Scientists", Pearson Education, Asia, 8th Edition, 2007.
Use of Bayes theorem, t -test for the research purposes
Practicing hypothesis framing on real time applications
1. Be exposed to big data
2, Learn the different ways of Data Analysis
Be familiar with data streams
Learn the mining and clustering
Be familiar with the visualization
After completion of this course, students will be able to;
Understand and apply the statistical analysis methods
Compare and contrast various soft computing frameworks
Design and develop distributed file systems 4, To develop Stream data model
5. Apply Visualization techniques in real time applications
- Modern data analytic tools, Stastical concepts: Sampling distributions, resampling, statistical inference, prediction error.
Michael Berthold, David J. Hand, “Intelligent Data Analysis”, Springer, 2007.
Anand RajaRaman and Jeffrey David Ullman, “Mining of Massive Datasets”, Cambridge University Press, 2012.
Bill Franks, “Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with advanced analystics”, John Wiley & sons, 2012.
Glenn J. Myatt, “Making Sense of Data”, John Wiley & Sons, 2007 Pete Warden, Big Data Glossary, O‟ Reilly, 2011.
Jiawei Han, Micheline Kamber “Data Mining Concepts and Techniques”, Second Edition, Elsevier, Reprinted 2008.
Predictive Analytics, linear regression
To study fundamentals of Computational Fluid Dynamics (CFD)
To perform CFD analysis of lid driven cavity in Open-Foam
To perform CFD analysis of square tube in Open-Foam
To perform CFD analysis of a 2D-plate in Open-Foam
To perform CFD analysis of bifurcated blood vessel in FEM
To study fundamentals of Finite element method and FEA
To perform FEM analysis of deep drawing process in FEM
To study fundamentals of Sci-Lab
To perform matrix operations in Sci-lab
To plot 2D & 3D graphs in Sci-lab
Versteeg H; An introduction to Computational Fluid Dynamics (The Finite Volume Method);Pearson
Jiyuan Tu; Computational Fluid Dynamics: A Practical Approach; Butterworth Heinemann.
Gokhale NS; Practical Finite Element Analysis; Finite to Infinite
Seshu P; Finite element analysis; PHI.
Reddy JN; Introduction to the Finite Element Method; McGraw Hill Inc.
Das VV; Programming in Scilab 4.1; New Age International Publishers.
Verma A K; Scilab : A Beginner’s Approach; Cengage publishers
To write a Python program to find GCD of two numbers.
To write a Python Program to find the square root of a number by Newton’s Method.
To write a Python program to find the exponentiation of a number.
To write a Python Program to find the maximum from a list of numbers.
To write a Python Program to perform Linear Search
To write a Python Program to perform binary search.
To write a Python Program to perform selection sort.
To write a Python Program to perform insertion sort.
To write a Python Program to perform Merge sort.
To write a Python program to find first n prime numbers.
To write a Python program to multiply matrices.
To write a Python program for command line arguments.
To write a Python program to find the most frequent words in a text read from a file.
To write a Python program to simulate elliptical orbits in Pygame.
To write a Python program to bouncing ball in Pygame.
Timothy A. Budd: Exploring python, McGraw-Hill Education.
R.Nageshwar Rao ,”Python Programming” ,Wiley India
Allen B. Downey; Think Python, O'Reilly Media, Inc.
Minor Project-I will be carried out in a group of students (Maximum 03) and team will work under faculty supervisor of relevant field.
Students are suggested to select recent topic related to Challenges and advancements in the field of Electric Vehicle Technology for research as a minor project -I.
To learn the structure of Vehicle , Electric Vehicles, Hybrid Electric Vehicle
To study about the EV conversion components
To know about the details and specifications for Electric Vehicles
To understand the concepts of Plug-in Hybrid Electric Vehicle
To model and simulate all types of DC motors
Course Outcomes:
After studying this course, students will be able to;
CO1: Summarize the History and Evolution of Vehicles, EVs, Hybrid and Plug-In Hybrid EVs CO2:Describe the various EV components
CO3: Describe the concepts related in the Plug-In Hybrid Electric Vehicles CO4: Analyze the details and Specifications for the various EVs developed. CO5: Describe the hybrid vehicle control strategy.
Vehicle mechanics- Roadway fundamentals, Laws of motion, Vehicle Kinetics, Dynamics of vehicle motion, propulsion power, velocity and acceleration, Tire –Road mechanics, Propulsion System Design.
Electric Vehicle History, and Evolution of Electric Vehicles. Series, Parallel and Series parallel Architecture, Micro and Mild architectures. Mountain Bike - Motorcycle- Electric Cars and Heavy Duty EVs. -Details and Specifications.
Power train Component sizing- Gears, Clutches, Differential, Transmission and Vehicle Brakes. EV power train sizing, HEV Powertrain sizing, Examples.
Vehicle supervisory controller, Mode selection strategy, Modal Control strategies.
Introduction-History-Comparison with electrical and hybrid electrical vehicle-Construction and working of PHEV-Block diagram and components-Charging mechanisms-Advantages of PHEVs.
Mehrdad Ehsani, YiminGao, Sebastian E. Gay, Ali Emadi, 'Modern Electric, Hybrid Electric and Fuel Cell Vehicles: Fundamentals, Theory and Design', CRC Press, 2004.
Build Your Own Electric Vehicle,Seth Leitman , Bob Brant, McGraw Hill, Third Edition 2013.
Advanced Electric Drive Vehicles, Ali Emadi, CRC Press, First edition 2017.
The Electric Vehicle Conversion Handbook: How to Convert Cars, Trucks, Motorcycles, and Bicycles
-- Includes EV Components, Kits, and Project Vehicles Mark Warner, HP Books, 2011.
Heavy-duty Electric Vehicles from Concept to Reality, Shashank Arora, Alireza Tashakori Abkenar, Shantha Gamini Jayasinghe, Kari Tammi, Elsevier Science, 2021
Electric Vehicles Modern Technologies and Trends, Nil Patel, Akash Kumar Bhoi, Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen Springer, 2020
Hybrid Electric Vehicles: A Review of Existing Configurations and Thermodynamic Cycles, Rogelio León , Christian Montaleza , José Luis Maldonado , MarCOs Tostado-Véliz and Francisco Jurado, Thermo, 2021, 1, 134–150. https://doi.org/10.3390/thermo10200
Course Outcomes:
After studying this course, students will be able to;
CO1: Understand the dynamics of the motor vehicle, modeling and simulation of the dynamic behavior of the vehicle.
CO2: Determine acceleration, tractive effort and reactions for different drives
CO3: Know about the gyroscopic effects and determine stability condition of a vehicle on a curved track and a banked road.
CO4: Design and analyze passive, semi-active, and active suspension using quarter-car, half car, and full car model
CO5: Understand vehicle aerodynamic and dynamic control system
History of road and off road vehicle system dynamics - dynamics of the motor vehicle, coordinate systems- vehicle fixed coordinates system, , details of vehicle systems, wheel angles, typical data of vehicles. Fundamental approaches to vehicle dynamics modeling lumped mass, vehicle fixed coordinate system, motion variables, earth fixed coordinate system, SAE coordinate system, Euler angles ,forces, Newton’s second law. Definitions- modeling and simulation of dynamic behavior of vehicle., motion analysis, force analysis, and energy analysis.
Introduction to longitudinal dynamics - Performance of road vehicles: forces and moments on vehicle, equation of motion, tire forces, rolling resistance, weight distribution, tractive effort/tractive resistance and power available from the engine/ power required for propulsion, road performance curves- acceleration, grade ability, drawbar pull and the problems related to these terms. Calculation of maximum acceleration braking torque, braking force, brake proportioning, braking efficiency, stopping distance, load distribution (three wheeled and four wheeled vehicles), calculation of acceleration, tractive effort and reactions for different drives, Stability of a vehicle on slope, (Problems related to these).
Introduction to lateral dynamics - Steering geometry, types of steering systems, fundamental condition for true rolling, development of lateral forces. slip angle, cornering force, cornering stiffness, pneumatic trail, self aligning torque, power consumed by tire, tire stiffness ,hysteresis effect in tires, steady state handling characteristics. yaw velocity, lateral acceleration, curvature response & directional stability. Stability of a vehicle on a curved track and a banked road. gyroscopic effects, weight transfer during acceleration,
cornering and braking, stability of a rigid vehicle and equations of motion of a rigid vehicle, cross wind handling, the problems related to these terms.
Introduction to vertical dynamics - Human response to vibrations, classification of vibration, specification and vibration , sources of vibration, suspension systems, Modal Analysis, One DOF, two DOF, free and forced vibration, damped vibration, magnification and transmissibility, vibration absorber, functions of suspension system. body vibrations: bouncing and pitching. doubly conjugate points (only basic idea). body rolling. roll center and roll axis, roll axis and the vehicle under the action of side forces, stability against body rolling. Vehicle dynamics and suspension design for stability, choice of suspension spring rate, chassis springs and theory of chassis springs, gas & and hydraulic dampers and choice of damper, damper characteristics, mechanics of an independent suspension system.. Design and analysis of passive, semi-active, and active suspension using quarter-car, half car, and full car model.
Road Loads: Air resistance-Mechanics of air flow around a vehicle, pressure distribution on a vehicle, factors affecting rolling resistance, aerodynamic forces – aerodynamic drag, drag components, drag coefficient, aerodynamic aids, aerodynamic side force, lift force, pitching moment, yawing moment, rolling moment, cross wind sensitivity . Vehicle dynamic Control, modelling of actuators, sensors for automobile control, sensors for detecting vehicle environment, central tyre inflation system. Prediction of vehicle performance. ABS, stability control, traction control.
Rajesh Rajamani, “Vehicle Dynamics and Control”, 1st edition, Springer, 2005
Singiresu S. Rao, “Mechanical Vibrations”, 5th Edition, Prentice Hall, 2010
Thomas D. Gillespie, “Fundamentals of Vehicle Dynamics”, Society of Automotive Engineers Inc, 1992
Wong. J. Y., “Theory of Ground Vehicles”, 3rd Edition, Wiley-Interscience, 2001 5. N.K. Giri, Automotive Mechanics, Kanna Publishers, 2007
Theory of Ground Vehicles - J. Y. Woung - John Willey & Sons, NY
Steering, Suspension & Tyres – J. G. Giles, Ilete Books Ltd., London
Mechanics of Road Vehicles – W. Steed, Ilete Books Ltd. London
Automotive Chassis – P. M. Heldt, Chilton Co. NK 5. Gillespie.T.D., “Fundamental of vehicle dynamic society of Automotive Engineers ",USA, 1992.
Vehicle dynamics and control by Rajesh Rajamani , Springer publication
Vehicle Dynamics : Theory and Application by Reza N Jazar, Springer publication.
Course Outcomes:
After studying this course, students will be able to; CO1: Understand basic concepts of Electric Drives
CO2: Perform Transient and steady-state analysis in DC Drives
CO3: Know the concepts used in Induction Motor Drives
CO4: Understand fundamentals used in Synchronous Motors Drives
CO5: Compare Switched reluctance motors, Stepper Motors, Permanent Magnet Motor.
Pillai S. K. "A first course on Electrical Drives", Second edition, Wiley Eastern.
Ned Mohan Electrical Machine Drive WILEY INDIA
Dubey G. K., "Power Semiconductor Controlled Drives", PHI,
Dubey G. K. , "Fundamentals of Electrical Drives". Narosa Publishing House.
Bose B. K., "Power Electronics and AC Drives", PHI Learning.
Murphy M. D., and Tumbuli F., "Power Electronic Control of AC Motors", Pergamon
Press, Oxford University Press.
P.V. Rao, "Power semiconductor Drives", BS Publications
S. Shiva Nagaraju power semiconductor drive PHI learning
After studying this course, students will be able to; CO1: Differentiate sensor, transmitter and transducer
CO2: Understand the Principle of operation of inductive & and capacitive transducer
CO3: Know about types, and selection criteria of Actuators
CO4: Compare principle of working of Micro Sensors and Micro Actuators CO5: Know about the Materials for sensors
Difference between sensor, transmitter and transducer - Primary measuring elements - selection and characteristics: Range; resolution, Sensitivity, error, repeatability, linearity and accuracy, impedance, backlash, Response time, Dead band. Signal transmission - Types of signal: Pneumatic signal; Hydraulic signal; Electronic Signal. Principle of operation, construction details, characteristics and applications of potentiometer, Proving Rings, Strain Gauges, Resistance thermometer, Thermistor, Hot-wire anemometer, Resistance Hygrometer, Photo-resistive sensor.
Inductive transducers: - Principle of operation, construction details, characteristics and applications of LVDT, Induction potentiometer, variable reluctance transducer, synchros, microsyn. Capacitive transducers: - Principle of operation, construction details, characteristics of Capacitive transducers – different types & signal conditioning- Applications:- capacitor microphone, capacitive pressure sensor, proximity sensor.
Definition, types, and selection of Actuators; linear; rotary; Logical and Continuous Actuators, Pneumatic actuator- Electro-Pneumatic actuator; cylinder, rotary actuators, Mechanical actuating system: Hydraulic actuator - Control valves; Construction, Characteristics and Types, Selection criteria. Electrical actuating systems: Solid-state switches, Solenoids, Electric Motors- Principle of operation and its application: D.C motors - AC motors - Single phase & 3 Phase Induction Motor; Synchronous Motor; Stepper motors - Piezoelectric Actuator.
Micro Sensors: Principles and examples, Force and pressure micro sensors, position and speed micro sensors, acceleration micro sensors, chemical sensors, biosensors, temperature micro sensors and flow micro sensors. Micro Actuators: Actuation principle, shape memory effects-one way, two way and pseudo elasticity. Types of micro actuators- Electrostatic, Magnetic, Fluidic, Inverse piezo effect, other principles.
Materials for sensors: Silicon, Plastics, metals, ceramics, glasses, nano materials Processing techniques: Vacuum deposition, sputtering, chemical vapour deposition, electro plating, photolithography, silicon micro machining, Bulk silicon micro machining, Surface silicon micro machining, LIGA process.
Patranabis.D, “Sensors and Transducers”, Wheeler publisher, 1994.
Sergej Fatikow and Ulrich Rembold, “ Microsystem Technology and Microbotics”, First edition, Springer –Verlag NEwyork, Inc, 1997.
Jacob Fraden, “Hand Book of Modern Sensors: Physics, Designs and Application” Fourth edition, Springer, 2010.
Robert H Bishop, “The Mechatronics Hand Book”, CRC Press, 2002.
Thomas. G. Bekwith and Lewis Buck.N, Mechanical Measurements, Oxford and IBH publishing Co. Pvt. Ltd.,
Massood Tabib and Azar, “Microactuators Electrical, Magnetic, thermal, optical, mechanical, chemical and smart structures”, First edition, Kluwer academic publishers, Springer, 1997.
Manfred Kohl, “Shape Memory Actuators”, first edition, Springer.
After completion of this course, students will be able to;
Know about comparative properties of alternate fuels, CNG, LPG, Alcohol, Vegetable oil and Bio-gas
Understand modifications required in SI and CI engines for CNG and LPG Engines
Compare the working principle of Hydrogen Cell and Fuel Cell
Understand about the Emission formation from SI & CI Engines and its Control
Measure Emission using Smokemeter
Estimate of petroleum reserve, need for alternate fuel, availability and comparative properties of alternate fuels, CNG, LPG, Alcohol, Vegetable oil and Bio-gas
Availability, properties, modifications required in SI and CI engines, performance and emission characteristics, storage, handling and dispensing, and safety aspects. Alcohol - Manufacture of alcohol, properties, blending of Methanol and Ethanol, engine design modifications required and effects of design parameters, performance and emission characteristics, durability. Types of vegetable oils for engine application, esterification, biogas, properties, engine performance and emission characteristics.
Production methods, properties, performance and emission characteristics, storage and handling, safety aspects, Working principle, classification, description of fuel cell systems, fuel cell components, properties of fuel cell, general performance characteristics, emission characteristics, merits and demerits, vehicle design and layout aspects.
Emission formation in S.I. engines – Hydrocarbons – Carbon monoxide – Nitric Oxide, Lead particulates – Polyneculear aromatic hydro carbon emission – Effects of design and operating variables on emission formation in spark ignition engines – Controlling of pollutant formation in engines – Thermal reactors –
Catalytic converters – Charcoal Canister Control for evaporative emission – Positive crank case ventilation system for UBHC emission reduction. Chemical delay – Significance – Intermediate compound formation – Pollutant formation on incomplete combustion – effect of operating variables on pollutant formation – Controlling of emissions – Driving behavior – Fumigation – Exhaust gas recirculation – Air injection – Cetane number effect.
Measurement of CO, CO2, by NDIR. Hydrocarbon by FID – Chemiluminescent detector for NOx measurement, Smoke meters – Dilution tunnel technique for particulate measurement. Procedures on Engine and Chassis Constant Volume Sampling procedures –Emission Test– Sampling probes and valves – Quantifying emissions – Dynamometers
Ganesan.V, Internal Combustion Engines, Tata McGraw Hill, 1994.
Crouse.W.M, Anglin.A.L., Automotive Emission Control, McGraw Hill 1995.
Springer.G.S, Patterson.D.J, Engine Emissions, pollutant formation, Plenum Press, 1986
Patterson, D.J, Henin.N.A, Emissions from Combustion engines and their Control, Anna Arbor Science, 1985. Linden.D, Handbook of Batteries and Fuel Cells, McGraw Hill, 1995.
Maxwell et al, Alternative Fuel : Emission, Economic and Performance, SAE, 1995
Watson, E.B., Alternative fuels for the combustion engine, ASME, 1990
Bechtold, R., Alternative fuels guidebook, 1998.
Joseph, N., Hydrogen fuel for structure transportation, SAE, 1996.
Holt and Danniel, Fuel cell powered vehicles: Automotive technology for the future, SAE, 2001.
This course aims to provide the required skill;
To introduce the fundamental concepts of machine learning and its applications
To learn the classification, clustering and regression based machine learning algorithms
To understand the deep learning architectures
To understand the methods of solving real life problems using the machine learning techniques
To understand the multiple learners, boosting and stacked generalization
After completion of this course, students will be able to;
Understand the basic concepts of Bayesian theory and normal densities
Implement different classification algorithms used in machine learning
Implement clustering and component analysis techniques
Design and implement deep learning architectures for solving real life problems
Combine the evidence from two or more models/methods for designing a system
Syllabus
- classification, clustering, linear and logistic regression – Types of learning - Bayesian decision theory - classifiers, discriminant functions, and decision surfaces -univariate and multivariate normal densities - Bayesian belief networks.
UNIT V – Combining Multiple Learners: Generating diverse learners - model combination schemes - voting - error-correcting output codes -bagging - boosting - mixture of experts revisited - stacked generalization - fine-tuning an ensemble –cascading
R. O. Duda, E. Hart, and D.G. Stork, “Pattern Classification”, Second Edition, John Wiley & Sons, Singapore, 2012.
Francois Chollet, “ Deep Learning with Python”, Manning Publications, Shelter Island, New York, 2018.
Ethem Alpaydin, “Introduction to Machine Learning”, 3rd Edition, MIT Press, 2014.
C. M. Bishop, “Pattern Recognition and Machine Learning”, Springer, 2006.
Kevin P. Murphy, “Machine Learning: A Probabilistic Perspective”, MIT Press, 2012.
Navin Kumar Manaswi, “Deep Learning with Applications using Python”, A press, New York, 2018.
Content Beyond Syllabus
1,Introduction to Genetic algorithm, Heuristic algorithms: A*, D*, Real-Time A*
This course aims at providing the required skill;
To apply the statistical tools in engineering problems
To introduce the basic concepts of probability and random variables
To introduce the basic concepts of two dimensional random variables
To acquaint the knowledge of testing of hypothesis for small and large samples which plays an important role in real life problems
To understand the basic concepts of statistical quality control
After completion of this course, students will be able to;
Understand the fundamental knowledge of the concepts of probability and have knowledge of standard distributions which can describe real life phenomenon
Understand the basic concepts of one and two dimensional random variables and apply in engineering applications
Apply the concept of testing of hypothesis for small and large samples in real life problems
Apply the basic concepts of classifications of design of experiments in the field of agriculture and statistical quality control
Have the notion of sampling distributions and statistical techniques used in engineering and management problems
Johnson, R.A., Miller, I and Freund J., "Miller and Freund’s Probability and Statistics for Engineers", Pearson Education, Asia, 8th Edition, 2015.
Milton. J. S. and Arnold. J.C., "Introduction to Probability and Statistics", Tata McGraw Hill, 4th Edition, 2007.
Devore. J.L., "Probability and Statistics for Engineering and the Sciences”, Cengage Learning, New Delhi, 8th Edition, 2014.
Papoulis, A. and Unnikrishnapillai, S., "Probability, Random Variables and Stochastic Processes", McGraw Hill Education India, 4th Edition, New Delhi, 2010.
Ross, S.M., "Introduction to Probability and Statistics for Engineers and Scientists", 3rd Edition, Elsevier, 2004.
Spiegel. M.R., Schiller. J. and Srinivasan, R.A., "Schaum’s Outline of Theory and Problems of Probability and Statistics", Tata McGraw Hill Edition, 2004.
Walpole. R.E., Myers. R.H., Myers. S.L. and Ye. K., "Probability and Statistics for Engineers and Scientists", Pearson Education, Asia, 8th Edition, 2007.
Use of Bayes theorem, t -test for the research purposes
Practicing hypothesis framing on real time applications
1. Be exposed to big data
2, Learn the different ways of Data Analysis
Be familiar with data streams
Learn the mining and clustering
Be familiar with the visualization
After completion of this course, students will be able to;
Understand and apply the statistical analysis methods
Compare and contrast various soft computing frameworks
Design and develop distributed file systems 4, To develop Stream data model
5. Apply Visualization techniques in real time applications
- Modern data analytic tools, Stastical concepts: Sampling distributions, resampling, statistical inference, prediction error.
Michael Berthold, David J. Hand, “Intelligent Data Analysis”, Springer, 2007.
Anand RajaRaman and Jeffrey David Ullman, “Mining of Massive Datasets”, Cambridge University Press, 2012.
Bill Franks, “Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with advanced analystics”, John Wiley & sons, 2012.
Glenn J. Myatt, “Making Sense of Data”, John Wiley & Sons, 2007 Pete Warden, Big Data Glossary, O‟ Reilly, 2011.
Jiawei Han, Micheline Kamber “Data Mining Concepts and Techniques”, Second Edition, Elsevier, Reprinted 2008.
Predictive Analytics, linear regression
To study fundamentals of Computational Fluid Dynamics (CFD)
To perform CFD analysis of lid driven cavity in Open-Foam
To perform CFD analysis of square tube in Open-Foam
To perform CFD analysis of a 2D-plate in Open-Foam
To perform CFD analysis of bifurcated blood vessel in FEM
To study fundamentals of Finite element method and FEA
To perform FEM analysis of deep drawing process in FEM
To study fundamentals of Sci-Lab
To perform matrix operations in Sci-lab
To plot 2D & 3D graphs in Sci-lab
Versteeg H; An introduction to Computational Fluid Dynamics (The Finite Volume Method);Pearson
Jiyuan Tu; Computational Fluid Dynamics: A Practical Approach; Butterworth Heinemann.
Gokhale NS; Practical Finite Element Analysis; Finite to Infinite
Seshu P; Finite element analysis; PHI.
Reddy JN; Introduction to the Finite Element Method; McGraw Hill Inc.
Das VV; Programming in Scilab 4.1; New Age International Publishers.
Verma A K; Scilab : A Beginner’s Approach; Cengage publishers
To write a Python program to find GCD of two numbers.
To write a Python Program to find the square root of a number by Newton’s Method.
To write a Python program to find the exponentiation of a number.
To write a Python Program to find the maximum from a list of numbers.
To write a Python Program to perform Linear Search
To write a Python Program to perform binary search.
To write a Python Program to perform selection sort.
To write a Python Program to perform insertion sort.
To write a Python Program to perform Merge sort.
To write a Python program to find first n prime numbers.
To write a Python program to multiply matrices.
To write a Python program for command line arguments.
To write a Python program to find the most frequent words in a text read from a file.
To write a Python program to simulate elliptical orbits in Pygame.
To write a Python program to bouncing ball in Pygame.
Timothy A. Budd: Exploring python, McGraw-Hill Education.
R.Nageshwar Rao ,”Python Programming” ,Wiley India
Allen B. Downey; Think Python, O'Reilly Media, Inc.
Minor Project-I will be carried out in a group of students (Maximum 03) and team will work under faculty supervisor of relevant field.
Students are suggested to select recent topic related to Challenges and advancements in the field of Electric Vehicle Technology for research as a minor project -I.