One of the most practical and impactful areas of MATLAB and Simulink application lies in HVAC (Heating, Ventilation, and Air Conditioning) system design. This blog explores a detailed HVAC simulation project developed using Simulink® and Simscape™, modeling an advanced HVAC setup for a 4-room apartment. The focus is on achieving high indoor comfort and air quality while maintaining energy efficiency—a central goal for engineers designing smart and sustainable homes.
This project is based on a real-world case, modeling a typical mid-floor apartment in Germany for a family of four. It incorporates real weather data, thermodynamic system models, airflow control, humidity regulation, and CO₂ monitoring. The design employs a hybrid control strategy with PI control, Stateflow®, and lookup tables to maintain comfortable living conditions. Whether you're exploring sustainable solutions or seeking help with MATLAB assignment tasks related to HVAC modeling, this example provides valuable insights into the simulation methodology, modeling approach, and performance results.
Introduction and Motivation
Modern building design goes far beyond aesthetics. With sustainability being a global priority, residential HVAC systems must now fulfill more stringent requirements—providing heating, cooling, and ventilation efficiently, while maintaining indoor air quality and minimizing environmental impact.
This project was driven by a simple but powerful objective: to simulate a smart HVAC system capable of optimizing energy consumption and indoor conditions for a typical family apartment. Modeling and simulation were central tools used to achieve this objective, as they allow engineers to explore complex thermodynamic systems and test control algorithms before physical deployment.
Germany, the contextual focus of the simulation, has been actively pursuing dual strategies since 2020: increasing renewable energy usage and enhancing energy efficiency in residential buildings. Policies like the Renewable Energy Sources Act and Energy Saving Ordinance further motivate engineers and researchers to explore innovative, eco-friendly HVAC technologies that balance comfort with sustainability. This HVAC project aligns directly with these efforts, offering a model that other countries can also adapt.
Simulation Framework
Understanding the Apartment Setting
In Germany, multi-family apartment buildings (Mehrfamilienhäuser) are a common type of housing, especially in urban areas. These apartment blocks typically house multiple families and feature a mix of 3- and 4-room apartments.
For the simulation, a 3-room apartment with a living area of 108.8 m² was chosen, located on a middle floor. This added complexity to the thermal simulation because of heat exchange with apartments both above and below. The household includes two adults and two children, with distinct daily routines affecting room usage patterns. Climate control was applied to the bedrooms and living room, while airflow followed a path from fresh-air intake in living areas and bedrooms, exiting through the kitchen and bathroom.
To add realism, the simulation integrated actual meteorological data from the German Weather Service. Simplifying assumptions included:
- Constant air density at 20°C
- No furniture, open windows, or closed doors
- Uniform airflow distribution
These assumptions allowed focus on key HVAC dynamics without overwhelming the system with granular details.
Simulink-Based Thermodynamic Model
The core of the apartment simulation was developed using Simulink® and Simscape™. Thermodynamic modeling included each room’s thermal mass, wall insulation, window properties, and interactions between adjacent rooms. Moist air and thermal domains were used to represent airflow and heat transfer accurately.
The system inputs included:
- Outside temperature (T_OUT)
- Initial room temperature (T_ENV)
Each room was linked using Simscape thermal resistances and masses, enabling simulation of heat transfer across walls, windows, and floors. Moist air was modeled based on room occupants, who contributed to humidity and CO₂ levels depending on their presence in a specific room. Human heat dissipation was also factored into the heat load.
Control-Oriented HVAC System Modeling
To ensure optimal indoor conditions, a control strategy was designed combining:
- PI controllers for temperature regulation
- Stateflow® logic for safety and airflow switching
- Lookup tables for humidity-based decisions
The system was configured to maintain:
- Temperature: 16°C to 24.5°C
- Humidity: 20% to 82%
- CO₂: Below 2000 ppm
Manipulated variables included:
- Heating power
- Cooling power
- Airflow rate
The PI controller was tuned using MATLAB’s Control System Toolbox™. The tuning prioritized a fast but stable response to temperature changes. Air handling was managed by Stateflow® and lookup tables, deactivating HVAC elements when the air properties deviated from comfort thresholds. Safety logic shut off air conditioning if indoor humidity exceeded 85%.
Lookup Table Configuration
A lookup table was created using comfort zone data based on human thermal comfort studies. This table mapped outdoor temperature and humidity to operational conditions of the air handling unit. When environmental variables were outside the comfort range, the system would deactivate to prevent unfavorable indoor humidity shifts. Stateflow® logic added robustness by applying hard limits on indoor humidity, effectively overriding the main control logic when needed.
Simulation Results
The system was tested under extreme weather conditions, including the hottest recorded day in Cologne, Germany, in 2023. Here are the key results:
- Temperature: The PI controller maintained room temperatures near the 20°C setpoint in all three climatized rooms, with brief deviations when humidity exceeded acceptable levels and the controller was temporarily disabled.
- Humidity: All rooms remained within the comfort humidity range, only reaching the 85% threshold in peak humidity moments. The safety mechanism kicked in when required.
- Air Quality: CO₂ levels were maintained well below the 2000 ppm limit for the majority of the simulation.
The model demonstrated the feasibility of integrating a smart HVAC system in a typical apartment. It also proved the efficacy of combining multiple MATLAB tools—Simscape™, Stateflow®, and Control System Toolbox™—to manage complex control tasks in a residential environment.
Insights from the Project
Importance of Integrated Modeling
This project shows that successful HVAC system modeling requires coupling multiple physical domains—thermal, airflow, and control. Simscape™ allowed for easy integration of these domains, providing a powerful toolset for building engineers and system designers.
Flexibility through MATLAB Toolboxes
The ability to switch between simulation, control design, and logic management within MATLAB made it possible to design a fully functioning system with robust controls. The use of lookup tables and Stateflow® added advanced logic handling to a relatively simple simulation structure.
Designing for Energy Efficiency
The real-world value of this project lies in its energy-conscious design. Rather than running HVAC components continuously, the control logic adapts to current indoor and outdoor conditions, saving energy while maximizing comfort. This reflects how HVAC systems should function in modern, eco-conscious construction.
Tailoring for Local Needs
Modeling the German apartment ensured cultural and environmental realism. Climate conditions, construction norms, and lifestyle patterns vary across regions, and effective HVAC systems must be localized. This methodology can easily be replicated for different countries using their own housing data and weather conditions.
Conclusion
Modeling and simulation of HVAC systems in MATLAB offer students and professionals a powerful platform to understand, optimize, and design real-world systems. This project, which modeled an intelligent HVAC setup for a German apartment, showcases how modern tools like Simulink®, Simscape™, and Stateflow® can help balance indoor comfort and environmental responsibility.
From integrating real-world weather data to fine-tuning control parameters and enforcing safety limits, this project demonstrates what’s possible when engineering principles and sustainability goals converge. The developed system ensured optimal temperature, humidity, and air quality for residents—all within an energy-efficient framework.
Engineers around the world can learn from this example and apply similar simulation-based design strategies in their own HVAC challenges. With MATLAB and Simulink, it’s easier than ever to prototype, analyze, and deploy innovative control systems that serve both people and the planet.