Industry-Sponsored Student Capstone Projects

SmartPDN is an early-stage chip power modeling tool developed in collaboration with Micron Technology. It allows engineers to describe a chip’s power system using simple input files containing chip design information such as its components and connections, then generates chip visualizations, design scripts, and simulation-ready circuit netlists before the full chip layout is completed. By supporting early impedance estimation, hierarchical modeling, and simplified circuit generation, SmartPDN helps engineers explore design options earlier in the development process, improve consistency between design intent and implementation, and reduce risks of costly issues later in semiconductor design.

In collaboration with Microsoft, this team developed a machine-learning pipeline to track the contributing factors behind battery swell in Microsoft Copilot PCs. Battery swell is a persistent issue in lithium batteries that arises from electrochemical processes that current methods cannot effectively predict from within the device. This project aims to monitor and estimate swell using on-device resources, enabling better control of its progression. To this end, the students analyzed extensive battery data gathered by Microsoft’s Battery Lab to identify the features most correlated with swell and developed scripts to capture device data and feed it into our prediction model.

At NASA's Jet Propulsion Laboratory (JPL), mission success relies on rigorous robotic testbed operations. Documenting these complex tests is a critical but manually intensive process that can distract operators from their primary tasks. This student team partnered with JPL to create ASTRA (Advanced System for Testbed Recording and Analysis). ASTRA is an intelligent engineering assistant developed for NASA JPL robotic testbeds. This system reduces operator workload during long duration missions by automatically capturing voice observations and syncing them with live hardware data. Using WebRTC and the OpenAI STT API, AISTRA transcribes speech in real time. It then queries the InfluxDB telemetry pipeline to fetch the exact sensor values from that specific moment. Finally, a LLM synthesizes both inputs into a structured, searchable engineering note. ​This event driven approach ensures every spoken observation is instantly backed by hard data, creating a highly traceable timeline for aerospace engineers.

Database of State Incentives for Renewables and Efficiency (DSIRE) is a leading source of information on policies and incentives that support renewable energy and energy efficiency, but its utility incentive data had been maintained through manual reviews of program websites. Because utility programs can change frequently, this approach did not always capture the latest information, and it limited coverage to utilities with 30,000 or more customers, leaving many smaller electric utilities outside DSIRE’s scope. To address this gap, the project developed an AI-based process to scan electric utility websites, identify text relevant to financial incentives, and extract key details about incentives for renewable energy systems, electrification devices, energy-efficient equipment, and building improvements. The effort produced a training dataset and a working model or application intended to help staff keep the system updated and support the addition of information from smaller utilities into DSIRE, expanding the potential to track incentive programs that were previously difficult to monitor at scale.

This project focused on the need for a more reliable backup method for bringing variable-buoyancy air hoses to the surface in tidal and river energy systems, where strong currents, corrosion, sedimentation, marine growth, and limited access complicate maintenance. The student team developed a prototype Secondary Air Umbilical Unit intended to mount to existing equipment or provide standalone secondary hose storage. The unit needed to hold three 20-meter, 1/2-inch air hoses and release them when remotely triggered through ORPC’s subsea control and instrumentation interface, allowing the hoses to be retrieved at the surface. The design accounted for fresh and saltwater operation, flow speeds up to 2.5 m/s, depths up to 15 meters, repeated surface reset cycles, and minimal-maintenance operation without exposing sealed electronics. The prototype provides a testing platform for a more dependable secondary air-umbilical release capability in demanding marine energy environments.

This project presents an AI-powered framework for the autonomous reverse engineering of proprietary Otis elevator service interface protocols, extensible to competing platforms. Using a stimulus-response methodology on an elevator simulator, the framework monitors serial communications, maps state transitions with protocol messages, and generates structured documentation by clustering diagnostic symbols into their signal state groups. Through a structured data collection process, engineers can feed elevator data into the system, eliminating manual protocol decoding. The framework enables querying of the elevator controller for specific signal states, bypassing the diagnostic tool entirely.

This project developed a distributed system for real-time tracking and prediction of trans-oceanic vessels using clipper race telemetry and AIS data. Built on the Paranet framework, this system enables dynamic communication across distributed nodes, including data ingestion, vessel nodes, and a marine overview interface. Beyond tracking, the team explored transformer-based models for trajectory prediction and investigated the integration of environmental factors such as wind and ocean currents. This work highlights both the challenges of limited maritime data and the potential for intelligent, predictive marine systems.

This project consisted of developing conceptual designs to decentralize heating and cooling plants at multiple facilities at JBLM. The project addressed the need to evaluate and select building mechanical systems with stronger consideration for energy use, life cycle cost, and environmental impact. It focused on developing a mechanical design and assessment capability grounded in heat transfer, thermodynamics, and fluid dynamics to compare system options, perform load calculations, model energy performance, and identify opportunities to reduce or recapture energy. The work included system selection, design layout in CAD or BIM software where available, and supporting calculations, drawings, and reports, providing a structured basis for understanding facility mechanical design and its effect on carbon footprint.

The E-Truck Challenge began in late 2023 through a partnership with PACCAR to retrofit a Class 7 Peterbilt truck into an all-electric vehicle over four years. The effort grew to include a broader UW student engagement through a Registered Student Organization (RSO) focused on giving participants hands-on experience with industry components, software, and engineering practices while advancing cleaner transportation. The Battery Truck Plant Model project is focused on developing a system-level MATLAB/Simulink model of a battery electric truck. The model integrates major subsystems, including the high-voltage battery, motor drive unit, vehicle dynamics, controller, and thermal monitoring. Using CAN test data from the actual truck, the team will calibrate and validate the simulation to study energy use, acceleration, braking, range, and subsystem interactions. The final deliverable is a modular, documented plant model that supports performance analysis and future electric truck development.

The E-Truck Challenge began in late 2023 through a partnership with PACCAR to retrofit a Class 7 Peterbilt truck into an all-electric vehicle over four years. The effort grew to include a broader UW student engagement through a Registered Student Organization (RSO) focused on giving participants hands-on experience with industry components, software, and engineering practices while advancing cleaner transportation. The battery electrical interface project seeks to develop a system connecting a 620 VDC battery to a battery electric vehicle (BEV) truck. This project will integrate and test systems such as a high voltage junction box, DC-DC converters, S-box and ECU. The focus is on creating a safe integration into the E-truck system to ensure proper communication between the different power systems and power distribution for other vehicle functions such as steering, torque, and motor control function.  

The E-Truck Challenge began in late 2023 through a partnership with PACCAR to retrofit a Class 7 Peterbilt truck into an all-electric vehicle over four years. The effort grew to include a broader UW student engagement through a Registered Student Organization (RSO) focused on giving participants hands-on experience with industry components, software, and engineering practices while advancing cleaner transportation. Within that larger vehicle conversion effort, this capstone project addressed a need to integrate CATL battery strings into the truck architecture with secure mounting and safe connections to the cooling and high-voltage electrical systems. The students worked to define battery, high-voltage junction box, and S-Box locations and develop a complete design for mounting and connecting the battery system within the vehicle.

The E-Truck Challenge began in late 2023 through a partnership with PACCAR to retrofit a Class 7 Peterbilt truck into an all-electric vehicle over four years. The effort grew to include a broader UW student engagement through a Registered Student Organization (RSO) focused on giving participants hands-on experience with industry components, software, and engineering practices while advancing cleaner transportation. The charge control unit (CCU) of an electric vehicle is an integral component, as it regulates the current flow between the charging station (EVSE) and the vehicle’s battery. As the truck is converted from a diesel-based system to an all-electric vehicle, the CCU must process an increased number of signals from other components, such as the vehicle control unit (VCU). This project involved developing software for the handshake sequence required to initiate charging using CAN bus signal messaging, the Raptor system, and the charging inlet. The software was then tested on physical hardware using hardware-in-the-loop testing with CANalyzer.

The E-Truck Challenge began in late 2023 through a partnership with PACCAR to retrofit a Class 7 Peterbilt truck into an all-electric vehicle over four years. The effort grew to include a broader UW student engagement through a Registered Student Organization (RSO) focused on giving participants hands-on experience with industry components, software, and engineering practices while advancing cleaner transportation. This team contributed to the electrification of the donated truck chassis by developing torque logic using Simulink, CANalyzer, and Raptor, for deployment on the electronic control unit. Prioritizing safety and efficiency, the developed software ensures precise and reliable power delivery to the wheels all while using SAE J1939 standards for easy integration and seamless adaptation.

Water for Injection (WFI) is critical in biotech for producing sterile, safe pharmaceutical products and medical devices by providing a highly purified, pyrogen-free solvent and diluent for injectable drugs, and for cleaning/rinsing production and packaging equipment. The North Creek site relies on a single distillation-based WFI generation system, meaning a catastrophic failure could disrupt manufacturing by removing a critical source of highly purified, pyrogen-free water used for injectable drug production and for cleaning and rinsing equipment. The project developed a business case for adding a second WFI generation system and compared newer membrane-based purification technology with traditional distillation. The assessment was intended to define the problem and opportunity, evaluate potential benefits, costs, risks, feasibility, and success criteria, and support justification of a redundant WFI capability. To inform that comparison, the work included a process flow diagram, mass and heat balance, capital cost estimate, and annual operating expense tabulation, providing a structured basis for evaluating alternatives and improving system redundancy for manufacturing operations.

The goal of this project involved figuring out a way to support the fully fueled 2.9 million pound Radian One vehicle during its ground sled run, when its wings carry very cold liquid oxygen and experience high rolling loads that could otherwise drive wing structural weight beyond mission limits. The project focused on a wing support system intended to reduce overall flight vehicle weight by carrying wing loads on the sled while still allowing enough airflow beneath the wings for normal takeoff. The concept evaluation considered alternative support approaches and their potential effect on dry weight, operability, wing aerodynamic performance, drag, and the risk of choked flow during separation conditions. A subscale model of the support system was built to enable wind tunnel testing and structural analysis.