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This article deals with the non-line-of-sight (NLOS) reception issue in the field of global navigation satellite system (GNSS). The NLOS reception has attracted a significant amount of attention because it is one of the main factors that limit the GNSS position accuracy in urban areas. In this article, we dig into the baseband signal processing level to explore a new solution to the NLOS detection and correction by means of the vector tracking loop (VTL). The NLOS effects on both conventional scalar tracking loops (STLs) and VTL are derived mathematically. Based on this, an NLOS detection algorithm is developed using metrics, such as the equivalent noise bandwidth, the time delay of multicorrelator peaks, as well as code discriminator outputs. Once detected, the NLOS-induced measurement error is corrected before being fed forward into the navigation estimator to improve the position accuracy. Two field tests in urban areas in Hong Kong are conducted to illustrate the effectiveness of the proposed method in real applications. The NLOS correction performance is also assessed using simulated NLOS receptions with controllable time delays and reflection coefficients, which reveals how the proposed algorithm performs in different NLOS scenarios. [ABSTRACT FROM AUTHOR]

The static voltage stability assessment model is effective in analyzing system stability states. However, the electrothermal coupling relationship dependent on practical current-carrying and ambient conditions is generally ignored for models concerning overhead transmission lines, thereby introducing certain analysis errors. Therefore, this article proposes a unified power flow model which allows for the electrothermal coupling effect characterized by the balance of heat absorption and dissipation for overhead conductors. Moreover, the meteorological and geographic information around the transmission lines is involved as variables in the power flow calculation. Then, the Newton iteration formulations are restated and the improved power flow model is solved by continuously adjusting the variables and updating an extended Jacobian matrix. Then, the extended matrix corresponding to the final power flow solutions is used to establish the improved V–Q sensitivity and modal analysis methods, which allows one to evaluate system static voltage stability considering variations of ambient factors. Consequently, based on an IEEE 14-bus test system, the results obtained by the traditional model and the improved model are contrastively analyzed in different scenarios, which are substantially different from each other. The results illustrate that the consideration of ambient conditions around the transmission line will cause remarkedly impacts on the static voltage stability assessment results. [ABSTRACT FROM AUTHOR]

As a typical energy storage in hydraulic hybrid powertrain, the hydraulic accumulator has high power density but low energy density. There are some efforts in improving the energy density of hydraulic energy storage to achieve balanced performance. Therefore in this study an electric-hydrostatic energy storage system is proposed to replace hydraulic accumulator in a hydraulic hybrid wheel loader. Through active control of proposed energy storage, constant system pressure is possible to provide good vehicle drivability. A rule-based energy management strategy without estimating final drive power is proposed. The vehicle performance and fuel consumption with different constant system pressures are studied. Results show the vehicle fuel consumption is reduced by 5.9% with constant system pressure reduced from 33 to 27 MPa. The energy density and power density of proposed energy storage are calculated, showing a much higher energy density and slightly lower power density than gas-charged accumulator. [ABSTRACT FROM AUTHOR]

Proposes a neural adaptive control method for plants with linear and nonlinear uncertainties. Use of a single neural network for control and identification; Derivation of a sufficient condition of local asymptotic stability; Application of the approach to the torque control of a flexible beam with uncertainties.

A new carrier-aided dual-frequency vectorized tracking (CA-DFVT) architecture for the Navigation with Indian Constellation (NavIC) is presented. CA-DFVT tracks both NavIC L5 (1176.45 MHz) and S-band (2492.028 MHz) signals concurrently. It uses the precise carrier phase measurements from the S-band signal and the unambiguous code phase measurements from the L5 signal to form a new measurement model for the extended Kalman filter (EKF) to estimate the position, velocity, and time (PVT) solutions. The new measurement model takes advantage of the benefits of the higher frequency S-band signal, i.e., less ionospheric delay and carrier phase noise, as well as the L5 signal’s inherent noise mitigation capabilities. Compared to the single-frequency approach, the dual-frequency approach in CA-DFVT eliminates the ionospheric effect and minimizes other errors, resulting in better navigation solutions. The proposed CA-DFVT enhances the reliability and robustness of NavIC signal tracking and position estimation in interference and high dynamics environments. We used static and dynamic field tests to validate the performance and robustness of the proposed CA-DFVT receiver architecture. In comparison to single-frequency (L5/S-band) vector tracking, the CA-DFVT receiver demonstrated consistent signal tracking and position estimation with higher position accuracy. In the static case, the mean horizontal position accuracy of CA-DFVT improves by approximately 2–4 and 9–14 m compared to L5-only VT and S-only VT, respectively, while, in the dynamic case, it improves by approximately 2–5 and 25–42 m, respectively. [ABSTRACT FROM AUTHOR]

Performing precise positioning is still challenging for autonomous driving. Global navigation satellite system (GNSS) performance can be significantly degraded due to the non-line-of-sight (NLOS) reception. Recently, the studies of 3D building model aided (3DMA) GNSS positioning show promising positioning improvements in urban canyons. In this study, the benefits of 3DMA GNSS are further extended to the GNSS/inertial navigation system (INS) integration system. Based on the shadow matching solution and scoring information of candidate positions, two methods are proposed to better classify the line-of-sight (LOS) and NLOS satellite measurements. Aided by the satellite visibility information, the NLOS-induced pseudorange measurement error can be mitigated before fusing GNSS with the INS in the loosely-coupled or tightly-coupled integration system. Both the proposed satellite visibility estimation methods achieve over 80% LOS/NLOS classification accuracy for most of the scenarios in the urban area, which are at least 10% improvement over the carrier-to-noise ratio ($C/{N_0}$)-based method. By further extending the satellite visibility estimation to exclude NLOS measurements and adjust the measurement noise covariance, the proposed 3DMA GNSS/INS tightly-coupled integrated positioning achieves nearly a factor of 3 improvements comparing to the conventional GNSS/INS integration method during the vehicular experiment in the urban canyon. [ABSTRACT FROM AUTHOR]

Rate control is the most used operation method for master–slave hydraulic manipulators. However, the trajectory from the master controlled by the operator cannot completely meet the dynamic limitations and flow restriction of the hydraulic manipulator. Continuous large errors and oscillation will occur due to flow restrictions and high-order dynamics beyond the dynamic boundaries that significantly limits the velocity tracking performance of a hydraulic manipulator. In this article, we propose a flow-limited rate control scheme for the master–slave hydraulic manipulators. The variable velocity mapping is developed, adjusting the velocities to meet the pump and valves’ flow limits. An adaptive robust rate controller of hydraulic manipulators is designed. An adaptive boundary estimator is introduced to estimate the hydraulic manipulator acceleration boundaries, and a variable structure controller is used to plan the velocities to meet dynamic limits. The proposed control scheme is tested on a hydraulic manipulator. The results show that the control scheme reduced velocity error and avoid the manipulator vibration, so the performance is improved for the hydraulic manipulator. [ABSTRACT FROM AUTHOR]

The energy management strategy is the key factor for hybrid vehicles since it determines how efficiently the engine power is transferred to the wheels. As a local-optimal and implementable strategy, the equivalent consumption minimization strategy is of great research interest. The equivalent factor and the gain coefficient of penalty function are two important parameters in the strategy that need to be determined in advance. It is challenging to choose these parameters to achieve minimum fuel consumption in different on-road driving cycles. For some off-road vehicles, such as wheel loaders, the loading cycle is highly repetitive. This brings a great opportunity to optimize these parameters cycle-to-cycle. In this study, an adaptive equivalent consumption minimization strategy is applied to a series hydraulic hybrid wheel loader. A cycle-to-cycle tuning scheme is developed where the equivalent factor and the gain coefficient of penalty function are optimized through repetitive loading cycles. The potential with parameter optimization in different loading cycles is identified. Results show a fuel-saving with the cycle-to-cycle optimization method of up to 6.36% in a 57 s loading cycle. [ABSTRACT FROM AUTHOR]

Colloidal nanoplatelets (NPLs) are a kind of two-dimensional nano-material with an atomically flat surface, leading to an ultra-narrow emission linewidth of 8~12 nm. In this article, we fabricated green light-emitting diodes (LEDs) based on CdSe/CdS core/crown NPLs. This device exhibited an electroluminescence (EL) at 521 nm with a full-width at half maximum (FWHM) of 15 nm and a maximum luminance of 4684 cd/m2. Such narrow EL FWHM indicates that the core/crown NPLs can achieve an ultrapure green LED with 124.7% of National Televison System Committee (NTSC), realizing a high color saturation and wide color gamut display. [ABSTRACT FROM AUTHOR]

Due to serious cloud contamination in optical satellite images, it is hard to acquire continuous cloud-free satellite observations, which limits the potential utilization of the available images and further data extraction and analysis. Thus, information reconstruction in cloud-contaminated images and the reprocessing of continuous cloud-free images are urgently needed for global change science. Many previous studies use one cloud-free reference image or multitemporal reference images to restore a target cloud-contaminated image; however, this paper is different and has developed a novel spatially and temporally weighted regression (STWR) model for cloud removal to produce continuous cloud-free Landsat images. The proposed method makes full utilization of cloud-free information from input Landsat scenes and employs a STWR model to optimally integrate complementary information from invariant similar pixels. Moreover, a prior modification term is added to minimize the biases derived from the spatially-weighted-regression-based prediction for each reference image. The results of the experimental tests with both simulated and actual Landsat series data show the proposed STWR can yield visually and quantitatively plausible recovery results. Compared with other cloud removal methods, our method produces lower biases and more robust efficacy. This approach provides a complete framework for continuous cloud removal and has the potential to be used for other optical images and to be applied to the reprocessing of cloud-free remote sensing productions. [ABSTRACT FROM PUBLISHER]