Presentation is loading. Please wait.

Presentation is loading. Please wait.

Drive Cycle Development and Real-world data in the United States

Similar presentations

Presentation on theme: "Drive Cycle Development and Real-world data in the United States"— Presentation transcript:

1 Drive Cycle Development and Real-world data in the United States
Working paper No. WLTP-02-17 GRPE Informal Group on WLTP, 2nd Meeting January 2009, Agenda Item 6. Drive Cycle Development and Real-world data in the United States Edward Nam US Environmental Protection Agency WLTP meeting, Geneva, Switzerland January 15, 2009

2 Outline Drive cycle development history in US
FTP & off-cycle Inventory cycles Other cycle development SAFD vs Vehicle Specific Power New driving activity data US EPA 5-cycle fuel economy labeling (drive cycle weighting) Next steps Apologies for the American units!

3 Why drive cycles are important
Serve as a standardized measurement stick for emissions and fuel economy Can compare across vehicles (benchmark) Manufacturers design vehicles to meet standards set by cycles and test procedures Serves as proxy for “average” or typical driving Emissions standards are strongly dependent on the cycle and test procedure Drive cycles also change over time, with infrastructure, policy (speed limits), and technology (power:weight) This presentation focuses mainly on the drive cycle aspect of test procedure harmonization.

4 FTP cycle development US Federal Test Procedure
LA4 (City, UDDS) Developed in the late 1960’s to describe typical driving (acquired in Los Angeles) The highway HFET cycle was developed to describe a typical rural route (acquired outside Ann Arbor, MI in the 1970s) These 2 cycles used to describe fuel economy in the US US06 (aggressive) and SC03 (A/C) cycles developed based on “3 cities data” of instrumented vehicles from Baltimore, Spokane, Atlanta. REP05, REM01, SC03 were developed to cover the full range of driving, but were simplified to US06 and SC03, while FTP remained in place These cycles are extreme to prevent “cycle beaters”

5 Inventory Cycles - California
Implemented new base cycle LA92 – determined from driving in LA in early 1990’s (40kph) More representative of 1990’s driving Facility Cycles (speed correction factors) 12 unified correction cycles (UCC) mainly from chase car data in LA From 4 to 95kph Chosen by mean speed, speed-acceleration frequency distribution, positive kinetic energy (PKE), load, maximum acceleration, maximum deceleration, percent idle, percent acceleration, distance, etc These cycles are used to correct the base emission factor from LA92 to other speeds

6 CARB LA92 & CO2 speed correction factor

7 US EPA Inventory Cycles
USEPA - Facility cycles (1997) Developed by Sierra Research from 3 cities chase car data (Baltimore, Spokane, LA) 11 cycles based on roadway type and congestion level (+ramp) Each cycle lasts ~10 minutes Matched second-by-second segments of chase car data by comparing SAFDs (speed acceleration frequency distribution) Can find on EPA website under MOBILE6 technical support documentation

8 Speed/Acceleration Frequency Distribution (SAFD)
A typical way to represent the overall driving behavior is a speed/acceleration frequency distribution. However, comparing SAFDs is difficult, since the relative impact of each bin on emissions can vary. Normally, the effect of these differences could only be properly quantified by expensive laboratory testing of vehicles. This is what was done to address the vehicle activity observed in the 1992 studies.

9 EPA & Sierra cycle specifications
time in acceleration/deceleration time at cruise time at idle maximum speed average speed average or predominant speed during cruise maximum acceleration/deceleration rate maximum power length (time and miles) stops per mile average positive kinetic energy (PKE) change per mile and specific power distributions of speed and acceleration

10 USEPA Cycle development (cont’d)
Microtrips were chosen based on how well they matched the specifications Cycle choice criteria lowest sums of differences on SAFD matching real world power (2va) Segments shortened or lengthened Cycles used for (emissions) “speed correction factors” and for speed dependent transportation planning in MOBILE6 (emissions inventory model)

11 UC-Riverside CE-CERT International Vehicle Emission Model
data collection and cycle development for rapid emissions inventory estimation Almaty, Kazakhstan Beijing, China Lima, Peru Mexico City, Mexico Nairobi, Kenya Pune, India Santiago, Chile Sao Paulo, Brazil Shanghai, China

12 Vehicle Specific Power: an alternate metric for cycle manipulation
MOVES is EPA inventory model replacing MOBILE MOVES is a modal model based on VSP activity Cycle metric should be based on a more physically causal variable for emissions formation: e.g. Road load (tractive) Power P ~ Av + Bv2 + Cv3 + Mva* A,B,C are vehicle target coastdown coefficients * including road grade VSP = P/M (M is mass of vehicle) Divided by mass since emissions (measured in g/km) is largely independent of vehicle mass With VSP distributions and proper modal data, emissions can be converted from one drive cycle to another This approach has been validated by a number of studies

13 VSP Distribution in MOVES
0-25 mph 0-40 kph 25-50 mph 40-81 kph >50 mph, >80kph One could make finer scale bins if necessary kW/tonne

14 Cycle Development requires data
Much second by second data has already been collected But these were not collected with harmonization in mind, so data is scattered and inconsistent Require new and more rigorous analysis methods

15 Real world driving data since 3 cities & LA92
Chase car: Los Angeles 2000 Instrumented Vehicle: US EPA Ann Arbor shootout data 2001 Kansas City data Atlanta (Georgia Tech) 1600+ vehicles, 800+ households, GPS, accelerometer, OBD Vehicles instrumented for 2-3 years Most comprehensive activity data in existence Data excellent source for start activity as well Due to privacy concerns, data has a finite lifetime

16 Los Angeles Comparison Speed
Los Angeles is a good place to start in comparing changes in vehicle activity. LA was both a site observed in 1992 and it is also a site in a more recent chase car study done in 2000. As expected, new (higher) speed limits have affected the average speed driven by vehicles. But is this really the full picture of the changes in vehicle activity? More time is spent at high speeds in 2000 than in 1992. Speed limits were increased during this period

17 Los Angeles Comparison Acceleration
More time is spent at high acceleration in 2000 than in 1992. Another way to compare vehicle activity is in terms of accelerations. There are more high accelerations in the new data than observed in 1992. But is this change significant, in terms of the effect on overall emissions from vehicles?

18 Operating Modes for MOVES VSP bins
For coast and cruise, 13 modes retained from MOVES2004, plus 8 modes added for MOVES2006 formerly bins 26 and 36 PLUS One mode each for idle, and decel/braking Gives a total of 23 opModes

19 Los Angeles in 1992 compared to 2000
So, using the operating mode bins defined by MOVES2004, we can again compare the 1992 and 2000 calendar year chase car measurements in Los Angeles. Because VSP has a more direct and quantifiable relationship to vehicle emissions, these comparisons can more easily determine significant differences that will affect overall vehicle emissions. In this chart, note that the activity (time in mode) for calendar year 2000 is higher in the most significant bins for emissions (high speeds and high accelerations, bins 26 and 36). This suggests that the vehicle activity used in current models from 1992 is still not aggressive enough (bins 16, 26 and 36) to account for current (2000) vehicle behavior.

20 Other Factors: California (2000) Urban vs Rural
Another interesting factor in the new data is the California chase car study done outside of urban areas. Nearly all driving studies have been done in urban areas, since that is where the air quality problems usually occur and the majority of emissions are produced. This allows for the first time some comparison of vehicle driving behavior outside of urban areas. This new data will allow us to better account for driving activity outside of urban areas. Rural driving is faster than urban driving

21 SouthEast Michigan Shootout data
15 PEMS instrumented vehicles. Driven by US EPA or SENSORS employees in calendar year 2001. Note: Drivers were not randomly chosen. Avg. distance driven per vehicle : 52 miles Average speed : 31.2 mph Similarly, 15 vehicles were instrumented in Michigan as part of the development of the MOVES2004 methodology.

22 Kansas City (Round 1.5 Only)
US EPA study Instrumented vehicles (not chase car) from random population of newer vehicle owners PEMS (Portable Emissions Measurement System) equipped to measure emissions and activity. Drivers measured for 15,000-30,000 seconds (battery lifetime) Measured conventional as well as hybrid vehicles Avg. distance driven per vehicle: 41 miles Average speed: 30.1 mph There are other studies available other than the chase car study in Los Angeles. In Kansas City, vehicles were equipped with instrumentation to measure both vehicle activity and emissions. Vehicles were not driven during the entire measurement time (4 to 8 hours), which resulted in about 1.4 hours of driving per vehicle. This data is from round 1.5 only of the KC study, which are SFTP certified Tier 1 vehicles ONLY. The vehicles were selected randomly from that pool with the exception that an effort was made to specifically recruit a certain number of hybrids. The study includes 61vehicles, 21 of which were hybrids. This study was an EPA study only, designed primarily to quantify real-world fuel economy. The KC study is STILL ongoing and will be complete by the end of April, so the activity results for the city may change. The results should be considered preliminary and not a measure of total KC activity as recorded by rounds 1, 1.5 and 2. Those results are pending.

23 Speed acceleration frequency distributions
Based on a 2-dimensional matrix of speed and accelerations FTP HFET is insufficient to describe real-world driving. Even though KC seems to be less aggressive than the US06 overall, it seems (as the next slide will hint) that LA driving may be as aggressive as the US06. This means that a cycle that was once designed to be extreme may now be more representative of real-world driving!

24 Recent Activity Surveys
When we compare all of these sources, all of the recent studies, when compared to MOVES2004, are more aggressive. MOVES2004 is based on the older 1992 data. Idle have been removed from the comparison, since instrumented vehicles record much more idle time than chase car studies (such as done in LA). This idle time must be accounted for properly, but is not as important as a vehicle activity issue. LA seems to have the most aggressive driving of the regions studied Recent surveys have the more high speed, high power driving. LA driving is the most aggressive, & may be comparable to US06

25 Conventional vs Hybrid Activity
Hybrid drivers may drive less aggressively as a group, or their vehicles may be weaker powered in general – it’s probably a combination of these factors that gives these results 25–50 mph >50 mph <25 mph Hybrid driving is slightly less aggressive than conventional vehicles

26 5-Cycle fuel economy labeling
Previously, label fuel economy was based on a 2 cycle number: city and highway Real-world fuel economy effects were captured with a 20% correction factor Thesis: Real-world driving can be described by a linear combination of existing drive cycles If weighted properly the activity and fuel economy can be captured better than a fixed correction factor The key is to use cycles with a broad enough range to capture the VSP profile US driving activity is mainly represented by a linear weighting of 3 cycles: FTP(city), HFET, and US06

27 VSP distribution of FTP, HWY & US06

28 Other relevant 5 cycle issues
Through a combination of FTP (city), highway, US06, cold FTP, and hot SC03 (air conditioning) real-world driving was bracketed Result: fuel economy label became more representative of what vehicle owners would truly get throughout a year of driving Potential lessons for harmonization: VSP weighting methodology can be a powerful tool May be able to represent different regions through a combination (and proper weighting) of drive schedules

29 Comparison of FTP, NEDC, JC08
The cycle as it looks immediately after start will define when the vehicle goes closed loop, so how the modules are ordered could have a significant impact on fuel economy. The NEDC and JC08 have similar VSP profiles – in hot start, should have similar emissions Main difference likely due to sequence following starts

30 Conclusions US has a long history of drive cycle development
Much new data exists in the US for a harmonization project (with more coming) Driving has been getting faster and more aggressive with each passing decade VSP activity is a powerful (yet simple) tool to characterize and combine drive cycles and to compare driving from different regions

31 Issues for future consideration
Definition of “city” vs “highway” (urban vs extra-urban) City can include high speed driving and highways can be congested stop and go Starts/km variability Shift schedules Scaling drive cycle for small engine “cars”

32 Next steps We should analyze the existing data especially the Atlanta data before it is destroyed Should agree on QA/QC procedures for data As well as a methodology for cycle generation and comparing “representativeness” The US EPA is going to start collecting second by second activity and emissions data from real-world operation from a variety of cities

33 Appendix

34 Data Limitations OBD data is noisy when used for accelerations
GPS is noisier than OBD Should make an effort to determine best filtering mechanism compared to directly measured accelerations Accelerometer, 5th wheel, etc. Do accelerations matter? Certification tests have x% eror band for drivers to follow cycles But Robot drivers and computer simulations can follow cycles exactly, so the exact cycle trace can matter

Download ppt "Drive Cycle Development and Real-world data in the United States"

Similar presentations

Ads by Google