Speed Curve Research Articles

Experimental study and modeling of rubber joints for railway vehicles using magnetorheological shear stiffening elastomers

With the rapid development of transportation industry, advanced rail vehicle technology receives more attention than ever. The stiffness of the train’s rubber joint at the primary suspension system has a crucial influence on the operation stability and curve-passing performance. When the train is running on straight track at high speed, a high primary longitudinal stiffness in bogie design is required, whereas running on the curve track calls for a soft primary longitudinal stiffness. To solve this critical problem, a new rubber joint based on magnetorheological shear stiffening elastomer (MSSE) was proposed. Its stiffness can be adjusted by not only external magnetic field but also its inherent frequency-dependent property, ensuring the functionality of the rubber joint even when the controller fails. The prototype of the MSSE joint was fabricated and assembled. Stiffness controllability of the MSSE joint was evaluated using an material testing system (MTS) machine, with MTS testing performed under varying displacement amplitude at fixed frequency to investigate the influence of the varying displacement amplitude on the effective stiffness. The results revealed that the stiffness of this MSSE joint can be controlled effectively credited to the rate-dependent SSE and adjustable electromagnetics, exhibiting exceptional fail-safe characteristics. Lastly, a dynamic model was established to describe the dynamic performance of the rubber joint. All the above studies demonstrate the feasibility of the joint to satisfy the conflicting stiffness requirements to achieve high speed stability and curve trafficability simultaneously.

Energy Saving Optimal Operation Strategy of Freight Trains under Complex Scenarios

Background: For the optimization of energy-saving driving of freight trains in complex operating environments, the use of reasonable train maneuvering methods can largely reduce the energy consumption of train traction. Recent patents on energy-efficient maneuvering strategies for complex scenarios of freight trains have been researched. Objective: Using the receding horizon algorithm and the improved NSGA-II algorithm to solve the target speed curve of freight trains to cope with the complex and changing operating environment, and to explore the recent patents of energy-saving maneuvering strategies for freight trains and methods. Methods: The recent patents of energy-efficient maneuvering strategies for freight trains in complex scenarios are investigated in this research. A multi-objective optimization model for freight train maneuvering with electrical phasing was developed with the objectives of reducing the traction energy consumption and running time of the train. A method for determining the optimal operating conditions of freight trains under complex line conditions is proposed. The offline optimization of the target speed curve under the electrical phasing constraints of freight trains and the online adjustment under the temporary speed restriction (TSR) are achieved by using the RH-INSGA-II (receding horizon-improved NSGA- II) algorithm. Results: Combined with an actual freight railroad line data as an example, simulation experiments were conducted and verified with HXD1 electric locomotive hauling 50 C80 wagons. Conclusion: The speed curve considering the split-phase constraint can effectively reduce the traction energy consumption. The electrical split-phase constraint affects the whole speed optimization process, not only the speed curve at the split-phase zone. Although the traction energy consumption is increased with the addition of the TSR on the line, the RH-INSGA-II algorithm dynamically changes the sequence of optimal train maneuvering conditions according to the planned train running time in order to avoid further amplification of the late train time.

Research and Design of Speed Profiles for Stacker Cranes

Given the industrial and commercial pursuit of efficiency, it has become urgent to enhance the overall operational efficiency of automated three-dimensional warehouses. This paper focuses on improving the operational efficiency of the stacker in such warehouses. To this end, we deduce the deflection formula and simulate the swing of the stacker to identify the factors that affect its operational stability. Based on these findings, we propose a new speed curve optimization control scheme that properly controls the maximum acceleration and selects an appropriate acceleration change form. This scheme can effectively restrain column swing and improve the stacker’s operational stability, thereby boosting work and production efficiency.

Hierarchical collision-free trajectory planning for autonomous vehicles based on improved artificial potential field method

To enable autonomous vehicles to generate smooth and collision-free trajectories and improve their driving performance on structured roads, this paper proposes a hierarchical trajectory planning algorithm based on an improved artificial potential field method. To improve the applicability of the algorithm to complex scenarios, the Frenet coordinate system was established to address these limitations. First, the safety distance model is applied to the risk assessment of the improved artificial potential field method. Then, the hierarchical solution is carried out, and the road solvable convex space and the rough path solution are solved by combining the artificial potential field method. On this basis, the potential field term and the smoothing term cost function are established, and the sequential quadratic programming (SQP) algorithm is used to solve the exact path that meets the requirements of safety and smoothness. Hierarchical planning shortens the solution time by quickly determining the bounds of the convex space. Finally, in the speed planning, in order to take into account the comfort and safety of the occupants, the speed curve is solved by considering the dynamic constraints of the vehicle. The obstacle avoidance effects of the algorithm on static and dynamic obstacles are tested in different simulation scenarios. The results of the simulation experiment show that the proposed algorithm can successfully achieve obstacle avoidance on complex structured roads.

A Sage-Husa Prediction Algorithm-Based Approach for Correcting the Hall Sensor Position in DC Brushless Motors.

Accurate knowledge of the rotor position is essential for the control of brushless DC motors (BLDCM). Any deviation in this identification can cause fluctuations in motor current and torque, increase noise, and lead to reduced motor efficiency. This paper focused on a BLDCM equipped with a three-phase binary Hall sensor. Based on the principle of minimum deviation, this paper estimated the relative installation offset between the Hall sensors. It also provided a clear method for ideal phase commutation position recognition and eliminated the Hall sensor installation position deviation. The proposed pre-calibration method identified and eliminated the offset of the permanent magnet poles, the delay time caused by the Hall signal conditioning circuit, and the offset of the sensor signal identification due to armature response under different loads. Based on the pre-calibration results, a correction strategy for correcting the rotor position information of BLDCMs was proposed. This paper presented a self-adaptive position information prediction algorithm based on the Sage-Husa method. This filters out rotor position information deviations that are not eliminated in pre-calibration. Experimental results on a hydrogen circulation pump motor showed that, after the pre-calibration method was adopted, the Mean Square Error (MSE) of motor speed fluctuations decreased by 92.0%, motor vibration was significantly reduced, average phase current decreased by 62.8%, and the efficiency of the hydrogen circulation pump system was significantly improved. Compared to the traditional KF prediction algorithm, the Sage-Husa adaptive position information prediction algorithm reduced the speed fluctuation during the uniform speed operation stage and speed adjustment stage, the speed curve overshoot, and the commutation time deviation throughout the process by 44.8%, 56.0%, 54.9%, and 14.7%, respectively. This indicates a higher disturbance rejection ability and a more accurate and stable prediction of the commutation moment.

Instantaneous speed estimation of induction motor by time-varying sinusoidal mode extraction from stator current

When an induction motor operates at variable speed, the fundamental wave and harmonics in the stator current are presented in the form of nonstationary sinusoidal components with time-varying parameters. To estimate the instantaneous speed of the motor utilizing the stator current signal, a time-varying sinusoidal mode extraction (TVSME) method is firstly proposed. In TVSME, a variational model, which compacts the frequency bandwidth of the desired time-varying sinusoidal mode (TVSM) to the narrowest bandwidth and excludes other harmonics as much as possible, is constructed to optimally extract the desired TVSM and to estimate its instantaneous frequency (IF). Then, the fundamental wave and the principal slot harmonics (PSH) are extracted by TVSME, and their IFs are used to calculate the instantaneous rotational speed of the motor. As a result, a highly accurate and smooth rotational speed curve, which is valuable for performance evaluation and fault diagnosis of induction motors, can be obtained. The proposed method is evaluated by both an artificial signal and two experimental signals collected from actual motors. Results show that the instantaneous speed of induction motor can be accurately estimated under the condition of speed variation and multi-harmonic interference.

Similarity identification of characteristic curves of environment stimulus for fuze safety system

For the current problems of limited environmental information, weak environment stimulus, and difficult to distinguish from interference environment stimulus faced by low-rotation munition fuzes in arming, this paper proposes a similarity identification method for characteristic curves of environment stimulus based on Euclidean distance (ED), and corresponding similarity index. By judging the similarity between real-time speed curve and standard curve, abnormal curve and standard curve respectively, the reasonableness and reliability of similarity index and the feasibility of using it as the predetermined condition for fuze arming are confirmed.

An adaptive safety control approach for virtual coupling system with model parametric uncertainties

Virtual coupling attracts extensive attention from the railway communities due to its promising capacity increase and flexibility improvement. Accurate control that guarantees system safety and performance remains a problem that needs to be further studied. This paper investigates the virtual coupling train system (VCTS) safety control problem with model parameter uncertainties using an adaptive nonlinear control strategy based on urban rail transit systems. A safe automatic train control model is introduced, and a novel control framework consisting of two levels is designed to give an overall virtual coupling train control architecture. For the leading train, we deploy an automatic train control system based on dynamic programming. Then, considering parameter uncertainties, we design an adaptive nonlinear controller that ensures safety and control efficiency for the following trains. The proposed control strategy can ensure that a virtually coupled train set tracks the given speed curve and keeps inner distance while guaranteeing the string stability and safety of the platoon, considering parameter uncertainties. The simulation results show that the proposed approach leads to great performance improvement in virtual coupling train operations.

Integrated Position and Speed Control for Rail Transit Doors Based on Speed-Current Loop

Different from typical servo systems that take position control as the first priority, rail transit door needs to reach the specified position with the established speed curve, so as to meet the safety requirements. Hence, both speed control and position control are simultaneously required, which cannot be achieved by the conventional cascaded position-speed-current loop structure. In this paper, an integrated position and speed control method for rail transit door based on speed-current loop structure is proposed. The movement of the door is divided into four stages, in which the speed mode or position mode are applied according to the instantaneous position of the door. In the last stage of position servo, in order to improve the accuracy of position control at low speed and meet the safety requirements, a method based on chopper regulator is proposed to realize servo accuracy and accident protection by adjusting the chopper current limit. Simulation and experimental results show that the proposed method is effective and easy to implement in engineering practice.

The gold rush in para swimming: changes in the speed curve of a visually impaired world and paralympic champion – a case study

ABSTRACT This case study examined the association between 50 m freestyle and speed curve parameters of a world-class Paralympic swimmer and analysed the changes in speed curves and their frequency components across her performance levels. From 2018 to 2021, a visually impaired female swimmer (26.59 s in 50 m freestyle, S12 class) underwent 22 tests to obtain instantaneous speed synchronised with video recording. She regularly performed 50 m freestyle in competitions and time trials. The fast Fourier transformation method converted the speed signal into frequency domains and determined the relative contribution of the harmonics with two maxima and minima (H2, arms actions) and six maxima and minima (H6, legs actions). The functional paired t-test compared the speed curves at the beginning (PRE) and end (POST) of the analysed period. The 50 m freestyle time correlated with average speed (r = −0.50, p = 0.02). The contribution of H6 increased in the first year and remained large, whereas the contribution of H2 was lower throughout the whole period. POST was faster than PRE in five moments that coincide with the downward leg kick moments. These changes allowed her to stay longer at the upper part of the curve and improve performance over time.

Impact of traffic volume and composition on the change in the speed of traffic flow

The problem of the change in the speed of traffic flow at different traffic volumes and compositions is researched in this study. The section of the road network with different geometric parameters (descent, ascent and horizontal section) was chosen for the study. The method of investigation of traffic flow`s speed and factors which have an impact on the reduction of road network capacity are analyzed. The change in the coefficients of the unevenness of traffic flow by hours of the day in the studied area was determined and a graph of the distribution of traffic volume by hours of the day was built. A diagram of the section was built to determine the speed of the traffic flow, on which the movement along the horizontal section, uphill and downhill movement is present. It was established that at a traffic volume of 700-800 p.c.u./h, the traffic flow moves at a constant speed (up to 10-15 km/h). Cumulative curves of traffic flow speed` distribution characterizing modes of traffic flow on the road network were built. It is determined that at volume-capacity ratio 0< z ≤ 0,4 on three investigated sections traffic flow moves with the speed from 35 km/h to 59 km/h. In the specialized software product PTV VISSIM, the simulation of the traffic flow on the horizontal section, ascent and descent has been developed. Using the MATHLAB software environment, it is shown how the speed of the traffic flow changes depending on the volume-capacity ratio and the share of the heterogeneous traffic flow. It was established that the highest speed of the flow is observed during the downhill movement – 58.62 km/h at the volume-capacity ratio – 0.13 and the share of heterogeneous traffic flow – 1.0 (100% cars). At a volume-capacity ratio of 0.88 and existing road conditions, the speed of traffic flow on the horizontal section and during uphill movement is almost the same (the average deviation is 6%). It can be explained by the fact that at a volume-capacity ratio of 0.88, traffic flow is in the traffic jam, hence, the speed of movement on the three sections is the same.

A triangular electrode triboelectric nanogenerator for monitoring the speed and direction of downhole motors

Downhole motors are essential in providing rotational power to the drill bit and achieving the desired trajectory of the wellbore, making them the most reliable component of the bottom-hole assembly. Monitoring their speed and direction is critical to improving drilling efficiency. In this paper, we propose the use of a triangular electrode triboelectric nanogenerator (T-TENG) for monitoring downhole motor speed and direction. The T-TENG employs triangular copper foils as the electrode layer and can determine the direction of rotation based on the transient characteristics of the output signal. Experimental results show that the T-TENG exhibits a measurement error of less than 3 % for speeds within the monitoring range of 0–1200 rpm, and demonstrates good linearity. To enable real-time detection of the downhole motor's instantaneous speed, we introduce an instantaneous speed algorithm based on MATLAB. The average speed curve is obtained by fitting the instantaneous speed using variational mode decomposition (VMD) analysis. Furthermore, the T-TENG exhibits impressive power generation performance and can simultaneously power a low-power temperature and humidity sensor and 436 series-connected light-emitting diodes (LEDs). Compared to conventional downhole sensors, the T-TENG obviates the requirement for an external power source and enables simultaneous measurement of speed and direction. Hence, it offers a fresh perspective for the advancement of next-generation downhole sensors.

Influence of Rock Layer Thickness on the Penetration Resistance of a Composite Target

To describe the influence of rock thickness on the penetration resistance of rock-concrete composite targets, a three-dimensional model was simulated using the nonlinear dynamic simulation software LS-DYNA. The penetration of four composite targets with rock-concrete thicknesses of 10-20, 20-20 cm, 30-20 and 40-20 cm by a projectile at a target angle of 75 degrees is investigated in this study. A damage cloud diagram of the target plate is obtained, and the curves of penetration speed and overload in the X and Y directions of the projectile with time are analysed. During penetration, the rock and concrete layers tend to restrain each other from destroying the target’s back and surface, and the projectile directly enters the tunnel area of the concrete layer from the tunnel area of the rock layer. When the ratio of rock thickness to shot length is less than 1.5, the attitude of the projectile after penetrating the composite target is relatively stable.

WIND POWER FORECASTING USING MACHINE LEARNING IN BHUTAN

In this research, an approach for predicting wind energy using machine learning has been explored. An indirect method has been adopted. Predicting wind speed at first using the hourly weather data and combining that predicted wind speed with the power curve of considered wind turbine prepared by the companies. This research aims to develop a generalized machine learning based wind power forecasting model for Bhutan. Thus, hourly weather data for the year 2018 and 2019 of 300kW On-grid Wind Farm at Rubesa was used to train the base model. Meanwhile, the trained base model was tested against the weather data sets for the selected sites namely Gaselo and Dagana. A Random Forest Regression machine learning algorithm was used in this research. The developed base model has five input variables which are time, temperature, global horizontal irradiance, relative humidity, and pressure, while the target is wind speed. The R- squared values, Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) for the developed base model were found to be 0.88, 0.40 and 0.30 respectively. Energy output in the wind turbine was calculated via the predicted wind speed and power curve prepared by the wind turbine companies. The calculated energy output could shape the considered theoretical power curve. The power curve considered in the present research is 300kW On-grid Wind Farm at Rubesa, Wangdiphodrang.

Exploring Microscopic Characteristics of Bicycle Riders’ following Behaviors in a Single-File Movement

Cycling can bring a wide range of social, economic, and health benefits to individuals and communities. The safety and efficiency of bicycle facilities can be significantly impacted by the interactions among riders. This study aims to examine the microscopic characteristics of how cyclists interact with each other when they are in a single file movement based on the trajectory data collected from an experiment. Reaction delay was obtained by optimizing the correlation between relative speed and acceleration curves for individual cyclists and it was found that even for a given cyclist, this characteristic time delay could vary considerably, and be situation-dependent. Furthermore, it was found that the distribution of reaction delay, which has an average (±SD) of 0.66 s (±0.33 s), followed a log-normal distribution. The strong correlation observed between relative speed and time-delayed acceleration resembles the behavior observed in car-following situations, highlighting that relative speed is an essential factor influencing the acceleration behavior of cyclists. Multiple linear regression models were used to understand the association between acceleration and other key microscopic variables, e.g., spacing and relative speed, which are commonly used in microscopic behavior models. While the spacing between cyclists was found to have a significant impact on acceleration behavior, its effect was not as significant as that of relative speed. The outcomes of this study provide valuable insights into the cyclists’ behavior and can aid in the development of microscopic simulation models.

Study of Rotation Speed Curve Optimization under the Three-Body Coupling Grinding Mode.

The three-body coupling grinding mode of a ball ensures the batch diameter variation and batch consistency of precision ball machining based on the principle of ball forming, resulting in a structure that is simply and feasibly controllable. The change in the rotation angle can be jointly determined using the fixed load of the upper grinding disc and the rotation speed coordination of the inner and outer discs of the lower grinding disc. Related to this, the rotation speed is an important index to guarantee grinding uniformity. To ensure the quality of three-body coupling grinding, this study aims to establish the best mathematical control model of the rotation speed curve of the inner and outer discs in the lower grinding disc. Specifically, it includes two aspects. First, the optimization of the rotation speed curve was mainly studied, and the machining process was simulated with three speed curve combinations: 1, 2, and 3. By analyzing the evaluation index of ball grinding uniformity, the results revealed that the third speed curve combination had the best grinding uniformity, and the three speed curve combinations were optimized on the basis of the traditional triangular wave speed curve. Furthermore, the obtained double trapezoidal speed curve combination not only achieved the traditionally verified stability performance but also overcame the shortcomings of the other speed curves. The mathematical model established in this way was equipped with a grinding control system, which improved the fine control ability of the rotation angle state of the ball blank under the three-body coupling grinding mode. It also obtained the best grinding uniformity and sphericity and laid a theoretical foundation for achieving a grinding effect that was close to the ideal circumstance during mass production. Second, via theoretical comparison and analysis, it was determined that the ball shape and sphericity deviation (SPD) were more accurate than the standard deviation (STD) of the two-dimensional trajectory point distribution. The SPD evaluation method was also investigated via the optimization analysis of the rotation speed curve by means of the ADAMAS simulation. The obtained results coincided with the STD evaluation trend, thus laying a preliminary foundation for subsequent applications.

Wind field and pressure characteristics on wind turbine surface under moving thunderstorms

Based on computational fluid dynamics and large-eddy simulation technologies, a numerical simulation method of a moving thunderstorm field is established by considering the impinging jet model. In addition, the influence of movement speed of the storm center and jet velocity changes on the characteristics of the wind field is presented. By drawing horizontal wind speed radial profile curves, the vertical profile curves of horizontal wind velocity, radial wind profile curves of vertical wind speed, and transient wind speed characteristics of a moving thunderstorm downburst are illustrated. The results demonstrate that the wind field of a moving thunderstorm exhibits clear asymmetric characteristics. As the height from the ground increases, the horizontal wind speed first increases and then decreases. The extreme value of the horizontal wind speed appears at the position of (0.01–0.03) Djet (where Djet is the jet spout diameter) near the ground, which is consistent with the characteristics of a static thunderstorm wind field. Simultaneously, the distribution characteristics of wind pressure on the surface of wind turbines under moving thunderstorms is further studied. By considering variations of the wind attack angle, jet velocity, and moving speed, the results of wind pressure on the tower and blades of the wind turbine are presented. The coupling of the moving speed and jet velocity has a significant influence on the wind field and pressure on the wind turbine surface.

Distribution Characteristics of Wind Speed Relative Volatility and Its Influence on Output Power

The stochastic fluctuations of wind speed and wind power curve modeling are complex tasks due to fluctuations in the difference between actual and theoretical power output, leading to a reduction in the accuracy of wind-power curve models. To address this issue, this paper proposes a normal distribution-modeling method based on relative volatility, which extracts the wind-speed variation patterns from the onsite SCADA (Supervisory Control And Data Acquisition) data, analyzes the correlation between wind-speed relative volatility and power relative volatility, and establishes a wind-power volatility-curve model to provide a basis for evaluating the efficiency of wind turbines. First, the definitions of relative volatility and probability vectors are provided, and a probability vector volatility-assessment function is designed to calculate the volatility-assessment index of the probability vector. Then, the relative volatility and probability vectors of wind speed are modeled, and features extracted from the onsite SCADA data, and characteristic parameters such as mean, standard deviation, and confidence interval of wind-speed relative volatility are statistically analyzed, as well as the wide-window coefficient, volatility-assessment index, attribute features (volatility center and volatility boundary), normal distribution features (mean and standard deviation) of the probability vectors of wind-speed relative volatility with different periods. The visualization descriptions of six typical probability vector distributions show that there is a correlation between the volatility assessment index of the probability vector based on relative volatility and the standard deviation of its distribution. Finally, the correlation between wind-speed relative volatility and power relative volatility is analyzed: in the maximum wind-energy tracking area, the derivative of power is linearly related to the derivative of wind speed, while in the constant power area, the derivative of the wind-energy utilization coefficient is linearly related to the derivative of wind speed. The conclusions obtained in this paper will provide a method reference for data processing to mine the parameter variation patterns and interrelationships of wind farm SCADA data and provide a basis for evaluating the power generation efficiency of wind turbines.

Sand Sedimentation Mechanism in and around the Railway Culvert and Its Structural Optimization of Sediment Reduction

A computational fluid dynamics (CFD) model of a railway culvert was established based on the two-phase flow theory to investigate wind-blown sand transport and sand sedimentation in and around a railway culvert. Then the flow field and the accumulation distribution of sand particles were analyzed through numerical simulation. The results show that the flow field around the culvert can be divided into deceleration, acceleration, and vortex areas. The curve of the horizontal wind speed along the central axis of the culvert had a W shape, indicating a significant increase in the wind speed inside the culvert. A large amount of sand accumulated at the culvert inlet because of the wing walls. The sand volume fraction in the culvert decreased with an increase in the inflow velocity, and there was almost no sand sedimentation when the inflow velocity was greater than 20 m/s. Three reasons for the sand accumulation in the culvert included the deflection by the wing walls, subgrade blocking, and a low inflow velocity. Based on the simulation results, straight and protruding culverts were designed to minimize sand accumulation. The straight culvert exhibited better performance than the protruding culvert and is recommended for use in railways. This work can provide theoretical support for designing railway culverts that minimize or prevent wind-blown sand accumulation.

Fuzzy adaptive PID speed controller design for modern elevator traction machine

With the development of the times, elevator has become an essential transportation in our life. In order to meet the comfort of elevator operation, this paper investigates the design of the speed control system of elevator permanent magnet synchronous traction motor in combination with the elevator operation curve. The whole system is based on SVPWM and uses direct torque control combined with fuzzy adaptive PID to achieve accurate control of motor running speed. It includes the input signal module, control module, drive module and feedback module. Firstly, the analysis of each module in the system is completed, and the connection between the modules is established, as well as the control system. Then case studies are carried out on MATLAB/SIMULINK, and the actual running speed curve of the elevator is obtained, and the simulation results are analyzed to verify the stability and reliability of this speed control system and complete the design.