Undergraduate workshttp://hdl.handle.net/20.500.14131/22024-03-28T16:22:04Z2024-03-28T16:22:04ZThe Future of Energy: A Hybrid Human Motion Energy HarvesterAlmatrafi, LinaAlaidaroos, BatoolShigdar, Basmahttp://hdl.handle.net/20.500.14131/15042024-03-28T04:47:11ZThe Future of Energy: A Hybrid Human Motion Energy Harvester
Almatrafi, Lina; Alaidaroos, Batool; Shigdar, Basma
This comprehensive study delves into the design, analysis, and implementation of an Energy Harvester system, leveraging human leg motion for electricity generation. DC-DC converters, vital components in power electronics systems, are thoroughly explored, encompassing Boost, Cuk, SEPIC, and Zeta converters. The design process involves meticulous component selection, aligning with desired converter performance and specific application requirements.
The investigation extends beyond theoretical analysis, focusing on key performance parameters like efficiency, voltage ripple, transient response, and output regulation. Through rigorous examination, the study aims to provide practical insights into the intricate dynamics of DC-DC converters. To validate theoretical analyses and design principles, sophisticated simulation tools such as Simulink and MATLAB are employed. The project addresses challenges faced in connecting various system components, employing a combination of PS-simulink and Simulink-PS blocks. Additionally, the project introduces single and double pendulum models to simulate human leg motion, providing a nuanced understanding of rhythmic walking patterns.
Results showcase the Boost converter as the most efficient among the evaluated DC-DC converters, despite some limitations. The successful generation of 2.4 W of DC power from human motion demonstrates the system's potential in low-power electronics and wearable devices.
This research not only advances the field of DC-DC converters but also sheds light on the intricate dynamics of pendulum-based energy harvesting systems. The findings contribute valuable insights into the optimization of energy harvesting systems, emphasizing the role of pendulum dynamics and advanced control techniques in achieving efficient voltage conversion.
Designing Grid-Connected PV System at Effat University IT Server BuildingAlsudairy, NuhaJan, Shrooghttp://hdl.handle.net/20.500.14131/14732024-03-07T01:49:22ZDesigning Grid-Connected PV System at Effat University IT Server Building
Alsudairy, Nuha; Jan, Shroog
Development of a Battery Management System for Enhancing the Performance and Safety of Lithium-Ion Battery PacksBinsalim, HayaBadaam, Salmahttp://hdl.handle.net/20.500.14131/13792024-01-25T01:58:29ZDevelopment of a Battery Management System for Enhancing the Performance and Safety of Lithium-Ion Battery Packs
Binsalim, Haya; Badaam, Salma
Electrical grids generate energy using diverse power sources, including fossil fuels (gas and coal) and renewable sources (e.g., solar panels). However, the variability in power generation from these sources can lead to inefficiencies within the grid, resulting in energy wastage and potential damage to energy storage systems. In this context, developing robust energy storage solutions is crucial to maintain grid stability and optimize energy utilization. Battery packs integrated into the grid offer a promising solution for energy storage, but their efficient operation requires precise monitoring and control, which is achieved through Battery Management Systems (BMS). It manages individual cells' charging and discharging processes to maximize efficiency and extend their lifespan. Additionally, the BMS continuously monitors voltage and current levels to ensure they remain within safe limits, mitigating the risk of heat damage. This research investigates the challenges associated with energy generation and storage in electrical grids, emphasizing the need for efficient energy storage systems to prevent energy wastage and battery damage. The proposed solution focuses on BMS to monitor and control the energy storage process. This study offers a novel BMS design, incorporating Extended Kalman Filtering and a CCCV-based passive balancing algorithm to manage battery states, state of charge (SOC), state of health (SOH), and thermal characteristics. The research also includes a comprehensive simulation study conducted in SIMULINK with the Simscape toolbox to assess the effectiveness of the proposed BMS in a simulated grid environment. The simulation consists of a plant model representing the grid-connected battery pack, the BMS Electronic Control Unit (ECU) system, and various operational scenarios. The simulation results demonstrate that the proposed BMS design effectively monitors the battery pack's state, maintains cell balancing, estimates SOC, and regulates temperature and current levels within safe limits.
Performance Evaluation of Classic and Intelligent Controllers for ActuatorsAli, MirnaKamal, Janahttp://hdl.handle.net/20.500.14131/13752024-01-22T01:52:56ZPerformance Evaluation of Classic and Intelligent Controllers for Actuators
Ali, Mirna; Kamal, Jana
This capstone project focuses on optimizing actuator control, specifically for DC motors. The project aims to design and evaluate various controllers, ranging from classic to intelligent. Finding the optimal controller for a DC motor offers many advantages, including stability, robustness, and precise control, which are useful in fields like robotics. This paper proposes several controllers: pole placement, different configurations of PID, LQR, and LQI with different optimization techniques, fuzzy logic, and adaptive neuro-fuzzy controller schemes. The MATLAB environment was used to develop and test these controllers. Their performance was measured in terms of rise time, settling time, and overshoot. Based on the performance, the I-PD controller is overall the optimal controller for the DC motor. It achieves the fastest rise time of 507.7 msec, a settling time of 2.3 sec, and an overshoot of 0.51%