Refine Your Search

Search Results

Viewing 1 to 4 of 4
Technical Paper

Platform Engineering Applied to Plug-In Hybrid Electric Vehicles

2007-04-16
2007-01-0292
Plug-in hybrid electric vehicle (PHEV) technology will provide substantial reduction in petroleum consumption as demonstrated in previous studies. Platform engineering steps including, reduced mass, improved engine efficiency, relaxed performance, improved aerodynamics and rolling resistance can impact both vehicle efficiency and design. Simulations have been completed to quantify the relative impacts of platform engineering on conventional, hybrid, and PHEV powertrain design, cost, and consumption. The application of platform engineering to PHEVs reduced energy storage system requirements by more than 12%, offering potential for more widespread use of PHEV technology in an energy battery supply-limited market. Results also suggest that platform engineering may be a more cost-effective way to reduce petroleum consumption than increasing the energy storage capacity of a PHEV.
Journal Article

Exploring the Relationship Between Octane Sensitivity and Heat-of-Vaporization

2016-04-05
2016-01-0836
The latent heat-of-vaporization (HoV) of blends of biofuel and hydrocarbon components into gasolines has recently experienced expanded interest because of the potential for increased HoV to increase fuel knock resistance in direct-injection (DI) engines. Several studies have been conducted, with some studies identifying an additional anti-knock benefit from HoV and others failing to arrive at the same conclusion. Consideration of these studies holistically shows that they can be grouped according to the level of fuel octane sensitivity variation within their fuel matrices. When comparing fuels of different octane sensitivity significant additional anti-knock benefits associated with HoV are sometimes observed. Studies that fix the octane sensitivity find that HoV does not produce additional anti-knock benefit. New studies were performed at ORNL and NREL to further investigate the relationship between HoV and octane sensitivity.
Technical Paper

Effects of Heat of Vaporization and Octane Sensitivity on Knock-Limited Spark Ignition Engine Performance

2018-04-03
2018-01-0218
Knock-limited loads for a set of surrogate gasolines all having nominal 100 research octane number (RON), approximately 11 octane sensitivity (S), and a heat of vaporization (HOV) range of 390 to 595 kJ/kg at 25°C were investigated. A single-cylinder spark-ignition engine derived from a General Motors Ecotec direct injection (DI) engine was used to perform load sweeps at a fixed intake air temperature (IAT) of 50 °C, as well as knock-limited load measurements across a range of IATs up to 90 °C. Both DI and pre-vaporized fuel (supplied by a fuel injector mounted far upstream of the intake valves and heated intake runner walls) experiments were performed to separate the chemical and thermal effects of the fuels’ knock resistance. The DI load sweeps at 50°C intake air temperature showed no effect of HOV on the knock-limited performance. The data suggest that HOV acts as a thermal contributor to S under the conditions studied.
Technical Paper

Bayesian Parameter Estimation for Heavy-Duty Vehicles

2017-03-28
2017-01-0528
Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses a Monte Carlo method to generate parameter sets that are fed to a variant of the road load equation. The modeled road load is then compared to the measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the current state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters.
X