In electrified vehicles, effective battery thermal management and heating performance under cold ambient conditions are critical for driving efficiency and system reliability. Accordingly, a detailed understanding of the operating characteristics of heat pump systems integrated into vehicle thermal management architectures is required. In this study, the operational behaviors of a heat pump system for a hybrid electric vehicle were experimentally investigated under battery heating mode and mixed mode with varying compressor speeds. The results indicate that the compressor suction pressure exhibited relatively stable behavior regardless of operating mode, while the discharge pressure and refrigerant mass flow rate showed distinct trends depending on the selected mode. In particular, the mixed mode enhanced heat transfer characteristics at the CHX, leading to simultaneous improvements in heating capacity and energy efficiency at the same compressor speed. Furthermore, considering both heating performance and energy efficiency, 1600 rpm was identified as the optimal compressor operating speed. The findings of this study provide valuable insights for developing operating strategies and control algorithms for thermal management systems in electrified vehicles.

With increasingly stringent zero-energy building (ZEB) requirements and growing interest in mid-rise timber buildings as low-carbon building systems, reducing the renewable energy capacity required for ZEB implementation has become an important design issue. Mid-rise timber buildings can contribute to embodied carbon reduction through long-term carbon storage, but their structural load limits, roof area, and façade design constraints can restrict the installation capacity of renewable energy systems. Therefore, improving the operational efficiency of HVAC systems is essential for achieving ZEB targets under constrained renewable energy installation conditions. This study evaluates the energy and economic impacts of Fuzzy Inference control applied to a PVT-GHX multi-heat-source heat pump system for a mid-rise timber building. A TRNSYS model of the baseline PVT-GHX system, validated against field-test data from a commercial building in Cheongju for heat pump load and system electricity use, was used as the base simulation model. The validated baseline model was then extended to the target mid-rise timber building, and annual simulations were conducted using standardized meteorological data for the Daejeon region. Rule-base control and Fuzzy Inference control were compared in terms of annual energy use, net energy use after PVT electricity generation, additional PV panel requirements for ZEB achievement, and initial capital cost. The results showed that Fuzzy Inference control reduced heat pump electricity consumption by 35.2% and net energy use by 53.7%, corresponding to 19,535.3 kWh per year, compared with Rule-base control. This reduction was mainly attributed to the ability of Fuzzy Inference control to modulate heat pump output across five discrete levels according to thermal demand, particularly because 52.2% of operating hours occurred in the part-load ratio range of 0.2 to 0.7. The number of additional 400 W PV panels required to achieve the ZEB target decreased from 89 under Rule-base control to 48 under Fuzzy Inference control, representing a 46.1% reduction. Consequently, the initial capital cost decreased by $16,336 despite the additional cost of variable-output control components. These findings demonstrate that control strategy improvement can reduce both renewable energy system capacity and initial investment for ZEB implementation in mid-rise timber buildings where renewable energy installation is constrained.

Uzbekistan, located in the hot-dry climate of Central Asia, currently rates room air conditioners based on EER measured under fixed rating conditions, which may not reflect actual seasonal cooling demand. This study reviews international seasonal efficiency indicators (SEER, APF) as institutional background and focuses on computing CSPF under Uzbekistan climate conditions to investigate the applicability of a climate-based seasonal efficiency rating system. EnergyPlus weather data (EPW) for six representative cities (Tashkent, Samarkand, Bukhara, Fergana, Namangan, and Andijan) were used to derive climate-based BIN fractions, which were compared with the ISO 16358-1 standard BIN distribution. ISO 5151 calorimeter test data of a 3.0 kW wall-mounted inverter AC unit were combined with both BIN fractions to compute CSPF. The results revealed that the ISO 16358-1 standard BIN concentrates between 24-27℃, whereas the Uzbekistan climate-based BIN shows substantial occurrence frequencies above 31℃, with cooling hours persisting even at 35-38℃ in Tashkent and Bukhara. The seasonal cooling load and electricity consumption derived from the local-climate BIN were approximately 1.94 times higher than those derived from the ISO standard BIN (3,213 vs 1,654 kWh; 719 vs 370 kWh, respectively), while the resulting CSPF values were nearly identical (4.470 vs 4.472). For the tested 3.0 kW inverter-type unit, the calculated CSPF was nearly unchanged despite substantial increases in seasonal cooling load and electricity consumption. This finding suggests that, at least for this product class, an absolute-consumption-based or climate-weighted indicator may be necessary to complement CSPF in capturing the true energy performance under Central Asian hot-dry climate conditions.