Environmental Engineering Reference
In-Depth Information
The next step in building the model to assess the ESS capacity requirements
is an understanding of the bus tractive effort and driveline losses. First, we develop
an approximation to tractive effort requirements. Figure 4.29 illustrates the effi-
ciency map of the bus driveline so that tractive effort and speed requirements at the
wheels can be translated to source power at the engine generator and ESS. Vehicle
ancillary and accessory loads for this study are modelled as a fixed power drain,
P
acc
= 5 kW, to include all hotel loads (engine controls, lights, entertainment
system), cabin climate control (mainly air handling fans) and hybrid supporting
subsystems for electric machine coolant pumps, inverter coolant pumps and fans as
well as ESS climate control.
P
e
Accessory,
P
acc
= 10 kW
Dist + INV,
h
= 0.95
Motor/gen,
h
= 0.86
Driveline,
h
= 0.88
Rolling =
f
(
M,V
)
Aerodynamic =
f
(
V
)
Wheels
tractive effort,
F
tr,
speed
V
Loss components
Figure 4.29 Hybrid city bus driveline efficiency map
The tractive effort,
F
tr
, and vehicle speed,
V
, in Figure 4.29 needed during
acceleration and braking (and grade climbing if present) are imposed during the
particular interval of the drive cycle noted in Figure 4.28. When the vehicle is
cruising, the power source delivers an electrical power,
P
e
, diminished by the
electric drive and driveline losses, which matches the resultant road load as illu-
strated in Figure 4.29.
The last remaining design detail before constructing the power source sizing
model is a description of the city bus gross mass during its drive around the fixed
circuit. For our analysis we assume that the number of passengers during heavy
commute periods of the day will have an expected value,
N
exp
, given as
N
exp
¼
E
f
N
pass
g¼
m
ð
N
pass
Þ #Þ
ð
4
:
15
Þ
The number of passengers is a random variable during each drive cycle
interval. We assume that the mean value shown in (4.15) equals the earlier stated
average occupancy of 60%. Using this value we assign occupancy numbers as a
random process having uniform distribution. For this particular choice of occu-
pancy one scenario may appear as shown in Figure 4.30 as the bus makes its rounds
