Battery life prediction method and device

Abstract

The embodiments of the invention provide a battery life prediction method and device. The method comprises the steps of: acquiring at least one group of first attribute information of each battery sample in at least one battery sample and at least one group of second attribute information of a battery to be predicted, determining a battery sample most similar to the battery to be predicted according to the at least one group of first attribute information of each battery sample and the at least one group of second attribute information of the battery to be predicted , and determining the lifeof the most similar battery sample as the life of the battery to be predicted. Thus, the accuracy of predicting the life of the battery is improved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of electric vehicles, and in particular to a battery life prediction method and device. Background technique [0002] Compared with traditional cars, electric vehicles can play an important role in reducing pollutant emissions and energy consumption. The battery life of the electric vehicle directly affects the performance and life of the electric vehicle. Therefore, predicting the battery life has become a crucial link. [0003] In the prior art, it is assumed that there is a fixed correspondence between the usage time of the battery, the location information of the electric vehicle, the use information of the electric vehicle, the current information of the battery, the temperature information of the environment where the battery is located, and the battery life, that is, all the above The battery life can be calculated by substituting the information into the standard formula as a k...

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Problems solved by technology

[0004] However, there are also factors that affect each other due to the usage time of the battery, the information of the region where the electric vehicle is located, the use information of the electric vehicle, the current information of the battery, and the temperature information of the environment where the battery is located. For example, when the temperature changes, It will inevitably affect the service time of the battery. Therefore, there will be large errors in simply calculating the battery life through standard formulas, thereby reducing the accuracy of predicting battery life.

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