A study of the interaction between vehicle exterior noise emissions and vehicle
energy demands for different drive cycles
Johan NYGREN†(1) , Susann BOIJ† , Romain RUMPLER† , Ciarán J. O’REILLY‡† KTH Royal Institute of Technology, The Center for ECO2 Vehicle Design, The Marcus Wallenberg Laboratory for Sound andVibration Research, Sweden‡ KTH Royal Institute of Technology, The Center for ECO2 Vehicle Design, Sweden(1) johnygr@kth.seAbstract
This initial study investigates the interaction between vehicle noise emissions and the energy required to move thevehicles along different drive cycles. There is a trade-off between reducing noise emissions and at the same time
reducing other environmental impacts. A vehicle’s energy demand associated with a specific drive cycle may beaffected when a different route is chosen between two locations to reduce the noise exposure at certain observer
points. The methodology of the study was to use the existing IMAGINE traffic noise model as a source model, andto evaluate the sound exposure level (SEL) at observer points as a function of instantaneous sound pressure level
estimates as the source moved from one location to another via two different routes. A noise impact estimate with alinear dependence on the difference between the SEL and a threshold level was proposed. Also, the energy demandfor each route was calculated. The results indicated that there is a difference between the two routes if the aim is toreduce the noise exposure or the energy demand. Suggested future research is to further improve the noise impact
evaluations in the context of very short durations of exposure.
Keywords: Vehicle noise emissions, Energy demand, Drive cycles.

1INTRODUCTION

Noise emissions from transport persists as one of the greatest environmental issues in modern day. The social
cost for road traffic noise in Europe was estimated to e40 billion per year in 2007, where passenger vehicles
and trucks were responsible for 90% of the annual cost (1). While most of the health effects due to traffic
noise are measured using long-term averaged noise indicators, effects such as sleep disturbance in the form ofawakenings can also be caused by noise events with transient behaviour which might not be resolved using
the long-term averaged noise indicators. In this context, a time-dependent measure, potentially capturing theseshort-time noise events, may be needed in order to provide estimations of the impact of noise emissions fromindividual vehicles.
There is often a trade-off between noise emissions and other environmental impacts such as energy use. For
example, the energy demand for moving from one point to another may change when taking different routes
between the two points. The level of impact related to noise emissions is measured with respect to one or several observer points, whereas the energy demand is related to the specific vehicle and the drive cycle. However,they are not necessarily independent from one another. When an attempt is made to minimize either the impactof noise or the energy demand, one does not necessarily keep the other unchanged. For example, one driving
strategy to minimize the impact of noise is to make sure that the route from one location to another remains as
far away from the observer points as possible, which might lead to a longer route than what would be taken if
the only goal was to minimize the energy required to move between the two locations.
The aim of this study is to investigate how a choice of route between two locations affects the resulting impact
due to noise emissions as well as the energy demand and how these two environmental impacts interact on7216

a system level. An initial study will be performed on a simplified model of a road network with two routes
between two different locations. The total sound exposure level (SEL) is suggested as a noise indicator, estimated over the duration of driving along each route. The energy demand required to move along a route is also
calculated.

2BACKGROUND

There has been extensive research in the field of long-term averaged traffic noise estimations and long-term
health effects regarding road traffic. Andersson and Ögren (2) investigated a pricing model for road and railway
noise using short-run marginal cost from changes in the SEL over 24 h. The World Health Organization (WHO)(3) recently published new guidelines and recommendations on community noise and a review of research providing evidence on health outcome related to noise exposure measured using noise indicators such as averagednight-time noise levels (Lnight ) or averaged day-evening-night noise levels (Lden ).
Traffic noise models can then be used to calculate estimations of these noise indicators. A common noiseassessment method (CNOSSOS-EU) was developed for the EU in 2010-2012 (4), and is currently being used
to harmonize the estimation of Lden in European countries. CNOSSOS-EU is a model on a macroscopic levelof traffic behaviour, and is one of several existing traffic noise models. Another traffic noise model developedby the EU is the IMAGINE traffic noise model (5), which is based on a microscopic level of traffic behaviour
instead. The IMAGINE model provides representative source models for vehicles of a certain category, andthese are defined as one or two point sources at different heights. The sound power level for each source isgiven in 1/3-octave bands and is speed and acceleration-dependent. Correction terms for vertical directivity areprovided in the model, but for a more detailed formulation of the directivity, including horizontal directivity,
one can use the correction terms found in (6).
However, long-term averaged traffic noise estimations do not provide information on the temporal structureof the noise. De Coensel et. al. (7) implemented the IMAGINE traffic noise model in a microscopic traffic
simulation to estimate the instantaneous sound pressure levels produced by individual vehicles. This enables anexposure analysis that includes the duration of the exposure and the time history of the sound pressure level.

3METHODOLOGYAs the aim of this initial study is to analyze both the effects of noise and energy demand along different
routes, the noise and energy models should be simple enough for calculation purposes but complex enough tocapture a variation in vehicle behaviour. The approach is to use the existing representative source model for acategory 1 vehicle in the IMAGINE traffic noise model. This category corresponds to light motor vehicles. The
source model will be used to estimate the instantaneous sound pressure level at a certain time step produced
by an individual vehicle, and then evaluate it over time as the vehicle moves. Any acoustic effects due tosource motion are assumed here to be negligible. The time delay related to the sound propagation between
source and observer will be omitted. This initial study only considers one vehicle at a time, and a time shiftcorresponding to the time delay would in this case only delay the same noise that will eventually be observed.
Also, the two point sources that the vehicle model is comprised of are very close to each other. Thus, one canassume the distances between the point sources and the observer are similar. Correction terms for horizontal
and vertical source directivity will be used in accordance to the documentation of acoustic source modelling ofnordic road vehicles (6). These correction terms are tabulated in 1/3-octave bands and depend on source heightand horizontal as well as vertical angles between observer and source direction. The sources are assumed to be
in a free field with standard temperature and pressure, and the sound propagation is therefore simplified to afunction of distance r(t) between an observer and the source at height h, given by7217

L p,h (t) = LW,h (t) − 10 log 4πr(t)2 ,(1)where LW,h (t) is the sound power level provided by the IMAGINE traffic noise model. The sound exposurelevel (SEL) LE will be used as noise indicator
Z TLE =

10L p (t)/10 dt,(2)0
where L p (t) = ∑h exp L p,h (t)/10 is the total instantaneous sound pressure level at time t and the integration isevaluated over a total time of T . The sound exposure level takes into account both the sound pressure level ofthe exposure as well as its duration. An exposure to a lower equivalent sound pressure level over a longer time
may have the same SEL as a higher equivalent sound pressure level over a shorter time. The impact I given
the SEL LE estimated over a number of observation points will then be calculated with an evaluation proposed
here to be such thatN
I = K ∑ max LE − LE,threshold , 0 ,

(3)

n=1

where K relates the impact to a difference in SEL with respect to some threshold level LE,threshold . K here isassumed to be independent of the total SEL LE . It is therefore assumed that the impact is linearly dependent
on the difference between the current SEL and the threshold level, and that there is no measurable impact related to SEL below the threshold level. The impact estimate does not resemble an actual cost or health effectestimate in the current state. However, it should aim to resemble such an estimate.
The noise exposure will be compared with the energy demand for each route. The energy demand is considered as the energy needed to overcome the aerodynamic, inertial and rolling resistance for a specific drive
cycle. For more details on the calculations, see references (8, 9). It translates into the total necessary mechanicalwork, and is calculated as
WT = WR +Wa +WL ,(4)where WT is the total energy required, WR is the energy required to overcome rolling resistance, Wa is the energy
to overcome the inertial resistance due to acceleration, and WL is the energy to overcome the aerodynamic drag.
They are calculated as
WR = (1 − r)g fRCW R
Wa = mCWa(5)

WL = 0.5ρcD ACW L
where r is the fraction of kinetic energy regained during deceleration, g is the gravitation constant, fR is therolling resistance coefficient, m is the mass of the vehicle, ρ is the density of air, cD is the drag coefficient,and A is the frontal area of the vehicle. The coefficients CW R , CWa and CW L are characteristic values that only
depend on the drive cycle. They are sums over discrete segments of ∆s over the length of the drive cycle, asCW R = ∑ ∆s, CWa = ∑ ai ∆si , and CW L = ∑ v2i ∆si where ai and vi are the incremental acceleration and velocity,respectively.
Lastly, the vehicle parameters will be defined for a typical passenger vehicle similar to the representative vehicleof category 1 in the IMAGINE traffic noise model.

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4SETUP OF ROUTES AND MEASUREMENT POINTSThe setup allows for an evaluation of noise exposure at set measurement points with respect to two similar, yetdifferent, routes.

Figure 1. Setup of the analysis.
The two routes in the setup shown in Figure 1 have the same locations for departure and arrival, respectively.
The measurement area located at a height of 2 m consists of 5600 measurement points distributed over the area.
The routes are flat and follow the same set of simple rules regarding speed and acceleration/braking, shown in
Table 1.
Table 1. Rules for the speed of the source.
vsvtta/b

50 km/h
40 km/h3s

The source will move at a constant speed of vs on the straight road sections. It will then brake for a time
length of ta/b with a constant deceleration just before it enters a turn, which it will drive in at a constant speedof vt . All the turns for both routes have the same radius of curvature of rturn = 10 m. Right after the turn thesource will then accelerate up to vs by accelerating with a constant acceleration for a time length of ta/b . The
distance travelled along each route and the time it takes for the source to go from the start point to the end
point are shown in Table 2.
Table 2. Distance travelled and time it takes to travel along each route given the rules in Table 1.
Route 1
Route 2Distance
491.4 m482.9 mTime
37.2 s38.3 s

The choice of vehicle parameters will have an impact on the resulting energy demand for each route. The
proposed vehicle parameters are chosen to be consistent with a vehicle of the same category as in the IMAGINE

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traffic noise model.
Table 3. Vehicle parameters.
Description
WeightAir drag coefficient
Frontal area
Rolling resistance coefficientParam.
mcD
AfR

Value
1500 kg
0.3
2 m20.01

In addition to the vehicle parameters in Table 3, the air density was set to ρ = 1.2 kg/m3 .

5RESULTS

The following sections will present the results of the noise level calculations as well as the energy demands
corresponding to each route.
5.1 Noise impact
The resulting total SEL over the measurement area differs when driving on either route.

Figure 2. Total sound exposure level on the measurement area when driving along route 1 (left) and route 2(right).
A higher SEL was observed close to where the source was accelerating after each turn in Figure 2. A histogramof the results is used for comparison of the distribution of the exposure level over the measurement area, see
Figure 3.

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Figure 3. A histogram comparing the total sound exposure level when driving along route 1 and 2.
The histogram is normalized with respect to the total number of observation points over the measurement area.
A larger portion of the measurement area has a lower SEL when the source moved along route 2 compared toroute 1, as the relative number of observations are larger for lower SEL for route 2 compared to route 1 inFigure 3. However, there is a small difference at very high SEL where route 2 has slightly more observations
compared to route 1. The results of the impact estimate given in Equation 3 is shown in 4.

Figure 4. Ratio of impact estimates as function of the threshold level.
The impact of route 1 appears to be slightly higher than the impact of route 2 for almost all choices of the7221

threshold level. At almost 60 dB there is a maximum related to the shape of the distributions in the histogram.
If the threshold level is set to 60 dB it means that the observations at low exposure levels are omitted, andthe larger difference between the exposure levels from the routes at 61 to 67 dB results in this peak. As thethreshold level is increased there are fewer data points in the ratio estimate, and there are no data points foreither route with a measured SEL above 72.5 dB.
5.2 Energy Demands
The resulting energy demands are a function of the drive cycle along each route and the vehicle parameters.
The characteristic values for each route are shown in Table 4.
Table 4. Characteristic values.
Route 1
Route 2CW R (m)
491.4
482.9

CW L (m3 /s2 )
8.7E4
7.8E4

CWa (m2 /s2 )
69.5
138.9

The ratio of the energy demands between route 1 and route 2 were calculated with Equation 4 to be W1 /W2 ≈0.69, meaning that the energy demand for route 1 was approximately 70 % of the energy demand needed tomove along route 2.

6ANALYSISGiven this specific scenario there appears to be a conflict in reducing noise exposure as well as the requiredenergy to move along a route at the same time. While route 1 seems to have a higher impact in terms of noise
exposure, it does also seem to require less overall energy associated with its drive cycle when compared to thecorresponding estimates associated with route 2. The difference in energy demand between the two routes waslargely as a result of the greater CWa for route 2 because of the additional cornering. As expected, the results
for noise levels and energy demand were dependent on how the source was moving along each route and where
the observer points were located with respect to the source.
However, the noise impact estimate needs to be further improved in order to determine the total impact, inparticular the coefficient K. It is not ideal for K to be assumed constant, as this coefficient can be related to
an individual cost as a function of a change in the SEL. Reviewing other studies on cost analysis of noise
one realizes that a difference in noise levels relates to different costs depending on the current noise level, aspresented by Andersson and Ögren (2). The same difference in noise levels will result in a higher cost if thecurrent noise level is higher compared to a lower current noise level. Also, other studies investigating costmeasures of noise often use the averaged day-evening-night noise level Lden or the A-weighted 24 h equivalentsound level LAeq,24h , which make it non-trivial to relate these to the estimation of the impact of noise eventswith very short durations (T  1 h). Given that both energy demand and a cost estimate based on noise exposure could be comparable quantities, it is of interest to further investigate the derivation of suitable indicators
in contribution of the steps presented with this contribution.

7

CONCLUSIONS

There is a trade-off between noise exposure and energy demand for the specific scenario presented here andthe associated drive cycles. It was possible to show that one route might be preferred with respect to one
environmental impact, whereas the other route would be preferred with respect to another environmental impact.
Continued research is needed to provide a comparison of the total environmental impact from noise exposureand energy demand using a common value of impact for very short durations of exposure as presented in thisinitial study.

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ACKNOWLEDGEMENTS
The authors would like to thank the Centre for ECO2 Vehicle Design at KTH, funded by the Swedish Innovation Agency Vinnova (Grant Number 2016-05195); and the strategic research area TRENoP for their financial
contributions to this work.

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