On Mitigating the Effects of Multipath on GNSS Using Environmental Context Detection

Accurate, ubiquitous and reliable navigation can make transportation systems (road, rail, air and marine) more efficient, safer and more sustainable by enabling path planning, route optimization and fuel economy optimization. However, accurate navigation in urban contexts has always been a challenging task due to significant chances of signal blockage and multipath and non-line-of-sight (NLOS) signal reception. This paper presents a detailed study on environmental context detection using GNSS signals and its utilization in mitigating multipath effects by devising a context-aware navigation (CAN) algorithm that detects and characterizes the working environment of a GNSS receiver and applies the desired mitigation strategy accordingly. The CAN algorithm utilizes GNSS measurement variables to categorize the environment into standard, degraded and highly degraded classes and then updates the receiver’s tracking-loop parameters based on the inferred environment. This allows the receiver to adaptively mitigate the effects of multipath/NLOS, which inherently depend upon the type of environment. To validate the functionality and potential of the proposed CAN algorithm, a detailed study on the performance of a multi-GNSS receiver in the quad-constellation mode, i.e., GPS, BeiDou, Galileo and GLONASS, is conducted in this research by traversing an instrumented vehicle around an urban city and acquiring respective GNSS signals in different environments. The performance of a CAN-enabled GNSS receiver is compared with a standard receiver using fundamental quality indicators of GNSS. The experimental results show that the proposed CAN algorithm is a good contributor for improving GNSS performance by anticipating the potential degradation and initiating an adaptive mitigation strategy. The CAN-enabled GNSS receiver achieved a lane-level accuracy of less than 2 m for 53% of the total experimental time-slot in a highly degraded environment, which was previously only 32% when not using the proposed CAN

Minimization of Torque Ripples in Multi-Stack Slotted Stator Axial-Flux Synchronous Machine by Modifying Magnet Shape

This paper presents a proposed model of a multi-stack slotted stator axial-flux type permanent magnet synchronous machine (AFPMSM) specifically for reducing torque ripple. The proposed AFPMSM model uses pentagon-shaped permanent magnets (PMs). It has a low value of cogging torque and torque ripples compared to the conventional model with a trapezoidal magnet shape. Additionally, it has increased internal generated voltage (Ef) as compared to the conventional model. To further enhance Ef phases and minimize cogging torque of the proposed model, the proposed AFPMSM model was optimized by varying different sides of PMs using a genetic algorithm (GA). A time-stepped three-dimensional (3D) finite element analysis (FEA) was performed for the comparative analysis of conventional, proposed, and optimized AFPMSM models. From this comparative performance analysis, it is observed that torque ripples and cogging torque of the optimized AFPMSM are significantly decreased, while output average torque is appreciably increased. Ef and output power are also enhanced

Minimization of Torque Ripples in Multi-Stack Slotted Stator Axial-Flux Synchronous Machine by Modifying Magnet Shape

This paper presents a proposed model of a multi-stack slotted stator axial-flux type permanent magnet synchronous machine (AFPMSM) specifically for reducing torque ripple. The proposed AFPMSM model uses pentagon-shaped permanent magnets (PMs). It has a low value of cogging torque and torque ripples compared to the conventional model with a trapezoidal magnet shape. Additionally, it has increased internal generated voltage (Ef) as compared to the conventional model. To further enhance Ef phases and minimize cogging torque of the proposed model, the proposed AFPMSM model was optimized by varying different sides of PMs using a genetic algorithm (GA). A time-stepped three-dimensional (3D) finite element analysis (FEA) was performed for the comparative analysis of conventional, proposed, and optimized AFPMSM models. From this comparative performance analysis, it is observed that torque ripples and cogging torque of the optimized AFPMSM are significantly decreased, while output average torque is appreciably increased. Ef and output power are also enhanced

Novel Protection Coordination Scheme for Active Distribution Networks

Distribution networks are inherently radial and passive owing to the ease of operation and unidirectional power flow. Proper installation of Distributed Generators, on the one hand, makes the utility network active and mitigates certain power quality issues e.g., voltage dips, frequency deviations, losses, etc., but on the other hand, it disturbs the optimal coordination among existing protection devices e.g., over-current relays. In order to maintain the desired selectivity level, such that the primary and backup relays are synchronized against different contingencies, it necessitates design of intelligent and promising protection schemes to distinguish between the upstream and downstream power flows. This research proposes exploiting phase angle jump, an overlooked voltage sag parameter, to add directional element to digital over-current relays with inverse time characteristics. The decision on the direction of current is made on the basis of polarity of phase angle jump together with the impedance angle of the system. The proposed scheme at first is evaluated on a test system in a simulated environment under symmetrical and unsymmetrical faults and, secondly, as a proof of the concept, it is verified in real-time on a laboratory setup using a Power Hardware-in-loop (PHIL) system. Moreover, a comparative analysis is made with other state-of-the-art techniques to evaluate the performance and robustness of the proposed approach