Dynamic Speed Research Articles

Characteristic analysis method for integrated multi-parameter hydro-viscous speed control system

Hydro-viscous clutch has become an inevitable choice for special vehicle transmissions. As a nonlinear dynamic system with large lagging link, its timing performance is affected by input rotational speed, lubricating oil temperature and pressure and other factors. However, from the control perspective, the speed regulation law, formation mechanism control characteristics, global model of hydro-viscous speed control system (HSCS) are unclear. To solve these problems, this paper presents a comprehensive analysis of the Hydro-viscous Speed Control System (HSCS), focusing on its steady-state and dynamic speed control characteristics. A data-driven model is established to describe the relationship between input rotational speed, output speed, control oil pressure, and lubricating oil temperature. The findings provide a foundation for optimizing HSCS structure and parameters, enhancing the performance and reliability of such systems in special vehicle transmissions and establishing a temperature-speed control system for special vehicle transmissions.

Exploring the Drive Motor of Electric Vehicles: Structure, Temperature Rises, and Operational Control of Permanent Magnet Motors

The drive motor is a critical component of electric vehicles. The design of its structure, along with the regulation of temperature rises and operational control, significantly impact the overall performance of electric vehicles, affecting aspects such as dynamic response, anti-interference capabilities, speed stability, and efficiency. This paper provides a review and comprehensive analysis of the Special Issue titled “Temperature Field, Electromagnetic Field, and Operation Control of Permanent Magnet Motor for Electric Vehicles”, and discusses the future development directions of permanent magnet motors in electric vehicles. The analysis reveals that the structural design is crucial for both the static and dynamic performance of permanent magnet motors. Additionally, it is imperative to identify an optimal trade-off among various performance parameters in these motors. The paper also verifies several future development directions for permanent magnet motors, including high-speed control, the use of advanced silicon steel sheets, power quality, battery charging efficiency, and energy feedback.

Development and safety evaluation of an adaptive personalized speed guidance system for on-ramp merging in highway service areas

As autonomous driving and Vehicle-to-Everything (V2X) technologies evolve, the efficiency and safety of ramp merging in the highway service areas have become increasing critical. This study introduces a closed-loop feedback speed guidance system that accommodates individual driving styles, aiming to optimize merging behaviour, reduce traffic accidents, and enhance total traffic efficiency. The system dynamically adjusts the merging vehicle speeds by continuously monitoring their speed and location with variable steps to promote smoother merging. Moreover, this research also involves collecting naturalistic driving data from ramp merging scenarios, using the K-means clustering and point estimation method to recognize and analyse driving style characteristics, and integrating these styles into the developed closed-loop feedback speed guidance system. This approach results in personalized speed guidance curves tailored to different driving styles, facilitating more efficient mering. Additionally, the study conducts a Safety of the Intended Functionality (SOTIF) evaluation of this system using the System-Theoretic Process Analysis (STPA) method, which helps identify potential security risks and develop appropriate mitigation strategies to ensure the system’s safe and stable operation. The simulation results confirm that this innovative dynamic speed guidance system substantially improves traffic safety and efficiency in ramp merging areas.

Influence of Deep Abdominal Flexor Muscle Recruitment on Dynamic Balance and Gait Speed in Middle-Aged Tailors

Influence of Deep Abdominal Flexor Muscle Recruitment on Dynamic Balance and Gait Speed in Middle-Aged Tailors

Dynamic Network-Level Traffic Speed and Signal Control in Connected Vehicle Environment.

The advent of connected vehicles holds significant promise for enhancing existing traffic signal and vehicle speed control methods. Despite this potential, there has been a lack of concerted efforts to address issues related to vehicle fuel consumption and emissions during travel across multiple intersections controlled by traffic signals. To bridge this gap, this research introduces a novel technique aimed at optimizing both traffic signals and vehicle speeds within transportation networks. This approach is designed to contribute to the improvement of transportation networks by simultaneously addressing issues related to fuel consumption and pollutant emissions. Simulation results vividly illustrate the pronounced the effectiveness of the proposed traffic signal and vehicle speed control methods of alleviating vehicle delay, reducing stops, lowering fuel consumption, and minimizing CO2 emissions. Notably, these benefits are particularly prominent in scenarios characterized by moderate traffic density, emphasizing the versatility and positive impact of the method across varied traffic conditions.

Fixed Switching Frequency Model Predictive Control and Passivity Based Control for DC-DC Converter

The DC-DC converter represents a crucial component in the renewable energy sources. The stability and dynamic capability enhancement of the DC/DC converter have emerged as a significant research topic in the current era. Model predictive control (MPC) is particularly prevalent due to its high dynamic response speed, simplicity of the controller design, and capacity for multi-objective optimization. However, the traditional finite control set model predictive control (FCS-MPC) method is suffer to variable switching frequency and vast computing. To improve the dynamic performance of the converter, a novel nonlinear control strategy named fixed switching frequency MPC and passivity-based control (PBC), named FSFPBMPC, is proposed, which could achieve fixed switching frequency and enhance the system's dynamic response speed. Firstly, the Euler-Lagrange (EL) model of the boost converter is established. Secondly, the relationship between duty cycle and MPC is established. Ultimately, the output voltage of PBC is incorporated into the cost function of the FCS-MPC. The characteristics of PBC power shaping and damping injection can enhance the system's immunity to interference, improve the system's dynamic response speed, and thus reinforce the system's stability. Then, depending on MATLAB, the simulation results proved that the proposed strategy has the same effect as we expected.

Comparative Analysis of the MDORA and AODV Routing Protocols for Vehicles Operating at Constant and Variable Speeds

The primary focuses of investigation have been and continue to be strategies for traffic management at intersections and measures to enhance road safety. An essential remedy for this issue is a Vehicular Ad-hoc Network (VANET). At VANET, a variety of protocols are used to route communications between vehicles. At this research, we utilize the Multipath Dynamic Optimized Routing Algorithm (MDORA), which is an acronym for position-based maximum distance on-demand routing. By choosing the vehicle closest to the destination vehicle, this protocol has the advantage of choosing the next best jumping path, which lowers the number of hops. In two scenarios—vehicle travel at a dynamic speed and constant speed—this paper compares the MDORA and AODV protocols. three standards: Factors including the time spent on communication, the pace at which packets are delivered, and the time it takes for information to travel from one end to another, were used to assess how well the two protocols performed. Finally, a comparison of the number of missed packets between the MDORA and AODV protocols was done for moving vehicles at constant and dynamic speeds, The MDORA protocol can identify the optimal route even when cars are moving at varying speeds, resulting in minimal packet loss.

Evaluating Driver Response to Bridge Deck Warning Systems During Winter Weather Conditions

Warning signs are often deployed at bridge overpasses during winter to warn motorists of potentially icy surface conditions on the bridge, although the effectiveness of these signs is questionable. One potential improvement to the standard signage methods is the bridge deck warning system (BDWS), which activates a flashing warning sign border or beacon when conditions warrant based on real-time weather and bridge surface data. However, BDWSs have not been broadly implemented in the United States, and consequently, their effectiveness as a safety countermeasure is not well established. To address this knowledge gap, a series of winter field evaluations were performed along three freeway bridge overpasses in Michigan to assess the effectiveness of various BDWS strategies as a speed reduction countermeasure for motorists approaching a potentially icy bridge. The results showed that a BDWS with a flashing light emitting diode (LED) border reduced motorist speeds when encountering a bridge during winter weather conditions compared with the standard “Bridge Ices Before Road” warning sign. The speed reduction effect was consistent between passenger cars and heavy trucks, but was somewhat stronger at night compared with daytime. Greater speed reductions were observed when the BDWS sign was combined with a dynamic speed feedback sign (DSFS) that displayed a “Slow Down” or “Icy Road” message to approaching motorists, with the strongest effects observed when the DSFS message was pulsed between high and low brightness intensities. BDWSs that included only a flashing overhead beacon did not have a significant effect on speeds compared with the standard warning sign.

Impact of a compound droplet on a solid surface: The effect of the shell on the core

The dynamic behavior of compound droplets impacting a solid surface was studied via experiments over κ (defined as the ratio of the compound droplet shell thickness h to the diameter D0 of compound droplet) ranging from 0 to 0.34, We ranging from 25 to 325 and Re ranging from 165.3 to 3405.2. The spreading diameter ratio, the maximum spreading dynamic contact angle and spreading speed of the core were investigated. Four modalities of the core of compound droplets were observed on the solid surface, including a) core rebound, b) no rebound, c) core splitting rebound, d) core splitting. The results revealed that the thickness of the shell, We, and the viscosity of the shell have a significant effect on the rebound and spreading processes of the core of the compound droplet. The high viscosity oil shell is conducive to its spreading. As the thickness of the oil shell increases, its cushioning effect on the water core also increases. In addition,κ=0.02254We0.503,κ=-0.336e-We121.056+0.319 and κ=0.06086e-We121.056+0.07716e-We121.70598+0.01595 were used to divide the modal boundary of the compound droplet core. Further analysis reveals the correlation between We, Re, βm and.κ,12+Weβm=8+31-cos22.78+84.57κβm3+0.955We1.05Reβm6.5.

An improved finite set model predictive control of SRM drive based on a voltage vectors strategy for low torque ripple

The robust rotor structure and fault-tolerance characteristics of the Switched Reluctance Motors (SRMs) are the best choice for next-generation Electric Vehicle (EV) applications. This machine has few restraints like high torque and flux ripples. However, the existing Model Predictive Control (MPC) using multiple control objectives and maximum sectors in the switching table results in high torque ripples due to the improper sector partition, Voltage Vectors (VVs) and weight factor (K1) selection. This paper proposes a Finite Set-Model Predictive Control (FS-MPC) for an analytical model of a non-linearity SRM machine to analyze the torque ripple performance. The proposed VVs are derived using sector partition based on the rotor position. The control is designed as a single cost function with the weighting factor contributing to smooth torque by selecting optimal control signals. Simulation studies and experiments with a four-phase 8/6 SRM drive verifies the enhanced FS-MPC for real-time implementation. The dynamic speed and ripple values of SRM Drives are measured using a mixed signal oscilloscope and the sensor probes. The laboratory outcomes calculate the analytical equations to validate the findings. The calculated value of torque ripple is 9 % through this FS-MPC. The study reveals that the proposed method is well suited for torque ripple reduction than flux ripples.

Blade Airfoil Optimization and Its Impact on Vertical Axis Wind Turbine Performance

Abstract Amidst the emergence of crises in petroleum prices and supply, the imperative for the development of clean energy has become increasingly apparent. Vertical axis wind turbines (VAWT), as a type of wind turbine, still grapple with challenges such as low wind energy utilization and sensitivity to dynamic wind speeds. This study focuses on optimizing the airfoil of a two-dimensional vertical axis wind turbine and analyzes the performance variations in a three-dimensional model. Following the optimization, the average power coefficients of the dual-blade two-dimensional VAWT increased by 7.9% and 4%, respectively, while those of the dual-blade three-dimensional model rose by 7.9% and 1.2%. However, the performance of the three-dimensional model was compromised due to the influence of tip vortices, resulting in inferior performance compared to the two-dimensional model. Both three-dimensional optimized blade designs exhibited a substantial reduction in the flow separation region downstream and improved pressure distribution fluctuations caused by the shedding of tip vortices, leading to decreased pressure differentials. Along the spanwise section, the power coefficient gradually decreased from the central segment to the tip segment. Notably, the power coefficient of the optimized blades at the tip segment increased significantly, accompanied by an augmented pressure differential between the upper and lower surfaces. This augmentation contributed to a significant enhancement in lift, thereby facilitating the rotation of the vertical axis wind turbine.

PCLOS based fractional-order sliding mode stochastic path following control for underactuated marine vehicles with multiple disturbances and constraints

This paper investigates the stochastic path following control of underactuated marine vehicles (UMVs) subject to multiple disturbances and constraints. Firstly, the complex marine environment in which UMVs navigate typically contains stochastic components, thus the multiple disturbances are categorized as slow-varying deterministic disturbances and stochastic disturbances. Secondly, a position-constrained line-of-sight (PCLOS) based fractional-order sliding mode stochastic (FSMS) control strategy is established to achieve path following control of UMVs. A PCLOS guidance law based on universal barrier Lyapunov function is proposed to ensure that the position errors remain within the constraint ranges, which is versatile for systems with symmetric constraints or without constraints. An FSMS controller based on fractional-order theory and sliding mode control is designed to improve the dynamic response speed of the system and effectively attenuate chattering phenomenon. A stochastic disturbance observer is developed to estimate the slow-varying deterministic disturbances in the stochastic system, and auxiliary dynamic compensators are used to mitigate the impact of input constraints. Lastly, theoretical analysis indicates that the closed-loop system is stable and the position constraint requirements are satisfied. Comparative simulations illustrate the effectiveness of the proposed control strategy.

Interval Type-2 Fuzzy Neural Network Based Cascade Predictive Control of Superheated Steam Temperature

Abstract The superheated steam temperature (SST) suffers from complex dynamic characteristics such as nonlinearity and large time delay. To deal with the negative effects, this paper proposes a cascade predictive control strategy (CPC-PI) based on interval type-2 fuzzy neural network (IT2FNN) to improve the performance of SST. First, this paper proposes the IT2FNN model for modeling the SST model. And then on the basis the local linearized IT2FNN model, the CPC-PI strategy is designed. In the following, fuzzy self-regulation of the weight factor in the CPCPI is carried out to further improve the dynamic response speed and stability of SST. Finally, the comparative simulations verify that the IT2FNN-based CPC-PI control strategy with self-regulated weight factor is superior to the PI-PI control strategy and the IT2FNN-based CPC-PI control strategy with fixed weight factor.

Defect passivation engineering for achieving 4.29% light utilization efficiency MA-free wide-bandgap semi-transparent perovskite solar cells

Wide-bandgap perovskite materials are a great candidate for semitransparent perovskite solar cells (ST-PSCs) due to their tunable bandgap, outstanding transparency, and excellent photovoltaic performance. Though Br-rich perovskite can widen the bandgap, Br influences the crystallization dynamic speed leaving small perovskite grain sizes and high defects. Surface passivation engineering has been one of the best choices to suppress defects caused by the rapid crystallization of Br-rich perovskites. Herein, we applied MA-free perovskite as a light absorber because of the erratic thermal aging of MA-containing perovskites and selected phenethylammonium iodide (PEAI) and 4-trifluoro phenylethylammonium iodide (CF3PEAI) as passivation materials for improving the performance of opaque PSCs and ST-PSCs. Consequently, CF3PEA possesses a larger dipole moment. It has been demonstrated to exhibit a stronger binding energy with the substrate than PEA by density functional theory (DFT) calculations. This enhanced molecular interaction underpins the performance improvements in our solar cells, which manifests as an inverted planar structure opaque PSCs with 1.78 eV bandgap achieve a power conversion efficiency (PCE) of 17.09 % with excellent stability. A PCE of 17.17 % with 25 % average visible-light transmittance (AVT) and 4.29 % light utilization efficiency (LUE) of ST-PSCs is achieved by further optimizing the fabrication process of the buffer layer for protecting the perovskites from the damage of ITO sputter. Meanwhile, a four-terminal tandem solar cell with ST-PSC and silicon-based passivated emitter rear cell (PERC) obtains a PCE of 26.28 %. This work provides a feasible way to fabricate high-performance ST-PSCs with limited materials and preparation conditions.

Non-contact measurement of conveyor belt speed based on fast point cloud registration of feature block

Abstract Non-contact, real-time measurement of conveyor belt speed is critical for energy-saving speed regulation and efficient development of coal mine conveyor systems. Existing speed measurement technologies for conveyor systems are often limited by the slippage and wear in contact measurement and complex environmental disturbance. This study introduces three-dimensional point cloud technology into coal flow information detection and innovatively presents a non-contact measurement method of conveyor belt speed based on fast point cloud registration of feature blocks. In the proposed method, a three-dimensional camera is used to capture point cloud data of the dynamically running conveyor belt, and the raw point cloud is preprocessed and segmented into blocks. Then, the C-MANV (curvature and mean angle of normal vectors) features of block point clouds are constructed based on the point cloud neighborhood curvature and the mean angle of neighborhood normal vectors. Finally, an improved block point cloud registration method based on C-MANV features is adopted to achieve the accurate measurement of the dynamic running speed of conveyor belt. Experimental results demonstrate that the proposed method achieves an average relative error of less than 1.8% in high-speed conveyor belt operation with an average processing time of less than 35 ms, which fulfils the accuracy and real-time requirements for conveyor belt speed detection in coal mines. This study provides an effective technical solution for the speed monitoring of coal mine conveyor systems.

The Effect of Eight Weeks of Selected Vestibular Exercises on Functional Balance, Walking Speed and Quality of Life of Sedentary Elderly Men

Introduction: Aging and sedentary lifestyle are associated with a decrease in physical and mental abilities. The purpose of this study is to investigate the effect of eight weeks of selected vestibular exercises on functional balance, walking speed, and quality of life of sedentary elderly men. Methods: This semi-experimental research was conducted from the winter of 1402 to the summer of 1403 with the participation of 30 sedentary elderly men from Tawheed Golmkan Elderly Care Center in Mashhad. The samples were selected purposefully and based on previous studies (25) and were divided into two experimental and control groups of 15 people. The experimental group performed selected vestibular exercises three sessions a week for eight weeks, while the control group did not perform any exercises. Dynamic comparison test, 10-meter walking speed and short-term life questionnaire were used to evaluate the quality of life. Data analysis was performed using Shapiro-Wilk test, analysis of covariance, and t-test at a significance level of P<0/05. Results: The results of paired t test showed that dynamic balance (P=0/001), walking speed (P=0/001), and quality of life (P=0/001) of the experimental group improved significantly after the exercise program. This was while there was no improvement in the control group. The covariance results did not show a significant difference between the groups in the pre-test phase, but there was a significant increase in the scores of the experimental group in the post-test phase. Conclusion: It is recommended to use exercises to prevent the disabilities of the elderly and improve their quality of independent life.

Effects of ambient temperature on drivers’ speed-selective behavior at different risk levels: A driving simulation study

Abnormal or inappropriate ambient conditions can lead to reduced driving performance or even crashes, and the ambient temperature could be the most critical and fundamental factor. However, the coupling effects of the ambient temperature and the road and traffic conditions on basic speed-selection behavior are rarely investigated. To this end, this study attempted to evaluate drivers’ speed-selective behavior at low-medium-high risk levels under the low (16 °C ± 2 °C), medium (26 °C ± 2 °C), and high (36 °C ± 2 °C) ambient temperature ranges. To achieve this, a series of driving simulation experiments were conducted with 45 participants. Results showed that, at the low-risk level, the limitations of low-temperature or high-temperature conditions resulted in higher average speed than the medium-temperature condition. At the medium-risk level, the driver’s dynamic speed adjustment behavior was degraded under low-temperature or high-temperature conditions, and the deceleration rate was higher than the medium-temperature condition. At the high-risk level, drivers failed to diminish their speed in a timely way under low-temperature or high-temperature conditions, increasing the risk of crashes. However, decreasing the speed at the point of conflict could be effective in reducing the severity of the collision. The findings of this study can be applied to autonomous vehicles (AVs) to search for better safety countermeasures.

A dynamic temporal and spatial speed control strategy for partially connected automated vehicles at a signalized arterial

The connected and automated vehicle (CAV) is able to acquire the global intelligence in advance by communicating with other CAVs and roadside units (RSU), thus integrated speed control has the potential of easing the traffic wave, reducing the fuel consumption and emissions. In this paper, a dynamic temporal and spatial speed control framework is proposed to optimize the travel speed of CAVs along the signalized arterial under the mixed traffic flow including CAVs and human driven vehicles (HDVs). A speed control optimization method is proposed to minimize the number of stops of the ego CAV and its follower HDV with considering the signal status and queuing. A secondary speed control method based on the dynamic control areas is introduced in the mentioned framework to guide the CAV to the targeted positions. The corresponding dynamic variable parameter model is then designed to optimize the operational parameters of the corresponding control area to minimize the total fuel consumption of all vehicles under different market penetration rates. Finally, the simulation platform of Urban Mobility (SUMO) is used to test the proposed speed control strategy. The results indicate that the total stop delays are reduced by 60.9 % and saving 6.5 % total fuel consumption under the 30 % penetration rate.

A preference adjustable capacity configuration optimization method for hydrogen-containing integrated energy system considering dynamic energy efficiency improvement and load fast tracking

The new hydrogen-containing integrated energy system proposed in this paper has complementary coupling of multiple energy forms such as electricity, gas, cold, heat, and hydrogen. For the same type of load demand, equipment with different energy input forms can be dispatched for joint supply. However, different equipment differ in dynamic response speed and energy utilization efficiency, and the reasonable configuration of equipment capacity will directly affect the overall dynamic characteristics and energy efficiency level of the system. Therefore, this paper first proposes an evaluation index that can comprehensively characterize the dynamic energy efficiency and load tracking ability of energy equipment. In addition, a preference adjustable capacity configuration optimization method based on utopian point tracking is proposed with the two optimization objectives of this indicator and the system's equivalent annualized investment cost, and the solution complexity is reduced through segmented linearization of the objective. Simulations presented here show that the capacity configuration optimization method proposed in this paper has a positive effect on improving the dynamic energy efficiency and load tracking ability of the new hydrogen-containing integrated energy system, and can also meet the preference setting needs of different investment entities for capacity configuration optimization goals.

Design and Performance Evaluation of an In Situ Online Soil Electrical Conductivity Sensor Prototype Based on the High-Performance Integrated Chip AD5941

Soil electrical conductivity has an important influence on the growth and development of plants. The existing real-time soil electrical conductivity detection device is affected by temperature, inconvenient to use, expensive, etc.; therefore, based on the classical four-terminal method of soil electrical conductivity detection principle, in this study, we aim to improve the limitations of the constant current source, selecting the high-performance integrated chip AD5941, optimizing the detection circuit and probe structure, improving the achievability of the detection circuit, and designing a type of in situ on-line real-time access to a soil electrical conductivity detection device, and improve the detection accuracy by temperature compensation. In this paper, dynamic performance, steady state performance, radial sensitivity range, and calibration test are carried out for the soil electrical conductivity detection prototype. The test results show that the dynamic response speed of the prototype is less than 50 ms, the steady state error is not more than ±2%, and the radial measurement sensitivity range is 8~10 cm. A comparison with the commercial sensor shows that the linear fit of the two measurements reaches 0.9995, and the absolute error ranges from −61.40 µS/cm to 23.90 µS/cm, with a relative error range of −1.94~1.86%. It shows that the performance of the two sensors is comparable, but the quality/price ratio of the prototype is much higher than that of the commercialized product. In this study, it is demonstrated that a high-precision, low-cost, and easy-to-use in situ online soil electrical conductivity detection device can be provided for agricultural and forestry production.