Evaluation of Objective Drivability for Passenger Cars Based on Hierarchical Mixture Model: A Case Study of Downshift Condition 2021-01-0716

In order to solve the problems of insufficient accuracy for theoretical models and data-driven models for objective drivability evaluation requiring a large amount of data, an objective drivability evaluation method based on a hierarchical mixture model is proposed. First, a novel method of constructing a drivability evaluation system is developed, which combined by work breakdown structure (WBS) and analytic hierarchy process (AHP). Then, downshift condition is taken as a case study, and the subdivision condition is identified based on the hybrid mixture model. What's more, the drivability evaluation indexes of downshift condition are analyzed to establish the evaluation system of drivability. Finally, combined with the real road test, the comprehensive weighting method is used to construct the downshift drivability evaluation model, in which the subjective weight is determined by the fuzzy AHP, and the objective weight is determined by criteria improved through inter-criteria correlation (CRITIC) method. The test results show that the evaluation method proposed in this paper has good reliability and provides effective guidance for the objective drivability evaluation of passenger cars.

The evaluation system proposed in this paper can be extended to other conditions of vehicle drivability evaluation, including engine start conditions, static shift conditions, idling conditions, crawling conditions, starting conditions, Tip in/Tip out conditions, upshifts conditions and shutoff conditions. At the same time, the subjective and objective weight determination methods proposed in this paper can provide certain theoretical support for evaluation, classification and decision-making.