Use of generated artificial road profiles in road roughness evaluation

Road roughness is an important factor in road network maintenance and ride quality. This paper proposes a road-roughness estimation method using the frequency response function (FRF) of a vehicle. First, based on the motion equation of the vehicle and the time shift property of the Fourier transform, the vehicle FRF with respect to the displacements of vehicle–road contact points, which describes the relationship between the measured response and road roughness, is deduced and simplified. The key to road roughness estimation is the vehicle FRF, which can be estimated directly using the measured response and the designed shape of the road based on the least-squares method. To eliminate the singular data in the estimated FRF, the shape function method was employed to improve the local curve of the FRF. Moreover, the road roughness can be estimated online by combining the estimated roughness in the overlapping time periods. Finally, a half-car model was used to numerically validate the proposed methods of road roughness estimation. Driving tests of a vehicle passing over a known-sized hump were designed to estimate the vehicle FRF, and the simulated vehicle accelerations were taken as the measured responses considering a 5% Gaussian white noise. Based on the directly estimated vehicle FRF and updated FRF, the road roughness estimation, which considers the influence of the sensors and quantity of measured data at different vehicle speeds, is discussed and compared. The results show that road roughness can be estimated using the proposed method with acceptable accuracy and robustness.

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Multi-Objective Optimisation of Tyre and Suspension Parameters during Cornering for Different Road Roughness Profiles

Applied Sciences ◽

10.3390/app11135934 ◽

2021 ◽

Vol 11 (13) ◽

pp. 5934

Author(s):

Georgios Papaioannou ◽

Jenny Jerrelind ◽

Lars Drugge

Keyword(s):

Optimal Solution ◽

Design Parameters ◽

Road Vehicles ◽

Propulsion Systems ◽

Vehicle Handling ◽

Optimum Parameters ◽

Trade Offs ◽

Road Roughness ◽

Control Technologies ◽

Tyre Wear

Effective emission control technologies and novel propulsion systems have been developed for road vehicles, decreasing exhaust particle emissions. However, work has to be done on non-exhaust traffic related sources such as tyre–road interaction and tyre wear. Given that both are inevitable in road vehicles, efforts for assessing and minimising tyre wear should be considered. The amount of tyre wear is because of internal (tyre structure, manufacturing, etc.) and external (suspension configuration, speed, road surface, etc.) factors. In this work, the emphasis is on the optimisation of such parameters for minimising tyre wear, but also enhancing occupant’s comfort and improving vehicle handling. In addition to the search for the optimum parameters, the optimisation is also used as a tool to identify and highlight potential trade-offs between the objectives and the various design parameters. Hence, initially, the tyre design (based on some chosen tyre parameters) is optimised with regards to the above-mentioned objectives, for a vehicle while cornering over both Class A and B road roughness profiles. Afterwards, an optimal solution is sought between the Pareto alternatives provided by the two road cases, in order for the tyre wear levels to be less affected under different road profiles. Therefore, it is required that the tyre parameters are as close possible and that they provide similar tyre wear in both road cases. Then, the identified tyre design is adopted and the optimum suspension design is sought for the two road cases for both passive and semi-active suspension types. From the results, significant conclusions regarding how tyre wear behaves with regards to passenger comfort and vehicle handling are extracted, while the results illustrate where the optimum suspension and tyre parameters have converged trying to compromise among the above objectives under different road types and how suspension types, passive and semi-active, could compromise among all of them more optimally.

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Surface roughness evaluation and morphology reconstruction of electrical discharge machining by frequency spectral analysis

Measurement ◽

10.1016/j.measurement.2020.108879 ◽

2021 ◽

Vol 172 ◽

pp. 108879

Author(s):

Han Wang ◽

Guanxin Chi ◽

Yuchao Jia ◽

Chuanyang Ge ◽

Fuxin Yu ◽

...

Keyword(s):

Surface Roughness ◽

Spectral Analysis ◽

Electrical Discharge ◽

Electrical Discharge Machining ◽

Roughness Evaluation

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Investigating the effect of road roughness on automotive component

Engineering Failure Analysis ◽

10.1016/j.engfailanal.2013.12.008 ◽

2014 ◽

Vol 41 ◽

pp. 96-107 ◽

Cited By ~ 16

Author(s):

Kazem Reza-Kashyzadeh ◽

Mohammad Jafar Ostad-Ahmad-Ghorabi ◽

Alireza Arghavan

Keyword(s):

Automotive Component ◽

Road Roughness

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Digital Object Memory Integration into Indirect Surface Roughness Measurement in Turning

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.465-466.764 ◽

2013 ◽

Vol 465-466 ◽

pp. 764-768 ◽

Cited By ~ 1

Author(s):

Tanel Aruväli ◽

Tauno Otto

Keyword(s):

Surface Roughness ◽

Tool Wear ◽

Digital Object ◽

Roughness Measurement ◽

Object Memory ◽

Surface Roughness Measurement ◽

Memory Integration ◽

Evaluation Time ◽

Roughness Evaluation ◽

Influencing Parameters

The paper investigates in-process signal usage in turning for indirect surface roughness measurement. Based on theoretical surface roughness value and in-process signal, a model is proposed for surface roughness evaluation. Time surface roughness and in-process signal surface roughness correlation based analysis is performed to characterize tool wear component behavior among others. Influencing parameters are grouped based on their behavior in time. Moreover, Digital Object Memory based solution and algorithm is proposed to automate indirect surface roughness measurement process.

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