Data-Driven 차량 횡방향 모델 정확도 개선

Abstract

In mis paper, a data-driven based method was proposed to improve the accuracy of the vehicle lateral model, hi the derivation of the conventional single-track model, several error factors occurred as a result of the simplification of the model. Among them, front and rear tire cornering stiffriess was the factor mat was most related to the accuracy of the vehicle lateral model. In general, the conventional model uses nominal cornering stiffness without considering its nonlinearity and the effect of lateral load transfer. The proposed method was developed to compensate sufficiently for the error factors in cornering stiffriess with a nonlinear map, which was designed by the parameter optimization method through the measurement data from real vehicle tests. This method was designed and validated with real vehicle experiments under various driving scenarios.