Title: Parametric vehicle mass estimation for optimisation

Authors: Robert J. Mau; Paul J. Venhovens

Addresses: R J Mau Solutions, LLC, 120 Todd Avenue, Laurens, South Carolina, 29360, USA ' Clemson University International Center for Automotive Research (CU-ICAR), 4 Research Drive Greenville, South Carolina, 29607, USA

Abstract: In order to perform optimisation of parametric vehicle designs in the conceptual design phase of vehicle development, before detailed design information and styling are defined, it is necessary to estimate the mass of significant vehicle subsystems and the resulting total vehicle curb mass as accurately as possible. This work develops estimation relationships for a number of subsystems and assesses the resulting correlations to actual vehicle subsystem and curb mass data. The mass estimation relationships have been intentionally developed using a minimal set of vehicle parameters (overall length, width, height, wheelbase and engine power) to simplify the process and increase the speed of optimisation iterations. Several of the subsystem estimations can also be used in determining vehicle centre of gravity location. Separate mass relationships for steel and aluminium have been developed for Body in White and closure mass estimation. Additional mass relationships for hybrid vehicles will be included in future work.

Keywords: mass estimation; body in white; parametric modelling; conceptual design; correlation; optimisation; vehicle curb mass; vehicle interior mass; vehicle suspension mass; vehicle engine mass; vehicle design; vehicle subsystems; vehicle centre of gravity; steel; aluminium.

DOI: 10.1504/IJVD.2016.079202

International Journal of Vehicle Design, 2016 Vol.72 No.1, pp.1 - 16

Accepted: 09 Apr 2015
Published online: 22 Sep 2016 *

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