Enhanced distributed estimation based on prior information

Khalid, Haris M.; Peng, Jimmy Chih-Hsien; Mahmoud, Magdi S.

doi:10.1049/iet-spr.2014.0029

Cited by 7 publications

(2 citation statements)

References 25 publications

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“…Growth and Expansion of Renewable Power Generation Rise in Installed Capacity: Statistics indicating the exponential growth of installed renewable energy capacity over recent years [72]. Technological Advancements: Innovations in renewable energy technologies driving increased efficiency and cost-effectiveness [73]. Economic Viability: Declining costs of renewable energy production making it increasingly competitive with traditional fossil fuel-based power generation [74,75].…”

Section: Optimizing Energy Storage Systems For Enhanced Integration I...mentioning

confidence: 99%

Innovations in Battery Technology: Enabling the Revolution in Electric Vehicles and Energy Storage

Khan

2024

BJMAS

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The rapid advancement of battery technology stands as a cornerstone in reshaping the landscape of transportation and energy storage systems. This paper explores the dynamic realm of innovations propelling the surge in electric vehicles (EVs) and revolutionizing energy storage solutions. Beginning with an overview of the current state of battery technology, this study delves into the critical role played by lithium-ion batteries in driving the EV market's expansion. It discusses the limitations of lithium-ion batteries in terms of energy density, charging times, and materials sourcing, thereby emphasizing the pressing need for breakthroughs in battery innovation. In addressing these challenges, the paper reviews emerging battery technologies, such as solid-state batteries, lithium-sulfur batteries, and flow batteries, shedding light on their potential to surpass existing limitations. It elucidates the principles, advantages, and challenges associated with each technology, offering insights into their feasibility for widespread adoption in EVs and grid-scale energy storage. The paper investigates ongoing research and development efforts, including advancements in nanotechnology, novel electrode materials, and manufacturing techniques aimed at enhancing battery performance, safety, and cost-effectiveness. It highlights the significance of scalable production methods and sustainable practices in ensuring the viability of next-generation batteries.

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Section: Optimizing Energy Storage Systems For Enhanced Integration I...mentioning

confidence: 99%

Innovations in Battery Technology: Enabling the Revolution in Electric Vehicles and Energy Storage

Khan

2024

BJMAS

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“…The ability to accurately monitor and analyze the behavior of dynamic systems in real time is essential for detecting faults, predicting failures, and optimizing performance. Signal processing and parameter estimation are fundamental techniques employed in dynamic system monitoring to extract valuable information from sensor data and estimate system parameters and states [2]. However, traditional approaches often face challenges in handling non-linear dynamics, noise, and uncertainties inherent in real-world systems.…”

Section: Introductionmentioning

confidence: 99%

Innovative Approaches for Dynamic System Monitoring: Signal Processing and Parameter Estimation Strategies

Gupta,

Patel

2024

JERR

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Dynamic system monitoring is essential for ensuring the optimal performance and reliability of various systems across multiple domains. This Abstract introduces innovative approaches focusing on signal processing and parameter estimation strategies for dynamic system monitoring. Signal processing techniques such as wavelet transform and adaptive filtering are utilized for noise reduction and feature extraction from sensor data. Additionally, parameter estimation strategies including Kalman filtering and Bayesian inference aid in accurately estimating system parameters and states in real-time. These advanced methods, integrating machine learning and statistical inference, promise enhanced monitoring capabilities, facilitating proactive maintenance and fault detection in complex dynamic systems. Through case studies and simulation results, the effectiveness and versatility of these approaches in addressing real-world challenges are demonstrated, illustrating their potential for advancing the field of dynamic system monitoring.

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Distributed estimation based on information‐based covariance intersection algorithms

Mahmoud

2015

Adaptive Control & Signal

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A distributed estimation approach is developed in this paper using information matrix filter on a distributed tracking system in which multiple sensors are tracking the same target. The information matrix filter version is derived from covariance intersection, weighted covariance and Kalman-like particle filter, respectively. The steady performance of these filters is evaluated with different feedback strategies. The developed filters are then validated on an industrial utility boiler.± and are optimal in the sense of minimum variance. At the end of each n sampling interval, each sensor transmits its local estimate to fusion center where track association and fusion are performed.

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Enhanced distributed estimation based on prior information

Cited by 7 publications

References 25 publications

Innovations in Battery Technology: Enabling the Revolution in Electric Vehicles and Energy Storage

Innovations in Battery Technology: Enabling the Revolution in Electric Vehicles and Energy Storage

Innovative Approaches for Dynamic System Monitoring: Signal Processing and Parameter Estimation Strategies

Distributed estimation based on information‐based covariance intersection algorithms

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