Eduardo dos Santos Costa

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.

A study of battery power for a different electric vehicle propulsion system

This paper presents a simulation of an electric vehicle propulsion system. The simulation assumes BLDC motors combined with a proportional-integral controller and batteries. Regarding the longitudinal dynamics of electric vehicles (EV), models of different components and configurations are introduced and simulated. The simulations show the potential of each configuration according to the battery size. Thus, the objective is to find the best configuration (batteries size and propulsion system setup), keeping the original drivability. Six different configurations will be analyzed using the standard Brazilian urban driving cycle NBR6601. A rule-based method is used in the power management strategy that indicates the batteries states. This information aids the decision on the correct specification of the battery for each simulated configuration according to some restrictions.

Gear shifting multi-objective optimization to improve vehicle performance, fuel consumption, and engine emissions

ABSTRACT In the present work, the Adaptive-Weight Genetic Algorithm was employed in order to determine the gear shifting strategies that allow an automobile to work in the best compromise among fuel consumption, engine emissions, and vehicle performance. For the assessment of each of the three objective functions, a simulation model based on engine data and on the well-established equations of the longitudinal dynamics was developed. The driving cycle chosen for the calculations was the FTP-75, which takes into account both cold and hot starts, meaning that the transient operation during the warm-up of the catalyst is also considered.

Study of Different Electric Vehicle Propulsion System Configurations

This paper presents a study of an electric vehicle (EV) with two different drive systems and three available electric motors (EMs) configurations. The EMs are BLDC (Brushless Direct Current) motors combined with a proportional-integral controller (PI). The vehicle power demand is divided between the drive systems through rules based vehicle power management control (PMC) that aims to reduce the lithium-ion battery discharges during the Brazilian urban driving cycle NBR6601. The results indicate the potential of each simulated configuration and the combination drive system/EM in which present the lower battery discharge. Each EV configuration is compared and the best configuration is defined.

Gear Shifting Strategy to Improve the Parallel Hybrid Vehicle Fuel Consumption

The hybrid electric vehicle (HEV) is an alternative to reduce the engine fuel consumption due to the extra electrical power addition in the system that allows changing the engine operation point for a better efficiency region. The gear shifting strategy is a way to modify the engine operation point and it can be combined with the power management strategy to reach a better operational condition. The aim of this study was to analyze the influence of the gear shifting strategy in the HEV configuration, comparing a conventional 1.0L vehicle with a parallel HEV.