Senior Engineering Design Conference
student in the electrical and computer engineering department working on a project

Electrical and Computer Engineering

Student presentations

Spring 2026

Session Chair: Dr. Dinesh Maddipatla 

Room D-204

Emotion Recognition for Human-Machine Interfacing

9 to 9:25 a.m.

Team Members:
Cameron Kline
Ethan Vandermolen
Melanie Caggiano
    
Faculty Advisor:
Dr. Simin Masihi

As technology becomes increasingly integrated into everyday life, there is a need to correlate human emotional states to existing physical systems for boosting usability and safety. An emotion recognition system was developed using physiological signals, including electroencephalogram, electrocardiogram, galvanic skin response and respiratory rate.  Data collected from human subjects were analyzed using machine learning techniques to estimate emotional states within an arousal and valence framework. The system was tested during tasked-based experiments, generating emotional outputs suitable for integration with machine control logic. Results demonstrated the feasibility of integrating emotion recognition into human-machine interfaces to allow more intuitive interaction.

Real Time DER Inverter Control Testbed

9:30 to 9:55 a.m.

Team Members:
Ethan Woodke
Noah Taylor
Ryan Bainbridge

Sponsor:
InterEnergy Center, Western Michigan University

Faculty Advisor:
Dr. Pablo Gomez

Cybersecurity is a major concern for the safe and reliable operation of power grids. This is especially true as the grid integrates more communication technologies for control, protection, and automation. Grid cybersecurity studies require the implementation of testbeds that assess vulnerabilities in communication protocols used in grid applications. In this project, a grid-connected distributed energy resource (DER) was modeled and tested using a real-time digital simulator (RTDS). A real-time automation controller (RTAC) was connected and programmed to interface with the RTDS, using DNP3-based interconnection and IEEE-1547-2018-compliant grid-support functions, enabling further field testing to enhance DER support and reduce cybersecurity threats.

Smart Industrial Heated Glove

10 to 10:25 a.m.

Team Members:
Allen Morton
Cameron Johnson
Mohammed Afnan

Sponsor:
WMU Center for Advanced Smart Sensors and Structures

Faculty Advisors:
Dr. Massood Atashbar
Tony Hanson

Designed for electricians and construction workers in extreme cold, this heated glove utilizes advanced multi-layer screen printing to maintain warmth in temperatures as low as negative forty degrees Fahrenheit. The heating element is fabricated using silver traces and positive temperature coefficient carbon ink on a flexible film, then heat-pressed directly into the glove. This ultra-thin electronic textile replaces bulky copper wiring, preserving essential hand dexterity and comfort. Controlled by a custom circuit that adapts to ambient conditions, the design demonstrates the practical application of flexible hybrid electronics to enhance safety and performance in harsh industrial environments.

Machine Tending Arm Integration

10:30 to 10:55 a.m.

Team Members:
Hannah David
Robert Norton
Ryan Kisser

Sponsor: 
Dr. Pavel Ikonomov, Western Michigan University

Faculty Advisor:
Dr. Dean Johnson

The increasing use of CNC machines in engineering education created a need for a safe, automated material handling solution suitable for classroom environments. A collaborative robotic arm was integrated with CNC equipment to automate the loading and unloading of raw materials during machining operations. The resulting Machine Tending Arm Integration was designed to identify part locations, execute precise pick-and-place motions, and synchronize with machine operation states. Motion paths, timing, and safety constraints were analyzed and tested to ensure reliable and repeatable performance. This integration improved classroom safety, reduced instructor workload and enhanced hands-on learning by demonstrating real-world automation used in modern manufacturing.

Inverse Pendulum Stabilization

11 to 11:25 a.m.

Team Members:
Foster Gilmore
Nolin Szafranski 
    
Faculty Advisor:
Dr. Damon A. Miller

Control theory concepts are difficult to grasp without a physical system that visibly demonstrates how feedback is used to stabilize a naturally unstable system. A low-cost inverse pendulum stabilization system was designed and built to provide a transparent educational demonstration for exploring control theory. A microcontroller-based controller was implemented using angular position, velocity and acceleration feedback to drive two fans to maintain upright stability. Experimental testing verified pendulum stability with a prescribed response time. The completed system enables visualization of real-time feedback control.

Passive Exosuit for Weight Lifting Assistance (PEWLA)

11:30 to 11:55 a.m.

Team Members:
Austin Simons
Maz Raaymakers
Nikhil Goud Soma

Sponsor: 
Dr. Tarun Gupta, Western Michigan University

Faculty Advisors:
Dr. Dean Johnson
Dr. Tarun Gupta

The lower spine is one of the most common sources of injury during manual lifting, and research is currently lacking on the use of passive exoskeletons for injury prevention. A system of wearable sensors was created to measure spinal bending, twisting and compression at the L5–S1 vertebra. The sensor data is sent wirelessly to an external program which assesses the risk of spinal injury according to guidelines set by the National Institute for Occupational Safety and Health. The Passive Exosuit for Weightlifting Assistance will be used in a research setting to evaluate the effectiveness of a passive exoskeleton in spinal injury prevention.

Presentations will take place at Floyd Hall in room D-204.

Three-Phase Dual-Active Bridge

9 to 9:25 a.m.

Team Members:
Ashton Shall
Cole Tilton
Gabe Mckinney

Faculty Advisor:
Dr. Sandun Kuruppu

The recent increase in power consumption, especially with rising electric vehicle ownership, has raised concerns of grid instability and a need for efficient, high voltage DC-DC converters. A three-phase dual-active bridge (DAB) was designed with bidirectional power flow and efficient energy transfer as the primary goals. The output voltage was kept constant using closed-loop control to ensure proper operation under various load conditions. The three-phase DAB ensures Galvanic isolation between input and output and offers increased power density when compared to the single-phase DAB. This design will serve as a scalable reference for high voltage DC applications.

 

32-bit RISC-V Out-Of-Order CPU

9:30 to 9:55 a.m.

Team Members:
Alex Marsh
Ben Davis
CJ Blanchard
Noah Braasch

Faculty Advisor:
Dr. Lina Sawalha

The design is a 32-bit CPU that uses the RISC-V instruction set architecture, an open-source standard designed for flexibility and efficiency. Traditional in-order processors execute instructions sequentially without reordering. In contrast, this design incorporates an out-of-order pipeline, enabling dynamic instruction reordering when no instruction dependencies are present. Simulations will compare performance against an in-order pipelined CPU to highlight throughput improvements. Implementation on a field-programmable gate array (FPGA) will demonstrate functional correctness while showcasing CPU operations in real time and emphasizing instruction-level parallelism in modern computer architecture.

 

CalmPaw: Pet-Award Vacuum System

10 to 10:25 a.m. 

Team Members:
Marcus Nesbary
Alfonso Jimenez

Sponsor:
Bissell, Inc.

Faculty Advisor:
Dr. Dean Johnson

A pet-friendly vacuum called CalmPaw that automatically adjusts its airflow when animals are nearby has been designed and built. Using a lightweight collar with a wireless sensor, the system detects pet proximity and sends a signal to the vacuum. Once triggered, the vacuum reduces suction power and airflow, creating a calmer environment while still maintaining cleaning ability. This helps pets feel less startled by noise and sudden air movement. Simple lighting indicators show when the vacuum is in pet mode. By combining smart sensing with gentle airflow control, CalmPaw offers a cleaner home without compromising the comfort and well-being of pets.


Sensory Feedback Integration for an EEG-Controlled Robot Arm

10:30 to 10:55 a.m.

Team Members:
Kyle Gilbert
TaVaughn Walker
Sherif Ayantayo
Bryan Ngu

Faculty Advisor:
Dr. Simin Masihi

A sensory-feedback system was developed to improve control and interaction with a robotic arm manipulator. The system integrated physiological signals, such as brainwaves recorded via an Electroencephalogram (EEG) cap, with robotic data including applied force to correlate human physiology with overall task performance. A Kinova Gen3-Lite robotic arm was equipped with force sensors and actuators that converted grip force into feedback modalities, delivered as visual cues through LED blinking or as tactile vibrations. MATLAB/Simulink simulations followed by hardware testing validated the closed-loop performance with millisecond-level latency. The final system demonstrated improved dexterity, comfort, intuitive control and enhanced user feedback, providing a foundation for advanced rehabilitation and assistive technologies.

 

Integrated Vacuum Tube Audio Amplifier

11 to 11:25 a.m.

Team Members:
Jacob Knotts
Robert Lulko

Sponsor:
Keystone Solutions Group
Kazoo Audio

Faculty Advisor:
Dr. Damon A. Miller

Vacuum tube amplifiers have been available since the early 1900s, and updated models are used today in the high-end audio market. Audiophiles often state that vacuum tube amplifiers have a “warmer” sound than modern units. A vacuum tube audio amplifier to capture this desired sound quality and improve upon signal distortion and power efficiency was designed, built and tested.

Presentations will take place at Floyd Hall in room D-204.

Depth of Calcination Probe

9 to 9:25 a.m.

Team Members:
Arpad Sefcsik
Jakob Preston

Sponsor:
Jason McPherson, B.S.E.’97, MSD Engineering

Faculty Advisor:
Dr. Janos Grantner

The need to improve fire investigation methods prompted the development of an enhanced depth-of-calcination meter for gypsum wallboard. Calcination depth, an indicator of heat exposure during a fire, was analyzed using an upgraded electronic probe integrated with more advanced components. The design utilized resistance measurements to distinguish between calcinated and non-calcinated wallboard sections. Machine learning algorithms were implemented to provide predictive results based on repeated measurements. The device was tested to account for variables such as wall thickness and material inconsistencies. This new design has improved greatly over the prototype in regards to ease of use and efficiency.


Smart Solutions for Bed Sore Detection

9:30 to 9:55 a.m.

Team Members:
Ben Exline
Dylan Greer
Dylan Nevar

Sponsor:
WMU Center for Advanced Smart Sensors and Structures (CASSS)

Faculty Advisor:
Dr. Massood Atashbar

Bed sores are a common issue caused by prolonged pressure on the skin, often going undetected until severe. Smart solutions for bed sore detection are now within reach. A compact, mattress-compatible device equipped with a flexible integrated circuit and advanced pressure sensors can monitor pressure points and posture during sleep. By analyzing data on areas of sustained pressure and duration, this smart bed can help identify early signs of bed sores. When integrated into more complex systems, it could even make real-time adjustments to reduce pressure and prevent sores, offering a proactive approach to bed sore management.

 

Real-Time Testbed for Smart Grid Recloser

10 to 10:25 a.m.

Team Members:
Asker Akil Islam
Ethan Weldert
Nathaniel Barnes

Sponsor:
WMU Center for Interdisciplinary Research on Secure, Efficient and Sustainable Energy Technology

Faculty Advisor:
Dr. Pablo Gomez

Microgrids and their smart components have become increasingly prevalent in the power grid with the introduction of renewable energy systems and electric vehicle charging stations. A real-time digital testbed (simulated environment) was developed to analyze the behavior of a physical microgrid recloser controller, a device that can disconnect, reconnect and isolate a microgrid from the main grid. This device can detect faults including over/undercurrent, over/undervoltage, overload, and inconsistent alternating current frequencies. The testbed can provide useful information on the capabilities of the recloser controller without the need for physical microgrid setup, providing safety and efficiency in power testing.


High Frequency Transformer Design

10:30 to 10:55 a.m.

Team Members:
Ethan Kotre
Landon Balogh
Nick Eastman

Sponsor:
Dr. Sandun Kuruppu, Western Michigan University

Faculty Advisor:
Dr. Pablo Gomez

Electric vehicle (EV) charging technology requires highly efficient high frequency transformers that can support bidirectional power transfer. This bidirectionality allows EVs to supply energy back to the grid, helping to stabilize the grid and reduce reliance on fossil fuels. This also provides backup power solutions to EV owners during outages or high-demand periods. A scaled-down high frequency transformer was designed and implemented for EV charging technology, focusing on providing high efficiency, power density and overall reliability. Initially, a finite element method-based model was developed and parameterized to support the evaluation of design alternatives. Based on this model, a transformer was built and tested for compliance with all main specifications.

 

Electronic Metronome

11 to 11:25 a.m.

Team Members:
Gage McCaffrey
Jalen Glenn

Sponsor:
Dr. Frank Severance, Western Michigan University

Faculty Advisor:
Dr. Frank Severance

An interactive metronome enhances rhythm training by combining traditional functionality with adaptive technology. It operates in two modes: Forward Mode allows users to manually set and adjust beat frequency using an analog dial, while Reverse Mode detects beats from user input and synchronizes timing. A built-in speaker and LED display provide real-time auditory and visual feedback. Utilizing microprocessors, circuit analysis, and linear systems, the design ensures precision and adaptability. Compact and user-friendly, this tool will support the musician at any level of proficiency in developing timing accuracy and rhythm internalization for more effective practice and performance.


Automated Sand Grain Size Analysis

11:30 to 11:55 a.m.

Team Members:
Annelise Kolp
David Micklewright
Emily Eringaard

Sponsors:
Dr. Sam Ramrattan, Western Michigan University
Dr. Robert Makin, Western Michigan University

Faculty Advisor:
Dr. Damon Miller

Sand grain size analysis is essential to the metal-casting industry. Current manual measurement methods are time and labor-intensive. Machine learning algorithms and computer vision techniques were developed to automate grain size characterization using high-resolution microscopic imaging. A custom system was designed to capture and analyze sand grain surface area and size distribution using a Raspberry Pi, PyTorch and a MicroCapture 200x microscope. Neural network models were trained to classify grain size using established geological standards. This novel approach significantly accelerates sand grain analysis, potentially revolutionizing particle assessment methodologies. 

Presentations will take place at Floyd Hall in room D-204.

Automated Control System for Reflection High-Energy Electron Diffraction (RHEED) Capture Analysis

9 to 9:25 a.m.

Team Members:
Brianna Murphy
Joseph Williams

Sponsor:
Dr. Robert Makin, Western Michigan University

Faculty Advisor:
Dr. Damon Miller

Molecular beam epitaxy is a process used for creating thin films of single-crystal materials used for manufacturing semiconductors and nanotechnology structures. During the molecular beam epitaxy process, reflection high-energy electron diffraction capture analysis is utilized to acquire information about the surface of the substrate, including roughness, structural properties, and growth rate. To improve the precision and accuracy of reflection high-energy electron diffraction data, an automation system was created and tested to perform this process, which also increases overall efficiency and safety.


EEG Controlled Robotic Arm

9:30 to 9:55 a.m.

Team Members:
Camryn Ruiz
Ladd Carpenter
Michael McCaulley

Sponsor:
WMU Center for Advanced Smart Sensors and Structures

Faculty Advisors:
Dr. Simin Masihi
Dr. Massood Atashbar

Integrating prosthetics into the lives of amputees is crucial for restoring functionality. Current prosthetics offer limited motion and lack intuitive control, often requiring strict maintenance. We recognize the potential of neuro-prosthetics to address these issues. A proposed robotic arm, controlled by neural signals captured via an electroencephalography cap, aims to enhance prosthetic functionality. This work involves data collection, signal processing, data analysis, machine learning, circuit design, and robotics to demonstrate the feasibility of mind-controlled prosthetics. This innovation could significantly improve the quality of life of amputees, by providing more natural limb movements and intuitive control.
 

Machine Learning Powered Stretchable Smart Textile Gloves

10 to 10:25 a.m.

Team Members:
Anika Tabassum
Farzana Mahbub
Georgia Hill

Sponsor:
WMU Center for Advanced Smart Sensors and Structures

Faculty Advisors:
Dr. Massood Atashbar
Tony Hanson

Effective communication with individuals with hearing loss often requires sign language, which can be a significant barrier. A machine learning powered glove system can overcome this barrier by capturing complex hand movements. This system translates sign language gestures into text and speech in real-time, providing a bridge between sign language users and those unfamiliar with it, thus facilitating smoother interactions in various social, educational, and professional environments. These gloves are designed using advanced machine learning algorithms to estimate hand-joint angles and recognize gestures accurately. The system integrates gesture control into digital environments through a computer program, offering feedback via visual and auditory cues. This technology aims to provide a precise, real-time solution for gesture recognition, enhancing user interaction and engagement.


Electric Motor Thrust Stand

10:30 to 10:55 a.m.

Team Members:
Evan Schober
Joshua Kraeuter

Sponsor:
Dr. Kapseong Ro, Western Michigan University

Faculty Advisor:
Dr. Johnson Asumadu

Understanding motor and propeller performance is an important part of the aircraft design process. A testing platform containing several sensors was developed for small scale electric propulsion systems. The data from the sensors are captured and processed using an integrated computer board known as Raspberry Pi. The device for small scale electric propulsion systems was developed using several commercial sensors. The data from these sensors allow users to measure key performance parameters such as input voltage, current draw, motor RPM, and thrust. This device will be used in aerospace classes and competition teams to evaluate aerial propulsion systems.
 

Automation Cart

11 to 11:25 a.m.

Team Members:
Jimmy Keusch
Hunter Ungaro
Conlan Wilder

Sponsor:
Sam Mensch, B.S.E.’11, Mensch Manufacturing

Faculty Advisor:
Dr. Damon Miller

Dairy farm workers face health risks from contact with manure and other byproducts. An automated cleaning vehicle was developed to navigate the barn autonomously and clean manure, allowing workers to focus on other tasks safely. The vehicle utilized Danfoss XM100 and MC018-030 controllers for automation and propulsion, programmed using PLUS+1® Guide software. A proof-of-concept vehicle was designed, built and tested in a dairy barn environment. The automated cleaning system improves worker health and safety while increasing overall farm efficiency.


Claims-Investigation Committee (CIC) Multi-Input Testing Device

11:30 to 11:55 a.m.

Team Members:
Daniel Baker
Dylan Matthew-Garza
Rohullah Sah

Sponsor:
Patrick McNally, ZF Group

Faculty Advisor:
Dr. Janos Grantner

The automotive industry requires rigorous testing of safety components to ensure vehicle reliability and passenger safety. An integrated test system is being developed to streamline the evaluation of automotive and safety components including brake signal transmitters, pressure sensors, wear sensors, electronic stability control modules, and string potentiometers. The system employs a custom-designed test device built around an ARM Cortex-M4 microcontroller and ARM Cortex-A7 running a custom embedded Linux image. It interfaces with peripherals through PWM, analog, and CAN communication protocols, while communicating with a web-based front-end application using Web Assembly, that communicates with a back-end server, both written in Rust, with the ability to save the test results in a text file. The project aims to reduce time and cost associated with field claim evaluations, improve accuracy in identifying faulty components, and enable efficient troubleshooting and root cause analysis.

Presentations will take place at Floyd Hall in room D-204.

DIY Electrometer for Neural Electrophysiology

9 to 9:25 a.m.
 
Team Members:
Connor Villanueva
Garrett Russell
Leanne Tuuk
 
Sponsor:
WMU Neurobiology Engineering Laboratory
 
Faculty Advisor:
Dr. Damon Miller
 
An electrometer is used to study the voltage response of a neuron by applying nanoamp-level currents through an intracellular electrode inserted into the cell. The electrometer provides amplification and filtering of the neuron response. Research-quality electrometers are expensive. Project deliverables included detailed assembly instructions, components list, prices, and a user manual. The approximately $600 electrometer will greatly reduce the capital cost of electrophysiology experiments for educational institutions.
 

Medium Frequency Power Control for Industrial Furnaces

9:30 to 9:55 a.m.
 
Team Members:
Devon Crites
Matt Leja
Sean Wiessner
 
Sponsor:
RoMan Manufacturing
 
Faculty Advisor:
Dr. Pablo Gomez
 
This project created a Medium Frequency Power Control (MFPC) for industrial furnace applications. Powered by a high-capacity Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET)-based inverter under the control of an industrial microcontroller, the MFPC optimizes energy usage while providing precision in process control. The inverter takes 650 Volts from a rectifier and converts it to a stable 680 VAC at 1 kHz. A Raspberry Pi was utilized to control the MFPC, allowing RoMan Manufacturing to optimize industrial power management by utilizing MOSFETs, which have less losses than the insulated-gate bipolar transistors (IGBTs) that are currently on the market for electric furnaces.


 

EEG Controlled Robotic Arm

10 to 10:25 a.m.
 
Team Members:
Isaac Bagley
Jacob Simons
Minhaz Shahrier
 
Sponsor:
WMU Center for Advanced Smart Sensors and Structures
 
Faculty Advisors:
Dr. Simin Masihi
Dr. Massood Atashbar
 
Individuals without the use of a limb face significant challenges in interacting with their surroundings. These unique challenges are often remedied with the use of a prosthetic limb. However, prosthetics provide limited movement options, lack natural neural control from the user, and require specific maintenance guidelines. To improve this solution, a Senior Design team at Western Michigan University has proposed the development of a robotic arm that is controlled by brain signals received by an electroencephalogram (EEG) cap worn by the user. This project aims to be completed as a proof of concept for EEG controlled prosthetic limbs.
 

1st Person Scaled EV with Electronic Differential

10:30 to 10:55 a.m.
 
Team Members:
Evan Cain
Lena Mandwee
Tessa Biondo
 
Sponsor:
Dr. Sandun Kuruppu, Western Michigan University
 
Faculty Advisor:
Dr. Sandun Kuruppu
 
A 1/7th scale custom electric vehicle was designed and constructed to explore advancements in stability control. This involved the development of an electronic differential, which enhanced the vehicle’s maneuverability and response to varying driving conditions. First person view technology was integrated, enabling remote driving and offering a novel perspective on vehicle handling. Vehicle dynamics were rigorously analyzed, focusing on stability under different scenarios. The results of testing the performance of this vehicle were evaluated to gain deeper insights into stability control mechanisms, potentially influencing future full-scale electric vehicle designs.
 

Real-time Testbed for Transmission Line Protection

11 to 11:25 a.m.
 
Team Members:
Mark Booge
Kyle Taiariol
Nolan Ulp
 
Sponsor:
Dr. Pablo Gomez, Western Michigan University
 
Faculty Advisor:
Dr. Pablo Gomez
 
Hardware in the loop (HIL) testing is crucial for designing and managing electric power grids. Combining physical components with modern real-time hardware/software testbeds creates effective tools for training, which might be too dangerous or impractical in the field. The project developed an HIL testbed connecting a real-time digital simulator and an SEL 421 protection relay. This serves as an educational tool for WMU instructors and students interested in power system protection. Additionally, the project provides documentation for configuring simulation parameters and grid topologies of different test cases without requiring a deep understanding of the necessary hardware and software tools.
 

Telemetry Enabled Vehicle EGT Monitoring

11:30 to 11:55 a.m.
 
Team Members:
Vito Torina
Eljiah Sargeant
 
Sponsor:
Noah Gould, WMU Formula SAE Team
 
Faculty Advisor:
Dr. Janos Grantner
 
Monitoring the exhaust gas temperature of an internal combustion engine is a vital method to understand the performance and health of an engine. A physical board was created to interface between the individual cylinder temperatures and a telemetry system to monitor them. This allows users to adjust spark timing and fuel flow to facilitate peak engine performance and health. This analysis can guarantee a safer operating environment and allow an internal combustion engine to be utilized to its maximum potential.
 

Real-time Testbed for Smart Inverter Cybersecurity Studies

1 to 1:25 p.m.
 
Team Members:
Alfred Batu
Badr Semia
Lucas Ling
 
Sponsor:
WMU InterEnergy Center
 
Faculty Advisor:
Dr. Pablo Gomez
 
The purpose of this project was to create an interactive testing environment to analyze cybersecurity threats targeting grid-tied smart inverters across various operational scenarios. This project utilized a real-time digital Simulator (RTDS) and its grid modelling software to replicate authentic grid topologies and inverter controls. Industrial-grade Distributed Network Protocol 3 (DNP3) was configured within the model to allow hardware interfacing between the Real Time Digital Simulator and automation controller for internal and external data transmission and acquisition. The testbed will allow further study and testing of smart inverter functionalities including reactive power compensation, voltage ride-through and fault-ride through, that may malfunction in response to a potential cybersecurity attack.
 

Data Collection and Real Time Monitoring of a Torque Transducer

1:30 to 1:55 p.m.
 
Team Members:
Cross Pui
Nathan Hand 
Tanvy
 
Sponsor:
Dr. Sandun Kuruppu, Western Michigan University
 
Faculty Advisor:
Dr. Sandun Kuruppu
 
In the pursuit of designing a product that adhered to sponsor specifications, the project aimed to create a torque transducer—a specialized tool for measuring rotational force. Unlike conventional systems that merely logged data, this advanced torque transducer seamlessly displayed real-time torque and speed on a user-friendly interface. With a sampling rate exceeding 8000 Hz and 16-bit digital resolution, users could monitor data through an oscilloscope while logging it on a Secure Digital (SD) card. Implementation involved researching scholarly articles and testing the system in software such as LTSpice, STM32CubeIDE, and KiCad. Ensuring a properly packaged form factor aligned with sponsor requirements, the completed project delivered a cost-effective and efficient system beneficial across various industries.
 

Formula SAE Electric Vehicle Accumulator

2 to 2:25 p.m.
 
Team Members:
Jack LeFevre
Josh Iwick
 
Sponsor:
WMU Formula SAE Team
 
Faculty Advisor:
Dr. Johnson Asumadu
 
The Western Michigan University Formula Society of Automotive Engineers (SAE) Team has designed the accumulator for a formula-style electric race car. The accumulator contains battery cells, battery management system, safety systems, and other electronics. The design of the safety system also includes pre-charge, discharge system, voltage indicator lights, and voltage and thermal monitoring systems. The main objective is to produce a safe and functional battery pack system, which also addresses the Formula SAE rules.
 

Sunseeker 2023 Car Next Generation Battery System

2:30 to 2:55 p.m.
 
Team Members:
Donovan Mahon
Jacob Lehman
Mitchell Jacobs
 
Faculty Advisor:
Dr. Bradley J. Bazuin
 
The WMU Sunseeker Solar Car has multiple critical electronic subsystems. One of the most important subsystems is the energy storage and distribution system, consisting of lithium ion batteries and the battery management, protection, and power connections. After analysis and review of prior generations of battery subsystems, new architectures have been defined and developed for current and future cars. With stringent racing organization requirements and specifications, subsystem architecture one is partially based on a commercially available battery management system along with a custom controller and architecture two is a completely custom subsystem that has been defined and critical electronic elements designed, fabricated and tested.
 

Assembly Line Status Monitoring System

3 to 3:25 p.m.
 
Team Members:
Hudson Phillips
Ryan Glave
Tronic Williams
 
Sponsor:
I I Stanley
 
Faculty Advisor:
Dr. Dean Johnson
 
The Assembly Status Monitoring System (ASMS) was designed to enhance assembly line monitoring. The system organizes and communicates machine analytics from production performance through a custom Python code-based GUI and Faytech capacitive touch screen monitor that provides both user interaction capabilities and graphical representations for improving productivity. The ASMS addresses inefficiencies in current manufacturing processes, including data exchange and labor-intensive tracking. The system features real-time data access and reporting, comprehensive machine data collection using the Revolution Pi single board computer with Modbus protocol and custom I/O signal interception. It improves decisiveness for managerial staff, supports operator proficiency, and production issue traceability. Key specifications include visual performance displays, data logging, machine-specific problem isolation, and secure administrative access. This system integrates with various manufacturing equipment using standard protocols and is tailored to meet the unique needs of automotive manufacturing.