Engineering topics

Abdullah, Muhammad

Publications and source records attributed to Abdullah, Muhammad.

3 records

DOE OSTI2024

Survey and Gap Prioritization of U.S. Electric Vehicle Charge Management Deployments

The goal of this study was to survey and characterize the scope of current technical and programmatic knowledge pertaining to EV charge management technologies and practices in the US and relevant international jurisdictions. This characterization of existing field demonstrations and knowledge derived were used to determine gaps in the SCM demonstration landscape. Addressing these gaps through research and demonstration could increase confidence in the U.S. that load management and EV charge control could achieve overarching societal benefits. A survey of charge management deployments and input from stakeholders was completed to determine the state-of-the-art of smart charge management (SCM) where SCM is defined as controlling the amount of power exchanged between chargers and EVs to meet customers' charging needs while also responding to external power demand or pricing signals to provide load management, resilience, or other benefits to the customer and electric grid. The survey was the basis of the gap analysis in this report and determines which areas are well understood, with high confidence, and which areas need further investigation. Existing examples of EV charge management are characterized here to determine aspects that are ready for widespread deployment and have been demonstrated in the field. These include demonstration studies, pilots, programs, and EV-specific tariffs. In all, 110 examples of charge management were characterized. The data sources were public literature and utility filings as well as targeted interviews. In addition, 43 interviews with stakeholders were conducted with a consistent set of questions used in each interview. This study prioritized gaps in demonstrated SCM capabilities based on 1) Urgency of the particular use-case to offset traditional grid assets, 2) Impact, extensibility, and scaling of results across the entire spectrum of 3000+ utility service territories including projected technical and market potential for a given grid service, and 3) Value of federal funding in addressing the gap, including potential to leverage and/or add scope to existing field demonstrations funded by other non-federal funding mechanisms.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Utilizing data-based modeling with low life cycle GHG emissions algae biofuels for engine optimization

Aquatic microalgae are a highly promising feedstock for the production of biocrude and tailored biofuels, with distinct advantages over traditional terrestrial crops, such as reduced land use and avoidance of food production competition. However, unlocking their full potential requires the development of biofuels with low life cycle greenhouse emissions biofuels, such as algae biofuels, which can significantly reduce the environmental impact of the transportation systems without requiring a complete overhaul of existing engine technology. In this study, we employ cutting-edge data-based AI modeling techniques to optimize the performance of heavy-duty engines, with a focus on transitioning towards biofuels with low life cycle greenhouse emissions biofuels. Our methodology offers significant advantages over traditional sweep testing, enabling efficient and accurate optimization of engine performance with minimal time and resources consumption. Our findings demonstrate the potential of utilizing this approach, with up to 55% NOx emissions reductions and up to 2% reduction in fuel consumption compared to the baseline optimized point. Moving forward, we plan to utilize a 30% blend of algae biofuels with diesel fuel, with the ultimate goal of achieving up to 60% lifecycle GHG emissions. Lastly, we plan to compare the results with 100% renewable biodiesel to add an additional dimension of investigating the impact of fuel chemistry on engine optimization. Overall, this study underscores the vital importance of biofuels for reducing the carbon footprint of the transportation sector and supporting a sustainable future. By harnessing the power of data-based AI modeling with low life cycle greenhouse emissions biofuels, we can accelerate the adoption of more environmentally friendly transportation systems and reduce their impact on the planet. Our findings contribute to this transition and offer insights for developing efficient and effective strategies for addressing global climate change.

09 BIOMASS FUELS↗

DOE OSTI2021

Polymer-ceramic composite electrolytes for all-solid-state lithium batteries: Ionic conductivity and chemical interaction enhanced by oxygen vacancy in ceramic nanofibers

Perovskite Li 3x La 2/3-x TiO3 (LLTO) nanofibers have been heat-treated in the hydrogen-containing atmosphere and then incorporated with the poly(vinylidene fluoride)-co-hexafluoropropylene (PVDF-HFP) polymer to form a composite electrolyte. Hydrogen treatment has created oxygen vacancies in the LLTO nanofibers, which has reduced the activation energy of Li ion transport along intra-grains and inter-grains, leading to improvement in the ion conductivity of LLTO nanofibers. Hydrogen treatment of the LLTO nanofibers has also enhanced the chemical interaction between the LLTO nanofibers and the polymer matrix in the composite electrolyte, and favored the Li ion transport at the nanofiber/polymer interface, improving the ion conductivity of the composite electrolyte to 3.4×10- 4 S/cm at room temperature. As a result, the Li|composite-electrolyte|Li half-cell exhibits good stability during lithium plating/stripping cycling at room temperature, showing an overpotential of ~91 mV at a constant current density of 0.5 mA/cm 2 . Finally, the full-cell battery with the composite electrolyte, lithium metal anode and lithium iron phosphate cathode shows excellent rate capacity and cycling performance.

25 ENERGY STORAGE↗