Integration of Traffic Simulation and Propulsion Modeling to Estimate Energy Consumption for Battery Electric Vehicles - Simulation and Modeling Methodologies, Technologies and Application - page 13

lower on an urban road. Also, the lower speeds on urban roads will result in lower
energy consumption. But the trade-off between an urban road and a freeway will be in
the travel times. A comparison is presented in the later sections of this chapter.
Table 4 shows the mean energy consumed on the urban highway by a BEV under
different traffic flow and gradient conditions. Similar to the freeway, the gradient has
a very significant effect on the energy consumption on the urban highway as well. It
is significantly greater than the effect of traffic loads.

Table 4. The effect of grade and traffic load (VPH) on energy consumption for the urban
highway

Grade

Flow (VPH) -2% 0% 2%

1000 16% 57% 100%

2000 15% 56% 99%

3000 14% 56% 98%

4000 14% 55% 0%

Also, simulations have been performed to understand the effect of the number of
lanes on the overall energy consumption. It has been observed that the number of
lanes has a very small effect on consumption in these traffic flow scenarios.

3.3 Residential Street

The results for residential roads show the mean energy required by a battery electric
vehicle to travel the 1 mile stretch of residential street with multiple stop signs.
The stop signs and the lower speeds on residential roads will significantly reduce the
energy consumption of a BEV due to aerodynamic drag, but will increase the signi-
ficance of other factors such as road grade or stop starts. Due to regenerative braking
the effects of stop start are expected to be smaller on BEV than would be normally
expected from conventional vehicles (see Table 5).
Fig. 7 shows the effect of gradient on energy consumption. It is expected that the
energy usage will be negative for a gradient of -4%. This shows that the battery of the
vehicle is gaining energy because of the regenerative braking.
Up to this point the effect of various traffic/road/driver characteristics on the ener-
gy usage for each of the individual road types has been discussed. In the next section,
a detailed comparison of the energy usage across the three different road-types is
presented to better understand how some of the scenarios impact the lowest energy
routes and distance-to-empty.

Table 5. The effect of stop-signs per mile on the energy consumption

Number of stop-signs per mile Energy (W-hours)

5 149.5

10 148.4

15 148.0