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"SOC Estimation using Deep Bidirectional Gated Recurrent Units with Tre" by D. N.T. How, M. A. Hannan et al.

State-of-charge (SOC) is a crucial battery quantity that needs constant monitoring to ensure cell longevity and safe operation. However, SOC is not an observable quantity and cannot be practically measured outside of laboratory environments. Hence, machine learning (ML) has been employed to map correlated observable signals such as voltage, current and temperature to SOC values. In recent studies, deep learning (DL) has been a prominent ML approach outperforming many existing methods for SOC estimation. However, yielding optimal performance from DL models relies heavily on appropriate selection of hyperparameters. At present, researchers relied on established heuristics to select hyperparameters through manual tuning or exhaustive search methods such as grid search (GS) and random search (RS). This results in lengthy development time in addition to less accurate and inefficient models. This study proposes a systematic and automated approach to hyperparameter selection with a Bayesian o ....

Tree Parzen Estimator , Idirectional Gated Recurrent Unit , Computational Modeling , Computer Architecture , Data Models , Deep Learning , Lithium Ion Battery , State Of Charge , Tate Of Charge Estimation , Temperature Measurement ,

"A review of controllers and optimizations based scheduling operation f" by M. S. Hossain Lipu, Shaheer Ansari et al.

The microgrid connected with the battery energy storage system is a promising solution to address carbon emission problems and achieve the global decarbonization goal by 2050. Proper integration of the battery energy storage system in the microgrid is essential to optimize the overall efficiency as well as manage the power efficiently and securely. However, battery energy storage system integrated microgrid exhibits several concerns, including intermittencies, poor power quality, high capital cost, and energy imbalance between supply and demand. To address these shortcomings, an improved scheduling controller and optimization of the battery energy storage system are required to ensure the resilient, sustainable, and economic operation of the microgrid. Several approaches have been employed to improve the performance of microgrids; however, the review studies on controllers and optimizations based scheduling operations in microgrid have not been explored yet. In light of this research g ....

Battery Energy Storage , Harging And Discharging , Cheduling Controller , State Of Charge ,

"On Data Collection in SIC-Capable Space–Air–Ground Integ" by Yawen Zheng and Kwan Wu Chin

This article considers routing and uplinks scheduling in space–air–ground integrated networks. Specifically, it considers a successive interference cancellation-capable unmanned aerial vehicle (UAV) that collects data from ground devices operating in an Internet of Things network. Its objective is to maximize the minimum flow rate to a terrestrial gateway over a fixed time horizon. It outlines a mixed integer linear program (MILP) to optimize in each time slot: the routing from the UAV to the gateway, the set of links from ground devices to the UAV, and the flow rate over links. It also proposes a novel algorithm, called iterative flow and path reservation (IFPR), for use by the UAV to select paths. Further, IFPR uses two methods to schedule communications between ground devices and the UAV. The first method, called simplified MILP (SMILP), aims to maximize the sum rate from ground devices. The second method, called less data schedule first, prioritizes ground devices that have upl ....

Intersatellite Links Isls , Link Scheduling , Ultipacket Reception ,