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PRODID:-//Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系 - ECPv6.15.20//NONSGML v1.0//EN
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X-ORIGINAL-URL:https://ece.hku.hk
X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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TZID:Asia/Hong_Kong
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TZOFFSETFROM:+0800
TZOFFSETTO:+0800
TZNAME:HKT
DTSTART:20240101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20250411T140000
DTEND;TZID=Asia/Hong_Kong:20250411T150000
DTSTAMP:20260512T004429
CREATED:20250410T071246Z
LAST-MODIFIED:20250410T071251Z
UID:111094-1744380000-1744383600@ece.hku.hk
SUMMARY:Mirror-Symmetrical Dijkstra’s Algorithm-Based Deep Reinforcement Learning for Dynamic Wireless Charging Navigation of Electric Vehicles
DESCRIPTION:Zoom Link: https://hku.zoom.us/j/91849018634?pwd=YgyqXnIIfUsd8YGU2YNaSa5aj3uWou.1\nMeeting ID: 918 4901 8634\nPassword: 038419 \nAbstract\nThe dynamic wireless charging (DWC) system based on wireless charging lanes (WCLs) is an important component of smart cities\, allowing electric vehicles (EVs) to charge while moving. It is necessary to establish a user-oriented real-time DWC navigation system to achieve the joint optimization of EV routing and charging. However\, the modeling characteristics of DWC and the risk preferences of EV owners towards congested WCLs are completely different from those in traditional wired charging. Furthermore\, optimal EV charging navigation is always challenging without prior knowledge of uncertainty in electricity prices and traffic conditions. This work first proposes a novel dynamic charging routing model for individual EVs to minimize travel and charging costs\, and reformulates it as a two-step optimization problem to facilitate feature extraction. Then\, mirror-symmetrical Dijkstra’s algorithm (MSDA) is proposed to solve the reformulated model in linear time and extract advanced features from the stochastic information. By feeding the system state containing extracted features into the deep Q network (DQN) in an event-triggered manner\, the near-optimal charging navigation strategy is finally obtained. The proposed MSDA-DQN approach not only efficiently extracts low-dimensional interpretable input features\, but also adaptively learns the unknown dynamics of system uncertainty. Numerical results based on simulated and real-world data validate the proposed approach. \nSpeaker\nMiss Chaoran Si\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nChaoran Si received her bachelor degree from Tianjin University in 2018 and her master degree from Zhejiang University in 2021\, both in electrical engineering. She is currently working toward the Ph.D. degree in electrical and electronic engineering in the Department of Electrical and Electronic Engineering at the University of Hong Kong. Her current research interests include power-transportation systems\, wireless charging of electric vehicles\, and deep reinforcement learning. \nOrganiser\nProf. Yunhe Hou\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome!
URL:https://ece.hku.hk/events/20250411-1/
LOCATION:Online via Zoom
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/11/rpg-seminar.jpg
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20250411T150000
DTEND;TZID=Asia/Hong_Kong:20250411T160000
DTSTAMP:20260512T004429
CREATED:20250410T071430Z
LAST-MODIFIED:20250410T071430Z
UID:111097-1744383600-1744387200@ece.hku.hk
SUMMARY:Wireless Permanent-Magnet Brushless DC Motor Using Contactless Feedback
DESCRIPTION:Zoom Link: https://hku.zoom.us/j/94707594608?pwd=oSy6rRXxpXyd6bapdlmVDCtv9GRPrd.1\nMeeting ID: 947 0759 4608\nPassword: 566410 \nAbstract\nWireless power transfer (WPT) is a fast-developing technology in industrial and domestic applications. It achieves electrical and physical isolation between the power supply and load\, bringing high flexibility and safety. Based on WPT\, wireless motors allow electric motors to work in sealed environments\, however\, when using a single controller at the transmitter side\, acquiring the feedback of wireless motors is challenging because of the contactless structure. We propose a wireless permanent-magnet brushless DC motor with contactless feedback\, the rotor position measured by a wireless-powered Hall effect sensor is modulated and sensed at the transmitter side for commutation and precise speed control. Also\, the proposed system adopts hybrid modulation including PWM and sigma-delta modulated PFM (Σ-Δ PFM) to reduce the switching loss in the whole control process. Compared with existing wireless motor systems\, the proposed system realizes both power and control in the fully wireless approach and keeps good dynamic performance.  \nSpeaker\nMr. Songtao LI\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nSongtao Li received the B.Eng and M.Eng degrees in instrument science and technology from Southeast University\, Nanjing\, China in 2018 and 2021\, respectively. He is currently working toward the Ph.D. degree in electrical and electronic engineering in the University of Hong Kong\, Hong Kong\, China. His current research interests include power electronics\, wireless power transfer\, and electric vehicle technologies. \nOrganiser\nProf. Yunhe Hou\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome!\n\n——-
URL:https://ece.hku.hk/events/20250411-2/
LOCATION:Online via Zoom
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/11/rpg-seminar.jpg
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