Research on speed estimation of hub-motor vehicle based on multi-sensor information fusion

Abstract

Accurate acquisition of longitudinal and lateral velocity of the vehicle plays an important role in the modern automobile control system. In this paper, the vehicle speed test system is composed of multiple sensors, data acquisition board (NI cDAQ9137) and LabVIEW software. The real-time acquisition of front-wheel angle, wheel speed, longitudinal acceleration, lateral acceleration, and yaw velocity of the hub-motor vehicle is completed by using the speed measuring system. Based on the real road test results, the vehicle speed estimation is obtained by Kalman filter technology and compared with the reference vehicle dynamics model. The comparison results show that the vehicle speed estimation has high accuracy and can meet the requirements of state parameter estimation. The algorithm has the advantages of simple structure, small computation and easy implementation and can provide more information for the automobile control system.