Project

# Title Team Members TA Documents Sponsor
7 SolarTrack
Rahul Patel
Rishikesh Balaji
Siddhant Jain
Haocheng Bill Yang design_document1.pdf
final_paper1.pdf
photo1.jpeg
photo2.jpeg
presentation1.pdf
proposal1.pdf
video
Problem:

Fixed solar panels waste potential energy due to changing sun positions and limited monitoring,

Solution:

This project proposes the design of a self positioning solar panel system that automatically orients itself to capture the maximum possible solar energy throughout the day and stores that energy in a battery. Unlike fixed panels the system continuously adjusts its angle using light sensors or a sun-position algorithm controlled by a microcontroller, ensuring the best alignment with the sun as conditions change. The harvested energy is routed through a charge controller to safely charge a battery while protecting against overvoltage, overcurrent, and deep discharge. In addition to energy generation and storage, the system includes a mobile or web application that displays real time and historical data such as panel voltage and current, total energy generated (Wh), battery state of charge, system efficiency, and power consumption of connected loads. This application allows users to monitor performance, compare tracked versus fixed operation, and understand how environmental conditions impact energy production.

Solution Components:

Dual Axis Tracking Mechanism

The solar panels will be mounted on a two axis articulating frame that is driven by servo and stepper motors. This will allow independent control of both the east to west orientation, as well as the angle at which the solar panels are mounted. This will enable the panels to follow the sun’s path through the day across the sky.

Light Sensor Array

We will use an array of photodiodes or LDR sensors to detect the light intensity in various positionings in order to determine the most optimal position for the panels. We could also implement an algorithm that calculates the sun’s theoretical position based on GPS coordinates for use during cloudy or partially shaded conditions.

Maximum Power Point Tracking Charge Controller

We will make use of a charge controller to interface between the solar panel and the battery to operate at the maximum power point. This will help us protect the battery from over charging, over discharging, and reverse current flow.

Energy Storage and Management System

We will incorporate voltage and current senors to measure the output from the panels, battery charge/discharge rates, and load consumption. We will make use of these measurements to compute realtime power, cumulative energy, and system efficiency for performance analysis.

Wireless Communication Module

We will use a WiFi communication module to send system data to a local server or even a cloud based server. This will allow remote monitoring, firmware updates, and long term data logging for performance analysis of tracked and fixed-tilt operations.

Mobile/Web Application Dashboard

We will use an application that will visualize live and historical metrics, including but not limited to orientation angles, power output, energy yield, and tracking efficiency. With the help of this application, users will be able to analyze trends, receive fault alerts, and evaluate the energy gained from solar tracking under different environmental conditions.

Criteria for success:

The success of this project will be evaluated under the following criteria.

Wi-Fi connection between the solar panel/battery and a local/cloud server.

Tracking of statistics, such as angle, output, etc... for display later.

A cache in which to store tracked statistics should the server be unavailable.

Creation of a web app to display the tracked statistics.

Creation of an algorithm allowing for the solar panel to "follow" the sun.

Integration of the algorithm onto a microcontroller + interfacing with light sensors and motors.



VoxBox Robo-Drummer

Craig Bost, Nicholas Dulin, Drake Proffitt

VoxBox Robo-Drummer

Featured Project

Our group proposes to create robot drummer which would respond to human voice "beatboxing" input, via conventional dynamic microphone, and translate the input into the corresponding drum hit performance. For example, if the human user issues a bass-kick voice sound, the robot will recognize it and strike the bass drum; and likewise for the hi-hat/snare and clap. Our design will minimally cover 3 different drum hit types (bass hit, snare hit, clap hit), and respond with minimal latency.

This would involve amplifying the analog signal (as dynamic mics drive fairly low gain signals), which would be sampled by a dsPIC33F DSP/MCU (or comparable chipset), and processed for trigger event recognition. This entails applying Short-Time Fourier Transform analysis to provide spectral content data to our event detection algorithm (i.e. recognizing the "control" signal from the human user). The MCU functionality of the dsPIC33F would be used for relaying the trigger commands to the actuator circuits controlling the robot.

The robot in question would be small; about the size of ventriloquist dummy. The "drum set" would be scaled accordingly (think pots and pans, like a child would play with). Actuators would likely be based on solenoids, as opposed to motors.

Beyond these minimal capabilities, we would add analog prefiltering of the input audio signal, and amplification of the drum hits, as bonus features if the development and implementation process goes better than expected.

Project Videos