Multisource fusion prediction method and system for unmanned vehicle power supply

Abstract

The invention provides a multisource fusion prediction method and system for an unmanned vehicle power supply. A multi-sensor data fusion technology is applied, multiple acquired parameters such as the effective snow depth, the road slope and the battery temperature are fused to an unmanned vehicle battery power comprehensive prediction model, intelligent and comprehensive calculation on the battery power of the unmanned vehicle in complex environments such as a snow road environment can be realized, and complete and perfect consideration factors are provided for the unmanned vehicle battery design and research and development field. The system has a simple structure and gets rid of dependence on a fixed snow depth measurement device along the road, optimal resource allocation for the power supply system of the unmanned vehicle is realized, and the endurance ability of the unmanned vehicle is enhanced to a certain degree.

Description

technical field [0001] The invention belongs to the field of unmanned vehicles, and in particular relates to a multi-source fusion prediction method and system for unmanned vehicle power supplies. Background technique [0002] In recent years, as the market has higher and higher requirements for vehicle safety and intelligence, unmanned vehicles have gradually become a hot technology, and more and more enterprises and scientific research institutions have participated in this field. Google, Volvo and other companies have been committed to the research and development of new technologies for unmanned vehicles, but most of them are distributed in improving the navigation technology of unmanned vehicles, improving positioning accuracy, optimizing decision-making control systems, road right allocation, and comprehensive planning of traffic intelligence. However, as a vehicle power source, the on-board power supply is the basis for the realization of all technologies of unmanned ...

AI Technical Summary

Problems solved by technology

[0005] The present invention proposes a multi-source fusion prediction method and system for the unmanned vehicle power supply. In order to solve the problem of low stability, especially in the ice and snow environment, the collected effective snow depth, road slope, battery temperature and other parameters are integrated into the comprehensive prediction model of battery power of unmanned vehicles to achieve high reliability of the battery , high-precision prediction

Images