Search Results (1,144)

An overview of the Common Rail (CR) diesel engine challenges and of the promising state-of-the-art solutions for addressing them is provided. The different CR injector driving technologies have been compared, based on hydraulic, spray and engine performance for conventional diesel combustion. Various injection patterns, high injection pressures and nozzle design features are analyzed with reference to their advantages and disadvantages in addressing engine issues. The benefits of the statistically optimized engine calibrations have also been examined. With regard to the combustion strategy, the role of a CR engine in the implementation of low-temperature combustion (LTC) is reviewed, and the effect of the ECU calibration parameters of the injection on LTC steady-state and transition modes, as well as on an LTC domain, is illustrated. Moreover, the exploitation of LTC in the last generation of CR engines is discussed. The CR apparatus offers flexibility to optimize the engine calibration even for biofuels and e-fuels, which has gained interest in the last decade. The impact of the injection strategy on spray, ignition and combustion is discussed with reference to fuel consumption and emissions for both biodiesel and green diesel. Finally, the electrification of CR diesel engines is reviewed: the effects of electrically heated catalysts, electric supercharging, start and stop functionality and electrical auxiliaries on NO_x, CO₂, consumption and torque are analyzed. The feasibility of mild hybrid, strong hybrid and plug-in CR diesel powertrains is discussed. For the future, based on life cycle and manufacturing cost analyses, a roadmap for the automotive sector is outlined, highlighting the perspectives of the CR diesel engine for different applications. Full article

Model predictive control (MPC) has emerged as a favorable control approach for PMSM drives, though its practical deployment is frequently hindered by superior computational complexity and execution burden. This paper presents four finite control set MPC (FCS-MPC) techniques applied to a two-level inverter-fed PMSM drive. Two of the approaches are conventional methods, while the other two are novel developed strategies proposed in this paper. The novel techniques focus on significantly decreasing computational burdens by employing an efficient space-vector selection mechanism that quickly selects the optimum switching vector without exhaustive evaluation. A comprehensive comparative assessment of all four control methods is conducted under various operating conditions, evaluating their dynamic and steady-state performance, computational requirements, and real-time feasibility. Simulation results demonstrate that the proposed techniques achieve a significant reduction in computational effort and faster processing, up to 39.65% faster than conventional full-state evaluation, while maintaining control performances comparable to conventional techniques. These results highlight the potential of the proposed MPC approaches to bridge the gap between advanced control theory and practical implementation in real-time PMSM drive systems, providing effective solutions for installing high-performance PMSM drives on hardware with limited resources. Full article

Within the modernizing energy infrastructure of today, the integration of renewable energy sources and direct current (DC)-powered technologies calls for the re-examination of traditional alternative current (AC) networks. Low-voltage DC (LVDC) grids offer an attractive way forward in reducing conversion losses and simplifying local power management. However, ensuring reliable operation depends on a thorough understanding of DC distortions—phenomena generated by power converters, source instability, and varying loads. Two complementary traceable measurement chains are presented in this article with the purpose of measuring the steady-state DC component and the amplitude and frequency of the distortions around the DC bus with low uncertainties. One chain is optimized for laboratory environments, with high effectiveness in a controlled setup, and the other one is designed as a flexible and easily transportable solution, ensuring efficient and accurate assessments of DC distortions for field applications. In addition to our hardware solutions fully characterized by the uncertainty budget, we present the measurement method used for assessing DC distortions after evaluating the limitations of conventional AC techniques. Both arrangements are set to measure voltages of up to 1000 V, currents of up to 30 A, and frequency components of up to 150–500 kHz, with an uncertainty varying from 0.01% to less than 1%. This level of accuracy in the measurements will allow us to draw reliable conclusions regarding the dynamic behavior of future LVDC grids. Full article

The increasing integration of renewable energy sources (RES) and rising energy demand have created challenges in maintaining stability in interconnected power systems, particularly in terms of frequency, voltage, and tie-line power. While traditional load frequency control (LFC) and automatic voltage regulation (AVR) strategies have been widely studied, they often fail to address the complexities introduced by RES and nonlinear system dynamics such as boiler dynamics, governor deadband, and generation rate constraints. This study introduces the Arithmetic Optimization Algorithm (AOA)-optimized PI(1+DD) controller, chosen for its ability to effectively optimize control parameters in highly nonlinear and dynamic environments. AOA, a novel metaheuristic technique, was selected due to its robustness, efficiency in exploring large search spaces, and ability to converge to optimal solutions even in the presence of complex system dynamics. The proposed controller outperforms classical methods such as PI, PID, I–P, I–PD, and PI–PD in terms of key performance metrics, achieving a settling time of 7.5 s (compared to 10.5 s for PI), overshoot of 2.8% (compared to 5.2% for PI), rise time of 0.7 s (compared to 1.2 s for PI), and steady-state error of 0.05% (compared to 0.3% for PI). Additionally, sensitivity analysis confirms the robustness of the AOA-optimized controller under ±25% variations in turbine and speed control parameters, as well as in the presence of nonlinearities, demonstrating its potential as a reliable solution for improving grid performance in complex, nonlinear multi-area interconnected power systems. Full article

This paper proposes an enhanced Model Predictive Direct Speed Control (MPDSC) framework for Permanent Magnet Synchronous Motor (PMSM) drives, integrating duty ratio optimization and load torque disturbance compensation to significantly improve both transient and steady-state performance. Traditional finite-control-set MPC strategies, which apply a single voltage vector per sampling interval, often suffer from steady-state ripples, elevated total harmonic distortion (THD), and high computational complexity due to exhaustive switching evaluations. The proposed approach addresses these limitations through a novel dual-stage cost function structure: the first cost function optimizes dynamic response via predictive control of speed error, while the second adaptively minimizes torque ripple and harmonic distortion by adjusting the active–zero voltage vector duty ratio without the need for manual weight tuning. Robustness against time-varying disturbances is further enhanced by integrating a real-time load torque observer into the control loop. The scheme is validated through both MATLAB/Simulink R2020a simulations and real-time experimental testing on a dSPACE 1202 rapid control prototyping platform across small- and large-scale PMSM configurations. Experimental results confirm that the proposed controller achieves a transient speed deviation of just 0.004%, a steady-state ripple of 0.01 rpm, and torque ripple as low as 0.0124 Nm, with THD reduced to approximately 5.5%. The duty ratio-based predictive modulation ensures faster settling time, improved current quality, and greater immunity to load torque disturbances compared to recent duty-ratio MPC implementations. These findings highlight the proposed DR-MPDSC as a computationally efficient and experimentally validated solution for next-generation PMSM drive systems in automotive and industrial domains. Full article

The need for non-toxic chemical propulsion systems is growing stronger in today’s space sector. One of the possible solutions for next-generation bipropellant systems is using hydrogen peroxide as the oxidizer. However, there is limited knowledge about using 98% High-Test Peroxide (HTP), which can enable high mass and volumetric performance. Therefore, this paper presents an overview of the development of green bipropellant technology using 98% HTP. The goal is to cover nearly 15 years of experience with 98% HTP and over 10 years of the use of bipropellants containing 98% HTP. The development approach and methods, including component testing and hot-firing, are described. This paper provides test data for various types of bipropellant thrusters and engines producing between 20 and 7000 N of thrust in vacuum, which is the range typically utilized for in-space propulsion. Fuel ignition processes via utilization of a catalyst bed and via hypergolic ignition are analyzed. Successful demonstrations under different operating requirements (steady state, pulse-mode operations, throttleability, etc.) are discussed. The obtained results show that green bipropellants could compete with traditional storable bipropellant technologies. The challenges and opportunities associated with using HTP bipropellants in complete propulsion systems are listed. This paper concludes with recommendations for further research. Full article

This paper proposes a multi-objective collaborative optimization method based on a two-layer optimization framework to address the problem of difficult coordinated optimization of multi-parameter coupling in the frequency regulation performance of heating units under deep peak shaving conditions. The upper-level optimization of this method focuses on the dynamic performance of primary frequency modulation and improves the fast response capability through multi-objective optimization of overshoot and adjustment time. Lower-level optimization is based on the optimal control parameter set output by the upper level, with comprehensive power deviation as the indicator, focusing on suppressing the deviation of frequency modulation power and the steady-state deviation of heating power. Propose a comprehensive quantitative index for frequency modulation performance and characterize the optimization effect of frequency modulation performance. Introducing a dynamic perturbation factor mechanism to generate an improved HO algorithm for dual-layer optimization solutions, preventing it from getting stuck in local optima and solving the problem of global search capability imbalance. The effectiveness of the method was verified based on actual unit calculations, and the obtained control parameter set met the objectives of optimal primary frequency regulation dynamic performance and optimal comprehensive power deviation performance, significantly improving the frequency regulation performance of heating units under deep peak shaving. After optimization, the overshoot performance score of the unit increased by 16.9%, the regulation time performance score increased by 25.1%, the frequency modulation power deviation score increased by 14.2%, the heating power deviation score increased by 17.7%, and the total frequency modulation performance score increased from 75.26 to 95.95, with a comprehensive optimization range of 27.5%. Full article

The integration of multiple renewable and storage units in electric vehicle (EV) hybrid energy systems presents significant challenges in stability, dynamic response, and disturbance rejection, limitations often encountered with conventional sliding mode control (SMC) and super-twisting SMC (STSMC) schemes. This paper proposes a condition-based integral terminal super-twisting sliding mode control (CBITSTSMC) strategy, with gains optimally tuned using an improved gray wolf optimization (I-GWO) algorithm, for coordinated control of a multi-source DC–DC converter system comprising photovoltaic (PV) arrays, fuel cells (FCs), lithium-ion batteries, and supercapacitors. The CBITSTSMC ensures finite-time convergence, reduces chattering, and dynamically adapts to operating conditions, thereby achieving superior performance. Compared to SMC and STSMC, the proposed controller delivers substantial reductions in steady-state error, overshoot, and undershoot, while improving rise time and settling time by up to 50%. Transient stability and disturbance rejection are significantly enhanced across all subsystems. Controller-in-the-loop (CIL) validation on a Delfino C2000 platform confirms the real-time feasibility and robustness of the approach. These results establish the CBITSTSMC as a highly effective solution for next-generation EV hybrid energy management systems, enabling precise power-sharing, improved stability, and enhanced renewable energy utilization. Full article

The adoption of synchronous optimal pulse-width modulation (SOPWM) in two-level voltage-source inverters (2L-VSIs) offers low switching-to-fundamental-frequency ratio (SFR) operation while maintaining reduced current total harmonic distortion (THD). Despite these advantages, the performance of SOPWM is highly sensitive to signal noise in the modulation index and reference voltage angle. To prevent degradation, conventional PI controllers are conservatively tuned with slow dynamic response, which limits overall system performance. Finite control set model predictive control (FCS-MPC) integrated with SOPWM offers a promising solution, combining the fast dynamic response of FCS-MPC with the optimal steady-state performance of SOPWM. Nevertheless, the intricate tuning of weighting factors in FCS-MPC presents a significant challenge, particularly in balancing between enhanced harmonic performance and fast dynamic response. This paper introduces a simplified FCS-MPC approach that eliminates the need for complex weighting factor tuning while retaining the excellent dynamic performance of FCS-MPC and ensuring the low current THD achieved by SOPWM under steady-state conditions. The efficacy of the proposed method is validated through MATLAB/Simulink (R2023b) simulations and experimental results. Full article

This study investigates steady-state heat conduction in materials with stepwise discontinuities in thermal conductivity, a phenomenon frequently encountered in layered composites, thermal barrier coatings, and electronic packaging. The problem is formulated for a 2D two-domain region, where each subdomain has a distinct constant conductivity. Both the direct problem—determining the temperature field from known conductivities—and the inverse problem—identifying conductivities and the internal heat source from limited temperature measurements—are addressed. To this end, three deterministic finite-difference-type models are developed: two for the standard formulation and one for a meshless formulation based on Moving Least Squares (MLS), all derived within a local framework that efficiently enforces interface conditions. In addition, two Monte Carlo models are proposed—one for the standard and one for the meshless setting—providing pointwise estimates of the solution without requiring computation over the entire domain. Finally, an algorithm for solving inverse problems is introduced, enabling the reconstruction of material parameters and internal sources. The performance of the proposed approaches is assessed through 2D benchmark problems of varying geometric complexity, including both structured grids and irregular node clouds. The numerical experiments cover convergence studies, sensitivity of inverse reconstructions to measurement noise and input parameters, and evaluations of robustness across different conductivity contrasts. The results confirm that the hybrid difference-meshless Monte Carlo framework delivers accurate temperature predictions and reliable inverse identification, highlighting its potential for engineering applications in thermal design optimization, material characterization, and failure analysis. Full article

The global timber construction market is experiencing steady growth, driven by increasing demand for sustainable building solutions, advancements in engineered timber technologies, and supportive policy frameworks. This study provides an overview of the global market for timber construction. Current status and industrial perspectives of the key timber construction markets from Australia, the United States, Austria, Switzerland, Finland, Sweden, Germany, and the SUDOE region (Southwest France, Portugal and Spain) are discussed and summarized. It was found that key markets such as Europe, North America, and Australia are leading this shift in the construction of more timber buildings, with growing numbers of mid- and high-rise timber projects. Industry voices highlight both the opportunities, such as carbon reduction, reduced construction times, and timber design benefits, and the challenges, including supply chain limitations, cost competitiveness, building code restrictions, and a need for broader industry education. Collaboration across architects, engineers, developers, and policymakers is emphasized as essential to scaling mass timber adoption in mainstream construction practices. Full article

The complex condition of an adjacent tunnel in urban city includes high water content, limited construction space, and the presence of an adjacent tunnel. To address these challenges, the artificial ground freezing method is employed to ensure construction safety and stability. Considering the complex problem of temperature field interaction in the freezing construction process of adjacent tunnels, for the first time, this paper proposes a generalized analytical solution for two-dimensional steady-state temperature fields suitable for the annular double-loop freezing system of adjacent tunnels. Based on the polar coordinate heat conduction control equation and the conformal transformation method, the complex geometric arrangement is mapped into a linear system that can be solved, and the analytical solution expression is constructed by combining the heat source superposition principle. In this paper, a numerical model of the adjacent tunnel annular double-loop freezing pipe is established through COMSOL Multiphysics 6.2 software. At the same time, the formula of the analytical method is programmed and solved using Python 3.12, and finally the temperature fields obtained by the two methods are compared. The results show that the analytical solution has good consistency in isotherm distribution, temperature field trend and characterization of frozen core area, which verifies the theoretical rationality and practicability of the constructed model. Full article

We perform large-eddy simulations (LESs) with realistic radiation, including topographic shading, and an advanced land surface model to investigate drainage flow dynamics in an idealized compound-slope mountain geometry. This allows an analysis not only of fully developed profiles in steady state—the subject of existing analytical solutions—but also of transient two- and three-dimensional dynamics. The evening onset of downslope flow is related to the duration of shadow front propagation along the eastern slopes, for which an analytic form is derived. We demonstrate that the flow response to this radiation pattern is mediated by the thermal inertia of the land through sensitivity to soil moisture. Onset timing differences on opposite sides of the peak are explained by convective structures that persist after sunset over the western slopes when topographic shading is considered. Although these preceding convective systems, as well as the presence of neighboring terrain, inhibit the initial development of drainage flows, the LES develops an approximately steady-state, fully developed flow over the finite slopes and finite nocturnal period. This allows a comparison to analytical models restricted to such cases. New analytical solutions based on surface heat flux boundary conditions, which can be estimated by the coupled land surface model, suggest the need for improved representation of the eddy diffusivity for analytical models of drainage flows. Full article

This work presents the results of a research study focused on the development and evaluation of an algorithmic optimal control framework for energy-efficient operation of screw compressors in smart power systems. The proposed approach is based on the Pontryagin maximum principle (PMP), which enables the synthesis of a mathematically grounded regulator that minimizes the total energy consumption of a nonlinear electromechanical system composed of a screw compressor and a variable-frequency induction motor. Unlike conventional PID controllers, the developed algorithm explicitly incorporates system constraints, nonlinear dynamics, and performance trade-offs into the control law, allowing for improved adaptability and energy-aware operation. Simulation results obtained using MATLAB/Simulink confirm that the PMP-based regulator outperforms classical PID solutions in both transient and steady-state regimes. Experimental tests conducted in accordance with standard energy consumption evaluation methods showed that the proposed PMP-based controller provides a reduction in specific energy consumption of up to 18% under dynamic load conditions compared to a well-tuned basic PID controller, while maintaining high control accuracy, faster settling, and complete suppression of overshoot under external disturbances. The control system demonstrates robustness to parametric uncertainty and load variability, maintaining a statistical pressure error below 0.2%. The regulator’s structure is compatible with real-time execution on industrial programmable logic controllers (PLCs), supporting integration into intelligent automation systems and smart grid infrastructures. The discrete-time PLC implementation of the regulator requires only 10³ arithmetic operations per cycle and less than 10² kB of RAM for state, buffers, and logging, making it suitable for mid-range industrial controllers under 2–10 ms task cycles. Fault-tolerance is ensured via range and rate-of-change checks, residual-based plausibility tests, and safe fallbacks (baseline PID or torque-limited speed hold) in case of sensor faults. Furthermore, the proposed approach lays the groundwork for hybrid extensions combining model-based control with AI-driven optimization and learning mechanisms, including reinforcement learning, surrogate modeling, and digital twins. These enhancements open pathways toward predictive, self-adaptive compressor control with embedded energy optimization. The research outcomes contribute to the broader field of algorithmic control in power electronics, offering a scalable and analytically justified alternative to heuristic and empirical tuning approaches commonly used in industry. The results highlight the potential of advanced control algorithms to enhance the efficiency, stability, and intelligence of energy-intensive components within the context of Industry 4.0 and sustainable energy systems. Full article

With the increasing deployment of unmanned surface vessels (USVs) in complex marine operations such as ocean monitoring, search and rescue, and military reconnaissance, precise heading control under environmental disturbances and system delays has become a critical challenge. This paper presents an advanced robust heading control strategy for USVs operating under these demanding conditions. The proposed approach integrates three key innovations: (1) an enhanced Smith predictor for accurate time-delay compensation, (2) a variable-universe fuzzy PID controller with self-adaptive scaling domains that dynamically adjust to error magnitude and rate of change, and (3) a hybrid metaheuristic optimization algorithm combining beetle antennae search, harmony search, and genetic algorithm (BAS-HSA-GA) for optimal parameter tuning. Through comprehensive simulations using a Nomoto first-order time-delay model under combined white noise and second-order wave disturbances, the system demonstrates superior performance with over 90% reduction in steady-state heading error and ≈30% faster settling time compared to conventional PID and single-optimization fuzzy PID methods. Field trials under sea-state 4 conditions confirm 15–25% lower tracking error in realistic operating scenarios. The controller’s stability is rigorously verified through Lyapunov analysis, while comparative studies show significant improvements in S-shaped path tracking performance, achieving better IAE/ITAE metrics than DRL, ANFC, and ACO approaches. This work provides a comprehensive solution for high-precision, delay-resilient USV heading control in dynamic marine environments. Full article