Heron José Dionísio

Gear Shifting Strategies Co-simulations to Optimize Vehicle Performance and Fuel Consumption

The vehicle longitudinal dynamics is responsible for calculating the vehicle power consumption to attend a specific route, estimating, by the equations, the forces acting on the system such as aerodynamic drag, rolling resistance, climbing resistance and the driver behavior. The gear shifting strategies influence significantly in the vehicle acceleration performance and fuel consumption because it changes the powertrain inertia and the engine speed. The literature presents gear shifting strategies based on the engine power and torque. A fuel economy strategy is more difficult to determine, because it depends on a large number of factors like the engine efficiency, vehicle speed, transition ratio and required acceleration. This paper presents a study based on the US06 standard velocity profile, in which the high speeds and acceleration stretches create a situation where the vehicle performance is limited by the engine available power and by the tire-ground traction limit. Because of the many factors involved in the vehicle behavior, it was developed an algorithm to optimize the gear shifting process to choose the more adequate strategy to each stretch. The analysis were performed by co-simulation between the multibody dynamics software Adams\( ^{\rm{TM}} \) and Matlab/Simulink\( ^{\rm{TM}} \), where is defined the vehicle power demand.

Vehicle gear shifting strategy optimization with respect to performance and fuel consumption

ABSTRACT Based on the movement resistance forces, the vehicle longitudinal dynamics is related to power demand for a specific route. The vehicle gear shifting influences significantly the acceleration performance and fuel consumption because it changes the engine operation point and the powertrain inertia. This paper presents a study based on the US06 velocity profile that involves high speed and high acceleration phases, where the vehicle performance is limited by both the engine power and the tire traction limit. For improving the vehicle performance without increasing fuel consumption, a genetic algorithm (GA) technique is used.