Browse Topic: Fuel economy

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ABSTRACT This paper presents a quantitative analysis and comparison of fuel economy and performance of a series hybrid electric HMMWV (High Mobility Multi-purpose Wheeled Vehicle) military vehicle with a conventional HMMWV of equivalent size. Hybrid vehicle powertrains show improved fuel economy gains due to optimized engine operation and regenerative braking. In this paper, a methodology is presented by which the fuel economy gains due to optimized engine are isolated from the fuel economy gains due to regenerative braking. Validated vehicle models as well as data collected on test tracks are used in the quantitative analysis. The regenerative braking of the hybrid HMMWV is analyzed in terms of efficiency from the kinetic energy at the wheels to the portion of regenerative power which is retrievable by the battery. The engine operation of both the series hybrid and conventional HMMWV are analyzed using a 2-D bin analysis methodology. Finally, the vehicle model is used to make
Nedungadi, AshokMasrur, AbulKhalil, Gus
ABSTRACT The US Army is seeking improvements in the fuel efficiency of their military vehicles.. They have initiated a number of R&D projects aimed at advancing the state-of-the-art of powertrain efficiency including demonstration in a laboratory environment. This effort will set a benchmark for the vehicle integrators, allowing them to improve future vehicle offerings. The SAIC, AVL, Badenoch, QinetiQ and Ker-Train Research team offered powertrain solutions from 7 Tons to 40 Tons that achieved the goal of 44% thermal efficiency and the stringent flexible fuel and emissions requirements. In each of these offerings the team was able to identify modifications to existing engines that allowed dramatic improvements in the thermal efficiency. These efficiency improvements were achieved through a combination of techniques, combustion cycle adjustments using in-cylinder pressure monitoring and precise control of fuel injector timing, and turbo-compounding. For the R&D project, the fuel
McDowell, JimHunter, Gary L.Hennessy, Chris
Abstract The variability in fuel, particularly for fuel blends containing sustainable aviation fuels (SAFs), emphasizes the importance of understanding fuel properties for optimizing engine performance. This paper introduces spectroscopic fuel sensors capable of real-time estimation of jet fuel properties, mainly derived cetane number (DCN). While initially developed for unmanned aircraft systems (UAS), the paper explores their potential in ground vehicle applications: enhancing engine performance through sensing for feed-forward control and fuel property monitoring at fuel depots. The fuel sensing technologies are based on spectroscopic techniques coupled with machine learning (ML) approaches. The combination of these techniques demonstrates a promising solution for a wide spectrum of fuel applications.
Patel, Dev B.Sutar, AshishAbraham, AbhinavAmbre, DhananjayBrezinsky, KennethLynch, Patrick T.Okada, HarunaStafford, Jacob M.Miganakallu, NiranjanSanders, ScottRothamer, DavidMayhew, EricKim, Kenneth S.
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