This document summarizes the process used to generate two full engine fuel consumption maps for a Toyota 2.5L TNGA Prototype Hybrid engine as presented in Toda, T., Sakai, M., Hakariya, M., & Kato, T. (2017). “The New Inline 4 Cylinder 2.5L Gasoline Engine with Toyota New Global Architecture Concept” in 38th International Vienna Motor Symposium, Vienna. These two full ALPHA engine maps define the complete operating boundaries of the engine which are needed for ALPHA modeling including idle, WOT, minimum torque, and maximum speed.
There was no information regarding the fuel properties provided in the reference Vienna paper. The assumption was the data in the paper were based on certification fuel, and therefore map #1 was developed using default Tier 2 test fuel specifications, referred to as “MTE Gasoline”.
Map #2 is based on a Tier 3 specified fuel and incorporates an octane-based fuel consumption modification. EPA’s proposed Multi-Pollutant Emissions Standards for Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles specifies that Tier 3 E10 fuel shall be used for all criteria, GHG, and fuel economy testing. In support of the new requirement, this second full ALPHA engine map using Tier 3 fuel was estimated based on the difference in fuel octane between the test fuel and Tier 3 fuel, as described in further detail below in the Octane-Based Fuel Consumption Modification section.
SUGGESTED CITATION:
Toyota 2.5L TNGA Prototype Hybrid Engine from 2017 Vienna Paper - ALPHA Map Package. Version 2023-03. Ann Arbor MI: US EPA National Vehicle and Fuel Emissions Laboratory, National Center for Advanced Technology, 2023.
Engine Physical Characteristics
Set physical characteristics based on published information provided in Toda, T., Sakai, M., Hakariya, M., & Kato, T. (2017). “The New Inline 4 Cylinder 2.5L Gasoline Engine with Toyota New Global Architecture Concept” in 38th International Vienna Motor Symposium, Vienna.
engine.name = 'Toyota 2.5L TNGA Prototype Hybrid Engine from 2017 Vienna Paper';
engine.combustion_type = enum_engine_combustion_type.spark_ignition;
engine.displacement_L = 2.5;
engine.num_cylinders = 4;
Test Data
Import the efficiency map image data provided in Figure 40 of the reference Vienna paper. The map was digitized by loading the image into MATLAB and manually tracing the efficiency contours.
load('2017 TNGA Hybrid Image Data.mat'); image_data.name = 'Efficiency Map Image Data'; image_data.speed_rpm = efficiency(:,1); image_data.torque_Nm = efficiency(:,2) ; image_data.efficiency_pct = efficiency(:,3); image_data.fuel_prop = class_REVS_fuel('MTE_GASOLINE'); % Need assumed fuel for Efficiency Input
Additional Fueling Data
Add additional estimated points to provide appropriate trends for high load or high speed extrapolation of the test data. The maximum torque data presented in the paper efficiency map is roughly 180 Nm, while the maximum torque output presented is approximately 250 Nm. Extrapolation of the image efficiency data resulted in high load fuel consumption that is likely too efficient. These additional points represent an estimate of how efficiency would be expected to roll off at high load.
est_data.name = 'Estimated Data';
est_data.speed_rpm = [ 5500, 5500, 5500, 5500];
est_data.torque_Nm = [ 150, 0, 190, 100];
est_data.fuel_gps = [ 6.15, 1.3, 8.3, 4.2];
Include measured idle consumption test data from NVFEL’s testing of the conventional Toyota A25A-FKS engine as documented in "2018 Toyota 2.5L A25A-FKS Engine Tier 2 Fuel - Test Data Package. Version 2020-07. Ann Arbor, MI: US EPA, National Vehicle and Fuel Emissions Laboratory, National Center for Advanced Technology, 2020.”
test_data = readtable('4a- 2018 Toyota 2.5L A25A-FKS Engine Tier 2 Fuel - Test Data.xlsx','Sheet','Steady State','VariableNamesRange','A4','VariableUnitsRange','A5','DataRange','A6'); pts = test_data.Speed < 1010 & test_data.Torque < 30; idle_data.name = 'Idle Data'; idle_data.speed_rpm = test_data.Speed(pts); idle_data.torque_Nm = test_data.Torque(pts); idle_data.fuel_gps = test_data.FuelMeterFlow(pts);
Maximum Torque (WOT) Curve Data
Create the WOT curve using the max power and torque points shown in Figure 38 of the reference paper Toda, T., Sakai, M., Hakariya, M., & Kato, T. (2017). “The New Inline 4 Cylinder 2.5L Gasoline Engine with Toyota New Global Architecture Concept” in 38th International Vienna Motor Symposium, Vienna. This image was digitized by loading the image into MATLAB and manually tracing the maximum torque curve.
load('2017 TNGA Hybrid Image Data.mat');
max_torque_image_data.speed_rpm = max_trq(:,1);
max_torque_image_data.torque_Nm = max_trq(:,2);
Add points for the lower speed portion of maximum torque curve. These estimates are based on the upper bound of the efficiency map contours and the maximum torque observed when testing the Toyota A25A-FKS engine as documented in "2018 Toyota 2.5L A25A-FKS Engine Tier 2 Fuel - Test Data Package. Version 2020-07. Ann Arbor, MI: US EPA, National Vehicle and Fuel Emissions Laboratory, National Center for Advanced Technology, 2020.”
max_torque_estimated_data.speed_rpm = [1300, 1200, 800]; max_torque_estimated_data.torque_Nm = [170, 159, 100];
Minimum Torque (Zero Accelerator Pedal) Curve Data
Use test data from "2018 Toyota 2.5L A25A-FKS Engine Tier 2 Fuel - Test Data Package. Version 2020-07. Ann Arbor, MI: US EPA, National Vehicle and Fuel Emissions Laboratory, National Center for Advanced Technology, 2020.”
pts = test_data.Torque < -5;
ct_data.name = 'CT Data';
ct_data.speed_rpm = test_data.Speed(pts);
ct_data.torque_Nm = test_data.Torque(pts);
Fuel Properties for Map #1
Utilize a default Tier 2 fuel, since no information is available regarding the fuel used for this map.
engine.fuel = class_REVS_fuel('MTE_GASOLINE');
disp(engine.fuel);
class_REVS_fuel with properties:
id: 'MTE_GASOLINE'
description: 'Gasoline for MTE'
density_kgpL_15C: 0.7401
energy_density_MJpkg: 43.3088
carbon_weight_fraction: 0.8660
anti_knock_index: 93
motor_octane_number: 88.5000
alcohol_pct_vol: 0
gCO2pgal: 8887
energy_density_BTUplbm: 1.8619e+04
specific_gravity: 0.7408
Set Idle Speed
Input based on idle speed observed during benchmarking of the Toyota A25A-FKS engine as documented in "2018 Toyota 2.5L A25A-FKS Engine Tier 2 Fuel - Test Data Package. Version 2020-07. Ann Arbor, MI: US EPA, National Vehicle and Fuel Emissions Laboratory, National Center for Advanced Technology, 2020.”
engine.idle_target_speed_radps = 580 * unit_convert.rpm2radps ;
Engine Build for Simulation in ALPHA
Construct simulation input for the engine, combining all of the above inputs. Fit the fueling data onto a grid for simple interpolation and establish points that represent the maximum and minimum engine torque versus speed. Confirm the quality of fit between the input data and the resulting engine description by examining the resulting plots.
engine = REVS_build_engine(engine, {image_data, est_data, idle_data}, 'WOT', { max_torque_image_data, max_torque_estimated_data} , 'CT', ct_data, 'image','plot_bsfc', 'plot_efficiency','no_point_labels');
Idle Fuel Verification
Confirm appropriate fuel consumption near idle conditions.
REVS_check_idle_fuel(engine)
Estimated idle fuel consumption @ 580 RPM & 22.8 Nm: 0.181 g/sec => Indicated Efficiency: 32.7%
Fuel Map Linearity
Confirm expected trends in output fuel map, specifically in regions where data are unavailable.
REVS_plot_engine_fuel_linearity(engine);
Model Calibration Options
Calibrate additional properties of the REVS engine model which can be set to match observed behaviors during the validation process.
Note: Default values are used unless properties are specified below, which are derived from the composite set of EPA testing and model validation activities.
Transient Fueling Adjustments
Use the default adjustment factors during the simulation, since there is no transient fueling data available. Additional explanation regarding transient fueling adjustments are provided in Dekraker, P., Stuhldreher, M., and Kim, Y., 2017, "Characterizing Factors Influencing SI Engine Transient Fuel Consumption for Vehicle Simulation in ALPHA," SAE Int. J. Engines 10(2):529-540.
File Description
Generate and write the created ALPHA engine definition into a file for use in later simulations.
engine.write_mscript('engine_Toyota_2L5_TNGA_Proto_Hybrid_Engine_paper_image.m');
Engine Build: engine_Toyota_2L5_TNGA_Proto_Hybrid_Engine_paper_image.m
% ALPHA ENGINE DEFINITION % Generated 21-Mar-2023 13:58:45 % Constructor engine = class_REVS_engine(); engine.name = 'Toyota 2.5L TNGA Prototype Hybrid Engine from 2017 Vienna Paper'; engine.source_filename = mfilename; engine.matrix_vintage = enum_matrix_vintage.present; % Physical Description engine.displacement_L = 2.5; engine.num_cylinders = 4; engine.combustion_type = enum_engine_combustion_type.spark_ignition; % Maximum Torque Curve engine.full_throttle_speed_radps = [ 0.0000000000000000 ; 83.775804095727807 ; 125.66370614359172 ; 136.13568165555770 ; 167.55160819145561 ; 208.79508099315544 ; 332.52549929353512 ; 463.12982986715770 ; 598.03035541520774 ; 609.20046255815828 ; 639.66048568606618 ; 670.12050881397420 ]; engine.full_throttle_torque_Nm = [ 0.0000000000000000 ; 100.00000000000000 ; 159.00000000000000 ; 170.00000000000000 ; 187.84552800000000 ; 198.82113799999999 ; 219.34959300000000 ; 220.97560999999999 ; 219.55284599999999 ; 211.42276400000000 ; 181.21951200000001 ; 0.0000000000000000 ]; % Minimum Torque Curve engine.closed_throttle_speed_radps = [ 0.0000000000000000 ; 105.03391438501875 ; 373.95424553230504 ; 470.50585975263135 ; 603.18578948924028 ; 670.12050881397420 ]; engine.closed_throttle_torque_Nm = [ -15.948686146731134 ; -22.000000000000000 ; -31.699999999999999 ; -38.600000000000001 ; -50.700000000000003 ; -54.556306762306079 ]; % Fuel Map engine.fuel_map_speed_radps = [ 0.0000000000000000 52.359877559829883 78.539816339744831 104.71975511965977 130.89969389957471 157.07963267948966 183.25957145940458 209.43951023931953 235.61944901923448 261.79938779914943 287.97932657906438 314.15926535897933 340.33920413889422 366.51914291880917 418.87902047863906 471.23889803846896 523.59877559829886 575.95865315812875 628.31853071795865 680.67840827778844 ]; engine.fuel_map_torque_Nm = [ -57.284122100421385 ; -39.642061050210692 ; -22.000000000000000 ; -11.876016250000001 ; -1.7520325000000021 ; 8.3719512499999986 ; 18.495934999999996 ; 28.619918750000004 ; 38.743902499999997 ; 48.867886249999998 ; 58.991869999999992 ; 69.115853749999999 ; 79.239837500000007 ; 89.363821250000001 ; 99.487804999999994 ; 109.61178874999999 ; 119.73577250000000 ; 129.85975625000000 ; 139.98373999999998 ; 150.10772374999999 ; 160.23170750000000 ; 170.35569124999998 ; 180.47967500000001 ; 190.60365874999999 ; 200.72764250000000 ; 210.85162624999998 ; 220.97560999999999 ; 232.02439050000001 ]; engine.fuel_map_gps = [ -0.042091507425468654 -0.17535474882008983 -0.21179231276461122 -0.23105549215901164 -0.24794739469172783 -0.26239714655874735 -0.27458159173781166 -0.28486707157942887 -0.29366071682131228 -0.30129087821669676 -0.30795814405832073 -0.31374300937648225 -0.31864204476237679 -0.32261090446585072 -0.32615239537494517 -0.32157316314811019 -0.30937403881191572 -0.29058620229444315 -0.26685629101408503 -0.24107251486891099 ; -0.022232108742018988 -0.097659349845480123 -0.10690162786550036 -0.11315154693317467 -0.11496322934176968 -0.11293129599991276 -0.10816617781838796 -0.10138343123574638 -0.092834660896413221 -0.082527693731688320 -0.070408848322744563 -0.056443008444800616 -0.040631408234576817 -0.023012714211254233 0.019979852848951252 0.074406557382498920 0.13597500119599845 0.19916331994103745 0.26072882438983752 0.32017115104599375 ; -0.0055964168915317207 -0.0014623543278392034 0.0023350548589135562 0.0067253956453464173 0.021330096759712362 0.039065972626842020 0.058794124878352276 0.081047819445809466 0.10628466845924209 0.13463121387107702 0.16601933508085623 0.20031040778097198 0.23734692409724870 0.27695535702965002 0.36678507089184514 0.47082907257167828 0.58183789404401542 0.68994944593050456 0.78761733511884391 0.87970002055239327 ; 0.0028565833467982232 0.050028011966125802 0.070105150291159574 0.086606165094543011 0.10434322032614461 0.12621497161276546 0.15278993912062319 0.18383168555456958 0.21904527582313066 0.25819685620334459 0.30107057215586819 0.34743884754961957 0.39705708037089926 0.44965704512215054 0.56685470987728215 0.69899757151906006 0.83738749927102718 0.97151258705204702 1.0887014163424953 1.2001996127490446 ; 0.018448872330816546 0.092540090267535249 0.13166947282809327 0.15811467967889919 0.18189824793161877 0.21060394703474414 0.24531704627041354 0.28561472589839160 0.33101335890644956 0.38115808219573888 0.43574828454452053 0.49447336021926414 0.55698844594753294 0.62290226012358985 0.76796839745932544 0.92792329677157115 1.0924114085384218 1.2517757964108454 1.3887293928576376 1.5208980560491074 ; 0.028815462766371328 0.12086208287648485 0.16822577153522314 0.20975388699881492 0.24935983812254456 0.29067907982505448 0.33595676533693125 0.38632078555974869 0.44217065370012487 0.50348692852506094 0.57003557406159244 0.64146632770532452 0.71732928686083153 0.79705572708975814 0.97081932886059430 1.1581663591383655 1.3467448446731554 1.5273145428468580 1.6878253396836687 1.8428225608354527 ; 0.033978851630332929 0.15016982926904987 0.20449949503515574 0.25590371381695987 0.31150682498150345 0.36707127268520656 0.42437850493741164 0.48568717333547318 0.55242030318420099 0.62516991060720561 0.70396517035542838 0.78853737672226387 0.87836283802482873 0.97260322222716067 1.1762554519553556 1.3902236157270438 1.6009138763942572 1.8014470886737353 1.9872759724311053 2.1674335740113113 ; 0.033530032590706700 0.17700300480296904 0.24651068963970715 0.31028859140538917 0.37503709562426396 0.44202997158300777 0.51130685185349878 0.58405812431850590 0.66197632707942533 0.74636191777239647 0.83771414843745440 0.93597826750124813 1.0405383465200453 1.1501142476849660 1.3851694530850422 1.6243101819198151 1.8556989832609352 2.0771563209780206 2.2891857577050212 2.4966907516051218 ; 0.028272317315513516 0.19758284919206817 0.27937838450024260 0.35875720934217259 0.43739714950569880 0.51711331245640646 0.59867693874653849 0.68298173081556379 0.77186811593760851 0.86764936952618366 0.97182897359046572 1.0845365699893490 1.2046022611298064 1.3301546622055755 1.5981768053166916 1.8600332127400774 2.1116695135398240 2.3561955394987697 2.5959635423249323 2.8330672378018580 ; 0.019726527525459597 0.21427863092637597 0.30948557555346345 0.40383792164796578 0.49779272489822723 0.59221236773352903 0.68769644883836689 0.78457407993674000 0.88428574199544052 0.99042125321756036 1.1076690706155086 1.2359220736298602 1.3715930747193725 1.5133337367885253 1.8147748136979933 2.0961254181191533 2.3691518828775218 2.6399196694675258 2.9100524898451283 3.1794458280318345 ; 0.010334107835381901 0.23019876327308431 0.33912487691051074 0.44786020663685949 0.55694177767941599 0.66704080310659064 0.77820157446064930 0.89026625836553985 1.0025924000657889 1.1180567957896277 1.2484764667916470 1.3928607906240644 1.5423405501732661 1.7010397818428311 2.0315465468351932 2.3306708481029581 2.6285410995922396 2.9297070444265350 3.2338441014264516 3.5389505489366622 ; 0.0032026031291781444 0.24769138906732896 0.37002095045270267 0.49256635835103341 0.61594295038346492 0.74170413033400373 0.86841850180989322 0.99837567462728072 1.1285597210103031 1.2608824286023321 1.4025346544446180 1.5548353800062515 1.7187323665505445 1.8963597848616272 2.2392998408881049 2.5622697199495246 2.8906343360474729 3.2270924748042917 3.5696534611073756 3.9147723812143975 ; 0.0017634852054018177 0.26840925313204517 0.40349195737655358 0.53950427707120807 0.67680308730551297 0.81660067327121444 0.95727547303669525 1.1021215075529931 1.2510079091188819 1.4009256464986304 1.5506022426418506 1.7080585294953510 1.8788866662054708 2.0606185708580602 2.4323487118868390 2.7918381900849725 3.1566700947543853 3.5337626223645517 3.9197021837954025 4.3100145351911472 ; 0.0094208078977554306 0.29377466403933022 0.44022249257704532 0.58908959366824776 0.74010353663483097 0.89158785836322285 1.0429582435655325 1.1974613910680929 1.3595123019787236 1.5230597258745453 1.6831447857720405 1.8507828530854813 2.0309562554128364 2.2224565308131430 2.6244839921033827 3.0223446472373467 3.4283114704896458 3.8515448724506460 4.2861225214474254 4.7275486212351110 ; 0.029012092366072811 0.32556282332713826 0.48059379678919029 0.63944305847844995 0.80149639634876990 0.96495470024519858 1.1277072086192985 1.2925559940449978 1.4653006390752614 1.6416282052719797 1.8157699060605019 1.9959501171087506 2.1883920785074573 2.3931526068714302 2.8229610946240977 3.2577230988412254 3.7081570166035567 4.1823626440060693 4.6710375402013682 5.1698503293938467 ; 0.061999943997695608 0.36616895477505867 0.52613666614843979 0.69146913337511506 0.86254576137250583 1.0379961521284682 1.2127161210332758 1.3884333863623521 1.5712764134751818 1.7592128656401782 1.9483485940586960 2.1440429108969230 2.3518047704573153 2.5708809923443865 3.0293049288877363 3.5021893694826445 4.0001709052392025 4.5280101948738265 5.0767833197973840 5.6387752785807512 ; 0.10767215936892217 0.41898127292627801 0.58045350476934332 0.74822041083720703 0.92597440455625235 1.1124269883619693 1.2989889808116091 1.4870159123645568 1.6805084106553871 1.8785140053335627 2.0789763940455805 2.2901513528078499 2.5157783254188786 2.7523488686163304 3.2437495849212561 3.7601963766220381 4.3098929385802931 4.8929951984521560 5.5062216725561228 6.1352611845219531 ; 0.16277872263684359 0.48722967425056651 0.64929321512851490 0.81478469819885979 0.99070104194107866 1.1825009769775341 1.3838359029655511 1.5869207455263865 1.7933727227355476 2.0026312064505261 2.2144947332511804 2.4386496867112393 2.6782524556832858 2.9338503260482920 3.4656492848777218 4.0367290552775152 4.6441019452165877 5.2818844480924181 5.9627127377515565 6.6590489057923721 ; 0.22219675455018967 0.57064374622321201 0.73842878735380957 0.90303205428288991 1.0715504556792794 1.2605213710501861 1.4664962064241993 1.6807844222424437 1.9045063229004213 2.1276453890978413 2.3517698925033326 2.5889022269436817 2.8423476921421149 3.1146827759017133 3.6952997780702823 4.3375009998809695 5.0098879831840017 5.7002433854919703 6.4497526359163260 7.2084475598884010 ; 0.28085550699247286 0.66383072943343757 0.84856720864438517 1.0270608629292388 1.1984418737124694 1.3726860610639167 1.5647940378053418 1.7753984538633851 2.0111322599709149 2.2517541960726581 2.4934294793118839 2.7457823227872984 3.0141703807804938 3.3004631499828387 3.9433815491620892 4.6684879971586417 5.4126643051195407 6.1572748864926545 6.9697482668839230 7.7803621529197553 ; 0.33575694063407224 0.75978907566203124 0.96967047485645730 1.1776180122811386 1.3777238538942698 1.5507038355951865 1.7210106354619081 1.9187161584200019 2.1471798410726892 2.3950699749482895 2.6538484473866819 2.9191215159898389 3.2014363718265977 3.5042639432504350 4.2252600683918864 5.0339291408960660 5.8530089800305207 6.6698659914258229 7.5214140090060857 8.3708660034818845 ; 0.38607638402269562 0.85404091980725871 1.0882636100304839 1.3215519656681141 1.5490316693312807 1.7590252458497322 1.9425838607148136 2.1335675621392087 2.3467908907444790 2.5894895602186692 2.8486095745520208 3.1184614970973588 3.4129083564978493 3.7430088709915399 4.5554323850546057 5.4340359895278674 6.3237076763849167 7.2144109986404663 8.0969830959701738 8.9762007921559128 ; 0.43167637187353736 0.94284830380113205 1.1980030208561825 1.4514479656254571 1.7001216973872315 1.9400479387574756 2.1645913196602269 2.3855133821786048 2.6151058411612160 2.8535348811105776 3.1023024357065201 3.3709513570967680 3.6841127171204500 4.0732694844155812 4.9447634178012230 5.8631685122651920 6.8130599487842165 7.7739772160810769 8.6851682194995519 9.5927979772498304 ; 0.47234204059728047 1.0240590060100285 1.2980980482398263 1.5697467782576968 1.8364054664292671 2.0948888346946157 2.3443301080122358 2.6031926095551290 2.8819976607414528 3.1471743165575496 3.4115132144505886 3.7070991127084589 4.0637605143386137 4.4993275385804301 5.3729572216118759 6.3116054554103345 7.3092862557119345 8.3303698274544544 9.2748108600386168 10.217392730624550 ; 0.50799735702950555 1.0975812075801341 1.3899938140570427 1.6802144651537674 1.9671466498930867 2.2510867825964764 2.5359180680418358 2.8288237935390987 3.1303823741659689 3.4325959037892924 3.7436562086893210 4.0843099832007139 4.4700384871815126 4.8955748964120929 5.7995205566349952 6.7700815059597099 7.8042551285612163 8.8594234226258344 9.8586099207345494 10.847042665771662 ; 0.53915201399676738 1.1650286828123952 1.4766102686868772 1.7874653537365617 2.0982501778370217 2.4109450043872211 2.7284887310647323 3.0528254936322021 3.3846429377688896 3.7263519879465306 4.0835805205093259 4.4639188468847708 4.8707111250911481 5.2994650165841444 6.2285372808666608 7.2320153552114235 8.2956673961303249 9.3796518667782482 10.435866995209251 11.478973728076207 ; 0.56708166995021181 1.2288927268747372 1.5608123574436976 1.8940958837725836 2.2304249082868184 2.5719859948316426 2.9207439018438017 3.2780405197426585 3.6457087449202832 4.0268070664094173 4.4237631235318808 4.8373176876418293 5.2665603441622846 5.7102831602146331 6.6618840006666558 7.6944125432371804 8.7843347649016188 9.8985044074728137 11.009005041702149 12.111385527196683 ; 0.59575764758123051 1.2969795961226926 1.6518957942983621 2.0105360290712087 2.3751403838605114 2.7479122504971558 3.1308075087153764 3.5256894740047340 3.9342908163010075 4.3573576940172059 4.7936917132619072 5.2406899438468164 5.6964537338868313 6.1612764290315027 7.1380528800902656 8.1987949541971616 9.3162260587354169 10.465218854015697 11.632641397130280 12.801407855218397 ]; % Fuel Properties engine.fuel = class_REVS_fuel('MTE_GASOLINE'); % Idle Speed engine.idle_target_speed_radps = class_REVS_dynamic_lookup; engine.idle_target_speed_radps.axis_1.signal = 'eng_runtime_sec'; engine.idle_target_speed_radps.axis_1.breakpoints = [ 0.0000000000000000 10.000000000000000 ]; engine.idle_target_speed_radps.table = [ 60.737457969402662 60.737457969402662 ]; % Calibration Adjustment Factors engine.variant = 'basic engine';
Estimate the Tier 3 Fuel Map #2
The EPA typically and whenever possible, benchmarks a gasoline engine using both Tier 2 and Tier 3 test fuels in order to create Tier 2 and Tier 3 BSFC and BTE engine maps. However, occasionally an engine is only benchmarked or modeled using one fuel type (in this case, a Tier 2-like fuel). Consequently, a corresponding Tier 3 fuel map must be estimated. To do this we use an internally developed octane-based fuel consumption modifier to estimate the second map based on differences between the octane of the fuel used to test the engine (e.g., Tier 2-like fuel) and the decreased octane of the fuel which would have been used to create the second target map (e.g., Tier 3-like fuel). The reference Vienna paper does not provide any information regarding this engine having been tested using Tier 3 fuel. As a result, the internally developed octane-based fuel consumption modifier, described in more detail in the Octane-Based Fuel Consumption Modification section below, was used to develop an estimated Tier 3 fuel map.
Tier 3 Fuel Properties
Define the Tier 3 fuel characteristics using average values for a typical Tier 3 fuel. The “LMDV Tier 3 Reg” fuel described below was specified for the EPA’s proposed Multi-Pollutant Emissions Standards for Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles.
tier_3_fuel = class_REVS_fuel('LMDV_TIER_3_REG')
tier_3_fuel =
class_REVS_fuel with properties:
id: 'LMDV_TIER_3_REG'
description: 'Regular Tier 3 Cert fuel for 2027+ LMDV rule'
density_kgpL_15C: 0.7465
energy_density_MJpkg: 41.7870
carbon_weight_fraction: 0.8273
anti_knock_index: 87.7000
research_octane_number: 91.8000
motor_octane_number: 83.6000
alcohol_pct_vol: 9.6900
gCO2pgal: 8.5665e+03
energy_density_BTUplbm: 1.7965e+04
specific_gravity: 0.7472
Octane-Based Fuel Consumption Modification
To determine differences in an engine’s fuel consumption associated with changes in fuel octane, EPA first compared data from various engines tested using both Tier 2 and Tier 3 test fuels in its engine benchmarking program at its National Vehicle and Fuel Emissions Laboratory. The octane-based fuel consumption modifier was developed to closely match the observed differences noted in efficiency between the laboratory tested Tier 2 and Tier 3 engine maps.
To ascertain the modification, the “knock sensitivity” is determined for each point in the map above the minimum BSFC line (or 30% of maximum torque). This knock sensitivity is based on the ratio of the fuel consumption at each point to (a) the fuel consumption at an equivalent power along the minimum BSFC line and (b) the minimum fuel per stroke at that load. The knock sensitivity is combined with the magnitude of the octane change to determine the proportion of extra fuel required. A smoothing function is applied to ensure the map decays smoothly with increasing speed. No change in the map is made if the target fuel increases in octane over the base fuel. Application of this modification typically results in negligible decreases in efficiency across most of the map, save for those areas at low speed and near the WOT line which are more sensitive to knock conditions.
[ engine, engine_modifiers ] = REVS_modify_engine( engine,'fuel', tier_3_fuel ,'fuel_octane_adjust',true ); engine.name = 'Toyota 2.5L TNGA Prototype Hybrid Engine from 2017 Vienna Paper Octane Modified for Tier 3 Fuel'; REVS_plot_engine(engine,'BSFC','show_CTP_curve','no_min_bsfc','show_bmep') REVS_plot_engine(engine,'Efficiency','show_CTP_curve','no_min_bsfc','show_bmep')
File Description
Generate and write the estimated Tier 3 ALPHA engine definition into a file for use in later simulations.
engine.write_mscript('engine_Toyota_2L5_TNGA_Proto_Hyb_Engine_paper_image_OM_Tier_3.m');
Engine Build: engine_Toyota_2L5_TNGA_Proto_Hyb_Engine_paper_image_OM_Tier_3.m
% ALPHA ENGINE DEFINITION % Generated 21-Mar-2023 13:58:51 % Constructor engine = class_REVS_engine(); engine.name = 'Toyota 2.5L TNGA Prototype Hybrid Engine from 2017 Vienna Paper Octane Modified for Tier 3 Fuel'; engine.source_filename = mfilename; engine.matrix_vintage = enum_matrix_vintage.present; % Physical Description engine.displacement_L = 2.5; engine.num_cylinders = 4; engine.combustion_type = enum_engine_combustion_type.spark_ignition; engine.inertia_kgm2 = 0.145; % Maximum Torque Curve engine.full_throttle_speed_radps = [ 0.0000000000000000 ; 83.775804095727807 ; 118.32968003379398 ; 125.66370614359172 ; 130.89969389957471 ; 136.13568165555770 ; 155.69378632099685 ; 157.07963267948966 ; 167.55160819145561 ; 179.28676069523979 ; 183.25957145940458 ; 196.53452398248217 ; 199.06269894523604 ; 201.36054608615734 ; 208.79508099315544 ; 332.52549929353512 ; 463.12982986715770 ; 598.03035541520774 ; 609.20046255815828 ; 639.66048568606618 ; 670.12050881397420 ]; engine.full_throttle_torque_Nm = [ 0.0000000000000000 ; 100.00000000000000 ; 148.66986840296687 ; 155.49378313787628 ; 158.91482195752729 ; 162.39360685934057 ; 170.67075444718628 ; 171.37012474763125 ; 176.58722352545087 ; 180.66207436623716 ; 182.79156569586559 ; 188.01903209102483 ; 193.41741977023321 ; 196.84267813404915 ; 198.82113799999999 ; 219.34959300000000 ; 220.97560999999999 ; 219.55284599999999 ; 211.42276400000000 ; 181.21951200000001 ; 0.0000000000000000 ]; % Minimum Torque Curve engine.closed_throttle_speed_radps = [ 0.0000000000000000 ; 105.03391438501875 ; 373.95424553230504 ; 470.50585975263135 ; 603.18578948924028 ; 670.12050881397420 ]; engine.closed_throttle_torque_Nm = [ -15.948686146731134 ; -22.000000000000000 ; -31.699999999999999 ; -38.600000000000001 ; -50.700000000000003 ; -54.556306762306079 ]; % Fuel Map engine.fuel_map_speed_radps = [ 0.0000000000000000 52.359877559829883 78.539816339744831 104.71975511965977 130.89969389957471 157.07963267948966 183.25957145940458 209.43951023931953 235.61944901923448 261.79938779914943 287.97932657906438 314.15926535897933 340.33920413889422 366.51914291880917 418.87902047863906 471.23889803846896 523.59877559829886 575.95865315812875 628.31853071795865 680.67840827778844 ]; engine.fuel_map_torque_Nm = [ -57.284122100421385 ; -39.642061050210692 ; -22.000000000000000 ; -11.876016250000001 ; -1.7520325000000021 ; 8.3719512499999986 ; 18.495934999999996 ; 28.619918750000004 ; 38.743902499999997 ; 48.867886249999998 ; 58.991869999999992 ; 69.115853749999999 ; 79.239837500000007 ; 89.363821250000001 ; 99.487804999999994 ; 109.61178874999999 ; 119.73577250000000 ; 129.85975625000000 ; 139.98373999999998 ; 150.10772374999999 ; 160.23170750000000 ; 170.35569124999998 ; 180.47967500000001 ; 190.60365874999999 ; 200.72764250000000 ; 210.85162624999998 ; 220.97560999999999 ; 232.02439050000001 ]; engine.fuel_map_gps = [ -0.043624377553855474 -0.18174074145323671 -0.21950527268256353 -0.23946997012840743 -0.25697703458778709 -0.27195301120545917 -0.28458118418588640 -0.29524123613883169 -0.30435512451134622 -0.31226315779094543 -0.31917322920717933 -0.32516876522319249 -0.33024621153946876 -0.33435960744169935 -0.33803007081950653 -0.33328407411402011 -0.32064068739733143 -0.30116864365763846 -0.27657454683545013 -0.24985178839509611 ; -0.023041747965371395 -0.10121586538251302 -0.11079472464567883 -0.11727225053548078 -0.11914991000254006 -0.11704397859995508 -0.11210532642629122 -0.10507556874186480 -0.096215473019120132 -0.085533151227121629 -0.072972967000583810 -0.058498525267392930 -0.042111105108521209 -0.023850781183552546 0.020707470401160617 0.077116262882348047 0.14092687938448525 0.20641636271572408 0.27022393280866236 0.33183100414768307 ; -0.0058002247569121299 -0.0015156097088737529 0.0024200918666213702 0.0069703181657524340 0.022106886904766181 0.040488660150735011 0.060935263632060553 0.083999383526030494 0.11015529708130208 0.13953415459984170 0.17206535469492457 0.20760522469947099 0.24599052068635605 0.28704139622506691 0.38014248936168493 0.48797552003971312 0.60302701227464239 0.71507572342571202 0.81630043913314176 0.91173655157551625 ; 0.0029606131511312641 0.051849910249556048 0.072658209026764856 0.089760150578256884 0.10814314613827775 0.13081141330787410 0.15835417637230051 0.19052638756628926 0.22702237098105707 0.26759975651092577 0.31203482872024141 0.36009172370980441 0.41151693165664260 0.46603245894421219 0.58749817705281271 0.72445335969898572 0.86788311137971630 1.0068927080106707 1.1283492688884951 1.2439079579001915 ; 0.019120735303374745 0.095910174845772370 0.13646455416548678 0.16387283100594296 0.18852253885667047 0.21827362956872209 0.25425089528681799 0.29601611820614548 0.34306805879723240 0.39503893071192986 0.45161717520035716 0.51248087502507833 0.57727260783366585 0.64558684249780873 0.79593593504621174 0.96171600200014906 1.1321943699593831 1.2973624204858667 1.4393035331754582 1.5762854570008875 ; 0.029864851700431856 0.12526358540817789 0.17435214418813363 0.21739261241778057 0.25844091576639583 0.30126490356158303 0.34819149204341271 0.40038964715155650 0.45827343139005100 0.52182269552356741 0.59079488055932405 0.66482696818242282 0.74345267144127214 0.82608255433938660 1.0061742030452738 1.2003439556231024 1.3957900100574989 1.5829356166115893 1.7492918255232794 1.9099336677594292 ; 0.035216278604248093 0.15563864850483217 0.21194686830313961 0.26522310346694700 0.32285114444186669 0.38043911392692048 0.43983333592677182 0.50337471662588296 0.57253810444291953 0.64793707528604050 0.72960186637952096 0.81725398640972524 0.91035067211885423 1.0080230614611123 1.2190918091194975 1.4408521720005230 1.6592152585338726 1.8670514017287370 2.0596477205894357 2.2463662229963255 ; 0.034751114668917844 0.18344902290240658 0.25548800823885293 0.32158854576760215 0.38869503272564554 0.45812762597305423 0.52992740140339434 0.60532809792528997 0.68608389175327422 0.77354260002153241 0.86822165631277926 0.97006431513478542 1.0784322174308429 1.1919986058926177 1.4356139490714992 1.6834636004926291 1.9232790181113220 2.1528012924026005 2.3725523245244209 2.5876141446371195 ; 0.029301926215835328 0.20477833507349852 0.28955266445150574 0.37182227265732687 0.45332608780533173 0.53594531915179888 0.62047929395046164 0.70785426110578664 0.79997767176831902 0.89924704520495002 1.0072206165758217 1.1240327489804074 1.2484709400062448 1.3785956535727715 1.6563785099975821 1.9277710896660876 2.1885713713329173 2.4420024392761475 2.6905022084788404 2.9362406427512409 ; 0.020444919586711387 0.22208213649291508 0.32075628603520440 0.41854471464890791 0.51592112287674829 0.61377929901455697 0.71274067766976734 0.81314635601336027 0.91648927381865597 1.0264899817197384 1.1480076789081908 1.2809313437548542 1.4215431520897877 1.5684456636661908 1.8808644900202816 2.1724611978361565 2.4554306211076700 2.7360591106560599 3.0160295100699304 3.2952334971535433 ; 0.010710450859742206 0.23858204126420204 0.35147497852018700 0.46417018397997073 0.57722424002094919 0.69133280365581695 0.80654177941687610 0.92268758602113987 1.0391043720765272 1.1587736997194880 1.2939429373220150 1.4435853863808084 1.5985088345082141 1.7629875054638386 2.1055305214311422 2.4155482008203686 2.7242661609941510 3.0363998356333561 3.3516128231030033 3.6678305039230392 ; 0.0033192341307759846 0.25671170586240322 0.38349621177069126 0.51050442479594571 0.63837409165596704 0.76871518731511312 0.90004418741214753 1.0347340837732122 1.1696591158823080 1.3068006940299768 1.4536115487476391 1.6114586955952874 1.7813244109918607 1.9654205870207242 2.3208496841831390 2.6555813392003991 2.9959041944307194 3.3446153186921839 3.6996515413356272 4.0573388514987645 ; 0.0018277070391766971 0.27818406404936047 0.41818615120180508 0.55915170813372661 0.70145060645572666 0.84633927983203838 0.99213711299705065 1.1422580871176966 1.2965665686099810 1.4519439446532216 1.6070713976837325 1.7702618588020014 1.9473111399630438 2.1356612777238215 2.5209289246262734 2.8935101335868425 3.2716283271719102 3.6624536457075392 4.0624481854764216 4.4669747615647450 ; 0.0097638907639918185 0.30447322140936839 0.45625432298630819 0.61054280112765091 0.76705630389387491 0.92405731547015491 1.0809402412297227 1.2410700168583433 1.4090224270453453 1.5785258495736330 1.7444408172441486 1.9181838544549086 2.1049187330336538 2.3033929818004113 2.7200613035372432 3.1324110741916042 3.5531622198533928 3.9918087509438336 4.4422126589025019 4.8997144215410122 ; 0.030068642070991278 0.33741902799443618 0.49809585171774345 0.66273001642077434 0.83068494195142328 1.0000959989471150 1.1687755570674954 1.3396277335413138 1.5186633175852147 1.7014123040532951 1.8818958212217098 2.0686377564783713 2.2680879851528126 2.4803053929824976 2.9257664584664278 3.3763614354133176 3.8431990588061189 4.3346740995753388 4.8411453446468729 5.3581236800736924 ; 0.064257830871526561 0.37950393579732755 0.54529728139644540 0.71665075418375579 0.89395757607920756 1.0757974425145531 1.2568802869148770 1.4389967468449474 1.6284984714382928 1.8232791112121276 2.0193027019581420 2.2221237289316034 2.4374517691259907 2.6645062131512249 3.1396248323383142 3.6297305718959731 4.1458473816624029 4.6929092919433062 5.2616673967810739 5.8441257331950833 ; 0.11159331702876069 0.46356974709061005 0.61139568026514723 0.77546877487483457 0.95969613587956926 1.1529388684244921 1.3462949940095337 1.5411694082101413 1.7417084317702827 1.9469249076903115 2.1546876480959773 2.3735530842478529 2.6073968413750030 2.8525827072611403 3.3618790401681915 3.8971335655026786 4.4668487367016398 5.0711861599264694 5.7067448478565721 6.3586924459529550 ; 0.18562769052265204 0.59378878221095266 0.71571002884867718 0.85313942822304223 1.0267799596667551 1.2255647809433745 1.4342318343063609 1.6447125319394069 1.8586829870593600 2.0755621548129461 2.2951412349732054 2.5274593655990447 2.7757878835333103 3.0406940054750877 3.5918597864536239 4.1837368904372028 4.8132288209316210 5.4742378083613072 6.1798602052314342 6.9015552396230246 ; 0.34421273747285541 0.77727625718815074 0.87502619050640829 0.98336288191996835 1.1197619696942671 1.3064264876416365 1.5199024245835440 1.7419944950267321 1.9738638021227368 2.2051290493474296 2.4374156210019171 2.6831837371989993 2.9458590686231951 3.2281119324847771 3.8298735909770394 4.4954622163172919 5.1923358950242928 5.9078323587694683 6.6846369096284652 7.4709616538813837 ; 0.54020297351481161 1.0076901317476272 1.1009585829023920 1.2106496997989411 1.3234673949640556 1.4522723005433626 1.6217800234433437 1.8400541391160505 2.0843727959864808 2.3337575966337165 2.5842341047542985 2.8457770238349140 3.1239391208701179 3.4206579750650352 4.0869898956259370 4.8385029534594670 5.6097803490862406 6.3815078333046298 7.2235695143077612 8.0637039827023997 ; 0.73552674299537446 1.2654256183216577 1.3746665141945698 1.5274410477239910 1.6761575194673657 1.7612589921158739 1.8506160788446746 2.0015049518826511 2.2253748984600414 2.4822925869323158 2.7504951407242393 3.0254288080466822 3.3180248829649450 3.6318806965848944 4.3791337436213134 5.2172525731147594 6.0661613039893414 6.9127662571552815 7.7953255784135393 8.6757125445136296 ; 0.90770596147254268 1.5324116873002540 1.6553313166758430 1.8420947723060310 1.9998310983706662 2.1224745538229217 2.1915294723785426 2.2925769318741422 2.4530469734734308 2.6837924597205998 2.9523489935309994 3.2320282654980694 3.5371981619855908 3.8793201328010456 4.7213301314658196 5.6319303381604398 6.5540016998276505 7.4771422665406009 8.3918554889307480 9.3030921510615450 ; 1.0532027552856351 1.7893079688624061 1.9104264182725048 2.0583526314440546 2.2264593085727817 2.3888145769318339 2.5234883361874747 2.6599250137377961 2.8248900487309800 3.0148283009701098 3.2309196214248956 3.4937131909105905 3.8182791245289649 4.2216080329597530 5.1248396516711727 6.0766908216304154 7.0611749894938498 8.0570865220233969 9.0014608813211598 9.9421443030618253 ; 1.1891132511026350 1.9906249784048831 2.1079939480111771 2.2569518044031418 2.4304500733325822 2.6000291338980994 2.7481534369245875 2.9127602480114825 3.1213044945451727 3.3368652935361145 3.5537829846760753 3.8421026286291489 4.2117527693648231 4.6631820832039610 5.5686272303587154 6.5414587454568620 7.5754726492747793 8.6337415964396946 9.6125768699389518 10.589485275290563 ; 1.3185643482226623 2.1843494045315421 2.2979940601939224 2.4488683262862128 2.6308681923893102 2.8160121886118588 2.9891210465062055 3.1762227614933223 3.3971409042479483 3.6432968842448981 3.9006915672871885 4.2330505998062442 4.6328263959270659 5.0738598041996870 6.0107249625587427 7.0166313765150807 8.0884670822923539 9.1820620343058827 10.217636469775842 11.242065526692961 ; 1.4417874948261149 2.3727412046483956 2.4846437142741897 2.6404715240594192 2.8354719817977028 3.0397141607598579 3.2337457269109202 3.4396115904265092 3.6804528262313965 3.9592176506948875 4.2558720475716880 4.6264838932435595 5.0480905549173176 5.4924586183157258 6.4553654304236705 7.4953877308781278 8.5977753871324811 9.7212359306588496 10.815915840195375 11.897009978345029 ; 1.5612700331274183 2.5601799790400830 2.6724054385623273 2.8354727456276860 3.0452545235111974 3.2681016926241835 3.4805032360179013 3.7061234154259148 3.9722919777968935 4.2829159912957131 4.6114878675935547 5.0134810098519704 5.4583556379090759 5.9182377576217808 6.9044935817438375 7.9746242976842669 9.1042388306495710 10.258983816502946 11.409926177671593 12.552452674076362 ; 1.6918616520026040 2.7683928872270016 2.8817554703109778 3.0533188228173698 3.2791317106942328 3.5212419783415916 3.7529594583211661 4.0011036780516998 4.2960998892620097 4.6397666611003263 4.9983924101644499 5.4315431006572386 5.9039046972878051 6.3856551022714543 7.3980033713885485 8.4973750869308500 9.6555003092483265 10.846336622172528 12.056273849436030 13.267603933781441 ]; % Fuel Properties engine.fuel = class_REVS_fuel('LMDV_TIER_3_REG'); % Idle Speed engine.idle_target_speed_radps = class_REVS_dynamic_lookup; engine.idle_target_speed_radps.axis_1.signal = 'eng_runtime_sec'; engine.idle_target_speed_radps.axis_1.breakpoints = [ 0.0000000000000000 10.000000000000000 ]; engine.idle_target_speed_radps.table = [ 60.737457969402662 60.737457969402662 ]; % Calibration Adjustment Factors engine.variant = 'basic engine';