Research And Implementation Of Sensor Signal Processing Component Interface And Fusion Algorithm Of Electric Vehicle Based On AUTOSAR

Sensors are an indispensable and important part of intelligent electric vehicles,which undertakes the work of information collection.With the development of intelligent vehicle,the number of sensors on the vehicle is increasing,the information to be processed is more complex,and the requirements for the accuracy and reliability of sensors are also increasing.Due to the influence of the variability environmental climate and the limitations of single sensor,the phenomenon of inaccurate recognition of single sensor often occurs.This paper describes the importance of building the interface library of sensor signal processing components and multi-sensor data fusion based on AUTOSAR architecture in intelligent electric vehicles,studies the research status of fusion algorithms at home and abroad,summarizes and analyzes the existing sensor and multi-sensor fusion algorithms in intelligent electric vehicles,and proposes an extended Kalman filter(EKF)algorithm with dynamic adaptive differential evolution algorithm is used to fuse the data of camera and lidar.The main research contents of this paper include:a)Based on the AUTOSAR software architecture,an intelligent electric vehicle sensor signal processing component interface library was designed and formulated,which establishes a unified naming standard for each sensor interface function in the library,developed a set of sensor priority standards with safety as the primary standard,divided from the urgency and importance of the information,and listed the sensor list for each control system of the intelligent electric vehicle;b)By studying the EKF algorithm in the multi-sensor data fusion algorithm,an improved EKF algorithm is proposed,which is improved by combining the dynamic adaptive differential evolution algorithm with the EKF algorithm;c)Using the improved EKF algorithm for data fusion between the camera and the lidar sensor on the intelligent electric vehicle,through the data preprocessing and data fusion of the image data collected by the camera and the point cloud data collected by the lidar,the fusion result can make up for the shortcomings of a single sensor.The experimental results show that the improved EKF algorithm proposed in this paper has a significant improvement in accuracy and speed compared with the traditional EKF algorithm.The data fusion of camera and lidar sensor implemented in this paper can effectively improve the limitations of a single sensor and accurately identify the surrounding environment of the vehicle body.