IRI Estimation by the Frequency Domain Analysis of Vehicle Dynamic Responses

• Published in: Procedia engineering Vol. 188; pp. 9 - 16
• Main Authors: Zhao, Boyu, Nagayama, Tomonori
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 2017
• Subjects: road condition evaluation; vehicle dynamic response; vehicle model identification; road condition evaluation; vehicle model identification; vehicle dynamic response
• ISSN: 1877-7058; 1877-7058
• DOI: 10.1016/j.proeng.2017.04.451

Smartphone based Dynamic Response Intelligent Monitoring System (iDRIMS) was developed to evaluate International Roughness Index (IRI) based on dynamic responses of ordinary vehicles [1]. However, the robustness and accuracy were limited. In this paper, iDRIMS is improved mainly by employing frequency domain analysis. The algorithm consists of two steps. The first step is to identify the vehicle model and the second step is to estimate the IRI by utilizing the identified vehicle model. In the first step, a half car (HC) model is selected as the vehicle model and its parameters are identified. The vehicle parameters are identified through a drive tests over a portable hump with a known size. As opposed to previous approach in the time domain using Unscented Kalman filter, the parameters are optimized to minimize the difference between simulation and measured hump responses in the frequency domain using genetic algorithm (GA). IRI is then estimated by measuring acceleration responses of ordinary vehicles. Measured acceleration is converted to the acceleration RMS of the sprung mass of standard quarter car by multiplying a transfer function. The transfer function, estimated through the simulation of the identified HC model as opposed to a QC model in previous approaches, reflects the vehicle pitching motions and sensor installation location. The RMS is further converted to IRI. Numerical simulation is conducted to investigate the IRI estimation performance in terms of various drive speeds and sensor locations. Experiment is carried out at a 13km road. Inacurate IRI estimation at speed change section is invesigated and compensated. Results from both simulation and experiment indicate that the proposed method accurately estimate IRI with high robustness and efficiency.