In the last few years, the number of Advanced Driver Assistance Systems (ADAS) on road vehicles has been increased with the aim of dramatically reducing road accidents. Therefore, the OEMs need to integrate and test these systems, to comply with the safety regulations. To lower the development cost, instead of experimental testing, many virtual simulation scenarios need to be tested for ADAS validation. The classic multibody vehicle approach, normally used to design and optimize vehicle dynamics performance, is not always suitable to cope with these new tasks; therefore, real-time lumped-parameter vehicle models implementation becomes more and more necessary. This paper aims at providing a methodology to convert experimentally validated light commercial vehicles (LCV) multibody models (MBM) into real-time lumped-parameter models (RTM). The proposed methodology involves the definition of the vehicle subsystems and the level of complexity required to achieve a good match between the simulation results obtained from the two models. Thus, an automatic vehicle model converter will be presented together with the assessment of its accuracy. An optimization phase is included into the conversion tool, to fine-tune uncertain vehicle parameters and to compensate for inherent modelling differences. The objective function of the optimization is based on typical performance indices used for vehicle longitudinal and lateral dynamics assessment. Finally, the simulation results from the original and converted models are compared during steady-state and transient tests, to prove the conversion fidelity.
Light Commercial Vehicle ADAS-Oriented Modelling: An Optimization-Based Conversion Tool from Multibody to Real-Time Vehicle Dynamics Model / Zerbato, L.; Galvagno, E.; Tota, A.; Mancardi, L.; Velardocchia, M.; Nosenzo, V.; Verrilli, G.; Voglino, A.. - In: SAE TECHNICAL PAPER. - ISSN 0148-7191. - ELETTRONICO. - 1:(2023), pp. 1-11. (Intervento presentato al convegno WCX SAE World Congress Experience tenutosi a Detroit, MI nel 18-20 April 2023) [10.4271/2023-01-0908].
Light Commercial Vehicle ADAS-Oriented Modelling: An Optimization-Based Conversion Tool from Multibody to Real-Time Vehicle Dynamics Model
Zerbato L.;Galvagno E.;Tota A.;Mancardi L.;Velardocchia M.;
2023
Abstract
In the last few years, the number of Advanced Driver Assistance Systems (ADAS) on road vehicles has been increased with the aim of dramatically reducing road accidents. Therefore, the OEMs need to integrate and test these systems, to comply with the safety regulations. To lower the development cost, instead of experimental testing, many virtual simulation scenarios need to be tested for ADAS validation. The classic multibody vehicle approach, normally used to design and optimize vehicle dynamics performance, is not always suitable to cope with these new tasks; therefore, real-time lumped-parameter vehicle models implementation becomes more and more necessary. This paper aims at providing a methodology to convert experimentally validated light commercial vehicles (LCV) multibody models (MBM) into real-time lumped-parameter models (RTM). The proposed methodology involves the definition of the vehicle subsystems and the level of complexity required to achieve a good match between the simulation results obtained from the two models. Thus, an automatic vehicle model converter will be presented together with the assessment of its accuracy. An optimization phase is included into the conversion tool, to fine-tune uncertain vehicle parameters and to compensate for inherent modelling differences. The objective function of the optimization is based on typical performance indices used for vehicle longitudinal and lateral dynamics assessment. Finally, the simulation results from the original and converted models are compared during steady-state and transient tests, to prove the conversion fidelity.File | Dimensione | Formato | |
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Light commercial vehicle ADAS oriented modelling an optimization based conversion tool from multibody to real-time vehicle dynamics model_FINAL.pdf
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2023-01-0908_SAE.pdf
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https://hdl.handle.net/11583/2979977