Bekke, Dirk

Bezemer-Krijnen, Marieke

De Boer, Andre

Wijnant, Ysbrand

English

The current tyre design process uses many experimental evaluations and it may take therefore more than 2 years to develop a tyre. The use of simulation tools improves and speeds up this process. Research has shown that the human perception of tyre tread pattern noise is mainly determined by the noise characteristics: level, tonalness and modulation (also called drumming). In this paper a new source model and human perception model is described. The source modelling approach predicts the correct trends of the three tyre tread pattern noise characteristics. From the noise characteristics dedicated Sound Quality Metrics are defined: for level the Standard Deviation (STD), for tonalness the Order Prominence (OP) and for modulation the Multi- Order Modulation (MOM). Using these Sound Quality Metrics the human perception model is obtained by regression analysis, predicting the human perception of tyre tread pattern noise correctly (R2=0.94). The coupled source - human perception model enables a very fast optimization of a complete tyre tread pattern design to human comfort.</p

University of Twente Research Information

Tyre tread pattern noise optimization by a coupled source-humanperception modelDirk BEKKE1; Ysbrand WIJNANT2; Andre DE BOER3; Marieke BEZEMER-KRIJNEN41 Apollo Tyres Global R&D, The Netherlands2 University of Twente, The Netherlands3 University of Twente, The Netherlands4 University of Twente, The NetherlandsABSTRACTThe current tyre design process uses many experimental evaluations and it may take therefore more than 2years to develop a tyre. The use of simulation tools improves and speeds up this process. Research has shownthat the human perception of tyre tread pattern noise is mainly determined by the noise characteristics: level,tonalness and modulation (also called drumming). In this paper a new source model and human perceptionmodel is described. The source modelling approach predicts the correct trends of the three tyre tread patternnoise characteristics. From the noise characteristics dedicated Sound Quality Metrics are defined: for levelthe Standard Deviation (STD), for tonalness the Order Prominence (OP) and for modulation the Multi- OrderModulation (MOM). Using these Sound Quality Metrics the human perception model is obtained by regressionanalysis, predicting the human perception of tyre tread pattern noise correctly (R2=0.94). The coupled source -human perception model enables a very fast optimization of a complete tyre tread pattern design to humancomfort.Keywords: Tyre, Road, Sound Quality, Vehicle, Perception.I-INCE Classification of Subjects Number(s): 11.7.1, 52.3, 63.7, 79.91. INTRODUCTION1.1 Sound QualityIn the automotive industry Noise, Vibration and Harshness (NVH) characteristics of a vehicle are evaluatedby an experienced test driver. This evaluation is given on a scale from 1 up to 10 according to the VDI 2563standard shown in Figure 1. Driving manoeuvres and evaluation forms are often prescribed by the VehicleOriginal Equipment Manufacturing (OEM) to obtain a common standard and terminology.Figure 1 – Vehicle Original Equipment Manufacturing (OEM) rating according to VDI 2563 standard (1).A widely used driving situation to evaluate the tyre tread pattern noise inside the vehicle is a coast down ona smooth road. During this coast down the vehicle rolls out from highway speeds of about 120 km/h to lowspeeds of 20 km/h with the engine shut and in free gear. The tyre tread pattern noise heard is evaluated andcharacterized in words using given noise terminology.1dirk.bekke@apollotyres.com2y.h.wijnant@utwente.nl3a.deboer@utwente.nl4m.bezemer@utwente.nlInter-noise 2014 Page 1 of 8Page 2 of 8 Inter-noise 2014Buss (2) analysed over more than 9500 of such coast down evaluations using a database of a tyre manu-facturer. She showed that the human perception of tyre tread pattern noise is best characterized by the noiseterminology: drumming noise, pattern noise and booming noise. Drumming noise is defined as an amplitudemodulation of the tyre tread pattern noise. Pattern noise is described as the tonalness perception of the tyretread patterns impact frequencies. Booming noise is the vehicles interior acoustical resonance modes.Earlier research of Daniel (3), (4) showed that loudness is also important in the human perception of thesound. Frank (5) and Freeman (6) modelled the human perception of interior tyre-road noise using Loudness(L), spectral balance (SB) and Tonality (T ) in a linear regression. Using indoor measurements of a single tyre,they could predict the subjective rating quite well.In summary, it can therefore be concluded that drumming noise, the noise level and the tonalness are thethree most important noise characteristics in the human perception of interior tyre tread pattern noise. Thehuman perception can be modelled using Sound Quality Metrics, but is has never been coupled to a sourcemodel enabling a direct optimisation of the tyre tread pattern design to the human comfort.1.2 Sound engineeringRegarding the sound source, the tyre industry spend many years of research reducing the tonalness byscaling the tyre tread pattern according to a so-called pitch sequence. Most of this research resulted in patents.Patents cover the developed pitch sequence, specific design rules or optimitsation methods.Different source models have also been developed and patented. Some based upon an impulse trainbased representing the tread impact frequency (7), (8). More physical approaches use the tyre tread patterngeometry (9), (10), or the contact force variation (11). Hybrid approaches using measured sounds are alsoclaimed (12). A source model predicting all three subjective noise characteristics at once or source modelsbeing coupled to the human perception models have not been reported.Furthermore the claimed source models still require a physical tyre in order to evaluate the tyre treadpattern noise according to Figure 1. Using this approach each iteration therefore takes still about 3-4 months.1.3 ObjectiveThe objective of the current research is therefore to provide an engineering tool enabling a direct optimisa-tion of the tyre tread pattern design to the human comfort. For this, two models are required:• A source model; describing the origin of tyre tread pattern noise• A human perception model; describing the sound quality of the tyre tread pattern noise.The models should be coupled using Sound Quality Metrics (SQM) describing the three relevant noisecharacteristics: drumming, noise level and tonalness. In this manner, the coupled source-human perceptionmodel enables a direct optimisation of the tyre tread pattern design to the human noise perception.Figure 2 – Tyre with four ribs (right) and the tread pattern height (left) with the leading and trailing edges ofthe contact patch.2. MODEL2.1 Source modelTyre-road noise originates from the contact patch between the tyre and road. Consider the tyre shown inFigure 2. The right hand side shows a tyre with a cylindrical axis system: axial direction (w), radial direction(r) and circumferential direction (ϕ). This tyre is used to clarify the theory and model. The left hand side ofshows the tread pattern height above the groove level:Htread(ϕ,w) = H0H(ϕ,w) (1)Page 2 of 8 Inter-noise 2014Inter-noise 2014 Page 3 of 8where H0[mm] is a scaling factor for the maximum tread depth and H(ϕ,w)[−] is the (normalized) treadpattern height. This (normalized) tread pattern height describes the shape of the tread pattern around the tyrecircumference ϕ[rad] and axial width w[mm].Upon rolling, this tyre tread pattern geometry passes the contact patch, resulting in contact pressurevariations in both time and space. For an theoretical smooth road, the tyre which is in contact with the road ismainly responsible for the contact pressure variations resulting in tyre vibrations and noise. For simplicity, it isassumed that the complete contact patch contributes to the interior noise and all contact points (ϕ,w) act ascoherent sources. The averaged tread pattern height in contact, as the surface integral over the contact patchper circumferential position, is therefore only relevant to consider:h̃(ϕ) =1A∫ ∫contactH̃(ϕ,w)dS for all ϕ = 0 . . .2π (2)where A is the contact area normalizing the contact averaged tread pattern height function h̃(ϕ) between0 and 1. As such it resembles the real contact area divided by the apparant contsct areaThe function of theexample tyre is shown in Figure 3.Figure 3 – Contact averaged tread pattern height versus the circumference.As can be seen from Equation 2 and Figure 3 the contact averaged tread pattern height function h̃(ϕ)varies around the tyre circumference. The tyre tread pattern and thus h̃(ϕ) repeats itself exactly after onerevolution around the tyre circumference ϕ = 0 . . .2π . The function h̃(ϕ) is thus periodic and continuousalong the circumferential ϕ-direction. A Fourier series reveals therefore the circumferential wavenumbers.This can be done for each axial location (w) as indicated by the lines shown in Figure 2 or for the contactaveraged tread pattern height function h̃(ϕ):h̃(ϕ) = 12 a0 +∞∑n=1An cos(nϕ +ϑn) (3)where the An represents the geometrical amplitude of the circumferential wavenumber n, also called order,and is defined by:|An|=√a2n +b2n (4)and ϑn is the phase of that geometrical wave:ϑn = arctan(bnan)(5)both calculated using the Fourier coefficients:an =1π∫ 2π0h̃(ϕ)cos(nϕ)dϕ (6)bn =1π∫ 2π0h̃(ϕ)sin(nϕ)dϕ (7)It is assumed that the interior sound pressure p(t) follows the same trend as the contact averaged treadpattern height:p(t(ϕ)) ∝ h̃(ϕ). (8)where the time t(ϕ) = ϕ/Ω with Ω is rotational speed of the tyre.Inter-noise 2014 Page 3 of 8Page 4 of 8 Inter-noise 20142.2 Human perception modelUsing the contact average tread pattern height as the source model the trends of the three relevant tyre treadpattern noise characteristics can be predicted.2.2.1 Level: Standard Deviation (STD)The variation of h̃(ϕ) around its mean value results in a similar acoustic pressure variation inside thevehicle. No material stiffness, tyre transmissiblity or vehicle transfer path is taken into account. Therefore themodel can be used in a comparitive manner. A simple metric describing the level of variation is the standarddeviation. The standard deviation of the averaged tread pattern height function, h̃ST D is therefore considered tobe a measure for the Sound Pressure Level inside the vehicle:h̃ST D =√∫ 2π0(h̃(ϕ)− h̃mean)2(9)The term between brackets will later be used and is the absolute deviation of each point in h̃(ϕ) from themean, also known as the variance. In Figure 3 the calculated standard deviation is shown to be 0.70%. In orderto reduce the noise level, the standard deviation of the averaged tread pattern height should be reduced.2.2.2 Tonalness: Order Prominence (OP)The result of the Fourier series analysis of h̃ST D of the example tyre is shown in Figure 4. In this so-calledorder spectrum the two fundamental orders corresponding with the amount of tread blocks can be identified,the58t h order originating from the two middle ribs and the 70t h order originating from the two shoulder ribs.The first harmonics of both can also be identified being 116 respectively 140. In this example tyre no pitchsequence, distributing the tread impact over more orders, is applied.Figure 4 – Order spectrum by Fourier series decomposition of the contact averaged tyre tread pattern height ofthe example tyre.Upon rotation of the tyre each circumfertial wavenumber will excite the tyre with the amplitude shown inthe order spectrum resulting in an impact frequency f [Hz] according to:f = nΩ = nv(2πR)(10)with n [-] is the order, Ω [Hz] the tyre rotation frequency, v [m/s] driving speed and R [m] is the rollingradius of a 235/45R17 tyre around 0.32 [m]. The order spectrum of the tyre tread pattern geometry is thusintrinsicly correlated with the tread impact frequencies (13), (14).A dedicated Sound Quality Metric using by the Prominence Ratio (15) is derived to obtain a scalar quantityfrom the order spectrum describing the amount of tonalness (16). This metric sums the amplitudes of theorders in 10 order wide range (representing the critical bands). The difference of each sum with it’s nearestneighbours is calculated. The maximum difference is defined as the Order Prominence (OP) value(16). As suchOP is a scalar quantity, to be used as the second tyre related Sound Quality Metric in the human perceptionmodel.Page 4 of 8 Inter-noise 2014Inter-noise 2014 Page 5 of 82.2.3 Modulation: Multi-Order Modulation (MOM)As mentioned, the term between brackets in Equation 9 is known as the variance h̃var(ϕ):h̃var(ϕ) = (h̃(ϕ)− h̃mean)2 (11)and is shown for the example tyre in Figure 5.Figure 5 – Variance of the contact averaged tread pattern height h̃var of the example tyre.Twelve peaks and valleys can be identified in the signal of h̃var(ϕ). These originate from a phenomenoncalled amplitude modulation (in acoustics called beating). Two sinusoidal signals of equal amplitude, but slightdifferent frequencies (ω1 < ω2) result in a signal of ω1 with a modulation frequency of |ω2−ω1|. For theexample tyre the two fundamental orders 58 and 70 are causing a beating frequency, called here a modulationorder, of 70-58=12.Tyres with a pitch sequence have all orders and contain thus many modulations. To determine the mostdominant modulations an enveloping procedure using the Hilbert Transform is applied to h̃(ϕ). A Fourierseries decomposition of the envelope reveals the modulation orders. As the human perception of the modulationdepends on the modulation frequency (17), a weighted sum of amplitudes of the modulation orders is appliedto obtain a single scalar quantity called the Multi-Order Modulation (MOM) (16).2.3 Sound Quality Preference IndexThe outline of the Sound Quality part of the research is shown in Figure 6 and can be split in two parts oncesounds are available from either a simulation or measurement. The Sound Quality calculation is the objectivepart calculating the Sound Quality Metrics described above. The Sound Quality Assessment is the subjectivepart and involves jury evaluations of the sound fragments.The human perception model is obtained by a linearregression of the subjective rating with the objective Sound Quality Metrics.Figure 6 – Outline of Sound Quality process used for establishing and validating the human perception model.Inter-noise 2014 Page 5 of 8Page 6 of 8 Inter-noise 2014A single subjective ranking, by which the human perception model can be fitted, is required for the humanperception model. It is therefore necessary that all three Sound Quality Metrics are present in one singlejury evaluation. In the current research 12 simulated sound fragments are created. The sound fragments of 3seconds are presented by head phones to the jury using a full Paired Comparison method. The test took about25 minutes per jury member. A small expert jury of 4 members is used, who are trained to evaluate tyre treadpattern noise on a daily basis (14).Figure 7 – Ranking of the 12 sound fragments and their standard deviation of the Sound fragments.The results of the Sound Quality Assessment is shown in Figure 7. In this figure the average ranking of thecomplete jury together with the standard deviation is shown. The maximum value is normalized to 10. TheSTD3 is highlighted as it is the reference sound from which all other metrics are varied independently.A linear regression of the subjective rating with the Sound Quality Metrics, STD, OP, MOM is exectuded.This results in the human perception model, called the Sound Quality Preference Index (SQPI):SQPI = Y0−α×ST D−β ×OP− γ×MOM (12)where α,β ,γ are coefficients and Y0 an off-set value.3. VALIDATIONTo validate the source model the interior noise is measured of a vehicle mounted on a drum. Using 28 tyresit is shown that the STD metric predicts the trend in the Sound Pressure Level (SPL) quite well(16). Figure 8shows the relative differences with respect to a referece tyre of the SPL (vertical axis) and h̃ST D (horizontalaxis). Clearly a trend is seen between h̃ST D and the measured SPL.The human perception model has been validated using sounds obtained by outdoor measurements. Of fivedifferent tyres the interior noise of a vehicle coasting down on a smooth road is measured. A jury assessmentusing headphones is executed to obtain a subjective ranking of these sounds. The SQPI of Equation 12 isused to predict the ranking. Figure 9 shows on the horizontal axis the prediction and on the vertical axis theobtained subjective ranking of the jury assessment. The high correlation indicates the quality of the humanperception model.4. CONCLUSIONSA new methodology and modelling approach to reduce the interior tyre tread pattern noise has beenproposed. The new source model describes the geometrical origin of tyre tread pattern noise with tyre treadpattern designs as an input. The human perception model describes the overall human perception of tyre treadpattern noise. Both models are validated and coupled by tyre related Sound Quality Metrics. The combinedsource-human perception model enables tyre designers to directly optimise the tyre tread pattern design to thehuman perception of the noise.ACKNOWLEDGEMENTSThe presented work is part of the project "Stil Veilig Wegverkeer" in the framework of GO and funded bythe "Europees Fonds voor Regionale Ontwikkeling" of the European Union together with Regio Twente andProvince Overijssel. Apollo Tyres Global R&D B.V. is gratefully acknowledged for the permission to publish.Page 6 of 8 Inter-noise 2014Inter-noise 2014 Page 7 of 8Figure 8 – Standard deviation of the averaged tread pattern height function versus the measured sound pressurelevel in values in percentage of a reference tyre.Figure 9 – Obtained ranking of jury evaluation versus the calculated Sound Quality Preference Index (SQPI).Inter-noise 2014 Page 7 of 8Page 8 of 8 Inter-noise 2014REFERENCES1. Verband Deutscher Ingenieure. VDI 2563: Noise components of vehicles: measurement and assessment.Duesseldorf, Germany; 1990.2. Buss S. Subjective perception of pattern noise, a tonal component of the tyre/road noise and its objectivecharacterisation by spectral analysis and calculating contours. University of Oldenburg. Oldeburg,Germany; 2006.3. Daniel P, Ellermeier W, Leclerc P. Tonalness and unpleasantness of tire sounds: Methods of assessmentand pyschoacoustical modelling. In: Proceedings of Euronoise 1998. München, Germany; 1998. .4. Daniel P, Ellermeier W, Vormann M. Computational and subjective procedures for the assessment ofsounds with weak tonal components. In: Proceedings of 16th international Congress on Acoustics (ICA).Seattle, Washington, United States of America; 1998. .5. Frank EC, Pickering DJ, Raglin C. In-vehicle tire sound quality prediction from tire noise data. SAEInternational. 2007;SAE Technical paper 2007-1-2253.6. Freeman T, Raglin C. Tire sound quality prediction - process improvements. In: Proceedings of SoundQuality Symposium 2008. Dearborn, Michigan, United States of America; 2008. .7. Varterasian J. Quieting noise mathematically - its applicaiton to snow tires. SAE International. 1969;SAETechnical paper 690520.8. Willet PR. Tire tread pattern sound generation. Tire Science and Technology. 1975;3(4):252–266.9. ; Method for improving tread noise by relative rotation of a rib and simulating the effect thereof, PatentUS4788651. US4788651; 1988.10. ; Method of developing tread pattern, Patent US6514366. US6514366; 2003.11. Ejsmont JA. Tire/road noise simulation for optimization of the tread pattern. In: Proceedings of Inter-noise2000. Nice, France; 2000. .12. ; Method of simulating tire tread noise and simulator therefor, Patent US5295087. US5295087; 1994.13. Bekke DA, Wijnant YH, Boer Ad. Experimental review on interior tire-road noise models. In: Proceedingsof ISMA 2010. Leuven, Belgium; 2010. .14. Bekke DA, Wijnant YH, Boer A. Modelling and evaluating interior tire-road noise. Journal of AcousticalSociety of the Netherlands. 2010;9.15. ECMA. ECMA-74 Measurement of airborne noise emitted by information technology and telecommuni-cations equipment. Geneva, Switzerland; 2012. Available from: http://www.ecma-international.org/publications/files/ECMA-ST/ECMA-74.pdf.16. Bekke DA. Engineering tools for interior tyre tread pattern noise. University of Twente. Enschede, TheNetherlands; 2014.17. Fastl H, Zwicker E. Psychoacoustics facts and models. Springer; 2005.Page 8 of 8 Inter-noise 2014

Tyre tread pattern noise optimization by a coupled source-human perception model

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Tyre tread pattern noise optimization by a coupled source-human perception model

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