Sistema de Torque Vectoring basado en técnicas de control inteligente para vehículos eléctricos con motores en rueda

Abstract

Transport electrification is currently a priority for authorities, manufacturers and research centers around the world. The development of electric vehicles and the improvement of their functionalities are a key element in this strategy. As a result, there is a need for further research in emission reduction, efficiency improvement or dynamic handling approaches. In order to achieve these objectives, the development of suitable Advanced Driver-Assistance Systems (ADAS) is required. Although traditional control techniques have been widely used for ADAS implementation, the complexity of electric multi-motor powertrains make intelligent control approaches appropriate for these cases. In this work, a novel intelligent Torque Vectoring (TV) system, composed by a neuro fuzzy vertical tire forces estimator and a fuzzy yaw moment controller, is proposed which allows to enhance the dynamic behaviour of electric multi-motor vehicles. The proposed approach is compared with traditional strategies using the high fidelity vehicle dynamics simulator Dynacar. Results show that proposed intelligent Torque Vectoring system is able to improve the handling and increase the efficiency of the vehicle by 10%.