Large Speed Variation Research Articles

A Microscopic Traffic Model to Investigate the Effect of Connected Autonomous Vehicles at Bottlenecks and the Impact of Cyberattacks

Bottlenecks reduce both traffic safety and efficiency, resulting in congestion and collisions. The introduction of connected autonomous vehicles (CAVs) has had a significant impact on road networks and can improve traffic efficiency at bottlenecks. This paper proposes a microscopic traffic model to investigate CAV behavior at bottlenecks and examine the effect of cyberattacks. The model is developed using data collected from a roadside sensor node. It is implemented in MATLAB using the Euler scheme to simulate a platoon of vehicles on a circular road of length 1 km. The performance is compared with the intelligent driver (ID) model. The results obtained indicate that the road capacity with the proposed model is 1.4 times higher than with the ID model. Further, the proposed model results in nearly constant speeds with small variations, which is realistic. Conversely, the ID model produces large speed variations that are unrealistic. In addition, the proposed model results in less acceleration and deceleration, which leads to lower vehicle emissions and pollution. The efficiency is better than with the ID model due to CAV communication and coordination, so queues dissipate faster. The traffic flow with the proposed model increases as the density decreases, which is consistent with traffic dynamics. It is also shown that the proposed model can characterize CAV behavior under cyberattacks that cause disruptions in the data. Thus, it can be employed for traffic control and forecasting when bottleneck conditions exist and there is malicious behavior.

Application of a regularised Coulomb sliding law to Jakobshavn Isbræ, western Greenland

Abstract. Reliable projections of future sea level rise from the polar ice sheets depend on the ability of ice sheet models to accurately reproduce flow dynamics in an evolving ice sheet system. Ice sheet models are sensitive to the choice of the basal sliding law, which remains a significant source of uncertainty. In this study we apply a range of sliding laws to a hindcast model of Jakobshavn Isbræ, western Greenland, from 2009 to 2018. We demonstrate that a linear viscous sliding law requires the assimilation of regular velocity observations into the model in order to reproduce the observed large seasonal and inter-annual variations in flow speed. This requirement introduces a major limitation for producing accurate future projections. A regularised Coulomb friction law, in which basal traction has an upper limit, is able to more accurately reproduce the range of speeds from 2012 to 2015, the period of peak flow and maximal retreat, without the requirement for assimilating regular observations. Additionally, we find evidence that the speed at which sliding transitions between power-law and Coulomb regimes may vary spatially and temporally. These results point towards the possible form of an ideal sliding parameterisation for accurately modelling fast-flowing glaciers and ice streams, although determining this is beyond the scope of this study.

Improved control of permanent magnet synchronous motors using adaptive nonlinear control with Deadbeat Observer

Permanent Magnet Synchronous Motor (PMSM) control optimization is crucial for a variety of applications, including electric vehicles, industrial automation, and renewable energy systems (RESs). However, traditional control methods often struggle to adapt to the dynamic and non-linear nature of PMSMs, leading to sub-optimal performance. To address these challenges, this paper proposes a hybrid adaptive nonlinear control strategy with a deadbeat observer (DO) designed to improve the performance of PMSMs. This approach aims to improve the accuracy and robustness of the control while taking into account the system parameters variations and disturbances. Simulation tests comparing the proposed method with an adaptive nonlinear control (ANLC) are presented, highlighting its superior effectiveness in controlling PMSMs under varying load conditions and speed fluctuations. The proposed strategy achieves a maximum relative speed error around of 6% at 0.4 s under gradually varying load torque disturbances, which is better than the ANLC with 8%. Furthermore, under large speed variations, the suggested method maintains a maximum relative speed error of 0.82% at 0.85 s. Furthermore, the robustness assessment under system parameters variations, stator resistance, and inductance, shows extraordinary performances of the proposed scheme. These results highlight the effectiveness and robustness of the proposed strategy in achieving precise PMSM control while dynamically adapting to changing conditions. This research underscores the potential of our approach to advance key technologies, including electric vehicles, industrial automation, and renewable energy systems. By optimizing PMSM control, this strategy contributes to increased efficiency, reliability, and adaptability, facilitating broader adoption of electric propulsion systems and sustainable energy solutions.

A nonlinear approach for the simulation of the buffeting response of long span bridges under non-synoptic storm winds

In recent years, extreme atmospheric events are becoming increasingly frequent and unpredictable. These phenomena are often characterized by low-frequency variations of the wind speed and angle of attack, mainly due to large-scale turbulence. These features can be critical for long-span bridges as they can lead the deck in conditions where the nonlinear effects of aerodynamic forces are enhanced. Therefore, it is increasingly important to develop reliable numerical tools to simulate the response of these structures to non-synoptic winds. In this work, a nonlinear rheological model that is able to account for the large variations in wind speed and angle of attack is employed to investigate the dynamic response of two different bridges subjected to two different wind fields. The first scenario is a standard synoptic wind field used as a baseline. On the other hand, the second wind scenario represents an extreme non-synoptic atmospheric event. The results highlight how the nonlinear effects of the aerodynamic forces, in particular those related to the large variation of the angle of attack, could lead to significant changes in the bridges’ response. These effects would not be captured by employing standard linearized methods.

Short-pitch corrugation formation on resilient fastener metro tracks explained using rail-bending vibrations within the bogie wheelbase

Short-pitch corrugation is a serious problem on resilient fastened railway track for many metro lines, causing severe noise and vibration that shortens the life of the vehicle and track components. To address this problem, the formation mechanism of this kind of corrugation is investigated in this study. The corrugation characteristics and natural frequency of the resilient fastener track are determined by field investigations. Then, ‘frequency sweeping’ and long-term rail-roughness prediction models are developed to reveal the crucial role of the interactions between two wheelsets in the corrugation formation and to estimate the effects of speed variations and bogie wheelbase on corrugation growth. The spectral analysis results indicate that the spatial frequency spectrum exhibits several peaks at equal intervals due to the short-pitch corrugation of a resilient fastener metro track, which are related to the third-order rail-bending vibration within the bogie wheelbase at about 775 Hz. In addition, large and small speed variations affect the wavelength and depth growth of the corrugation, respectively. The growth of corrugation depth is amplified when the resonance frequency associated with the corrugation formation is an integer-multiple of the wheel-passing frequency. The wheelbase is also an important factor in determining the corrugation wavelength because of its influence on the resonance frequency.

Techno-economic assessment of offshore wind energy potential at selected sites in the Gulf of Guinea

Offshore wind power has been found to stand out among the most dynamic renewable energy technologies. With its long coastal line, Nigeria has an overwhelming advantage in developing marine energy resources to relieve the power crisis effectively. This work analyzed and characterized observation data of sea-surface wind speed and direction at 30-minute intervals between 1979 and 2015 at five synoptic offshore stations in the Gulf of Guinea. The seasonal variations in hourly surface wind speed and directions as well as the Weibull distribution of wind speed and wind power at 100 m hub height were examined. The wind shears, capacity factors, and accumulated energy outputs for seven offshore wind turbine types were determined for the selected locations. In addition, the economic analysis of the selected offshore turbines using levelized cost of energy was carried out, while sensitivity analysis of the total levelized cost of energy to key input parameters was further determined. The results revealed large spatial and temporal variations in wind speed and wind power in the Gulf of Guinea. The most viable offshore site for wind energy exploitation was Agbami (the deepest offshore site), while Bonny (the shallow coastal site) had the least. The findings established very good fits (having mean bias (between −0.08 ms−1 and −2.44 ms−1), percentage bias (between −0.47% and −13.98%), correlation coefficients (between 0.97 and 0.98), Chi-square (between 0.2 and 1.2), and root mean square error (between 1.2 ms−1 and 3.1 ms−1)) between Weibull distribution and the actual wind data. The wind turbines with the highest and the lowest wind power densities, capacity factors, and power outputs across the seasons and sites were V236-15.0 MW and Siemens SWT113, respectively. The levelized cost of energy was considered for the deep waters due to the moderately high-capacity factors. The highest values ranged between 101.48 and 137.12 USD/MWh at Sea Eagle with V236-15 MW and V117-4.2 MW, respectively, while the lowest ranged from 52.29 to 69.66 USD/MWh at Agbami with V236-15 MW and Siemens (SWT113), respectively. The exploitation of Nigeria’s offshore wind resources could also be dedicated to producing renewable hydrogen and can serve to meet the country’s ambitious targets set for carbon neutrality by 2060.

An enhanced instantaneous angular speed estimation method by multi-harmonic time–frequency realignment for wind turbine gearbox fault diagnosis

Gearboxes are one of the most critical transmission devices in wind turbines (WTs). Order tracking (OT) of variable-speed WT gear is a powerful means to carry out fault diagnosis. Since it is difficult to install a tachometer or encoder for gearboxes with limited structural space, it is impossible to obtain the instantaneous angular speed (IAS) of the gearbox. In recent years, many tacholess techniques have been presented to estimate instantaneous phase from vibration signals for OT. However, their performance needs to be further improved to get a more exact diagnosis result. To solve this issue, this paper presents an enhanced IAS estimation approach for WT tacholess order tracking (TLOT), which is available for accurate IAS estimation of the rotating shaft, so that TLOT can be more effectively conducted under conditions of large speed variation and background noise. An improved cost function algorithm is designed to extract the IAS from the vibration signal. A Vold–Kalman filter and Hilbert transform are combined to calculate the instantaneous phase. Afterwards, the raw non-stationary vibration signal is resampled at an equal angle increment, and the envelope order spectrum is calculated from the resampled signal for fault diagnosis of the WT gearbox. The main innovating idea of this approach is to improve the traditional cost function ridge-extraction method by introducing gradient information based on probability and multi-harmonic time–frequency realignment, which makes the IAS estimation process more accurate and overcomes the limitations of traditional IAS estimation techniques. The effectiveness of the presented approach is demonstrated by using a vibration signal measured from real-world WT gearboxes, and the validation results demonstrate that the presented approach surpasses some state-of-the-art methods in IAS estimation accuracy and efficiency.

Enhanced order spectrum analysis based on iterative adaptive crucial mode decomposition for planetary gearbox fault diagnosis under large speed variations

Variable speed conditions are omnipresent in the operation of rotating machinery. Tacholess order tracking (TOT) technique based on time-frequency representation (TFR) has been attracting much attention in recent years, but the challenges of low time-frequency resolution, parameter selection and computational consumption limit its practical applications. To this end, this paper presents a novel time-frequency analysis (TFA) method named iterative adaptive crucial mode decomposition (IACMD), which accurately extracts the time-varying component in the signal through the instantaneous frequency refinement strategy and the adaptive bandwidth parameter update rule. Then, an enhanced order spectrum analysis scheme based on IACMD is further proposed, which highlights the fault characteristic order by eliminating the amplitude modulation effect and is completely independent of the tachometers. Both simulation analysis and test-rig experiments have demonstrated the effectiveness of the proposed strategy in fault diagnosis of planetary gearboxes under various large speed variations. Compared with traditional TFA methods, the results show that the IACMD provides higher accuracy and efficiency even in the case of large time-varying and strong noise.

Deep Reinforcement Learning for Stability Enhancement of a Variable Wind Speed DFIG System

Low-frequency oscillations are a primary issue for integrating a renewable source into the grid. The objective of this study was to find sensitive parameters that cause low-frequency oscillations and design a Twin Delayed Deep Deterministic Policy Gradient (TD3) agent controller to damp the oscillations without requiring an accurate system model. In this work, a Q-learning (QL)-based model-free wind speed DFIG was designed on the rotor-side converter (RSC), and a QL-based model-free DC-link voltage regulator was designed on the grid-side converter (GSC) to enhance the stability of the system. In the next step, the TD3 agent was trained to learn the system dynamics by replacing the inner current controllers of the RSC, which replaced the QL-based model. In the first stage, the conventional PSS and Proportional–Integral (PI) controllers were introduced to both the RSC and GSC. Then, the system was trained to become model-free by replacing the PSS and the PI controller with a QL algorithm under very small wind speed variations. In the second stage, the QL algorithm was replaced with the TD3 agent by introducing large variations in wind speed. The results reveal that the TD3 agent can sustain the stability of the DFIG system under large variations in wind speed without assuming a detailed control structure beforehand, while QL-based controllers can stabilize the doubly fed induction generator (DFIG)-equipped wind energy conversion system (WECS) under small variations in wind speed.

A tacholess order tracking method based on extended intrinsic chirp component decomposition for gears under large speed variation conditions

Abstract Order tracking has been considered as the most effective non-stationary signal analysis technique for condition monitoring and fault diagnosis. Conventional order tracking is performed with a reference signal measured by the auxiliary device, which is expensive and inconvenient to install. In order to to break the constraint of the traditional order tracking technique, some tacholess order tracking methods have been developed in the past few years. However, current tacholess order tracking approaches are only applicable to slightly varying speed applications. To overcome the shortcoming above, a novel tacholess order tracking method is proposed in this paper. In the proposed method, each mode of the vibration signal is reconstructed by a method called extended intrinsic chirp component decomposition, and the Hilbert transform is used to estimate the instantaneous phase of reference shaft. Then the vibration signal is resampled to the angle domain, and the fault characteristic orders can be identified in the order spectrum accurately. The effectiveness of the proposed method has been validated by a simulated meshing gear vibration signal. The result illustrates that the proposed method can realize gears fault diagnosis under large speed variation conditions.

Real-Time Reduction of Rotor Position Estimation Error Based on the Stator Flux Estimation-Combined Method for Sensorless Control of PMSMs Drives

This paper presents the implantation and the performance improvement of real-time reduction of rotor position estimation error based on the stator flux estimation-combined method for sensorless control of PMSMs drives. Wherein, the proposed method is designed based on a simple algorithm for accurate estimation and robust control of quasi-exact stator flux and position/speed of PMSMs. A large-speed range of applications in sensorless control strategies is achieved by using the mathematical model of PMSM motor. The latter presents the main idea of the estimators’ structures design. They are generally composed of voltage and current models (VM and CM). However, the dynamic performances of these methods are influenced in the low and high-speed ranges, and they are sensitive to parameters variations. The estimators’ structures are dominated by the current model at the low-speed range, and by the voltage model at the high-speed range. The technique proposed in this study is the combination of the two preceding models; this provides performances’ improvement in the PMSM dynamics for a large speed variation with compensating estimation errors for the two separate methods (VM and CM). The main objective of this combined method is the drawback reduction for the separate use of VM and CM estimators. The algorithm principle is based on exploiting and combining the two estimators while measuring the stator voltages and the currents, in addition to estimating the rotor position and the speed. Furthermore, the performances of the proposed method have been tested and validated through real-time experiments by using dSPACE ds 1104 DSP board.

An Active Voltage Coordinate Control Strategy of DFIG-Based Wind Farm with Hybrid Energy Storage System

In a power system with wind farms, the point of common coupling (PCC) usually suffers from voltage instability under large wind speed variations and the load impact. Using the internal converter of a doubly fed induction generator (DFIG)-based wind turbine to provide voltage support auxiliary service is an effective scheme to suppress the voltage fluctuation at PCC. To satisfy the reactive power demand of the connected grid, an active voltage coordinate control strategy with the hybrid energy storage system of the wind farm is proposed. The dynamic reactive power balance model is established to show the interaction between the reactive power limitation of the wind farm and the reactive power compensation demand of the grid. This indicates the initial conditions of the active voltage coordinate control strategy. According to the critical operating point and the operation state of the DFIG, the active and reactive power coordinate control strategy composed of active ω-β coordinate control and active β control is proposed to enhance the reactive power support capability and stabilize the grid voltage. To compensate the active power shortage, an auxiliary control strategy based on the hybrid energy storage system is introduced. The simulation results show that the proposed strategy can suppress the voltage fluctuation effectively and make full use of primary energy.

Body Wave Speed Structure of Eastern North America

AbstractThe eastern, passive margin of the North American continent is more heterogeneous than originally envisioned. Imaged by teleseismic body wave arrivals, both compressional Vp and shear Vsh, the lithospheric mantle of the stable, eastern North America contains rapid and large wave speed variations from the fast, older interior toward the slower, margin structures along the continental edge. At multiple regions at the continental edge, wave speeds indicate the presence of a small amount of melt, <1%–2%. Melt assessments were computed using a suite of mineralogical/petrological models to convert Vp and Vsh into absolute temperatures and melt fraction. Moreover, along the Atlantic margin, wave speeds are lower than expected for a previously rifted margin. Within the continent interior, wave speeds in the mantle lithosphere vary spatially at wavelengths, suggesting strong compositional and mineralogical influence likely a result of later stage alteration from volatile rich fluids.

Estimation of the instantaneous rotational frequency of gear transmission with large speed variations using short-time angular resampling and ridge-enhancing techniques

Instantaneous rotational frequency (IRF) is essential for most of the gear fault diagnosis methods used for nonstationary conditions. However, estimating the IRF under large speed-variation conditions is challenging. In this work, we developed a short time angular resampling and ridge-enhancing (STAR-RE) method for estimating the IRF of a gear transmission system of large speed variations. The method is integrated with a rigorous approach for eliminating ridge smearing based on angular resampling and a straightforward scheme for enhancing the target ridge by merging the ridges of several gear meshing harmonics. Data collected from a laboratory gearbox and an in-field wind turbine gearbox operated at variable speed regimes were used to test the accuracy and effectiveness of the STAR-RE method. The results indicated that the STAR-RE method achieved more accurate IRFs than the benchmark methods.

Numerical simulation of a methane-oxygen rotating detonation rocket engine

The rotating detonation engine (RDE) is an important realization of pressure gain combustion for rocket applications. The RDE system is characterized by a highly unsteady flow field, with multiple reflected pressure waves following detonation and an entrainment of partially-burnt gases in the post-detonation region. While experimental efforts have provided macroscopic properties of RDE operation, limited accessibility for optical and flow-field diagnostic equipment constrain the understanding of mechanisms that lend to wave stability, controllability, and sustainability. To this end, high-fidelity numerical simulations of a methane-oxygen rotating detonation rocket engine (RDRE) with an impinging discrete injection scheme are performed to provide detailed insight into the detonation and mixing physics and anomalous behavior within the system. Two primary detonation waves reside at a standoff distance from the base of the channel, with peak detonation heat release at approximately 10 mm from the injection plane. The high plenum pressures and micro-nozzle injector geometry contribute to fairly stiff injectors that are minimally affected by the passing detonation wave. There is no large scale circulation observed in the reactant mixing region, and the fuel distribution is asymmetric with a rich mixture attached to the inner wall of the annulus. The detonation waves’ strengths spatially fluctuate, with large variations in local wave speed and flow compression. The flow field is characterized by parasitic combustion of the fresh reactant mixture as well as post-detonation deflagration of residual gases. By the exit plane of the RDRE, approximately 95.7% of the fuel has been consumed. In this work, a detailed statistical analysis of the interaction between mixing and detonation is presented. The results highlight the merit of high-fidelity numerical studies in investigating an RDRE system and the outcomes may be used to improve its performance.

Robust nonlinear control of wind turbine driven doubly fed induction generators

This paper presents the active and reactive powers control of a doubly fed induction generator (DFIG) connected to the grid utility and driven by a wind turbine, this machine allowing a large speed variation and so a large range of wind is achieved. Traditionally vector control is introduced to the DFIG control strategies, which decouples DFIG active and reactive powers, and reaches good performances in the wind energy conversion systems (WECS). However, this decoupling is lost if the parameters of the DFIG change. In this direction, a robust control scheme based on the nonlinear input-output linearizing and decoupling control strategy for the rotor side converter (RSC) of the WECS is presented. Simulation results show that the proposed control strategy provides a robust decoupled control and perfect tracking of the generated active and reactive powers of the wind turbine driven DFIG with a low THD rate of the generated currents.

Tacholess order tracking method for gearbox based on time-varying filter and energy centrobaric correction method

Under the premise that the instantaneous speed can be accurately measured or precise estimated, order tracking is considered to be a classical and effective technique for non-stationary vibration analysis of rotating machinery. The meshing frequency components of the vibration signal measured from complex gearbox system interfere with each other mutually. The energy centrobaric correction method exhibits exact instantaneous frequency estimation (IFE) ability under the interference, but is susceptible to strong noise. Combining with time-varying filter and energy centrobaric correction method, a tacholess order tracking technique for gear fault diagnosis under the rotating frequency multi-linear fluctuation is proposed. The time-varying filter is designed to filter the strong noise signal, and then IFE could be accurately calculated from the filtered signal by energy centrobaric correction method. The instantaneous phase of reference shaft based on the Vold-Kalman filter (VKF) is used for angular resampling of the original vibration signal. The results show that the shaft rotating speed could be accurately identified from extracted gear meshing components. The order spectrum obtained by the proposed method with tacholess is substantially the same as the order spectrum obtained by a tachometer. Simulation analysis and experimental results verify the advantages of proposed tacholess order tracking technology for monitoring and fault diagnosis of gearbox vibration under the condition of strong noise and large speed variation.

DSP in the Loop Implementation of a Backstepping Controller for Wind Energy Conversion System Based on a Doubly Fed Induction Generator Connected to Grid

This paper deals with the design and implementation of the control strategy of a grid connected Doubly Fed Induction Generator wind turbine on a TMS320F28335 Digital Signal Processor (DSP). The synthesized controller is a nonlinear Backstepping control law whose stability is guaranteed in the context of Lyapunov stability theory. The control aim is to optimize the power extracted by the generator for large wind speed variations through Maximum Power Point Tracking (MPPT) and Unity Power Factor (UPF) control. These command strategies are implemented in order to achieve the following specifications: good static precision for optimal energy conversion; electrical dynamics as high as possible regardless of slow mechanical dynamics, smooth transient without overshoots that could damage the lifecycle of the machine and converters, rapid disturbance isolation and robustness to any parametric variations or uncertainties. The results of the Hardware in the Loop (HIL) implementation on DSP show satisfactory performance in terms of response time, setpoint tracking, stability, and robustness under stochastic wind speed profile and parameter variations.

The optimization and the application for the wind turbine power-wind speed curve

An optimized wind turbine power-wind speed curve (P-v curve) was presented in this paper to solve the problems in the low-wind-speed regions like the large wind speed variation and the low wind turbine efficiency. When the wind speed was lower than the cut-in wind speed, the operation mode of the wind turbine was changed by the extra power supplied by the motor excitation source to keep the wind turbine operating. The application condition of the optimized P-v curve was derived and calculated. The effects of various wind speeds on the powers and the power generation of the wind turbine were analyzed by comparison with and without the improvement. The results indicated that the prolonged working period, the improved efficiency of the wind turbine and the incremental power generation were induced by the usage of the optimized P-v curve. The cut-in wind speed was declined by 42.8%. The power generation was enhanced by 73.4% at the actual wind condition of some wind field. The motor power was augmented with the huge amplitude of the wind speed. Compared with the traditional P-v curve, the optimized P-v curve was more suitable for the lower average and larger amplitude of the wind speed.

Correcting Multibeam Echosounder Bathymetric Measurements for Errors Induced by Inaccurate Water Column Sound Speeds

In this contribution a method for correcting bathymetric measurements affected by inaccurate water column sound speed profiles (SSPs) is presented. The method exploits the redundancy in the multibeam echosounder measurements obtained from the overlap of adjacent swaths by minimizing the difference between depths along overlapping swaths. Two optimization methods are used, i.e., Differential Evolution (DE) and Gauss-Newton (GN). While DE inverts for the sound speed by minimizing the depth variation, GN inverts for both bathymetry and sound speed by minimizing the squared sum of the differences between the modeled and measured travel times. The inversion method assumes a constant SSP in the water column. Applying the method to a salt wedge survey area with large variations in the water column sound speed indicates a good agreement between the original depth measurements and those derived after the inversion with the mean and standard deviation of the depth differences equaling 0.009m and 0.024m, respectively. This indicates that even with a simple parametrization of the sound speed in the water column, the correct bathymetry can be derived from the inversion. The SSP inversion method is also applied to an area with existing refraction artefacts. It corrects the bathymetry and reduces the mean and standard deviation of the depth standard deviation by a factor of around 2.75 compared to the case where the measured SSPs were used. Furthermore, the SSP inversion method neither manipulates the existing morphology nor introduces artificial bathymetric features in the areas where such refraction artefacts are not present. Considering constant SSPs, both DE and GN give almost identical results with GN being faster. However, GN is less flexible with regards to varying sound speed parameterizations.