A real-time power intelligent prediction method and device for unmanned vehicles
An unmanned vehicle, real-time power technology, applied in the field of artificial intelligence, can solve the problem of not fully considering the nonlinear dynamic influence of power, predicting battery power consumption, etc., achieving good timeliness, high accuracy, and self-learning. strong effect
Active Publication Date: 2021-12-21
CENT SOUTH UNIV
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[0004] The current power of unmanned vehicles is only considered based on the vehicle's own factors such as vehicle speed, history, and battery capacity. It does not fully consider the nonlinear dynamic impact of road conditions on the power of unmanned vehicles in different environments. Predict the actual power consumption of the battery
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[0082] The present invention will be further described below in conjunction with accompanying drawings and examples.
[0083] Such as figure 1 As shown, a real-time electric power intelligent prediction method for unmanned vehicles includes the following steps:
[0084] Step 1: Obtain training data;
[0085] The training data includes the energy consumption value, driving distance and power consumption of the unmanned vehicle within a specified time nT during driving, and the energy consumption value includes wind resistance energy consumption value, slope energy consumption value and temperature energy consumption value ;
[0086] The wind resistance energy consumption value is obtained by accumulating the relative wind speed of the unmanned vehicle within a specified time nT, and the relative wind speed refers to the difference between the external wind speed of the vehicle and the vehicle speed;
[0087]The slope energy consumption value is obtained by integrating the cl...
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The invention discloses a real-time electric power intelligent prediction method and device of an unmanned vehicle. The method studies the main power consumption aspects of vehicle running, such as air conditioning and wind resistance, and establishes a power consumption prediction model in combination with the complex road environment. , the selected model is obtained based on neural network training, with strong self-learning ability and good accuracy; the model predicts power has nothing to do with the battery itself, the model is trained in real time, can identify the usage of power in different road conditions, and the prediction results are highly accurate , good timeliness, and better avoid the inaccurate problem in the prior art caused by calculating the power consumption only for the basic working principle and charging and discharging characteristics of the battery.
Description
technical field [0001] The invention belongs to the field of artificial intelligence, in particular to a method and device for real-time power intelligent prediction of unmanned vehicles. Background technique [0002] Artificial intelligence has developed rapidly recently, and unmanned vehicles are one of the hottest concerns among people. For the development of unmanned vehicles, the power storage device is the focus of its development. The performance of the power storage device using electric energy will affect the speed decision and path planning decision of the unmanned vehicle. The high-precision prediction of vehicle power is in the To a certain extent, it can provide decision-making and suggestions for the power storage device to exert its maximum effect. [0003] The power of unmanned vehicles is a piece of data that needs to be obtained in real time during the driving process of unmanned vehicles. The power of the unmanned vehicle reflects the matching relationsh...
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IPC IPC(8): G06Q10/04G06N3/00G06N3/04
CPCG06N3/006G06Q10/04G06N3/044
Inventor 刘辉李燕飞段铸
Owner CENT SOUTH UNIV