Engineering topics

Vijayagopal, Ram

Publications and source records attributed to Vijayagopal, Ram.

5 records

DOE OSTI2024

Annual Technology Baseline (ATB): The 2024 Transportation Update

The Transportation Annual Technology Baseline (ATB) provides detailed cost and performance data, estimates, and assumptions for vehicle and fuel technologies in the United States. It includes current and projected estimates for vehicle technologies as well as fuels, and it details the assumptions used to calculate those costs, such as gas and electricity prices, discount rates, and vehicle miles traveled. The 2024 update added more biofuels pathways to align with pathways used in the Biomass Scenario Model.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗

DOE OSTI2024

A real-time energy and cost efficient vehicle route assignment neural recommender system

Here, this paper presents a neural network recommender system algorithm for assigning vehicles to routes based on energy and cost criteria. In this work, we applied this new approach to efficiently identify the most cost-effective medium and heavy duty truck (MDHDT) powertrain technology, from a total cost of ownership (TCO) perspective, for given trips. We employ a machine learning based approach to efficiently estimate the energy consumption of various candidate vehicles over given routes, defined as sequences of links (road segments), with little information known about internal dynamics, i.e. using high level macroscopic route information. A complete recommendation logic is then developed to allow for real-time optimum assignment for each route, subject to the operational constraints of the fleet. We show how this framework can be used to (1) efficiently provide a single trip recommendation with a top-k vehicles star ranking system, and (2) engage in more general assignment problems where n vehicles need to be deployed over m (m ≤ n) trips. This new assignment system has been deployed and integrated into the POLARIS. Transportation System Simulation Tool for use in research conducted by the Department of Energy's Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium (SMART, 2024).

Energy consumption↗

DOE OSTI2024

Potential Adoption and Benefits of Co-Optimized Multimode Engines and Fuels for U.S. Light-Duty Vehicles

Exploring a diverse portfolio of technologies for decarbonization is crucial to understanding the potential impacts of different technological solutions and their associated environmental implications. Using high-octane, high-sensitivity biofuel blends in co-optimized multimode engines can increase engine efficiency and reduce vehicle emissions. Here, the multimode engine research focuses on the benefits of light-duty vehicle engines, which can operate in multiple modes depending on the vehicle's load. Low-temperature combustion can improve efficiency and reduce emissions (such as those from oxides of nitrogen and particulate matter) during low-load operation, while spark ignition performance is maintained in high-load operation. These advanced engines can be optimized to run on blends of biobased fuels. This analysis models scenarios for potential market adoption of co-optimized multimode vehicles fueled by three different bioblendstocks: ethanol, isopropanol, and isobutanol. An integrated modeling approach is used to forecast the energy and environmental impacts of the deployment of co-optimized multimode vehicles and fuels in the light-duty sector over the 2020-to-2050 time horizon. The multidisciplinary approach combines vehicle sales modeling, system dynamics modeling of the biorefining industry, and life cycle assessment to estimate the emissions and energy benefits. The models consider market forces such as consumer preferences for vehicle attributes, biofuel supply and demand dynamics subject to biorefinery capacity build-out and bioresource constraints, and forecasted changes to the U.S. bulk energy system over time. Market adoption of co-optimized vehicles is evaluated across a wide parameter space for incremental vehicle cost and engine efficiency improvement. This analysis reveals that the deployment of co-optimized multimode fuels and vehicles results in up to a 5% reduction in annual sector-wide life cycle greenhouse gas (GHG) emissions by 2050, relative to a business-as-usual scenario, but is also indicates environmental trade-offs, such as higher life cycle water-use. Emission benefits could potentially increase beyond 2050, as the new technologies penetrate the market and gain a foothold. Results also show that, under certain circumstances, vehicles with engines co-optimized for use with high-octane, high-sensitivity biofuel blends can be cost-competitive with conventional gasoline, while reducing GHG emissions. Our modeling results indicate that co-optimized multimode fuels and engines can be strategically leveraged in tandem with electrification to decarbonize the light-duty sector. Co-optimized vehicles could play a role in the early years of the time horizon, while electric vehicles (EVs) could become more competitive in the later years, highlighting the complementary benefits of these technologies for GHG reductions.

Oke, Doris↗

DOE OSTI2024

Practical low-temperature gasoline combustion for very high efficiency off-road, medium- and heavy-duty engines

Low-temperature gasoline combustion (LTGC) with additive-mixing fuel injection (AMFI) is a new combustion strategy that has been demonstrated to deliver 9%–25% better brake thermal efficiency than similar-sized market-leading diesel engines over the operating map. Moreover, the LTGC-AMFI engine shows near-zero smoke, and NOx emissions are 4–100 times lower than those of a diesel, sufficiently low that no aftertreatment, or only passive NOx aftertreatment, would be sufficient (diesel exhaust fluid is not required). LTGC-AMFI combustion is based on kinetically controlled compression ignition of a dilute charge with a variable amount of low-to-moderate fuel stratification. Fast combustion control is provided by adding minute amounts of an ignition-enhancing additive into the fuel each engine cycle to control its reactivity. This strategy was used to operate a medium-duty (MD) LTGC-AMFI engine at loads from idle to 16.3 bar BMEP and speeds from 600 to 2400 rpm with regular E10 gasoline, which covers nearly the entire operating map of a typical MD engine. Turbine-out temperatures were sufficient for an oxidation catalyst to control hydrocarbon and CO emissions. Autonomie simulations over the GEM ARB Transient and the GEM 55 mph Cruise driving cycles for class-6 trucks using this technology showed fuel economies of 8.1 and 11.4 mpg-gasoline-equivalent, respectively, corresponding to 18.6% and 13.4% improvements over a similar-size diesel engine. Engine-out NOx emissions were 0.024 and 0.01 g/bhp-h, respectively, well below current U.S. emission standards. These results show that switching from diesel to LTGC-AMFI engines would greatly reduce greenhouse gas (GHG) emissions for off-road, MD and HD applications, which will continue to rely on combustion engines because electrification is not practical in the foreseeable future. Finally, with their reduced fuel consumption, the lower cost of gasoline compared to diesel fuel, and much lower aftertreatment costs, LTGC-AMFI engines also offer a significantly lower total cost of ownership.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

A methodology to develop multi-physics dynamic fuel cell system models validated with vehicle realistic drive cycle data

Fuel cell (FC) technology has been identified as a technically attractive solution to decarbonize the transportation sector, especially for heavy-duty vehicles. In this context, the industry and the scientific community are in need of advanced fuel cell systems (FCS) models that are able to replicate real -world operating conditions. Due to the scarcity of said models in the open literature, this study aimed to develop a comprehensive methodology to calibrate and validate multi -physics dynamic FCS models. Therefore, the key contribution of this paper is the detailed description of the calibration process for each component and the calibration order. The specific focus here was to accurately describe the behavior of the FC stack as well as the cathode, anode, and cooling circuits of the balance of plant. The model was calibrated with the aid of experimental data from a Toyota Mirai FC electric vehicle, which was predominantly retrieved from the vehicle's Controller Area Network (CAN) bus system thereby negating the need for major intrusion into the powertrain system. The validation process was deemed successful with the model being able to truthfully replicate the characteristics of the FC vehicle operated on the World-wide harmonized Light duty Test Cycle (WLTC) 3b and US06 driving cycle. The time -resolved physical parameters such as the cathode pressure, mass flow, or the FC stack temperature were captured with high fidelity, while the overall performance parameters such as the H2 consumption in the stack and the system, and the compressor energy consumption were predicted accurately with a deviation lower than 0.47%, 1.75% and 1.89% with respect to the experimental data, respectively.

Lopez-Juarez, Marcos↗