Combining Powertrain Efficiency and Drivability for Optimizing Hybrid Development

Abstract

It is undisputed that vehicle hybridization has become one of the most prospective solution to the global energy and environmental problems caused by the transport sector. After having experienced a rapid development, Hybrid Electric Vehicles (HEV) are widely recognized by more and more customers and gradually dominating the automobile market by their remarkable performance, fuel economy and emission reduction. To survive the fierce market competition and to meet the increasingly strict emission regulation, many car manufacturers are looking to decrease development time and cost. Part of the actions in order to shorten development time, the demand for virtual optimization and evaluation, as well as early drivability and high level customer experience is needed. This thesis is aimed at exploring the possibility of having access to the drivability evaluation and optimization virtually. The first part involves identifying all the necessary signals and generating the missing signals. The second part involves establishing the signal connection between GT-Suite and AVL-Drive. The third part involves evaluating the drivability using the AVL-Drive and carrying out the drivability optimization on targeted operation modes. In total, 12 vehicle signals are requested for a drivability assessment in AVL-Drive and three of them (Brake State, Brake Pedal Position and Accelerator Pedal Position) have been generated successfully. With the help of Matlab, the signal connection between GT-Suite and AVL-Drive has been created and the drivability reference objects of a competitor vehicle and LYNK&CO 01 are provided for comparison. The drivability ratings of engine start and gear shift selected as the targeted operation modes have been improved significantly.