Due to the substantial increase in the number of electrically driven systems onboard more electric aircraft (MEA), the onboard electric power systems (EPSs) are becoming more and more complex. Therefore, there is a need to develop a control strategy to manage the overall EPS energy flow and ensure the operation of safety-critical systems (which are electrical loads) under different operating scenarios and to consider EPS losses minimization, exploiting the thermal capability of generators, different load priorities, and available batteries with their charging and discharging schedules. This article presents an energy management (EM) strategy that considers the aforementioned objectives. The optimal droop gain approach is employed as a power-sharing method to minimize the total EPS losses in MEA. A finite state machine (FSM) has been used to implement the control strategy to realize the EPS reconfiguration

This paper provides a design, a charging control, and energy management of a movable Photo Voltaic (PV) charging station with an Automatic Battery Replacement (ABR) system to enable drones for ongoing missions. The paper represents the first stage of a three-staged project titled Fall Armyworm (FAW) insect killer. The other two stages involve the flight control of drones and detecting and killing FAW insects. Without chemical methods, the project aims to eliminate harmful FAW insects that are rapidly spreading in Africa and Asia. The power source is a hybrid PV system with energy storage devices (batteries and supercapacitors). The maximum power from PV panels is tracked using three different online methods (PSO, IC, and P&O), and the best method with the highest accuracy is selected. The experimental and simulation results approved that PSO is the recommended method used in this project among the studied methods because of its high target reach (about 97%) and low steady-state oscillation (maximum 2.15%). An intelligent energy management system is investigated and designed to efficiently utilize solar power with a constant-current constantvoltage charger for LiPo batteries. A new Battery Selection System (BSS) is designed and verified to efficiently utilize the harvested energy and increase the mission time. The BSS targets to manage the selection of the appropriate battery to charge and control its charging rate. The system performance is tested using MATLAB software. Then, an experimental setup for the system is built to validate simulation results. The results of simulations and experiments proved the reliability of BSS

Finding the optimum path for mobile robots is now an essential task as lots of autonomous mobile robots are widely used in factories, hospitals, farms, etc. Many path planning algorithms have been developed to finding the optimum path with the minimum processing time. The vertical cell decomposition algorithm (VCD) is one of the popular path planning algorithms. It is able to find a path in a very short time. In this paper, we present a new algorithm, called the Radial cell decomposition (RCD) algorithm, which can generate shorter paths and a slightly faster than VCD algorithm. Furthermore, the VCD algorithm cannot be applied directly to obstacles in special cases, like two vertices have the same x-coordinate; on the other hand, the RCD algorithm can be applied to these special cases directly. In addition to that, the RCD algorithm is very suitable for corridor environments, unlike the VCD algorithm. In this paper …

Structure health monitoring is a general term used to describe the process of assessing the civil structure status and detecting and/or identifying any damage that occurs in the structure under monitoring. This work presents the design and operation of a synchronized structure health monitoring system that utilizes the internet of things technology. The proposed system consists of leaf nodes, a central node, and a monitoring server. The system utilizes two different wireless technologies to efficiently transfer the data and eliminate the need of fixed network infrastructure. The leaf nodes collect the acceleration signals from specific points in the structure using synchronized accelerometer sensors and send these signals to the central node using short range wireless communication protocol. The sampling process is synchronized among different sensors using an accurate timing signal from the global positioning system and an accurate external clock. The central node gathers the signals and relays them to a remote server using long range cellular internet connectivity. At the server, different damage detection and identification techniques are applied on the received data to assess the status of the structure. We provide details about the proposed system design and operation including the hardware and software parts. The different damage detection and identification techniques were considered and compared for predicting structural damage. Moreover, practical experiments were carried out, in which a five-story building model and real plane truss bridge were used to test the system. The results show the feasibility of the proposed synchronized system in automating the change in stiffness and mass by monitoring the dynamic behaviour.