Snehal L. Kadam, Rahul S. Ingole, Yong Tae Kim
et al.
The growing demand for sustainable, high‐performance energy solutions has intensified the need for advanced electrochemical electrode materials, particularly for real‐life applications, notably electric vehicles, grid stabilization, and portable electronics. Supercapacitors have become essential in this real‐world energy storage landscape due to their exceptional power density, rapid charge–discharge capability, and long operational lifetime. While various electrode materials and their electrochemical performances have been extensively studied, limited attention has been paid to the transition from laboratory‐scale development to real‐world application. This article fills this gap by exploring the latest advancements in supercapacitor electrode materials with a particular focus on their progression from laboratory innovation to practical real‐time energy storage and supply. Emphasizing the crucial role of electrode materials in optimizing electrochemical performance, we provide a thorough analysis of the state‐of‐the‐art supercapacitor technologies in terms of the electrode materials and their advanced processing methods. We further highlight the emerging integrations of machine learning techniques for predictive material discovery and synthesis optimization, and of the environmentally sustainable materials for dissemination of the high‐performance supercapacitors to our society. This article provides a clear roadmap for translating lab‐scale innovations into sustainable, market‐ready supercapacitor technologies, emphasizing the crucial role of advanced electrode materials.
Unmanned vertical takeoff and landing (VTOL) aircraft are increasingly deployed for logistics, surveillance, and urban air mobility (UAM) applications. However, the limitations of full-electric (FE) and internal combustion engine (ICE) systems in meeting diverse mission requirements have motivated the development of hybrid-electric (HE) propulsion systems. The design of HE powertrains remains challenging due to configuration flexibility and the lack of unified criteria for performance trade-offs among FE, ICE-powered, and HE configurations. This study proposes an integrated propulsion co-design framework coupling power allocation, energy management, and component capacity constraints through parametric system modeling. These interdependencies are represented by three key matching parameters: the power ratio (Φ), energy ratio (Ω), and maximum continuous discharge rate (rc). Through Pareto-optimal design space exploration, trade-off analysis results and optimization principles are derived for diverse mission scenarios such as UAM, remote sensing, and military surveillance. Different technological conditions are considered to guide component-level technological advancements. The method was applied to the power system retrofit of the Great White eVTOL. Subsystem steady-state tests provided accurate design inputs, and a simulation model was developed to reproduce the full flight mission. By comparing the simulation with flight-test measurements, mean absolute percentage errors of 8.91% for instantaneous fuel consumption and 0.26% for battery voltage were obtained. Based on these error magnitudes, a dynamic design margin was defined and then incorporated into a subsequent re-optimization, which achieved the 1.5 h endurance target with a 10.49% increase in cost per ton-kilometer relative to the initial design. These results demonstrate that the proposed co-design methodology offers a scalable, data-driven foundation for early-stage hybrid-electric VTOL powertrain design, enabling iterative performance correction and supporting system optimization in subsequent design stages.
Udhaya Mugil Damodarin, Gian Carlo Cardarilli, Luca Di Nunzio
et al.
This paper presents a smart electric vehicle (EV) charging management system that integrates Reinforcement Learning intelligence on a Field-Programmable Gate Array (FPGA) platform. The system is based on the Q-learning algorithm, where the RL agent perceives environmental conditions, captured through hardware sensors such as current, voltage, and priority indicators, and makes optimal charging decisions to address grid stress and prioritize charging needs. The FPGA implementation leverages hardware design strategies to ensure efficient operation and real-time response within a limited amount of required energy, allowing for its implementation in embedded applications and possibly enabling the use of an energy harvesting power source, like a small solar panel. The proposed design effectively manages multiple EV chargers by dynamically allocating current and prioritizing charging tasks to maintain service quality. Through intelligent decision making, informed by continuous sensor feedback, the system adapts to fluctuating grid conditions and optimizes energy distribution. Key findings highlight the system’s ability to maintain stable operation under varying demand conditions, improving power efficiency, safety, and service reliability. Moreover, the design is scalable, enabling seamless expansion for larger installations by following consistent architectural guidelines. This FPGA-based solution combines RL intelligence, sensor-based environmental perception, and robust hardware design, offering a practical framework for an efficient EV charging infrastructure in modern smart grid environments.
Dual power supply cascaded-type power electronic transformers (DPSC-PET) is connected to two power supplies with high operational reliability and flexible operation mode, and it can be widely used in medium and low voltage distribution networks. It is of great importance to conduct in-depth research on its voltage sag tolerance and regulation method for maintaining efficient energy transmission of DPSC-PET as well as high quality power supply during voltage sag. Firstly, the topological structure and control strategy of DPSC-PET are analyzed. Secondly, the influence factors of voltage sag tolerance of DPSC-PET are analyzed for three-phase symmetrical voltage sag which has the most serious power shortage. Then, from the perspective of power balance, a real-time analysis method of voltage sag immunity of DPSC-PET as well as power coordination method between dual input ports when voltage sag occurs on different power supply are proposed to achieve a perfect recovery of low-voltage DC bus voltage, which means the significant improvement of DPSC-PET to cope with transient disturbances. Finally, the simulation model of DPSC-PET is established and the simulations for voltage sag occurred with different magnitudes on different power supply are cited out. The results show that the voltage sag tolerance of DPSC-PET is significantly improved with the proposed method.
Abstract As a type of magnetic device being able to realize contact‐free power transmission together with sufficient volumetric torque density, the field‐modulated magnetic gear (FMMG) has become a promising alternative to the mechanical gear having rigid construction yet suffering lots of issues generated by the continuous teeth friction. The conventional magnetic gears (MGs) that behave as simple copies of their mechanical counterparts and can be roughly defined as origination of the FMMG are briefly introduced at first. Subsequently, the topology and material advancements proposed to improve operational performance of the FMMG are comprehensively summarised so as to clarify its current development status. Finally, potential applications of the FMMG due to its inherent advantages are compared against the existent challenges. The review aims to provide referable guidelines for researchers working at the field of high‐performance MGs.
Abstract Current transformers (CTs) are widely used for energy metering, relay protection, condition monitoring and control circuits. However, CT saturation may lead to non‐negligible measurement errors and relay malfunctions, posing a threat to the stability and security of the power grid. In order to address the problem of CT saturation, a novel measurement‐protection‐integrated current transformer (MPICT) is proposed. First, the working states of the MPICT are summarised and the approximate expressions for the steady‐state measuring characteristics, the transient response characteristics, and the measurement errors are derived from the equivalent circuit model. Then, the feasibility of the MPICT and the theoretical analyses are verified by the 3D FEM simulation imitating the presented MPICT excited by diverse currents. Finally, a down‐scale prototype is fabricated and a series of tests are conducted in the laboratory to validate the effectiveness of the equipment. The simulation and experimental results suggest that the output of the MPICT can accurately reconstruct the primary current waveform, even if the primary current contains decaying or constant DC component.
Abstract The segmental translator linear switched reluctance motor (STLSRM) is a special type of linear switched reluctance motor (LSRM) that has more output power than its conventional type. Therefore, it can be a good choice for certain applications. Heat is one of the factors limiting the output in machines. Therefore, predicting the thermal distribution of machine is as important as the magnetic design. A comprehensive thermal model is presented based on the lumped parameter approach for STLSRM, which predicts temperature distribution in different parts of this motor, including slot winding, end‐winding, stator pole, stator yoke, and the moving part. Considering that the proposed thermal model depends on dimensions and materials used in machine, it can be used for other designs of the STLSRM. The presented thermal model is applied to a typical STLSRM and temperature is determined in its different parts. The simulation results are then compared with the results of 3‐D thermal modelling based on the finite element method (FEM) for validation.
Abstract In order to diagnose the mechanical fault of transformer on‐load tap‐changer (OLTC) effectively, a fault diagnosis method based on improved variational mode decomposition (VMD) and relative density‐based outlier score (RDOS) is proposed. Firstly, the signal is decomposed into a series of modal components with narrow band and distinguishing centre frequency by improved VMD based on optimal quality factor. Then, the energy, permutation entropy, power spectrum concentration degree and characteristic frequency of each modal component are calculated, and Laplacian‐score method is used to select the features with better discriminative ability. Finally, a RDOS is used to diagnose the mechanical fault of OLTC, and the mechanical condition is judged according to RDOS value. An experiment is conducted on the OLTC simulation experiment platform and the collected signals are processed. The result shows that the proposed method can diagnose mechanical fault effectively.
Péter Bodolai, Attila Vörösváczki, Gábor Bihari
et al.
Abstract This article describes the collaborative efforts between Tecnam, Rolls‐Royce, and Rotax to equip a 4‐seat Tecnam P2010 aircraft with a parallel hybrid‐electric powertrain, the first of its kind ever developed for general aviation, to help reduce fuel consumption while maintaining, and even extending, the aircraft range. The High Power, High Scalability Hybrid Powertrain project set out to design, build, ground‐test and demonstrate in a flight campaign such a propulsion system. Creating a parallel hybrid‐electric drive system, which brings together the electric and combustion engine worlds, creates a completely new set of challenges in the design, assembly, operation, and safety assurance of aircraft which must be addressed for a successful business proposition. The article reflects on some of the challenges faced as this innovative and scalable powertrain was developed on the road to minimise emissions in the aviation industry.
Transportation engineering, Applications of electric power
Using the one-way fluid-structure interaction method, the aerodynamic and strength performance of the last stages in high-pressure cylinder of a steam turbine were numerically investigated at four extraction percentages (0%, 8%, 15% and 20% of the total mass flow rate in stages). The aerodynamic efficiency of last stages, as well as the aerodynamic loads on the blades, was obtained under design and off-design conditions. With the computed aerodynamic loads, the strength performance of the last rotor blade was analyzed, and the maximum stress and deformation in rotor blade at various conditions were derived. The results show that the power output of last two stages is nearly linearly decreased with the increase of extraction percentage. If the extraction percentage equals to 20%, the power output is reduced by 44% as compared with the design case. As the extraction percentage increases, the total temperature at last stage outlet is gradually increased. With 20% extraction rate, the total temperature at last stage outlet is increased by about 10 ℃ compared with the design case. The extraction rate has a significant influence on the leakage performance in the tip and hub labyrinth seals of last stage, resulting in the variations of total-total isentropic efficiency, reaction degree and outlet flow angle distributions along the spanwise direction in the off-design conditions. The influence region in the last stage is mainly existed within 30% blade span near hubs due to varied extractions. Compared with the original design case, the total-total isentropic efficiency, reaction degree and outlet flow angle in the last stage are varied by 3.8%, 1.6% and 2.4° at most as the extraction percentage varies from 0 to 20%. With the centrifugal and aerodynamic forces, the maximum stress in the last stage rotor blade is occurred at the upstream side bottom fillet of T-shape root, and the maximum displacement in blade tip is 0.443 mm. As the extraction percentage increases, the maximum stress and maximum displacement in last stage rotor blade are almost linearly decreased.
Applications of electric power, Production of electric energy or power. Powerplants. Central stations
Meriem Ben Lazreg, Sabeur Jemmali, Bilal Manai
et al.
Abstract The precision of equivalent circuit model (ECM)‐based state of charge (SoC) estimation methods is vulnerable to the variation of the battery parameters, due to several internal and external factors. In this regard, this study proposes a fuzzy logic method for the approximate estimation of the ECM parameters at different temperatures and SoC levels. The fuzzy inference system is designed to handle the non‐linear deviation of the battery parameters from their reference values. On this basis, the extended Kalman filter and smooth variable structure filter are used to estimate the SoC. The two algorithms with fuzzy parameters (FP), namely FP‐EKF and FP‐SVSF, are tested on a 20 Ah Nickel Manganese Cobalt cell with maximum voltage of 4.2 V. The results show that the maximum root mean square error (RMSE) of the estimated SoC is kept within 1.51% with the FP‐EKF and 0.68% with the FP‐SVSF. Moreover, the reduction of the maximum absolute error may reach 0.34% with the FP‐EKF, and 0.82% with the FP‐SVSF, compared to the same algorithms without the proposed FP method. The executable codes are implemented on a low‐cost controller, and the average computational time is obtained as 215 μs, which confirms the real‐time practicality of the proposed method.
Transportation engineering, Applications of electric power
A Polymer Electrolytic Membrane Fuel Cell (PEMFC) is an efficient power device for automobiles, but its efficiency and life span depend upon its air delivery system. To ensure improved performance of PEMFC, the air delivery system must ensure proper regulation of Oxygen Excess Ratio (OER). This paper proposes two nonlinear control strategies, namely Integral Sliding Mode Control (ISMC) and Fast Terminal ISMC (FTISMC). Both the controllers are designed to control the OER at a constant level under load disturbances while avoiding oxygen starvation. The derived controllers are implemented in MATLAB/ Simulink. The corresponding simulation results depict that FTISMC has faster tracking performance and lesser fluctuations due to load disturbances in output net power, stack voltage/power, error tracking, OER, and compressor motor voltage. Lesser fluctuations in these parameters ensure increased efficiency and thus extended life of a PEMFC. The results are also compared with super twisting algorithm STA to show the effectiveness of the proposed techniques. ISMC and FTISMC yield 7% and 20% improved performance as compared to STA. The proposed research finds potential applications in hydrogen-powered fuel cell electric vehicles.
Abstract Switched reluctance motor drives are a common technology used in traction motor drives. Herein, an online method is proposed for the fault diagnosis of power transistors in the popular asymmetric half‐bridge power converter of the SRM drive. Based on the rearrangement of three current sensors, each phase current was first calculated by solving equations associated with their detected values and the drive signals of the transistors. The faults in the transistors were then preliminarily detected by monitoring the error between the calculated sum of currents and the sum of actual phase currents detected by a current sensor. Once a fault was identified, the actual states of all transistors of the power converter were solved for inversely using a mathematical model and the necessary rule for a trade‐off. Then, the faulty transistors and the fault types were identified by comparing the actual states with the drive signals. Compared with prevalent methods, the diagnostic range of the proposed scheme was wider, and its control modes and the number of motor phases were not limited. A higher accuracy than currently available methods was its prominent advantage. The effectiveness of the proposed solution was also validated on a three‐phase 6/4 SRM drive.
Abstract This work presents the comparative study of the linear tubular permanent magnet motor (LTPMM) for the active suspension system in vehicles. To analyse and design the LTPMM, a finite element‐based optimisation process is proposed. Since the proposed method reconstructs the entire field by storing the information of the air‐gap magnetic flux distribution in the form of a snapshot, it provides high accuracy and a reduced computation time. The magnetic fields are analysed in LTPMMs with external and internal permanent magnets that are classified according to the position of the permanent magnet. In the comparative analysis, an optimal model for the LTPMM is presented, taking into account characteristics such as thrust, detent force and THD. Especially, various magnetisation patterns are considered to accomplish high force density. The analytical model is verified by performing finite element analysis and experiments.
Danilo Santoro, Iñigo Kortabarria, Andrea Toscani
et al.
DC nanogrid architectures with Photovoltaic (PV) modules are expected to grow significantly in the next decades. Therefore, the integration of multi-port power converters and high-frequency isolation links are of increasing interest. The Triple Active Bridge (TAB) topology shows interesting advantages in terms of isolation, Zero Voltage Switching (ZVS) over wide load and input voltage ranges and high frequency operation capability. Thus, controlling PV modules is not an easy task due to the complexity and control stability of the system. In fact, the TAB power transfer function has many degrees of freedom, and the relationship between any of two ports is always dependent on the third one. In this paper we analyze the interfacing of photovoltaic arrays to the TAB with different solar conditions. A simple but effective control solution is proposed, which can be implemented through general purpose microcontrollers. The TAB is applied to an islanded DC nanogrid, which can be useful and readily implemented in locations where the utility grid is not available or reliable, and applications where isolation is required as for example More Electric Aircraft (MEA). Different conditions have been simulated and the control loops are proved for a reliable bus voltage control on the load side and a good maximum power point tracking (MPPT).
Abstract The increasing complexity of modern industrial systems calls for automatic and innovative predictive maintenance techniques. As suggested by the Industry 4.0 process, this demand translates in the need of more‐intelligent drives. Herein, the use of a special kind of neural networks to interpret the data from motor currents for diagnostic purposes is described. The early detection of possible faults in the electrical motor allows programmed maintenance and reduces the risk of unplanned shutdowns. The innovation is in the overall approach to the neural network training, which does not call anymore for a large set of faulty motors. A large training dataset generated using a combination of tuned motor models and some data augmentation techniques is proposed. The result is a comprehensive and effective motor condition monitoring algorithm, whose hearth is a convolutionary neural network trained by a safe and cheap simulation‐based dataset. The details of the design are fully reported here. The method has been implemented in the laboratory and fully tested on both healthy and faulty permanent magnet synchronous motors. The generality of the proposed method also paves the way for the detection of other failures and the application to different electrical motors.
Diego Perrone, Angelo Algieri, Pietropaolo Morrone
et al.
The work aims at investigating the techno-economic performance of a biodiesel micro combined heat and power (CHP) system for residential applications. The CHP unit is based on a direct-injection compression ignition engine providing 6.7 kW<sub>el</sub> and 11.3 kW<sub>th</sub>. A 0D model is developed and validated to characterise the behaviour of the biodiesel-fired engine at full and partial load in terms of efficiency, fuel consumption, and emissions. Furthermore, non-dimensional polynomial correlations are proposed to foresee the performance of biodiesel-fuelled engines for micro-CHP applications at partial loads. Afterwards, the CHP system is adopted to satisfy the electric and thermal demand of domestic users in Southern Italy. To this purpose, a parametric analysis is performed considering a different number of apartments and operating strategies (electric-driven and thermal-driven). A bi-variable optimisation based on the primary energy saving (<i>PES</i>) index and payback period (<i>PBT</i>) permits selecting the thermal-driven strategy and five apartments as the most suitable solution. The optimal <i>PBT</i> and <i>PES</i> are equal to 5.3 years and 22.4%, respectively. The corresponding annual thermal self-consumption reaches 81.3% of the domestic request, and the thermal surplus is lower than 8%. Finally, a sensitivity analysis is adopted to define the influence of the costs of energy vectors and a cogeneration unit on the economic feasibility of the biodiesel CHP system. The analysis highlights that the investigated apparatus represents an attractive option to satisfy the energy requests in micro-scale applications, providing valuable energy and economic advantages compared to traditional energy production.
The magnetic effects and consequently the radial force are the main causes of noise in switched reluctance motors (SRMs). In this study a new design for SRM is developed in order to reduce acoustic noise. In this research a new design for SRM is developed in order to reduce the acoustic noise. In this investigation, at first, different SRM structures are simulated using JMAG software. An 8/6‐pole SRM is designed and built with special modification in the rotor and stator structures. For increasing mechanical strength, trapezoidal stator and rotor pole shape with poles arc β r = β s = 21° are proposed. In this design the taper angles of stator and rotor poles are equal. For noise reduction, the mechanical restructuring is done according to stress analysis. The new designed SRM are simulated and tested experimentally under no‐load and full‐load conditions. The results are shown and compared. Comparison between these results and the results of other structures shows that the acoustic noise of the newly designed motor is reduced considerably. The results show an acoustic noise reduction of ∼72% in new structure SRM.