**5. Conclusions**

In this research work, a field study was carried out on the cooling energy performance of an existing, operating ventilation system under the operation of an air-to-air rotary heat wheel and direct expansion cooling coil, connected to a variable refrigerant volume outdoor unit. The major findings obtained from the study can be summarized as follows:

1. The operation of the heat wheel has a significant cooling energy saving impact on the electric energy consumption of the outdoor unit. Comparing the measured ventilation system with an air handling unit without a heat wheel operation, the cooling energy consumption is 25.1% higher;

2. Based on the measurements, the real sensible effectiveness and the CO2 cross-contamination of the heat wheel are not in accordance with the design assumptions for the cooling period;

3. The sensible effectiveness of the heat wheel performed 4.7% higher than the data (74.9%) given in the technical data book of the producer;

4. Having completed the measurements for the whole cooling period, the amount of CO2 cross-contamination in the heat wheel was much higher (with 16.4% relative average and 30.1% maximum values) than predicted during the designing phase.

Future work will focus on heating and annual energy performance investigations by conducting further field studies on the system. Moreover, simulation model development will also be considered for an annual energy consumption investigation of the existing ventilation system and model validation is planned based on data given by an annual field study. The long-term goal is to develop a simulation model which is suitable for determination of the energy consumption of ventilation systems in the design phase with a high accuracy.

**Funding:** The sensors, instruments, and transducers were financially supported and installed, and BMS software for data recording was made for this research work, by the national Intherm Ltd. In addition, the research project was financially supported by the National Research, Development and Innovation O ffice from the NRDI Fund [grant number: NKFIH PD\_18 127907], the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, Budapest, Hungary. Moreover, the research reported in this paper has been supported by the National Research, Development and Innovation Fund (TUDFO/51757/2019-ITM, Thematic Excellence Program), as well as the Higher Education Excellence Program of the Ministry of Human Capacities in the frame of Artificial Intelligence research area of Budapest University of Technology and Economics (BME FIKP-MI).

**Acknowledgments:** The author wishes to thank Árpá<sup>d</sup> Nagy and Gyula Szabó from the group of Intherm Ltd., as well as Balázs Zuggó and Noémi Bálint from the group of Daikin Hungary Ltd., for providing their professional technical and practical knowledge for the research background of this research. Moreover, special thanks go to Laith Al-Hyari for his contribution in simple data saving.

**Conflicts of Interest:** The author declares no conflicts of interest.
