Dynamic graph-based modeling and predictive control of waste heat recovery cycles for hybrid aircraft
Open Access
Author:
Williams, Michael
Graduate Program:
Mechanical Engineering
Degree:
Master of Science
Document Type:
Master Thesis
Date of Defense:
March 26, 2025
Committee Members:
Herschel C Pangborn, Thesis Advisor/Co-Advisor Stephen P Lynch, Committee Member Robert Kunz, Professor in Charge/Director of Graduate Studies
Keywords:
dynamic modeling model predictive control hybrid aircraft graph-based modeling waste heat recovery energy systems
Abstract:
This thesis explores the effects of integrating supercritical carbon dioxide (sCO2) Waste Heat Recovery (WHR) cycles into aircraft propulsion, power, and thermal management systems using dynamic models and model predictive control (MPC). Dynamic models are developed using graph-based modeling (GBM), a component-based modeling technique that uses conservation equations to model system behavior. Next, hybrid aircraft architectures are developed and WHR benefits are analyzed using MPC, an optimal control method that uses physical constraints and performs in real-time. Case study results show that, depending on aircraft size, flight conditions, and overall design, sCO2 WHR can generate between 100 and 400 kW during takeoff and cruise -while respecting
physical property limits. Additionally, these results show that these limits are strictly maintained during flight transience. The findings demonstrate how advanced control algorithms and thermal cycles can enhance the performance of electrified aircraft while overcoming limitations of traditional control and design approaches.
