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Conference Object A Lithium-Ion Battery Fast Charging Algorithm Based on Electrochemical Model: Experimental Results(Amer Soc Mechanical Engineers, 2024) Anwar, Sohel; Pramanik, Sourav; Amini, AliLithium-Ion batteries have become the principal battery technology for EVs to date. However, one of the principal factors limiting the widespread usage of the EVs is the length of charging times for the lithium-ion battery packs. The appropriate charging algorithm is critical to shorten the battery charging times while keeping the battery safe. In our earlier work, we proposed a novel optimal strategy for charging the lithium-ion battery based on electrochemical battery model using A performance index that aimed at achieving a faster charging rate while maintaining safe limits for various battery parameters. A more realistic model, based on battery electro-chemistry has been used for the design of the optimal charging algorithm as opposed to the conventional equivalent circuit models. Simulation results showed that the proposed optimal charging algorithm is capable of shortening the charging time of a lithium-ion cell by as much as 30% when compared with the standard constant current charging. Here we present the results from a number of experiments using Lithium-Ion cylindrical cells that were charged using the proposed algorithm and compared the charging times with the standard constant current-constant voltage (CC-CV) charging algorithms. A Maccor Series 4300 battery testing system was used to carry out the experiments. The experimental results showed that the proposed algorithm offered shorter charging times by up to 16% when compared to the CC-CV charging algorithms under the same battery initial conditions such as SOC and temperature of the cells.Conference Object Queue Management Systems in Airport Management: Enhancing Passenger Flow and Operational Efficiency(Springer Science and Business Media Deutschland GmbH, 2026) Erkan, T.E.; Ozdemir, M.F.Queue management systems (QMS) streamline airport operations by determining travel patterns that help manage the passenger flow, reducing wait times, and enhancing operational efficiency. They help optimize queue configurations by real-time data analytics and employing algorithms, working to guide passengers efficiently through the place for check-in, security clearance, and boarding. It leads to a much more pleasant time for the passengers while ensuring better resource utilization and operational planning. This Paper investigates a new queue management system that utilizes advanced technologies like artificial intelligence and real-time data analytics. Such systems enable monitoring of passenger flocking and behavior for adjustability concerning the length of queues and the optimization of service times. The result is an enhanced travel experience and improved airport operational efficiency. The paper takes Singapore Changi Airport as a case study to aid the understanding of how effective management of queues can lead to effective Rose operational efficiency. These findings show that airports can significantly reduce passenger wait times using advanced queue management technologies and enhance the travel experience while facilitating operations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
