Search Results

The drivability plays an important role for marketability and competitiveness of passenger car in meeting some customer requirements, which directly affects the driving experience and the desire of purchasing. In this paper, a framework of objective drivability evaluation with multi-source information fusion for passenger car is proposed. At first, according to vehicle powertrain system and optimization theory, certain vehicle performances, which are closely related to objective drivability are analyzed, including vehicle longitudinal acceleration, vehicle speed, engine torque, engine speed, gear position, accelerator pedal, brake signal and voltage signal. Then, combined with the evaluation criterion of signal-to-noise ratio (SNR), mean error (ME), root mean squared error (RMSE) and signal smoothness (SS), a de-noising method is developed for the drivability evaluation information.

In order to improve the drivability of passenger cars with dual clutch transmission (DCT) and reveal the criteria for objective evaluation criteria and characteristic index and feature index division of vehicles under specific working conditions, a drivability evaluation system that integrates data-driven and the consistency between subjective and objective is proposed. At first, combined with the control principle and dynamics theory of specific working conditions, a quantitative index system of vehicle drivability is constructed, including three modules: data source, evaluation working conditions and objective indicators. Then, a novel intelligent drivability objective evaluation tools (I-DOET) is designed, including data acquisition, de-noising, working condition recognition, feature extraction and automatic scoring.