Thermo-Fluids Control Laboratory

Research Overview

Control of thermofluid systems lies at the intersection of two traditionally disparate fields of mechanical engineering. Many types of energy systems such as vapor compression cycles, solar boilers, fuel cells, and biomass reactors, use fluid phase changes and/or chemical reactions to transform or transport energy. These systems often operate almost exclusively in transient, despite being designed for steady-state operating conditions. Although precise transient control of energy systems like fuel cells is critical to achieving high efficiencies, the traditional static viewpoint of more standard energy systems also results in a missed opportunity for efficiency improvement. This is particularly true for vapor compression cycles, which find wide use in refrigeration, air conditioning, and heat pump applications. Moreover, with legislation phasing out typical HFC refrigerants, more environmentally friendly refrigerants (e.g. CO2) are being vigorously pursued. The technological focus of current research projects focus primarily on vapor compression systems and related energy systems. This necessarily includes research in the areas of dynamic modeling (model development, reduction, and validation) and nonlinear control design (gain-scheduling, Model Predictive Control, sets of stabilizing controllers). We ensure the viability of our research by developing software tools for industrial partners (e.g. HVAC&R Dynamix) and involving direct experimentation for virtually every project (Research Facilities). Some of our current research projects are listed below. Please visit our Research Opportunities page for more information on current opportunities for students.


Current Projects

Industrail Assessment Center

Students: Trevor Terrill, Christopher Price, Rohit Chintala

The Texas A&M University (TAMU) Industrial Assessment Center (IAC) proposes to train/employ 12 young engineers (engineering undergraduate and graduate students) annually and conduct 24 assessment days in 22 small and medium-sized manufacturing plants each contract year. The engineering students will receive hands-on and formal training about industrial energy conservation, waste reduction, and productivity improvement. Within 60 days of each assessment visit, a formal, technical report will be supplied for each plant, and assessment data will be uploaded to the national IAC database.
Twenty-four assessment days in 22 plants allow two plants each year to have two-day assessment visits due to facility size and/or complexity, and in coordination with the state Manufacturing Extension Partnership (MEP). In the event two plants are not identified for twoday assessment visits, more plants will be selected so that the contracted number, 24, of assessment days is fulfilled. Additional multiple-day assessments will be with DOE approval, to serve plants with relatively large energy bills, or to serve large, complex plants or processes.


Distributed Model Predictive Control for Building Energy Systems (National Institute of Science and Technology)

Students: Students: Matthew Elliot, Chris Bay, Rawand Jalal, Rohit Chintala

This research seeks to create coordinated control strategies for building energy systems that minimize energy usage while ensuring occupant comfort and health. This requires effective component- and system-level control strategies, understanding of building-occupant interactions, and in situ experiments. Building operations account for approximately 40% of US energy usage and carbon emissions, and 75% of peak electrical demand. The successful completion of this project will result in the next generation of energy management systems critical to achieving Net Zero Energy Buildings (NZEB). The proposed modeling tools will enable engineers to model complex interconnected energy systems, with an accompanying set of control tools that ensure stable, effective operation under changing conditions and configurations. These tools also provide an effective means for both interpreting occupant comfort demands and providing essential feedback that can shape occupant behaviors for greater energy efficiency. While the proposed tools and methods will be applicable to a wide range of energy systems, the particular focus of this study will be heating, ventilation, and air conditioning (HVAC) systems.

Heat Pump Dynamic Simulation Model (Emerson)

Students: Shuangshuang Liang, Chao Wang

Texas A&M University proposes to develop a heat pump dynamic simulation tool that will allow transient modeling of variable (or fixed) speed heat pumps systems for residential markets to address issues such as energy use, energy cost, system and component optimization, control strategies, comfort predictions, and impact on reliability. The proposed model is specifically designed for rapid execution with easy to visualize output reports, including graphs and tables of
data, and will includes an easy to use interface. The model includes a simplified representation of the house load in heating and cooling seasons, including weather from standard databases, and will be validated with experimental data. This toolset will be able to simulate dynamic operating conditions and be ready for full integration with control algorithms.
Despite extensive published literature regarding dynamic modeling of vapor compression systems (VCS) there is distinct lack of commercial tools for realtime simulation of the complex two-phase flow dynamics of these systems. Published efforts serve as proof-of-concept that such models are possible in existing software, such as MATLAB © /Simulink © or Dymola/Modelica. However, these models currently exist only as “expert tools” and lack the refinement and robustness critical to enable adoption by the HVAC&R industry. The proposed project will leverage extensive existing code, while customizing, refining, and documenting this tool to provide the Emerson with the desired software capabilities.

Past Projects

National Science Foundation Career Award

Students: Shuangshuang Liang, Matthew Elliot

This project proposes to apply a novel dynamic modeling paradigm to Vapor Compression Cycle (VCC) systems, while developing advanced model based control and diagnostic algorithms appropriate to the nonlinear, coupled dynamics of these systems. Particular attention will be given to transcritical CO2 based systems that are an attractive alternative to current air conditioning and refrigeration systems due to lower environmental impact. Nonlinear control strategies are proposed to maximize system efficiency while simultaneously satisfying changing demands for cooling capacity. Additionally, diagnostic algorithms will be employed to identify soft system faults that precede catastrophic system failure. The proposed work has the potential for dramatic economic and environmental improvements by significantly reducing energy usage, component failure, and the negative impacts of Hydrofluorocarbon (HFC) refrigerants in terms of global warming.
The project leverages the development of a relative breakthrough in control-oriented modeling of vapor compression systems, which has been recently developed by the PI and his colleagues with close industrial collaboration. This dynamic modeling approach identifies and explains the transient system cycle phenomena as well as possible paths to system instability. The novel modeling technique gives a low order dynamic model of a typical cycle that still retains physical system characteristics so as to be transparent to system changes such as sizing, configuration (e.g. μ-channel), or material of heat exchanger. This approach contrasts with other black box modeling techniques and enables the development of model-based controllers that are more universal, adaptable, and robust to changes in environmental conditions. This modeling paradigm will be applied to both subcritical and transcritical air conditioning systems for the purpose of developing model-based control and diagnostic algorithms. Previously, a software library for modeling simple vapor compression cycles, known as Thermosys TM , was developed by the PI sponsored by a consortium of industrial companies. The proposed project will leverage this work to provide a virtual environment for initial testing of control concepts. Experimental tests will complement the simulation studies in the evaluation of the proposed approaches.

Dynamic Model Development of a Ground Combat Vehicle Environmental Control Systems (Marvin Land Systems)

Students: Erik Rodriguez, Rohit Chintala

The primary focus of this project is the development and customization of dynamic component models for the VCSU and AHU designed by MLS. The VCSU simulation model will include compressor and motor assembly, condenser, receiver, chiller and thermal expansion valves and associated piping. The VCSU model will be capable of predicting transient response of the VCSU to variations in cooling load and outdoor ambient conditions (air temperature and
flow rates). Moreover, the VCSU model will predict the system response to changes in compressor speed to permit evaluation of speed control strategies. Similar efforts will be made to model the AHU, which will include the heat exchanger, heater, fan and motor assembly. The AHU model will be able to predict the transient response for both heating mode and cooling modes.