HVAC & Thermal Energy Systems
Heat pumps, vapor-compression systems, water heating, thermal storage, and integrated thermal systems.
Modeling · Control · Optimization · Experimentation
Intelligence for efficient, flexible, and resilient energy systems.
ESIL develops modeling, control, optimization, diagnostics, and experimental methods for HVAC and thermal energy systems, with emphasis on efficiency, demand flexibility, reliability, and real-world implementation.
Led by Junke Wang, Ph.D. · Assistant Professor, School of Aerospace and Mechanical Engineering
Mission
Engineering intelligence that works in real energy systems.
We study how thermal systems behave, how they can be modeled and diagnosed, and how advanced control can make them more efficient and grid-responsive without sacrificing comfort, reliability, or practical implementability.
Selected publication venues
Applied EnergyEnergy and BuildingsBuilding and EnvironmentScience and Technology for the Built EnvironmentASHRAE Transactions
Research
Six connected research thrusts
The lab spans physical energy systems, intelligence and control, and experimental verification rather than treating modeling, algorithms, and hardware as separate activities.
Advanced Control & Optimization
Model predictive control, supervisory control, real-time optimization, and autonomous operation.
Grid-Interactive Buildings
Demand flexibility, load shifting, building-grid integration, and coordinated operation of flexible assets.
Fault Diagnostics
Fault detection, diagnosis, virtual sensing, performance degradation detection, and automated correction.
Modeling & AI
Physics-based, reduced-order, data-driven, hybrid, and AI-enabled models for prediction and decisions.
Experimental Validation
Controlled-environment testing, instrumentation, controller validation, and field demonstration.
Research directions
Where we are focusing now
ESIL is building depth in a small number of broad, connected themes that link physical energy systems, intelligent decision-making, flexibility, resilience, and experimental evidence.
Intelligent systems
Adaptive thermal energy systems
Develop models, sensing, and control methods that help HVAC, heat-pump, storage, and coupled thermal systems adapt to changing weather, loads, equipment conditions, and operating objectives.
Autonomy
Safe, resilient, and self-correcting control
Advance predictive, learning, and fault-tolerant control strategies that operate under uncertainty while respecting comfort, equipment, reliability, and safety constraints.
Flexibility
Integrated energy flexibility and building-grid interaction
Coordinate buildings, thermal storage, controllable loads, and distributed energy resources to provide flexible operation across multiple timescales without compromising core building services.
Discovery
Experimentally grounded energy-system intelligence
Use controlled experiments, high-resolution sensing, integrated testbeds, and field data to identify system behavior, validate algorithms, and accelerate learning from real energy systems.
Selected publications
Recent work
Representative peer-reviewed work that reflects the lab's core technical directions.
Building and Environment · 2025
Automated calibration of coupled residential building and HVAC models
RC modeling and genetic-algorithm optimization for efficient model calibration.
Energy and Buildings · 2024
Modeling variable refrigerant flow systems in building applications
A comprehensive review of VRF modeling approaches for building energy applications.
Applied Energy · 2022
Precooling optimization for residential buildings
Control-oriented analysis of thermal storage in buildings for load flexibility.
News
Latest
ESIL is recruiting Ph.D. students year-round in 2027. Prospective students with interests in HVAC/heat pumps, controls, optimization, diagnostics, modeling/AI, or experimental energy systems are encouraged to review the Join Us page.
ESIL established at the University of Oklahoma. Junke Wang joined OU's School of Aerospace and Mechanical Engineering as an Assistant Professor.
New paper in Building and Environment. Automated calibration of coupled residential building and HVAC models using RC models and genetic-algorithm optimization.
Opportunities
Interested in intelligent energy systems?
Ph.D. positions are available year-round in 2027. ESIL is building a multidisciplinary team across thermal sciences, controls, optimization, data, and experimentation.