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Comparative study of fuel economy and emissions for plug-in hybrid electric Payang Water Taxi on different driving cycles using ADVISOR

10.11591/ijpeds.v17.i1.pp25-36
Ahmad Luqmanul Hakim Ahmad Tarmizi , Siti Norbakyah Jabar , Salisa Abdul Rahman
A new conceptual series-parallel plug-in hybrid vehicle for water transportation, known as the plug-in hybrid electric Payang Water Taxi (PHEPWT), is designed to improve vehicle fuel economy and significantly lower boat emissions. This article aims to analyze the fuel economy and emissions of PHEPWT, which are Hydrocarbons (HC), Carbon Monoxide (CO), and Nitrogen Oxides (NOx), with 6 driving cycles including Pulau Warisan river route, Kuala Terengganu river route, Kampung Laut river route, Seberang Takir river route, Pulau Kapas river route, and Tasik Kenyir river route. The analysis of the PHEPWT model will be compared with the existing powertrain architectures using water drive cycles by using the advanced vehicle simulator (ADVISOR). The results will be expected based on the fuel economy and emissions analysis that will show about 30-50% improvement in driving cycle for each driving cycle, and the fuel economy of the PHEPWT will indicate about 15-20% higher than that of the ADVISOR model. Also, for emission, the PHEPWT and ADVISOR models are based on the result of three-type emission such as HC, CO, and NOx, and show that the PHEPWT model has a lower emission compared to the ADVISOR model.
Volume: 17
Issue: 1
Page: 25-36
Publish at: 2026-03-01

Optimizing small-scale geothermal power: insights from long-term testing and system modifications of a 3 MW geothermal condensing power plant in Kamojang, Indonesia

10.11591/ijpeds.v17.i1.pp709-719
Lina Agustina , Suyanto Suyanto , Budi Ismoyo
This study presents the design, development, and performance evaluation of a 3 MW geothermal pilot power plant in Kamojang, Indonesia, developed by retrofitting a 2 MW backpressure turbine into a six-stage condensing turbine. With a 63.81% local content, the plant serves as one of Indonesia’s first demonstrations of small-scale condensing turbine technology. Multi-phase testing yielded a maximum net output of 2.2 MW, below the design target due to condenser vacuum inefficiencies, strainer pressure losses, and reduced turbine isentropic efficiency. Subsequent condenser and strainer modifications improved vacuum stability, reduced pressure drops, and enhanced specific steam consumption (SSC) and overall performance. Exergy analysis identified the condenser (16.1%) and turbine (9.5%) as the primary sources of exergy destruction, resulting in an overall exergy efficiency of 73.6%, higher than typical small-scale geothermal benchmarks. While operational performance improved significantly, sustaining long-term vacuum stability and optimizing turbine operation under variable steam conditions remain key challenges. Future work should focus on automated vacuum control, real-time monitoring, and advanced thermodynamic-electrical optimization to enhance system reliability. This study provides practical insights into turbine retrofitting, condenser stabilization, and integrated exergy evaluation, contributing to the advancement and localization of small-scale geothermal power technology in Indonesia.
Volume: 17
Issue: 1
Page: 709-719
Publish at: 2026-03-01

A novel approach to flexible BTMS for 2-wheeler electric vehicle to avoid fire accidents-an Indian perspective

10.11591/ijpeds.v17.i1.pp49-57
Mahmooda Mubeen , Gangishetti Srinivas
The Indian electric vehicles market share has significantly increased due to various government initiatives, increased fuel prices, and charging infrastructure. On the contrary, fire accidents of EV’s in India are no rarer due to inappropriate BTMS and its inability to work with different environmental conditions prevailing in India, so it has become one of the major concerns. Two-wheelers, being one of the most used modes of transport, are dominating the Indian roads; it well deserves an innovative BTMS that suits local environmental conditions for preventing thermal runaways and maintaining better performance of the battery. As we get to see diverse environmental conditions at different parts of India, it will be good if we can develop flexible BTMS. Major challenges being faced in the development of suitable BTMS are space and cost constraints. This paper focuses on the development of BTMS for electric two-wheelers, suitable for various environmental conditions, which fits in the available space with low additional cost. It also provides flexibility to drop or add some of the features based on one’s operational requirements or environmental conditions prevailing at the place of operation, which can be as easy as one can drop or choosing to have fog lamps, speakers, camera, and sunroof depending upon their requirement and budget.
Volume: 17
Issue: 1
Page: 49-57
Publish at: 2026-03-01

THD and spectral performance analysis of two-triangle RPWM for inverter applications

10.11591/ijpeds.v17.i1.pp370-382
G. Jegadeeswari , R. Sundar , S. P. Manikandan , E. Poovannan , C. Rajarajachozhan , M. Batumalay , Sukumar Kalpana
Pulse width modulation (PWM) is essential for voltage source inverters (VSI) to generate high-quality voltage outputs. Conventional deterministic PWM generates predictable harmonics, causing clusters that increase acoustic noise. Random PWM (RPWM) disperses harmonic power over a wider frequency range, reducing noise and electromagnetic interference. Many RPWM techniques improve inverter quality, but only partially suppress dominant harmonics and lack effective harmonic spreading. Most studies focus on simulations with limited FPGA implementation or hardware validation. The use of digital tools like VHDL, ModelSim, and MATLAB co-simulation remains underutilized. This paper proposes two-triangle RPWM strategies to enhance harmonic dispersion and reduce total harmonic distortion (THD). Co-simulation results are shown for both SPWM and RPWM, along with comparisons of fundamental voltages, THD, and HSF across different modulation indexes. Additionally, synthesis data for the Xilinx XC3S500E FPGA processor is supplied. The last section offers a comparative analysis and experimental validation of SPWM and RPWM. These techniques enable enhanced inverter performance, lower acoustic noise, and process innovations in power electronic systems.
Volume: 17
Issue: 1
Page: 370-382
Publish at: 2026-03-01

Investigation of efficiency and safety in wireless capacitive power transfer through a single-layer tissue phantom

10.11591/ijpeds.v17.i1.pp502-517
Yusmarnita Yusop , Amy Sarah Ngu , Cheok Yan Qi , N. B. Asan , Huzaimah Husin , Shakir Saat , Peter Adam Hoeher
Wireless power transfer (WPT) is a promising solution for implantable biomedical devices, offering an alternative to traditional implanted batteries and percutaneous connections, which are limited by short lifespans and high infection risks. Existing capacitive power transfer (CPT) systems for biomedical implants often utilize media such as animal meat or liquids to validate power transfer across the human body, but these materials exhibit inconsistent and inaccurate dielectric properties. To address this limitation, this study proposes a CPT system designed to operate with a single-layer tissue phantom that closely mimics the dielectric characteristics of human tissue. The system is integrated with a class-E LCCL resonant topology to enhance power transfer efficiency. In addition to evaluating performance, this work also investigates safety aspects in terms of electric field emission and specific absorption rate (SAR). Simulations using MATLAB Simulink and ANSYS HFSS reveal that at a 1 mm tissue gap, the electric field reaches 298.09 V/m and the SAR is 1.14 W/kg, which are both within established safety limits (614 V/m and 2 W/kg per 10 g of tissue). Furthermore, a 5 W, 1 MHz system operating across a 2 mm tissue gap demonstrates power transfer efficiencies of 40.61% for skin tissue and 20.53% for muscle tissue. These results validate the system’s safety and efficiency for powering deeply implanted biomedical devices.
Volume: 17
Issue: 1
Page: 502-517
Publish at: 2026-03-01

A new boost LED driver

10.11591/ijpeds.v17.i1.pp602-616
Dzhunusbekov Erlan , Orazbayev Sagi
Reducing the cost, increasing efficiency, and improving the reliability of LED drivers are critical due to the widespread adoption of LED lighting. This paper presents a research study on a novel boost LED driver designed to minimize voltage pulsations across power switches, thereby reducing dynamic losses in all power components. A small number of Schottky diodes were used to reduce conduction losses. To reduce switching losses in semiconductors, a quasi-resonant switching (QRS) at zero current was implemented for driving transistors. The operating principle is analyzed using computer modeling and validated experimentally in critical conduction mode (CrCM). In the initial evaluation, one version of the proposed driver achieved a high efficiency of up to 98.7% at 120 W input power. Additionally, the size and value of the main inductor were significantly reduced. The proposed driver provides an efficient and scalable solution for high-power LED lighting. Lower dynamic losses and reduced impulse voltages create opportunities for integrating the control circuit and power switches into a single chip.
Volume: 17
Issue: 1
Page: 602-616
Publish at: 2026-03-01

Advances in dermatological imaging: enhancing skin melanoma classification for improved patient outcomes

10.11591/csit.v7i1.p111-120
Debadutta Sahoo , Soumya Mishra
The study presents an enhanced AlexNet-based deep learning system for binary classification of melanoma skin cancer as either benign or malignant using two paired dermatoscopic and clinical image datasets. The study evaluates the resilience of the models across different image sets with common preprocessing and specific data augmentation, using a melanoma dataset containing 10,000 images and a benign versus malignant dataset with 3,600 images. The AlexNet refinement exceeded several standard machine learning (ML) classifiers and other deep architectures on the two datasets with practical training times, gaining 97.12% and 96.21% in balanced accuracy. The training proceeded with SGD as optimiser and cross-entropy as loss on 256×256 images. Benchmarking against support vector machine (SVM), k-nearest neighbour (KNN), and other convolutional neural networks (CNNs) designs shows that the selected architecture and hyperparameters achieved the highest performance on cost-effective computation for the routine melanoma triage. The report highlights the need for external validation, incorporation into dermatological workflows, and explainability to improve trust, diminish dataset bias, and support the safe clinical deployment in practice.
Volume: 7
Issue: 1
Page: 111-120
Publish at: 2026-03-01

Study of neural controller based MPPT in comparison with P&O for PV systems

10.11591/ijpeds.v17.i1.pp797-808
Djaafar Toumi , Mourad Tiar , Abir Boucetta , Ikram Boucetta , Ahmed Ibrahim
This study investigated the performance of two prominent maximum power point tracking (MPPT) strategies: the established perturb and observe (P&O) technique and an artificial neural network (ANN)-based controller. Through simulations conducted in MATLAB/Simulink, a 50 W photovoltaic (PV) array was evaluated under dynamic irradiance and temperature variations. Notably, data generated by the P&O system served as the training dataset for the ANN model. The simulation results indicate that the ANN controller effectively and accurately identifies the PV system’s optimal operating point even amidst fluctuating environmental conditions. When compared to the conventional P&O method, the ANN approach demonstrated superior characteristics, including a significantly faster response, diminished oscillations around the maximum power point, and enhanced tracking accuracy during rapid environmental shifts. These findings underscore the substantial potential of ANN-based MPPT strategies for improving both the efficiency and operational stability of photovoltaic power systems.
Volume: 17
Issue: 1
Page: 797-808
Publish at: 2026-03-01

Voltage compensation using fuel cell fed dynamic voltage restorer

10.11591/ijpeds.v17.i1.pp663-673
Ryma Berbaoui , Rachid Dehini
One of the basic tasks of the dynamic voltage restorer (DVR) is to maintain voltage stability in distribution systems by correcting any deviations or disturbances in the three-phase supply. Whether they are increases or decreases. However, one of its disadvantages is its power source, as it cannot supply itself with power from the electrical grid like parallel compensators, which obtain power directly from the grid. This article presents an energy study of a dynamic voltage regulator (DVR) when operated using a power source represented by fuel cells, which are considered a clean and renewable source. On the other hand, excess energy from the regenerator or fuel cells can be output and injected into the distribution network for utilization via a parallel compensator (CP). The parallel compensator also compensates for reactive energy on the reactive load side to increase the power factor measured at the source side of the distribution system. This integrated system also uses neural networks to identify voltage disturbances and determine the voltages (modules/arguments) that must be added to the voltages in the power grid for correction. This analytical study was completed using a simulation system to confirm the effectiveness of this integrated system. The distinctive feature of this study is the integration of fuel cells and neural network-based control in the DVR system, providing a sustainable and intelligent alternative to conventional configurations, which makes it different from traditional DVRs that operate with batteries and supercapacitors. Its efficiency in compensating for voltage drops and surges is evident, and it also improves the power factor and ensures reliable operation of voltage-sensitive devices.
Volume: 17
Issue: 1
Page: 663-673
Publish at: 2026-03-01

Ferrite-based magnetic shielding for efficiency enhancement in resonant inductive wireless power transfer systems

10.11591/ijpeds.v17.i1.pp572-581
Wan Muhamad Hakimi Wan Bunyamin , Rahimi Baharom
This paper presents a detailed simulation-based investigation of ferrite-based magnetic shielding to enhance the efficiency and electromagnetic performance of resonant inductive wireless power transfer (RIPT) systems, with a particular emphasis on electric vehicle (EV) wireless charging applications. Two system configurations, a baseline coil-only system and a ferrite-shielded system, were modelled and simulated using CST Studio Suite 3D electromagnetic simulation software under identical geometric and electrical conditions to ensure a fair comparative evaluation. Key performance metrics, including power transfer efficiency (PTE), H-field distribution, and magnetic flux confinement, were analyzed to quantify the shielding impact. The ferrite-shielded configuration achieved a PTE improvement from 98.29% to 99.01%, demonstrating stronger flux concentration, reduced leakage, and lower electromagnetic interference (EMI) exposure. Additional analyses highlight the trade-offs in ferrite integration, including potential core loss, material cost, and thermal drift, while also discussing the system’s robustness against coil misalignment and its alignment with SAE J2954 and IEC 61980 standards for EV charging. The study is limited to a simulation-based approach without experimental validation; however, the findings establish a solid foundation for future hardware prototyping and hybrid shielding exploration, integrating ferrite and composite or metamaterial-based structures. Overall, this work contributes to the development of efficient, EMI-compliant, and thermally stable WPT systems suitable for next-generation EV charging infrastructures.
Volume: 17
Issue: 1
Page: 572-581
Publish at: 2026-03-01

Solar power forecasting using a SARIMA approach for Indonesia's grid integration

10.11591/ijpeds.v17.i1.pp293-302
Ricky Maulana , Syafii Syafii , Aulia Aulia
Indonesia’s transition toward a renewable energy-dominated power grid is progressing to meet increasing energy demands while reducing dependence on fossil fuels. According to the National Energy General Plan, their goal is to have 23% of the energy mix come from renewables by 2025 and 31% by 2050. Accurate forecasting of photovoltaic (PV) power output is crucial to address the intermittent nature of solar energy and ensure grid stability. A seasonal autoregressive integrated moving average (SARIMA) model was developed to estimate day-ahead photovoltaic power output in Padang City, Indonesia. Using NASA solar irradiance data from March 1-31, 2024, the SARIMA(1,0,1)(4,0,3)24 model achieved high accuracy with an NRMSE of 4.19%. To evaluate its performance, a comparative evaluation was conducted between the SARIMA model and two machine learning methods, namely artificial neural network (ANN) and long short-term memory (LSTM), in which SARIMA achieved the lowest forecasting error. These findings indicate that SARIMA remains an effective and interpretable statistical method for short-term PV forecasting, supporting reliable energy planning and power grid operations towards Indonesia's renewable energy goals.
Volume: 17
Issue: 1
Page: 293-302
Publish at: 2026-03-01

A novel high-gain DC-DC converter with fuzzy logic control for hydrogen fuel cell vehicle applications

10.11591/ijpeds.v17.i1.pp617-628
Gaddala Anusha , A. V. V. Sudhakar , Shaik Rafikiran , Ram Ragotham Deshmukh , C. H. Hussaian Basha
Hydrogen fuel cell vehicles (HFCVs) are emerging as a sustainable alternative to conventional internal combustion engines due to their zero-emission characteristics and high energy efficiency. However, the low output voltage of fuel cells poses a significant challenge in meeting the high-voltage requirements of electric traction systems. To address this, this paper proposes a high-gain non-isolated switched-capacitor (SC) DC-DC converter integrated with a fuzzy logic controller (FLC) for efficient power management in hydrogen fuel cell vehicle applications. The proposed converter topology achieves a significant voltage step-up without the use of bulky magnetic components, making it lightweight and compact for automotive integration. A maximum power point tracking (MPPT) controller using fuzzy logic is used to recover optimum energy out of the fuel cell stack during different loads and conditions of the environment. MATLAB/Simulink simulation results validate the high voltage gain, stable operation, and improved dynamic response of the proposed converter under FLC control. The proposed intelligent control strategy enhances fuel cell utilization and ensures effective operation of HFCV powertrains.
Volume: 17
Issue: 1
Page: 617-628
Publish at: 2026-03-01

Analysis of different converter topologies for EV applications

10.11591/ijpeds.v17.i1.pp518-532
Bodapati Venkata Rajanna , Kondragunta Rama Krishnaiah , Sakimalla Prabhakar Girija , Shaik Hasane Ahammad , Mohammad Najumunnisa , Syed Inthiyaz , Gouthami Eragamreddy , Giriprasad Ambati , Nitalaksheswara Rao Kolukula
Electric vehicles (EVs) are gaining global prominence due to their high efficiency, low noise, and minimal carbon emissions. A critical aspect of EV performance lies in the interaction between energy storage systems (ESS) and power converters. Nonetheless, power delivery from storage units tends to be unreliable and needs strong converter units for effective and stable energy transmission. Several forms of direct current-to-direct current conversion systems used in electric vehicles are thoroughly examined in the paper, including both isolated and non-isolated designs such as those with the cuk, flyback, and push-pull architectures. The paper looks at converter categorization, control methods such as proportional-integral and artificial neural networks, as well as the method of modulation using unipolar and bipolar sinusoidal pulse-width modulation (PWM). Additionally, the role of optimization algorithms in improving converter performance is explored. Simulations were conducted using MATLAB/Simulink to evaluate each topology under varying load and input voltage conditions. The results demonstrate that the Push-Pull converter has the best efficiency for high-power applications, while the Cuk and Flyback converters are best for applications requiring continuous current and low-power, compact designs, respectively. This research offers insights for choosing optimal converter structures to improve energy efficiency and reliability of systems in electric vehicles.
Volume: 17
Issue: 1
Page: 518-532
Publish at: 2026-03-01

D-STATCOM control for distribution grids with distributed sources based on MMC structure using FCS-MPC algorithm

10.11591/ijpeds.v17.i1.pp425-437
Pham Viet Phuong , Le Hoai Nam , Pham Chi Hieu , Tran Hung Cuong
This paper proposes a D-STATCOM structure based on a modular multilevel converter (MMC) with the use of FCS-MPC control method for the purpose of compensating reactive power and stabilizing voltage in the distribution grid. The D-STATCOM is effectively used in cases involving non-sinusoidal and unstable voltages, which often occur in the distribution grid due to the effects of unbalanced nonlinear loads and power injection from renewable energy systems. The proposed structure also has the capability of reactive power compensating flexibility in fault conditions to stabilize the grid voltage. In this paper, a new control strategy, which is based on the combination of an outer PI controller and an inner FCS-MPC controller, was introduced. The outer PI controller is used to reduce static deviations in control values and to provide a reference value for the FCS-MPC controller. The inner FCS-MPC controller calculates the optimal switching state for the purpose of reducing the switching frequency of the MMC. The implementation process begins with the construction of a mathematical model and a control model. Simulations were carried out by MATLAB/Simulink to demonstrate the responsiveness of the control algorithm and the performance of D-STATCOM under the conditions of non-sinusoidal and unstable voltages.
Volume: 17
Issue: 1
Page: 425-437
Publish at: 2026-03-01

Hybrid renewable energy for cold chain in Indonesia: technical and economic evaluation

10.11591/ijpeds.v17.i1.pp674-682
I Made Aditya Nugraha , I Gusti Made Ngurah Desnanjaya , Anis Khairunnisa , Mahaldika Cesrany
Cold storage plays a crucial role in preserving temperature-sensitive products, particularly in the fisheries and food sectors. However, its operation is highly energy-intensive and often constrained by unstable electricity supply in many Indonesian regions. This study quantitatively evaluates a hybrid renewable energy system integrating photovoltaic (PV) panels, diesel generators, batteries, and the utility grid to ensure sustainable cold storage operations. Using measured load profiles, solar irradiation data, and annual operating costs, the system achieved a 60% reduction in diesel fuel consumption, 30-50% lower CO₂ emissions, and annual savings exceeding IDR 100 million compared to conventional generator-based systems. The system demonstrated 83.5% overall efficiency, with a payback period of 4.4 years and a positive net present value (NPV), confirming its economic viability. The novelty of this research lies in presenting the first comprehensive techno-economic analysis of a PV-diesel-battery-grid hybrid system specifically designed for fisheries-based cold storage facilities in Indonesia, considering local solar potential and grid reliability. Despite its feasibility, implementation challenges remain, including a lack of skilled technicians, limited financial incentives, and bureaucratic constraints. To overcome this, the study recommends PV subsidies, low-interest green loans, and public–private partnerships aligned with Indonesia's energy transition roadmap and cold chain development goals.
Volume: 17
Issue: 1
Page: 674-682
Publish at: 2026-03-01
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