Project

# Title Team Members TA Documents Sponsor
17 Integrated Brushless Motor Exploration Platform
Alex Roberts
Jason Vasko
Michael Gamota design_document1.pdf
final_paper1.pdf
grading_sheet1.pdf
presentation1.pptx
proposal1.pdf
# Integrated Brushless Motor Exploration Platform

Note, project changed marginally from initial idea. Original idea post is [Multiple Motor Stimulation Hardware Investigation Tool](https://courses.grainger.illinois.edu/ece445/pace/view-topic.asp?id=76583)

# Team Members:
- Alex Roberts (asr9)
- Jason Vasko (jrvasko2)

# Problem
Exploring topics in motor control requires at least a moderate knowledge of electronic hardware systems. Even when using commercial off the shelf motor drivers, microcontrollers, power regulators, and power supplies still need to be connected to the motor driver, which can cause confusion for people without a working electrical engineering knowledge. This makes it difficult for students in disciplines other than ECE, such as mechanical or aerospace engineering, to experimentally learn about motor control.

# Solution
We propose a single integrated device which is usable with minimal electronics experience that allows the user to test motors with different motor control algorithm parameters at different speeds. The board will act as an educational tool to allow people interested in topics such as field oriented control, or 3-phase power system in general, to operate brushless motors and explore control algorithms with as few external connections as possible. Our project integrates the microcontroller, sensors, power regulation, and motor drive circuitry required to spin a brushless DC motor into a single board. It will only require the user to connect a computer over USB, the 3 phase wires of the motor, and two simple power connections (one to a 12V wall adapter for logic and sensing power, and the other to a benchtop supply used only for motor bus voltage). On the computer there will be a GUI application that allows the user to control the motor, modify the motor control algorithms, and measure motor performance. Ultimately, the system will serve as a single platform for learning about brushless DC motor drivers and control algorithms with as few external tools needed as possible.

# Solution Components

## Control Subsystem

The control subsystem is responsible for driving and/or monitoring all other subsystems. It will periodically read data from the sensory array, monitor the health of the power subsystem, and generate PWM signals for the motor drive subsystem. It will also communicate with the PC app, updating the GUI periodically and allowing the user to set motor parameters such as speed and PID controller coefficients. This subsystem includes:
- System Microcontroller (STM32F446RET6)

## Sensor Array

The sensor array is responsible for recording data related to the motor’s operation and the overall health of the board. This subsystem includes:
- Current and voltage sensors for the three-phase signals driving the motor and to monitor health of the voltage regulators (INA230AIDGSR) - We will use shunt resistors to use this same IC for both voltage and current monitoring.
- Physical encoder to measure motor angle and speed (PEC11R-4220K-S0024) - We will use a 3D printed jig that the user attaches the motor to during operation. The motor shaft and encoder shaft will then be connected using gears attached to each, so the motor shaft position can be measured using the rotary encoder.

## Power Subsystem

The power subsystem is responsible for generating the needed voltages for components on the board such as sensors and the microcontroller. A small 12V DC wall adapter will plug into a banana jack on the PCB, which is converted using a buck regulator to our logic voltage of 3.3V. We also require the user to connect a benchtop power supply which will provide motor bus voltage directly. This avoids needing to integrate a complex, multiple hundred watt converter into the board, which would be unrealistic given the timescale of this project. This subsystem includes:
- Adjustable switching buck converter to convert the 12V supply to 3.3V to power the microcontroller (TPS562201DDCR)

## Motor Drive Subsystem

The motor drive subsystem is responsible for generating the AC waveforms supplied to each phase of the motor. To do so, we will use gate drivers and half-bridges connected to the motor bus voltage coming from the benchtop power supply. This subsystem’s primary components are:
- MOSFETs for the half-bridges for each phase (IRFI1310N)
- Half-bridge gate driver ICs for each phase (DGD05473)

# Criterion For Success

We consider the project a success if it satisfies the following criteria:
- User should be able to control motor speed and/or position through a PC app GUI connected to the board via USB.
- User should be able to set and change motor driver parameters such as PID coefficients.
- User should be able to see aspects of the motor control algorithm performance on the GUI, such as motor speed and three-phase voltages and currents.
- User should only require four external connections to use the device: a wall power connection, a benchtop power supply, a usb connection to the laptop, and the motor phases.

CHARM: CHeap Accessible Resilient Mesh for Remote Locations and Disaster Relief

Martin Michalski, Melissa Pai, Trevor Wong

Featured Project

# CHARM: CHeap Accessible Resilient Mesh for Remote Locations and Disaster Relief

Team Members:

- Martin Michalski (martinm6)

- Trevor Wong (txwong2)

- Melissa Pai (mepai2)

# Problem

There are many situations in which it is difficult to access communicative networks. In disaster areas, internet connectivity is critical for communication and organization of rescue efforts. In remote areas, a single internet connection point often does not cover an area large enough to be of practical use for institutions such as schools and large businesses.

# Solution

To solve these problems, we would like to create a set of meshing, cheap, lightweight, and self-contained wireless access points, deployable via drone. After being placed by drone or administrator, these access points form a WiFi network, usable by rescuers, survivors, and civilians. Our network will have QoS features to prioritize network traffic originating from rescuers. Having nodes/access points deployable by drone ensures we are able to establish timely connectivity in areas where search and rescue operations are still unable to reach.

Over the course of the semester, we will produce a couple of prototypes of these network nodes, with built in power management and environmental sensing. We aim to demonstrate our limited network’s mesh capabilities by setting up a mock network on one of the campus quads, and connecting at various locations.

# Solution Components

## Router and Wireless Access Point

Wireless Access for users and traffic routing will be the responsibility of an Omega2 board, with onboard Mediatek MT7688 CPU. For increased signal strength, the board will connect to a RP-SMA antenna via U.FL connector.

The Omega2 will be running OpenWRT, an Linux-based OS for routing devices. We will develop processes for the Omega2 to support our desired QoS features.

## Battery Management System

This module is responsible for charging the lithium-ion battery and ensuring battery health. Specifically, we will ensure the battery management system has the following features:

- Short circuit and overcurrent protection

- Over- and under-voltage protection

- An ADC to provide battery status data to the microcontroller

- 3.3v voltage regulation for the microcontroller and other sensors

In addition to miscellaneous capacitors and resistors, we intend to use the following components to implement the battery management system:

- The MT2492 step-down converter will be used to step down the output voltage of the battery to 3.3 volts. Between the GPS and extra power the microcontroller might consume with an upgraded Wifi antenna, low-dropout regulators would not provide sufficient power in an efficient manner. Instead, we will implement a 2 amp buck converter to improve efficiency and ensure there are no current bottlenecks.

- We will utilize two button-top protected 18650 3400 mAh lithium ion batteries in series to power each node. Placing two of these batteries in series will ensure their combined voltage never falls below the minimum voltage input of the buck converter, and accounting for the buck converter’s inefficiency these batteries should give us about 21 Wh of capacity. The cells we plan on using include a Ricoh R5478N101CD protection IC that provides over-voltage, under-voltage, and over-current protection. Using a standard battery form factor will make them easy to replace in the future as needed.

- A USB-C port with two pulldown resistors will provide 5 volt charging input with up to 3 amps of current, depending on the charger.

- The MT3608 step-up converter will boost the input voltage from the usb-c port and feed it into the charging controller.

- The MCP73844 Charge Management Controller will be used to charge the batteries. This controller supports CC/CV charging and a configurable current limit for safe and effective battery charging.

- The TI ADS1115 ADC will be used for battery voltage monitoring. This chip is used in the official Omega2 expansion board, so it should be easy to integrate in software. We will use a voltage divider to reduce the battery voltage to a range this chip can measure, and this chip will communicate over an I2C bus.

## Sensor Suite

Each node will have a battery voltage sensor and GPS sensor, providing the system with health information for each node. On top of the Wifi-connectivity, each module would have a series of sensors to detect the status of the physical node and helpful environment variables. This sensor suit will have the following features and components to implement it

- Ultimate GPS Module PA1616D will be used for positioning information. This chip utilizes 3.3V which is supplied through our battery management system.

Battery Voltage Monitor

- The TI ADS1115 ADC (mentioned in the BMS section) is for battery voltage monitoring. It interfaces via I2C to the Omega2.

## System Monitor

A system monitor which provides visibility of the overall system status for deployed network nodes. Information that we will show includes: last known location, battery health, and network statistics (e.g. packets per second) from the physical devices.

We plan on using React to provide an intuitive UI, using google-map-react and other React packages to create an interactive map showing the last known location and status of each node.

The backend will be hosted on a server in the cloud. Nodes will continually update the server with their status via POST requests.

# Criterion For Success

We aim to achieve the following performance metrics:

- 1.5 kg maximum mass

- Cover 7500 m^2 (North Quad) with 4 nodes

- Display the last known location, time connected, and battery voltage for all nodes via our system monitor

- 3 hour battery life

- 5 Mb/s WiFi available to laptops and smartphones in the coverage area

[*Link*](https://courses.engr.illinois.edu/ece445/pace/view-topic.asp?id=71252) *to assciated WebBoard discussion*