In order to improve the driving experience of drivers and the efficiency of vehicle development, a method of objective drivability for passenger car powertrain is proposed, which is based on prior knowledge, principal component analysis (PCA) and SMART principle. First, drivability parameters of powertrain for passenger cars are determined according to working principle of powertrain, including engine torque, engine speed, gearbox position, accelerate pedal, brake pedal, steering wheel angle, longitudinal acceleration and lateral acceleration, etc. The drivability quantitative index system is designed based on field test data, prior knowledge and SMART principles. Then, D-S evidence theory and sliding window method are applied to identify objective drivability evaluation conditions of powertrain for passenger cars, including static gearshift conditions, starting conditions, creep conditions, tip-in, tip out, upshift conditions, acceleration, downshift conditions and de-acceleration. In addition, a quantitative index coupling analysis model is constructed by PCA, Kaiser-Meyer-Olkin (KMO) and correlation analysis are used to streamline the evaluation indicators by combining expert knowledge. Finally, fuzzy analytic hierarchy process (FAHP) is applied to build an objective index and subjective score mapping analysis model, and the tip-in condition is used as a case study to verify the reliability and accuracy of the objective evaluation model for the powertrain drivability proposed in this paper.
This research can be used as a key reference for achieving the objective evaluation of passenger cars, including drivability, vehicle comfort and handling stability, and also provides a theoretical basis for the evaluation of drivability for new energy vehicles and autonomous vehicles.