• Importance of mathematical modelling
• Block diagram approach & model-based design for engineering systems
• Introduction to Simulink environment
• Creating a simple model
• Obtaining results
• Introduction to various Simulink toolboxes

• How does a model run in Simulink?
• Types of solvers
• Model configuration
• Continuous & discrete-time systems
• Timestep
• Solving ODE
• Introduction to physical modelling using simscape

• Using a script file with Simulink models
• Creating a subsystem
• Variant subsystem
• Projects
• Template
• lookup tables
• Running simulation in steps

• Control logic for engineering applications
  
• Using a finite state machine
• Making logic diagrams

In this module, we will introduce the ideas of Statistics, machine learning and artificial intelligence. 

⮚ Basics of Probability

⮚ Basics of Statistics

⮚ What is ML & AI

In this section, we start with supervised learning

⮚ Introduction to normal distribution & standard normal distribution

⮚ Introduction to business moments

⮚ Artificial Intelligence

In this section, we start with supervised learning

⮚ Introduction to supervised learning

⮚ What is linear regression

⮚ One hot encoding

⮚ Cost function and gradient descent

In this section, we start with classification algorithm

⮚ Introduction to classification problems

⮚ What is logistic regression

⮚ Cost function and gradient descent

In this module, we will introduce some more classification algorithms

⮚ Decision tree

⮚ Entropy

⮚ Information gain

In this section, we will assess the algorithms

⮚ Random Forest

⮚ Bootstrapping and majority rule

⮚ Evaluation of classifiers

In this module, we will introduce SVM

⮚ Support Vector Machines

⮚ Mathematical intuition behind SVM 

⮚ How SVM is different from other classifiers

In this section, we will introduce knn

⮚ K-Nearest Neighbour

⮚ Lazy Algorithm

⮚ Single layer Neural Network

In this section, we will introduce clustering

⮚ What is clustering

⮚ Why clustering is important

⮚ Kmeans and elbow curve

In this section, we will introduce another type of clustering

⮚ Hierarchical Clustering

⮚ Dendrogram

⮚ Evaluation of clustering algorithms

In this module, we will introduce some feature selection techniques

⮚ Feature Selection

⮚ Principal Component Analysis

⮚ Mathematical intuition behind PCA

In this section, we will introduce neural network

⮚ Artificial Neural Network

⮚ Deep learning

⮚ Different activation functions

⮚ Understanding back propagation

• Vehicle power requirement calculations: Rolling resistance, air drag, hill climbing and acceleration forces
• Driving patterns and vehicle testing standards, important terms and definitions related to driving cycle, Energy expenditure calculation

• Different configurations of power train components: Battery Electric Vehicle, Hybrid Electric Vehicle: Series, Parallel and Series-Parallel 
• MATLAB Simulation: ADVISOR and Powertrain block set
• Various modelling options, Control strategies 

In a motor vehicle, the powertrain or powerplant comprises the main components that generate power and deliver that power to the road. In hybrid powertrains, the torque generated by the combustion engine and the electric motor has to be brought together and distributed to the wheels. The control of this power flow is discussed along with the working of electric motors.

Electrical engineering terminologies, Fundamentals of DC and AC motors: working principle, characteristics, and control.

• Understanding power electronics, basic DC converter circuit operation, power devices, switching losses 
• Power electronic control of PMDC, PMBLDC and induction motor
• Inverter operation, Sine PWM, Variable frequency control
• Review of induction motor controller, connections and features, limitations of variable frequency control, introduction to vector control 

Moving vehicles have a lot of kinetic energy, and when brakes are applied to slow a vehicle, all of that kinetic energy has to go somewhere. Regenerative braking uses an electric vehicle’s motor as a generator to convert much of the kinetic energy lost when decelerating back into stored energy in the vehicle’s battery. To evaluate regenerative braking, we really need to look at two different parameters, efficiency and effectiveness.

• Braking requirements of vehicle, Methods of braking of DC & Induction motors: regenerative braking and dynamic braking  
• Coordinating electrical and mechanical brakes, braking control strategies

• Fundamentals of control engineering
• Important terms
• Feedback system
• Transfer functions
• Poles zeros
• State-space
• Laplace transform

This section dealt with the stability analysis of control systems. It is a prerequisite for any of the systems to be stable to give satisfactory behaviour. Students can learn about stability theories and how to implement the same using the MATLAB command.

• Stability
• Bode plot and MATLAB tools for control system engineering

A PID controller is considered to be very important in the industrial standpoint. This section helps to learn the significance of the PID controller and how to auto-tune the gain parameters of the PID controller in MATLAB simulation environment.

• PID control actions and simulations for step response

In an Electric Vehicle, the motor plays a crucial part to propel the vehicle. The motor characteristic needs to be known to control it efficiently. This section helps to learn about the transfer function of DC motors and control of DC-DC power converter.

• DC motor transfer function
• Setpoint tracking and disturbance rejection

This section briefs the difference between analogue and digital systems. The significance of discrete control systems and the domain that is to be defined for the discrete control system. Student can get an insight on the advantage of using Discrete control system over the Analog control system

• Limitations of analog control
• Discrete control system
• Z-domain analysis

• Digital power control
• Microcontroller fundamentals
• Programming and interface

• Intelligent and connected vehicle system
• Master controller and its interfacing with the local controller

• Sources of energy for propulsion & their comparison: Net Calorific Value, Conversion efficiency

• History and background of battery technology

• Electrochemistry fundamentals & terminologies

• Lithium ion battery and different chemistries

  
  

  
  

• Portable power applications and electrical load requirements

• Factors affecting the choice of EV battery systems

• Commercially available lithium ion cells

• Electrical characteristics of battery: Capacity, C-rate, impedance, DOD, SOC, SOH, Life cycles, Mechanical characteristics, Form factor, Safety

• Reading cell manufacturer’s specifications

• Cell characterization

• Tools and standard testing

• Battery capacity estimation algorithms

• Electrical equivalent circuit & mathematical model in MATLAB