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Co-Optimization of Fuels and Engines John Farrell
SAE High Efficiency Internal Combustion Engine Symposium April 11, 2016
NREL/PR-5400-66333 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.
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Goal: better fuels and better
vehicles sooner
Fuel and Engine Co-Optimization
o What fuel properties maximize engine performance?
o How do engine parameters affect efficiency?
o What fuel and engine combinations are sustainable, affordable, and scalable?
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30% per vehicle petroleum
reduction via efficiency and displacement
source: EIA 2014 reference case
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Fuel selection overview
If we identify target values for the critical fuel properties that maximize efficiency and emissions performance for a given engine architecture,
then fuels that have properties with those values (regardless of chemical composition) will provide comparable performance
Governing Co-Optima hypotheses:
There are engine architectures and strategies that provide higher thermodynamic efficiencies than available from modern internal combustion
engines; new fuels are required to maximize efficiency and operability across a wide speed/load range
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5 5 Current fuels constrain engine design
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Fuel is more than just octane
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Leveraging expertise and facilities from 10
national labs
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Integrated multi-lab teams with significant
external stakeholder engagement
8 Biofuel companies
13 Light and heavy duty vehicle manufacturers
10 Oil companies/ refiners
End consumer organizations 2
Regulatory agencies 4
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Parallel efforts are underway
Low reactivity fuel High reactivity fuel Range of fuel properties TBD
Thrust I: Spark Ignition (SI)
Thrust II: Advanced Compression Ignition (ACI) kinetically-controlled and compression-ignition combustion
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10 10 Applicable to
light, medium, and heavy-duty engines hybridized and non-hybridized powertrains
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identify and mitigate
barriers to wide-scale
deployment
Identify and mitigate
barriers to wide-scale
deployment
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Co-Optimization:
9-14% GHG reduction
(beyond “business as usual”)
National goal: 80%
reduction in transportation GHG by
2050
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Six integrated teams
Low Greenhouse Gas Fuels
Advanced Engine Development
Market Transformation
Fuel Properties
Analysis of Sustainability, Scale, Economics, Risk,
and Trade
Modeling and Simulation Toolkit
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FY16 Activities
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What fuels can we make?
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Fuel selection criteria (“decision tree”)
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Thrust I decision tree results
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Fuel property database Database of critical fuel properties of bio-derived and petroleum blendstocks 366 molecules, 12 mixtures (at present)
25 database fields for fuel properties
Will add capability for fully blended fuels
Data from experiment and literature or calculated/estimated (where needed)
Shared resource for team and public
Fioroni et al., NREL
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Identification of Thrust I candidates Tier I criteria Melting point/cloud point below -10C Boiling point between 20C and 165C Measured or estimated RON ≥ 98 Meet toxicity, corrosion, solubility, and biodegradation requirements
34 promising bio-blendstocks from many functional group classes
Not final – this is an iterative process!
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High-level LCA, TEA,* feedstock availability analyses Identify cost/environmental/scale attributes
Fifteen key metrics identified GHG, water, economics, TRL
Evaluation of 20 Thrust I blendstocks underway
Cost and environmental impact analyses
* LCA = Life cycle analysis; TEA = techno-economic analysis; TRL = technology readiness level
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Identify and mitigate challenges of moving new fuels/ engines to markets
Historical analysis of new fuel and vehicle introduction
Engage stakeholders across value chain
Identifying/mitigating market barriers
Adapted from S. Przesmitzki
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Fuel-related tasks
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Fuel-related tasks (continued)
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Heat of vaporization (HOV): complex mixtures Pure compound approach not applicable to gasoline True HOV underestimated
Approach: directly measure HOV by DSC/TGA* and calculate via detailed hydrocarbon analysis
Very similar HOV for wide range of gasolines and ethanol blends
* DSC = differential scanning calorimetry; TGA = thermogravimetric analysis Fioroni et al., NREL
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Rapid compression machine study of CRC FACE-F / ethanol blends (E0–E30, E100) Data to validate LLNL gasoline surrogate kinetic mechanism
Bench-scale autoignition studies combined with engine experiments Data from customized IQT to validate LLNL kinetic mechanisms Zigler (NREL)
Kinetics and SI autoignition behavior
Goldsborough, ANL
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Develop archival mechanisms for representative bio-blendstocks and surrogates
Validate against high-fidelity experimental data Anisole - surrogate for methylated phenolics from biomass (Pitz et al., LLNL)
Kinetic mechanism development M
ole
fract
ion
Mol
e fra
ctio
n
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Thrust I tasks
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Engine performance merit function
Provides systematic ranking of blendstock candidates on engine efficiency when multiple fuel properties are varying simultaneously
Allows fuel economy gains to be estimated based on fuel properties
RON = research octane number K = engine-dependent constant S = sensitivity (RON-MON) ON = effective octane number HoV = heat of vaporization SL = flame speed LFV = liquid fuel volume at 150°C H = Heaviside function PMI = particle mass index
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Relationship between sensitivity and HOV Inconsistencies in literature regarding HOV impact on knock HOV effect only been observed when covariant with octane sensitivity
Main conclusion: HOV is a thermal contributor to sensitivity Consistent with vaporization effects in RON and MON tests
HOV appears to improve performance at elevated intake air temperatures
Sluder, Szybist (ORNL) McCormick, Ratcliff, Zigler (NREL)
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Quantify relative fuel impact on dilution tolerance and compare vs engine parameters Fuel properties: flame speed, HOV Engine: tumble, ignition energy, etc.
Hypothesis: laminar flame speed predicts dilution tolerance (lean and EGR) of an SI fuel Preliminary results confirm positive correlation
Fuel effects on EGR and lean dilution limits
Wallner ANL
Iso-octane N-heptane
Toluene
Ethanol
Methanol
0
10
20
30
40
50
60
40 45 50 55 60
Hea
t of V
apor
izat
ion
[kJ/
MJ]
LFS at 1atm, 358K [cm/s]
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Single cylinder version of GM Ecotec 2.0L, 9.2: CR
Dilution tolerance correlates to laminar flame speed
Flame speed at ignition provides good indication of spark-to-CA5, combustion stability
Fuel effects on EGR and lean dilution limits
Szybist ORNL
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Thrust II tasks
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Evaluate Thrust I fuel performance in GCI engine, Particular focus: challenging low load operation
Identify relationships of fuel HoV, sensitivity with GCI combustion, emissions, and performance
Thrust I Fuel Behavior in GCI
Ciatti ANL
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1.9L GM diesel engine platform with production viable hardware Modified for both single- and dual-fuel LTC operation
Identify performance trends in CI/LTC strategies spanning RCCI + GCI Vary reactivity differential between premixed and DI fuels
Matched experiments to optical work at SNL
Multi-cylinder RCCI experiments
ORNL RCCI Multi-Cylinder 1.9L GM (Curran)
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Measure in-cylinder mixing/ kinetics to optimize dual-fuel heat-release Noise, efficiency, and load range
Understand mixing/ignition interaction for different reactivity combinations
Provides in-cylinder diagnostic for measuring reactivity stratification Adds new insights for CFD as well
Optical diagnostics of RCCI
Musculus SNL
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18 month decision point
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First major milestone: 18 month decision point Marks completion fuel discovery efforts (i.e., candidate identification) for Thrust I (advanced spark ignition)
Will conduct rigorous assessment of fuel/engine options and identify promising* low-GHG fuel/engine combinations
Will identify whether new low-GHG fuel candidates have been identified that require additional development work
Outcome will dictate balance between Thrust I vs Thrust II work after 18 months
* Sustainable, affordable, scalable
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41 41 The 18 months decision point
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Approach
Need to explicitly account for uncertainty
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Identifying options: a multi-objective optimization problem
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18 month decision point summary • Co-Optima team is conducting R&D across wide technology space to identify
− Properties and attributes of Thrust I blendstock candidates − Engine/vehicle merit function to relate properties to performance
• At end of 18 months (3/31/17) we will have surveyed all promising candidates and characterized performance along multiple dimensions
• Decision will address whether promising* low-GHG blendstocks/fuels have been identified that merit further fuel development/scale-up efforts − If “no” – shift fuel discovery/development efforts to Thrust II (other Thrust I
efforts – engine testing, ASSERT and MT metrics, etc – will likely continue) − If answer is “yes” – continue development and scale-up efforts
Need stakeholder input to define what constitutes “promising” − Focus of 2016 Stakeholder Listening Days (stay tuned)
*
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Status and next steps Initiative started October 1 2016
FY16 budget: $27M; FY17 budget request: $30M
External advisory board formed
Active stakeholder engagement efforts underway (sign up!)
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Acknowledgements DOE Sponsors: Alicia Lindauer (BETO) Kevin Stork and Gurpreet Singh (VTO)
Co-Optima Technical Team Leads: Dan Gaspar (PNNL), Paul Miles (SNL), Jim Szybist (ORNL), Jennifer Dunn (ANL), Matt McNenly (LLNL), Doug Longman (ANL)
Other Co-Optima Leadership Team Members: John Holladay (PNNL), Art Pontau (SNL), Robert Wagner (ORNL)
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Thank You