Electric vehicle residual charging time prediction method and system based on cloud sparse charging data

Abstract

The invention provides an electric vehicle residual charging time prediction method and system based on cloud sparse charging data. The method comprises the steps of 1, battery charging test data is obtained, a battery predictive charging time adaptive network model is established, cross validation and statistical evaluation are performed on the model, and a trained network model is arranged at the cloud; 2, the cloud receives and stores sparse data of battery charging, detects whether the data meets a preset condition or not, and predicts the total charging time of the next cycle and updates the remaining time-capacity ratio diagram by using the network model if the data meets the preset condition; and 3, the cloud inquires the remaining time-capacity ratio diagram, the predicted total charging time in the current state is recorded, the current accumulated charging time is recorded at the same time, and the remaining charging time of the battery is predicted. The technical problem that the online residual charging time of the current electric vehicle is difficult to accurately obtain in the whole life cycle is solved, and the user experience is improved.

Description

technical field [0001] The present invention relates to the technical field of electric vehicles, in particular to a method and system for predicting remaining charging time of electric vehicles based on cloud-based sparse charging data. Background technique [0002] As the number of charging and discharging of the power battery increases, the internal physical state of the battery degrades nonlinearly, resulting in the inability to accurately predict and display the time required for each full charge of the user, which is an important problem encountered by enterprises at present. [0003] The remaining charging time (RCT, Remain Charging Time) of an electric vehicle refers to the time required for an electric vehicle to be fully charged from the current moment when it is plugged into a charging pile and charged with a certain charging strategy, usually in seconds or minutes form of expression. This amount is one of the important indicators that users pay attention to when...

AI Technical Summary

Problems solved by technology

[0005] Patent document CN108445400A (application number: CN201810133081.0) discloses a method for estimating the remaining charging time of a battery pack, which directly calculates the remaining charging time as the sum of preheating time, constant current charging time and constant voltage charging time; patent document CN111257752A ( Application number: CN201811455643.X) discloses a method, device, system and storage medium for estimating the remaining charging time, which is to estimate the remaining charging time of each interval according to the current of the state of charge of each interval and then accumulate; the above patents are based on the terminal charge The method of accumulating the remaining charging time of the battery state / current segment has a wide range of applications, but it is too simple and has large errors, especially the constant voltage stage when the battery is seriously aging is more difficult to estimate and easily leads to jumps in the remaining charging time; the above is based on cloud big data The method needs to accumulate one-year data samples of real vehicles, and the remaining charging time of the vehicle within the one-year sampling period cannot be accurately predicted, and the full coverage of the battery life cycle by the data samples cannot be guaranteed.

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