Attachment C Energy Balance Analysis

Written correspondence and verbal testimony offered during the October 5, 2001, public hearing suggested energy balance analysis as a method to avoid the potential for double counting of benefits. As noted above, such analyses can most accurately be applied to a particular vehicle with unique engine, powertrain, and vehicle characteristics and must be performed for each incremental improvement. In addition, engine map data (torque, speed, fuel consumption) must be incorporated that represent the incremental improvements for the various technologies being considered. These data must then be linked to transmission, driveline, and vehicular-specific parameters (rolling resistance, aerodynamic drag, etc.) and then simulated over various driving cycles. Furthermore, as the complexity of the technologies increases to include such things as intake valve throttling, integrated starter generators, or electrically controlled accessories, then assumptions and decisions on operating strategy, drivability, and emissions compliance are required that are time-consuming and require increasing amounts of proprietary data for simulation.

In an attempt to determine whether some fundamental flaws, resulting in gross errors, had inadvertently entered the judgment-simplified analysis described above, the committee conducted a simulation of a single vehicle (midsize SUV), for which it had access to data that could be used to attempt a more in-depth energy consumption/balance-type analysis. The analysis employed the computational methods outlined by Sovran and Bohn (SAE 810184) and a commercial engine simulation code (GT-Power1) to assess the contribution of gas exchange (pumping), thermodynamic efficiency (indicated efficiency), and cooling and exhaust heat losses. A proprietary test cycle simulation code was also employed to determine the percentage of fuel consumed by the simulated vehicle during deceleration and idle operation over the FTP-75 highway and city cycles, weighted (55/45), for a combined-cycle estimation.

Using the Sovran/Bohn equations, together with some limited cycle-estimated engine parameters (indicated efficiency, torque (brake mean effective pressure, BMEP), and speed (RPM)), the model was calibrated to 20.3 mpg for a simulated midsize SUV with a weight of 4300 1bs. A more detailed summary is shown in the table below. The committee’s overall conclusion is that the path 1 and path 2 estimated average fuel consumption improvements in Table 3–4 (see Attachment A) appear quite reasonable, although the uncertainty in the analysis grows as more technology features are considered. The average path 3 prediction is, by definition, more aggressive. However, as previously stated, all Path 3 scenarios are presented as examples only, with increasing uncertainty as the number of technologies increases.

Overall, the committee believes that its judgment-based approach provides a sufficiently rigorous analysis for drawing the conclusions included in its report.

Reference

Sovran, G., and M.S.Bohn. 1981. Formulae for the Tractive-Energy Requirements of Vehicles Driving the EPA Schedules. SAE paper No. 810184, Detroit.

1  

Cycle analysis software marketed by Gamma Technologies, Inc., and used by nearly all major engine manufacturers worldwide in the design and development of new engines.



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Attachment C Energy Balance Analysis Written correspondence and verbal testimony offered during the October 5, 2001, public hearing suggested energy balance analysis as a method to avoid the potential for double counting of benefits. As noted above, such analyses can most accurately be applied to a particular vehicle with unique engine, powertrain, and vehicle characteristics and must be performed for each incremental improvement. In addition, engine map data (torque, speed, fuel consumption) must be incorporated that represent the incremental improvements for the various technologies being considered. These data must then be linked to transmission, driveline, and vehicular-specific parameters (rolling resistance, aerodynamic drag, etc.) and then simulated over various driving cycles. Furthermore, as the complexity of the technologies increases to include such things as intake valve throttling, integrated starter generators, or electrically controlled accessories, then assumptions and decisions on operating strategy, drivability, and emissions compliance are required that are time-consuming and require increasing amounts of proprietary data for simulation. In an attempt to determine whether some fundamental flaws, resulting in gross errors, had inadvertently entered the judgment-simplified analysis described above, the committee conducted a simulation of a single vehicle (midsize SUV), for which it had access to data that could be used to attempt a more in-depth energy consumption/balance-type analysis. The analysis employed the computational methods outlined by Sovran and Bohn (SAE 810184) and a commercial engine simulation code (GT-Power1) to assess the contribution of gas exchange (pumping), thermodynamic efficiency (indicated efficiency), and cooling and exhaust heat losses. A proprietary test cycle simulation code was also employed to determine the percentage of fuel consumed by the simulated vehicle during deceleration and idle operation over the FTP-75 highway and city cycles, weighted (55/45), for a combined-cycle estimation. Using the Sovran/Bohn equations, together with some limited cycle-estimated engine parameters (indicated efficiency, torque (brake mean effective pressure, BMEP), and speed (RPM)), the model was calibrated to 20.3 mpg for a simulated midsize SUV with a weight of 4300 1bs. A more detailed summary is shown in the table below. The committee’s overall conclusion is that the path 1 and path 2 estimated average fuel consumption improvements in Table 3–4 (see Attachment A) appear quite reasonable, although the uncertainty in the analysis grows as more technology features are considered. The average path 3 prediction is, by definition, more aggressive. However, as previously stated, all Path 3 scenarios are presented as examples only, with increasing uncertainty as the number of technologies increases. Overall, the committee believes that its judgment-based approach provides a sufficiently rigorous analysis for drawing the conclusions included in its report. Reference Sovran, G., and M.S.Bohn. 1981. Formulae for the Tractive-Energy Requirements of Vehicles Driving the EPA Schedules. SAE paper No. 810184, Detroit. 1   Cycle analysis software marketed by Gamma Technologies, Inc., and used by nearly all major engine manufacturers worldwide in the design and development of new engines.

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Category and Performance Base Engine Path 1 Path 2 Path 3 Aggressive Path 3 Upper Bound Case Engine size (L) 4.0 3.5 (12.5% downsizing due to 2V to 4V) 3.4 (15% downsizing due to 2V to 4V, VVT, etc.) 3.0 (25% downsizing, due to 2V to 4V, VVT and supercharging) 2.5 (37.5% downsizing, due to 2V to 4V, VVT and supercharging) 2.3 (42.5% downsizing, due to 2V to 4V, VVT and supercharging) FMEP (bar) 0.6 (city) and 0.65 (highway) 0.6 (city) and 0.65 (highway) 0.53 (city) and 0.57 (highway) (12% reduction) 0.54 (city) and 0.59 (highway) (10% reduction) 0.42 (city) and 0.46 (highway) (30% reduction) 0.35 (city) and 0.38 (highway) (42% reduction) PMEP (bar) 0.5 (city and highway) 0.4 for active cylinders (20% down) and 0.1 for deactivated cylinders (80% down) 0.4 for active cylinders (20% down) and 0.1 for deactivated cylinders (80% down) 0.10 (city and highway, 80% down, mainly due to eliminating intake throttle) 0.05 (city and highway, 90% down, mainly due to eliminating intake throttle) 0.05 (city and highway, 90% down, mainly due to eliminating of intake throttle) Indicated efficiency (%) 37 37 37.7 (2% increase from 2V to 4 V, VVLT and intake valve throttling) 38.9 (5% increase due to 4V and VCR) 38.9 (5% increase due to 4V and VCR) 39.2 (6% increase due to 4V and VCR) Cylinder deactivation? No Yes (3 cylinder deactivated) Yes (3 cylinder deactivated) No No No Braking and idle-off? No No Yes Yes Yes Yes Vehicle loss reduction No –0.75% (weight increase-rolling resistance reduction, etc) 8% (account for averaged rolling/CD and accessory improvements, and 1/3 of transmission improvement, accessory improvement) 8.6% (account for averaged rolling/CD and accessory improvements, and 1/3 of transmission improvement, accessory improvement) 13% (account for max. rolling/CD and accessory improvements, and 1/3 of transmission improvement, accessory improvement) 13% (account for max. rolling/CD and accessory improvements, and 1/3 of transmission improvement, accessory improvement) FE—city (mpg) 15.6 19.4 (24%) 25.6 (64%) 28.9 (85%) 33.8 (117%) 35.6 (128%) FE—highway (mpg) 27.7 32.5 (18%) 37.3 (35%) 41.1 (48%) 47.1 (70%) 49.3 (78%) FE—combined (mpg) 21.0 25.3 (20%) 30.9 (47%) 34.4 (64%) 39.8 (90%) 41.8 (99%) FC—combined (g/100m) 4.76 3.95 (17%) 3.24 (32%) 2.92 (39%) 2.51 (47%) 2.40 (50%) FE improvement (on base) 0 20% 47% 64% 90% 99% FC improvement (on base) 0 16.9% 31.9% 38.8% 47.3% 49.6% BSFC excluding idle + braking (g/kwh) 403w 330 320 289 261 249 BSFC including idle + braking (g/kwh) 446 364 320 289 261 249