Semester-1

• Maths-I
• Applied Physics -I
• Applied Chemistry-I
• Engineering Graphics
• Engineering Workshop
• Communication Skills
• Fundamentals of IT and Programming
• Design Thinking
• SHD Health Practices

Semester-2

• Applied Physics-II
• Object Oriented Programming
• Fundamentals of Electrical & Electronics
• Computer Architecture
• Unix & Shell Scripting
• SHD (Engineering communication and soft skill)
• Design Thinking (Practice)

Semester-3

• Maths-II
• Computer Graphics
• Software Engineering
• Fundamentals of Database
• Basics of Java
• Lab1-DBMS
• Lab2-JAVA
• Minor Project1
• Internship

Semester-4

• Java Programming for Automation
• Data Communication
• Software Testing-Basics of Manual Testing
• Data Structures
• Operating System
• Lab3-Selenium Essentials
• Lab4-Computer Networks Lab/ VB Script Lab
• Minor Project2
• Internship
• Audit Course (Enviromental Sciences)

Semester-5

• Maths-III
• Introduction to Python Programming
• Software Testing (Automation For beginner)
• Program Elective Course 1
• Open Elective Course 1
• Lab 5-Python Lab
• Lab 6-Automation and selenuim
• Seminar
• Major Project Phase1

Semester-6

• Program Elective Course 2
• Program Elective Course 3
• Open Elective Course 2
• Lab 7-QTP Tool
• Major Project Phase2
• Audit Course (Indian Constitutions / Essence of Indian knowledge Tradition)

Program Elective Course-1

• Project Management
• Data mining

Program Elective Course-2

• Machine Learning
• Information Security

Program Elective Course-3

• Artificial Intelligent
• Development Cycle with GITHUB

Semester-1

• Maths-I
• Applied Physics -I
• Applied Chemistry-I
• Engineering Graphics
• Engineering Workshop
• Communication Skills
• Fundamentals of IT and Programming
• Design Thinking
• SHD Health Practices

Semester-2

• Applied Physics-II
• Object Oriented Programming
• Fundamentals of Electrical & Electronics
• Computer Architecture
• Unix & Shell Scripting
• SHD (Engineering communication and soft skill)
• Design Thinking (Practice)

Semester-3

• Maths-II
• Data Structures
• Python Essentials
• Operating System
• Softaware Engineering
• Data structure Lab
• Python Lab
• Minor Project1 (Python based)
• Internship

Semester-4

• Introduction to Advance Python
• Probability
• Data modeling and data visualization
• Fundamentals of Database
• Introduction to network
• Lab 1: DMDV Lab
• Lab 2: Python Lab
• Minor Project2 (AI+Python)
• Internship
• Audit Course (Enviromental Sciences)

Semester-5

• Maths-III
• Machine Learning for Data Science
• Statistics for data science
• Program Elective Course 1
• Open Elective Course 1
• PEC1 Lab
• ML Lab
• Seminar
• Major Project Phase1

Semester-6

• Program Elective Course 2
• Program Elective Course 3
• Open Elective Course 2
• Program Elective Course 2 Lab
• Major Project Phase2
• Audit Course (Indian Constitutions / Essence of Indian knowledge Tradition)

Program Elective Course-1

• Introduction to BIG DATA ANALYTICS
• Business Analytics

Program Elective Course-2

• Digital Image Processing
• Human Computer Interaction

Program Elective Course-3

• Certification using IBM
• Certification using NPTEL

Open Elective Course 1

• Data mining and data warehousing
• Information retrieval

Open Elective Course 2

• Cloud Computing
• Introduction to IoT

Semester-1

• Maths-I
• Applied Physics -I
• Applied Chemistry-I
• Engineering Graphics
• Engineering Workshop
• Communication Skills
• Fundamentals of IT and Programming
• Design Thinking
• SHD Health Practices

Semester-2

• Applied Physics-II
• Object Oriented Programming
• Fundamentals of Electrical & Electronics
• Web Page Designing and Development (HTML and CSS Fundamentals)
• Computer Architecture
• SHD (Engineering communication and soft skill)
• Design Thinking (Practice)

Semester-3

• Maths-II
• Introduction to Complete Javascript
• Fundamentals of Database
• Web Based Application development with PHP
• Introduction to Network
• Lab1-DBMS
• Lab2-Javascript and PHP
• Minor Project1
• Internship

Semester-4

• Core Java Programming
• Software Engineering
• Data structures
• Computer Graphics
• Unix and Shell Scripting
• Lab3-Data Structure
• Lab4-Jquery and Bootstrap
• Minor Project2 (Java Based )
• Internship
• Audit Course (Enviromental Sciences)

Semester-5

• Maths-III
• Advanced Java Programming
• Operating System
• Program Elective Course 1
• Open Elective Course 1
• Lab5-Adv Java
• Lab6-OS Lab
• Seminar
• Major Project Phase1

Semester-6

• Program Elective Course 2
• Program Elective Course 3
• Open Elective Course 2
• Lab7-No SQL DB
• Major Project Phase2
• Audit Course (Indian Constitutions / Essence of Indian knowledge Tradition)

Program Elective Course-1

• Development Cycle with GitHub
• Advanced Computer Network
• Software Testing

Program Elective Course-2

• Web development with flutter
• Cloud Computing
• Advanced DBMS

Program Elective Course-3

• Building Web Applications in Django
• Introduction to WordPress and Photoshop
• Android app development with Kotlin

COURSE CONTENT: MODULE 1

• Introduction to cell testing
• Cell terminologies
• Complete understanding of Cell data sheet
• Li Ion Cell Characteristics

Introduction to Cell Testing

• Types of tests needed to validate a - - cell Cell Testing equipment
• Testing Procedure

Cell Characterization tests

• Activation Test
• Static Capacity Test
• Pulse Characterization Test
• Rate Discharge & Charging Test
• Electrochemical Impedance Spectroscopy Test

Performance tests

• Dynamics Stress test
• Drive Cycle Test
• CC, CV, CP & CR Test
• Peak Power Test

Life Cycle Tests

• -Cycling test - Ageing Test - Self Discharge
  • Test Mechanical & Electrical
  • Test Safety
  • Tests Data Visualization Results
  • Validations, Discussions & Conclusions

COURSE CONTENT: MODULE 2

• Matlab foundation
• Simulink with practical case studies
  • NI_MH Battery Modeling
  • Project on Thermal modeling

Li-ion Modeling Approaches

• Classification of modeling approaches
• Introduction to Thevenin model
• Tests for estimation of ECM values
• Procedure for estimation of ECM values
• Calculation of ECM values

Modeling of Li Ion cell in Simulink

• Estimation of open circuit voltage (OCV)
• Terminal Voltage (Vt)
• Estimation of ohmic and polarization resistances (R0 & Rp)
• Estimation of Cell temperature (T)

Results, Validations, Discussions & Conclusions

• Introduction to BMS
  • BMS Functionalities
  • Sensing and High Voltage Control
  • Protection functionality
  • Estimation functionality
  • Balancing functionality
  • Interface functionality
  • Diagnostics

Designing Protection Circuits

Voltage protection logic

Current protection logic

• Temperature protection logic

Modeling BMS in MATLAB Simulink, Modeling the test cases FTP 75, WLTP & MNEDC, Dashboard Indications for State of charge estimation (Coulomb counting), State of energy estimation (Energy Integration)

Results, Validations, Discussions

• SOC variation studies
• Validation of V/I/T logic with & without - -
• BMS Case studies

COURSE CONTENT: MODULE 1

• Introduction of EV Electrical Systems Understanding the requirements of electrical systems and discussing the communication between the systems to setup a process flow
• Modeling of EV Chargers
  • Understanding the working of a charger & its electrical characteristics
  • Types of chargers & their working Physics Based modeling of charger circuit
• Modeling of Inverters
  • Types of Inverters & their operation based on the LOAD's nature
• Physics based modeling of inverters
  • Modeling of Buck Converters Requirement of a Buck Converter circuit in the Electric Vehicle and its operation. Defining the electrical circuit of the buck converter to transform it to its mathematical equivalent
• Modeling of Boost Converters
  • Need for a Boost Converter and the characteristics of the circuit with applications. Steps to convert the electrical circuit to its mathematical equivalent
• Modeling of DC Motor
  • Defining the electrical characteristics of a motor and alternatives to the brushed DC Motor. The electrical and physical sub-models with the setup of the motor's transfer functions

COURSE CONTENT: MODULE 2

• Matlab foundation
• Simulink with practical case studies
  • NI_MH Battery Modeling
  • Project on Thermal modeling
• Motor Control Introduction· Need for Motor Control·
  • Industry applications for motor control Types of Control strategies
    • Sensor-based· Sensorless FOC
    • Flux Weakening
• Control Theory
  • What is a control system? Types of Control Systems
    • Open Loop Closed Loop
  • PID Control for system tuning· Function·
    • Terminologies·
    • Configurations (P - PI - PD - PID) Strategies
      • Trial and Error Ziegler Nichols

• Model Examples (MATLAB \ SIMULINK) Motor Control Strategies
• Speed Control
• Torque/ Current Control Cascade
• Motor & Inverter
  • Motor characteristics·
  • Motors characteristics: DC, BLDC & PMSM
• BLDC Motor Electrical configuration Phase Current Estimate
  • Torque – Angular Velocity Estimate
  • Rotor Position Estimation from Hall Sensor Commutation Logic
• Back EMF Estimation of the rotor 3-phase EMF equation
• Working of inverter
• Electrical Equations of inverter
• Modeling and Simulation
  • Setup of physical parameters for motor Model Build the Inverter Block
• BLDC Motor Block
  • Position Sensing Logic, Estimation of Back-EMF, Phase Current & Torque + Angular Velocity·
• Commutation Logic
• Modeling the Input to Controller
• Results and Discussion·
  • Open-loop and Closed-loop speed control analysis
  • System response to the closed-loop parameters Varying target speed feed to estimate model performance

Course content

• Introduction
• BMS Functionalities
• SOC Estimation Strategies
  • Coulomb Counting Methodology
  • Current Integration Methodology
  • Voltage Lookup Based Estimation Methodology
  • Kalman Filter Based Estimation
  • Example Calculations

• Introduction to Kalman Filters
  • Basic Introduction to UKF, EKF
  • Understanding the EKF flow process
  • Predict and Update Steps
  • State Equations
  • Discretization of the State Equations

• Governing State Equations for the SOC Estimation
  • State Space Representation of the Equations
  • Discretization of the State Space Equations

• Development of Matlab Code for SOC Estimation
  • SOC Estimation for Constant Current Discharge/ Charge
  • SOC Estimation for Dynamic Profiles

• Model Based SOC Estimation
  • Predict Step Modelling
  • Update Step Modelling
  • Thevenin Circuit Modelling

• Post Processing
• Results and Discussion
  • SOC Estimations Plots
  • Voltage Variation w.r.t Discharge Capacity
  • Voltage Variation across R0 and RC Circuit
  • Estimation Errors

• Model prediction validation w.r.t tested data
• Future Scope of Study

Electric Vehicle HVAC Modeling and Sizing

Course name	Advanced HVAC system modeling & energy consumption study
Course Level	3 (Advance)
Course Duration	24 Hours
Software tool used	MATLAB & Simulink
Course approach	Project based (50% tool based & 50% theory + numerical)

About the course: The objective HVAC modeling to analyze the various loads acting on the vehicle such as metabolic load acting on the cabin based on the weight, height, and Dubois area of the passenger, Radiation load (direct radiation load based on the transmissivity, surface area, and the angle of incidence the sun’s race, Diffuse radiation due to diffuse radiation per unit area as per the ASHRAE handbook and the reflected radiation load acting on the HVAC system due to the ground reflectivity, angle of incidence of the sun’s rays and the transmissivity of the vehicle body), the ambient load acting on cabin due to the ambient temperature and the car surface area and Ventilation load based on the mass flow rate of ventilation. The battery sizing including the HVAC load, Cabin temperature variation based on the loads, and analysis of the energy consumption variation based on the different ambient temperatures will be discussed in the course.

Course need & Purpose:

• Introduces the working principle of an HVAC in an Electric vehicle
• To train the participants on modelling a HVAC system in a vehicle
• To understand the contribution of various loads on the HVAC

Course prerequisites:

• A foundation on MATLAB & Simulink software.
• Creation of Equations.

Course outcomes:

• Training on modelling the HVAC system in an electric vehicle
• Understanding on how sizing of an HVAC system is done for an electric vehicle
• HVAC system model validation with) a real-life test data (Idaho National laboratory test)

Course Content

• Review of the Heating Ventilation and Air Conditioning (HVAC) system
  • Review of Heating and Air conditioning system need and working principle in a vehicle
• Review on loads acting on the HVAC system
  • Introduction to the loads acting on HVAC system. An understanding on the different loads acting on the heating and cooling of the HVAC.
• Introduction to Metabolic load
  • Explanation on what is metabolic load and How metabolic load acts as a load on the HVAC system. Numerical calculations to estimate the metabolic load.
• Introduction to Radiation load
  • Explanation on what is radiation load, the different types of radiation load acting on the HVAC system & how radiation load acts as a load on the HVAC system. Numerical calculations to estimate the radiation load.
• Introduction to ambient load
  • Explanation of ambient load acting on cabin due the ambient temperature and the car surface area.
  • Defining the ambient load variation on the HVAC system due to the variation of the vehicle’s velocity, ambient temperature and the thermal conductivity of the vehicle. Numerical calculations to estimate the ambient load.
• Introduction to ventilation load
  • Detailed understanding on the ventilation acting on the HVAC system due the mass flow rate of the air, Cabin and ambient temperature. Numerical calculations to estimate the ventilation load
• Modeling and sizing of HVAC system
  • Utilizing the MATLAB & Simulink software to create an HVAC model of Nissan leaf vehicle.
  • Modeling each and individual load acting on the Heating the cooling system of the vehicle.
  • Estimating the energy consumption of the battery due to utilization of the HVAC and the powertrain to run the electric vehicle.
  • Electric vehicle battery sizing including the effect of the HVAC system on the electric vehicle.
  • Cabin temperature variation estimation and HVAC model validation with real time test data.
• Results and Discussion
  • Analysis of the energy consumption and SOC variation the battery when vehicle is driven at different ambient temperatures
  • Comparative study on the amount of powertrain, metabolic, ambient and the ventilation load variation for different ambient temperature of the environment
  • Model validation to estimate the average percentage of variation of the built model with the actual test data

Electric Vehicle Motor and Battery cooling Modeling and Sizing

Course name	Advanced Battery Cooling & Motor Cooling
Course Level	3 (Advance)
Course Duration	24 Hours
Software tool used	MATLAB & Simulink
Course approach	Project based (50% tool based & 50% theory + numerical)

About the course: The objective of the course is to understand various losses occurring in a motor (Copper, Hysteresis, Iron, eddy current, Switching, friction, and windage losses) and Battery (cell power losses due to the internal cell resistance, and Battery pack power loss based on the number of cells connected in series and parallel in the battery pack) to model the motor and battery cooling to size the coolant mass flow rate for both motor and battery cooling. In the course, we will be focusing on the motor, battery temperature for both passive and active cooling systems to analyze the amount of battery energy consumption.

Course need & Purpose:

• Introduces the working principle of a Battery and Motor cooling in an Electric vehicle
• To train the participants on modelling a Battery and motor cooling system in a vehicle
• To model and size the motor and battery cooling in an Electric vehicle

Course prerequisites:

• A foundation on MATLAB & Simulink software.
• Creation of Equations.

Course outcomes:

• Training on modelling the Motor and Battery cooling system in an electric vehicle
• Understanding on how sizing of a Motor and Battery cooling system is done for an electric vehicle
• Motor and Battery coolant mass flowrate sizing

About the course: The objective of the course is to understand the working principle of an electric machine, Motor physics for modeling needs, Motor operating Characteristics, and motor operating modes (Braking and Driving) and estimate Electric Machines Performance from Datasheets, perform numerical hand calculations to calculate the stall torque, nominal torque, peak torque, nominal and a peak speed of a motor. In the course of the regenerative braking in electric vehicles is discussed, to understand the regenerative limitations of the electric machine, detailed understanding of cell datasheet, cell resistance and a battery pack voltage and Study on the regenerative limitations of a cell and a battery pack. Analysis of the vehicle’s range, energy consumption, and SOC variation with and without regeneration.

Course need & Purpose:

• Introduces the working principle of an Electric machine in an Electric vehicle
• Introduces regenerative mode in electric vehicle.
• To train the participants on modelling advance motor model.

Course prerequisites:

• A foundation on MATLAB & Simulink software.
• Creation of Equations.

Course outcomes:

• Training on modelling of advance motor model.
• Understanding on how sizing of electric motor voltage, current and advance regenerative model is done for an electric vehicle.

Course Content

• Review of the Motor cooling system
  • Understanding the need and the working principle of motor cooling system.
• Review on the Electric Motor losses
  • Explanation on the various losses occurring in the electric motor.
  • Derivation of different losses occurring in the electric motor.
  • Explanation the electric motor efficiency map with respect to the motor speed and motor torque.
  • Derivation of equation to estimate motor power loss, motor cooling power and motor temperature.
• Electric motor cooling
  • Detailed explanation on the different types motor cooling (Passive and Active cooling).
  • Explanation on motor temperature variation.
  • Explanation on control logic working and modeling for active type of motor cooling system.
• Electric motor coolant sizing
  • Coolant mass flowrate estimation for active cooling system based on the estimated motor power loss graph.
• Modeling and Analysis of motor cooling system
  • Utilizing the MATLAB & Simulink software to create electric motor cooling system for both passive and active type of cooling.
  • Estimation of battery energy consumption for active type of cooling system based on the specified temperature control range.
  • Analyzing the motor temperature variation for both passive and active type of cooling system.
• Review of the Battery cooling system
  • Understanding the need and the working principle of battery cooling system.

• Review on the Battery Pack losses
  • Explanation on the various losses occurring in a cell and battery pack.
  • Detailed explanation on cell power losses due to the internal cell resistance.
  • Battery pack power loss derivation based on the number of cells connected in series and parallel in the battery pack.
• Battery cooling and battery coolant sizing
  • Detailed explanation on the different type’s battery cooling (Passive and Active cooling).
  • Explanation on battery temperature variation based on passive and active cooling system.
  • Explanation on control logic working and modeling for active type of battery cooling system.
  • Coolant mass flowrate estimation for active cooling system based on the estimated battery power loss graph.

• Modeling and Analysis of battery cooling system
  • Create battery cooling system for both passive and active type of cooling.
  • Estimation of battery energy consumption for active type of cooling system based on the specified temperature control range.
  • Analyzing the battery temperature variation for both passive and active type of cooling system.

Electric Vehicle Advance Motor Modeling and Sizing

Course name	Advanced Traction Motor & regenerative energy modeling
Course Level	3 (Advance)
Course Duration	24 Hours
Software tool used	MATLAB & Simulink
Course approach	Project based (50% tool based & 50% theory + numerical)

About the course: The objective of the course is to understand the working principle of an electric machine, Motor physics for modeling needs, Motor operating Characteristics, and motor operating modes (Braking and Driving) and estimate Electric Machines Performance from Datasheets, perform numerical hand calculations to calculate the stall torque, nominal torque, peak torque, nominal and a peak speed of a motor. In the course of the regenerative braking in electric vehicles is discussed, to understand the regenerative limitations of the electric machine, detailed understanding of cell datasheet, cell resistance and a battery pack voltage and Study on the regenerative limitations of a cell and a battery pack. Analysis of the vehicle’s range, energy consumption, and SOC variation with and without regeneration.

Course need & Purpose:

• Introduces the working principle of an Electric machine in an Electric vehicle
• Introduces regenerative mode in electric vehicle.
• To train the participants on modelling advance motor model.

Course prerequisites:

• A foundation on MATLAB & Simulink software.
• Creation of Equations.

Course outcomes:

• Training on modelling of advance motor model.
• Understanding on how sizing of electric motor voltage, current and advance regenerative model is done for an electric vehicle.

Course Content

• Review on electric machine
  • Understanding the working principle of an electric machine.
  • Detailed understanding of Motor physics for modeling needs, Motor operating Characteristics and motor operating modes (Braking and Driving).
  • Steady state study of EM Operating Region.
  • Understanding the Field Weakening of Motors.
  • Estimating Electric Machines Performance from Datasheets.
• Numerical hand calculation on Electric machine
  • Performing numerical hand calculations to calculate the motor current wrt torque needs and motor voltage wrt to the RPM needs.
  • Estimating Electric Machines Performance from Datasheets
  • Performing numerical hand calculations to calculate the stall torque, nominal torque, peak torque, nominal speed and peak speed of a motor.
• Advance motor modeling
  • Utilizing the MATLAB & Simulink software to create motor model to estimate the Motor Current wrt torque needs and Motor Voltage w.r.t RPM needs.
• Advance motor model (Results and Discussion)
  • Selection of Motors based on the Simulation Data.
  • Plotting the performance curves of the selected Electric Machine.
• Review on Regeneration in Electric Vehicle
  • Understanding the working of regenerative braking in electric vehicles.
  • Review on electric machine working in regenerative mode and battery regeneration in regenerative mode in electric vehicles.
  • Study on regenerative limitations of electric machine.
  • Detailed understanding of cell datasheet, cell resistance and a battery pack voltage.
  • Study on the regenerative limitations of a cell and a battery pack.
• Advance electric vehicle regeneration modeling
  • Utilizing the MATLAB & Simulink software to create motor model which includes the regenerative limitations of the motor and estimate the regenerative power of the motor in regenerative mode.
  • Modeling of a cell and battery pack regenerative limitations and estimating the actual power that can be utilized in order to the charge the battery pack.
• Advance regeneration model (Results and Discussion)
  • Selection of cell based on the Simulation Data.
  • Plotting motor regenerative power, current, voltage and torque.
  • Estimating vehicles range with and without regeneration.