Vehicle drivetrain design multi-objective optimization. (February 2021)

• Record Type: Journal Article
• Authors: Eckert, Jony Javorski; Santiciolli, Fabio Mazzariol; Silva, Ludmila C.A.; Dedini, Franco Giuseppe
• Is Part Of: Mechanism and machine theory. Volume 156(2021)
• Publication Date: 2021-02
• Subjects: Drivetrain design -- Gear shifting strategies -- Fuel economy -- Vehicle performance -- Genetic algorithms; Machine theory -- Periodicals; Machinery -- Periodicals; Machines -- Périodiques; Génie mécanique -- Périodiques; Machine theory; Machinery; Periodicals; 621.81
• DOI: 10.1016/j.mechmachtheory.2020.104123
• Languages: English
• ISSNs: 0094-114X

Abstract

Highlights: Drivetrain optimizations for fuel economy, emissions reduction and performance. Design variables consist of existing and modular vehicle parts. Gear shifting map derived from the optimizations and applicable for AMT software. Adaptive shifting control according to the engine temperature to mitigate emissions. Trade-off between antagonistic optimization objectives has been found. Abstract: This paper presents a multi-objective optimization aiming to improve vehicle fuel consumption, acceleration performance and mitigate emissions. The optimization considers design variables such as the gearbox gear ratios, the gear numbers, the differential gear ratio, tire size and gear shifting control of the automated manual transmission. The simulation model of the vehicle longitudinal dynamics was implemented in the Simulink™interface, with the addition of the ADVISOR™fuel converter block, which is used in several works as benchmark to emissions and fuel consumption simulation. Moreover, the optimization is conducted under three driving cycles, FTP-75 (urban driving), HWFET (highway) and the US06 (high acceleration and speed), aiming to ensure that the optimized drivetrain configuration is robust to different driving conditions. The optimization problem was solved by the Interactive Adaptive-Weight Genetic Algorithm (i-AWGA), reaching the best-compromised solution, which was able to enhance acceleration performance as compared to the standard vehicle configuration, saving 14.53% fuel and decreasing the emissions in 0.68% CO, 23.68% NOx and 2.45% HC .