COLLEGE OF ENGINEERING & SCIENCE

We will build an enclosure centered around a programmable logic controller (PLC) which will provide the control system to a series of environmental monitoring systems. This enclosure will ultimately serve as a test bench for engineers at Sabre Industries, which constructs battery energy storage systems and the HVAC systems that maintain them. The enclosure must provide a basic monitoring system that Sabre engineers can use to test the software. The environmental monitoring system will oversee the temperature and humidity through probes and digitally simulate gas detection and smoke detection with digital switches. The system’s conditions and reactions will be output through a built-in human machine interface (HMI) screen and a series of LEDs. The final project we seek to deliver will be an enclosure with a programmed PLC reading a set of inputs and appropriately reacting with a set of output LEDs and expected values on the HMI.

Uniform circular arrays (UCAs) offer many benefits over uniform linear arrays (ULAs) for direction-of-arrival (DoA) estimation including an increased range of measurement of the azimuth angle and the ability to measure an angle of elevation. Unlike ULAs, UCAs are disadvantaged in that their array manifold vectors do not have the Vandermonde structure which allows for convenient electronic steering of an array. This project utilized a technique to transform the array manifold vector of a UCA into a Vandermonde vector by using a Butler-type matrix [Davies, November, 1965]. This technique has been known to transform a UCA into an effective ULA. We tested this technique for simulated wide sense stationary plane-wave signals in Gaussian white noise. We also built a sixty-three microphone UCA and gathered acoustic data to test our results. We implemented conventional beamforming (CBF) and eigendecomposition-based method such as multiple signal classification (MUSIC) for DoA estimation and compared the performances. The results showed that the transformed UCA is equivalent to a ULA for MUSIC but not for CBF. CBF degenerates for particular numbers of sensors, whereas MUSIC works well for any number of sensors. However, at unrealistically high signal to noise ratios, CBF is functional.

The electric brushless DC (BLDC) motor design project will be the foundation for the new electric vehicle platform in the Shell Eco-marathon competition for the Louisiana Tech Eco-marathon team. The motor consists of a purpose-designed and built sensorless BLDC controller. This design is for both a senior project and the Louisiana Tech Eco-marathon team. The senior project goals consist of a self-standing and functioning 48 V sensorless BLDC motor controller. The Eco-marathon team goals consist of integrating the self-standing system into the team’s vehicle, assisting in the wiring of the vehicle, and recording data gathered from testing. However, due to COVID-19, we are only able to complete the senior project goals.

CubeSats are a type of nanosatellite that are becoming increasingly popular as vehicles on which both government and private agencies conduct experiments in space. One struggle that these groups face is the limit to both the weight and size of the payload. Our project aims to alleviate those issues by providing a common communication and power system which can be utilized by multiple CubeSats. The platform harnesses solar energy that will be used to supply adequate and reliable power. The platform contains multiple batteries to store the energy for the CubeSats and the main control system. Power and communication are both regulated from the central control system. This enables developers to focus more on the experimental portions of their design while the core elements are addressed by our project. A communication system receives information from the CubeSats and transmits it via radio waves received by a ground station. The messages from the CubeSats are encoded into QAM signals for reliable transmission and are decoded at a ground station. With the CubeSat Hosting  Platform’s systems in place, developers will be able to focus more on their experiments and less on the logistics. Our project will provide a valuable service to important research endeavors.

Our project involves using machine learning (ML) algorithms to optimize the use and integration of drone-based platform technology into next-generation communication networks to create available internet access points and hotspots while decreasing latency and improving bandwidth for users. Drones, such as the one we will make, will be utilized to provide a low-cost solution for faster and affordable deployment to areas on-demand than setting up terrestrial stations. We will be utilizing open-source software within Python and affordable hardware such as the Nvidia Jetson TX2 and Raspberry Pi as the basis for our on-board computer for the drone and ground users, respectfully. ML algorithms will run the platform as optimally and self-sufficiently as possible while also providing network improvements to users. The project’s feasibility relies on our successful implementation of optimal 3D placement and optimal flight path planning on a single platform to provide better network quality. This will require testing of different parameters, such as altitude and flight path correction. If results improve communication quality and speeds, users will have a more convenient, highspeed network with lower latency. This would be a needed improvement, as currently, no other platforms exist to solve this problem, and existing 4G infrastructure will struggle to provide these solutions for new 5G networks.

The goal of our project is to design a device that is capable of measuring and automatically correcting a low power factor of balanced three-phase inductive loads. Our design is intended to improve the efficiency of electrical systems by automatically compensating for the low power factor caused by inductive loads. The design utilizes an Arduino UNO microcontroller to calculate the power factor of the connected load and to control a switchable capacitor bank to correct the power factor.

The purpose of this project is to design and implement a megohmmeter (megger) as an insulation testing device. This device will be used to test for and quantify the level of insulation deterioration for a variety of wires, cables, and electrical devices. Testing for deteriorated insulation is essential for the safe, efficient operation of electrical equipment and must be executed periodically to ensure safe and proper functionality of electrical equipment and machines. This design team is constructing a portable insulation testing device that can produce a maximum DC test voltage of approximately 500 volts. The final device will include a digital output screen to display the approximate resistance of the device under test. The test voltage produced by this device is generated by rechargeable batteries and boosted with power electronics. To make this megger more helpful and useful, multiple test voltage values have been implemented to allow testing of a variety of electric machines and materials. This megger will be considered complete once it can accurately measure large known resistances with a relatively small error of <5 %. This device will benefit the designers as well as the University by providing a safe and effective method of testing the insulation in the large machines currently in use in the power lab.

Induction machines experience large inrush currents during the initial connection to a full-rated voltage supply. While momentary, the magnitude of these currents is large enough to cause significant damage to the motor and the connecting electrical cables. Additionally, the mechanical systems being driven by the motors can suffer damage from the abrupt acceleration brought on by an instantaneous full-voltage connection. The device we’ve made is a variable resistance soft starter (VRSS) which limits the magnitude of inrush currents affecting 3-phase induction motors (IM). This device reduces input voltage using an automatically controlled 3-phase rheostat in series with the motor’s supply line voltage. The rheostat is a combination of three single-phase rheostats with the wipers mounted on a common shaft. The rheostat shaft rotates by a small motor driven by a microcontroller. A current transformer probe is clamped around a single-phase of the motor power supply line to provide the NXP microcontroller with information about the IM input current. The microcontroller processes the rate of change in the IM current signal and adjusts the rate of change in resistance of the 3-phase rheostat to gradually bring the 3-phase induction motor up to full speed.

We aim to take self-driving cars and alter their use slightly to offer better localization by sharing data between cars in a small area. We believe that today’s self-driving cars are limited in their efficiency and safety due to a lack of shared data about themselves and their surroundings. We aim to fix this by implementing data sharing over a local mesh network to allow important pieces of information to be provided for cars that otherwise would not know about it. We have approached this by first building a miniature electric car and showing that it has basic functionality such as driving around and receiving position and orientation data from a GPS and an IMU. We then built a second mini car that can communicate over a mesh network with the first one to share the most critical data. Algorithms have been developed to assist in the selection and sharing of the data over the network. We believe that the perception, and, therefore the self-driving capability of the cars, has been improved thanks to the implementation of this mesh network and the data-sharing ability given to the cars.