Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

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%.

Energy Cooperation in Energy Harvesting Communication Systems

In energy harvesting communications, users transmit messages using energy harvested from nature. In such systems, transmission policies of the users need to be carefully designed according to the energy arrival profiles. When the energy management policies are optimized, the resulting performance of the system depends only on the energy arrival profiles. In this dissertation, we introduce and analyze the notion of energy cooperation in energy harvesting communications where users can share a portion of their harvested energy with the other users via wireless energy transfer. This energy cooperation enables us to control and optimize the energy arrivals at users to the extent possible. In the classical setting of cooperation, users help each other in the transmission of their data by exploiting the broadcast nature of wireless communications and the resulting overheard information. In contrast to the usual notion of cooperation, which is at the signal level, energy cooperation we introduce here is at the battery energy level. In a multi-user setting, energy may be abundant in one user in which case the loss incurred by transferring it to another user may be less than the gain it yields for the other user. It is this cooperation that we explore in this dissertation for several multi-user scenarios, where energy can be transferred from one user to another through a separate wireless energy transfer unit. We first consider the offline optimal energy management problem for several basic multi-user network structures with energy harvesting transmitters and one-way wireless energy transfer. In energy harvesting transmitters, energy arrivals in time impose energy causality constraints on the transmission policies of the users. In the presence of wireless energy transfer, energy causality constraints take a new form: energy can flow in time from the past to the future for each user, and from one user to the other at each time. This requires a careful joint management of energy flow in two separate dimensions, and different management policies are required depending on how users share the common wireless medium and interact over it. In this context, we analyze several basic multi-user energy harvesting network structures with wireless energy transfer. To capture the main trade-offs and insights that arise due to wireless energy transfer, we focus our attention on simple two- and three-user communication systems, such as the relay channel, multiple access channel and the two-way channel. Next, we focus on the delay minimization problem for networks. We consider a general network topology of energy harvesting and energy cooperating nodes. Each node harvests energy from nature and all nodes may share a portion of their harvested energies with neighboring nodes through energy cooperation. We consider the joint data routing and capacity assignment problem for this setting under fixed data and energy routing topologies. We determine the joint routing of energy and data in a general multi-user scenario with data and energy transfer. Next, we consider the cooperative energy harvesting diamond channel, where the source and two relays harvest energy from nature and the physical layer is modeled as a concatenation of a broadcast and a multiple access channel. Since the broadcast channel is degraded, one of the relays has the message of the other relay. Therefore, the multiple access channel is an extended multiple access channel with common data. We determine the optimum power and rate allocation policies of the users in order to maximize the end-to-end throughput of this system. Finally, we consider the two-user cooperative multiple access channel with energy harvesting users. The users cooperate at the physical layer (data cooperation) by establishing common messages through overheard signals and then cooperatively sending them. For this channel model, we investigate the effect of intermittent data arrivals to the users. We find the optimal offline transmit power and rate allocation policy that maximize the departure region. When the users can further cooperate at the battery level (energy cooperation), we find the jointly optimal offline transmit power and rate allocation policy together with the energy transfer policy that maximize the departure region.

Self-Assembled InAs/GaAs Quantum Dot Solar Cells

Our work focuses on experimental and theoretical studies aimed at establishing a fundamental understanding of the principal electrical and optical processes governing the operation of quantum dot solar cells (QDSC) and their feasibility for the realization of intermediate band solar cell (IBSC). Uniform performance QD solar cells with high conversion efficiency have been fabricated using carefully calibrated process recipes as the basis of all reliable experimental characterization. The origin for the enhancement of the short circuit current density (Jsc) in QD solar cells was carefully investigated. External quantum efficiency (EQE) measurements were performed as a measure of the below bandgap distribution of transition states. In this work, we found that the incorporation of self-assembled quantum dots (QDs) interrupts the lattice periodicity and introduce a greatly broadened tailing density of states extending from the bandedge towards mid-gap. A below-bandgap density of states (DOS) model with an extended Urbach tail has been developed. In particular, the below-bandgap photocurrent generation has been attributed to transitions via confined energy states and background continuum tailing states. Photoluminescence measurement is used to measure the energy level of the lowest available state and the coupling effect between QD states and background tailing states because it results from a non-equilibrium process. A basic I-V measurement reveals a degradation of the open circuit voltage (Voc) of QD solar cells, which is related to a one sub-bandgap photon absorption process followed by a direct collection of the generated carriers by the external circuit. We have proposed a modified Shockley-Queisser (SQ) model that predicts the degradation of Voc compared with a reference bulk device. Whenever an energy state within the forbidden gap can facilitate additional absorption, it can facilitate recombination as well. If the recombination is non-radiative, it is detrimental to solar cell performance. We have also investigated the QD trapping effects as deep level energy states. Without an efficient carrier extraction pathway, the QDs can indeed function as mobile carriers traps. Since hole energy levels are mostly connected with hole collection under room temperature, the trapping effect is more severe for electrons. We have tried to electron-dope the QDs to exert a repulsive Coulomb force to help improve the carrier collection efficiency. We have experimentally observed a 30% improvement of Jsc for 4e/dot devices compared with 0e/dot devices. Electron-doping helps with better carrier collection efficiency, however, we have also measured a smaller transition probability from valance band to QD states as a direct manifestation of the Pauli Exclusion Principle. The non-linear performance is of particular interest. With the availability of laser with on-resonance and off-resonance excitation energy, we have explored the photocurrent enhancement by a sequential two-photon absorption (2PA) process via the intermediate states. For the first time, we are able to distinguish the nonlinearity effect by 1PA and 2PA process. The observed 2PA current under off-resonant and on-resonant excitation comes from a two-step transition via the tailing states instead of the QD states. However, given the existence of an extended Urbach tail and the small number of photons available for the intermediate states to conduction band transition, the experimental results suggest that with the current material system, the intensity requirement for an observable enhancement of photocurrent via a 2PA process is much higher than what is available from concentrated sun light. In order to realize the IBSC model, a matching transition strength needs to be achieved between valance band to QD states and QD states to conduction band. However, we have experimentally shown that only a negligible amount of signal can be observed at cryogenic temperature via the transition from QD states to conduction band under a broadband IR source excitation. Based on the understanding we have achieved, we found that the existence of the extended tailing density of states together with the large mismatch of the transition strength from VB to QD and from QD to CB, has systematically put into question the feasibility of the IBSC model with QDs.

Predictors of Patient Activation Among Underserved Patients in a Nurse-managed Health Center: A Pilot Study

The concept of patient activation has gained traction as the term referring to patients who understand their role in the care process and have “the knowledge, skills and confidence” necessary to manage their illness over time (Hibbard & Mahoney, 2010). Improving health outcomes for vulnerable and underserved populations who bear a disproportionate burden of health disparities presents unique challenges for nurse practitioners who provide primary care in nurse-managed health centers. Evidence that activation improves patient self-management is prompting the search for theory-based self-management support interventions to activate patients for self-management, improve health outcomes, and sustain long-term gains. Yet, no previous studies investigated the relationship between Self-determination Theory (SDT; Deci & Ryan, 2000) and activation. The major purpose of this study, guided by the Triple Aim (Berwick, Nolan, & Whittington, 2008) and nested in the Chronic Care Model (Wagner et al., 2001), was to examine the degree to which two constructs– Autonomy Support and Autonomous Motivation– independently predicted Patient Activation, controlling for covariates. For this study, 130 nurse-managed health center patients completed an on-line 38-item survey onsite. The two independent measures were the 6-item Modified Health Care Climate Questionnaire (mHCCQ; Williams, McGregor, King, Nelson, & Glasgow, 2005; Cronbach’s alpha =0.89) and the 8-item adapted Treatment Self-Regulation Questionnaire (TSRQ; Williams, Freedman, & Deci, 1998; Cronbach’s alpha = 0.80). The Patient Activation Measure (PAM-13; Hibbard, Mahoney, Stock, & Tusler, 2005; Cronbach’s alpha = 0.89) was the dependent measure. Autonomy Support was the only significant predictor, explaining 19.1% of the variance in patient activation. Five of six autonomy support survey items regressed on activation were significant, illustrating autonomy supportive communication styles contributing to activation. These results suggest theory-based patient, provider, and system level interventions to enhance self-management in primary care and educational and professional development curricula. Future investigations should examine additional sources of autonomy support and different measurements of autonomous motivation to improve the predictive power of the model. Longitudinal analyses should be conducted to further understand the relationship between autonomy support and autonomous motivation with patient activation, based on the premise that patient activation will sustain behavior change.

Tying it Together: Education-Focused Community Change Initiatives

Policymakers make many demands of our schools to produce academic success. At the same time, community organizations, government agencies, faith-based institutions, and other groups often are providing support to students and their families, especially those from high-poverty backgrounds, that are meant to impact education but are often insufficient, uncoordinated, or redundant. In many cases, these institutions lack access to schools and school leaders. What’s missing from the dominant education reform discourse is a coordinated education-focused approach that mobilizes community assets to effectively improve academic and developmental outcomes for students. This study explores how education-focused comprehensive community change initiatives (CCIs) that utilize a partnership approach are organized and sustained. In this study, I examine three research questions: 1. Why and how do school system-level community change initiative (CCI) partnerships form? 2. What are the organizational, financial, and political structures that support sustainable CCIs? What, in particular, are their connections to the school systems they seek to impact? 3. What are the leadership functions and structures found within CCIs? How are leadership functions distributed across schools and agencies within communities? To answer these questions, I used a cross-case study approach that employed a secondary data analysis of data that were collected as part of a larger research study sponsored by a national organization. The original study design included site visits and extended interviews with educators, community leaders and practitioners about community school initiatives, one type of CCI. This study demonstrates that characteristics of sustained education-focused CCIs include leaders that are critical to starting the CCIs and are willing to collaborate across institutions, a focus on community problems, building on previous efforts, strategies to improve service delivery, a focus on education and schools in particular, organizational arrangements that create shared leadership and ownership for the CCI, an intermediary to support the initial vision and collaborative leadership groups, diversified funding approaches, and political support. These findings add to the literature about the growing number of education-focused CCIs. The study’s primary recommendation—that institutions need to work across boundaries in order to sustain CCIs organizationally, financially, and politically—can help policymakers as they develop new collaborative approaches to achieving educational goals.