Uncertainty analysis of vehicle fuel consumption in twin-roller chassis dynamometer experiments and simulation models. (February 2023)

• Record Type: Journal Article
• Authors: Lourenço, Maria Augusta de Menezes; Eckert, Jony Javorski; Silva, Fabrício Leonardo; Miranda, Matheus Henrique Rodrigues; Silva, Ludmila Corrêa de Alkmin e
• Is Part Of: Mechanism and machine theory. Volume 180(2023)
• Publication Date: 2023-02
• Subjects: Uncertainty analysis -- Fuel consumption -- Chassis dynamometer -- Vehicle simulation -- Experimental validation; Machine theory -- Periodicals; Machinery -- Periodicals; Machines -- Périodiques; Génie mécanique -- Périodiques; Machine theory; Machinery; Periodicals; 621.81
• DOI: 10.1016/j.mechmachtheory.2022.105126
• Languages: English
• ISSNs: 0094-114X

Abstract

Abstract: Chassis dynamometers are one of the main test benches applied to vehicle development and homologation, however, vehicle experiments and simulations present associated uncertainties. Thus, aiming to allow previous analyses to assist the vehicle homologation process, this research analyzes uncertainties and their impacts on fuel consumption on a vehicle-dynamometer testing simulation on Matlab/Simulink™, under a driving cycle, and experimentally validated. The paper analyzes the developed model inputting variations (speed profiles, tire parameters, and rolling resistance coefficient) and quantifies the fuel consumption response and its uncertainties, comparing them with experimental results. The results showed the experimental fuel consumption (0.9985 ± 0.0522 (l)) compared to the ones submitted to input variations. Among these, the rolling coefficient was the most influential factor (0.9670 ± 0.1338 (l)). The final variation analysis presented the mean value closest to the experimental (0.9951 ± 0.0959 (l) and mean error of 0.33%). The simulation allows reproducing experiments virtually, mitigating experimental time and cost spent on real benches, and providing an analysis tool in order to help the vehicle homologation. Graphical abstract: Highlights: Fuel consumption uncertainties through twin-roller chassis dynamometer simulation. Driver styles, tire parameters, and rolling coefficient impact fuel consumption. The rolling resistance coefficient is the most influential on fuel consumption. Vehicle-bench simulation with tire-roller slip, bench losses, and rolling resistance. Virtual experiments of vehicle and chassis dynamometer bench under a driving cycle.