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Analytical design, modelling and simulation of an LLC resonant converter for an electric vehicle auxiliary power module

10.11591/ijpeds.v17.i3.pp1885-1901
Mohamad Affan Mohd Noh , Jacques Juicy Patureau Ravina , Sivakumar Sivanesan , Hafizul Azizi Ismail , Ali Akbar Firoozi
This paper presents an analytical design, modelling, and simulation of an LLC resonant converter for an electric vehicle auxiliary power module (APM). The work contributes a complete LLC‑focused workflow that starts from design specifications and proceeds through: i) Resonant‑tank selection using normalized gain–frequency maps to choose the inductance ratio Ln and a quality factor Qe with soft‑switching in mind; ii) Transformer sizing from core data and loss limits; and iii) Small‑signal‑based PI controller tuning those accounts for the plant’s inherent inversion. The workflow is implemented and validated in MATLAB Simulink and PLECS for input voltages of 235-265 V and load levels from 10% to 100%. The converter achieves a peak efficiency of 98.1% within an 80.6-128.3 kHz switching range, full‑load efficiency of 93.5%, and about ±1% output voltage regulation. The controller maintains stable output settling times of 0.42-0.44 ms during 100% to 80% load steps and the reverse transition. At the highest input voltage, the switching frequency drifts beyond the intended range, which indicates a clear target for controller refinement in future work. The results show that the proposed analytical workflow is practical for designing LLC converters that meet APM efficiency and regulation goals, with cross‑platform simulation providing consistent evidence of performance.
Volume: 17
Issue: 3
Page: 1885-1901
Publish at: 2026-09-01

Enhanced voltage control and load compensation for DFIG-based wind energy systems using a stator-side series converter

10.11591/ijpeds.v17.i3.pp2224-2246
Preethicaa Ramesh , Sowmmiya Uthayakumar , Tole Sutikno , Vigna Kumaran Ramachandaramurthy
The increasing deployment of doubly-fed induction generator (DFIG)-based wind energy systems (WESs) requires effective voltage regulation and power-quality enhancement under varying operating conditions. This paper proposes a coordinated voltage regulation and load-compensation technique using a rotor-side converter (RSCR) and a stator-side series converter (SSSCR). The RSCR provides two-directional slip-power control through cascaded voltage and current control loops, while the SSSCR provides series voltage injection for voltage regulation and load compensation. The proposed system is developed in MATLAB/Simulink and validated using an OPAL-RT OP4512 real-time platform under variable wind speed, unbalanced and non-linear loading, and voltage sag/swell conditions. Quantitative results show reductions in overall current total harmonic distortion (THD) of 25.34% and 36.78% under non-linear and unbalanced load conditions, respectively. The voltage regulation error is reduced from 9% to 3%, while the settling time decreases from 0.24 s to 0.12 s under non-linear loading. The proposed configuration also reduces the voltage overshoot from 2.61% to 0.02% during speed transition. These results demonstrate the effectiveness of the coordinated RSCR-SSSCR configuration for simultaneous voltage regulation and load compensation.
Volume: 17
Issue: 3
Page: 2224-2246
Publish at: 2026-09-01

To enhance efficiency in photovoltaic systems using optimization methods in battery management system

10.11591/ijape.v15.i3.pp985-994
Penumala Poornima , Kannan Boopathy
Battery management systems (BMS) have undergone significant advancements over the years, transitioning from basic control strategies to sophisticated optimization algorithms. Historically, established BMS approaches were limited in their ability to handle energy efficiently, often leading to suboptimal power utilization and higher total harmonic distortion (THD). Integration of in a BMS application in modern days. advanced algorithms, such as flying squirrel search optimization (FSSO), have been optimized using grey wolf optimizer (GWO), and artificial neural network (ANN) significantly enhanced the performance of the system. These algorithms are efficient in terms of optimizing the duty cycle, whereby there is even a healthy energy flow between renewable load requirements and power requirements. These algorithms are analyzed, and their effectiveness in comparing their effectiveness is different operational scenarios. GWO algorithm is indicated as having the best reduction of THD and consequently improving the quality of power in a minimized way reliability. The ANN shows great expertise in voltage. regulating, low level of THD. Meanwhile, the FSSO algorithm shows significant potential in improving energy efficiency and reducing operational costs, despite its higher THD levels in current phases. GWO has a minimal current THD of 4.65% in Phase 1, exceeding ANN and FSSO. ANN has a voltage THD of 10.61%. FSSO has greater current THD values over 15% and good voltage control, highlighting decisions.
Volume: 15
Issue: 3
Page: 985-994
Publish at: 2026-09-01

Techno-economic optimization of hybrid renewable energy systems for low-carbon EV charging station

10.11591/ijpeds.v17.i3.pp2039-2046
Jeyagopi Raman , Sudesh Nair Baskara , Harpreet Kaur Channi
The rapid adoption of electric vehicles (EVs) requires charging infrastructure that is sustainable, power-electronically efficient, and grid-compatible. This study presents a techno-economic and environmental optimization of a hybrid renewable energy-based EV charging station near Guru Nanak Dev Engineering College (GNDEC), Ludhiana, India, as a sustainable alternative to conventional petrol stations. Unlike studies based on assumed EV load profiles, the proposed framework integrates real-world e-rickshaw utilization data, inverter efficiency, and sensitivity analysis within a HOMER Pro optimization framework. The system combines solar photovoltaic (PV), battery storage, and grid supply through a bidirectional inverter to manage dynamic charging demand. Local solar irradiance (~5.6 kWh/m²/day) and actual e-rickshaw usage data were used as simulation inputs. Configurations were evaluated using net present cost (NPC), levelized cost of energy (LCOE), inverter efficiency, and CO₂ emissions. The optimal PV-battery-grid configuration achieved an NPC of $28,500, LCOE of $0.11/kWh, inverter efficiency of 95%, and approximately 95% lower CO₂ emissions than grid-connected configuration, with a 6.5-year payback period. The findings highlight the importance of power-electronic efficiency and energy management for economically viable, low-carbon EV charging infrastructure, supporting SDGs 7 and 9.
Volume: 17
Issue: 3
Page: 2039-2046
Publish at: 2026-09-01

Analysis a mixtures of bentonite, palm kernel shell charcoal and magnesium sulfate (MgSO4) for reducing grounding resistance using rod-type electrodes at varying soil depths

10.11591/ijape.v15.i3.pp1386-1398
Ferry Rahmat Astianta Bukit , Naemah Mubarakah , Adrian Sinaga
A grounding system is an essential electrical safety mechanism designed to protect humans and equipment from disturbances such as lightning-induced surge currents or short circuits. It operates by channeling excess current into the ground through grounding electrodes, thereby reducing the risk of damage and hazards. High grounding resistance can compromise the dissipation of fault currents and overvoltages, leading to safety risks. This study focuses on reducing grounding resistance through chemical soil treatment using bentonite combined with a mixture of magnesium sulfate (MgSO₄) and palm shell charcoal. The optimal composition consists of 10% bentonite, 10% native soil, and 80% of the material mixture. Experiments were conducted at electrode depths of 30 cm, 60 cm, 90 cm, and 110 cm. Results showed that the initial resistance of 312.5 Ω at 30 cm depth decreased to 86.1 Ω, and at 110 cm depth, resistance decreased from 186.5 Ω to 53.0 Ω. The average reduction reached 77.4%, indicating that this material combination is highly effective in lowering grounding resistance and improving system performance.
Volume: 15
Issue: 3
Page: 1386-1398
Publish at: 2026-09-01

Heuristic-based optimization for smart home energy management with renewable integration and energy storage systems

10.11591/ijpeds.v17.i3.pp1747-1754
M. J. Suganya , Y. Sukhi , J. C. Vinitha , J. Sumithra
The rapid growth of energy demand in urban areas emphasizes the necessity of efficient demand-side management (DSM) strategies in smart homes. This study presents a heuristic-based optimization framework for appliance scheduling in smart home environments that incorporates renewable and sustainable energy resources (RSERs) and energy storage systems (ESSs). The objective is to minimize the electricity cost and the peak-to-average ratio (PAR) while satisfying the user comfort constraints. Three optimization techniques, genetic algorithm (GA), binary particle swarm optimization (BPSO), and wind-driven optimization (WDO), are implemented and evaluated in three scenarios: without renewable integration, with RSERs, and with both RSERs and ESSs. Simulation results show that BPSO has the lowest electricity cost and carbon emissions, while WDO has a faster convergence speed and competitive performance in PAR reduction. RSER and ESS integration has a major positive impact on energy efficiency, grid dependence, and sustainability. The results give useful insights to choose appropriate optimization methods and contribute to the development of effective, sustainable, and user-centric smart home energy management systems.
Volume: 17
Issue: 3
Page: 1747-1754
Publish at: 2026-09-01

Sliding-mode fuzzy logic controller based direct torque control and ripple minimization of induction motors

10.11591/ijpeds.v17.i3.pp1714-1727
S. Sujitha , Hima Bindu Eluri , P. B. Savitha , S. Venkateshwarlu
Conventional direct torque control is one of the most effective strategies for managing the torque of an induction machine (DTC), which is one of the most common types of machines. Instead, the DTC's inadequate control ability is made worse at low speeds by the audible flux and torque waves that are generated by its extremely low switching frequency. This is because the DTC's switching frequency is exceedingly low. In an effort to address these concerns, a variety of direct torque control strategies focused solely on flux and torque as their primary concerns. An improvement in DTC control and the elimination of ripples in induction motors are the goals of this research, which introduces a sliding mode fuzzy logic controller technique. The complexity of the algorithm, sensitivity of the parameters, the tracking speed, the switching loss, and the ripple reduction properties of the technique will all be thoroughly investigated. Simulation of the control mechanism is performed with MATLAB/Simulink in order to verify that it functions as intended.
Volume: 17
Issue: 3
Page: 1714-1727
Publish at: 2026-09-01

Design of a novel single-source 15-level inverter with self-balancing capacitors and sensorless PWM control

10.11591/ijpeds.v17.i3.pp1950-1961
Taoufiq El Ansari , Ayoub El Gadari , Youssef Ounejjar
Multilevel inverters (MLIs) are widely used in energy-conversion systems because they generate high-quality AC voltages with reduced harmonic distortion. However, existing MLIs often require numerous power devices, multiple DC sources, voltage sensors, or dedicated capacitor-balancing controllers, which increases both hardware cost and control complexity. This paper proposes a single-phase 15-level inverter derived from the Packed U-Cell structure. It employs a single DC source, three capacitors, and a reduced number of power switches. Based on the number of power switches, gate drivers, diodes, capacitors, DC sources, output levels, and total standing voltage per unit (TSVpu), the proposed topology achieves a lower cost function than the compared topologies reported in the literature. The proposed topology achieves a relatively low total standing voltage per unit (TSVpu) of 4.43. Sensorless open-loop SPWM offers inherent capacitor-voltage self-balancing, eliminating the need for voltage sensors or additional balancing loops. MATLAB/Simulink validation at 2 kHz and a modulation index of 1 covers steady-state operation, load transients, nonlinear loading, and DC-source voltage fluctuations. For a 50 Ω–20 mH load, the current THD is 2.20% without an output filter, confirming suitability for energy-conversion systems.
Volume: 17
Issue: 3
Page: 1950-1961
Publish at: 2026-09-01

One-day analysis of natural sound via very low frequency signal from Malaysian ionosphere

10.11591/ijaas.v15.i3.pp902-910
Suryadi Suryadi , Mariyam Jamilah Homam , Rohaida Mat Akir , Mardina Abdullah
This paper presents findings on the impact of lightning discharges on very low frequency (VLF) signal, which falls from 30 Hz up to 50 kHz has been used effectively for space parameter detection of the lower ionosphere signal propagation over Malaysia. Using a VLF line receiver installed at Universiti Kebangsaan Malaysia (Latitude 2° 55' N, Longitude 101° 46' E), observations conducted on 22 July 2009 revealed distinct diurnal variations. During the daytime, broadband and narrowband data were analyzed to investigate natural radio signals from transmitters in neighboring countries such as India, Japan, China, and Australia. The results reveal significant perturbations in VLF signal propagation caused by lightning discharges, leading to the detection of natural sferics, tweeks, and ionospheric disturbances. These phenomena, originating from radiated lightning discharge activity, were found to average 44 occurrences per hour during the afternoon and evening. The study highlights how these natural electromagnetic events contribute to amplitude and phase variations in VLF signals, offering deeper insights into ionospheric interactions with lightning activity. Additionally, the findings emphasize the presence of natural radio emissions such as sferics and their components, which further illustrate the effect of lightning discharges on the lower ionosphere above Malaysia.
Volume: 15
Issue: 3
Page: 902-910
Publish at: 2026-09-01

A novel machine learning based maximum power point tracking in interleaved buck-boost converter for portable solar-powered electric vehicle charging in rural areas

10.11591/ijpeds.v17.i3.pp2247-2258
C. Niranjana , P. K. Vineeth Kumar , J. J. Jijesh , G. B. Arjun Kumar , Dileep Reddy Bolla , K. N. Sunil Kumar
Need for off-grid electric vehicle (EV) charging solutions, using intelligent control systems, such as machine learning (ML)-based maximum power point tracking (MPPT), to harness solar energy, offers a means of optimizing efficiency even in the face of fluctuations. This innovative strategy combines clean energy, cutting-edge power electronics, and practical application, which makes it perfect for fostering innovation in areas with inadequate infrastructure. For rural areas without grid infrastructure, this paper presents a novel design and performance assessment of a portable solar-powered EV charging system. To maximize solar energy harvesting and charging efficiency, the system combines an interleaved buck-boost converter with an ML-driven MPPT algorithm. It is appropriate for small electric vehicles (EVs) like auto rickshaws because it uses a 48 V lithium iron phosphate (LiFePO₄) battery. A supervised regression model trained on real-time electrical (voltage, current, and power) and environmental (temperature, irradiance) parameters is used to implement the MPPT algorithm. The system was created using MATLAB/Simulink, and the key performance parameters were evaluated using real-time information. Analyses of the key performance metrics like charging efficiency, converter stability, and tracking accuracy show a superior energy harvesting efficiency of 97%.
Volume: 17
Issue: 3
Page: 2247-2258
Publish at: 2026-09-01

Real-time selective harmonic elimination in multilevel inverters using embedded metaheuristic optimization on PYNQ-Z2

10.11591/ijpeds.v17.i3.pp1914-1925
Taha Ahmad Hussein , Dahaman Ishak
This paper offers a structured methodology for regulating optimal control switching angles in multilevel inverters to achieve selective harmonic elimination (SHE) using embedded optimization algorithms on the PYNQ‑Z2 FPGA operating base. The proposed approach employs metaheuristic techniques including particle swarm optimization (PSO), genetic algorithm (GA), gray wolf optimization (GWO), slime mould algorithm (SMA), and whale optimization algorithm (WOA) to generate candidate switching angles across a wide range of modulation indices. For each modulation index, the most effective solution towards harmonic reduction and waveform quality is selected and implemented on the FPGA controller, enabling reliable real‑time operation with very low delay. Experimental validation of a 31‑level single‑phase inverter confirms the effectiveness of the method in eliminating selected harmonics and refining the fundamental output. Combining comparative algorithmic selection with FPGA‑based control demonstrates a systematic and efficient strategy for advanced inverter systems. A MATLAB/Simulink model is constructed to represent the 31-level inverter to enhance the practical aspect and study the frequency spectrum, where many harmonics that contribute to obtaining THD within the IEEE standards are eliminated. Also, the different types of losses are calculated based on the governing mathematical rates.
Volume: 17
Issue: 3
Page: 1914-1925
Publish at: 2026-09-01

Novel improvised satin bowerbird algorithm for speed control and torque ripple minimization for switched reluctance motor

10.11591/ijpeds.v17.i3.pp1659-1674
M. Upanya , S. Rashmi
Switched reluctance motors (SRMs) have gained a lot of popularity for adjustable speed drive systems, cost-effectiveness, and simplicity. Currently, SRMs are widely used in electric vehicles, compressors, and machine tools. In the proposed work, the satin bowerbird (SBB) algorithm is improvised and implemented to determine the optimal turn-off angle (θoff), along with gain parameters for the proportional integral (PI) controller, to regulate the speed and to enhance the torque profile of the SRM. The performance of the SRM drive is tested for 4 different control schemes with different load torque and reference speed. The control schemes are a PI controller with hysteresis current control (HCC), implemented with conventional SBB and improvised SBB (ISBB). The other control scheme is a PI controller with an improved torque sharing function (TSF) and HCC, implemented with conventional SBB and improvised SBB. The TSF used in the control scheme has been improvised with adaptive smoothing and adaptive boosting functions. For the different control schemes tested, ISBB with a PI controller and improvised TSF with HCC has resulted in better speed regulation and a 50% reduction in total harmonic distortion (THD) when compared to the control scheme constituting the conventional SBB algorithm with a PI controller and HCC. The proposed work is extended with the computation of torque rising time (Tr) and torque settling time (TS).
Volume: 17
Issue: 3
Page: 1659-1674
Publish at: 2026-09-01

Mapping significant clinical factors to relapse-free survival prognosis in breast cancer patients

10.11591/ijaas.v15.i3.pp1193-1202
Boby Al Qurthuby , I Made Murwantara
This study explores the role of clinical factors in influencing relapse-free survival (RFS) in breast cancer patients through comprehensive survival analysis (SA). The data were derived from a large cohort of breast cancer patients, encompassing clinical variables such as age at diagnosis, tumor size, number of positive lymph nodes, tumor grade, histological subtype, and receipt of chemotherapy and radiotherapy. Analytical methods included Kaplan-Meier plots, log-rank tests, Cox proportional hazards modeling, and feature ranking based on univariate and multivariate log-rank and Cox tests. The results show that patients who received chemotherapy demonstrated a shorter median RFS compared to those who did not (102.7 vs. 145.0 months, p = 0.03), likely due to high-risk patients being selected for chemotherapy. Meanwhile, radiotherapy was associated with improved prognosis (hazard ratio (HR) < 1 in Cox model, p < 10−5), in line with meta-analyses showing reduced breast cancer mortality post-radiotherapy. The contribution maps the key clinical determinants of RFS in breast cancer and highlights the practicality of performing SA.
Volume: 15
Issue: 3
Page: 1193-1202
Publish at: 2026-09-01

Cost-effective and emission-aware dispatch strategy for a smart EV charging parking lot

10.11591/ijpeds.v17.i3.pp1591-1600
O. K. Rajesh , N. Shanmugasundaram , V. Rajendran
The growing adoption of electric vehicles (EVs) necessitates intelligent charging strategies to alleviate grid congestion and control rising operational costs. This study introduces an IoT-enabled centralized energy management framework for a PV-BESS-EV integrated smart parking system, leveraging real-time data on carbon emissions, grid pricing, and solar irradiance. A key innovation is its bi-objective optimization model, which simultaneously minimizes both cost and carbon footprint, setting it apart from traditional single-objective approaches. The study evaluates teaching-learning-based optimization (TLBO) and particle swarm optimization (PSO) for addressing the system’s nonlinear challenges. Results indicate that TLBO offers faster convergence and greater robustness, leading to improved load flattening, enhanced PV utilization, and stable battery energy storage system (BESS) state of charge (SoC). Overall, the framework provides a scalable solution that effectively balances economic and environmental objectives for modern grid-integrated EV charging systems.
Volume: 17
Issue: 3
Page: 1591-1600
Publish at: 2026-09-01

Space vector control for multilevel static synchronous compensator in wind energy systems

10.11591/ijaas.v15.i3.pp1270-1285
Gundala Muni Reddy , Ammapalli Hema Sekhar , Selika Narasimha Rao , Kuruna Divakar , Kola Murali Kumar , Nathella Munirathanm Giri Kumar , Gunti Kishor Babu , Vayyala Jyothsna Priya
To meet the higher demand for energy, fossil fuels have been the leading energy source. These fuels produce greenhouse gases (GHG) and these gases are the reason for climate change, and the fossil fuel resources are also running out quickly. Because of this, lawmakers need to switch to clean and renewable energy sources, including solar, geothermal, wind, tidal, and biomass. The wind energy industry has developed a lot because of new technologies, which has led to more wind turbines (WTs) being connected to the grid. Integrating a lot of WTs into the grid has caused challenges like power quality (PQ), grid stability, and reactive power correction. This study utilizes a multilevel inverter-based static synchronous compensator (STATCOM) with a space vector hysteresis current controller (SVHCC) to mitigate the impacts of WTs. The proposed control strategy improves PQ by reducing total harmonic distortion (THD) and maintaining unity power factor (UPF) even in the presence of nonlinear load and induction generator (IG). The desired results are obtained with a lower switching frequency, thereby improving efficiency and reducing stress on power electronic devices. The proposed SVHCC-based STATCOM is modelled and evaluated using MATLAB/Simulink, and its performance is compared with both uncompensated system and a simple hysteresis current controller (SHCC)-based STATCOM.
Volume: 15
Issue: 3
Page: 1270-1285
Publish at: 2026-09-01
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