Electrical & Computer Engineering Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2765
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Item Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles(2016) Shen, Junyi; Khaligh, Alireza; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.Item A Platform Towards In Situ Stress/Strain Measurement in Lithium Ion Battery Electrodes(2012) Baron, Sergio Daniel; Ghodssi, Reza; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis demonstrates the design, fabrication and testing of a platform for in situ stress/strain measurement in lithium ion battery electrodes. The platform - consisting of a Microelectromechanical System (MEMS) chip containing an electrochemical cavity and an optical sensing element, a custom electrochemical package and an experimental setup - was successfully developed. Silicon was used as an active electrode material, and a thin-film electrochemical stack was conceived and tested. Finally, multiple experiments showed correlation between the active material volume change inside the battery and a signal change in the optical sensing element. The experimental results, combined with the MEMS implementation of the sensing element provide a promising way to evaluate electrochemical reaction-induced stress monitoring in a simple and compact fashion, while experiments are carried out in situ.