IRI (International Roughness Index): An Indicator Of Vehicle Response

Pawar, Prashant R.; Saraf, M. R.

doi:10.1016/j.matpr.2018.02.143

Cited by 25 publications

(15 citation statements)

References 14 publications

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“…IRI is measured in m/km, i.e. the amount of asperities per km [23,24]. The IRI value, for each case under test, is reported in Table 2, whereas Figure 3 is the Simulink scheme of the regenerative SA of Figure 2.…”

Section: Simulink Model and Simulation Results For Three Casesmentioning

confidence: 99%

Simulink Model of a Regenerative Shock Absorber

Vergura¹

2020

REPQJ

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The field of the Electric Vehicles (EVs) is becoming a strategic laboratory for new solutions focused on the energy saving and/or the renewable energy sources. Regenerative brakes are well known and already applied in recent cars. In this paper, instead, the attention is focused on a regenerative Shock Absorber (SA), which converts its vibration-induced by the road roughness-in electrical energy. The vibration is transmitted to an electric generator through a mechanical component. Finally, the produced energy can be stored in a super capacitor for a future use. The paper proposes a Simulink-based model of this regenerative SA and compares the energy performance when the vehicle travels roads with different roughness, scientifically defined by means an index, said IRI.

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Section: Simulink Model and Simulation Results For Three Casesmentioning

confidence: 99%

Simulink Model of a Regenerative Shock Absorber

Vergura¹

2020

REPQJ

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show abstract

“…For profiling, various devices such as a straightedge, a dipstick, the Merlin machine, and an inertial profiler have commonly been used [39,40]. Response-based devices (displacement or acceleration sensors, equipped trailers, or vehicles) are widely applied due to fast processing and low-cost equipment availability [41][42][43][44][45][46][47]. Monitoring the state and quality of unpaved roads can be based on visual observations and in-person surveying, contrary to paved road evaluations in which data are collected automatically [48].…”

Section: Related Workmentioning

confidence: 99%

“…The profile of gravel pavement cannot be approximated with the waviness of w = 2 used in ISO 8608, which usually occurs on paved roads [46]. Múčka [71] reported that up to 40% of roads had differences in wavebands, and 20% of tested sections had short wave unevenness (w > 2).…”

Section: Indexes For Gravel Road Quality Assessmentmentioning

confidence: 99%

Variability of Gravel Pavement Roughness: An Analysis of the Impact on Vehicle Dynamic Response and Driving Comfort

et al. 2021

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Gravel pavement has lower construction costs but poorer performance than asphalt surfaces on roads. It also emits dust and deforms under the impact of vehicle loads and ambient air factors; the resulting ripples and ruts constantly deepen, and therefore increase vehicle vibrations and fuel consumption, and reduce safe driving speed and comfort. In this study, existing pavement quality evaluation indexes are analysed, and a methodology for adapting them for roads with gravel pavement is proposed. We report the measured wave depth and length of gravel pavement profile using the straightedge method on a 160 m long road section at three stages of road utilization. The measured pavement elevation was processed according to ISO 8608, and the frequency response of a vehicle was investigated using simulations in MATLAB/Simulink. The international roughness index (IRI) analysis showed that a speed of 30–45 km/h instead of 80 km/h provided the objective results of the IRI calculation on the flexible pavement due to the decreasing velocity of a vehicle’s unsprung mass on a more deteriorated road pavement state. The influence of the corrugation phenomenon of gravel pavement was explored, identifying specific driving safety and comfort cases. Finally, an increase in the dynamic load coefficient (DLC) at a low speed of 30 km/h on the most deteriorated pavement and a high speed of 90 km/h on the middle-quality pavement demonstrated the demand for timely gravel pavement maintenance and the complicated prediction of a safe driving speed for drivers. The main relevant objectives of this study are the adaptation of a road roughness indicator to gravel pavement, including the evaluation of vehicle dynamic responses at different speeds and pavement deterioration states.

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“…For profiling, various devices as a straightedge, a dipstick, the Merlin machine and an inertial profiler are commonly used [39,40]. Response based devices (displacement or acceleration sensors, equipped trailers or vehicles) are widely applied due to fast processing and low-cost equipment available [41,42,43,44,45,46,47]. Monitoring the state and quality of the unpaved roads can be based on visual observations and in-person surveying, contrary to paved road evaluation when data are collected automatically [48].…”

Section: Related Workmentioning

confidence: 99%

“…For general use, the road roughness indicator usually takes the values of 1.75 < < 2.25 [61] and for ISO classification assuming constant velocity PSD, = 2. The gravel pavement profile cannot be approximated with the waviness of w = 2 used in ISO 8608, which usually occurs on paved roads [46]. Múčka [62] reviewed that up to 40% of roads had differences in wavebands, and 20% of sections had short wave une-venness ( > 2).…”

Section: Indexes For Gravel Road Quality Assessmentmentioning

confidence: 99%

Variability of Gravel Pavement Roughness: Analysis of the Impact on Vehicle Response and Driving Comfort

Žuraulis¹,

Sivilevičius²,

Šabanovič³

et al. 2021

Preprint

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The gravel road pavement has a lower construction cost but poorer performance than the asphalt surface. It also emits dust and deforms under the impact of vehicle loads and ambient air factors. The resulting ripples and ruts are constantly deepening, increasing vehicle vibrations and fuel consumption, reducing safe driving speed and comfort. In this article, existing pavement quality evaluation indexes are analysed, and a methodology for their adaptation for roads with gravel pavement is proposed. This article reports the measured wave depth and length of the gravel pavement profile by the straightedge method of a 160 m long road section in three road exploitation stages. The measured pavement elevation was processed according to ISO 8608, and vehicle frequency response has been investigated using simulations in MATLAB/Simulink. The applied International Roughness Index (IRI) analysis showed that a speed of 30-45 km/h instead of 80 km/h provides the objective results of IRI calculation on the flexible pavement due to a decreasing velocity of vehicle's unsprung mass on a more deteriorated road pavement state. The influence of the corrugation phenomenon of gravel pavement has been explored, identifying specific driving safety and comfort cases. Finally, an increase in the Dynamic Load Coefficient (DLC) at a low speed of 30 km/h on the most deteriorated pavement and a high speed of 90 km/h on the middle-quality pavement demonstrates the demand for timely gravel pavement maintenance and the complicated prediction of a safe driving speed for drivers.

show abstract

IRI (International Roughness Index): An Indicator Of Vehicle Response

Cited by 25 publications

References 14 publications

Simulink Model of a Regenerative Shock Absorber

Simulink Model of a Regenerative Shock Absorber

Variability of Gravel Pavement Roughness: An Analysis of the Impact on Vehicle Dynamic Response and Driving Comfort

Variability of Gravel Pavement Roughness: Analysis of the Impact on Vehicle Response and Driving Comfort

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