Comfort analysis of car occupants: comparison between multibody and finite element models

Pennestrı̀, Ettore; Valentini, Pier Paolo; Vita, L.

doi:10.1504/ijvsmt.2005.008573

Cited by 26 publications

(31 citation statements)

References 11 publications

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“…Another interesting point is that the frequency of the highest accelerations of all signals is in the 0 to 20 Hz range, or ride range for road unevenness (0.5 < ν <20 Hz), something discerned in other studies [23][24][25][26][27]. Apart from that, human discomfort, when traveling in vehicles, has been proved to be more sensitive in low frequencies (from 3 to 10 Hz), above the vehicle's eigenfrequency, and higher acceleration, such as the data presented by [28] in a subjective discomfort assessment and in multibody approaches [7,29,30].…”

Section: -Frequency Domainmentioning

confidence: 50%

Comparison between vertical acceleration data from acquired signals and multibody model for an off-road vehicle

Fontoura

Passos²,

Bareta³

et al. 2018

Sci. cum Ind.

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SAE Mini Baja competitions require efforts in developing a reliable vehicle project that enables their teams to manage time and resources wisely. Vehicle simulations are one the best ways to deal with these conditions and prevent failure during a test. This work outlines the methodology that was carried out for validating the multibody dynamics model of a Mini Baja vehicle through vertical acceleration data acquisition. The data was acquired with the vehicle in different sets of obstacles, based on those seen in previously held competitions. Simulation was done through ADAMS/Car, with the vehicle's multibody model being simulated in different three-dimensional roads, counterpart to those where data acquisition took place. Simulation data, when compared to acquired acceleration signals for most of the obstacles, exhibited equivalence. Additional data computation revealed that the spectra in the frequency domain presented most severe loads concentrated between 0 and 20 Hz, incoming mostly from road unevenness. Gathering such data, by the presented approach can assist future analyses and guide the Baja Team in defining an improved project by predicting its dynamic behavior.

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Section: -Frequency Domainmentioning

confidence: 50%

Comparison between vertical acceleration data from acquired signals and multibody model for an off-road vehicle

Fontoura

Passos²,

Bareta³

et al. 2018

Sci. cum Ind.

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“…This is achieved with the component mode synthesis. Pennestrì 6 , et al developed numerical models to simulate the vibrational and postural comfort of car occupants. His approach was with multi-body dynamics model and also with finite element model.…”

Section: Introductionmentioning

confidence: 99%

Ride Dynamics of a Tracked Vehicle with a Finite Element Vehicle Model

Jothi

Balamurugan

Mohan

2016

DSJ

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Research on tracked vehicle dynamics is by and large limited to multi-rigid body simulation. For realistic prediction of vehicle dynamics, it is better to model the vehicle as multi-flexible body. In this paper, tracked vehicle is modelled as a mass-spring system with sprung and unsprung masses of the physical tracked vehicle by Finite element method. Using the equivalent vehicle model, dynamic studies are carried out by imparting vertical displacement inputs to the road wheels. Ride characteristics of the vehicle are captured by modelling the road wheel arms as flexible elements using Finite element method. In this work, a typical tracked vehicle test terrain viz., Trapezoidal blocks terrain (APG terrain) is considered. Through the simulations, the effect of the road wheel arm flexibility is monitored. Result of the analysis of equivalent vehicle model with flexible road wheel arms, is compared with the equivalent vehicle model with rigid road wheel arms and also with the experimental results of physical tracked vehicle. Though there is no major difference in the vertical bounce response between the flexible model and the rigid model, but there is a visible difference in the roll condition. Result of the flexible vehicle model is also reasonably matches with the experimental result.

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“…Other researchers attempted to simulate vehicle impact system via simplified linear visco-elastic one degree-of-freedom models [4,5]. Some others seek for further simplifications via equivalent square wave method [10], and multi-body model [12,13].…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of vehicle front structure in crash energy management using lumped mass spring system

Ofochebe

Ozoegwu

Enibe

2015

Adv. Model. and Simul. in Eng. Sci.

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Background: The design for vehicle structural crashworthiness which ensures that components of desired crash performance characteristics are used in product manufacturing essentially involves the evaluation of the energy absorption potentials of the structures using suitable computation method. Due to unresolved difficulties in achieving detailed results through the existing methods researchers seek for more alternative computation methods. Although previous efforts in this regard are quite significant, yet some concerns still exist on accuracy or computational efficiency achievable through the conventional methods. Method: The lumped mass spring (LMS) method is applied in the present study. Some new steps were introduced in the basic procedure to improve the accuracy and computational efficiency of the method. A new dynamic stiffness formula is written in terms of the specific energy absorption indices of the structural components. The new procedure allowed for standard state-space formulation of the crash problem. Results: The performance of the new simulation approach is tested for a typical vehicle structure in two possible orientations called normal mode and reversed mode. The results obtained for the impact problem in normal structural mode show that a desirable energy absorption pattern of 45%, 25% and 20% of the total impact energy could be achieved through plastic deformation of the front frame, sheet metal and torque box respectively. Testing the impact system in reversed structural mode results in a rather poor energy absorption pattern in which 2.5%, 50% and 43% of the total impact energy were absorbed through deformation of the front frame, sheet metal and torque box respectively, showing that unreasonably high percentage of the total impact energy is transmitted to the interior structures. Conclusion: The effort to quantify the energy absorbed by major vehicle front structure in both desirable and undesirable crash responses, and the computational efficiency achieved through the present method could help to enhance decision process during assessment of the components or prototype. It is found that good crash performance may be guaranteed by ensuring sufficiently high (up to 65%) contribution to the energy absorption scheme through the deformation of the foremost structures which includes the front frame and the sheet metal.

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Comfort analysis of car occupants: comparison between multibody and finite element models

Cited by 26 publications

References 11 publications

Comparison between vertical acceleration data from acquired signals and multibody model for an off-road vehicle

Comparison between vertical acceleration data from acquired signals and multibody model for an off-road vehicle

Ride Dynamics of a Tracked Vehicle with a Finite Element Vehicle Model

Performance evaluation of vehicle front structure in crash energy management using lumped mass spring system

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