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The Electrical & Hybrid Vehicles Lab is dedicated to advancing the technology and innovation in the field of electric and hybrid vehicles. Our research focuses on developing efficient, sustainable, and high-performance solutions for the automotive industry. We work on cutting-edge projects involving electric powertrains, energy storage systems, vehicle control systems, and charging infrastructure. Our lab collaborates with industry partners, academic institutions, and government agencies to push the boundaries of what is possible in the realm of electric and hybrid vehicles. We provide state-of-the-art facilities and a collaborative environment for researchers, engineers, and students to create innovative solutions that contribute to a greener and more sustainable future.
SUBJECT EXPERTS
Dr. Madhuri Bayya
madhuri.bayya@pilani.bits-pilani.ac.in
Prof. Amar Singh
amar.s@pilani.bits-pilani.ac.in
Prof. Radhika Sudha
Prof. Ramani Kalpathi
ramani.kalpathi@wilp.bits-pilani.ac.in
G. Vykunta Rao
gvykunta.rao@pilani.bits-pilani.ac.in
FACILITIES
E-Mobility Lab aims to encompass the different aspects of electric mobility like the sources,
power electronics, battery management systems, motor control, communication, diagnostics to
name a few. The focus is on modelling and control of the individual components and integration
of these systems to emulate and test the different subsystems of the vehicle. E-Mobility Lab
aims to be a platform to impart hands-on learning on vehicle technologies and creation of a
research platform.
Hardware Components: Induction Motor (IM) Control test rig, Permanent Magnet Synchronous Motor (PMSM) test rig, Brushless DC Hub Motor Control test rig, eV Powertrain Smart bench, Hybrid Panel trainer, Open Cathode PEMFC, Electric Vehicle Reva-i, 2-MTR Dyno with load and Battery Management System (BMS), Electric vehicle REVA- i.
Software Components: Ricardo Ignite, Altair Embed, MATLAB, Electude, Dorleco
EQUIPMENTS AVAILABLE IN LAB
Hardware Components
2-MTR Dyno with Load :
Complex control strategies such as Filed-Oriented Control (FOC), sensor feedback (QEP or Hall sensor).
Basic embedded system programming concepts, particularly using Ti-LAUNCHXL-F28379D controller.
Single-Cell Battery Management System :
Understanding current and voltage sensing aspects of a cell.
The analysis of performance of data acquisition system, monitoring system and charge and discharge control.
Electric Vehicle Powertrain (smart bench) :
Understand EV powertrain components and their integration from source to wheels.
Performance analysis, data acquisition and efficiency testing.
Tuning and optimization along with troubleshooting and diagnostics of vehicle.
Battery Management System Module:
Monitoring and controlling the equalization of the many cells in series while maintaining the operating temperature of the battery pack within limits.
Monitoring of the cell voltages during charging is necessary in order to equalize the charge applied to the cells, therefore maximizing the available state-of-charge (SOC) & state-of-health (SOH) of the battery pack.
Hybrid Panel Trainer:
Modes of hybrid electric vehicle systems and power flow
The voltage and power levels of the different vehicle sub systems in different modes.
Fault generation and mitigation in a hybrid system.
PROJECT DETAILS
EV Power Train (Smart Bench)
The EV Power Train Smart Bench is a hands-on learning platform designed to simplify the development and testing of electric vehicle (EV) control systems. It streamlines hardware and software integration, allowing users to work with EV electronics, perform system testing, and gain practical experience in coding, calibration, and troubleshooting. By bridging theory and practice, the bench enables testing and optimization of powertrain components, supports performance analysis, and improves understanding of EV powertrain integration from battery to wheels.
Hardware and Software Requirements:
Hardware: 57.6V DC 2.88kWh Battery Pack, VCU(Vehicle Control Unit),
CAN based BMS controller, Brushless DC Motor, Kelly BLDC Motor
Controller. Brake, Accelerator.
Software: DORLECO VCU Flash, MATLAB, FREEMASTER
Learning Outcomes:
Understand EV Power Train components and their integration from source to wheels.
Performance analysis data acquisition and efficiency testing.
Tuning and optimization along with troubleshooting and diagnostic of vehicle
IOT based Smart Green Parking and Wireless Charging System for Electric Vehicles
The IoT-based Smart Green Parking and Wireless Charging System transforms urban parking and EV charging by using IoT sensors to track parking space availability and enable easy reservations. Wireless charging eliminates connectors, enhancing convenience, while solar panels provide sustainable energy, reducing the carbon footprint. A mobile app or web platform offers real-time updates on parking, charging status, and energy use, optimizing the experience and promoting EV adoption.
Hardware and Software Requirements:
Hardware: Arduino (Microcontroller), Power Supply,
LCD Display, WI-FI Module, SERVO Motor, Solar Panel, Wireless Charging Circuit, Relay, IR Sensor (X6), Charging Coil (Transmitter), Charging Coil(Receiver), Jumper Wires
Software: Arduino IDE, Embedded C, C Programming
Learning Outcomes:
Drivers can quickly find and reserve wireless charging parking spots, saving time.
Simplified charging and green energy solutions encourage EV adoption.
Renewable energy reduces the carbon footprint of EV charging, promoting cleaner cities.
Real-time data helps optimize parking and charging resource management.
Single Cell Battery Management System
The single cell battery management system uses an Arduino microcontroller to measure the battery’s instantaneous voltage and current to control charging and discharging of the battery.
Hardware and Software Requirements:
Arduino IDE software, ICR1 18650 Li-ion cell, Arduino Uno Rev3, INA219 DC current monitor
Learning Outcomes:
Understanding current and voltage sensing aspects of a cell.
Analysis of performance of data acquisition system, monitoring system and charge and discharge control.
16-Cell Battery Management System
A Battery Management System (BMS) is an essential component in battery-powered systems, responsible for managing and protecting battery packs, especially in applications like electric vehicles, renewable energy storage, and consumer electronics. The BMS optimizes battery usage, prolongs battery life, and ensures safe operation.
Hardware and Software Requirements:
F2837x Control Card, Bq 76PL 455A- Q1 Evaluation Module, DC power supply, Altair Embed Software
Learning Outcomes:
Understanding Battery Chemistry and Characteristics
Battery Monitoring and Protection Mechanisms.
Cell Balancing Techniques
Wireless Power Transmission
To understand the principles of wireless power transfer (WPT) and its application for electric vehicle (EV) charging.
Hardware and Software Requirements:
Rectifier and smoothening capacitor, Oscillating Circuit, Relay Module, Arduino Uno Rev 3
Learning Outcomes:
Learn the fundamentals of wireless power transfer, like electromagnetic induction.
Learn how wireless charging technology is applied to electric vehicles and the benefits of on-road wireless charging systems.
Understand how to use relays to control high-power circuits with low-power microcontrollers (Arduino).
AI and ML-based road detection for power source optimization
This project leverages AI and ML to classify road conditions in real-time using image processing. Based on the classification, it optimizes power source selection between the IC engine and battery, improving fuel efficiency, reducing emissions, and enhancing hybrid vehicle performance.
Learning Outcomes:
Achieve high accuracy in identifying various road surfaces (e.g., asphalt, mud, snow) using image processing.
Reduce IC engine usage by prioritizing battery power on smoother surfaces.
Lower overall vehicle emissions by optimizing power usage based on road conditions.
Provide smoother and safer driving experiences through adaptive power source management.
A flexible system that can be integrated into different types of hybrid vehicles and adapt to various environmental
STUDENTS WORKING ON THE PROJECTS
Mathew Thomas - f20212955@hyderabad.bits-pilani.ac.in
Hemant Goyal - f20212315@pilani.bits-pilani.ac.in
Shreya Pandey- f20213118@hyderabad.bits-pilani.ac.in
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