Results 71 to 80 of about 15,890,225 (198)
This paper presents a new recursive filter algorithm, the robust high-degree cubature information filter, which can provide reliable state estimation in the presence of non-Gaussian measurement noise. The novel algorithm is developed in the framework of
Naigang Cui +3 more
core +1 more source
ABSTRACT This study introduces a novel calibration strategy for the linear Kalman filter (LKF) fusion application in condition monitoring, specifically utilizing accelerated aging data. Unlike the existing literature that often focuses on complex nonlinear Kalman filter variants, this research delves into the calibration of LKF.
Emre Genis, Duygu Bayram Kara
wiley +1 more source
Develops a joint SOH‐RUL estimation model suitable for LIBs. This method leverages the PatchTST model and novel dynamic weighted kernel MSE (DWKMSE) loss function, employing transfer learning techniques to estimate SOH and RUL across different batteries. ABSTRACT This study proposes a transfer learning estimation method based on dynamic weighted kernel
Kaiyi Zhang, Xingzhu Wang
wiley +1 more source
Enhancing Energy Storage Efficiency: Advances in Battery Management Systems in Electric Vehicles
The rapid adoption of electric vehicles (EVs) underscores the urgent need for advanced battery management systems (BMS) to ensure safety, efficiency, and reliability. This article delves into the core functionalities of BMS, including state estimation, thermal management, and cell balancing, which are pivotal for optimizing battery performance ...
Hamid Naseem +3 more
wiley +1 more source
Square Root Cubature Particle Filter
The square root cubature particle filter (SRCPF) uses the square root cubature Kalman filter (SRCKF) for generating the proposal distribution. The SRCPF algorithm is easy to be implemented and has numerical stability.
Jun Min Zhang, Jing Mu, Yuan Li Cai
core +1 more source
Detecting Changes in Space‐Varying Parameters of Local Poisson Point Processes
ABSTRACT Recent advances in local models for point processes have highlighted the need for flexible methodologies to account for the spatial heterogeneity of external covariates influencing process intensity. In this work, we introduce tessellated spatial regression, a novel framework that extends segmented regression models to spatial point processes,
Nicoletta D'Angelo
wiley +1 more source
Cubature H∞ information filter
This paper presents a state estimation algorithm referred to as a cubature H∞ information filter (CH∞IF) for nonlinear systems. The proposed algorithm is developed from a cubature Kalman filter, an H∞ filter and an extended information filter. The CH ∞IF
Postlethwaite, Ian +2 more
core
A Type‐3 Fuzzy‐Based Model Predictive Control Approach for Management of Constant Energy
Application of the type‐3 fuzzy logic system (T3‐FLS) for management of constant energy and a comparison with the type‐2 fuzzy logic system. ABSTRACT Despite direct current (DC) microgrids' benefits over alternating current microgrids, these systems confront several difficulties.
Man‐Wen Tian +7 more
wiley +1 more source
ABSTRACT Numerical models are essential for comprehending intricate physical phenomena in different domains. To handle their complexity, sensitivity analysis, particularly screening is crucial for identifying influential input parameters. Kernel‐based methods, such as the Hilbert‐Schmidt Independence Criterion (HSIC), are valuable for analyzing ...
Guerlain Lambert +2 more
wiley +1 more source
In this article, hybrid probabilistic and geometric constellation shaping to enhance spectral efficiency in coherent optical communication systems, particularly under a Wiener phase noise channel, is investigated. By integrating a two‐stage phase search algorithm with digital signal processing and gradient descent, the method outperforms geometrically ...
Zhiyang Liu +5 more
wiley +1 more source

