Validation of Computer Simulations of Vehicle Dynamics

Bernard, J. E.; Clover, C.L.

doi:10.4271/940231

Cited by 26 publications

(13 citation statements)

References 5 publications

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“…For example, a vehicle model is developed for durability analysis but is only validated against accelerations. This approach may have certain risks involved such as stated in reference [11]. They use the example of a vehicle doing a severe J-turn with the assumption that the measured yaw rate and lateral acceleration are available from vehicle tests, but measured normal loads on the tyres are not.…”

Section: Verificationmentioning

confidence: 99%

Validation metric based on relative error

Kat

Schalk

2012

Mathematical and Computer Modelling of Dynamical Systems

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-Engineers and scientists are often faced with the problem of objectively comparing time histories of measured and/or simulated data. This paper presents a reliable and intuitive validation metric for use in the validation process. The proposed validation metric is able to quantify the agreement/disagreement between deterministic system response quantities of interest obtained from measurements on a physical system and predictions from a mathematical model. The validation metric is based on the relative error and the challenges concerning the use of the relative error on periodic signals are addressed. The validation metric is compared to similar metrics and their advantages and limitations are discussed. The results show that the proposed validation metric gives a comprehensive error that is able to quantify the agreement between two periodic signals and is easily interpretable.

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Section: Verificationmentioning

confidence: 99%

Validation metric based on relative error

Kat

Schalk

2012

Mathematical and Computer Modelling of Dynamical Systems

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“…If the gas is, for example, compressed from state 1 to state 2, Equation 1 can be re-written as: (2) If the temperature is constant during this compression ( ) it is an isothermal process and the following relation can be used:…”

Section: Ormentioning

confidence: 99%

“…This is emphasised by [1] who states that simulations offer great advantages over physical prototypes, but in order to obtain meaningful results the model should be validated using the correct parameters. Bernard and Clover [2] define validation within the context of vehicle simulation as: "the process of gaining confidence that the calculations yield useful insight into the behaviour of the simulated vehicle. "…”

Section: Introductionmentioning

confidence: 99%

Comparison of different gas models to calculate the spring force of a hydropneumatic suspension

Westhuizen

Schalk

2015

Journal of Terramechanics

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When developing any simulation model some compromise must be made between computational efficiency and the accuracy of the model. This study compares the performance of three ideal gas (IG) law variations (IG with the energy equation (EE), isothermal and adiabatic), and two real gas approaches (Benedict Webb Rubin (BWR) equation with and without the EE) to model the spring force of a hydropneumatic suspension. These models are compared with experimental data obtained from laboratory tests on a single hydropneumatic suspension unit. Both the BWR and IG models with the EE offer a significant improvement in correlation compared to the models without the EE. The real gas BWR approach offers a small improvement over the IG approach under the test conditions. The best (BWR with EE) and worst (IG isothermal) models are then used to model the spring forces in a full vehicle model of a 4x4 Sports Utility vehicle (SUV). The data is again compared with experimental results and the BWR model with the EE correlates significantly better than the IG isothermal model. It is thus concluded that the inclusion of the EE will yield significantly better results and it should only be omitted if the parameters investigated are not sensitive to errors in the spring model.

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“…Reference [5] shows it is impossible to know if either the equations of motion or the in put data to a nonlinear vehicle simulation is error free, but that continued checking leads to increasing confidence that whatever errors may be in the simulation are inconsequential. In that spirit, the DOM has included a set of sanity checks, acceleration gain, understeer gradient and the like, that are designed to detect errors in the linear range.…”

Section: Sanity Checksmentioning

confidence: 99%

Exploring rollover performance of road vehicles

Balling¹

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Validation of Computer Simulations of Vehicle Dynamics

Cited by 26 publications

References 5 publications

Validation metric based on relative error

Validation metric based on relative error

Comparison of different gas models to calculate the spring force of a hydropneumatic suspension

Exploring rollover performance of road vehicles

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