Reformulated diesel fuel and method

• US 7,096,123 B1
• Filed: 05/12/2003
• Issued: 08/22/2006
• Est. Priority Date: 02/06/2003
• Status: Expired due to Fees

• Current Assignee: US Department of Energy (Government of the United States of America)
• Original Assignee: United States Department of Energy
• Inventors: Crawford, Robert W., Hadder, Gerald R., McNutt, Barry D., McAdams, Hiramie T.
• Primary Examiner(s): Hoff, Marc S.
• Assistant Examiner(s): Desta, Elias
• Application Number:
  US10/435,537
• Time in Patent Office: 1,198 Days
• Field of Search: 702 22- 23, 702/104, 702/194, 422/98, 422/82.01, 443/00, 443/24, 446/00, 446/03, 449/03, 706/45
• US Class Current: 702/22
• CPC Class Codes: C10L 1/08 for compression ignition

Abstract

A method for mathematically identifying at least one diesel fuel suitable for combustion in an automotive diesel engine with significantly reduced emissions and producible from known petroleum blendstocks using known refining processes, including the use of cetane additives (ignition improvers) and oxygenated compounds.

Claims

1. A method for mathematically identifying at least one diesel fuel suitable for combustion in an automotive diesel engine and producible from known petroleum blendstocks using known refining processes, including the use of cetane additives (ignition improvers) and oxygenated compounds, comprising the steps of:

a) providing a data set comprising a plurality of measurable fuel properties of at least two diesel fuels suitable for combustion in an automotive diesel engine, each of said measurable fuel properties having a numerical value;

b) selecting a set of at least two fuel property values from said data set;

c) generating from said at least two selected fuel property values a set of at least two eigenvectors using Principal Components Analysis, each of said at least two eigenvectors mathematically representing a naturally-occurring relationship among said selected properties of said diesel fuels and each having an observed weight in each of said diesel fuels in said dataset, said observed weights forming a range of weights for each of said generated eigenvectors;

d) optionally generating at least one vector representing the use of diesel fuel additives, including, but not limited to cetane additives (ignition improvers) and oxygenated compounds, augmenting said set of at least two eigenvectors with said at least one generated vector, and identifying for each of said at least one vector a quantitative range of additive usage consistent with the requirements of ASTM 975-02, said quantitative range of additive usage forming a range of weights for said generated vector;

e) choosing a numerical weight for each of said at least two eigenvectors, as optionally augmented, wherein said chosen weight falls within said range of weights for said generated eigenvectors; and

f) proportionally combining said at least two eigenvectors, as optionally augmented, in accordance with said chosen numerical weights to identify a diesel fuel suitable for combustion in an automotive diesel engine and producible from known petroleum blendstocks using known refining processes, including the use of cetane additives (ignition improvers) and oxygenated compounds.

2. The method of claim 1, further comprising the step of generating a set of at least one diesel fuel suitable for combustion in an automotive diesel engine by repeated application of said means for choosing numerical weights and combining said at least two eigenvectors according to said chosen weights.

3. The method of claim 2, wherein said numerical weights are chosen by a Monte Carlo simulation process.

4. The method of claim 3, further comprising the step of using a predictive model of emissions from diesel engines or vehicles as a function of said diesel fuel properties or said eigenvector weights, said model having been developed using a multivariate statistical technique to identify, from said set of least one diesel fuel suitable for combustion in an automotive diesel engine, a subset of at least one diesel fuel having reduced emissions of at least one pollutant.

5. The method of claim 4, wherein said pollutants are selected from the group consisting of nitrogen oxides, particulate matter, hydrocarbons, and carbon monoxide.

6. The method of claim 5, wherein said multivariate statistical method is selected from the group consisting of Principal Components Regression Plus, Ordinary Least Squares, Partial Least Squares, Ridge Regression, and Mixed Effects Modeling based on Maximum Likelihood Estimation.

7. The method of claim 4, further including the step of using a multivariate statistical technique to identify from said subset of at least one diesel fuel having the characteristic of reduced emissions of at least one pollutant, a further subset of at least one diesel fuel that is bounded by one or more mathematical equations involving one or more measurable properties of said diesel fuel.

8. The method of claim 7, wherein said multivariate statistical method is selected from the group consisting of correlation analysis, discriminant function analysis, and graphical analysis.

9. The method of claim 1, wherein said set of at least two fuel properties is selected from the group consisting of natural cetane, cetane difference, specific gravity, viscosity, sulfur content, total aromatics content, initial boiling point, 10 volume percent boiling point, 50 volume percent boiling point, 90 volume percent boiling point, final boiling point, and oxygen content.