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Methods and systems for producing fuel compositions with predetermined desirable properties are disclosed. Feedback control can be employed to meter precise amounts of fuel composition components while monitoring fuel composition properties to obtain fuel compositions having specifically defined pro

Methods and systems for producing fuel compositions with predetermined desirable properties are disclosed. Feedback control can be employed to meter precise amounts of fuel composition components while monitoring fuel composition properties to obtain fuel compositions having specifically defined properties.

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What is claimed is: 1. An automated method of making a fuel composition having a maximum Reid Vapor Pressure of 10 psi, comprising: identifying one or more predetermined properties of the fuel composition; charging one or more hydrocarbon feedstock, one or more oxygenate feedstock, and one or more

What is claimed is: 1. An automated method of making a fuel composition having a maximum Reid Vapor Pressure of 10 psi, comprising: identifying one or more predetermined properties of the fuel composition; charging one or more hydrocarbon feedstock, one or more oxygenate feedstock, and one or more additives into a blending tank to make a fuel composition mixture, each of the one or more hydrocarbon feedstock, one or more oxygenate feedstock, and one or more additive feed having a charge rate; determining amounts of each of the one or more hydrocarbon feedstock, the one or more oxygenate feedstock, and the one or more additives charged into the blending tank to make the fuel composition mixture; determining one or more current properties of the fuel composition mixture in the blending tank, the one or more current properties of the fuel composition mixture corresponding to the one or more predetermined properties of the fuel composition; comparing the predetermined properties of the fuel composition with the current properties of the fuel composition mixture; and adjusting the charge rate of at least one of the one or more hydrocarbon feedstocks, one or more oxygenate feedstocks, and one or more additives into the blending tank in response to the amounts of each of the one or more hydrocarbon feedstock the one or more oxygenate feedstock, and the one or more additives charged into the blending tank and comparing the predetermined properties and the current properties to provide the fuel composition having a maximum Reid Vapor Pressure of 10 psi, wherein adjusting the charge rate is performed using a trained neural network, the trained neural network operative to determine adjustments to the charge rate of at least one of the one or more hydrocarbon feedstocks, one or more oxygenate feedstocks, and one or more additives into the blending tank based upon the current properties of the fuel composition mixture. 2. The method of claim 1, wherein the one or more hydrocarbon feedstock comprises at least two of: a straight-run product feedstock, a reformate feedstock, a cracked gasoline feedstock, a high octant feedstock, an isomerate feedstock, a polymerization feedstock, an alkylate feedstock, a hydrotreated feedstock, and an desulfurization feedstock. 3. The method of claim 1, wherein the oxygenate feedstock provides at least one of: methanol, ethanol, methyl tertiary butyl ether, tertiary amyl methyl ether, and ethyl tertiary butyl ether; and the one or more additive feed comprises at least two of: an antioxidant feed, a corrosion inhibitor feed, a metal deactivator feed, a demulsifier feed, an antiknock compound feed, a deposit control additive feed, an anti-icing additive feed, a dye feed, a drag reducer feed, a detergent feed, and an octane enhancer feed. 4. The method of claim 1, wherein the predetermined properties comprise at least two of: Reid Vapor Pressure of about 8 psi or less, a 50% D-86 distillation temperature of about 170° F. or more, a 50% D-86 distillation temperature of about 225° F. or less, an oxygenate content of about 15 volume % or less, an olefin content of about 6 volume % or less, a sulfur content of about 30 ppmw or less, an aromatic hydrocarbon content of about 30 volume % or more, a paraffin content of above about 50 volume %, a Research Octane Number of about 90 or more, an anti-knock value of about 87 or more, a 10% D-86 distillation temperature of about 140° F. or less, and a 90% D-86 distillation temperature of about 330° F. or less. 5. The method of claim 1, wherein comparing the predetermined properties and the current properties generates comparison data; the method further comprising sending the comparison data to a memory, the memory comprising data associated with properties of specific fuel compositions and data associated with changing the properties of the specific fuel compositions by changing amounts of components of the specific fuel compositions. 6. The method of claim 1, wherein the predetermined property of the fuel composition comprises at least one of: a Reid Vapor Pressure of about 7.5 psi or less, a Research Octane Number of about 90 or more, an anti-knock value of about 87 or more, a 10% D-86 distillation temperature of about 140° F. or less, a 90% D-86 distillation temperature of about 330° F. or less and a 50% D-86 distillation temperature of about 215° F. or less. 7. The method of claim 1, wherein the charge rate of the one or more oxygenate feedstocks is increased in response to comparing the predetermined properties and the current properties. 8. An automated method of making a gasoline having a maximum Reid Vapor Pressure of 10 psi, comprising: identifying one or more predetermined properties of the gasoline; charging one or more hydrocarbon feedstock, one or more oxygenate feedstock, and one or more additives into a blending tank to make a gasoline mixture, each of the one or more hydrocarbon feedstock, one or more oxygenate feedstock, and one or more additive feed having a charge rate; determining one or more current properties of the gasoline mixture in the blending tank, the one or more current properties of the gasoline mixture corresponding to the one or more predetermined properties of the gasoline; determining amounts of each of the one or more hydrocarbon feedstock the one or more oxygenate feedstock, and the one or more additives charged into the blending tank to make the gasoline mixture; comparing the predetermined properties of the gasoline with the current properties of the gasoline mixture; and adjusting the charge rate of at least one of the one or more hydrocarbon feedstocks, one or more oxygenate feedstocks, and one or more additives into the blending tank in response to the amounts of each of the one or more hydrocarbon feedstock, the one or more oxygenate feedstock, and the one or more additives charged into the blending tank and comparing the predetermined properties and the current properties to provide the gasoline having a maximum Reid Vapor Pressure of 10 psi, wherein adjusting the charge rate is performed using a trained neural network, the trained neural network operative to determine adjustments to the charge rate of at least one of the one or more hydrocarbon feedstocks, one or more oxygenate feedstocks, and one or more additives into the blending tank based upon the current properties of the fuel composition mixture. 9. The method of claim 1, wherein the predetermined property of the gasoline comprises a sulfur content of about 30 ppmw or less. 10. The method of claim 8, wherein adjusting the charge rate comprises increasing or decreasing the charge rate of at least one of: methanol, ethanol, methyl tertiary butyl ether, tertiary amyl methyl ether, and ethyl tertiary butyl ether. 11. The method of claim 8, wherein the predetermined property of the gasoline comprises an anti-knock value of about 87 or more. 12. The method of claim 8, wherein adjusting the charge rate comprises increasing or decreasing the charge rate of one or more of an antioxidant, a corrosion inhibitor, a metal deactivator, a demulsifier, an antiknock compound, a deposit control additive, and a detergent. 13. The method of claim 8, wherein the predetermined property of the gasoline comprises a sulfur content of about 30 ppmw or less. 14. The method of claim 8, wherein the predetermined properties comprise at least three of: Reid Vapor Pressure of about 8 psi or less, a 50% D-86 distillation temperature of about 170° F. or more, a 50% D-86 distillation temperature of about 225° F. or less, an oxygenate content of about 15 volume % or less, an olefin content of about 6 volume % or less, a sulfur content of about 30 ppmw or less, an aromatic hydrocarbon content of about 30 volume % or more, a paraffin content of above about 50 volume %, a Research Octane Number of about 90 or more, an anti-knock value of about 87 or more, a 10% D-86 distillation temperature of about 140° F. or less, and a 90% D-86 distillation temperature of about 330° F. or less. 15. The method of claim 8, wherein comparing the predetermined properties and the current properties generates comparison data; the method further comprising sending the comparison data to a memory, the memory comprising data associated with properties of specific gasolines and data associated with changing the properties of the specific gasolines by changing amounts of components of the specific gasolines. 16. An automated method of making a reformulated gasoline having a maximum Reid Vapor Pressure of 10 psi, comprising: identifying one or more predetermined properties of the reformulated gasoline; charging one or more hydrocarbon feedstock, an ethanol feedstock, and one or more additives into a blending tank to make a reformulated gasoline mixture, each of the one or more hydrocarbon feedstock, the ethanol feedstock, and one or more additive feed having a charge rate; determining amounts of each of the one or more hydrocarbon feedstock the ethanol feedstock, and the one or more additives charged into the blending tank to make the reformulated gasoline mixture; determining one or more current properties of the reformulated gasoline mixture in the blending tank, the one or more current properties of the reformulated gasoline mixture corresponding to the one or more predetermined properties of the reformulated gasoline; comparing the predetermined properties of the reformulated gasoline with the current properties of the reformulated gasoline mixture; and adjusting the charge rate of at least one of the one or more hydrocarbon feedstocks, the ethanol feedstock, and one or more additives into the blending tank in response to the amounts of each of the one or more hydrocarbon feedstock, the ethanol feedstock, and the one or more additives charged into the blending tank and comparing the predetermined properties and the current properties to provide the reformulated gasoline having a maximum Reid Vapor Pressure of 10 psi, wherein adjusting the charge rate is performed using a trained neural network, the trained neural network operative to determine adjustments to the charge rate of at least one of the one or more hydrocarbon feedstocks, the ethanol feedstock, and one or more additives into the blending tank based upon the current properties of the fuel composition mixture. 17. The method of claim 16, wherein the predetermined properties of the reformulated gasoline comprise a Reid Vapor Pressure of about 8 psi or less and an anti-knock value of about 87 or more. 18. The method of claim 16, wherein the predetermined property of the reformulated gasoline comprises a sulfur content of about 30 ppmw or less. 19. The method of claim 16, wherein the charge rate of the ethanol feedstock is increased in response to comparing the predetermined properties and the current properties. 20. The method of claim 1, wherein the trained neural network is further operative to indicate an extent one or more of the charge rates deviates from an adjustment. 21. The method of claim 8, wherein the trained neural network is further operative to detect adjustment implementation errors. 22. The method of claim 16, wherein the trained neural network is further operative to indicate an extent one or more of the charge rates deviates from an adjustment.