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25,002 Article Results

Technical and cost analysis of an electric hand plow tractor for specific land in Java, Indonesia

10.11591/ijpeds.v16.i1.pp175-184
Cuk Supriyadi Ali Nandar , Setyo Margo Utomo , Endra Dwi Purnomo , Amiruddin Aziz , Lia Amelia , Achmad Ridho Mubarak , Marsalyna Marsalyna , Sherly Octavia Saraswati , Fandy Septian Nugroho
This study focuses on the technical and cost analysis of an electric hand plow tractor, especially in the East Java region. The manufacturing cost of electric tractors increases significantly in line with the battery capacity. Although the manufacturing cost of an electric tractor is 3–5 times higher than that of a fuel tractor, the operational cost of an electric tractor is about 79% that of a fuel tractor. Based on the investment analysis, it is feasible to assembly electric tractors with a power of 5.5 HP or 4.1 kW using NMC18650 and NMC21700 batteries with an energy capacity of 14 kWh in case for rural residents with access to an electricity network available in their paddy fields. The price of electricity and the unit cost of a battery pack have a large impact on operational costs. The manufacture of electric tractors will be more attractive to get better economic returns when the price of electricity does not increase, and the unit cost of battery packs falls due to the battery technology trend. Nevertheless, certain challenges to the utilization of electric tractors are the farmers' preferences and habits, market demands, the environment, and the regulations of the tractor component manufacturers.
Volume: 16
Issue: 1
Page: 175-184
Publish at: 2025-03-01

Design and implementation of PV emulator based on synchronous buck converter using Arduino Nano microcontroller

10.11591/ijpeds.v16.i1.pp448-456
Ahmad Saudi Samosir , Herri Gusmedi , Alfin Fitrohul Huda
This paper discusses the comprehensive design and implementation of a photovoltaic (PV) emulator hardware using a synchronous buck converter. The primary objective is to simulate the electrical characteristics of a real PV module under varying environmental conditions. The process involves detailed simulations carried out using MATLAB/Simulink software to evaluate the performance and accuracy of the emulator model. Various load values were tested to account for the impact of fluctuations in radiation and temperature. The accuracy of the emulator's output characteristics was validated by comparing them with the actual attributes of the SolarWorld Sun-module SW50 PV module. The final step involves constructing the hardware of the PV emulator using electronic components, with an Arduino Nano employed as the controller.
Volume: 16
Issue: 1
Page: 448-456
Publish at: 2025-03-01

Efficiency enhanced adaptive quasi-sliding mode controller for variable-speed induction motor drive

10.11591/ijpeds.v16.i1.pp151-161
Shaija Palackappillil Jacob , Asha Elizabeth Daniel
Recent advancements in automated manufacturing and processing industries necessitate fast-responding, efficient, and robust methods for controlling induction motor (IM) drives. Classical proportional-integral (PI) controllers provide optimal performance only at specific operating points and are sensitive to parameter variations. This work proposes an adaptive quasi-sliding mode controller (AQSMC), which utilizes a tangent (tanh) function as the switching function and demonstrates enhanced robustness and adaptability across a wider range of operating conditions. The AQSMC employs an adaptation law to estimate the dynamic disturbances, offering insensitivity to structured and unstructured uncertainties. Numerical simulations are carried out with the AQSMC that analytically deduces the optimum field flux ensuring efficient performance. A lookup table derived from the efficiency optimization algorithm (EOA) is incorporated to further streamline the computational requirements. To validate simulation results, a prototype was developed using a 1 HP induction motor, a DSP controller board with a TI C2000 Delfino MCU F28379D microcontroller, and an IGBT-based Inverter module. Simulations show a 6.3% efficiency improvement at half load and 300 rpm, while experimental analysis records a 3.9% improvement with the EOA, highlighting the potential for enhancing energy efficiency in various industrial applications.
Volume: 16
Issue: 1
Page: 151-161
Publish at: 2025-03-01

Optimizing low-speed DTC performance for three-phase induction motors with sector rotation strategy

10.11591/ijpeds.v16.i1.pp464-471
Nurul Syahada Muhamad Sabri , Siti Azura Ahmad Tarusan , Syed Abrar S. A. Zawawi , Auzani Jidin , Tole Sutikno
This paper proposes a modification to the direct torque control (DTC) strategy for induction motors, focusing on improving flux performance at lower speeds. The method employs a sector rotation strategy to address stator flux droop, which occurs in conventional DTC due to the impact of stator resistance at low speed becoming more significant. This constrains the ability of the flux vector to be tangential to the voltage vector in the default sector. Consequently, an improper flux locus leads to distortion of the phase currents which disrupts precise control of torque. The proposed approach dynamically adjusts the sector angle to mitigate flux droop while maintaining the simplicity and original structure of DTC. The new sector rotation strategy is validated through simulations in MATLAB/Simulink to demonstrate the effectiveness of the proposed method in reducing stator flux droop. These findings have potential applications in the industrial sector and electric vehicles, where stable motor operation and smoother driving performance at low speeds are crucial for precise control operation.
Volume: 16
Issue: 1
Page: 464-471
Publish at: 2025-03-01

Hybrid energy storage system for dynamic power management in grid-connected microgrid

10.11591/ijpeds.v16.i1.pp485-496
Yaya Kamagaté , Heli Amit Shah
This paper presents an adaptive rule-based approach for dynamic power management in grid-connected microgrids. Solar photovoltaics (PV) and a battery-ultracapacitor hybrid energy storage system form the DC subsystem. Initially, the reference power is processed through a low-pass filter, diverting high-frequency power variations to the ultracapacitor, thereby safeguarding the battery. Then, a power allocation factor proportional to the battery state of charge manages the average power distribution between the battery and the grid. Finally, a microgrid power management system (MPMS) establishes rules to regulate power sharing among sources and loads. In the proposed method, the battery handles long-term energy requirements, the ultracapacitor meets short-term power demands, and the grid is adjusted to align with the system’s requirements. The main benefits involve effective power distribution among sources and loads, DC bus voltage stabilization, smooth transitions between different operating modes, and enhanced grid power quality. Additionally, safety protocols prevent overcharging/deep discharging, thus reducing the risk of premature degradation and resulting in longer lifespan of storage devices. MATLAB/Simulink is used to implement and validate the method.
Volume: 16
Issue: 1
Page: 485-496
Publish at: 2025-03-01

Design and implementation of 4-quadrant chopper for speed control of EVs and regenerative braking analysis

10.11591/ijpeds.v16.i1.pp407-417
Magdy Saoudi Abdelfatah , Parmal Singh Solanki , Sasidharan Sreedharan
This paper presents a novel 4-quadrant chopper design for controlling the speed of electric vehicles, featuring a regenerative braking mechanism to improve energy efficiency. Regenerative braking recovers energy during deceleration by converting kinetic energy into electrical energy stored in the battery. This process activates automatically when the accelerator pedal is released, slowing the vehicle while reducing reliance on mechanical brakes, which remain available for emergency situations. The system’s voltage control is achieved using a pulse-width modulation (PWM) technique that adjusts the duty cycle of switching devices. A microcontroller serves as the system’s core, generating PWM signals and coordinating its operation. The performance of the chopper was evaluated through simulations and experiments, demonstrating that optimal energy recovery occurs at duty cycles of 55-65%. The results revealed that up to 400 joules of energy can be regenerated per braking cycle, particularly in stop-start driving conditions. This innovative design contributes to a 5-10% extension in battery life per charge cycle, enhancing the overall efficiency and sustainability of electric vehicles. The proposed system demonstrates significant potential for energy recovery and reduced wear on mechanical braking systems, paving the way for more efficient electric vehicle technologies.
Volume: 16
Issue: 1
Page: 407-417
Publish at: 2025-03-01

A new hybrid MPPT algorithm combining P&O and fuzzy logic techniques

10.11591/ijpeds.v16.i1.pp497-508
Oumaima Mrhar , Khalid Kandoussi , Mohamed Eljouad
This study introduces an innovative approach to maximum power point tracking (MPPT) in photovoltaic systems using a hybrid algorithm that combines perturb and observe (P&O) with fuzzy logic. The novelty of this work lies in the choice of input variables for the fuzzy controller, specifically dV and dP, which addresses significant challenges such as slow response to environmental condition variations and limited responsiveness under low solar irradiation. This method of MPPT is modified to make it particularly suitable for extracting peak power from photovoltaic systems. To evaluate the effectiveness of this approach, a simulation was conducted using MATLAB/Simulink software on a system comprising a photovoltaic panel connected to the new controller. Simulation results indicate that the suggested hybrid algorithm surpasses traditional methods like perturb and observe (P&O) and fuzzy logic (FL) in several ways. It notably excels in response time and tracking efficiency, achieving a remarkable success rate of 99.7% in pinpointing the maximum power point. These outcomes could significantly boost the performance of photovoltaic systems and, consequently, further the adoption of renewable energy while lessening environmental impacts.
Volume: 16
Issue: 1
Page: 497-508
Publish at: 2025-03-01

Enhancing efficiency and stability in CPT systems: a state feedback controller approach

10.11591/ijpeds.v16.i1.pp225-234
Ahmed Al-Hattami , Shakir Saat , Yusmarnita Yusop , Md Rabiul Awal , A. H. M. Shapri , Huzaimah Husin
This work aims to present an innovative design and simulation of an auto-tuning capacitive power transfer (CPT) system. The system utilizes a Class-E converter, renowned for its exceptional efficiency. Challenges arise when trying to regulate the output voltage of a Class-E converter in the presence of load fluctuations, leading to an escalation in switching losses. By employing first harmonic approximation (FHA) and generalized state space averaging (GSSA), a state-space model of the system is constructed to effectively address this problem. The output voltage is regulated by a state feedback controller developed using the Lyapunov approach. This paper presents a comparative analysis of a traditional PID controller and a recently suggested state feedback controller, with a primary emphasis on system stabilization. The study examines the similarities and differences between the two controllers. The efficacy of the proposed controller design is demonstrated through the utilization of simulation data. Furthermore, these results confirm the validity of the comparative study, making it a substantial contribution to the field of CPT systems.
Volume: 16
Issue: 1
Page: 225-234
Publish at: 2025-03-01

Advancing solar energy harvesting: Artificial intelligence approaches to maximum power point tracking

10.11591/ijpeds.v16.i1.pp55-69
Meriem Boudouane , Lahoussine Elmahni , Rachid Zriouile , Soufyane Ait El Ouahab
This paper presents a comparative study of five maximum power point tracking (MPPT) control techniques in photovoltaic (PV) systems. The algorithms evaluated include classical methods, such as perturb and observe (P&O) and incremental conductance (IC), as well as intelligent approaches such as fuzzy logic (FL), artificial neural networks (ANNs), and adaptive neuro-fuzzy inference system (ANFIS). Intelligent methods provide faster response times and fewer oscillations around the maximum power point (MPP). The structure of the PV system includes a PV generator, load, and DC/DC boost converter driven by an MPPT controller. The performance of these techniques is analyzed under identical climatic conditions (same irradiation and temperature) in terms of efficiency, response time, response curve, accuracy in tracking the MPP, and others considered in this work. Simulations were performed using MATLAB-Simulink software, demonstrating that ANNs and ANFIS outperform traditional methods in dynamic environments, with FL being computationally intensive. P&O exhibited significant oscillations, while IC a showed slower tracking speed.
Volume: 16
Issue: 1
Page: 55-69
Publish at: 2025-03-01

Comparative analysis of wind speed prediction: enhancing accuracy using PCA and linear regression vs. GPR, SVR, and RNN

10.11591/ijpeds.v16.i1.pp538-545
Somasundaram Deepa , Jayanthi Arumugam , Raguraman Purushothaman , D. Nageswari , Lingisetty Rajasekhara Babu
For power systems with significant wind power integration to operate in an efficient and dependable manner, wind speed prediction accuracy is crucial. Factors such as temperature, humidity, air pressure, and wind intensity heavily influence wind speed, adding complexity to the prediction process. This paper introduces a method for wind speed forecasting that utilizes principal component analysis (PCA) to reduce dimensionality and linear regression for the prediction model. PCA is employed to identify key features from the extensive meteorological data, which are subsequently used as inputs for the Linear Regression model to estimate wind speed. The proposed approach is tested using publicly available meteorological data, focusing on variables such as temperature, air pressure, and humidity. Popular models like recurrent neural networks (RNN), support vector regression (SVR), and Gaussian process regression (GPR) are used to compare its performance. Evaluation metrics such as root mean square error (RMSE) and R² are used to measure effectiveness. Results show that the PCA combined with Linear Regression model yields more accurate predictions, with an RMSE of 94.11 and R² of 0.9755, surpassing the GPR, SVR, and RNN models.
Volume: 16
Issue: 1
Page: 538-545
Publish at: 2025-03-01

Estimator-based single phase second order variable structure controller for the pitch control of a variable speed wind turbine

10.11591/ijpeds.v16.i1.pp235-242
Cong-Trang Nguyen , Tai Thanh Phan
A novel single phase second order variable structure controller (SPSOVSC) based on estimated variables and output information only is presented for the variable speed wind turbine (VSWT) system. In contrast with a recent method, the output feedback and second order sliding mode control techniques are deliberated for the SPSOVSC design in the VSWT. The selection of an integral single-phase sliding surface is established such that the reaching phase required in the basic variable structure control (BVSC) scheme is removed since the plant’s state trajectories always begin from the sliding surface. In addition, appropriate stability constraints by Lyapunov based novel linear matrix inequality (LMI) technique are acquired to guarantee the entire VSWT plant’s steadiness. Using the proposed techniques, the SPSOVSC is developed to modify BVSC to advance the performance of VSWT plant in terms of overshoot and settling time. The results show the new scheme is highly robust in sliding variable's fast convergence to zero asymptotically. It is obvious that the robustness of the proposed controller in terms of steadiness and usefulness of the scheme.
Volume: 16
Issue: 1
Page: 235-242
Publish at: 2025-03-01

Efficient SOC estimation for electric vehicles: Extended Kalman filter approach for lithium-ion battery systems

10.11591/ijpeds.v16.i1.pp440-447
Meriem Mossaddek , El Mehdi Laadissi , Sohaib Bouzaid , Abdelowahed Hajjaji
This study investigates the estimation of the state of charge (SOC) in lithium-ion batteries by utilizing the extended Kalman filter (EKF) algorithm. A simulation model was developed in MATLAB, integrating the Thevenin model with the EKF algorithm to assess SOC levels. The results from the simulations confirm the accuracy and reliability of the proposed approach in estimating SOC. Moreover, a Simulink-based model of the Thevenin equivalent circuit and the EKF algorithm was implemented to further verify the effectiveness of the EKF in SOC estimation. This research underscores the potential of the EKF algorithm to deliver precise SOC estimates, which is crucial for optimizing battery management systems, particularly in electric vehicles.
Volume: 16
Issue: 1
Page: 440-447
Publish at: 2025-03-01

Evaluation of pulse width modulation techniques to reduce total harmonic distortion in grid-connected PV systems

10.11591/ijpeds.v16.i1.pp564-574
Bouledroua Adel , Mesbah Tarek , Kelaiaia Samia
The proliferation of grid-connected photovoltaic systems (GCPVs) has created significant challenges in maintaining power quality standards, particularly with respect to total harmonic distortion (THD). This research is concerned with evaluating three well-known pulse width modulation (PWM) techniques - sine PWM (SPWM), third harmonic injection PWM (THIPWM) and space vector PWM (SVPWM) for their effectiveness in mitigating THD in three-phase single stage GCPVs. Through extensive simulations performed in MATLAB/Simulink, a comprehensive comparative analysis is presented that reveals the strengths and limitations of each PWM strategy. The results show that SVPWM is the most effective technique for THD mitigation and outperforms its counterparts. THIPWM proves to be a promising second-best option, while SPWM lags behind in terms of harmonic suppression capabilities. This research not only quantifies the THD reduction achieved by each PWM technique but also delves into the underlying mechanisms and theoretical underpinnings that contribute to their distinct performances. The results are further supported by detailed harmonic spectrum analyses, providing valuable insights into the harmonic profiles associated with each modulation strategy.
Volume: 16
Issue: 1
Page: 564-574
Publish at: 2025-03-01

Optimal parameter identification of fractional-order proportional integral controller to improve DC voltage stability of photovoltaic/battery system

10.11591/ijpeds.v16.i1.pp519-529
Taibi Abdelhalim , Laroussi Kouider , Hegazy Rezk , Rouibah Abdelkader , Ayman Al-Quraan
This study addresses the critical challenges of voltage stabilization in DC microgrids, where the inherent variability of renewable energy sources significantly complicates reliable operation. The focus is on optimizing the fractional-order proportional-integral (FO-PI) controller using four advanced techniques a whale optimization algorithm (WOA), grey wolf optimizer (GWO), genetic algorithm (GA), and sine cosine algorithm (SCA). Voltage instability poses substantial risks to the reliability and efficiency of DC microgrids, making the optimization of the FO-PI controller an essential task. Through comparative analysis, the study demonstrates that WOA outperforms the other methods, achieving superior voltage stability, resilience, and overall system performance. Notably, WOA achieves the lowest average cost function at 0.0004, compared to 0.892 for GWO, 0.659 for GA, and 0.096 for SCA, showcasing its effectiveness in fine-tuning the controller’s parameters. These findings highlight WOA robustness as a powerful tool for enhancing microgrid performance, especially in voltage regulation. The study underscores WOA potential in ensuring the reliable and efficient integration of renewable energy systems into DC microgrids and lays the groundwork for further research into its application in more complex and dynamic grid scenarios. By optimizing the FO-PI controller, WOA significantly contributes to the long-term stability and efficiency of DC microgrids.
Volume: 16
Issue: 1
Page: 519-529
Publish at: 2025-03-01

Post-fault voltage limit assessment for six-phase induction machines: a synchronous and slip frequency approach

10.11591/ijpeds.v16.i1.pp162-174
Nooradzianie Muhammad Zin , Wan Noraishah Wan Abdul Munim , Ahmad Farid Abidin , Hang Seng Che , Mohamad Fathi Mohamad Elias , Rahimi Baharom
Six-phase machine research has attracted a lot of attention lately, as seen by the large number of articles and case studies that have been written about it. Six-phase induction machines are prevalent due to their simplicity in construction. A fault-tolerance system is essential to guaranteeing machine operation that is both available and continuous in the event of a disruption or failure in the system. The operational topologies of dual three-phase (D3-IM) and symmetrical six-phase (S6-IM) induction machines were studied in this research. One open-phase fault (1OPF) is covered in the study, and different scenarios including the derating factor, neutral configuration, and maximum torque (MT) operational strategy are taken into account. Using MATLAB software, machine characteristics, machine equations, and Clarke's transformation show the fault-tolerant capability of each type of machine. Moreover, a MATLAB program is developed to assess post-fault voltage control limits, allowing for a comparison between current and voltage control limits. Simulated graph results depicting line-to-line voltages against synchronous and slip frequencies across all possible fault scenarios reveal distinct fault-tolerant capabilities between the two machine types. The comparative study shows that S6-IM offers better fault-tolerant capability than D3-IM based on both various synchronous and slip frequency approaches.
Volume: 16
Issue: 1
Page: 162-174
Publish at: 2025-03-01
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