Hybrid-electric propulsion systems powered by clean energy derived from renewable sources offer a promising approach to decarbonise the world's transportation systems. Effective energy management systems are critical for such systems to achieve optimised operational performance. However, developing an intelligent energy management system for applications such as ships operating in a highly stochastic environment and requiring concurrent control over multiple power sources presents challenges. This article proposes an intelligent energy management framework for hybrid-electric propulsion systems using deep reinforcement learning. In the proposed framework, a Twin-Delayed Deep Deterministic Policy Gradient agent is trained using an extensive volume of historical load profiles to generate a generic energy management strategy. The strategy, i.e. the core of the energy management system, can concurrently control multiple power sources in continuous state and action spaces. The proposed framework is applied to a coastal ferry model with multiple fuel cell clusters and a battery, achieving near-optimal cost performance when applied to novel future voyages.
Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems
Islamic Azad University（伊斯兰阿扎德大学）；Khaje Nasirodin Toos (K.N.Toosi) University of Technology（霍贾·纳西罗丁·图斯（K.N.图斯）理工大学）；Shiraz University（设拉子大学）；Florida Atlantic University（佛罗里达大西洋大学）；The University of Alabama（阿拉巴马大学）；The University of Texas at Arlington（德克萨斯大学阿灵顿分校）；University of Alabama（阿拉巴马大学）
Distributed Adaptive Control for DC Power Distribution in Hybrid-Electric Aircraft: Design and Experimental Validation
Brandenburg University of Technology Cottbus-Senftenberg（勃兰登堡工业大学科特布斯-森夫滕贝格）；Potsdam Institute for Climate Impact Research（波茨坦气候影响研究所）；Rolls-Royce Deutschland Ltd & Co（罗尔斯·罗伊斯德国有限公司）
Intelligent Condition Monitoring of Industrial Plants: An Overview of Methodologies and Uncertainty Management Strategies
Department of Electrical and Computer Engineering, University of Victoria（电气与计算机工程系，维多利亚大学）；Department of Mechanical Engineering, University of Victoria（机械工程系，维多利亚大学）
Intelligent Duty Cycling Management and Wake-up for Energy Harvesting IoT Networks with Correlated Activity
Centre for Wireless Communications（无线通信中心）；University of Oulu（奥卢大学）；Instituto Universitario de Investigación y Desarrollo Tecnológico（大学技术研究与发展研究所）；Universidad Tecnológica Metropolitana（都市科技大学）；Aalborg University（奥尔堡大学）；University of Houston（休斯顿大学）
