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Power supply model prediction method and system for unmanned vehicle in ice and snow environment

An unmanned vehicle and model prediction technology, applied in vehicle components, neural learning methods, biological neural network models, etc., can solve problems such as poor practicability, poor adaptability, and poor system prediction implementation.

Active Publication Date: 2018-09-25
CENT SOUTH UNIV
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Problems solved by technology

[0005] The present invention proposes a power supply model prediction method and system for an unmanned vehicle in an ice and snow environment. Problems of poor practicability and poor practicability, especially in ice and snow environments, integrate the collected effective snow depth, road slope, battery temperature and other parameters into the comprehensive prediction model of unmanned vehicle battery power to realize battery High reliability and high precision prediction

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  • Power supply model prediction method and system for unmanned vehicle in ice and snow environment
  • Power supply model prediction method and system for unmanned vehicle in ice and snow environment
  • Power supply model prediction method and system for unmanned vehicle in ice and snow environment

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Embodiment Construction

[0086] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0087] Such as figure 1 As shown, a power model prediction method for unmanned vehicles in ice and snow environment, including the following steps:

[0088] Step 1: Obtain historical driving data of unmanned vehicles in ice and snow environment;

[0089] The driving data includes road snow depth, road slope, battery temperature, power consumption rate, and remaining power at each moment;

[0090] Using the on-board electronic level instrument of the unmanned vehicle, the angle between the vehicle body direction and the horizontal direction is sensed as the road slope measurement value.

[0091] 16 non-contact temperature sensors evenly distributed on the battery surface are used to collect the battery temperature of the unmanned vehicle in real time. Through interpolation processing, the three-dimensional temperature distribution data map of the batte...

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Abstract

The invention provides a power supply model prediction method and system for an unmanned vehicle in an ice and snow environment. According to the method, a multi-sensor data acquisition and fusion technology is adopted to fuse a plurality of acquired parameters such as effective snow depth, road slope and battery temperature into a comprehensive battery power prediction model for the unmanned vehicle, and weighted fusion is performed by using a measured value of snow depth and a corresponding three-dimensional depth image observed value, so that intelligent integrated calculation of the battery power of the unmanned vehicle in complex environments such as a snow road environment is realized, and more complete considerations are provided for the research and development field of the batteries of unmanned vehicles. The system is simple in structure, the dependence on a fixed snow depth measuring device along a road is eliminated, optimal allocation of resources in a power supply system of the unmanned vehicle is realized, and the endurance ability of the unmanned vehicle is improved to a certain extent.

Description

technical field [0001] The invention belongs to the field of unmanned vehicles, in particular to a method and system for predicting power supply models of unmanned vehicles in ice and snow environments. 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. Automobile production companies such as Google and Volvo 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 intelligent traffic planning. On the other hand, there is no technical solution or technological innovation for the on-board power supply of unman...

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Application Information

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IPC IPC(8): G07C5/00G07C5/08G06K9/62G06N3/08B60W40/06
CPCG06N3/084G07C5/004G07C5/0808B60W40/06B60W2555/20B60W2552/15G06F18/25
Inventor 刘辉李燕飞
Owner CENT SOUTH UNIV