https://doi.org/10.5207/JIEIE.2026.40.2.71

Dain An ; An-Seop Choi

In this study, an Internet of Things (IoT)-based smart lighting control system is proposed in which user involvement is minimized while the most suitable lighting conditions for dining situations are provided. In dining spaces, lighting is regarded as a critical factor not only in the provision of visual brightness but also in the creation of the atmosphere. It has been demonstrated in previous studies that the perceived surface color of foods can be changed according to the light sources, which directly influences freshness perception and appetite. Accordingly, tailoring lighting conditions to individual food types can accentuate the intrinsic colors of ingredients, thereby improving the visual quality of the dining environment and contributing to enhanced user satisfaction. However, manual lighting control during dining may hinder user engagement, as the cognitive and behavioral effort associated with adjusting the lighting is often perceived as inconvenient, which may lead users to refrain from modifying the lighting environment. With the advancement of artificial intelligence (AI), IoT, and smart lighting technologies, new possibilities have been introduced to overcome this limitation. The system is designed to extend beyond simple convenience, and a personalized dining experience tailored to the user’s contextual needs is offered.

https://doi.org/10.5207/JIEIE.2026.40.2.79

Kun-Han Choi ; Won-Kuk Son ; Uh-Chan Ryu

This study presents a design and onboard demonstration of a 5kW marine energy storage system (ESS) using repurposed electric vehicle (EV) batteries to replace conventional diesel generators on small vessels. The proposed system consists of three 2.4kWh EV battery modules connected in series, providing a total storage capacity of 7.2kWh, and a pure sine-wave inverter delivering a rated AC output of 5kW at 220V and 60Hz. The ESS can be charged from shore power and is designed to be expandable to include photovoltaic charging sources. A battery management system (BMS) continuously monitors key parameters such as state of charge (SOC), state of health (SOH), and state of energy (SOE), ensuring safe operation by protecting against overcharge, overdischarge, overcurrent, and cell imbalance. Field tests conducted on a coastal working vessel under realistic operating conditions showed that the system can supply combined lighting and HVAC loads for approximately 2.6h while maintaining the battery temperature below 47°C and output voltage variation within ±2%. Compared with the previously implemented 3kW or 7kW system, the 5kW ESS provides a balanced trade-off between endurance time, installation space, and cost, making it suitable as a standard rating for small and medium-sized ships. The results confirm that the proposed system can effectively replace diesel generators during berthing and low-speed operations and can contribute to greenhouse gas reduction and noise abatement in port areas.

https://doi.org/10.5207/JIEIE.2026.40.2.85

Yun-Jin Lee ; Kyo-Beum Lee

This paper presents a comparison of RLC and LC filters for overvoltage suppression in SiC inverter systems with long cables. SiC-based inverter systems enable high power density due to their fast switching characteristics; however, when long motor cables are employed, voltage reflection phenomena may give rise to overvoltage issues. Such overvoltage may accelerate insulation degradation at the motor terminals and adversely affect overall system reliability, thus necessitating effective mitigation measures. The overvoltage characteristics of SiC inverter systems with long cables are investigated, and the mitigation performance of LC and RLC output filters is comparatively evaluated. Cable modeling is carried out and utilized in the filter design process to account for the high-frequency behavior of long cables. The RLC filter incorporating damping elements is shown to be effective in suppressing oscillatory overvoltage components. The validity of the filter design to suppress overvoltage by reducing a dv/dt is verified through simulation results.

https://doi.org/10.5207/JIEIE.2026.40.2.96

Geun-Soo Kim ; Kyung-Ho Noh

The adoption of AI-based autonomous control technologies in Building Energy Management Systems (BEMS) is accelerating to achieve carbon neutrality in the building sector. However, existing international Measurement and Verification(M&V) protocols, which rely on static baselines, have limitations in accurately evaluating the dynamic control characteristics of AI and the intermittent contributions of renewable energy. Furthermore, the lack of standards for quantitatively judging the intelligence level of systems makes objective evaluation of the technology difficult. Therefore, this study proposes an integrated calculation model that links energy savings and carbon emission reductions into a single formula and introduces a Renewable Energy Alternative Supply Reflection Coefficient(fr) to prevent double counting. In addition, to evaluate the technical sophistication of AI systems, this study redefines the concept of NIST’s ALFUS(Autonomy Levels for Unmanned Systems) optimized for the building control environment. By presenting detailed score distribution criteria(0-10 points) for three core axes(Human Independence, Mission Complexity, and Environmental Difficulty), this study establishes a framework to quantitatively verify the performance of AI BEMS.

https://doi.org/10.5207/JIEIE.2026.40.2.104

Pyeong-Kang Kim ; Seung-Ho Song

This paper proposes a method for estimating the output voltage and current of a series resonant converter (DCM-SRC) operating in discontinuous conduction mode (DCM) for high-voltage applications, considering parasitic components. Cathode power supplies used in high-voltage systems have output terminals that float at high voltage potentials of several tens of kV without ground connection, and thus utilize double-insulated transformers for high-voltage isolation. In this case, the parasitic capacitance between the transformer windings appears large, and error correction for this is required during indirect measurement and output estimation. To solve these problems, this paper proposes an output estimation method that minimizes the error caused by the parasitic capacitance of a cathode power supply. A DCM-SRC with current source output was used as a cathode power supply, and an output estimation equation was derived based on an operation mode analysis considering parasitic components to minimize the estimation error. To validate the output estimation equation, a cathode power supply with a rated output of 20 V and 20 A was designed. The proposed estimation equation was validated through simulations. The proposed estimation method achieved an average error rate of 0.36% for voltage estimation and 0.74% for current estimation under various output conditions. This validates the validity of the proposed estimation method.

https://doi.org/10.5207/JIEIE.2026.40.2.110

Won-Young Jo ; Yun-Hyun Cho

The EGR system is a critical solution for NOx emissions in marine diesel engines. A key component of this system is the driving motor for the EGR blower, which must satisfy demanding operational requirements, including enhanced efficiency, improved rotor shaft stability during high-speed operation, and strict saturation temperature limits. In this study, a high-speed IPMSM utilizing SmCo permanent magnets is proposed to achieve high efficiency and a compact, lightweight design. The proposed IPMSM is designed with rated speed of 9,000rpm, max speed of 12,500rpm, and rated output-power of 150kW. The electromagnetic characteristics were analyzed using the FEM. To validate the design, a prototype IPMSM was fabricated and integrated into an EGR blower system. Finally, the performance characteristics were evaluated and discussed in relation to key electrical and mechanical design parameters.

https://doi.org/10.5207/JIEIE.2026.40.2.119

Dong Sang Yoo

This paper proposes an optimal controller design to enhance the upright balancing and driving performance of a two-wheeled robot. The control system for the two-wheeled robot is based on the Linear Quadratic Regulator (LQR) technique. To determine the optimal control gain by tuning the weighting matrices, the Bacterial Foraging Optimization Algorithm (BFOA) and the hybrid BFOA-PSO (Particle Swarm Optimization) algorithm were implemented. Control performance was quantitatively evaluated using a fitness function that integrates the Integral of Time-weighted Absolute Error (ITAE) index with control input weighting. To verify the practical effectiveness of the proposed controller, a 3D model was established by interfacing SolidWorks CAD data with the Simscape Multibody environment. The results demonstrate that the BFOA-based optimization technique is effective in deriving robust control parameters for the robot. While the hybrid algorithm exhibited slightly superior performance under specific operating conditions, it was observed that the relative superiority among the algorithms varies depending on the initial parameter configurations and environmental factors.

https://doi.org/10.5207/JIEIE.2026.40.2.126

Jaesang Kim ; Bonhyuk Ku ; Yechan Kim ; Hyoungku Kang

In this study, the applicability of a PTFE (Polytetrafluoroethylene) spray-coated insulation layer for high-temperature superconducting (HTS) coils used in medical particle accelerator systems was experimentally investigated. Prior to coil fabrication, the fundamental reliability and insulation characteristics of the PTFE coating were systematically evaluated. PTFE coatings were applied to REBCO (Rare-Earth Barium Copper Oxide) tapes and STS 304-based specimens, and mechanical stability was examined through bending and folding tests, while thermal reliability was assessed under repeated cooling?heating cycles between room temperature (293 K) and liquid nitrogen temperature (77 K). Electrical insulation performance was evaluated through dielectric breakdown tests using sphere?plane and turn-to-turn electrode configurations, and the breakdown voltage corresponding to a 63.2% probability was obtained via Weibull analysis. In addition, the effect of the coating process on superconducting performance was examined by measuring the critical current of REBCO tapes before and after coating at liquid nitrogen temperature. The results showed that the PTFE coating maintained mechanical and thermal stability without noticeable degradation, exhibited increased dielectric strength with increasing coating cycles, and caused no significant change in critical current (Ic). These results indicate that PTFE spray coating is a promising insulation approach for HTS coils in medical accelerator applications.

https://doi.org/10.5207/JIEIE.2026.40.2.132

Seung-Dong Shin

With the rapid advancement of vehicle electrification and the increasing integration of electronic systems, electromagnetic interference (EMI) has emerged as a critical issue affecting the reliability and safety of automotive electronics. In hybrid vehicles, low-voltage auxiliary batteries supply stable power to electronic control units and onboard electrical systems, requiring battery cases that simultaneously provide effective EMI shielding, high mechanical strength, lightweight characteristics, and good processability. In this study, Nylon 6 (polyamide 6)-based carbon nanocomposites were developed as lightweight EMI-shielding materials to replace conventional aluminum auxiliary battery cases. Multi-walled carbon nanotubes (MWCNTs), carbon black (CB), and graphene nanoplatelets (GNPs) were incorporated with a total filler loading of 10phr, and the effects of filler composition and dispersion on the electrical, mechanical, rheological, and thermal properties of the composites were systematically investigated. The optimized nanocomposite exhibited a surface resistivity of 10³?10⁴Ω/□ and a tensile strength exceeding 70MPa while maintaining shear-thinning behavior suitable for injection molding. Furthermore, a prototype battery case fabricated using the optimized composite achieved more than 54% weight reduction compared with conventional aluminum cases while satisfying automotive environmental and durability requirements. These results demonstrate the strong potential of polymer-based carbon nanocomposites for lightweight EMI shielding applications in automotive battery systems.

https://doi.org/10.5207/JIEIE.2026.40.2.138

Young-Hye Choi

This study evaluates the performance and economic feasibility of a self-consumption photovoltaic (PV) system installed at a vocational training institution under an industrial electricity tariff. The PV system was designed with a capacity of approximately 40kWp based on the available rooftop area and the facility’s load characteristics. Annual energy production was estimated using PVsyst simulation, and the results were compared with actual electricity consumption data to assess the potential for self-consumption. Economic feasibility was analyzed for both self-consumption and power purchase agreement (PPA) models using net present value (NPV), internal rate of return (IRR), payback period, and levelized cost of electricity (LCOE). In addition, sensitivity analysis was conducted considering variations in electricity price, discount rate, and self-consumption ratio. The analysis period was set to 20 and 25 years to evaluate long-term economic performance. The results show that the self-consumption PV system can significantly reduce electricity costs and provide stable economic benefits due to its independence from electricity sales conditions. Although the PPA model may yield higher profitability under ideal conditions without curtailment, its economic performance is highly sensitive to grid constraints and electricity pricing. Therefore, for facilities with high daytime electricity demand, such as vocational training institutions, the self-consumption PV system is considered a practical and reliable option for reducing energy costs and enhancing energy independence.

https://doi.org/10.5207/JIEIE.2026.40.2.148

Min Hyeok Kang ; Sun Jae Kim ; Seung-Woo Woo ; Hong-Keun Ji ; Eel-Hwan Kim

Series arc faults from partial disconnections are a major cause of electrical fires, yet extremely difficult to detect as their currents resemble normal loads. Under non-linear loads like Switched-Mode Power Supplies (SMPS), massive switching pulses mask high-frequency arc signals, causing critical Arc Fault Circuit Interrupter (AFCI) nuisance tripping. This paper proposes a Discrete Wavelet Transform (DWT)-based multi-resolution analysis to accurately detect series arcs under these complex conditions. To secure highly realistic simulation data, a 'Stochastic Modified Cassie Model' reflecting the physical intermittency of arc plasma was established. While conventional Fast Fourier Transform (FFT) failed due to SMPS harmonic masking and a lack of time-localization, the proposed DWT method successfully filtered the 15A-class SMPS pulses and 60Hz fundamental wave into the approximation coefficients. Consequently, it precisely isolated the asymmetrical, random high-frequency arc signals exclusively within the detail coefficient bands. This study mathematically proves that the DWT algorithm reliably diagnoses series arcs in non-linear environments, providing fundamental data for designing future intelligent fire prevention systems and mitigating AFCI nuisance tripping.