Related papers: Sensorless Battery Internal Temperature Estimation…
In this paper, data-driven algorithms based on Koopman Operator Theory are applied to identify and predict the nonlinear dynamics of a vapor compression system and cabin temperature in a light-duty electric vehicle. By leveraging a…
Kelvin probe force microscopy (KPFM) is a powerful tool for studying contact electrification, using an tiny tip to image voltages caused by transferred charge. It has been used in stationary studies focused on finding patterns (e.g.…
To control structural responses under various actions, the growing use of supplementary damping systems in modern civil engineering structures necessitates inspecting and evaluating their operational performance postinstallation. However,…
Cloud-based battery management system (BMS) requires accurate terminal voltage measurement data to ensure optimal and safe charging of Lithium-ion batteries. Unfortunately, an adversary can corrupt the battery terminal voltage data as it…
Recent advances in counter-adversarial systems have garnered significant research attention to inverse filtering from a Bayesian perspective. For example, interest in estimating the adversary's Kalman filter tracked estimate with the…
Accurate estimation of thermosphere mass density is critical to determining how satellite orbits evolve over time and thus to planning and managing space missions. Empirical thermosphere models are commonly employed for this purpose, but…
In this paper, we focus on sensor placement in linear dynamic estimation, where the objective is to place a small number of sensors in a system of interdependent states so to design an estimator with a desired estimation performance. In…
This paper proposes the online parameters identification of semi-empirical models of Proton Exchange Membrane Fuel Cell (PEMFC). The covariance of unknown measurement noise is also estimated simultaneously. The actual data are fed to Kalman…
Accurate and stable state estimation is critical for battery management. Although dual Kalman filtering can jointly estimate states and parameters, the strong coupling between filters may cause divergence under large initialization errors…
Measuring the total electron emission yield of dielectric materials remains a challenging task. Indeed, the charge induced by irradiation and electron emission disturbs the measurement. It is therefore important to quantify this charge…
Kalman filter-based algorithms are fundamental for mobile robots, as they provide a computationally efficient solution to the challenging problem of state estimation. However, they rely on two main assumptions that are difficult to satisfy…
The complex ac impedance of a bolometer or microcalorimeter detector is easily measured and can be used to determine thermal time constants, thermal resistances, heat capacities, and sensitivities. Accurately extracting this information…
In this paper, we report on a multicore fiber-based (MCF) temperature sensor that operates in a wide thermal range and that is robustly packaged to withstand harsh environments. To develop the sensor, the fundamentals concerning the effect…
We propose a Neural-Enhanced Distributed Kalman Filter (NDKF) for multi-sensor state estimation in nonlinear systems. Unlike traditional Kalman filters that rely on explicit analytical models and assume centralized fusion, NDKF leverages…
Optimal cooling that minimises thermal gradients and the average temperature is essential for enhanced battery safety and health. This work presents a new modelling approach for battery cells of different shapes by integrating Chebyshev…
A concise approach is proposed to determine a reduced order control design oriented dynamical model of a multi-stage hot sheet metal forming process starting from a high-dimensional coupled thermo-mechanical model. The obtained reduced…
We apply estimation theory to a system formed by two interacting trapped ions. By using the Fisher matrix formalism, we introduce a simple scheme for estimation of the temperature of the longitudinal vibrational modes of the ions. We use…
A fast inverse heat conduction model (IHCM) is developed for estimating unknown properties of multi-layer composites considering internal heat generation. This work builds on the validated analytical forward models presented in Part I.…
The input-parameter-state estimation capabilities of a novel unscented Kalman filter is examined herein on both linear and nonlinear systems. The unknown input is estimated in two stages within each time step. Firstly, the predicted dynamic…
Lithium-ion batteries are widely used in electric vehicles and grid energy storage systems. Compared to cylindrical batteries, prismatic cells are the primary choice because of their advantage for dense packing. However, thermal runaway and…