Search Results (887)

The High-Pressure Common Rail System (HPCRS) is designed based on fundamental hydrodynamic principles, after which this paper formally defines the key control challenges. The proposed continuous sliding mode control strategy is developed based on a non-singular terminal sliding mode framework, integrated with an improved power reaching law. This design effectively eliminates chattering and achieves fast dynamic response with enhanced tracking precision. Subsequently, a bidirectional adaptive mechanism is integrated into the proposed control scheme to eliminate the necessity for a priori knowledge of unknown disturbances within the HPCRS. This mechanism enables real-time evaluation of the system’s state relative to a predefined detection region. To validate the effectiveness of the proposed strategy, experimental studies are conducted under three distinct operating conditions. The experimental results indicate that, compared with conventional rail pressure controllers, the proposed method achieves superior tracking accuracy, faster dynamic response, and improved disturbance rejection. Full article

This work proposes an effective control technique for enhancing the stability of Doubly Fed Induction Generator-Based Wind Turbines (DFIG-WTs) connected to the grid during voltage sag and swell events, ensuring the reliable and efficient operation of wind energy systems integrated with the grid. The proposed approach integrates a Dynamic Voltage Restorer (DVR) in series with a Wind Turbine Generator (WTG) output terminal to enhance the Fault Ride-Through (FRT) capability during grid disturbances. To develop a flexible control strategy for both unbalanced and balanced fault conditions, a combination of feedforward and feedback control based on a sliding mode control (SMC) for DVR converters is used. This hybrid strategy allows for precise voltage regulation, enabling the series compensator to inject the required voltage into the grid, thereby ensuring constant generator terminal voltages even during faults. The SMC enhances the system’s robustness by providing fast, reliable regulation of the injected voltage, effectively mitigating the impact of grid disturbances. To further enhance system performance, Model Predictive Control (MPC) is implemented for the Rotor-Side Converter (RSC) within the back-to-back converter (BTBC) configuration. The main advantages of the predictive control method include eliminating the need for linear controllers, coordinate transformations, or modulators for the converter. Additionally, it ensures the stable operation of the generator even under severe operating conditions, enhancing system robustness and dynamic response. To validate the proposed control strategy, a comprehensive simulation is conducted using a 2 MW DFIG-WT connected to a 120 kV grid. The simulation results demonstrate that the proposed control approach successfully limits overcurrent in the RSC, maintains electromagnetic torque and DC-link voltage within their rated values, and dynamically regulates reactive power to mitigate voltage sags and swells. This allows the WTG to continue operating at its nominal capacity, fully complying with the strict requirements of modern grid codes and ensuring reliable grid integration. Full article

The large-scale integration of volatile and intermittent renewables necessitates greater flexibility in the power system. Improving this flexibility is key to achieving a high proportion of renewable energy consumption. In this context, the scientific selection of energy storage technology is of great significance for the construction of new power systems. From the perspective of life cycle cost analysis, this paper conducts an economic evaluation of four mainstream energy storage technologies: lithium iron phosphate battery, pumped storage, compressed air energy storage, and hydrogen energy storage, and quantifies and compares the life cycle cost of multiple energy storage technologies. On this basis, a three-dimensional multi-energy storage comprehensive evaluation indicator system covering economy, technology, and environment is constructed. The improved grade one method and entropy weight method are used to determine the comprehensive performance, and the fuzzy comprehensive evaluation method is used to carry out multi-attribute decision-making on the multi-energy storage technology in the source, network, and load scenarios. The results show that pumped storage and compressed air energy storage have significant economic advantages in long-term and large-scale application scenarios. With its fast response ability and excellent economic and technical characteristics, the lithium iron phosphate battery has the smallest score change rate (15.2%) in various scenarios, showing high adaptability. However, hydrogen energy storage technology still lacks economic and technological maturity, and breakthrough progress is still needed for its wide application in various application scenarios in the future. Full article

The automotive suspension must perform competently to support comfort and safety when driving. Traditionally, car suspension control tuning is performed through trial and error or with classical techniques that cannot guarantee optimal performance under varying road conditions. The study aims at designing a Linear Quadratic Regulator-based Bacterial Memetic Algorithm (LQR-BMA) for suspension systems of automobiles. BMA combines the bacterial foraging optimization algorithm (BFOA) and the memetic algorithm (MA) to enhance the effectiveness of its search process. An LQR control system adjusts the suspension’s behavior by determining the optimal feedback gains using BMA. The control objective is to significantly reduce the random vibration and oscillation of both the vehicle and the suspension system while driving, thereby making the ride smoother and enhancing road handling. The BMA adopts control parameters that support biological attraction, reproduction, and elimination-dispersal processes to accelerate the search and enhance the program’s stability. By using an algorithm, it explores several parts of space and improves its value to determine the optimal setting for the control gains. MATLAB 2024b software is used to run simulations with a randomly generated road profile that has a power spectral density (PSD) value obtained using the Fast Fourier Transform (FFT) method. The results of the LQR-BMA are compared with those of the optimized LQR based on the genetic algorithm (LQR-GA) and the Virus Evolutionary Genetic Algorithm (LQR-VEGA) to substantiate the potency of the proposed model. The outcomes reveal that the LQR-BMA effectuates efficient and highly stable control system performance compared to the LQR-GA and LQR-VEGA methods. From the results, the BMA-optimized model achieves reductions of 77.78%, 60.96%, 70.37%, and 73.81% in the sprung mass displacement, unsprung mass displacement, sprung mass velocity, and unsprung mass velocity responses, respectively, compared to the GA-optimized model. Moreover, the BMA-optimized model achieved a −59.57%, 38.76%, 94.67%, and 95.49% reduction in the sprung mass displacement, unsprung mass displacement, sprung mass velocity, and unsprung mass velocity responses, respectively, compared to the VEGA-optimized model. Full article

As manufacturing demands for challenging-to-machine metallic materials continue to evolve, the performance of cutting tools has emerged as a critical limiting factor. The synergistic application of micro-texture and coating in cutting tools can improve various properties. For the processing of existing micro-texture, because of the fast cooling and heating processing method of laser, there are defects such as remelted layer stacking and micro-cracks on the surface after processing. This study introduces a preheating-assisted technology aimed at optimizing the milling performance of textured coated tools. A milling test platform was established to evaluate the performance of these tools on titanium alloys under thermally assisted conditions. The face-centered cubic response surface methodology, as part of the central composite design (CCD) experimental framework, was employed to investigate the interaction effects of micro-texture preparation parameters and thermal assistance temperature on milling performance. The findings indicate a significant correlation between thermal assistance temperature and tool milling performance, suggesting that an appropriately selected thermal assistance temperature can enhance both the milling efficiency of the tool and the surface quality of the titanium alloy. Utilizing the response surface methodology, a multi-objective optimization of the textured coating tool-preparation process was conducted, resulting in the following optimized parameters: laser power of 45 W, scanning speed of 1576 mm/s, the number of scans was 7, micro-texture spacing of 130 μm, micro-texture diameter of 30 μm, and a heat-assisted temperature of 675.15 K. Finally, the experimental platform of optimization results is built, which proves that the optimization results are accurate and reliable, and provides theoretical basis and technical support for the preparation process of textured coating tools. It is of great significance to realize high-precision and high-quality machining of difficult-to-machine materials such as titanium alloy. Full article

The development of multifunctional conductive hydrogels with rapid self-healing capabilities and powerful sensing functions is crucial for advancing wearable electronics. This study designed and prepared a polyvinyl alcohol (PVA)–borax hydrogel incorporating carbon nanotubes (CNTs) and biomass carbon nanospheres (CNPs) as dual-carbon fillers. This hydrogel exhibits excellent conductivity, mechanical flexibility, and self-recovery properties. Serving as a highly sensitive piezoresistive sensor, it efficiently converts mechanical stimuli into reliable electrical signals. Sensing tests demonstrate that the CNT/CNP/PVA–borax hydrogel sensor possesses an extremely fast response time (88 ms) and rapid recovery time (88 ms), enabling the detection of subtle and rapid human motions. Furthermore, the hydrogel sensor also exhibits outstanding cyclic stability, maintaining stable signal output throughout continuous loading–unloading cycles exceeding 3200 repetitions. The hydrogel sensor’s characteristics, including rapid self-healing, fast-sensing response/recovery, and high fatigue resistance, make the CNT/CNP/PVA–borax conductive hydrogel an ideal choice for multifunctional wearable sensors. It successfully monitored various human motions. This study provides a promising strategy for high-performance self-healing sensing devices, suitable for next-generation wearable health monitoring and human–machine interaction systems. Full article

Thermal sensors are widely used in medical, industrial and other fields, where the requirements for high sensitivity and portability continues to increase. Here we propose a suspended bridge structure fabricated using MEMS, which effectively shrinks the size and reduces heat loss. This study reviews current sensor-related theories of heat conduction, convective heat transfer and thermal radiation. Heat loss models for suspended and non-suspended bridge structures are established, and finite element analysis is conducted to evaluate their thermal performance. The thermal performance of the suspended bridge structure is further validated through infrared temperature measurements on the manufactured sensor device. Theoretical calculations demonstrate that the proposed suspension bridge structure reduces heat loss by 88.64% compared with traditional designs. Benefiting from this improved heat retention, which was also confirmed by infrared thermography, the thermal sensor fabricated based on the suspension bridge structure achieves an ultra-high sensitivity of 0.38 V/W and a fast response time of less than 200 ms, indicating a high accuracy in thermal characterization. The correlation coefficient obtained for the sensor output voltage and input power of the sensor is approximately 1.0. Based on this design, multiple microfluidic channels with suspended bridge structures can be integrated to realize multi-component detection, which is important for the development of multifunctional biomedical detection. Full article

The demand for rapid, portable, and cost-effective analytical tools has driven advances in smartphone-based microfluidic sensors. By combining microfluidic precision with the accessibility and processing power of smartphones, these devices offer real-time and on-site diagnostic capabilities. This review explores recent developments in smartphone-integrated microfluidic sensors, focusing on their design, fabrication, smartphone integration, and analytical functions with the applications in forensic science, agriculture, and environmental monitoring. In forensic science, these sensors provide fast, field-based alternatives to traditional lab methods for detecting substances like DNA, drugs, and explosives, improving investigation efficiency. In agriculture, they support precision farming by enabling on-demand analysis of soil nutrients, water quality, and plant health, enhancing crop management. In environmental monitoring, these sensors allow the timely detection of pollutants in air, water, and soil, enabling quicker responses to hazards. Their portability and user-friendliness make them particularly valuable in resource-limited settings. Overall, this review highlights the transformative potential of smartphone-based microfluidic sensors in enabling accessible, real-time diagnostics across multiple disciplines. Full article

The low-carbon transition of the global energy system is an urgent necessity to address climate change and meet growing energy demand. As a major source of energy consumption and emissions, buildings play a key role in this transition. This study systematically analyzes the flexible resources of building energy systems and vehicle-to-grid (V2G) interaction technologies, and mainly focuses on the regulation characteristics and coordination mechanisms of distributed energy supply (renewable energy and multi-energy cogeneration), energy storage (electric/thermal/cooling), and flexible loads (air conditioning and electric vehicles) within regional energy systems. The study reveals that distributed renewable energy and multi-energy cogeneration technologies form an integrated architecture through a complementary “output fluctuation mitigation–cascade energy supply” mechanism, enabling the coordinated optimization of building energy efficiency and grid regulation. Electricity and thermal energy storage serve as dual pillars of flexibility along the “fast response–economic storage” dimension. Air conditioning loads and electric vehicles (EVs) complement each other via thermodynamic regulation and Vehicle-to-Everything (V2X) technologies, constructing a dual-dimensional regulation mode in terms of both power and time. Ultimately, a dynamic balance system integrating sources, loads, and storage is established, driven by the spatiotemporal complementarity of multi-energy flows. This paper proposes an innovative framework that optimizes energy consumption and enhances grid stability by coordinating distributed renewable energy, energy storage, and flexible loads across multiple time scales. This approach offers a new perspective for achieving sustainable and flexible building energy systems. In addition, this paper explores the application of demand response policies in building energy systems, analyzing the role of policy incentives and market mechanisms in promoting building energy flexibility. Full article

The West Africa Power Pool (WAPP) Interconnected Transmission System (WAPPITS) has faced challenges with frequency control due to limited primary frequency control reserves (PFRs). Battery Energy Storage Systems (BESSs) have been identified as a possible solution to address frequency control challenges and to support growing levels of variable renewable energy in the WAPPITS. This paper uses a dynamic PSS/E grid simulation to evaluate the effectiveness of BESSs and conventional power plants for the maximum N-1 contingency scenario in WAPPITS—the loss of 400 MW of generation. BESSs outperform conventional power plants in fast frequency response; a BESS-only PFR mix produces the best technical performance for the metrics analyzed. However, this approach does not have the best marginal cost; a balanced mix of BESSs and conventional reserves achieves adequate performance on all metrics to meet grid requirements. This hybrid approach combines BESSs’ rapid power injection with the lower cost of conventional units, resulting in improved nadir frequencies (e.g., 49.70–49.76 Hz), faster settling times (1.00–2.20 s), and cost efficiency. The study indicates that an optimal approach to frequency control should include a combination of regulatory reforms and coordinated reserve procurement that includes BESS assets. Regulatory reforms should require or incentivize conventional plant to provide PFRs, possibly through creation of a (new to WAPPITS) market for ancillary services. While not a comprehensive analysis of all variables, these findings provide critical insights for policymakers and system operators. Full article

In response to the increasing demands for reliable, fast, and secure communications beyond 5G scenarios, the high-capacity networks have become a focal point. Quantum communication is at the forefront of this research, offering unmatched throughput and security. A free space optics (FSO) communication system integrated with fiber-end is designed and investigated using the Bennett–Brassard 1984 quantum key distribution (BB84-QKD) protocol. Simulation results show that reliable transmission can be achieved over a 10–15 km fiber length with a signal power of −19.54 dBm and high optical-to-signal noise of 72.28–95.30 dB over a 550 m FSO range under clear air, haze, fog, and rain conditions at a data rate of 1 Gbps. Also, the system using rectilinearly and circularly polarized signals exhibits a Stokes parameter intensity of −4.69 to −35.65 dBm and −7.7 to −35.66 dBm Stokes parameter intensity, respectively, over 100–700 m FSO range under diverse weather conditions. Likewise, for the same scenario, an FSO range of 100 m incorporating 2.5–4 mrad beam divergence provides the Stokes power intensity of −6.03 to −11.1 dBm and −9.04 to −14.12 dBm for rectilinearly and circularly polarized signals, respectively. Moreover, compared to existing works, this work allows faithful and secure signal transmission in free space, considering FSO–fiber link losses. Full article

Topological insulators (TIs) hold considerable promise for the advancement of optoelectronic technologies, including spectroscopy, imaging, and communication, owing to their remarkable optical and electrical characteristics. This study proposes a novel combination of Bi${}_2$Se${}_3$ TIs and ReSe${}_2$ for self-powered broadband photodetectors with high sensitivity and fast response time. The Bi${}_2$Se${}_3$/ReSe${}_2$ heterojunction photodetector achieves broadband response spectra ranging for 375 nm to 1 $\mathsf{\mu }$m. It demonstrates a significant responsivity of 64 mA/W at a wavelength of 600 nm (1 mW/cm${}^2$), exhibits a rapid response speed of 345 $\mathsf{\mu }$s rise/336 $\mathsf{\mu }$s fall time, and has a 3 dB bandwidth of 1.4 kHz under zero-bias conditions. The high performance can be attributed to the suitable energy band structure of Bi${}_2$Se${}_3$/ReSe${}_2$ and high carrier mobility in surface states of Bi${}_2$Se${}_3$. Excitingly, self-powered TIs photodetectors allow for high-quality signal transmission. The TIs employed in photodetectors can stimulate the production of new optoelectronic features, but they could also be used for highly integrated photonic circuits in the future. Full article

In the power system of a polysilicon reduction furnace, especially during the silicon rod growth process, the issue of insufficient temperature control accuracy arises due to the system’s nonlinear and time-varying characteristics. To address this challenge, a dual-loop control system is proposed, combining model-free adaptive control (MFAC) with an improved PID controller. The inner loop utilizes a hysteresis PID controller for dynamic current regulation, ensuring fast and accurate current adjustments. Meanwhile, the outer loop employs a hybrid MFAC-based improved PID algorithm to optimize the temperature tracking performance, achieving precise temperature control even in the presence of system uncertainties. The MFAC component is adaptive and does not require a system model, while the improved PID enhances stability and reduces the response time. Simulation results demonstrate that this hybrid control strategy significantly improves the system’s performance, achieving faster response times, smaller steady-state errors, and notable improvements in the uniformity of polysilicon deposition, which is critical for high-quality silicon rod growth. The proposed system enhances both efficiency and accuracy in industrial applications. Furthermore, applying the dual-loop model to actual industrial products further validated its effectiveness. The experimental results show that the dual-loop model closely approximates the polysilicon production model, confirming that dual-loop control can allow the system to rapidly and accurately reach the set values. Full article

The Super-Twisting Sliding Mode Controller (STSMC) is regarded as one of the most straightforward and most practical nonlinear control systems, due to its ease of application in industrial systems. Its application helps minimize the chattering problem and significantly improves the resilience of the system. This controller possesses multiple deficiencies and issues, as its use does not promote the expected improvement of systems. To overcome these shortcomings and optimize the efficiency and performance of this technique, a new method is suggested for the super-twisting algorithm (STA). This study proposes and uses a new STA approach, named the fast super-twisting algorithm (FSTA), utilized the conventional IFOC technique to mitigate fluctuations in torque, current, and active power. The results from this suggested the IFOC-FSTA method are compared with those of the traditional SMC and STA methods. The results obtained from this study demonstrate that the suggested method, which is based on FSTA, has outperformed the traditional method in terms of ripple ratio and response dynamics. This demonstrates the robustness of the proposed approach to optimize the generator performance and efficiency in the double-fed induction generator-based wind system. Full article

Abnormal operations, such as faults occurring in an electrical power system (EPS), disrupt its balanced operation, posing potential hazards to human lives and the system’s equipment. Effective monitoring, control, protection, and coordination are essential to mitigate these risks. The complexity of these processes is further compounded by the presence of intermittent distributed energy resources (DERs) in active distribution networks (ADNs) with bidirectional power flow, which introduces a fast-changing dynamic aspect to the system. The deployment of phasor measurement units (PMUs) within the EPS as highly responsive equipment can play a pivotal role in addressing these challenges, enhancing the system’s resilience and reliability. However, synchrophasor measurement-based studies and analyses of power system phenomena may be hindered by the absence of PMU blocks in certain simulation tools, such as PSCAD, or by the existing PMU block in Matlab/Simulink R2021b, which exhibit technical limitations. These limitations include providing only the positive sequence component of the measurements and lacking information about individual phases, rendering them unsuitable for certain measurements, including unbalanced and non-symmetrical fault operations. This study proposes a new reliable PMU model in Matlab and tests it under normal and abnormal conditions, applying real-time simulation and controller-hardware-in-the-loop (CHIL) techniques. Full article