Method for estimating SOC of battery

Abstract

The invention discloses a method for estimating SOC (State Of Charge) of a battery. A battery model is established by use of an SOC equation of the battery. Compared with the prior art, the method is characterized in that temperatures, charge / discharge rates and the SOC equation model are added, and finally, the SOC of the battery is estimated by use of a self-adaptive kalman filtering algorithm. In practical estimation, the estimated value of a kalman filtering state vector is updated any time in combination with the influence of the temperatures and charge / discharge rates on the battery, and therefore, the latest SOC state value in the current state can be obtained. In this way, the estimation accuracy of the SOC of the battery is improved and the application prospect of the engineering is also expanded.

Description

technical field [0001] The invention belongs to the technical field of batteries, and more specifically relates to a battery SOC estimation method. Background technique [0002] For electric vehicles, the power battery is a very common energy storage component, and its performance plays a decisive role in the performance of the vehicle. In the power battery, lithium-ion batteries are used as an important energy storage medium, and have been widely used in the field of new energy. Wide range of applications. [0003] The SOC of the battery state of charge is an important indicator to reflect the state of the battery. For the estimation of the battery SOC, scholars at home and abroad have proposed the ampere-hour integration method, the Kalman filter method, and the adaptive Kalman filter method. The ampere-hour integration method is simple and easy to implement, but the cumulative error caused by current sampling and other factors gradually increases, resulting in an increas...

AI Technical Summary

Problems solved by technology

However, the existing adaptive Kalman filter algorithm often does not consider the temperature factor and the charge-discharge rate factor. The reason is that these two factors do not change much under ideal laboratory conditions, but in practical engineering applications, such as electric During the energy feedback process of the car, the temperature and charge-discharge rate will have a great impact on the SOC estimation accuracy of the battery

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