Thermal management is pivotal for ensuring the safe and efficient operation of LIBs under dynamic conditions. Accurate core temperature monitoring remains a key BTMS challenge for predicting thermal distributions and ...
详细信息
Thermal management is pivotal for ensuring the safe and efficient operation of LIBs under dynamic conditions. Accurate core temperature monitoring remains a key BTMS challenge for predicting thermal distributions and mitigating TR risks. This study proposes a real-time core temperature estimation framework integrating joint EKF with an electro-thermal-aging model (ECM-1D). Using only surface temperature and voltage measurements, it simultaneously estimates core temperature, SOC, and capacity with bidirectional electro-thermal coupling. The hybrid approach pre-calibrates temperature/SOC/SOH-dependent parameters offline while updating capacity online. Validation under extreme conditions (high-rate cycling, aging, and ISCs) demonstrates 60% lower core temperature RMSE during high-rate cycling, a maximum estimation error below 0.9 K, and 58.9% reduction in SOC estimation error under aging conditions versus existing methods. The framework reliably tracks core temperature trends despite parasitic heat and signal noise, enabling earlier critical temperature warnings. This provides a foundation for TR prevention, advancing battery safety for EV and grid storage applications. Future extensions could integrate physical aging mechanisms and enhance fault detection capabilities.
At the early age of Railway Systems, the DC solution enabled the deployment of lightweight and efficient traction locomotives compared to AC systems as they do not have to carry a heavy step-down transformer and the r...
详细信息
ISBN:
(纸本)9798350346893
At the early age of Railway Systems, the DC solution enabled the deployment of lightweight and efficient traction locomotives compared to AC systems as they do not have to carry a heavy step-down transformer and the rectifier bridge. Moreover, the contact line voltage is sustained by substations connected in parallel along the line, determining a high supply reliability and a balanced load for the AC power grid. However, the protection of this system against short circuit is a challenging task as the configuration of the DC system can change and the short-circuit current is in the order of the substation rated current. The protection system currently installed in DC railway systems is effective in clearing faults, however, it has reached its performance limit, and in order to increase the global system performance, new protection technologies must be investigated. In this paper, a new model-based Fault Detection algorithm (FDA) is proposed. The simulation results prove its ability to overcome the limitations of the current protection system and to localize the fault position in many operating conditions.
In a centralized protection and control substation (CPC), all of the measurements of the substation, includes voltages and currents, are available to its centralized high-performance processor. This paper proposes a m...
详细信息
In a centralized protection and control substation (CPC), all of the measurements of the substation, includes voltages and currents, are available to its centralized high-performance processor. This paper proposes a model-based algorithm for protection of the power transformer in a CPC-based substation. The main difficulty in the use of conventional model-based algorithms lies in modeling of the nonlinear behavior of the transformer core. To tackle this problem, in this paper, multiple linear models are employed to simulate the nonlinearity of the magnetic core. At each time instance, the dynamic behavior of the transformer will be followed by one of these linear models and, the proposed algorithm switches between these linear models based on the concept of interactive multiple model (IMM) algorithm. This way, not only the accuracy of the proposed algorithm increases but also the computational burden is significantly reduced compared to conventional model-based algorithms. Therefore, the proposed algorithm has better potential to be implemented in real-world microprocessors. Several experimental tests include turn-to-turn (TTF) and turn-to-ground faults (TGFs) have been employed to reveal the effectiveness of the proposed IMM-based protection algorithm.
Grasping deformable objects remains a challenging operational task for robots in diverse industrial applications. Different characteristics of deformable objects to be gripped need to be considered in the mechanical d...
详细信息
Grasping deformable objects remains a challenging operational task for robots in diverse industrial applications. Different characteristics of deformable objects to be gripped need to be considered in the mechanical design of the gripper. Mechanical grippers often rely on sensors and appropriate control strategies to grasp deformable objects. This study classifies deformable objects, grippers and gripper manufacturers, and their corresponding gripping strategies. In the study of control strategies, model-based algorithm control strategies are often ineffective as often the objects to be gripped are unknown in terms of its rigidity and other morphological characteristics. In contrast, model-free algorithms do not need parametric information of the objects as only input-output signal is required. This allows the model-free controlled grippers adapt to diverse and unstructured environments. Finally, the advantages and disadvantages of current deformable object-grasping techniques are discussed and summarized. The challenges and future directions of robots grasping deformable objects are pointed out.
Computer-based radiation therapy requires high targeting and dosimetric precision. Analytical dosimetric algorithms typically are fast and clinically viable but can have increasing errors near air-bone interfaces. The...
详细信息
Computer-based radiation therapy requires high targeting and dosimetric precision. Analytical dosimetric algorithms typically are fast and clinically viable but can have increasing errors near air-bone interfaces. These are commonly found within dogs undergoing radiation planning for sinonasal cancer. This retrospective methods comparison study is designed to compare the dosimetry of both tumor volumes and organs at risk and quantify the differences between collapsed cone convolution (CCC) and Monte Carlo (MC) algorithms. Canine sinonasal tumor plans were optimized with CCC and then recalculated by MC with identical control points and monitor units. Planning target volume (PTV)(air), PTVsoft tissue, and PTVbone were created to analyze the dose discrepancy within the PTV. Thirty imaging sets of dogs were included. Monte Carlo served as the gold standard calculation for the dosimetric comparison. Collapsed cone convolution overestimated the mean dose (D-mean) to PTV and PTVsoft tissue by 0.9% and 0.5%, respectively (both P < 0.001). Collapsed cone convolution overestimated D-mean to PTVbone by 3% (P < 0.001). Collapsed cone convolution underestimated the near-maximum dose (D-2) to PTVair by 1.1% (P < 0.001), and underestimated conformity index and homogeneity index in PTV (both P < 0.001). Mean doses of contralateral and ipsilateral eyes were overestimated by CCC by 1.6% and 1.7%, respectively (both P < 0.001). Near-maximum doses of skin and brain were overestimated by CCC by 2.2% and 0.7%, respectively (both P < 0.001). As clinical accessibility of Monte Carlo becomes more widespread, dose constraints may need to be re-evaluated with appropriate plan evaluation and follow-up.
Monitoring the health of large-scale infrastructure with the required precision necessitates high-dimensional support models and extensive instrumentation. However, in a model-based structural health monitoring (SHM) ...
详细信息
Monitoring the health of large-scale infrastructure with the required precision necessitates high-dimensional support models and extensive instrumentation. However, in a model-based structural health monitoring (SHM) framework, the ability to localize damage is constrained by the discretization of the model. To enhance the resolution of discretization, dense instrumentation is essential to address the inherent challenges in solving the inverse problem. Yet, increasing dimensionality can introduce detection delays, a critical concern in SHM. Additionally, addressing uncertainties stemming from the model, measurements, or external factors is crucial for reliable real-world SHM. This study focuses on localized damages, such as cracks, where detection precision is paramount. To tackle these challenges, this study proposes an innovative hybrid interacting Particle-Kalman filter (h-IPKF)-based SHM approach that surpasses model discretization limitations for detection resolution. This approach employs two distinct indices for crack localization: global (GDI) and local (LDI) damage indices. GDI identifies the affected element using a coarsely discretized predictor model, while LDI precisely pinpoints the crack location within the element. This paper represents the crack as a massless rotational spring with deteriorated stiffness (gamma) and parameterizes it using GDI, LDI, and gamma. Subsequently, the h-IPKF framework is employed to estimate the crack parameters, capable of handling both continuous and discrete random variables, which is advantageous for addressing discrete variables like GDI. Extensive numerical and real validation tests on beam structures were conducted to assess the algorithm's sensitivity to noise and damage severity, demonstrating its efficiency, promptness, and precision in detecting cracks within structures.
The increasing development in the computational field that allowed software and hardware advances enables more refined building performance analysis. Simulation-based optimization (SBO) methods allow high standards to...
详细信息
The increasing development in the computational field that allowed software and hardware advances enables more refined building performance analysis. Simulation-based optimization (SBO) methods allow high standards to be achieved by combining parametric modeling, simulation, and optimization methods. However, SBO methods still need development, especially regarding the correct choice of the optimization algorithmbased on the specific characteristics of each problem. This study proposes a multi-objective optimization algorithms benchmark by comparing seven multi-objective optimization algorithms: RBFMOpt, NSGA2, MHACO, NSPSO, MOEA/D, HypE, and SPEA2, across nine building-related problems, including thermal, energy, and daylight simulation. The problems varied from 5 to 18 discrete, continuous, and mixed parameters. The objective functions varied between two and three. We used the hypervolume indicator, IGD+, GD+, and EPS + to compare algorithms' performance and assess the tendency to reduce computational costs. We also performed the Kruskal-Wallis non-parametric test to analyze the impact of multiple runs on the hypervolume indicator. The results showed that RBFMOpt and HypE perform best across all problems. However, RBFMOpt tends to reduce computational costs since the algorithm requires fewer simulations to obtain the best results.
A model-based algorithm is proposed and tested using the simulator and operation data of a plastic pipeline prototype to locate multiple non-simultaneous leaks in the pipeline. A combination of an extended Kalman filt...
详细信息
ISBN:
(纸本)9781728115085
A model-based algorithm is proposed and tested using the simulator and operation data of a plastic pipeline prototype to locate multiple non-simultaneous leaks in the pipeline. A combination of an extended Kalman filter and obtained relations from the steady state response is used in order to tackle the problem of multi-leak localization. To achieve the mentioned relations, a real pipe with two leaks is equated to a virtual pipe with a single virtual equivalent leak.
In previous study, a tomographic imaging system is built up for measuring the three-dimensional refractive index distribution inside the micrometer-sized biological cell by optically driven full-angle rotation scheme ...
详细信息
ISBN:
(数字)9781510628007
ISBN:
(纸本)9781510628007
In previous study, a tomographic imaging system is built up for measuring the three-dimensional refractive index distribution inside the micrometer-sized biological cell by optically driven full-angle rotation scheme based on digital holographic microscopy, named as optical-driven tomographic DHM (OT-DHM) system. However, a small perturbation of the system will lead the inaccurate of the positions and the orientation of the micrometer-sized sample, thus the automatic calibration of the reconstructed phase images in the OT-DHM system is required. For this purpose, a novel model-based algorithm is proposed, in which we employ a 3-D ellipse shape for modeling the samples. The parameters of the ellipse-like shape on a small number of the projections are estimated and used them to build up the 3-D ellipse model of the samples. In advance, the reconstructed phase images are highly contaminated by the uneven background and coherence speckle noise. The block-based between-class criterion is used to suppress the effect of the non-uniform background, and the anisotropic diffusion process is utilized for the noise cleaning, including shot noise and speckles noise on the reconstructed phase. The boundary of the cell in each projection can be considered as the 2-D ellipse, and used to estimate the parameters of the 2-D ellipse. The established 3-D ellipse shape is applied for the calibration of the spatial positions and the orientations of the all other rotational angles. With the automatic calibration algorithm, the OT-DHM system can effectively reconstructed the three-dimensional refractive index distribution inside the micrometer-sized samples.
The paper deals with the optimization of an anaerobic digester with respect to a performance criterion which targets the maximization of the methane production. It is penalized by the environment pollution with the di...
详细信息
The paper deals with the optimization of an anaerobic digester with respect to a performance criterion which targets the maximization of the methane production. It is penalized by the environment pollution with the discharged water. The paper includes a comparative study regarding the performances of two optimization approaches: the extremum seeking control, in stochastic and deterministic versions, and the model-based control respectively. The latter uses a characteristic of the optimal regimes which supplies the optimal setpoint (the dilution rate) as a function of the substrate concentration in the inflow, estimated by an extended Kalman filter. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
暂无评论