Vehicle-mounted data self-adaptive time interval transmission method of new energy vehicle

Abstract

The invention relates to a vehicle-mounted data self-adaptive time interval transmission method of a new energy vehicle, and belongs to the field of vehicle-mounted data processing. The method comprises the following steps of S1, selecting dynamic working condition data under a laboratory condition or a power battery of an actual energy vehicle, and collecting and settling technical parameters ofthe battery; S2, intercepting a length of voltage, temperature or current data, extracting wavelet decomposition coefficients by using Haar wavelet transform, and then performing wavelet reconstruction after coefficient processing; S3, recording the initial moment of each length and the corresponding original voltage, temperature or current data according to the reconstructed voltage, temperatureor current data, thereby obtaining the dimension-reduced voltage, temperature or current data, and recording other vehicle-mounted data at the corresponding moment; and S4, modelling and estimating the state of the processed battery data. Through the method disclosed by the invention, the vehicle-mounted data transmitted at self-adaptive time intervals can be acquired, the integrity of the data under an acute working condition is guaranteed, the modelling and state estimation precision is higher, and the method has more advantage in comparison with the current fixed time interval transmission.

Description

technical field [0001] The invention belongs to the field of in-vehicle data processing, and relates to an adaptive time interval transmission method for in-vehicle data of a new energy vehicle. Background technique [0002] With the advent of the Internet of Things and the era of automobile intelligence, a large amount of vehicle data is connected to the cloud data center through the Internet of Things. For various types of data uploaded by vehicle smart terminals in real time and at high frequency, it will be aggregated into massive data in the data center. For the collection, cleaning, conversion, storage, real-time and offline data analysis and value mining of these data, major automobile companies have built their own big data platforms to realize the information of new energy vehicles such as battery status, vehicle status and geographical location. 24 / 7 real-time monitoring. [0003] At present, the data communication between the on-board terminal, vehicle enterprise...

AI Technical Summary

Problems solved by technology

It is understood that the time interval adopted by the big data platforms of various enterprises is mostly fixed at 10s, which will lead to the loss of data uploaded to the platform under severe working conditions or short-term changes in working conditions, thus missing some useful information. value data

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