Project

# Title Team Members TA Documents Sponsor
30 Model For Charging Pad for EVs
 Maneesh Madala
Ronald Roy
Xingjian Gong
 William Zhang design_document2.pdf
final_paper1.pdf
presentation1.pdf
proposal1.pdf
# Students:
Jason Gong ( xg8) (in person), Ronald Roy ( rroy21) (in person), Maneesh Madala (mmadala2) (online)

# Problem:
Electrical vehicles are becoming more common in our world and a much more environmentally friendly option when compared to traditional cars. However, battery technology is currently very limited as the charge of the battery is heavily limited by its size. In order to have more range for EVs, we are planning to make a charging pad for EVs that can be used in garages/parking spaces to charge the car while parked.

# Solution Overview:
Our solution for this issue is to create a charging pad for EVs in home garages and parking spaces. We will create a pad that will lay under an EV and use wireless charging methods to charge the EV. The PCB for the pad will envelop the charging coils, control circuitry, a microcontroller, 4 ultrasonic sensors, and an RF receiver . The PCB on the car will have the charging coils, a general BMS to control battery charge and discharge, and also an RF transmitter that will send an RF signal when the battery is full. We will have on and off buttons on the backside of a wall plug to turn the pad on and off. We will also use the ultrasonic sensors to see if the car is over the pad. If the car is not over the pad and the pad is on the charging pad will turn off. The BMS for the car will also need to be customized in order to take the possibility of wireless and wired charging at the same time. This wireless charging pad can be applied in a general home or parking space and will push the accessibility of EVs and push more EV ownership.

# Solution Components/Subsystems:

Ground Pad: The ground pad is plugged into the power source and has a Qi coil array, 4 ultrasonic sensors, control circuitry, a microcontroller, and an RF receiver. The Qi coils use the incoming current to generate an upward point magnetic field. The microcontroller will process signals from the ultrasonic sensors, the button on the power brick (used to turn the ground pad off and on), and the RF receiver. The ultrasonic sensors will be placed at the edges of the ground pad and will indicate the car is not above the ground pad and send a signal to the microcontroller to indicate when this action occurs. The RF receiver will receive a signal from the transmitter which is placed on the car pad. When the RF receiver gets a signal that the car is done charging from the transmitter it will send a signal to the microcontroller. The control circuit will control the power flow to the Qi coils that will be determined by the microcontroller.

Car Pad: The car pad will be placed under the vehicle and will have a receiving Qi coil array, a small BMS and RF transmitter. The coils absorb the energy from the magnetic field and turn it into the current to charge the Li-Ion cells. The BMS will protect the Li-Ion cells from conditions like over and under voltage, overcurrent and etc. The BMS will include back to back n-type MOSFETS, a fuse resistor, a current sense resistor, a small microcontroller to act as a fuel gauge, a thermistor and with time permitting some possible cell balancing. The figure shown below shows the general idea of the BMS. The RF transmitter will be connected to the fuel gauge and when the cells are fully charged the RF transmitter will send a signal to the receiver to end charging.


# Criterion for Success:
Our criterion for success would be dependent on creating a working model of the pad as a proof of concept. We will create a reasonable sized model of both the charging pad and an EV. If the charging system works as expected then this project can be considered a success.

Decentralized Systems for Ground & Arial Vehicles (DSGAV)

Mingda Ma, Alvin Sun, Jialiang Zhang

Featured Project

# Team Members

* Yixiao Sun (yixiaos3)

* Mingda Ma (mingdam2)

* Jialiang Zhang (jz23)

# Problem Statement

Autonomous delivery over drone networks has become one of the new trends which can save a tremendous amount of labor. However, it is very difficult to scale things up due to the inefficiency of multi-rotors collaboration especially when they are carrying payload. In order to actually have it deployed in big cities, we could take advantage of the large ground vehicle network which already exists with rideshare companies like Uber and Lyft. The roof of an automobile has plenty of spaces to hold regular size packages with magnets, and the drone network can then optimize for flight time and efficiency while factoring in ground vehicle plans. While dramatically increasing delivery coverage and efficiency, such strategy raises a challenging problem of drone docking onto moving ground vehicles.

# Solution

We aim at tackling a particular component of this project given the scope and time limitation. We will implement a decentralized multi-agent control system that involves synchronizing a ground vehicle and a drone when in close proximity. Assumptions such as knowledge of vehicle states will be made, as this project is aiming towards a proof of concepts of a core challenge to this project. However, as we progress, we aim at lifting as many of those assumptions as possible. The infrastructure of the lab, drone and ground vehicle will be provided by our kind sponsor Professor Naira Hovakimyan. When the drone approaches the target and starts to have visuals on the ground vehicle, it will automatically send a docking request through an RF module. The RF receiver on the vehicle will then automatically turn on its assistant devices such as specific LED light patterns which aids motion synchronization between ground and areo vehicles. The ground vehicle will also periodically send out locally planned paths to the drone for it to predict the ground vehicle’s trajectory a couple of seconds into the future. This prediction can help the drone to stay within close proximity to the ground vehicle by optimizing with a reference trajectory.

### The hardware components include:

Provided by Research Platforms

* A drone

* A ground vehicle

* A camera

Developed by our team

* An LED based docking indicator

* RF communication modules (xbee)

* Onboard compute and communication microprocessor (STM32F4)

* Standalone power source for RF module and processor

# Required Circuit Design

We will integrate the power source, RF communication module and the LED tracking assistant together with our microcontroller within our PCB. The circuit will also automatically trigger the tracking assistant to facilitate its further operations. This special circuit is designed particularly to demonstrate the ability for the drone to precisely track and dock onto the ground vehicle.

# Criterion for Success -- Stages

1. When the ground vehicle is moving slowly in a straight line, the drone can autonomously take off from an arbitrary location and end up following it within close proximity.

2. Drones remains in close proximity when the ground vehicle is slowly turning (or navigating arbitrarily in slow speed)

3. Drone can dock autonomously onto the ground vehicle that is moving slowly in straight line

4. Drone can dock autonomously onto the ground vehicle that is slowly turning

5. Increase the speed of the ground vehicle and successfully perform tracking and / or docking

6. Drone can pick up packages while flying synchronously to the ground vehicle

We consider project completion on stage 3. The stages after that are considered advanced features depending on actual progress.

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