Objective Evaluation Of CVT Car Drivability Under Starting And Accelerating Conditions

With the gradual maturity of the domestic automobile market,competition in the automotive industry will become more and more fierce.In addition to fuel economy and power,drivability will become one of the important factors for consumers to focus.Therefore,improving vehicle driving will become a reality for manufacturers.An important approach to differentiated competition,the foundation for improving drivability is to establish an evaluation system for drivability.In order to realize the in-depth study of driving performance of the company,the objective evaluation method of driving performance is selected after analysis in this paper.Taking an enterprise vehicle model as the research object,starting from the subjective perception of the driver,the objective evaluation index for fixed acceleration at the starting condition is selected.And define the index parameters,conduct driving tests according to the selected parameters,in order to obtain reliable index parameters,select reliable signal processing methods for different indexes,and finally use the obtained processed parameters as the input of the objective evaluation system to measure the equipment The scoring model is used as the expected value,and a BP neural network prediction model is established.The main research contents and results of this article are as follows:(1)According to the characteristics of the enterprise vehicle model,aiming at the starting condition and the fixed throttle acceleration in the acceleration condition,starting from the subjective perception of the driver,a comprehensive objective evaluation index of driving performance was selected,and the parameters of each index were defined.(2)A driving signal acquisition test plan was formulated,in which the vehicle operation during the test was in accordance with the index requirements,and the experimental equipment used AVL-Drive,and the measurement sensor installation was simplified according to the characteristics of the working conditions.(3)Because the driving data obtained are original data,including various disturbance signals,a variety of data processing methods are selected,and data processing is performed according to different objective indicators.The fluctuation of objective index parameters is repeatedly tested as a signal processing method.Selection criteria,and finally a reliable signal processing method was selected for each objective evaluation index.(4)Take the model score of AVL-Drive as the expected value,and take the parameters obtained by the parameter processing method selected in this paper as independent inputs to construct a BP neural network prediction model and verify the prediction model.