Electrical & Computer Engineering Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2765
Browse
2 results
Search Results
Item GALLIUM NITRIDE BASED ONBOARD CHARGER FOR ELECTRIC VEHICLES(2019) Zhang, Zeyu; Khaligh, Alireza; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Next generation of electric vehicles will be equipped with high power density and high efficiency onboard charging systems with bi-directional power flow. These benefits can be achieved by utilizing the emerging Wide Bandgap devices, planar magnetic solutions, innovative circuit topologies, and advanced control methods to enable MHz switching frequencies without sacrificing efficiency. However, the advantage of higher switching speed is gained at the expense of higher switching losses in both the semiconductors and the magnetics. Conventional circuit topologies, operation modes and control algorithms would no longer be effective in such conditions. Furthermore, the practical implementation of the system has shown more stringent requirements on the controller speed, layout parasitic and the thermal management. In this Ph.D. dissertation work, aforementioned challenges have been addressed, and the proposed innovations have been validated through design and development of a new bi-directional onboard charger using Gallium Nitride devices. The first part of this work has been focused on a thorough characterization of the front-end AC-DC power factor correction and rectification stage of an onboard charger, utilizing advanced planar magnetics and newly proposed soft-switching control methods. The second part of this work is focused on developing a CLLC DC-DC converter, to interface the AC-DC stage and the high-voltage traction battery. Extended Harmonic Approximation method has been developed and a novel “f-φ” control scheme is proposed to enhance the efficiency at high switching speed. This system allows insights into the practical implementation and evaluation of utilizing Wide Bandgap semiconductors to achieve high power density and efficiency for the transportation industry.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%.