the effects of tread patterns on tire pavement interaction noise · 2018-05-06 · tread pattern...

The Effects of Tread Pattern on Tire Pavement Interaction Noise

Tan LI1; Jianxiong FENG2; Ricardo BURDISSO3; Corina SANDU4 1-4 Department of Mechanical Engineering, Virginia Tech, USA

ABSTRACT Tread pattern contributes to tire pavement interaction noise through two major mechanisms: (a) tread impact due to the interaction between the tread blocks and the pavement texture and (b) air pumping due to the air compression/expansion in the tread grooves. In this study, five tires with different tread patterns were tested on a same nonporous asphalt pavement using an on-board sound intensity (OBSI) method. Compared to the conventional OBSI system, an optical sensor was added to the system to provide a once per revolution signal to monitor the vehicle speed and isolate the contribution of the tread pattern from the tire noise through order tracking analysis. For the tires tested, 3D profiles of their tread patterns have been digitized and converted to parameters characterizing tread impact and air pumping, i.e., tread profile and air volume velocity spectrum. The two spectra showed good agreement with the tread pattern related noise spectrum. It is concluded that, for the nonporous asphalt pavement tested, the tread pattern does contribute to the tire noise, but usually marginally compared to the total noise except for some special purpose tires, e.g., snow tires of which the tread patterns are not perfectly randomized. Keywords: Tire noise, Tread pattern, Noise separation I-INCE Classification of Subjects Number(s): 52.3 Road traffic noise

1. Introduction As of 2004, there were approximately 16,000 different tread patterns used on tires (1) and they

continue increasing with time. The tire tread pattern is designed as a compromise between traction, handling, ride, noise, safety, and tire longevity criteria (1). As regulations for silent tires and vehicles are introduced internationally together with increasing costumer needs for driving comfort (2), a number of attempts to reduce tire pavement interaction noise (TPIN) have been made. Among the important aspects investigated, the tread pattern design is of great interest.

Sandberg and Ejsmont (3) presented three approaches to reduce the tire noise related to tread pattern: (a) pattern randomization to reduce tread impact concentrated in specific frequencies; (b) groove ventilation to reduce air pumping; and (c) modification of the geometry of tread segment (length, width, depth, angle of block/groove). For the first approach, randomization often does not reduce overall tire noise levels, but it distributes the spectrum energy over a wider frequency range and makes the sound more pleasant. Iwao and Yamazaki (4) showed that, for a car at a speed of 56 km/h with randomized tire tread pattern, the sound associated with the first-order component (excites the side wall having low dynamic stiffness) of the pattern with a central frequency of 500 Hz is spread out into the frequency range from 400 to 600 Hz. The sound associated with the second-order component (excites the tread surface) of the pattern with a central frequency of 1000 Hz is spread out into the frequency range from 800 to 1.2 kHz. For the second approach, it is good practice to avoid closed pockets (air pumping), cavities with narrow outlets and long grooves without ventilated side channels (pipe resonance). Cusimano (5) patented a quiet tire design with strategic placement of grooves such that the amount of groove void across the trailing and/or leading edges of the footprint is substantially uniform across the circumference of the tire to reduce the air volume change and air pumping. For the third approach, it was shown that increased groove length reduces the frequency of pipe resonance but will usually cause higher amplitude due to the coincidence with the impact

1 [email protected] 2 [email protected] 3 [email protected] 4 [email protected]

INTER-NOISE 2016

2185

frequency (6). As groove width increases, tire noise increases due to increased air cavity between blocks. However, after the groove width reaches beyond 9 mm, tire noise decreases, probably due to the tread stiffness reduction (3). Increased groove depth also increased air pumping. It was indicated that groove depth is more important than groove width (7). Tire noise decreases with the increased groove angle with respect to the lateral direction because it avoids simultaneous impact over the tread width. However, it cannot explain why TPIN is not sensitive to groove angle once it is over 20°. Another study showed that the lowest TPIN occurred when the groove angle is 0° (7). However, the groove angle was shown to be the least important parameter.

A couple of models were developed to correlate tread patterns with tire noise. These models can be categorized into three types: deterministic model, statistical model and hybrid model. For deterministic models, Kido et al. (8) and Bremner et al. (9) analyzed the effect of tread impact; Chen et al. (10) and Kim et al. (11) mainly focused on air pumping; De Roo and Gerretsen (12) and Plotkin and Stusnick (13) investigated both tread impact and air pumping. For statistical models, both Che et al. (14) and Li et al. (15) utilized fuzzy logic method, the former artificial neural network and the latter fuzzy genetic arithmetic. For hybrid models, Kuijpers and Blokland (16) calculated the static contact pressure distribution from the tire tread profiles while Cao et al. (17) assumed physically explainable formulas with coefficients to be statistically determined and calculate tread impact noise and air pumping noise separately. Unfortunately, the tread pattern parameters, such as fixed groove width or angle, in most of these models cannot be applied to an arbitrary tread pattern because these parameters usually change over the entire tread pattern.

It is believed among the general public that the slick tire is the quietest tire because the tread impact is reduced to the minimum (17). Alt et al. (18) also showed that noise from a patterned tire has more spectral content around 1000 Hz than a slick tire. However, VTI (19) found that a slick tire might be the noisiest tire if tested on rough pavement. Fong (20) also found that the sound levels from smooth tires (P175/70R13) were slightly greater than the patterned tire over all the chipseal pavements. Therefore, it is difficult to make a conclusion about the effect of tire tread pattern on tire noise without further investigation.

The main objective of this paper is to estimate the contribution of the tread pattern to the TIPN. Firstly, the experimental setup for collecting tire noise data from five tires with different tread patterns is introduced. Secondly, a tread pattern analysis is performed to quantify the tread pattern in the form of spectrum. Thirdly, the tread pattern-related noise is separated from the total tire noise. Finally, the comparison is made between the tread pattern spectra and the tread pattern noise and conclusions are drawn for the pavement tested.

2. Experiments Five different tires were tested and they are listed in Table 1. Pictures of their tread patterns are

displayed in Figure 1. The tires have different tread patterns but with the same or very similar size and aspect ratio. The number of blocks, as shown in Table 1, is the number of tread elements around the full tire circumference. The values range from 60 to 81.

The test pavement is a non-porous asphalt pavement, dense graded hot mix asphalt (HMA). For each tire, the noise data were collected under five different vehicle speeds (45, 50, 55, 60, and 65 mph). In addition, an acceleration test was also conducted where the vehicle accelerated from 45 to 65 mph within 10 seconds. All tires were inflated at 32 psi. The ambient temperature range during the test days was 55-74 ̊ F.

Table 1 – Specifications of the test tires.

No. Size Condition Number of Blocks

12 215/60R16 Winter/Snow 77

15 215/60R16 All season 72

18 215/60R16 All season 65

19 215/60R16 Winter/Snow 60

20 225/60R16 All season 81

INTER-NOISE 2016

2186

of 33

Table 3: Tread Patterns for the First Set of Tires

12 15 18 19 20 21

2.4 Pavement The test pavement is U.S. Route 460 near VT (section between Toms Creek Rd. and North Main St.), as shown in Figure 2. Both eastbound and westbound will be tested, as shown in Figure 2. Noise data will be recorded from the “start point” (65 mph speed limit sign) all the way until the exit. For constant speed test, at least 11 seconds of data for each test run needs to be secured (so max. 320 m @ 65 mph, shown in Figure 2); it should be sufficient for any case of noise data analysis. If the analysis for the same length of pavement section is needed, it is also very easy to obtain the specific duration of noise data based on the optical speed signal.

Figure 1 – Tread patterns of the test tires.

The vehicle used for testing was a 2012 Chevrolet Impala LT. The equipment used for collecting noise data was an on-board sound intensity (OBSI) system based on standard AASHTO TP-76 (21). The setup of the OBSI system is shown in Figure 2. The system was installed at the rear right tire with a camber angle close to zero. The conventional OBSI system has two sound intensity probes, one at the leading edge of the tire-road contact patch, the other at the trailing edge. Each probe consists of two microphones to record the sound pressure. The sound intensity along the direction of the two microphones (away from the tire) is then calculated. However, in the present OBSI system, one of the microphones at the trailing edge was disconnected and the channel was used to record the optical sensor signal. The optical sensor, as shown in Figure 2, radiates a beam onto the side face of the black disk rotating with the tire, and once the beam encounters the retroreflective tape and gets reflected to the optical sensor, the optical sensor generates a pulse. Therefore, a pulse signal is recorded at the exact time the tire completes one revolution. The microphone and optical signals were recorded simultaneously at 25.6 kHz.

4/3/16 14Monthly-Project-Update – Confidential-&-Proprietary-to-CenTiRe

5.-Test-equipment

Task%8:%Tests%and%Data%Process%

OnEboard-Sound-Intensity-(OBSI)-System

5/9/16 14Monthly.Project.Update – Confidential.&.Proprietary.to.CenTiRe

Only.three.microphones.were.used.to.collect. noise.data..The.channel. for.Mic.4.(trailing.outboard).was.used.to.record.optical.sensor.signal..

Mic.3 Mic.1 Mic.2

Optical.sensor

Task%8:%Tests%and%Data%Process%

Retroreflectivetape

2..Experiments2.5.Optical.Sensor

Figure 2 – On-board sound intensity (OBSI) system installed on the test vehicle.

3. Tread Pattern Characterization The three-dimensional tread pattern/profile was obtained using a CTWIST laser scanning

machine. The tread profile data were then converted to parameters for quantifications of the tread impact mechanism and of the air pumping mechanism. An example of the digitized 3D profile is illustrated in Figure 3. The measurement resolution is ~0.5 mm in the length/width direction and <0.01 mm in the height direction.

3.1 Tread Profile Spectrum The tread impact mechanism of tire noise generation is the sudden impulse contact between tire

tread blocks and pavement. The resulting sound can be considered as the contribution from hundreds of small hammer strokes each second (22). At the leading edge, the impact mechanism occurs as the tread block is pushed in toward the tire center; at the trailing edge, the release of the tread block can be considered as an inverse impact (23). This mechanism is caused by the in-homogeneities of the tire tread assuming the pavement surface is smooth and homogeneous. The parameter used in this paper to quantify the in-homogeneities of the tire tread is the tread profile spectrum characterizing the height variations of the tire tread. The tread profile height for each circumferential section is converted from the spatial domain (height versus length) to the time domain (height versus time) assuming a vehicle speed, e.g. 60 mph. The time domain signal is then Fourier transformed, complex data that contain both amplitude and phase, and then the spectrum is computed. Figure 4a illustrates

INTER-NOISE 2016

2187

the resulting profile spectra for all circumferential sections (width of tire) as a 2D color plot for tire. In this plot, the tread pattern block passing frequency is easily observed at around 1000 Hz. The block passing frequency is computed as the number of block times the tire angular velocity.

There are two options to reduce the 2D spectral information in Figure 4a to a single representative spectrum. The simplest approach is to compute the average spectrum across the tire width, i.e. in-coherent addition. This approach ignores the phase information (e.g. offsets between different rows of tread blocks) and it doesn’t correlate well with the tire noise. Therefore, this approach is not considered further. If the tread block offset information is to be accounted for, the averaging process across the tire width must be performed using the Fourier transform complex data and then the spectrum computed from the average Fourier Transform. This average power spectrum is called coherent tread profile spectrum since it accounts for the relative phase between tread profile along the tire width. As an illustration, the coherent tread profile spectra for test tire 12 is displayed in Figure 4b. It can be observed that peaks occur around the block passing frequency (~980 Hz) indicating that the number of blocks has the greatest influence on the tread profile spectrum.

0 50 100 150 200 250 30002040

Length [mm]

Heig

ht [m

m]

Width Position = 40.6 mm

0 50 100 1500

20

40

Width [mm]

Heig

ht [m

m]

Length Position = 205.9 mmTransverse(section

Circumferential(section

Tire(12

Figure 3 – Illustration of 3D tread profile of Tire 12.

(a)

(b)

0 500 1000 1500 20000

1

2

3

4

5

6x 10−6

Frequency [Hz]

Coh

eren

t Tre

ad P

rofil

e Sp

ectru

m [m

2 ]

Figure 4 – (a) Tread profile power spectra for all circumferential sections and (b) coherent tread profile

spectrum at 60 mph for tire 12 (frequency resolution = 12.5 Hz). The in-coherent and coherent tread profile spectrums are displayed in Figure 5 for all 5 tires. It is

shown that, the coherent tread profile spectrum is nearly an order of magnitude smaller than that of incoherent tread profile, indicating that the process of tread element randomization and offset plays a

INTER-NOISE 2016

2188

great role in making the tread pattern less aggressive. Tires 18 and 20 prove to be among the most “gentle” tread patterns since the spectral contents around their corresponding block passing frequencies are greatly reduced compared to the in-coherent tread profile spectra. Tire 12 is the most “aggressive”, probably because the tread pattern is symmetric with respect to the central line of the tire tread band and the length of each block is nearly the same. There are no cancellation effects (destructive interference) between rows in the tread pattern. On the contrary, the noise produce by these rows adds constructively since they produce perfectly phased noise, e.g. influence of tread element randomization and offset is not significant.

(a) In-coherent tread profile spectrum

0 500 1000 1500 20000

1

2

3

4

5

6x 10−5

Frequency [Hz]

Inco

here

nt T

read

Pro

file

Spec

trum

[m2 ]

Tire12_12.72Hz_0980HzTire15_12.88Hz_0927HzTire18_12.89Hz_0838HzTire19_12.90Hz_0774HzTire20_12.57Hz_1018Hz

(b) Coherent tread profile spectrum

0 500 1000 1500 20000

1

2

3

4

5

6x 10−6

Frequency [Hz]

Coh

eren

t Tre

ad P

rofil

e Sp

ectru

m [m

2 ]


Figure 5 – In-coherent and coherent tread profile spectra at 60 mph for all tires (legend includes

information of tire number, tire rotational speed [Hz] and the block passing frequency [Hz]; frequency

resolution = 12.5 Hz)

3.2 Air Volume Velocity Spectrum The air pumping mechanism is caused by the variation of the air volume enclosed between the

tread and the road surface in the contact patch. As the tire rolls, the air volume in the contact patch changes with time becoming a noise source. This noise generation mechanism is known as air pumping (22,24). In terms of acoustics (25), noise is produced by the rate of change of air volume (volume velocity). Likewise, Figure 6 illustrates the approach implemented to estimate the volume velocity time history and spectrum for the tires tested. Firstly, a simple rectangular shaped contact patch geometry is assumed (Figure 6a). In the future, this contact patch shape can be improved to better represent the actual contact patch. Secondly, the tire is assumed to rotate at 60 mph, so the contact patch moves along the tire circumference also at 60 mph, e.g. to the right in Figure 6a. Next, utilizing the 3D digitized tread profile, the air volume in the tread grooves within the contact patch at each time is calculated, air volume vs. time in Figure 6b. Then, the air volume signal is differentiated with respect to time to yield the volume velocity trace in Figure 6c. Finally, the air volume velocity spectrum is obtained by taking the Fourier transform.

The air volume velocity spectra for the five tires are shown in Figure 7. Alike the coherent tread profile spectra, the dominant part of the volume velocity spectrum also occurs around the block passing frequency. However, there is no significant spreading of the energy around the BPF, e.g. a single dominant peak at the BPF. The spectral content agreement between the coherent tread profile and air volume velocity spectra indicates the tread impact and air pumping mechanisms have the same dominant frequency ranges (around BPF), which is different than the results reported from most literature where it was argued that the tread impact is dominant in the low frequency below 1000 Hz while the air pumping is dominant in the high frequency over 1000 Hz (3).

INTER-NOISE 2016

2189

Contact' patch

60'mph

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

6.57

7.58 x 10−5

Time [s]

Air V

olum

e [m

3 ]

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08−0.02

0

0.02

Time [s]

Air V

olum

e

V

eloc

ity [m

3 /s]

1st order'derivative' w.r.t.'time'

DFT

Air'volume'in'the'grooves'between' tire'and'pavement'within'the'contact'patch

(a)

(b)

(c)

Tire'12

Figure 6 – Illustration of calculation of air volume velocity spectrum (Tire 12).

0 500 1000 1500 20000

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2x 10−6

Frequency [Hz]

Air V

olum

e Ve

loci

ty S

pect

rum

[m6 /s

ec2 ]


Figure 7 – Air volume velocity spectra at 60 mph for all 5 tires (legend includes tire number, tire rotational

speed [Hz] and the block passing frequency [Hz]; frequency resolution = 12.5 Hz)

4. Tire Noise Analysis As indicated, the OBSI system used in the present study has three microphones since the 4th

channel was used to record the optical sensor signal. Here, only the signal from the leading inboard microphone (Mic 1) will be used for the noise data analysis. However, the same results were observed and conclusions drawn from the other microphones. It should be pointed out that all the results presented in this section are only valid for the pavement tested.

4.1 Tire Noise Components The un-weighted sound pressure level spectrogram (dB) for Tire 12 during the acceleration test

(from 45 mph to 65 mph within 10 seconds) is shown in Figure 8. This figure is used to illustrate that there exist two main noise components in the dominant part of the spectrum, e.g. 600 to 1200 Hz. The first component is clearly associated to the vehicle speed or tire speed with the center band frequency going from 700 to 1000 Hz as the vehicle speed increases from 45 mph to 65 mph. The

INTER-NOISE 2016

2190

second component is independent of the vehicle speed (or tire rotation) with the spectral content encompassed always within the fixed frequency range between 600-1200 Hz.

Both the tread impact and air pumping are periodic with the rotation of the tire. It is reasonable to infer that the first component of noise is related to the tread pattern. This noise component is, thus, referred to as tread pattern noise. The second component is clearly not related to the periodic tread pattern and most likely due to tire structural radiation excited by the roughness of the pavement. However, for the sake of generality, this second noise component is referred here as non-tread pattern noise.

For a proper correlation analysis between the tire noise and the tread pattern, these two noise components must be separated. To this end, the optical sensor is used to perform this separation. The appendix briefly describes the separation technique using the optical sensor signal. The spectrum of the tread-pattern noise component is then compared to the tread pattern characterization performed in section 3.

5/13/16 9IAB*Meeting*Project*Presentation*– Confidential*&*Proprietary*to*CenTiRe

Tread&Pattern&vs.&Non/Tread&Pattern&Noise&Components:& Insights• Spectrogram*of*Mic.*1*for*Tire*12*(from* acceleration*test)

• There*are*clearly*two*components*of*TPIN• Component*1:*A*function*of*speed* (tire*rotation)* M>*Tread*pattern*noise• Component*2:*Independent* of*tire*rotation*M>*NonMtread*pattern*noise

Component* 1

Component* 2

• Conflicting* results*presented* in*the* literature.• There* is*a*need*to*separate*these* two*components* to*better*model*the*problem.*• No*separation*attempted* in*the*open*literature.*

Figure 8 – Spectrogram of microphone 1 (leading inboard) for Tire 12 accelerating from 45 mph to 65 mph.

4.2 Tire Noise Separation In this section, order tracking analysis utilizing the optical signal is performed to separate the two

components of noise signals. The total, tread pattern and non-tread pattern noise spectra for each tire are displayed in Figure 9. It can be observed that tread pattern noise component is important for tires 12 and 19 (both snow tires). For the other tires, the tread pattern noise is significantly lower than the non-tread pattern noise. It also explains why the total noise spectrum coincides to a large degree with the non-tread pattern noise spectrum as shown in Figure 9b-c,-e. On the other hand, for tires 12 and 19 the tread pattern has a more important contribution to the tire noise. The tread pattern noise is more easily observed in the spectra in Figure 9a and 9d. It is important to mention that the relative contribution between tread-pattern and non-tread pattern noise components is a function of the pavement. Thus, the results presented here are valid for the pavement tested. Preliminary data from testing on a newer and smoother asphalt pavement shows that the tread pattern noise contribution increases to 50% of the total tire noise for Tire 12.

For the tires that have large component of tread pattern noise, more oblique spectral contents will occur in the spectrogram of acceleration test, as shown in Figure 8. For the tires that have small component of tread pattern noise, the spectral contents in the spectrogram of acceleration test will remain nearly level. This explains why the results contradicted with each other in some of the literature (18,26).

The non-tread pattern noise can be potentially considered as the minimum tire noise for a specific tire when the tread pattern is perfectly randomized and the tread pattern noise is reduced to zero. A perfectly randomized tread pattern is similar to a slick tread pattern in perspective of tire pavement interaction noise generation. That is also to say, usually for the tires of which the tread patterns are already well randomized, the further optimization of tread patterns will not result in too much noise reduction. An important conclusion of this initial study is that the easier way to reduce tire noise is to reduce the non-tread pattern noise which is shown by the data to be the major component, at least for the pavement used in this field tests. This also explains why sometimes the slick tire is among the

INTER-NOISE 2016

2191

noisiest tires (19), as it is the non-tread pattern noise rather than the tread pattern noise that predominantly determines the acoustic performance of a tire for some specific pavement.

(a) Tire 12

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−w

eigh

ted

p2 rms [P

a2 ]

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−w

eigh

ted

p2 rms [P

a2 ]

Sound Pressure Power Spectrum for Mic 3 (Trailing Inboard)

Total NoiseTread Pattern NoiseNon−Tread Pattern Noise

0 500 1000 1500 2000

0

1

2

3

4x 10−4

Frequency [Hz]A−w

eigh

ted

Soun

d In

tens

ity [W

/m Sound Intensity Spectrum for Probe 1 (Leading Edge)


0 500 1000 1500 2000

0

1

2

3

4x 10−4

Frequency [Hz]A−w

eigh

ted

Soun

d In

tens

ity [W

/m2 ]

Sound Intensity Spectrum for Probe 2 (Trailing Edge)


0 200 400 600 800 1000 1200 1400 1600 1800 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−w

eigh

ted

p2 rms [P

a2 ]

Sound Pressure Power Spectrum for Mic 1 (Leading Inboard)


0 200 400 600 800 1000 1200 1400 1600 1800 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−w

eigh

ted

p2 rms [P

a2 ]



0 200 400 600 800 1000 1200 1400 1600 1800 2000

0

1

2

3

4x 10−4

Frequency [Hz]

A−w

eigh

ted

Sou

nd In

tens

ity [W

/m2 ]

Sound Intensity Spectrum for Probe 1 (Leading Edge)


0 200 400 600 800 1000 1200 1400 1600 1800 2000

0

1

2

3

4x 10−4

Frequency [Hz]

A−w

eigh

ted

Sou

nd In

tens

ity [W

/m2 ]



(b) Tire 15

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−we

ight

ed p

2 rms [P

a2 ]

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−we

ight

ed p

2 rms [P

a2 ]



0 500 1000 1500 2000

0

1

2

3

4x 10−4

Frequency [Hz]A−we

ight

ed S

ound

Inte

nsity

[W/m Sound Intensity Spectrum for Probe 1 (Leading Edge)


0 500 1000 1500 2000

0

1

2

3

4x 10−4


ight

ed S

ound

Inte

nsity

[W/m

2 ]



(c) Tire 18

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−we

ight

ed p

2 rms [P

a2 ]

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−we

ight

ed p

2 rms [P

a2 ]



0 500 1000 1500 2000

0

1

2

3

4x 10−4


ight

ed S

ound

Inte

nsity



0 500 1000 1500 2000

0

1

2

3

4x 10−4


ight

ed S

ound

Inte

nsity

[W/m

2 ]



(d) Tire 19

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−we

ight

ed p

2 rms [P

a2 ]

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−we

ight

ed p

2 rms [P

a2 ]



0 500 1000 1500 2000

0

1

2

3

4x 10−4


ight

ed S

ound

Inte

nsity



0 500 1000 1500 2000

0

1

2

3

4x 10−4


ight

ed S

ound

Inte

nsity

[W/m

2 ]



(e) Tire 20

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−we

ight

ed p

2 rms [P

a2 ]

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

Frequency [Hz]

A−we

ight

ed p

2 rms [P

a2 ]



0 500 1000 1500 2000

0

1

2

3

4x 10−4


ight

ed S

ound

Inte

nsity



0 500 1000 1500 2000

0

1

2

3

4x 10−4


ight

ed S

ound

Inte

nsity

[W/m

2 ]



Figure 9 – Total, tread-pattern, and non-tread pattern noise components at 60 mph (5 Hz resolution).

5. Comparison between Tread Pattern Parameters and Tread Pattern Noise To correlate the tread pattern to the tire noise, the spectral content of the tire tread pattern and the

tire noise are compared. Specifically, the tread pattern profile and air volume velocity spectral shapes are compared with the tread pattern noise spectral shape. As mentioned in Section 3, tires 12 and 19 have the largest spectral contents in both the coherent tread profile and air volume velocity spectrums. Thus, these tread pattern characterization spectrums are compared to the tire noise spectrum, for both the total and tread-pattern component. The results for tires 12 and 19 are shown in Figure 10 and Figure 11, respectively.

INTER-NOISE 2016

2192

(a) Tread profile vs total noise

0 500 1000 1500 20000

1

2

3

4

5

6 x 10−6

Frequency [Hz]

Coh

eren

t Tre

ad P

rofil

e Sp

ectru

m [m

2 ]

0 500 1000 1500 20000

0.04

0.08

0.12

0.16

0.2

Noi

se S

pect

rum

for M

ic 1

[Pa2 ]

Noise

Tread*pattern*parameter

(b) Tread profile vs tread pattern noise

0 500 1000 1500 20000

1

2

3

4

5

6 x 10−6

Frequency [Hz]

Coh

eren

t Tre

ad P

rofil

e Sp

ectru

m [m

2 ]

0 500 1000 1500 20000

0.04

0.08

0.12

0.16

0.2

Noi

se S

pect

rum

for M

ic 1

[Pa2 ]

(c) Air volume velocity vs total noise

0 500 1000 1500 20000

0.4

0.8

1.2

1.6

2 x 10−6

Frequency [Hz]

Air V

olum

e Ve

loci

ty S

pect

rum

[m6 /s

ec2 ]

0 500 1000 1500 20000

0.04

0.08

0.12

0.16

0.2

Noi

se S

pect

rum

for M

ic 1

[Pa2 ]

(d) Air volume velocity vs tread pattern noise

0 500 1000 1500 20000

0.4

0.8

1.2

1.6

2 x 10−6

Frequency [Hz]

Air V

olum

e Ve

loci

ty S

pect

rum

[m6 /s

ec2 ]

0 500 1000 1500 20000

0.04

0.08

0.12

0.16

0.2

Noi

se S

pect

rum

for M

ic 1

[Pa2 ]

Figure 10 – Comparison between the coherent tread profile and air volume velocity spectrums and the

A-weighted tread pattern noise spectrum for tire 12 at 60 mph (Frequency resolution = 5 Hz).

(a) Tread profile vs total noise

0 500 1000 1500 20000

1

2

3

4

5

6 x 10−6

Frequency [Hz]

Coh

eren

t Tre

ad P

rofil

e Sp

ectru

m [m

2 ]

0 500 1000 1500 20000

0.04

0.08

0.12

0.16

0.2

Noi

se S

pect

rum

for M

ic 1

[Pa2 ]

Noise

Tread*pattern*parameter

(b) Tread profile vs tread pattern noise

0 500 1000 1500 20000

1

2

3

4

5

6 x 10−6

Frequency [Hz]

Coh

eren

t Tre

ad P

rofil

e Sp

ectru

m [m

2 ]

0 500 1000 1500 20000

0.04

0.08

0.12

0.16

0.2

Noi

se S

pect

rum

for M

ic 1

[Pa2 ]

(c) Air volume velocity vs total noise

0 500 1000 1500 20000

0.4

0.8

1.2

1.6

2 x 10−6

Frequency [Hz]

Air V

olum

e Ve

loci

ty S

pect

rum

[m6 /s

ec2 ]

0 500 1000 1500 20000

0.04

0.08

0.12

0.16

0.2

Noi

se S

pect

rum

for M

ic 1

[Pa2 ]

(d) Air volume velocity vs tread pattern noise

0 500 1000 1500 20000

0.4

0.8

1.2

1.6

2 x 10−6

Frequency [Hz]

Air V

olum

e Ve

loci

ty S

pect

rum

[m6 /s

ec2 ]

0 500 1000 1500 20000

0.04

0.08

0.12

0.16

0.2

Noi

se S

pect

rum

for M

ic 1

[Pa2 ]

INTER-NOISE 2016

2193

Figure 11 – Comparison between the coherent tread profile and air volume velocity spectrums and the

A-weighted tread pattern noise spectrum for tire 19 at 60 mph (Frequency resolution = 5 Hz). From general inspection of these figures, it is clear that the tread pattern spectrums (profile and

air volume velocity) do not completely match the total noise spectrum of the tire (left side plots). However, it can be observed that a very good match is observed between the tread pattern spectrums when compared to only the tread pattern noise component (right side plots), especially around block passing frequency. This agreement is also found for the other driving speeds. For example, Figure 10a shows that the tread pattern profile spectrum doesn’t match the total tire noise spectrum in the 600 to 900 Hz range. However, when the non-tread pattern noise component is removed, there is a very good agreement in the spectral content in the 600 to 1200 Hz range as shown in Figure 10b. The spectral agreement is even better when the same comparison is performed for the air volume velocity spectrum in Figure 10d. It is supposed that both tread impact and air pumping contribute to tread pattern noise. The separation of the two mechanisms can be investigated in the future.

It is also important to note that the tread profile spectral content at high frequencies over 1800 Hz (around twice the block passing frequency) do not generate corresponding tread pattern noise.

6. Conclusions In this study, experimental measurements were carried out for five tires with different tread

patterns but with the same or very similar size and aspect ratio. The noise measurements were performed using the OBSI method. The conventional OBSI system was modified by incorporating an optical sensor to provide a once per revolution signal. The tire noise measured by the OBSI was separated into tread pattern and non-tread pattern related noise through a conventional order tracking analysis using the signal from the optical sensor. The three-dimensional tread patterns were digitized using a CTWIST laser scanning machine. The tread pattern digitized data were then converted to tread profile and air volume velocity spectra. These spectra were then compared to the total tire noise spectrum and the tread-pattern and non-tread-pattern noise components. Very good match was found between the coherent tread profile spectrum, the air volume velocity spectrum and the tread pattern noise component spectrum, supporting the conclusion that the tread pattern leads to the tread pattern noise.

For the commonly used tires, however, the tread pattern noise was found not to be the dominant noise source, at least for the pavement used in these tests. Considerable tread pattern noise only exists for some snow tires whose tread patterns look aggressive due to traction requirement and are not perfectly randomized. In future studies, models to correlate tread pattern spectral parameters and the tread pattern noise will be developed. Future work involves the testing of additional tires on pavements of different characteristics.

Acknowledgment This study has been partially supported by the Center for Tire Research (CenTiRe), an

NSF-I/UCRC (Industry/University Cooperative Research Centers) program led by Virginia Tech. The authors hereby wish to thank the project mentors and the members of the industrial advisory board (IAB) of CenTiRe for their kind support and guidance. The authors also would like to extend their thanks to Nexen Tire for providing the test tires in this study and to Hankook Tire for the digitization of the tire tread patterns. Finally, the OBSI system used in the experimental field tests was provided by AVEC, Inc., which is greatly appreciated.

References 1. Hanson DI, James C RS, NeSmith C. Tire/Pavement Noise Study. NCAT Report 04-02. United States;

2004. p. 49p – . 2. Nijland R, Vos E, Hooghwerff J. The Dutch Noise Innovation Program Road Traffic (IPG). The 32nd

International Congress and Exposition on Noise Control Engineering, Inter-noise 2003. 2003. 3. Sandberg U, Ejsmont JA. Tyre/road noise reference book. Kisa, Sweden; Harg, Sweden: INFORMEX;

2002. 4. Iwao K, Yamazaki I. A study on the mechanism of tire/road noise. JSAE Review no 17. Amsterdam,

Netherlands; 1996. p. 139–44.

INTER-NOISE 2016

2194

5. Cusimano FJI. Low noise pneumatic tire tread and method for producing same. European Patent EP0513676 A1. Google Patents; 1992. p. 1–14.

6. Ejsmont JA, Sandberg U, Taryma S. Influence of tread pattern on tire/road noise. Passenger Car Meeting, October 1, 1984 - October 4, 1984. Technical University of Gdansk, PolandSwedish Road and Traffic Research Institute, Linkoeping, Sweden: SAE International; 1984. p. 9p – .

7. Zhou H. Investigate into Influence of Tire tread Pattern on Noise and Hydroplaning and Synchronously Improving Methods. PhD Dissertation, Jiangsu University, China. 2013. p. 1–178.

8. Kido I, Ueyama S, Hashioka M, Yamamoto S, Tsuchiyama M, Yamaoka H. Tire and Road Input Modeling for Low-Frequency Road Noise Prediction. SAE Technical Papers. 400 Commonwealth Drive, Warrendale, PA 15096-0001, United States; 2011. p. 1277–82.

9. Bremner P, Huff J, Bolton JS. A model study of how tire construction and materials affect vibration-radiated noise. SAE Technical Papers. 400 Commonwealth Drive, Warrendale, PA 15096-0001, United States; 1997.

10. Chen C, Kuan Y, Chen C, Sung M. Using CFD Technique to Investigate the Effect of Tire Roiling-noise with Different Pattern Design. Applied Mechanics and Materials. Switzerland; 2014. p. 469–72.

11. Kim S, Jeong W, Park Y, Lee S. Prediction method for tire air-pumping noise using a hybrid technique. J Acoust Soc Am. USA; 2006;119(6):3799–812.

12. Roo F De, Gerretsen E. TRIAS - tyre road interaction acoustic simulation model. InterNoise 2000, The 29th International Congress and Exhibition on Noise Control Engineering 27-30 August 2000, Nice, FRANCE. 2000.

13. Plotkin KJ, Stusnick E. A Unified Set of Models for Tire/Road Noise Generation. Report: WR-81-26, 63p, Environmental Protection Agency, Arlington, VA Office of Noise Abatement and Control. United States; 1981. p. 63p – .

14. Che Y, Xiao W, Chen L, Huang Z, Yong C, Wangxin X, et al. GA-BP Neural Network Based Tire Noise Prediction. Advanced Materials Research. Shanghai, China; 2012. p. 65–70.

15. Li X-H, Liu J, Liu D-Q, Sun K-M. Application of tread patterns noise-reduction based on self-adaptive fuzzy genetic algorithm. Comput Eng Appl. 2009;45(22).

16. Kuijpers A, Blokland G van. Tyre/road noise modeling: The road from a tyre’s point-of-view. Proceedings of Inter-Noise 2003, The 32nd International Congress and Exposition on Noise Control Engineering Jeju International Convention Center, Seogwipo, Korea, August 25-28, 2003. 2003. p. 249.

17. Cao P, Yan X, Xiao W, Chen L. A prediction model to coupling noise of tire tread patterns and road texture. Proceedings of the 8th International Conference of Chinese Logistics and Transportation Professionals - Logistics: The Emerging Frontiers of Transportation and Development in China. Chengdu, China: American Society of Civil Engineers; 2008. p. 2332–8.

18. Alt N, Wolff K, Eisele G, Pichot F. Fahrzeug Außen Geräuschsimulation (Vehicle exterior noise simulation). Automob Zeitschrift. 2006;108:832–6.

19. VTI. TYRE / ROAD NOISE. FEHRL Final Report SI2408210. 2001. 20. Fong S. Tyre noise predictions from computed road surface texture induced contact pressure.

Proceedings of INTER-NOISE 98 Christchurch, New Zealand. 1998. p. 137–40. 21. AASHTO. Standard Method of Test for Measurement of Tire/Pavement Noise Using the On-Board

Sound Intensity (OBSI) Method. AASHTO TP 76. 2013; 22. Rasmussen RO, Bernhard RJ, Sandberg U, Mun EP. Little Book of Quieter Pavements. United

States; 2007; 23. Negrus EM, Teodorescu C. Testing and evaluation of tyre like component part of motor vehicle.

ISBN 973-648-027-5, BREN Publisher, Bucharest. 2002. p. 102p. 24. McDaniel R, Shah A, Dare T, Bernhard R. Hot Mix Asphalt Surface Characteristics Related to Ride ,

Texture , Friction , Noise and Durability. 2014. 25. Kinsler LE, Frey AR, Coppens AB, Sanders J V. Fundamentals of acoustics. 4th Edition. ISBN

0-471-84789-5. Wiley-VCH. 1999. p. 560. 26. Schuhmacher A. Blind Source Separation Applied to Indoor Vehicle Pass-By Measurements. SAE

Int J Passeng Cars - Mech Syst. 2015;8(3).

INTER-NOISE 2016

2195

Appendix - Tread Pattern Related Noise Separation Algorithm The technique used for the separation of the tread-pattern and non-tread-pattern noise components using

the optical sensor signal is a conventional approach and briefly described here. Figure 12a shows a typical trace from the optical sensor. The time elapsed between successive pulses represents a full revolution of the tire been tested. Since the optical signal was simultaneously recorded with the microphone sound pressure signals, these pulses were then used to identify the microphone signal windows corresponding to each tire revolution as shown in Figure 12b. Each individual microphone windowed signal was resampled to have the same number of data points (1800 pts here), independent of their actual time length. The resampled microphone windowed signals were then Fourier Transformed and coherently averaged, thus, rejecting the noise signal not related to the tire rotation (e.g. tread pattern). The averaged complex value Fourier Transform is then converted back to the time domain by taking the inverse Fourier Transform as illustrated in Figure 12c. The non-tread pattern noise component, as shown in Figure 12d, is computed by subtracting (window by window) the tread-pattern noise time traced from the total (or original) resampled signal, e.g. difference between Figure 12b and Figure 12c.

(a) Optical sensor signal example

1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2

−6−4−2

0246

Time [sec]

Opt

ical S

igna

l [Vo

lt]

(b) Total microphone signal (each window representing one tire revolution)

1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2−30

−20

−10

0

10

20

30

Time [sec]

Pres

sure

Sig

nal [

Pa]

(c) Tread-pattern noise signal

1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2−30

−20

−10

0

10

20

30

Time [sec]

Pres

sure

Sig

nal [

Pa]

(d) Non-tread-pattern noise signal

1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2−30

−20

−10

0

10

20

30

Time [sec]

Pres

sure

Sig

nal [

Pa]

Figure 12 – Illustration of separation of tread-pattern noise and non-tread-pattern noise (60 mph test).

INTER-NOISE 2016

2196

the effects of tread patterns on tire pavement interaction noise · 2018-05-06 · tread pattern...

Documents