Wireless power transfer (WPT) is an essential enabler for novel sensor networks such as the wireless powered communication network (WPCN). The efficiency of an energy rectifier is dependent on both input power and loading condition. In this work, to maximize the rectifier efficiency, we present a low-complexity numerical method based on an analytical rectifier model to calculate the optimal load for different rectifier topologies, including half-wave and voltage-multipliers, without needing time-consuming simulations. The method is based on a simplified analytical rectifier model based on the diode equivalent circuit including parasitic parameters. Furthermore, by using Lambert-W function and the perturbation method, closed-form solutions are given for low-input power cases. The method is validated by means of both simulations and measurements. Extensive transient simulation results using different diodes (Skyworks SMS7630 and Avago HSMS285x) and frequency bands (400 MHz, 900 MHz, and 2.4 GHz) are provided for validation of the method. A 400 MHz 1- and 2-stage voltage multiplier are designed and fabricated, and measurements are conducted. Different input signals are used when validating the proposed methods, including the single sinewave signal and the multisine signal. The proposed numerical method shows excellent accuracy with both signal types, as long as the output voltage ripple is sufficiently low.
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http://dx.doi.org/10.3390/s21238038 | DOI Listing |
Proc Natl Acad Sci U S A
February 2025
Department of Construction Sciences, Lund University, Lund SE-22100, Sweden.
Preemptive identification of potential failure under loading of engineering structures is a critical challenge. Our study presents an innovative approach to design built-in prefailure indicators within multiscale structural designs with optimized load carrying capabilities utilizing the design freedom of topology optimization. The indicators are engineered to visibly signal load conditions approaching the global critical buckling load at predefined locations.
View Article and Find Full Text PDFPLoS One
January 2025
Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao, Liaoning, China.
To address the susceptibility of conventional vector control systems for permanent magnet synchronous motors (PMSMs) to motor parameter variations and load disturbances, a novel control method combining an improved Grasshopper Optimization Algorithm (GOA) with a variable universe fuzzy Proportional-Integral (PI) controller is proposed, building upon standard fuzzy PI control. First, the diversity of the population and the global exploration capability of the algorithm are enhanced through the integration of the Cauchy mutation strategy and uniform distribution strategy. Subsequently, the fusion of Cauchy mutation and opposition-based learning, along with modifications to the optimal position, further improves the algorithm's ability to escape local optima.
View Article and Find Full Text PDFMicrobiol Spectr
January 2025
Center for Infectious Diseases, Lab of Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands.
Unlabelled: Due to increasing antimicrobial resistance and side effects caused by current standard antimicrobial regimens used for treatment of prosthetic joint infection (PJI), alternative options are urgently needed. We aimed to investigate the effect of clindamycin in different exposure strategies against in an mature biofilm model. In short, 7-day biofilms were generated on polystyrene plates and titanium-aluminum-vanadium discs using a clinical PJI isolate.
View Article and Find Full Text PDFSci Rep
January 2025
Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, UK.
In general, edge computing networks are based on a distributed computing environment and hence, present some difficulties to obtain an appropriate load balancing, especially under dynamic workload and limited resources. The conventional approaches of Load balancing like Round-Robin and Threshold-based load balancing fails in scalability and flexibility issues when applied to highly variable edge environments. To solve the problem of how to achieve steady-state load balance and provide dynamic adaption to edge networks, this paper proposes a new framework that using PCA and MDP.
View Article and Find Full Text PDFSci Rep
January 2025
Seenovate, Paris, 75009, France.
Optimizing athletic training programs with the support of predictive models is an active research topic, fuelled by a consistent data collection. The Fitness-Fatigue Model (FFM) is a pioneer for modelling responses to training on performance based on training load exclusively. It has been subject to several extensions and its methodology has been questioned.
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