Energy Management Systems

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The following ARG students are currently conducting research in the field of energy system modeling and control.

Justin Koeln: Dynamic Modeling and Model-based Control of Electro-Thermal Systems
Thermal energy systems are becoming increasingly important to the advancement of technology.  This is largely due to the rapid advancement and miniaturization of electrical system whose inefficiency can generate significant amounts of heat.  Managing this heat effectively is crucial to the performance of electro-thermal systems ranging from advanced aircraft to consumer electronics.  My current research focuses on improving the power density of thermal management systems through model-based control of these systems, without changes to the physical system itself.  This goal is to be achieved using a multi-level hierarchical control framework with varying degrees of system dynamics knowledge used at each level, capable of preparing the system for upcoming thermal loads and routing heat through the system more efficiently.

Donald Docimo: Modeling and Control of Energy Systems
The improved understanding and control of coupled thermal and electrical subsystems is a rising challenge associated with electric vehicles and other applications. My current research addresses this issue by extending hierarchical energy management strategies and validating their effectiveness through developed testbeds. In addition, I am leveraging my battery pack modeling and control experience to assist incorporating such devices into ARG tools.
Herschel Pangborn: Dynamic Modeling and Control of Energy Systems
Optimizing the performance, efficiency, and safety of energy systems is a critical research area. Improvements in energy management are needed for both stationary systems (e.g. air conditioning and refrigeration) and vehicle systems (e.g. high performance aircraft). My research spans a number of challenges associated with the control of energy systems.  For vehicle systems, I work to develop modeling frameworks that capture multi-domain and multi-timescale interactions. By embedding these models into model predictive controllers (MPC), we can utilize preview of upcoming loads and disturbances to improve energy management for these systems as compared to traditional approaches. Ongoing work includes the development of model-based hierarchical controllers that leverage knowledge of system interconnections to robustly optimize system-wide performance and efficiency. For air conditioning and refrigeration systems, I work to better understand and control the complex dynamics of multi-phase heat exchangers. These systems can be captured in modeling by treating them as a collection of distinct operating modes, each with its own model formulation. Controllers for these systems can also benefit from a switched framework, allowing for the development of model-based control laws for each mode.
Pamela Tannous: Electrical Thermal Power Systems
headshot My current research is sensors placement and optimization. High temperature has negative effects on the lifetime and the efficiency of electronic components. This research objective is to decide on the minimum number and placement of temperature sensors needed in order to estimate the temperature distribution of an inverter so that the highest temperature of the board can be maintained below a certain specific temperature.

Malia Kawamura: Information-Driven Energy Systems
Kawamura_headshotWith the rapid development of many new energy related technologies, there is a need for a quicker way to test novel ideas and system designs without building large physical plants. For instance, solar farms, wind farms, chemical plants, vehicle platforms, and other complex machines are expensive, energy consuming, and slow to build. Ideally, these information-driven energy systems could be modeled, simulated, and optimized with a hardware-in-the-loop (HIL) implementation prior to full-scale construction. To demonstrate the effectiveness and broad applicability of the developed methodology, I will develop a dynamic model and test control algorithms using HIL for a chemical process system.

Oyuna Angatkina: Thermosys Improvements
headshotMy current research is about making Thermosys more user-friendly. In the Fall semester I worked on the thermostatic expansion valve model to better align the model parameters with information available on manufacturer data sheets.

Sarah Garrow: Electro-Thermal Power Systems
headshot My research focus is on developing modular and scalable models of electrical and thermal subsystems of a Battery Electric Vehicle (BEV). I have developed dynamic vapor compression system (VCS) components for transcritical cycles that were released to the Thermosys toolbox using finite volume (FV) method and conservation equations. I am developing a system model for a BEV with a transcritical vapor compression system, cabin, and battery pack subsystem models. This research also includes designing a control architecture for the thermal management of the cabin and battery pack via the control inputs of the mobile VCS such as compressor and evaporator fan speed and electronic expansion valve (EEV) opening. The model based control will use an objective function that will weight the constraints of the battery pack and the bounds of the cabin temperature for human comfort while minimizing power consumption.

Sunny Sharma: Energy Optimization of Battery Powered HVAC Systems
headshot My research will be centered on the energy optimization of battery powered HVAC systems.

Christopher Aksland: Electro-Thermal Power Systems
My research focuses on the modeling of electro-thermal systems and components such as batteries and battery packs. The performance of batteries is closely related to their operating temperature; if a battery is to hot, its lifetime degrades. By modeling these components and integrating them with HVAC components, we can better understand and control a variety of power systems, such as those that exist in HEVs.