Modeling and Identification of Longitudinal Responses of an Electric Vehicle for Drivability Improvement

Abstract

This paper develops a control-oriented drivability model for an electric vehicle. First, we establish a discrete-time nonlinear input-output mechanism model through investigating the longitudinal dynamic characteristics of the vehicle. Second, we use the least squares method to identify the model parameters based on the data obtained from a real electric vehicle. The model is built in Simulink and its accuracy is validated by CRUISE. The calibration results demonstrate that the identified model is capable of predicting longitudinal vehicle responses that affect drivability and useful in control algorithm design.