Algorithm model improving electric automobile SOC estimation precision

Abstract

The invention discloses an algorithm model improving electric automobile SOC (State of Charge) estimation precision and relates to the technical field of electric automobiles. The method specifically includes steps of (1), initial SOC error correction, namely, obtaining the total capacity of a current battery according to a proportional relation of a difference value between an SOC value saved last time and an SOC value obtained through an open circuit voltage table lookup method and a difference value between a battery total capacity saved last time and a total capacity calculated after temperature and self discharge correction factors are added, and realizing correction of available capacity at an initial time point by combining the corrected battery total capacity and the influence on battery aging degree by cycle service lifetime, and obtaining an initial SOC value after correction through correction; (2), SOC accumulation error correction. According to the invention, the initial SOC is estimated based on temperature correction, converted coulombic efficiency correction, self discharge and SOH compensation and an accumulation error correction algorithm combining an ampere-hour accumulation algorithm and the open circuit voltage algorithm is adopted, so that problems of initial errors and accumulation errors in an SOC estimation process are solved effectively.

Description

technical field [0001] The invention relates to the technical field of electric vehicles, in particular to an algorithm model for improving the SOC estimation accuracy of electric vehicles. Background technique [0002] The SOC (state of charge) estimation of the remaining battery capacity is an important part of the BMS. As one of the criteria for judging the vehicle control strategy, the SOC estimation is affected by many factors (such as charge and discharge rate, initial SOC, ambient temperature, self-discharge Wait). In addition, the complex working conditions during the driving process of the car also make it difficult to estimate the SOC accurately in practical applications, so improving the estimation accuracy of the battery SOC is a research hotspot in the field of battery management. [0003] Some SOC algorithms mainly include discharge experiment method, ampere-hour integral method, open circuit voltage method, linear model method, neural network method, Kalman f...

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Problems solved by technology

The disadvantage of the discharge experiment method is that it cannot adapt to the SOC estimation under the condition of current change; the disadvantage of the ampere-hour integration method is that it depends on the initial SOC value and is easily affected by the self-discharge of the battery itself; the open circuit voltage method is not suitable for online SOC real-time monitoring. It is generally combined with other methods to assist in correcting the accuracy; the disadvantage of the linear simulation method is that it is only suitable for systems with little change in SOC, which is relatively rare in practical applications; the disadvantage of the neural network method is that it requires a large amount of reference data for training, and the estimation method It is greatly affected by data and methods; the Kalman filter algorithm is suitable for various battery systems, especially for power vehicle SOC estimation under the condition of large current fluctuations, but it has high requirements for algorithm design, is cumbersome, and is not easy to implement in the system

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