As a high-efficiency and zero-emission energy conversion device that directly converts the chemical energy of fuels and oxidants into electricity, proton exchange membrane fuel cell (PEMFC) is one of the most important end-uses of hydrogen. Improving power density is the most crucial trend for the development of PEMFC. As a promising alternative to traditional channel-rib flow fields, metal foam flow field has gained increasing attention. Its unique open-cellular structure ensures high porosity and tortuosity, which facilitates uniform distribution of reactants and enhances mass transfer while possessing advantages like superior electrical and thermal conductivities, light-weight, and uniform stress distribution. Hence, from the perspectives of functions and requirements, a PEMFC employing metal foam flow field holds the potential feasibility of removing the gas diffusion layer (GDL) away from the membrane electrode assembly (MEA).In this dissertation, an experimental investigation of the effects of different flow field configurations on PEMFC performance is first conducted. The PEMFCs utilizing parallel flow field, serpentine flow field, and Ni foam flow field are compared. The effects of operating conditions on the performance of PEMFC using Ni foam flow field are studied, including operating temperature, back pressure, intake flow rate, and relative humidity. The effects of Ni foam physical parameters on the performance of PEMFC using Ni foam flow field are then investigated, including compression ratio, pore size, hydrophobicity, and surface treatments. A comprehensive numerical simulation on PEMFC performance, including oxygen concentration, membrane water content, and overpotentials, using a 3D non-isothermal multi-phase model is conducted for cell structure evaluation, including straight channel, fine channel, wave-like channel, partially narrow channel, channel inserting baffle, modified pin-type structure, 3D fine mesh, and metal foam. The influence of GDL thickness on PEMFC performance is then experimentally studied to verify the simulation results. The effects of the micro-porous layer (MPL) are examined. Wet and dry fabrication methods of traditional particle-stacking MPL are investigated. A promising alternative to traditional MPL, namely carbon nanofiber film (CNFF), is fabricated and ex-situ characterized, showing great potential. A GDL-less PEMFC utilizing CNFF at the cathode as the alternative to traditional MPL is assembled and experimental investigated. A peak power density of 1.835 W cm-2 is achieved, representing a successful elimination of GDL away from the electrode. GDL-less PEMFC shows a spectacular capability of water management and remarkably low reactant transport resistance. A Dual GDL-less PEMFC with CNFF on both sides is assembled and tested. The Dual GDL-less PEMFC shows a 90% reduction in the volume of MEA and simplified morphology of electrodes. The peak power density reaches 1.774 W cm-2. Assuming GDL-less design is employed on the Toyota 2nd-gen Mirai PEMFC stack with identical cooling configuration, dimension of end plates, and operating conditions, the peak stack volumetric power density of GDL-less with and without endplates are 7.72 kW L-1 and 9.79 kW L-1, respectively, which are 76% and 81% greater than those of the 2nd-gen Mirai PEMFC stack, respectively, surpassing the 6.0 kW L-1 short-term target and approaching the 9.0 kW L-1 target set for the year 2040.

As lithium-ion battery (LIB) cells degrade over time and usage, it is crucial to understand the remainingcapacity, also known as State of Health (SoH), and inconsistencies between cells in a pack, also known as cell-to-cell variation (CtCV), to appropriately operate and maintain LIB packs. This study outlines efforts to model pack SoH and SoH CtCV of nickel-cobalt-aluminum (NCA) and lithium-iron-phosphate (LFP) battery packs consisting of four cells in series using pack-level voltage data. Using a small training data set and an under 3-minute testing procedure, partial least squares regression (PLS) models were built and achieved a mean absolute error of 0.38% and 1.43% pack SoH for NCA and LFP packs, respectively. PLS models were also built that correctly categorized packs having low, medium, and high ranked SoH CtCV 72.5% and 65% of the time for NCA and LFP packs, respectively. This study further investigates the relationships between pack SoH, SoH CtCV, and the voltage response of NCA and LFP packs. The slope of the discharge voltage response of the NCA packs was shown to have a strong correlation with pack dynamics and pack SoH, and the lowest SoH cell within NCA packs was shown to dominate the dynamic response of the entire pack.

Lithium-ion batteries are widely used in the Electric Vehicle (EV) and the Energy Storage Systems (ESS) applications. In such systems, the batteries are connected in combinations of series and parallel connections in such a way that the overall current and voltage of the pack meets the performance requirements of the application. However, due to the inherent degradation mechanisms and inconsistencies in operating conditions for cells within a series connected battery pack, there is a differential in the State-of-Health (SoH) of cells which subsequently affects the utilizable energy of the overall pack. Thus, it is imperative to have models which rely on short duration tests to rapidly estimate the SoH of the battery packs. In this project, two of the most widely used Li ion battery types – Nickel-Manganese-Cobalt (NMC) and Lithium-Iron-Phosphate (LFP) chemistry cells are evaluated.An empirical model is proposed which relies on two quick 10 second pulses to estimate the SoH of a battery pack consisting of 4 series connected cells. The empirical models are trained with a variety of series connected battery packs constructed using combinations of differently aged cells. The model yields excellent results for the NMC chemistry battery packs with Root-Mean-Squared Error (RMSE) of 2.05 Total SoH % points and Mean Absolute Error (MAE) of 1.60 Total SoH % points. However, the LFP chemistry of cells only achieve an RMSE of 6.09 Total SoH % points and MAE of 4.81 Total SoH % points. The hypothesis is that this performance differential exists due to the much steeper Open Circuit Voltage – State of Charge (OCV-SoC) curve for NMC cells over LFP cells. Further tests expanding the range of SoH of packs is recommended along with additional models to also estimate information about the distribution of SoH of the constituent cells are suggested as part of future work.

The goal of this research was to determine how temperature gradients in series-connected lithium-ion battery packs affect the performance and cycle-life degradation of each of the cells in the battery pack as well as the pack as a whole. This degradation was compared to cells cycled individually and cells subjected only to calendar aging. This allowed attribution of degradation rates to specific usage conditions. Cell performance and capacity degradation was measured by utilizing standard capacity and resistance checks, neutron radiography, and other battery performance metrics. It was found that cells subjected to non-uniform temperatures within the pack degraded faster, and battery pack capacity was reduced relative to an ideal battery pack. It was also determined that the hottest cell in a series connected pack with a temperature gradient will degrade faster than an equivalent cell cycled individually at the same temperature.

Despite the presence of large battery packs in modern electric vehicles, little work has been done to verify pack performance and degradation models, especially when paired with non-uniform pack temperature. This was due to the interwoven degradation stressors and mechanisms at play that need to be separately investigated to gain a full understanding of the combined effect of series packs and temperature gradients. In this work, the effects of calendar aging, cycling aging, temperature, and temperature gradients were all measured and compared. The causes of increased degradation measured on the packs with an applied temperature gradient were determined to be the superimposed effects of varying depths of discharge and non-uniform current distributions within the cells. It was also found that cell degradation did not scale linearly with applied temperature gradient. Rather, the relative rate of aging was found to follow a second order polynomial in temperature and in temperature difference. This meant that depending on the pack average temperature, the hottest or the coldest cell can degrade the most. This behavior was quantified to allow for use in optimizing the design of battery thermal management systems, and an example analysis of thermal management performance was performed on a battery pack from a Nissan Leaf.

Battery energy storage systems (BESS) play a role in addressing the challenges of the current electric grid. BESS will be instrumental for meeting energy storage requirements with the increasing adoption of intermittent energy sources. California is a global leader in the adoption of intermittent renewables on their grid, and has had to devise solutions for meeting the energy storage demands of these energy sources. California has the largest proportion of solar photovoltaic (PV) on the grid of any region of the world. It thus is the first to face the challenges of meeting energy storage needs. This paper analyzes one of California’s steps in meeting this challenge by increasing the adoption of BESS through its Self-Generating Incentive Program (SGIP). The paper studies SGIP beneficiaries’ perceptions, satisfaction, and performance of some of the BESS currently installed for commercial and industrial (C&I) applications. This paper also defines BESS's actual and potential benefits for C&I customers. Results show that most SGIP tickets submitted for C&I installations in the last five years are yet to go live and currently installed BESS aligns with SGIP's goal of reducing electricity bills. In addition, most customers are satisfied with the installation process and the promptness of getting their BESS to serve them. SGIP has been successful for C&I customers because it has reduced the energy bill of the beneficiaries.