FI20176201A1 - Method for determining the amount of renewable fuel in a fuel blend - Google Patents
Method for determining the amount of renewable fuel in a fuel blend Download PDFInfo
- Publication number
- FI20176201A1 FI20176201A1 FI20176201A FI20176201A FI20176201A1 FI 20176201 A1 FI20176201 A1 FI 20176201A1 FI 20176201 A FI20176201 A FI 20176201A FI 20176201 A FI20176201 A FI 20176201A FI 20176201 A1 FI20176201 A1 FI 20176201A1
- Authority
- FI
- Finland
- Prior art keywords
- fuel
- amount
- renewable
- blend
- fuel component
- Prior art date
Links
- 239000000446 fuel Substances 0.000 title claims abstract description 468
- 239000000203 mixture Substances 0.000 title claims abstract description 259
- 238000000034 method Methods 0.000 title claims abstract description 67
- 239000002803 fossil fuel Substances 0.000 claims abstract description 44
- 238000004458 analytical method Methods 0.000 claims abstract description 26
- 239000003925 fat Substances 0.000 claims description 73
- 238000002329 infrared spectrum Methods 0.000 claims description 51
- 238000001228 spectrum Methods 0.000 claims description 45
- 239000003921 oil Substances 0.000 claims description 40
- 238000011088 calibration curve Methods 0.000 claims description 39
- 150000002430 hydrocarbons Chemical class 0.000 claims description 31
- 241000251468 Actinopterygii Species 0.000 claims description 26
- 241001465754 Metazoa Species 0.000 claims description 24
- 229930195733 hydrocarbon Natural products 0.000 claims description 22
- 239000003054 catalyst Substances 0.000 claims description 18
- 239000010773 plant oil Substances 0.000 claims description 18
- 229940013317 fish oils Drugs 0.000 claims description 16
- 238000002156 mixing Methods 0.000 claims description 15
- 238000012845 near infrared spectroscopy analysis Methods 0.000 claims description 15
- 238000006317 isomerization reaction Methods 0.000 claims description 14
- 238000006243 chemical reaction Methods 0.000 claims description 12
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 11
- 150000001875 compounds Chemical class 0.000 claims description 11
- 239000001301 oxygen Substances 0.000 claims description 11
- 229910052760 oxygen Inorganic materials 0.000 claims description 11
- 239000003981 vehicle Substances 0.000 claims description 11
- 150000002148 esters Chemical class 0.000 claims description 10
- 238000002835 absorbance Methods 0.000 claims description 9
- 239000012188 paraffin wax Substances 0.000 claims description 9
- 150000004945 aromatic hydrocarbons Chemical class 0.000 claims description 8
- 230000001105 regulatory effect Effects 0.000 claims description 8
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 claims description 7
- 150000001335 aliphatic alkanes Chemical class 0.000 claims description 7
- 239000010775 animal oil Substances 0.000 claims description 7
- 239000002245 particle Substances 0.000 claims description 7
- 235000013305 food Nutrition 0.000 claims description 6
- 238000012804 iterative process Methods 0.000 claims description 6
- 108090000623 proteins and genes Proteins 0.000 claims description 4
- 229920006395 saturated elastomer Polymers 0.000 claims description 4
- 229930195735 unsaturated hydrocarbon Natural products 0.000 claims description 4
- 230000003247 decreasing effect Effects 0.000 claims description 3
- 239000001257 hydrogen Substances 0.000 claims description 3
- 229910052739 hydrogen Inorganic materials 0.000 claims description 3
- 150000001336 alkenes Chemical class 0.000 claims description 2
- 150000001924 cycloalkanes Chemical class 0.000 claims description 2
- 150000001925 cycloalkenes Chemical class 0.000 claims description 2
- 235000019197 fats Nutrition 0.000 description 63
- 230000003595 spectral effect Effects 0.000 description 44
- 235000019198 oils Nutrition 0.000 description 35
- 235000019688 fish Nutrition 0.000 description 25
- 230000008569 process Effects 0.000 description 17
- 241000196324 Embryophyta Species 0.000 description 16
- 238000004519 manufacturing process Methods 0.000 description 16
- 238000005259 measurement Methods 0.000 description 16
- 235000015112 vegetable and seed oil Nutrition 0.000 description 16
- 239000001993 wax Substances 0.000 description 16
- 238000010521 absorption reaction Methods 0.000 description 14
- 235000014113 dietary fatty acids Nutrition 0.000 description 14
- 239000000194 fatty acid Substances 0.000 description 14
- 229930195729 fatty acid Natural products 0.000 description 14
- 239000012164 animal wax Substances 0.000 description 12
- 150000004665 fatty acids Chemical class 0.000 description 12
- 239000012165 plant wax Substances 0.000 description 12
- 239000002551 biofuel Substances 0.000 description 11
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 description 10
- 239000007788 liquid Substances 0.000 description 10
- 239000000047 product Substances 0.000 description 10
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 9
- 238000002485 combustion reaction Methods 0.000 description 8
- 239000008158 vegetable oil Substances 0.000 description 8
- 229910002092 carbon dioxide Inorganic materials 0.000 description 7
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 description 6
- 239000003225 biodiesel Substances 0.000 description 6
- -1 e.g. added alcohol Chemical class 0.000 description 6
- 229910052710 silicon Inorganic materials 0.000 description 6
- 239000010703 silicon Substances 0.000 description 6
- 239000004215 Carbon black (E152) Substances 0.000 description 5
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 description 5
- 238000004760 accelerator mass spectrometry Methods 0.000 description 5
- 239000012620 biological material Substances 0.000 description 5
- 229910052500 inorganic mineral Inorganic materials 0.000 description 5
- 239000000463 material Substances 0.000 description 5
- 239000011707 mineral Substances 0.000 description 5
- 230000035945 sensitivity Effects 0.000 description 5
- 239000000126 substance Substances 0.000 description 5
- 235000019737 Animal fat Nutrition 0.000 description 4
- 241000252203 Clupea harengus Species 0.000 description 4
- 150000001298 alcohols Chemical class 0.000 description 4
- 230000003466 anti-cipated effect Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 4
- 230000000035 biogenic effect Effects 0.000 description 4
- 229910052799 carbon Inorganic materials 0.000 description 4
- BVKZGUZCCUSVTD-UHFFFAOYSA-N carbonic acid Chemical class OC(O)=O BVKZGUZCCUSVTD-UHFFFAOYSA-N 0.000 description 4
- 239000004203 carnauba wax Substances 0.000 description 4
- 238000001514 detection method Methods 0.000 description 4
- 235000021588 free fatty acids Nutrition 0.000 description 4
- 239000010460 hemp oil Substances 0.000 description 4
- 238000002347 injection Methods 0.000 description 4
- 239000007924 injection Substances 0.000 description 4
- 238000005567 liquid scintillation counting Methods 0.000 description 4
- 238000007670 refining Methods 0.000 description 4
- 239000003784 tall oil Substances 0.000 description 4
- 239000003760 tallow Substances 0.000 description 4
- 240000002791 Brassica napus Species 0.000 description 3
- 241000195493 Cryptophyta Species 0.000 description 3
- 241000221089 Jatropha Species 0.000 description 3
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 description 3
- 229910003294 NiMo Inorganic materials 0.000 description 3
- MWUXSHHQAYIFBG-UHFFFAOYSA-N Nitric oxide Chemical compound O=[N] MWUXSHHQAYIFBG-UHFFFAOYSA-N 0.000 description 3
- 235000019482 Palm oil Nutrition 0.000 description 3
- 238000000862 absorption spectrum Methods 0.000 description 3
- PNEYBMLMFCGWSK-UHFFFAOYSA-N aluminium oxide Inorganic materials [O-2].[O-2].[O-2].[Al+3].[Al+3] PNEYBMLMFCGWSK-UHFFFAOYSA-N 0.000 description 3
- 125000003118 aryl group Chemical group 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 239000007789 gas Substances 0.000 description 3
- 239000003502 gasoline Substances 0.000 description 3
- 230000006872 improvement Effects 0.000 description 3
- 238000005457 optimization Methods 0.000 description 3
- 239000002540 palm oil Substances 0.000 description 3
- 239000002994 raw material Substances 0.000 description 3
- 239000003549 soybean oil Substances 0.000 description 3
- 235000012424 soybean oil Nutrition 0.000 description 3
- 238000005809 transesterification reaction Methods 0.000 description 3
- 150000003626 triacylglycerols Chemical class 0.000 description 3
- 235000019871 vegetable fat Nutrition 0.000 description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 3
- 239000002028 Biomass Substances 0.000 description 2
- 235000006008 Brassica napus var napus Nutrition 0.000 description 2
- 241001454694 Clupeiformes Species 0.000 description 2
- 244000180278 Copernicia prunifera Species 0.000 description 2
- 235000010919 Copernicia prunifera Nutrition 0.000 description 2
- RTZKZFJDLAIYFH-UHFFFAOYSA-N Diethyl ether Chemical compound CCOCC RTZKZFJDLAIYFH-UHFFFAOYSA-N 0.000 description 2
- 241000233866 Fungi Species 0.000 description 2
- 241000238631 Hexapoda Species 0.000 description 2
- 235000016856 Palma redonda Nutrition 0.000 description 2
- 235000019483 Peanut oil Nutrition 0.000 description 2
- 235000004599 Pongamia pinnata Nutrition 0.000 description 2
- 244000037433 Pongamia pinnata Species 0.000 description 2
- 235000019484 Rapeseed oil Nutrition 0.000 description 2
- 235000019774 Rice Bran oil Nutrition 0.000 description 2
- 240000004808 Saccharomyces cerevisiae Species 0.000 description 2
- 241001125048 Sardina Species 0.000 description 2
- 241000269821 Scombridae Species 0.000 description 2
- 244000044822 Simmondsia californica Species 0.000 description 2
- 235000004433 Simmondsia californica Nutrition 0.000 description 2
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical class [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 description 2
- 150000001299 aldehydes Chemical class 0.000 description 2
- ZOJBYZNEUISWFT-UHFFFAOYSA-N allyl isothiocyanate Chemical compound C=CCN=C=S ZOJBYZNEUISWFT-UHFFFAOYSA-N 0.000 description 2
- 235000019513 anchovy Nutrition 0.000 description 2
- 150000008064 anhydrides Chemical class 0.000 description 2
- 125000004429 atom Chemical group 0.000 description 2
- 235000013871 bee wax Nutrition 0.000 description 2
- 235000013868 candelilla wax Nutrition 0.000 description 2
- 239000004204 candelilla wax Substances 0.000 description 2
- 229940073532 candelilla wax Drugs 0.000 description 2
- 235000019519 canola oil Nutrition 0.000 description 2
- 239000000828 canola oil Substances 0.000 description 2
- 125000004432 carbon atom Chemical group C* 0.000 description 2
- 239000001569 carbon dioxide Substances 0.000 description 2
- 239000004359 castor oil Substances 0.000 description 2
- 235000019438 castor oil Nutrition 0.000 description 2
- 230000003197 catalytic effect Effects 0.000 description 2
- 239000012174 chinese wax Substances 0.000 description 2
- 239000003240 coconut oil Substances 0.000 description 2
- 235000019864 coconut oil Nutrition 0.000 description 2
- 230000000295 complement effect Effects 0.000 description 2
- 235000005687 corn oil Nutrition 0.000 description 2
- 239000002285 corn oil Substances 0.000 description 2
- 239000002385 cottonseed oil Substances 0.000 description 2
- 235000012343 cottonseed oil Nutrition 0.000 description 2
- 230000006866 deterioration Effects 0.000 description 2
- 150000001991 dicarboxylic acids Chemical class 0.000 description 2
- 239000002283 diesel fuel Substances 0.000 description 2
- 230000003292 diminished effect Effects 0.000 description 2
- 150000002009 diols Chemical class 0.000 description 2
- 239000012183 esparto wax Substances 0.000 description 2
- 230000032050 esterification Effects 0.000 description 2
- 238000005886 esterification reaction Methods 0.000 description 2
- 238000011066 ex-situ storage Methods 0.000 description 2
- 150000002191 fatty alcohols Chemical class 0.000 description 2
- 238000010353 genetic engineering Methods 0.000 description 2
- ZEMPKEQAKRGZGQ-XOQCFJPHSA-N glycerol triricinoleate Natural products CCCCCC[C@@H](O)CC=CCCCCCCCC(=O)OC[C@@H](COC(=O)CCCCCCCC=CC[C@@H](O)CCCCCC)OC(=O)CCCCCCCC=CC[C@H](O)CCCCCC ZEMPKEQAKRGZGQ-XOQCFJPHSA-N 0.000 description 2
- IUJAMGNYPWYUPM-UHFFFAOYSA-N hentriacontane Chemical compound CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC IUJAMGNYPWYUPM-UHFFFAOYSA-N 0.000 description 2
- 235000019514 herring Nutrition 0.000 description 2
- 230000007062 hydrolysis Effects 0.000 description 2
- 238000006460 hydrolysis reaction Methods 0.000 description 2
- 238000011065 in-situ storage Methods 0.000 description 2
- 239000012182 japan wax Substances 0.000 description 2
- 235000020640 mackerel Nutrition 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 229910052751 metal Inorganic materials 0.000 description 2
- 239000002184 metal Substances 0.000 description 2
- 244000005700 microbiome Species 0.000 description 2
- 235000013336 milk Nutrition 0.000 description 2
- 239000008267 milk Substances 0.000 description 2
- 210000004080 milk Anatomy 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 239000008164 mustard oil Substances 0.000 description 2
- 229910017464 nitrogen compound Inorganic materials 0.000 description 2
- 150000002830 nitrogen compounds Chemical class 0.000 description 2
- 239000004006 olive oil Substances 0.000 description 2
- 235000008390 olive oil Nutrition 0.000 description 2
- 239000003346 palm kernel oil Substances 0.000 description 2
- 235000019865 palm kernel oil Nutrition 0.000 description 2
- 239000000312 peanut oil Substances 0.000 description 2
- 229920005862 polyol Polymers 0.000 description 2
- 150000003077 polyols Chemical class 0.000 description 2
- 238000000197 pyrolysis Methods 0.000 description 2
- 238000004064 recycling Methods 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 239000008165 rice bran oil Substances 0.000 description 2
- 229940119224 salmon oil Drugs 0.000 description 2
- 150000003839 salts Chemical class 0.000 description 2
- 238000007127 saponification reaction Methods 0.000 description 2
- 235000019512 sardine Nutrition 0.000 description 2
- 239000012176 shellac wax Substances 0.000 description 2
- 238000004611 spectroscopical analysis Methods 0.000 description 2
- 238000010183 spectrum analysis Methods 0.000 description 2
- 235000020238 sunflower seed Nutrition 0.000 description 2
- 235000007586 terpenes Nutrition 0.000 description 2
- 150000003505 terpenes Chemical class 0.000 description 2
- UFTFJSFQGQCHQW-UHFFFAOYSA-N triformin Chemical compound O=COCC(OC=O)COC=O UFTFJSFQGQCHQW-UHFFFAOYSA-N 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 239000002023 wood Substances 0.000 description 2
- 241000269350 Anura Species 0.000 description 1
- 235000004977 Brassica sinapistrum Nutrition 0.000 description 1
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 244000068988 Glycine max Species 0.000 description 1
- 235000010469 Glycine max Nutrition 0.000 description 1
- 238000004497 NIR spectroscopy Methods 0.000 description 1
- 229910021536 Zeolite Inorganic materials 0.000 description 1
- 238000005452 bending Methods 0.000 description 1
- 230000001588 bifunctional effect Effects 0.000 description 1
- JJWKPURADFRFRB-UHFFFAOYSA-N carbonyl sulfide Chemical compound O=C=S JJWKPURADFRFRB-UHFFFAOYSA-N 0.000 description 1
- 238000004517 catalytic hydrocracking Methods 0.000 description 1
- 239000008162 cooking oil Substances 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- HNPSIPDUKPIQMN-UHFFFAOYSA-N dioxosilane;oxo(oxoalumanyloxy)alumane Chemical compound O=[Si]=O.O=[Al]O[Al]=O HNPSIPDUKPIQMN-UHFFFAOYSA-N 0.000 description 1
- 238000004821 distillation Methods 0.000 description 1
- 239000000839 emulsion Substances 0.000 description 1
- 150000002170 ethers Chemical class 0.000 description 1
- 238000001704 evaporation Methods 0.000 description 1
- 235000019387 fatty acid methyl ester Nutrition 0.000 description 1
- 239000012467 final product Substances 0.000 description 1
- 238000005194 fractionation Methods 0.000 description 1
- 239000000295 fuel oil Substances 0.000 description 1
- 239000004519 grease Substances 0.000 description 1
- 238000005984 hydrogenation reaction Methods 0.000 description 1
- 239000012535 impurity Substances 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 150000002632 lipids Chemical class 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 230000000813 microbial effect Effects 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 125000004433 nitrogen atom Chemical group N* 0.000 description 1
- 229910000510 noble metal Inorganic materials 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 125000004430 oxygen atom Chemical class O* 0.000 description 1
- 230000003449 preventive effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000002285 radioactive effect Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 239000011949 solid catalyst Substances 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000029305 taxis Effects 0.000 description 1
- 150000005691 triesters Chemical group 0.000 description 1
- 235000013311 vegetables Nutrition 0.000 description 1
- 239000010457 zeolite Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D19/00—Controlling engines characterised by their use of non-liquid fuels, pluralities of fuels, or non-fuel substances added to the combustible mixtures
- F02D19/06—Controlling engines characterised by their use of non-liquid fuels, pluralities of fuels, or non-fuel substances added to the combustible mixtures peculiar to engines working with pluralities of fuels, e.g. alternatively with light and heavy fuel oil, other than engines indifferent to the fuel consumed
- F02D19/0639—Controlling engines characterised by their use of non-liquid fuels, pluralities of fuels, or non-fuel substances added to the combustible mixtures peculiar to engines working with pluralities of fuels, e.g. alternatively with light and heavy fuel oil, other than engines indifferent to the fuel consumed characterised by the type of fuels
- F02D19/0649—Liquid fuels having different boiling temperatures, volatilities, densities, viscosities, cetane or octane numbers
- F02D19/0652—Biofuels, e.g. plant oils
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D19/00—Controlling engines characterised by their use of non-liquid fuels, pluralities of fuels, or non-fuel substances added to the combustible mixtures
- F02D19/06—Controlling engines characterised by their use of non-liquid fuels, pluralities of fuels, or non-fuel substances added to the combustible mixtures peculiar to engines working with pluralities of fuels, e.g. alternatively with light and heavy fuel oil, other than engines indifferent to the fuel consumed
- F02D19/08—Controlling engines characterised by their use of non-liquid fuels, pluralities of fuels, or non-fuel substances added to the combustible mixtures peculiar to engines working with pluralities of fuels, e.g. alternatively with light and heavy fuel oil, other than engines indifferent to the fuel consumed simultaneously using pluralities of fuels
- F02D19/082—Premixed fuels, i.e. emulsions or blends
- F02D19/085—Control based on the fuel type or composition
- F02D19/087—Control based on the fuel type or composition with determination of densities, viscosities, composition, concentration or mixture ratios of fuels
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/26—Oils; Viscous liquids; Paints; Inks
- G01N33/28—Oils, i.e. hydrocarbon liquids
- G01N33/2829—Mixtures of fuels
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/26—Oils; Viscous liquids; Paints; Inks
- G01N33/28—Oils, i.e. hydrocarbon liquids
- G01N33/2835—Specific substances contained in the oils or fuels
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D2200/00—Input parameters for engine control
- F02D2200/02—Input parameters for engine control the parameters being related to the engine
- F02D2200/06—Fuel or fuel supply system parameters
- F02D2200/0611—Fuel type, fuel composition or fuel quality
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/0025—Controlling engines characterised by use of non-liquid fuels, pluralities of fuels, or non-fuel substances added to the combustible mixtures
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/30—Use of alternative fuels, e.g. biofuels
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Spectroscopy & Molecular Physics (AREA)
- General Health & Medical Sciences (AREA)
- Pathology (AREA)
- Immunology (AREA)
- General Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- Oil, Petroleum & Natural Gas (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Medicinal Chemistry (AREA)
- General Chemical & Material Sciences (AREA)
- Food Science & Technology (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Biodiversity & Conservation Biology (AREA)
- Biotechnology (AREA)
- Botany (AREA)
- Sustainable Development (AREA)
- Sustainable Energy (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
Disclosed here is a method for determining the amount of renewable and fossil fuel components in a fuel blend using near infrared analysis.
Description
Method for determining the amount of renewable fuel in a fuel blend.
Technical Field
The present invention relates to a method for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component, and to the use of a system thereto.
Background Art
Combining bio-based liquid hydrocarbon fuel with fossil fuel has attracted increasing attention during the past years. National directives exist which vary considerable from one country to another, but many recommend biofuel to be present in the fuel. On the other hand, refining constraints exist which are imposed 10 by commercial specifications limiting the degree of freedom in the integration of biofuel as a function of refining bases composing the fossil fuel. There is thus a need for analysing methods, which can provide accurate information on the content of biological components present in the fuel.
The state of the art and most accurate biogenic analysis method is the carbon-14isotope analysis (14C analysis) of the fuel. This analysis is based on knowledge of the ratio between the three naturally occurring isotopes of carbon, 12C, 13C, and 14C, combined with the decay time of the radioactive 14C. Small amounts of 14C isotopes are being formed in the upper atmosphere due to cosmic rays hitting 20 atmospheric nitrogen atoms. The resulting 14C/12C ratio in the atmosphere is rather constant and about 1 part-per-trillion (ppt;10-12), that is, the amount of 14C in the atmosphere is very very small, but yet it is still measurable. The 14C atoms being formed in the atmosphere do not stay as isolated atoms in the atmosphere but instead they form molecules like carbon dioxide. All living organisms will 25 subsequently take up the 14C contained in the atmospheric carbon dioxide. The half-life time of 14C is around 5700 years, which means that for fossil fuel, which is hundreds of millions of years old, all the 14C has completely decayed. In contrast, the level of the residual 14C left in biofuels, which are derived from young biomass (normally up to a few 1000 years old) can be measured with modem 30 instrumentation.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
2/38
For determining if the liquid hydrocarbon fuel is fossil or bio-based, or what is the blending ratio between these two components, there are mainly two practically employed measurement techniques: Accelerator Mass Spectrometry (AMS) and 5 Liquid Scintillation Counting (LSC).
The advantage of AMS is that it is the most accurate scientific-grade biogenic method. One disadvantage is that the instrument is large and presently costs 1-2 MEUR. Further, it requires a dedicated laboratory and trained personnel for 10 operation, where it typically takes about 2-14 days to get the analytical result of one analysis and the cost for analysis is therefore high. Thus, by no means can AMS be considered suitable for online analysis.
Also, the LSC can perform biogenic analysis, but is typically limited to visually 15 clear gasoline and diesel fuels. It is more cost efficient (starting presently from 60
000 EUR) than AMS and ordinary lab technicians can perform the analysis, which takes typically 2-10 hours depending on the biogenic content of the fuel. However, LSC is only available as a laboratory off-line technique and hence is not suitable for online process analysis.
Consequently, there is a need for an online type fast analysis, which can provide knowledge on whether the liquid hydrocarbon fuel is fossil or bio-based, or if it is a mixture of the two, and what the blending ratio between these components might be.
Typically biofuel refers to a bio-based product manufactured through a transesterification reaction. For example vegetable oils and alcohols may be reacted into esters, and glycerol is formed as co-product. For example biodiesel may include mono-alkyl esters of vegetable oils or animal fats. Biodiesel is 30 produced by transesterifying the oil or fat with an alcohol such as methanol under mild conditions in the presence of a base catalyst. Biodiesel can be used in any diesel engine when mixed with mineral diesel. However, the oxygenate containing
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
3/38 bio-based fuels may only be used to a minor extent, such as 20 wt-% in a fuel blend for conventional diesel equipment designed for mineral diesel operation.
Another type of product that may be obtained from lipid feedstocks is a fuel having a composition that simulates the composition of fossil diesel fuel, namely renewable diesel. Renewable diesel is produced from the fat or oil by a hydrodeoxygenation reaction at an elevated temperature and pressure in the presence of a catalyst. The renewable diesel has a considerably higher energy content compared to biodiesel containing oxygenates and is suitable for use as 10 such, e.g. as 100 wt-%, in existing vehicles.
The applicant has disclosed production of renewable fuels based on vegetable oil or animal fat refining processes in several patent documents, e.g. FI100248, EP1396531, EP1741768 and EP1741767. These depict detailed catalytic 15 hydrotreatment and isomerization of plant oils and animal fats, which contain triglycerides, into the corresponding alkanes. The glycerol chain of the triglyceride is hydrogenated to the corresponding alkane without any glycerol sidestream. These processes remove oxygen from the oil or fat; the diesel produced is not an oxygenate like in e.g. traditional transesterified FAME biodiesel. Catalytic 20 isomerization into branched alkanes is done to adjust the cloud properties in order to meet winter operability requirements. As the final product is chemically similar to conventional mineral diesel, it requires no modification or special precautions for conventional diesel engine use for example.
US2008162016 discloses a method for optimizing operation of an engine driven by an electronic or digital system. In the method, the fuel composition is analysed by at least one sensor located in a fuel circuit of an engine, wherein the fuel composition analysis comprises spectroscopic analysis of the molecular structure of the hydrocarbons, such as e.g. added alcohol, composing said fuel.
US2010168984 discloses a method for adjusting injection, combustion and/or post-treatment parameters of an internal combustion engine with auto-ignition. The
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
4/38 method includes a step of determining the content or type of ester-based biofuel present in the fuel feeding, the injection system, using a spectroscopic unit.
US2010305827 discloses a device for the centralized management of measurements and data relating to liquid and/or gas flows needed for the correct operation of a combustion engine controlled by an engine computer. This device comprises means for analyzing at least two liquid and/or gas flows including at least one light source, at least one optical signals detector and at least one system for analyzing the detected signals. The device is characterized in that at least one of said analysis means is arranged to be used for analyzing two of said flows. The description further discloses that in spite of the regulatory or internal provisions recommended by fuel distributors and vehicle manufacturers many users introduce a non-adapted fuel into the tanks of their vehicles. An increasing number of vehicles are used with products which are not certified by the manufacturers and the customs services like used frying oils, non-esterified vegetable oils, domestic fuel oils, causing serious damages to the power unit, the fuel supply system and the post-treatment system. The damages may severely impact the engine injection and combustion phases and increase the regulated or not polluting emissions, which can lead to engine break. Similarly, some fuels such as water/gasoil or gasoline/alcohol or gasoil/bio-fuels emulsions can be instable and the quality thereof can deteriorate over time. Such deterioration of the nature of the fuel potentially entails an increase in the vehicle pollution, damages to the vehicle or at least important corrective operations. Thus, concepts and methods aim at providing preventive safety to the elements of the power unit of a vehicle equipped with a combustion engine, prior to or during the ignition phase further to deterioration of the nature of the fuel contained in the tank and the fuel supply system. Such concepts and systems involve the measurement of the fuel quality, ideally in the fuel supply system.
US20120226425 discloses that it aims at providing a method for optimising the operation of a thermal engine supplied with bio-fuel, wherein said bio-fuel is analysed with accuracy in order to provide adjustments of the engine to be best suited to the fuel. This is achieved by a method for optimizing the operation of a
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
5/38 thermal engine having combustion parameters controlled by an electronic housing and at least one engine mapping. The method comprises the following steps: A step of carrying out a near-infrared spectroscopic analysis of a bio-fuel containing a mixture of alcohols and/or ethers and/or water in order to determine the proportion of water and of at least one other oxygenated compound of the alcohol and/or ether type contained in the bio-fuel; A step of selecting and/or modifying said mapping on the basis of the result of said step of analysis and determination in order to optimize the operation of the thermal engine. The description further discloses that thermal internal combustion engines must meet always stricter requirements as regards CO2, NOx, HC emission standards and this is the reason why the proportion of bio-fuels in the commercial fuels, i.e. gasoline and gas-oil, such as bio-ethanol and bio-diesel which are manufactured from multiple sources enabling the substitution of oxygen atoms for carbon atoms has been rising for a few decades.
None of the discussed prior art documents, however, addresses the issue of providing a reliable, cost efficient and fast analysis method for online analysis of fuel blends when the bio-based fuel component is renewable fuel component.
Consequently, there is a need for a reliable method and system, which can provide knowledge on the amount of renewable fuel components in a liquid fuel blend comprising mineral or fossil fuel and renewable fuel components.
Summary of the Invention
The object of the present invention is to provide online knowledge of the amount of a renewable fuel component in a fuel blend.
A further object of the present invention is to provide a method for adjusting the 15 amount of renewable fuel component to the amount of fossil fuel in a fuel blend.
A yet further object of the present invention is to provide use of a system for determining the amount of the renewable fuel in a fuel blend.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
6/38
To solve the problem, the present invention provides in a first aspect of the invention the use of a near infrared spectroscopic system for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component, the near infrared spectroscopic system comprising:
• means for carrying out near infrared spectroscopic analysis of the fuel blend, and • means for determining the amount of the renewable fuel component in the fuel blend based on comparing results from the near infrared spectroscopic analysis of the fuel blend to one or more values obtained from predefined near infrared spectrum calibration curves thereby providing the amount of the renewable fuel component in the fuel blend.
That is, the inventor of the present invention found that a number of advantages are obtainable for the first aspect of the invention including the obtainability of composition data in less than a few minutes compared to hours as is the case for other methods. Preferably the composition information is obtained in two minutes, 5 more preferably within a minute, or even less, such as in 50 s or even in 30 s. The precision of the method is about 1% which is accurate enough for the intended use. The composition analysis time is thereby greatly reduced compared to especially the conventional off-line 14C analysis used for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel 10 component and a fossil fuel component. The first aspect of the invention consequently provides revenue for being able to measure in real time and with good accuracy.
Additionally, the first aspect of the invention enables the manufacturing of precise 15 quality blend products in situ or online, further enabling accurate determination of the cost for the renewable fuel blend. Presently, the blend composition quality is monitored ex situ with a possible delay of even 24 h while using the 14C isotope measuring method.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
7/38
The amount of the renewable fuel component in the fuel blend tends to drift from the desired or predetermined value during production of the fuel blend causing a too low anticipated amount or a too high actual amount of the renewable fuel component in a fuel blend. This blend quality fluctuation may in both cases imply 5 cost related issues for the blender. The use of the system and the method of the present invention enable an accurate real time determination of the amount of the renewable fuel component, reducing the production cost notably and simplifying the quality monitoring.
Furthermore, by having exact and real time knowledge of the amount of a renewable fuel component in a fuel blend, the amount of CO2 and particle emissions when using the blend in vehicle applications can be minimized by optimization of the engine performance to the known renewable fuel component in the fuel blend.
A second aspect of the invention disclosed herein is a method for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component, wherein the method comprises the steps of:
• providing a sample of the fuel blend to a device comprising a near infrared spectrometer;
• measuring one or more infrared spectra of the fuel blend using the near infrared spectrometer;
• determining the amount of renewable fuel component in the fuel blend by analysing the one or more infrared spectra of the fuel blend and comparing the analysis result to one or more predefined near infrared spectrum calibration curves linking a known amount of the renewable fuel component in a fuel blend to the one or more measured near infrared spectra of the fuel blend.
Detailed Description of the Invention
In describing the embodiments of the invention specific terminology will be resorted to for the sake of clarity. However, the invention is not intended to be
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
8/38 limited to the specific terms so selected, and it is understood that each specific term includes all technical equivalents which operate in a similar manner to accomplish a similar purpose.
When describing the embodiments of the present invention, the combinations and permutations of all possible embodiments have not been explicitly described. Nevertheless, the mere fact that certain measures are recited in mutually different dependent claims or described in different embodiments does not indicate that a combination of these measures cannot be used to advantage. The present 10 invention envisages all possible combinations and permutations of the described embodiments.
The terms “comprising”, “comprise” and “comprises” herein are intended by the inventors to be optionally substitutable with the terms “consisting of”, “consist of” 15 and “consists of”, respectively, in every instance.
The present invention was made in view of the prior art described above, and the object of the present invention is to provide online knowledge of the amount of a renewable fuel component in a fuel blend.
In the first aspect of the invention is disclosed the use of a near infrared spectroscopic system for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component, the near infrared spectroscopic system comprising:
• means for carrying out near infrared spectroscopic analysis of the fuel blend, and • means for determining the amount of the renewable fuel component in the fuel blend based on comparing results from the near infrared spectroscopic analysis of the fuel blend to one or more values obtained from predefined near infrared spectrum calibration curves thereby providing the amount of the renewable fuel component in the fuel blend.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
9/38
In some embodiments of the present invention, the means for carrying out near infrared spectroscopic analysis comprises means for measuring one or more near infrared spectra of the fuel blend, and means for analysing the measured one or more near infrared spectra. The means for measuring the one or more near 5 infrared spectra may include infrared sensors operating in a narrow spectral band range spanning a few 100 nm up to larger spectral band ranges covering e.g. the near infrared spectral range from 700-3000 nm. Different types of sensors are commercially available.
Near infrared (NIR) spectroscopy is based on molecular overtone and combination vibrations. Multivariant calibration technologies may be employed to extract the desired chemical information from the recorded spectra.
Examples of more narrow spectral ranges includes the near infrared wavelength 15 range from 800 nm to 900 nm. In this spectral range signals are often weak.
However, the different absorption features may possibly be better spectrally separated from each other in this spectral wavelength range although the signal is weak. More easily spectrally separable features may provide an improved accuracy and performance to the measurements. For example, silicon based 20 detector technology may be used at these short NIR wavelengths, which lowers the costs due to the low price of silicon based detectors.
Alternatively, the spectral wavelength range from 1000 nm to 1600 nm, such as from 1100-1300 nm, or from 1150-1250 nm may be used. In these spectral ranges, absorption signals are normally stronger, which increases the sensitivity of the measurements. The detectors suitable for measuring NIR spectra in the spectral wavelength range from 1000-1600 nm are, however, normally slightly more expensive compared to e.g. silicon based detectors.
Yet alternatively, the spectral wavelength range from 1600 nm to 1800 nm, or even more narrow spectral range from 1700 nm to 1775 nm, also provides NIR 25 spectra, where signals from renewable fuel components may be separable from those from fossil fuel components.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
10/38
Thus, the near infrared spectral range, which is chosen for measuring the one or more near infrared spectra of the fuel blend, may vary depending on the requirements to cost, sensitivity and selectivity in the spectral data.
The means for analysing the one or more near infrared spectra may include chemometric models, which are able to produce one or more near infrared 5 calibration curves from one or more near infrared spectra of fuel blends with known amounts of the renewable fuel component and/or compare near infrared spectra of fuel blends with unknown amounts of the renewable fuel component to the calibration curve(s), thereby determining the amount of the renewable fuel component in the fuel blend with the unknown amount of renewable fuel 10 component.
In some embodiments of the present invention, the means for analysing the measured one or more near infrared spectra further comprises means for obtaining derivative spectra of the one or more measured near infrared spectra. By forming the derivative spectra of the measured near infrared spectra, background variation observed between measurements performed on different days or different times during the day may be vastly reduced if not completely avoided. A more robust system is thereby obtained.
In some embodiments of the present invention, the one or more predefined near infrared calibration curves are comprised in the near infrared spectroscopic system. Thus, the near infrared spectroscopic system may be set up to include a multiple of predefined near infrared calibration curves representing fuel blends with known amounts of renewable fuel components. Each of the near infrared calibration curves may be a representative of a known type of renewable fuel and its spectral characteristic in a fuel blend comprising known amounts of this known type of renewable fuel.
In some embodiments of the present invention, the amount of renewable fuel component in the fuel blend is determined within 2 minutes or less, preferably
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
11/38 within 1 minute or less, such as within 50 s or less, even in 30 s. The operation time of 2 minutes or less renders the near infrared spectroscopic system very attractive for online measurements. The short operation time is a vast improvement compared to the 14C detection method, which cannot be operated online and which typically takes days for providing the needed result.
In some embodiments of the present invention, the one or more predefined near infrared calibration curves are obtained by 1) forming fuel blends comprising different known amounts of the renewable fuel component in the fuel blends, and 2) recording multiple near infrared spectra of the fuel blends, 3) forming derivative spectra from the obtained multiple near infrared spectra, 4) obtaining absorbance values from each of the derivative spectra at a first wavelength, and 5) relating each of the absorbance values to the known amounts of the renewable fuel component in the fuel blends. It has been shown that reliable calibration curves focusing on the value of the derivative spectra at a favourably chosen wavelength are sufficient to obtain reliable calibration curves allowing for determination of the amount of renewable fuel component in a fuel blend. By obtaining the derivative spectra instead of the directly measured infrared spectra, the background signals are diminished to a reasonable extent.
In some embodiments of the present invention, the amount of renewable fuel component in the fuel blend is from 1 to 100 wt-%, preferably from 20 to 80 wt-%, more preferably from 30 to 60 wt-%. The blend composition depends on the blend properties and its use, which again depend on the qualities of the blend components. The method of the present invention is capable of measuring virtually any ratios of renewable fuel component and mineral/fossil fuel components in a fuel blend comprising these components. But typically the desired contents of renewable fuel components are around 1-70 wt-%. The contents of renewable fuel components vary depending on country, and time of year, etc. for example summer diesel aims at around 30 wt-% blend whereas winter diesel aims at around 50-60 wt-%. Another factor, which may also influence the chosen contents of renewable fuel components in fuel blends, is the national taxes imposed on the
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
12/38 fuel blends. The method disclosed herein is able to provide a reliable result independently of the content of renewable fuel components in fuel blends.
In some embodiments of the present invention, a feedstock for the renewable fuel component originates from plant oils or fats, or animal oils or fats, or fish oils or fats. The feedstock originating from a biological raw material containing fatty acids and/or fatty acid esters that originate from plants, animals or fish may be used. The biomaterial being selected from the group consisting of vegetable oils/fats, animal fats, fish oils and mixtures thereof is also suitable for use as feedstock. Examples of suitable biomaterials are any kind of fats, and any kind of waxes such as e.g.:
• any kind of plant fats, plant oils, and plant waxes;
• any kind of animal fats, animal oils, animal waxes, animal-based fats, fish fats, fish oils, and fish waxes;
• fatty acids or free fatty acids obtained from plant fats, plant oils, plant waxes; animal fats, animal oils, animal waxes; fish fats, fish oils, fish waxes, and mixtures thereof by hydrolysis, transesterification or pyrolysis;
• fats contained in milk;
• metal salts of fatty acids obtained from plant fats, plant oils, plant waxes; animal fats, animal waxes; fish fats, fish oils, fish waxes, and mixtures thereof by saponification;
• anhydrides of fatty acids from plant fats, plant oils, plant waxes; animal fats, animal waxes; fish fats, fish oils, fish waxes, and mixtures thereof;
• esters obtained by esterification of free fatty acids of plant, animal and fish origin with alcohols;
• fatty alcohols or aldehydes obtained as reduction products of fatty acids from plant fats, plant oils, plant waxes; animal fats, animal waxes; fish fats, fish oils, fish waxes, and mixtures thereof;
• recycled fats of the food industry;
• fats contained in plants bred by means of gene manipulation or genetic engineering;
• dicarboxylic acids or polyols including diols, hydroxyketones, hydroxyaldehydes, hydroxycarboxylic acids, and corresponding di- or
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
13/38 multifunctional sulphur compounds, corresponding di- or multifunctional nitrogen compounds, and • compounds derived from algae, molds, yeasts, fungi and/or other microorganisms capable of producing compounds mentioned above or compounds similar to those.
Examples of fish oils include Baltic herring oil, salmon oil, herring oil, tuna oil, anchovy oil, sardine oil, and mackerel oil.
Examples of plant oils and/or wood-based oils include rapeseed oil, colza oil, canola oil, tall oil, crude tall oil, sunflower seed oil, soybean oil, corn oil, hemp oil, hempseed oil, olive oil, linen seed oil, cotton seed oil, mustard oil, palm oil, peanut oil, castor oil, Jatropha seed oil, Pongamia pinnata seed oil, palm kernel oil, and, coconut oil.
Examples of animal fats include lard, tallow, rendered lard and rendered tallow.
Examples of animal waxes include bee wax, Chinese wax (insect wax), shellac wax, and lanoline (woll wax).
Examples of plant waxes include carnauba palm wax, Ouricouri palm wax, jojoba seed oil, candelilla wax, esparto wax, Japan wax, rice bran oil, terpenes, terpineols and triglycerides or mixtures thereof.
The basic structural unit of a typical vegetable or animal fat useful as the feedstock is a triglyceride, that is a triester of glycerol with three fatty acid molecules, having the structure presented in the following formula I:
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
14/38 wherein R1; R2 and R3 are hydrocarbon chains, and R-ι, R2 and R3 may be saturated or unsaturated C6-C24alkyl groups. The fatty acid composition may vary considerably in feedstocks of different origin.
Mixtures of a biological raw material and hydrocarbon may also serve as the feed, and further, the hydrocarbon component obtained as the product may, if desired, be recycled back to the feed to control the exothermal character of the reactions.
The renewable fuel component may be produced in a number of different manners. One process for producing renewable fuel components from a material of biological origin comprises the steps of:
a) evaporating the material of biological origin in order to remove impurities from the material of biological origin thereby producing purified biological material;
b) hydroprocessing the purified biological material in the presence of hydrogen gas and at least one catalyst to form a mixture of hydrocarbon compounds;
c) separating gaseous compounds from the mixture of hydrocarbon compounds to obtain liquid hydrocarbon compounds, and
d) fractionating the liquid hydrocarbon compounds to obtain fuel components.
A further step of recycling a portion of the liquid hydrocarbon compounds obtained from the separation or fractionation back to the hydroprocessing may also be included in the process.
The material of biological origin may be selected from any material of biological origin or the above disclosed preferred options.
In some embodiments of the invention, the feedstock is subject at least to a hydrodeoxygenation reaction in the presence of hydrogen and a hydrodeoxygenation catalyst and optionally to an isomerisation reaction in the presence of an isomerisation catalyst, for obtaining the renewable fuel component.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
15/38
If a hydrodeoxygenation step and an isomerisation step are applied, these may be done either simultaneously or in sequence. The hydrodeoxygenation reaction may be done in the presence of hydrogen gas and may be performed in the presence of a hydrodeoxygenation catalyst, such as CoMo, NiMo, NiW, CoNiMo on a support, for example an alumina support, zeolite support, or a mixed support. The hydrodeoxygenation reaction may for example be conducted at a temperature in the range from 250 to 400 °C, and at a pressure in the range from 20 to 80 barg, a WHSV (Weight Hourly Space Velocity i.e. mass flow/catalyst mass) in the range from 0.5 to 3 h-1, and a H2/01I ratio of 350-900 nl/l, using a catalyst, such as NiMo, optionally on a alumina support.
The product of the hydrodeoxygenation step may be subjected to an isomerization step in the presence of hydrogen and an isomerization catalyst. The isomerisation catalyst may be a noble metal bifunctional catalyst such as for example Pt-SAPO or Pt-ZSM-catalyst or NiW. The isomerization reaction may for example be conducted at a temperature of 250-400 °C and at a pressure of 10-60 barg. The isomerisation reaction may for example be conducted at a temperature of 250400 °C, at a pressure of between 10 and 60 barg, a WHSV of 0.5 - 3 h-1, and a H2/oil ratio of 100-800 nl/l.
The hydrodeoxygenation and hydroisomerisation steps may be done in a single step on the same catalyst bed using a single catalyst for this combined step, e.g. NiW, or a Pt catalyst, such as Pt/SAPO in mixture with a Mo catalyst on a support, e.g. NiMo on alumina.
In some embodiments of the present invention, the renewable fuel component has an iso-paraffin content of more than 70 wt-%, preferably more than 80 wt-%, more preferably more than 90 wt-%. Thus, the iso-paraffin content may be dominating in of renewable fuel.
In some embodiments of the present invention, the renewable fuel component comprises C15 to C18 paraffins in an amount of more than about 70 wt-%, preferably more than about 85 wt-%, and more preferably more than about 90 wt1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
16/38
%. By C15 and C18 paraffins are meant paraffins containing 15 carbons and 18 carbons, respectively. By C15 to C18 paraffins is meant paraffins containing either 15, 16, 17 or 18 carbons in each paraffin.
Alternatively or complementary, in some embodiments of the present invention, the renewable fuel component comprises paraffins smaller than C15 paraffins in an amount of less than about 20 wt-% of, preferably less than about 10 wt-%, more preferably less than about 7 wt-%.
Yet alternatively or complementary, in some embodiments of the present invention, the renewable fuel component comprises paraffins larger than C18 paraffins in an amount of less than about 10 wt-%, preferably less than about 5 wt%, more preferably less than about 3 wt-%.
In some embodiments of the present invention, the renewable fuel component comprises at least 95 wt-% saturated paraffinic hydrocarbons.
In some embodiments of the present invention, the renewable fuel component contains less than 5 wt-%, preferably less than 3 wt-%, more preferably less than 1 wt-%, of aromatic hydrocarbons, esters, oxygen containing hydrocarbons, and/or unsaturated hydrocarbons, such as less than 0.5 wt-% of the oxygen containing hydrocarbons.
In some embodiments of the present invention, the renewable fuel component comprises:
- 10-40 wt-% of Ce-30 linear alkanes;
- 10-40 wt-% of C8-3o cycloalkanes;
- up to 20 wt-% of C7-20 aromatic hydrocarbons, at least 90 wt-% of which are monoaromatic, and
- no more than 1 wt-% in total of oxygen-containing compounds, wherein the total amount of C8-3o alkanes in the fuel blend is 50-90 wt-%, and wherein the total amount of C8_3o alkenes, C7-20 aromatic hydrocarbons and C8_3o cycloalkenes is at least 95 wt-%.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
17/38
In some embodiments of the present invention, the feedstock of renewable fuel is selected from plant oils and/or fats, animal fats and/or oils, fish fats and/or oils, fats contained in plants bred by means of gene manipulation, recycled fats of food industry and combinations thereof.
In some embodiments of the present invention, determining the amount of the renewable fuel component is carried out online while producing the fuel blend by mixing the renewable fuel component with the fossil fuel component. By online determination of the renewable fuel component in the fuel blend during the fuel blend mixing process, a constant feedback is obtainable allowing the producers of the fuel blend to interactively adjust the content of the renewable fuel added to the fuel blend. Thereby the amount of renewable fuel, which is to be added to a fuel blend in order to obtain a pre-determined ratio between renewable fuel and fossil fuel component (often defined by industry standards), does not need to be determined with a very high accuracy prior to starting the fuel blend mixing process, as the ratio between the different components may be adjusted during the mixing process based on the results of the infrared spectral analysis. This possibility does not exist if online measurements are not an option, making the use of the near infrared spectroscopic system according to the invention highly advantageous when producing large quantities of fuel blend comprising a mixture of renewable fuel and fossil fuel components.
In some embodiments of the present invention, the fuel blend is produced at an oil refinery. At oil refineries, large quantities of fuels and fuel blends are produced. The high volumes make the use of the near infrared spectroscopic system according to the invention advantageous.
In some embodiments of the present invention, the near infrared spectroscopic system is used for adjusting the amount of the renewable fuel component to be added to the fuel blend at the oil refinery based on the amount of renewable fuel component in the fuel blend determined by the near infrared spectroscopic system. This may be done in order to meet the varying targets of fuel blend quality
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
18/38 and economy and functionality. This use may be in the form of an iterative process. By adjusting the amount of the renewable fuel component to be added to the fuel blend, the ratio between the renewable fuel component and the fossil fuel component is varied.
Another aspect of the present invention discloses the use of a near infrared spectroscopic system for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component, the system comprising 1) means for carrying out near infrared spectroscopic analysis of the fuel blend, and 2) means for determining the amount of the renewable fuel component in the fuel blend based on comparing the near infrared spectroscopic analysis results of the fuel blend to one or more values obtained from predefined near infrared spectrum calibration curves thus providing the amount of the renewable fuel component in the fuel blend, wherein the system is used for decreasing CO2 and/or particle emissions from an engine in a vehicle, wherein the engine is being fuelled by said fuel blend, wherein the system further comprises means for adjusting the engine operating parameters regulating the amount of CO2 and particle emissions to match the amount of renewable fuel component in the fuel blend.
In one aspect of the invention, an engine may be equipped with a system for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component, where the system comprises means for carrying out near infrared spectroscopic analysis of the fuel blend, and means for determining the amount of the renewable fuel component in the fuel blend based on comparing results from the near infrared spectroscopic analysis of the fuel blend to one or more values obtained from predefined near infrared spectrum calibration curves thereby providing the amount of the renewable fuel component in the fuel blend, wherein the calculated amount of renewable fuel in the fuel blend is used for optimization of the engine. The engine operation may be optimised based on the composition of the injected fuel composition. Software regulating the engine performance may be adjusted e.g. in terms of optimising power losses, injection, exhaust gas recycling, etc.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
19/38
In the second aspect of the invention is disclosed a method for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component, wherein the method comprises the steps of:
• providing a sample of the fuel blend to a device comprising a near infrared spectrometer;
• measuring one or more infrared spectra of the fuel blend using the near infrared spectrometer;
• determining the amount of renewable fuel component in the fuel blend by analysing the one or more infrared spectra of the fuel blend and comparing the analysis result to one or more predefined near infrared spectrum calibration curves linking a known amount of the renewable fuel component in a fuel blend to the one or more measured near infrared spectra in the fuel blend.
In some embodiments of the invention, the amount of renewable fuel component in the fuel blend is determined within 2 minutes or less, preferably within 1 minute or less, such as within 50 s or less. The precision of the method is about 1 % which is accurate enough for the intended use. The composition analysis time is thereby 5 greatly reduced compared to especially the conventional off-line 14C analysis used for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component. The short operation time is a vast improvement compared to the 14C detection method, which cannot be operated online and which takes days for providing the needed 10 result. Presently, the blend composition quality is monitored ex situ with a possible delay of even 24 h while using 14C isotope measuring method. Thus, the operation time of 2 minutes or less renders the near infrared spectroscopic system according to the present invention very attractive for online measurements.
Additionally, the second aspect of the invention enables the manufacturing of 15 precise quality blend products in situ or online, further enabling accurate determination of the cost for the renewable fuel blend. The amount of the
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
20/38 renewable fuel component in the fuel blend tends to drift from the desired or predetermined value during production of the fuel blend causing a too low anticipated amount or a too high actual amount of renewable fuel component in a fuel blend. This blend quality fluctuation may in both cases imply cost related 5 issues for the blender. The use of the method of the present invention enables an accurate real time determination of the amount of the renewable fuel component, reducing the production cost notably and simplifying the quality monitoring.
Further, by having exact and real time knowledge of the amount of a renewable 10 fuel component in a fuel blend, the amount of CO2 and particle emissions when using the blend in vehicle applications can be minimized by optimization of the engine performance to the known renewable fuel component in the fuel blend.
In some embodiments of the present invention, the method further comprises the step of mixing the renewable fuel component and the fossil fuel component to obtain the fuel blend prior to providing the sample of the fuel blend to the near infrared spectrometer.
In some embodiments of the present invention, an iterative method may be used in which the method further comprises the step of adjusting the amount of renewable fuel component to be mixed with the fossil fuel component in the fuel blend based on the determination of the amount of renewable fuel component in the fuel blend. The iterative process provides a robust and cost efficient method, as it allows the producers to account for drift from the desired/predetermined value during production of the fuel blend, thereby avoiding a too low anticipated amount or a too high actual amount of renewable fuel component in a fuel blend. The use of the method of the present invention instead enables an accurate real time determination of the amount of renewable fuel component in the fuel blend, thereby reducing the production cost notably.
Thus, in some embodiments of the present invention, the adjustment of renewable fuel component and the determination of the amount of renewable fuel component
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
21/38 in the fuel blend is done in an iterative process until a predefined target value is reached.
The method may further comprise the step of stopping the adjustment of the amount of renewable fuel in the fuel mixture when a desired pre-defined amount of renewable fuel in the fuel mixture is obtained. As the amount of renewable fuel can be determined within a minute or less, the mixing can be stopped at the exact correct time in the process. With exact correct time may be meant before the determined amount of renewable fuel content deviates too much from the predefined amount or when the renewable fuel content is at a pre-defined value.
The adjustment of the amount of renewable fuel component may be performed by decreasing or increasing the amount of renewable fuel component mixed with the fossil fuel component. The iterative process can thus be controlled by adjusting the amount of renewable fuel component added to the fuel blend. Alternatively, the method may be set up to adjust the amount of fossil fuel added to the fuel blend.
The fuel blend may be obtained and/or mixed in an oil fuel refinery.
The one or more near infrared calibration curves may be obtained by 1) obtaining a multiple of infrared spectra of fuel blends comprising a known amount of the renewable fuel component in the fuel blend, 2) calculating derivative spectra curves of the multiple of infrared spectra, 3) obtaining a derivative value from each of the derivative spectra curves at a first wavelength, and 4) relating each of the derivative values to the known amount of the renewable fuel component in the fuel blend.
Description of the Drawings
The invention is here described in the following figures and examples, wherein:
Figure 1 shows an overview of the different groups of hydrocarbons normally present in fuel components.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
22/38
Figure 2 shows NIR spectra of fuel blends with known amounts of renewable fuel components.
Figure 3 shows derivative of the NIR spectra of fuel blends with known amounts of 5 renewable fuel components of figure 2.
Vegetable oils have extremely varying origins like rapeseed, palm oil, soya, soybean oil and other vegetables, which may all be used as possible raw materials for the production of renewable fuel components. By renewable fuel component is therefore normally meant fuel component produced from renewable resources such as vegetable oil or fats and/or animal fats. Other examples include waste fats and residues from the food industry, biogas, algae oil, jatropha oil, and/or microbial oil. Examples of possible waste fats from the food industry include cooking oil, animal fat, and/or fish fat.
The applicant has disclosed production of renewable fuels based on vegetable oil or animal fat refining processes in several patent documents, e.g. FI100248, EP1396531, EP1741768 and EP1741767. Examples of suitable biomaterials are any kind of fats, and any kind of waxes such as e.g.:
• any kind of plant fats, plant oils, and plant waxes;
• any kind of animal fats, animal oils, animal waxes, animal-based fats, fish fats, fish oils, and fish waxes;
• fatty acids or free fatty acids obtained from plant fats, plant oils, plant waxes; animal fats, animal oils, animal waxes; fish fats, fish oils, fish waxes, and mixtures thereof by hydrolysis, transesterification or pyrolysis;
• fats contained in milk;
• metal salts of fatty acids obtained from plant fats, plant oils, plant waxes; animal fats, animal waxes; fish fats, fish oils, fish waxes, and mixtures thereof by saponification;
• anhydrides of fatty acids from plant fats, plant oils, plant waxes; animal fats, animal waxes; fish fats, fish oils, fish waxes, and mixtures thereof;
• esters obtained by esterification of free fatty acids of plant, animal and fish origin with alcohols;
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
23/38 • fatty alcohols or aldehydes obtained as reduction products of fatty acids from plant fats, plant oils, plant waxes; animal fats, animal waxes; fish fats, fish oils, fish waxes, and mixtures thereof;
• recycled fats of the food industry;
• fats contained in plants bred by means of gene manipulation or genetic engineering;
• dicarboxylic acids or polyols including diols, hydroxyketones, hydroxyaldehydes, hydroxycarboxylic acids, and corresponding di- or multifunctional sulphur compounds, corresponding di- or multifunctional nitrogen compounds, and • compounds derived from algae, molds, yeasts, fungi and/or other microorganisms capable of producing compounds mentioned above or compounds similar to those.
Examples of fish oils include Baltic herring oil, salmon oil, herring oil, tuna oil, anchovy oil, sardine oil, and mackerel oil.
Examples of plant oils and/or wood-based oils include rapeseed oil, colza oil, canola oil, tall oil, crude tall oil, sunflower seed oil, soybean oil, corn oil, hemp oil, hempseed oil, olive oil, linen seed oil, cotton seed oil, mustard oil, palm oil, peanut oil, castor oil, Jatropha seed oil, Pongamia pinnata seed oil, palm kernel oil, and, coconut oil.
Examples of animal fats include lard, tallow, rendered lard and rendered tallow.
Examples of animal waxes include bee wax, Chinese wax (insect wax), shellac wax, and lanoline (woll wax).
Examples of plant waxes include carnauba palm wax, Ouricouri palm wax, jojoba seed oil, candelilla wax, esparto wax, Japan wax, rice bran oil, terpenes, terpineols and triglycerides or mixtures thereof.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
24/38
Future methods may also make it possible to increase the diversity of renewable fuels using biomass and grease of animal origin, for example.
The diversity of the sources and the production methods entails significant 5 differences in the chemical structures such as the number of carbon atoms composing the hydrocarbon chains on the one hand, and the ester chemical group on the other hand. These significant chemical specificities entail significant differences as regards the emissions of nitrogen oxide and particles upon their combustion.
The amount of renewable fuel component in the fuel blend will naturally vary from 1 to 100 wt-%. The variation may depend on a number of factors including the country in which the fuel blend is to be sold, the time of year and naturally, the composition and properties of the renewable fuel components.
Renewable fuel components typically comprise iso-paraffins and n-paraffins and only a minor amount of other compounds. In the renewable fuel component, the amount of iso-paraffins is typically more than about 50 wt-%, more than about 60 wt-%, more than about 70 wt-%, more than about 80 wt-%, or more than about 90 wt-%. The saturated paraffin content is thus most often the dominating one. In some examples, less than 5 wt-% of the renewable fuel component contains aromatic hydrocarbons, esters, oxygen containing hydrocarbons, and/or unsaturated hydrocarbons. Thus, the renewable fuel component preferably contains less than 3 wt-%, more preferably less than 1 wt-%, of aromatic hydrocarbons, esters, oxygen containing hydrocarbons, and/or unsaturated hydrocarbons, such as less than 0.5 wt-% of the oxygen containing hydrocarbons and esters.
Traditionally, hydrocarbons present in fuel components can be classified in different groups including aromatic (ARO), linear (LIN), isomerised (ISO), naphthenic (NAPH), and olefinic (OLE) hydrocarbons. Further, fatty acid methyl 15 ester (FAME) type components may also be present in fuel components. The FAME type components are, however, normally not observed in renewable fuels,
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
25/38 as renewable fuels are essentially oxygen free due to the manufacturing method i.e. hydrodeoxygenation (and isomerisation) processing.
Figure 1 illustrates different groups of hydrocarbons normally present in fuel 5 components and which can be classified in different groups including aromatic 10, linear 12, naphthenic 14, isomerised 16, and olefinic 18 hydrocarbons. Further, fatty acid methyl ester 20 type components may also be present in fuel components.
When the renewable fuel component is produced from feed, comprising plant oils or fats, or animal oils or fats, or fish oils or fats, the resulting renewable fuel component may often have an iso-paraffin content of more than 70 wt-%. In some examples, the iso-paraffin content may constitute more than 80 wt-% or even more than 90 wt-% of the renewable fuel component. This makes the iso-paraffin content in the renewable fuel the dominating type of component.
Often, the renewable fuel component comprises C15 to C18 paraffins as the dominant paraffin type. The paraffins smaller than C15 paraffins and the paraffins larger than C18 paraffins will normally be present in an amount of less than about 20 wt-% and 10 wt-%, respectively.
The renewable fuel component may be produced by means of a hydrotreatment process. Hydrotreatment involves various reactions where molecular hydrogen reacts with other components, or the components undergo molecular conversions in the presence of molecular hydrogen and a solid catalyst. The reactions include, but are not limited to, hydrogenation, hydrodeoxygenation, hydrodesulfurization, hydrodenitrification, hydrodemetallization, hydrocracking, and isomerization. The renewable fuel component may have different distillation ranges which provide the desired properties to the component, depending on the intended use.
When choosing an analysis method for determining the amount of a renewable 20 fuel component in a fuel blend, spectroscopic analysis in the near infrared region has proven to be a promising method. By the term near infrared (NIR) is meant
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
26/38 light in the wavelength range between 700-3000 nm, preferably in the wavelength range from 700-2500 nm.
In the longer mid infrared (MIR) wavelength range between 3.000-10.000 nm, the fundamental strong vibrational absorption bands are normally observed. However, in this spectral range the liquid may absorb so strongly that the absorption length needs to be much less than 1 mm in order to get any light through the sample. Additionally, the detection instrumentation is normally expensive and difficult to use due to the requirement of cooled detectors etc. Thus, the NIR spectral region 10 is favoured compared to the MIR spectral range, since instrumentation is more affordable and robust and the absorption path length can be on the order of millimetres or even more without observation of signal saturation.
The NIR spectral range can be divided into a number of different sub-ranges all 15 being regions where specific molecular vibrations may be observed. When choosing an adequate operational spectral range, the sensitivity of the obtainable signal always needs to be balanced with the obtainable selectivity, i.e. how well one can spectrally separate the different absorption bands originating from different substances and/or hydrocarbons in the solution.
In the spectral NIR region from approximately 1950-3000 nm bordering to the MIR spectral region, absorption signals origination from the combinations of e.g. a stretch and a bending mode, are normally observed. An additional combinational spectral region is observable around 1200-1700 nm. The combinations observable 25 in the spectral range from 1200-1700 nm are normally combinations of three vibrations.
Overtone regions originating from the strong fundamental vibrations observed at higher IR wavelength ranges are normally observed in the NIR spectral region. 30 The 1st, 2nd and 3rd overtone regions are normally observable in the spectral ranges from approximately 1500-2150 nm, 1325-1650 nm, and 825-1100 nm, respectively. The combination region from 1200-1700 nm may thus overlap with the overtone regions.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
27/38
Depending on the chemical structure of a specific hydrocarbon compound, the NIR spectrum observed will vary, as small differences in the hydrocarbon structure often result in differences in the NIR spectrum.
Using an adequate chemometric model employing NIR data, hydrocarbons and fatty acid components or the combinations thereof can be identified and quantified. Overall, the NIR spectra of renewable fuel has been found to differ from the NIR spectra of fossil fuel in such a way which allows the determination of the 10 composition of fuel blends by utilizing knowledge obtained from NIR spectra of known amounts of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component. In this manor, the specific origin of spectral absorbance peaks is not in itself a known requirement as the difference in spectral signatures may be used for determining the ratio of the fuel 15 blend mixture.
Different NIR spectral ranges may be used for identifying spectral differences allowing for determination of the renewable fuel component in a fuel blend also comprising fossil fuel.
An example of a narrow spectral range includes the near infrared wavelength range from 800 nm to 900 nm. In this spectral range where the 3rd overtones are normally found, near infrared signals are often weak. However, the different absorption features may possibly be better spectrally separated from each other in 25 this spectral wavelength range although the signal is weak. More easily spectrally separable features may provide an improved accuracy and performance of the measurements. Silicon based detector technology may be used at these short NIR wavelengths, which lowers the costs due to the low price of silicon based detectors.
Alternatively, the spectral wavelength range from 1000 nm to 1600 nm, such as from 1100-1300 nm, or from 1150-1250, nm may be used for determining the amount of renewable fuel in a fuel blend also comprising fossil fuel components. In
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
28/38 this spectral range, where the 2nd overtone bands are observable, absorption signals are normally stronger, which increases the sensitivity of the measurements. The detectors suitable for measuring NIR spectra in the spectral wavelength range from 1000-1600 nm are however normally slightly more expensive compared to e.g. silicon based detectors.
Yet alternatively, the spectral wavelength range from 1600 nm to 1800 nm, or even more narrow from 1700 nm to 1775 nm, also provides NIR spectra, where signals from renewable fuel components may be separable from those from fossil fuel components. Thus, which spectral range within the NIR spectral range to use may vary depending on the requirements to cost, sensitivity and selectivity in the spectral data.
Figure 2 shows infrared spectra of fuel blends measured in the spectral range from 1550-1950 nm, where the composition of the different mixtures of renewable fuel and fossil fuel components are known for each blend. As seen in figure 2, the 5 absorbance signals at approximately 1665 nm, 1740 nm, and 1880 nm (indicated with arrows) increases as the amount of renewable fuel decreases, whereas an opposite trend is seen at approximately 1820 nm.
When analysing the infrared spectra as the ones e.g. shown in figure 2, 10 chemometric models employing the NIR data may be utilized. From the NIR spectra as exemplified in figure 2, one or more calibration curves may be obtained e.g. relating the known amounts of the renewable fuel component to an absorption value at one or more wavelength. The calibration curves may subsequently be used when comparing infrared spectra of fuel blends with unknown amounts of the 15 renewable fuel component for determining the amount of the renewable fuel component in the fuel blend with the unknown amount of renewable fuel component on basis of the calibration curve(s).
When looking at figure 2, the absorption value around 1740 nm may be applied for 20 creating a calibration curve plotting the absorption value as a function of the known wt-% of renewable fuel component in the fuel blend.
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
29/38
When measuring NIR spectra on different days, a difference in offset in the data may be observable even when measuring the same sample. This difference is normally a result of NIR sensor drifts and day-to-day variations. For a reliable 5 determination of the amount of renewable fuel in a fuel blend, a new calibration curve often needs to be determined before starting to analyse the amount of renewable fuel in a fuel blend with an unknown amount of renewable fuel component.
Alternatively, background subtraction from the measured NIR spectra may be performed before identifying a usable value of the absorption at a pre-determined wavelength.
As an alternative to subtracting background signals from the measured NIR absorption spectra, means for analysing the one or more infrared spectra may obtain the derivative spectrum of the one or more infrared spectra. By determining the derivative spectra of the measured infrared spectra, background variation observed between measurements performed on different days/different times during the day may be vastly reduced, if not completely avoided. A more robust system is thereby obtained.
Figure 3 shows the first derivative of the infrared spectra shown in figure 2. From figure 3, the spectral difference when varying the content of renewable fuel and fossil fuel is detectable at different wavelengths compared to the absorbance spectra shown in figure 2. The advantage of comparing the first derivative of the spectra instead of the raw spectra is that equipment-induced background 20 variations are not observable. Calibration curves can therefore be obtained directly from the first derivative spectra without correcting for background signals in the original spectra first. One way of obtaining background free calibration curves is to first calculate derivative spectra curves of a multiple of infrared spectra of fuel blends comprising a known amount of the renewable fuel component in the fuel 25 blend. An example of such derivative spectra is shown in figure 3. After obtaining the derivative spectra, a derivative value from each of the derivative spectra
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
30/38 curves at a first wavelength is obtained. In figure 3, a suitable wavelength choice for a calibration wavelength could be e.g. somewhere between 1705-1710 nm, around 1730 nm or around 1755 nm, where a large change in the derivative absorption value is observed depending on the amount of renewable fuel in the 5 fuel blend. The derivative values at the chosen wavelength are afterwards matched to the known amount of the renewable fuel component in the fuel blend.
It has surprisingly been shown that very reliable calibration curves focusing on the value of the derivative spectra at a favourably chosen wavelength are sufficient to 10 obtain a very reliable calibration curve allowing for determination of the amount of renewable fuel in a fuel blend. By obtaining the derivative spectra instead of the directly measured infrared spectra, the background signals are greatly diminished.
The other spectral regions/sub-regions in the NIR spectrum may also be used for 15 analysing and determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component in a similar manner as exemplified with the examples shown in figures 2 and 3.
The NIR calibration curve may be comprised in the system. Thus, the system may 20 be setup to include a multiple of calibration curves representing fuel blends with known amounts of renewable fuel components.
Each of the measured calibration curves may be a representative of a known type of renewable fuel and its spectral characteristic in a fuel blend comprising known 25 amounts of this known type of renewable fuel. The renewable fuel component may change as a function of the season of the year and the source of the renewable fuel, resulting in that the NIR absorption spectra of the fuel blend may change over the year. Regular measurements of calibration curves based on known blend mixtures may thus be required.
The amount of renewable fuel in the fuel blend is normally determined within 1-2 minutes or less. The operation time of 1-2 minutes or less makes the system and the method very suitable for online measurements, e.g. at an oil refinery. The short
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
31/38 time for obtaining reliable information on the amount of renewable fuel component in the fuel blend is a vast improvement compared to the 14C detection method, which is not online and which takes a day or more before providing a result.
Determining the amount of the renewable fuel component may be carried out online while producing the fuel blend, i.e. during the process of mixing a renewable fuel component and a fossil fuel component. By online determination of the renewable fuel component in the fuel blend during the fuel blend mixing process, a constant feedback is obtainable allowing the producers of the fuel blend to interactively adjust the content of the renewable fuel added to the fuel blend. Thereby the amount of renewable fuel, which is to be added to a fuel blend in order to obtain a pre-determined ratio between renewable fuel and fossil fuel component (often defined by industry standards), does not need to be determined with a very high accuracy prior to starting the fuel blend mixing process, as the ratio between the different component may be adjusted during the mixing process based on the results of the infrared spectral analysis. This possibility does not exist if online measurements are not an option, making the use of the system according to the invention highly advantageous when producing large quantities of fuel blend comprising a mixture of renewable fuel and fossil fuel components.
The fuel blend may be produced at an oil refinery. After the amount of renewable fuel has been determined in a fuel blend with an unknown amount of renewable fuel using the method described herein, the amount of renewable fuel may subsequently be regulated on site in the refinery. At oil refineries, large quantities of fuel blends are normally produced making the use of the system according to the invention highly advantageous, as the amount of renewable fuel component mixed with the fossil fuel component during the production process may be adjusted up and down at least once a minute based on the measurement of the exact renewable fuel component online. The iterative process provides a robust and cost efficient method, as it allows the producers to account for drift from the desired/predetermined value during production of the fuel blend, thereby avoiding a too low anticipated amount or a too high actual amount of renewable fuel component in a fuel blend. The use of the method of the present invention instead
1-16027 / P-17017 / P81700724EP00
20176201 prh 29 -12- 2017
32/38 enables an accurate real time determination of the renewable fuel component in the fuel blend, thereby reducing the production cost notably.
The process of regulating the amount of renewable fuel added to a fuel blend in a refinery may thus advantageously be performed iteratively by determining the amount of renewable fuel in the fuel blend, regulating the amount of renewable fuel added to the fuel mixture, measuring the amount of renewable fuel component in the fuel blend as so forth iteratively until a desired pre-defined amount of renewable fuel component in the fuel blend is obtained.
Stopping the adjustment of the amount of renewable fuel in the fuel mixture when a desired pre-defined amount of renewable fuel in the fuel mixture is obtained is also possible based on the online measurements and the updates of the result online. As the amount of renewable fuel can be determined within a minute or less, the mixing can be stopped at the exact correct time in the process, where the predetermined amount of renewable fuel component in the fuel blend is obtained.
Examples
Example 1 samples of fuel blends all with known amounts of summer grade renewable fuel and summer grade fossil fuel were provided and the near infrared spectra of the samples were measured in the NIR spectral range from 1550 to 1950 nm. The fuel blends varied in composition, with mixtures from one fuel blend having no renewable fuel component to another fuel blend comprising only renewable fuel components. Six samples were chosen for obtaining a calibration curve. Before calculating the calibration curve, the measured NIR spectra were corrected for offset variation by calculating the derivative of the NIR spectra. A representative wavelength was chosen and the absorbance value of the obtained derivative spectrum was plotted as a function of the known content of the renewable fuel component in the fuel blend. A calibration curve line was obtained from the plots.
Derivative spectra were obtained from the NIR spectra of the remaining six samples. A wavelength was chosen and the absorbance value of the obtained
1-16027 / P-17017 / P81700724EP00
33/38 derivative spectrum at this chosen wavelength was obtained. By comparing the absorbance values from the remaining six samples with the calibration curve, values representing the estimated content of renewable fuel component in the fuel blend in the six remaining samples were obtained. By comparing the obtained estimated values for the renewable fuel component with the known values of the same in the six samples, it could be determined that the precision of the method when using only six samples as basis for obtaining the calibration curve, was more than 2%. Using a larger set, such as double amount, for obtaining the calibration curve improves this accuracy to about 1%.
Claims (24)
- Claims1. Use of a near infrared spectroscopic system for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component, the near infrared spectroscopic system comprising:• means for carrying out near infrared spectroscopic analysis of the fuel blend, and • means for determining the amount of the renewable fuel component in the fuel blend based on comparing results from the near infrared spectroscopic analysis of the fuel blend to one or more values obtained from predefined near infrared spectrum calibration curves thereby providing the amount of the renewable fuel component in the fuel blend.
- 2. Use according to claim 1, wherein the means for carrying out near infrared spectroscopic analysis comprises means for measuring one or more near infrared spectra of the fuel blend, and means for analysing the measured one or more near infrared spectra.
- 3. Use according to claim 2, wherein the means for analysing the measured one or more near infrared spectra further comprises means for obtaining derivative spectra of the one or more measured near infrared spectra.
- 4. Use according to any one of the claims 1-3, wherein the one or more predefined near infrared spectrum calibration curves are comprised in the near infrared spectroscopic system.
- 5. Use according to any one of the claims 1-4, wherein the amount of the renewable fuel component in the fuel blend is determined within 2 minutes or less, preferably within 1 minute or less, such as within 50 s or less.
- 6. Use according to any one of the claims 1-5, wherein the one or more predefined near infrared spectrum calibration curves are obtained by:1-16027 / P-17017 / P81700724EP0020176201 prh 29 -12- 201735/38 • forming fuel blends comprising different known amounts of the renewable fuel component in the fuel blends;• recording multiple near infrared spectra of the fuel blends;• forming derivative spectra from the obtained multiple near infrared spectra; and • obtaining absorbance values from each of the derivative spectra at a first wavelength, and • relating each of the absorbance values to the known amounts of the renewable fuel component in the fuel blends.
- 7. Use according to any one of the claims 1-6, wherein the amount of renewable fuel component in the fuel blend is from 1 to 100 wt-%, preferably from 20 to 80 wt-%, more preferably from 30 to 60 wt-%.
- 8. Use according to any one of the claims 1-7, wherein a feedstock for the renewable fuel component originates from plant oils or fats, animal oils or fats, or fish oils or fats.
- 9. Use according to any one of the claim 8, wherein the feedstock is subject at least to a hydrodeoxygenation reaction in the presence of hydrogen and a hydrodeoxygenation catalyst and optionally to an isomerisation reaction in the presence of an isomerisation catalyst, for obtaining the renewable fuel component.
- 10. Use according to any one of the claims 1-9, wherein the renewable fuel component has an iso-paraffin content of more than 70 wt-%, preferably more than 80 wt-%, more preferably more than 90 wt-%.
- 11. Use according to any one of the claims 1-10, wherein the renewable fuel component comprises:• C15 to C18 paraffins in an amount of more than about 70 wt-%, preferably more than about 85 wt-%, and more preferably more than about 90 wt-%, and/or1-16027 / P-17017 / P81700724EP0020176201 prh 29 -12- 201736/38 • paraffins smaller than C15 paraffins in an amount of less than about 20 wt-% of, preferably less than about 10 wt-%, more preferably less than about 7 wt-%, and/or • paraffins larger than C18 paraffins in an amount of less than about 10 wt-%, preferably less than about 5 wt-%, more preferably less than about 3 wt-%.
- 12. Use according to any one of the claims 1-11, wherein the renewable fuel component comprises at least 95 wt-% saturated paraffinic hydrocarbons.
- 13. Use according to any of the claims 1-12, wherein the renewable fuel component contains less than 5 wt-%, preferably less than 3 wt-%, more preferably less than 1 wt-%, of aromatic hydrocarbons, esters, oxygen containing hydrocarbons, and/or unsaturated hydrocarbons, such as less than 0.5 wt-% of the oxygen containing hydrocarbons.
- 14. Use according to any of the claims 1-13, wherein the renewable fuel component comprises:o 10-40 wt-% of C8-3o linear alkanes;o 10-40 wt-% of C8_3Q cycloalkanes;o up to 20 wt-% of C7-20 aromatic hydrocarbons, at least 90 wt-% of which are monoaromatic, and0 no more than 1 wt-% in total of oxygen-containing compounds, wherein the total amount of C8.3o alkanes in the fuel blend is 50-90 wt-%, and wherein the total amount of C8_3o alkenes, C7-20 aromatic hydrocarbons and C8. 30 cycloalkenes is at least 95 wt-%.
- 15. Use according to any one of the claims 8-14, wherein the feedstock of renewable fuel is selected from plant oils and/or fats, animal fats and/or oils, fish fats and/or oils, fats contained in plants bred by means of gene manipulation, recycled fats of food industry and combinations thereof.1-16027 / P-17017 / P81700724EP0020176201 prh 29 -12- 201737/38
- 16. Use according to any one of the claims 1-15, wherein determining the amount of the renewable fuel component is carried out online while producing the fuel blend by mixing the renewable fuel component with the fossil fuel component.
- 17. Use according to any one of the claims 1-15, wherein the fuel blend is produced at an oil refinery.
- 18. Use according to claim 17, further comprising adjusting the amount of the renewable fuel component to be added to the fuel blend at the oil refinery based on the amount of renewable fuel component in the fuel blend determined by the near infrared spectroscopic system.
- 19. Use of a near infrared spectroscopic system for decreasing CO2 and/or particle emissions from an engine in a vehicle based on determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component, the near infrared spectroscopic system comprising:• means for carrying out near infrared spectroscopic analysis of the fuel blend, and • means for determining the amount of the renewable fuel component in the fuel blend based on comparing the near infrared spectroscopic analysis results of the fuel blend to one or more values obtained from predefined near infrared spectrum calibration curves thus providing the amount of the renewable fuel component in the fuel blend;wherein the engine is being fuelled by said fuel blend, wherein the system further comprises means for adjusting the engine operating parameters regulating the amount of CO2 and particle emissions to match the amount of renewable fuel component in the fuel blend.
- 20. Method for determining the amount of a renewable fuel component in a fuel blend comprising said renewable fuel component and a fossil fuel component, wherein the method comprises the steps of:1-16027 / P-17017 / P81700724EP0020176201 prh 29 -12- 201738/38 • providing a sample of the fuel blend to a device comprising a near infrared spectrometer;• measuring one or more infrared spectra of the fuel blend using the near infrared spectrometer;• determining the amount of renewable fuel component in the fuel blend by analysing the one or more infrared spectra of the fuel blend and comparing the analysis result to one or more predefined near infrared spectrum calibration curves linking a known amount of the renewable fuel component in a fuel blend to the one or more measured near infrared spectra of the fuel blend.
- 21. Method according to claim 20, wherein the amount of renewable fuel component in the fuel blend is determined within 2 minutes or less, preferably within 1 minute or less, such as within 50 s or less.
- 22. Method according to claim 20 or 21, further comprises the step of mixing the renewable fuel component and the fossil fuel component to obtain the fuel blend prior to providing the sample of the fuel blend to the near infrared spectrometer.
- 23. Method according to claim 22, further comprising the step of adjusting the amount of renewable fuel component to be mixed with the fossil fuel component in the fuel blend according to claim 22 based on the result of the determination of the amount of renewable fuel component in the fuel blend according to claims 20.
- 24. Method according to claim 23, wherein the adjustment of renewable fuel component and the determination of the amount of renewable fuel component in the fuel blend is done in an iterative process until a predefined target value is reached.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| FI20176201A FI20176201A1 (en) | 2017-12-29 | 2017-12-29 | Method for determining the amount of renewable fuel in a fuel blend |
| PCT/EP2018/097089 WO2019129858A1 (en) | 2017-12-29 | 2018-12-28 | Method for determining the amount of renewable fuel in a fuel blend |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| FI20176201A FI20176201A1 (en) | 2017-12-29 | 2017-12-29 | Method for determining the amount of renewable fuel in a fuel blend |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| FI20176201A1 true FI20176201A1 (en) | 2019-06-30 |
Family
ID=65009746
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| FI20176201A FI20176201A1 (en) | 2017-12-29 | 2017-12-29 | Method for determining the amount of renewable fuel in a fuel blend |
Country Status (2)
| Country | Link |
|---|---|
| FI (1) | FI20176201A1 (en) |
| WO (1) | WO2019129858A1 (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102019125083A1 (en) | 2019-09-18 | 2021-03-18 | Volkswagen Aktiengesellschaft | Method for sensing a fuel composition to limit the usability of a vehicle in the event of incorrect fueling |
| DE22787208T1 (en) | 2021-04-15 | 2024-03-21 | lOGEN Corporation | Process and system for producing renewable hydrogen with low carbon intensity |
| EP4326671A1 (en) | 2021-04-22 | 2024-02-28 | Iogen Corporation | Process and system for producing fuel |
| US11807530B2 (en) | 2022-04-11 | 2023-11-07 | Iogen Corporation | Method for making low carbon intensity hydrogen |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2439577C (en) | 2002-09-06 | 2011-05-31 | Fortum Oyj | Process for producing a hydrocarbon component of biological origin |
| FR2883602B1 (en) | 2005-03-22 | 2010-04-16 | Alain Lunati | METHOD FOR OPTIMIZING THE OPERATING PARAMETERS OF A COMBUSTION ENGINE |
| US7404411B2 (en) * | 2005-03-23 | 2008-07-29 | Marathon Ashland Petroleum Llc | Method and apparatus for analysis of relative levels of biodiesel in fuels by near-infrared spectroscopy |
| EP1741768B2 (en) | 2005-07-04 | 2023-04-05 | Neste Oyj | Process for the manufacture of diesel range hydrocarbons |
| DK1741767T3 (en) | 2005-07-04 | 2015-10-26 | Neste Oil Oyj | A process for the preparation of dieselcarbonhydrider |
| US20080246955A1 (en) * | 2007-04-09 | 2008-10-09 | Nippon Soken, Inc. | Method of detecting alcohol concentration and alcohol concentration detecting apparatus |
| FR2916019B1 (en) | 2007-05-07 | 2014-06-27 | Sp3H | METHOD FOR ADJUSTING THE PARAMETERS OF INJECTION, COMBUSTION AND / OR POST-PROCESSING OF A SELF-IGNITION INTERNAL COMBUSTION ENGINE. |
| DE102007025585A1 (en) * | 2007-06-01 | 2008-12-04 | Siemens Ag | Method for operation of combustion engine with fuels of different composition, involves illuminating part of fuel with light, where fuel is supplied in operation of combustion engine |
| FR2920475B1 (en) | 2007-08-31 | 2013-07-05 | Sp3H | DEVICE FOR CENTRALIZED MANAGEMENT OF MEASUREMENTS AND INFORMATION RELATING TO LIQUID AND GASEOUS FLOWS NECESSARY FOR THE OPERATION OF A THERMAL ENGINE |
| FR2930598B1 (en) | 2008-04-24 | 2012-01-27 | Sp3H | METHOD FOR OPTIMIZING THE OPERATION OF A THERMAL ENGINE BY DETERMINING THE PROPORTION OF OXYGEN COMPOUNDS IN THE FUEL |
-
2017
- 2017-12-29 FI FI20176201A patent/FI20176201A1/en not_active Application Discontinuation
-
2018
- 2018-12-28 WO PCT/EP2018/097089 patent/WO2019129858A1/en active Application Filing
Also Published As
| Publication number | Publication date |
|---|---|
| WO2019129858A1 (en) | 2019-07-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Shameer et al. | Exploration and enhancement on fuel stability of biodiesel: A step forward in the track of global commercialization | |
| Sakthivel et al. | Prediction of performance and emission characteristics of diesel engine fuelled with waste biomass pyrolysis oil using response surface methodology | |
| Kraiem et al. | Production and characterization of bio-oil from the pyrolysis of waste frying oil | |
| Pradhan et al. | Mahua seed pyrolysis oil blends as an alternative fuel for light-duty diesel engines | |
| Mofijur et al. | Comparative evaluation of performance and emission characteristics of Moringa oleifera and Palm oil based biodiesel in a diesel engine | |
| WO2019129858A1 (en) | Method for determining the amount of renewable fuel in a fuel blend | |
| Patel et al. | Study of Jatropha curcas shell bio-oil-diesel blend in VCR CI engine using RSM | |
| US9822321B2 (en) | Gasoline compositions and method of producing the same | |
| Velmurugan et al. | Experimental investigations on combustion, performance and emission characteristics of thermal cracked cashew nut shell liquid (TC-CNSL)–diesel blends in a diesel engine | |
| Kolakoti et al. | Elemental, thermal and physicochemical investigation of novel biodiesel from wodyetia bifurcata and its properties optimization using artificial neural network (ANN) | |
| Thangaraj et al. | Homogeneous catalytic transesterification of renewable Azadirachta indica (Neem) oil and its derivatives to biodiesel fuel via acid/alkaline esterification processes | |
| Paramasivam et al. | Characterization of pyrolysis bio-oil derived from intermediate pyrolysis of Aegle marmelos de-oiled cake: study on performance and emission characteristics of CI engine fueled with Aegle marmelos pyrolysis oil-blends | |
| Gutiérrez-Antonio et al. | Production Processes of Renewable Aviation Fuel: Present Technologies and Future Trends | |
| Borugadda et al. | Influence of waste cooking oil methyl ester biodiesel blends on the performance and emissions of a diesel engine | |
| Kaisan et al. | Physico-chemical properties of bio-diesel from wild grape seeds oil and petro-diesel blends | |
| Koul et al. | A review on the production and physicochemical properties of renewable diesel and its comparison with biodiesel | |
| Rodríguez et al. | Thermal behavior of Jatropha curcas oils and their derived fatty acid ethyl esters as potential feedstocks for energy production in Cuba | |
| Pattanaik et al. | Experimental studies on production of deoxygenated vegetable oils and their performance evaluation in a compression ignition engine | |
| Mikulec et al. | Catalytic transformation of tall oil into biocomponent of diesel fuel | |
| Yilbaşi et al. | The production of methyl ester from industrial grade hemp (Cannabis sativa L.) seed oil: a perspective of Turkey—the optimization study using the Taguchi method | |
| Hemanandh et al. | Production of green diesel by hydrotreatment using jatropha oil: performance and emission analysis | |
| Ahmad et al. | Effect of butanol additive with mango seed biodiesel and diesel ternary blends on performance and emission characteristics of diesel engine | |
| Vellaiyan | Energy conversion from Bauhinia malabarica seed as novel feedstock—optimisation for higher yield rate and fuel characterisation | |
| Muthukumaran et al. | Synthesis of cracked Mahua oil using coal ash catalyst for diesel engine application | |
| Subramanian et al. | An alternative fuel to CI engine: delonix regia seed through biochemical and solar-assisted thermal cracking process |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| FD | Application lapsed |