Search Results (2,536)

Aviation is under increasing pressure to reduce carbon emissions in conventional transports and support the growth of low-altitude operations such as long-endurance eVTOLs. Hybrid-electric propulsion addresses these challenges by integrating the high specific energy of fuels or hydrogen with the controllability and efficiency of electrified powertrains. At present, the field of hybrid-electric aircraft is developing rapidly. To systematically study hybrid-electric propulsion control in aviation, this review focuses on practical aspects of system development, including propulsion architectures, system- and component-level modeling approaches, and energy management strategies. Key technologies in the future are examined, with emphasis on aircraft power-demand prediction, multi-timescale control, and thermal integrated energy management. This review aims to serve as a reference for configuration design, modeling and control simulation, as well as energy management strategy design of hybrid-electric propulsion systems. Building on this reference role, the review presents a coherent guidance scheme from architectures through modeling to energy-management control, with a practical roadmap toward flight-ready deployment. Full article

Battery technology plays an increasingly vital role in portable electronic devices, electric vehicles, and renewable energy storage. During operation, batteries undergo performance degradation, which not only reduces device efficiency, but may also pose safety risks. The State of Health (SOH) is a crucial indicator for assessing battery condition. Traditional SOH prediction methods face limitations in real-time adjustment and accuracy under complex operating conditions. By determining electrode capacity loss and identifying complex patterns that traditional methods struggle to detect, prediction accuracy can be improved. Based on electrode capacity matching and compensation relationships, this paper proposes an electrode capacity balance model to evaluate battery development trends and degradation during cycling. We use q_Li − q_p state assessment as a trend criterion, q_p to quantify aging, and Q_c to identify thermal runaway risk levels, developing more efficient SOH prediction indicators and methods to ensure battery safety and performance. Full article

Fuel cell trucks are a promising solution to reduce the disproportionately high greenhouse gas emissions of heavy-duty long-haul transportation. However, unlike conventional diesel vehicles, they lack combustion engine waste heat for cabin heating. As a result, electric heaters are often employed, which increase auxiliary energy consumption and reduce driving range. To address this challenge, advanced control strategies are needed to improve heating efficiency while maintaining passenger comfort. This study proposes and validates a methodology for implementing Model Predictive Control (MPC) in the cabin heating system of a fuel cell truck. Vehicle experiments were conducted to characterize dynamic heating behavior, passenger comfort indices, and to provide validation data for the mathematical models. Based on these models, an MPC strategy was developed in a Model-in-the-Loop simulation environment. The proposed approach achieves energy savings of up to 8.1% compared with conventional control using purely electric heating, and up to 21.7% when cabin heating is coupled with the medium-temperature cooling circuit. At the same time, passenger comfort is maintained within the desired range (PMV within ±0.5 under typical winter conditions). The results demonstrate the potential of MPC to enhance the energy efficiency of fuel cell trucks. The methodology presented provides a validated foundation for the further development of predictive thermal management strategies in heavy-duty zero-emission vehicles. Full article

In lithium-ion battery charging, balancing charging speed with efficiency and state of health (SOH) is paramount. First, a multi-state electric-thermal-aging coupling model was developed to accurately reflect battery operating conditions. Second, a voltage-based multi-stage constant current-constant voltage (VMCC-CV) strategy was implemented, incorporating an innovative V-SOC-R_int conversion mechanism—integrating voltage, state of charge (SOC), and internal resistance—to effectively mitigate thermal buildup during transitions. To optimize the VMCC-CV currents, an innovative enhancement was applied to the moth-flame optimization (MFO) algorithm, demonstrating superior performance over its traditional counterpart across diverse charging scenarios. Finally, three practical strategies were devised: rapid charging, multi-objective balanced charging, and enhanced safety performance charging. Relative to the manufacturer’s 0.75 C-CCCV protocol, the balanced strategy significantly accelerates charging, reducing time by 34.11%, while sustaining 93.54% efficiency and limiting SOH degradation to 0.006856%. Compared to conventional CCCV methods, the proposed approach offers greater versatility and applicability in varied real-world scenarios. Full article

To address the complex trade-offs among charging efficiency, battery lifespan, energy efficiency, and safety in high-power electric vehicle (EV) fast charging, this paper presents an intelligent control framework based on contrastive learning and manifold-constrained multi-objective optimization. A multi-physics coupled electro-thermal-chemical model is formulated as a Mixed-Integer Nonlinear Programming (MINLP) problem, incorporating both continuous and discrete decision variables—such as charging power and cooling modes—into a unified optimization framework. An environment-adaptive optimization strategy is also developed. To enhance learning efficiency and policy safety, a contrastive learning–enhanced policy gradient (CLPG) algorithm is proposed to distinguish between high-quality and unsafe charging trajectories. A manifold-aware action generation network (MAN) is further introduced to enforce dynamic safety constraints under varying environmental and battery conditions. Simulation results demonstrate that the proposed framework reduces charging time to 18.3 min—47.7% faster than the conventional CC–CV method—while achieving 96.2% energy efficiency, 99.7% capacity retention, and zero safety violations. The framework also exhibits strong adaptability across wide temperature (−20 °C to 45 °C) and aging (SOH down to 70%) conditions, with real-time inference speed (6.76 ms) satisfying deployment requirements. This study provides a safe, efficient, and adaptive solution for intelligent high-power EV fast-charging. Full article

Modern power systems require better heat dissipation and thermal stability, but traditional low-filler composites cannot significantly enhance thermal conductivity. To address this issue, electric field induction technology orientation can efficiently orient boron nitride nanosheets (BNNSs), thereby improving the thermal conductivity of epoxy composites composed of BNNSs as the thermally conductive filler. In this study, an innovative approach employing a pulsed superimposed direct current (DC) electric field to synergistically induce filler orientation is used to construct efficient thermally conductive channels. The study found that the thermal conductivity of the composite prepared by superimposing an 8 kV/mm pulsed electric field on a 30 V/mm DC electric field is about 0.474 W/(m·K), which is 34.66% higher than that prepared by only a pulsed-induced field and 17.5% higher than the theoretical superposition value. Similarly, the composite prepared by superimposing a 4 kV/mm pulsed electric field on a 70 V/mm DC electric field increased to about 0.464 W/(m·K), which is 27.47% higher than that prepared by only a DC-induced field and 12.4% higher than the theoretical superposition value. These results indicate that the superimposed electric field treatment synergistically improves the thermal conductivity of the composite. Compared to other materials, composites prepared using the superimposed pulsed and DC electric field induction also exhibit superior thermal stability. This strategy effectively addresses the issue of material thermal aging caused by insufficient thermal conductivity, providing innovative ideas and a solid theoretical foundation for material design and thermal management. Full article

Glazed façades play a decisive role in building energy performance, particularly in high-radiation equatorial climates. This study examines the thermal behavior and economic feasibility of three glazing systems—10 mm monolithic clear glass, laminated solar-control glass, and selective double glazing—applied to the Plataforma Gubernamental Norte, the largest institutional building in Ecuador. Dynamic simulations using DesignBuilder with the EnergyPlus engine assessed solar gains, HVAC demand, and operative temperatures, complemented by a sensitivity analysis of SHGC, U-value, and Tvis. Results indicate that selective double glazing reduced annual HVAC consumption by 78.21% (110.6 MWh), while laminated glazing achieved a 55.40% reduction. SHGC and U-value emerged as the most influential parameters, whereas Tvis had no impact on energy loads. Despite strong technical performance, the economic analysis revealed payback periods exceeding 235 years under Ecuador’s subsidized tariff (USD 0.10/kWh), compared to the 18–25 years commonly observed in Europe. This highlights the “efficiency paradox”: advanced glazing solutions deliver significant energy savings but remain financially unfeasible in subsidy-driven contexts. The findings underscore the need for policy reforms to better align façade design strategies with energy resilience, an issue particularly relevant after Ecuador’s 2024 electricity crisis and ongoing debates on subsidy elimination. Full article

This work explores the integration of Proton Exchange Membrane (PEM) electrolysis waste heat with district heating networks (DHN), aiming to enhance the overall energy efficiency and economic viability of hydrogen production systems. PEM electrolysers generate substantial amounts of low-temperature waste heat during operation, which is often dissipated and left unutilised. By recovering such thermal energy and selling it to district heating systems, a synergistic energy pathway that supports both green hydrogen production and sustainable urban heating can be achieved. The study investigates how the electrolyser’s operating temperature, ranging between 50 and 80 °C, influences both hydrogen production and thermal energy availability, exploring trade-offs between electrical efficiency and heat recovery potential. Furthermore, the study evaluates the compatibility of the recovered heat with common heat emission systems such as radiators, fan coils, and radiant floors. Results indicate that valorising waste heat can enhance the overall system performance by reducing the electrolyser’s specific energy consumption and its levelized cost of hydrogen (LCOH) while supplying carbon-free thermal energy for the end users. This integrated approach contributes to the broader goal of sector coupling, offering a pathway toward more resilient, flexible, and resource-efficient energy systems. Full article

In this study, the performance and reliability of two different types of Braille modules, i.e., coil and piezoelectric, under varying temperature conditions were compared. The coil module works on the principle of electromagnetic forces generated by coils, while the piezoelectric module is based on the deformation of piezoelectric materials under electric voltage to move needles. The main purpose of this research was to discuss the stability and functionality of both modules within the temperature range from −30 °C to +50 °C. One thousand cycles of operation were conducted for each temperature step in 5 °C increments, focusing on the correctness of needle movement and system reliability. The results demonstrated that the piezoelectric module exhibited stable operation over the entire temperature range, while the coil module showed instabilities, such as self-jamming and overheating, above 20 °C. These problems were probably due to thermal expansion and reduced lubrication efficiency. These results underscore the piezoelectric module’s improved adaptation to high-temperature operation, making it a promising solution for applications requiring reliable operation under varying conditions. Full article

This study examines the mechanical, thermal, and electrical properties of copper tool electrodes processed via Equal Channel Angular Pressing (ECAP), with a specific focus on their performance in Electrical Discharge Machining (EDM) applications. A novel Crystal Plasticity Finite Element Method (CPFEM) framework is employed to model anisotropic slip behavior and microscale deformation mechanisms. The primary objective is to elucidate how initial crystallographic orientation influences hardness, thermal conductivity, and electrical conductivity. Simulations are performed on single-crystal copper for three representative Face Centered Cubic (FCC) orientations. Using an explicit CPFEM model, the study examines texture evolution and deformation heterogeneity during the ECAP process of single-crystal copper. The results indicate that the <100> single-crystal orientation exhibits the highest Taylor factor and the most homogeneous distribution of plastic equivalent strain (PEEQ), suggesting enhanced resistance to plastic flow. In contrast, the <111> single-crystal orientation displays localized deformation and reduced hardening. A decreasing Taylor factor correlates with more uniform slip, which improves both electrical and thermal conductivity, as well as machinability, by minimizing dislocation-related resistance. These findings make a novel contribution to the field by highlighting the critical role of crystallographic orientation in governing slip activity and deformation pathways, which directly impact thermal wear resistance and the fabrication efficiency of ECAP-processed copper electrodes in EDM. Full article

This article presents a gear selection methodology for electric vehicle powertrains employing two identical Permanent Magnet Synchronous Machines (PMSMs) arranged in a twin-drive configuration. Both machines are coupled through a shared output shaft and operate with coordinated torque–speed characteristics, enabling efficient utilization of the available gear stages. The proposed approach establishes a control-oriented drivetrain framework that incorporates mechanical dynamics together with real-time thermal states and loss mechanisms. Unlike conventional strategies, which rely mainly on static or speed-based shifting rules, the method integrates detailed thermal and electromagnetic loss modeling directly into the gear-shifting logic. By accounting for the dynamic thermal behavior of PMSMs under variable load conditions, the strategy aims to reduce cumulative drivetrain losses, including electromagnetic, thermal, and mechanical, while maintaining high efficiency. The methodology is implemented in a MATLAB/Simulink R2024a and LabVIEW 2024Q2 co-simulation environment, where thermal feedback and instantaneous efficiency metrics dynamically guide gear selection. Simulation results demonstrate measurable improvements in energy utilization, particularly under transient operating conditions. The resulting efficiency maps are broader and flatter, as the motors’ operating points are continuously shifted toward zones of optimal performance through adaptive gear ratio control. The novelty of this work lies in combining real-time loss modeling, thermal feedback, and coordinated gear management in a twin-motor system, validated through experimentally motivated efficiency maps. The findings highlight a scalable and dynamic control framework suitable for advanced electric vehicle architectures, supporting intelligent efficiency-oriented drivetrain strategies that enhance sustainability, thermal management, and system performance across diverse operating conditions. Full article

The aim of this paper is to present a novel and comprehensive methodology for the dynamic modeling and experimental validation of a photovoltaic/thermal system. The dynamic model is divided into thermal and electrical subsystems, encompassing the photovoltaic/thermal module and the thermal energy storage. The thermal subsystem of both the photovoltaic/thermal module and the thermal energy storage is described by a one-dimensional dynamic model of heat transfer mechanisms and optical losses, while the electrical subsystem is presented as an electrical equivalent circuit of double diode solar cell. Model validation was conducted on a modern experimental photovoltaic/thermal system over an extended operational period at a five-minute resolution, with validation days classified as sunny, cloudy, or overcast based on weather conditions, thereby demonstrating an applied approach. The results demonstrate the lowest deviation values reported to date, confirmed using six quantitative indicators. The added value of the proposed methodology, not previously addressed in the literature, lies in the following contributions: (i) comprehensive modeling of the entire photovoltaic/thermal system, (ii) accurate consideration of optical losses in the photovoltaic/thermal module, and (iii) long-term experimental validation. Overall, the proposed methodology provides a reliable and efficient framework for PV/T system design, optimization, and long-term performance assessment. Full article

Railway turnouts are highly susceptible to snow and ice accumulation during winter, which can cause malfunctions, resulting in train delays or, in extreme cases, derailments with potential casualties. To mitigate these risks, resistive heating (RH) systems using nichrome wires have traditionally been employed. However, these systems suffer from slow heat transfer and high power consumption. To address these limitations, this article proposes an induction heating (IH) system designed for rapid thermal response and improved electrical and thermal efficiency. The proposed system comprises a power conversion unit featuring a boost power factor correction (PFC) stage and a high-frequency resonant inverter, along with an improved IH coil. An experiment in real snowfall demonstrates the IH system’s fast heat-up capability, effective snow cover removal, and enhanced energy efficiency compared to conventional methods. Full article

Municipal solid waste (MSW) disposal is one of the areas of sustainability development of modern countries including the Republic of Kazakhstan. Annually, more than 4 million tons of MSW are generated, and this amount continues to grow. Additionally, approximately 120 million tons of waste have already accumulated in landfills across the country. It is essential to select an MSW disposal technology that is environmentally friendly, minimizes the generation of more hazardous waste, and maximizes energy efficiency. Ideally, the technology should not only reduce energy consumption but also generate energy and valuable by-products that have market demand. The aim of this study is to conduct experimental research to evaluate the efficiency and environmental impact of incinerating both unsorted and sorted municipal solid waste. As a result of the experiment, the volumes of flue gases and the concentrations of harmful substances produced by the combustion of both unsorted and sorted waste were determined. Additionally, an analysis of the slag and ash generated from the combustion of sorted MSW was conducted. The obtained results enable the development of a waste-free technological scheme for a plant designed for the complete utilization of municipal solid waste. Full article

With the rapid development of the electric vehicle (EV) industry, the regenerative braking system (RBS) has become a pivotal technology for enhancing overall vehicle energy efficiency and safety. This article systematically reviews recent research advances, spanning macro-architecture, drive and energy-storage hardware, control strategies, and evaluation frameworks. It focuses on comparing the mechanisms and performance of six categories of intelligent control algorithms—fuzzy logic, neural networks, model predictive control, sliding-mode control, adaptive control, and learning-based algorithms—and, leveraging the structural advantages of four-wheel independent drive (4WID) electric vehicles, quantitatively analyzes improvements in energy-recovery efficiency and coordinated vehicle-dynamics control. The review further discusses how high-power-density motors, hybrid energy storage, brake-by-wire systems, and vehicle-road cooperation are pushing the upper limits of RBS performance, while revealing current technical bottlenecks in high-power recovery at low speeds, battery thermal safety, high-dimensional real-time optimization, and unified evaluation standards. A closed-loop evolutionary roadmap is proposed, consisting of the following stages: system integration, intelligent control, scenario prediction, hardware upgrading, and standard evaluation. This roadmap emphasizes the central roles of deep reinforcement learning, hierarchical model predictive control (MPC), and predictive energy management in the development of next-generation RBS. This review provides a comprehensive and forward-looking reference framework, aiming to accelerate the deployment of efficient, safe, and intelligent regenerative braking technologies. Full article