Composite estimating method of power battery SOC based on PNGV equivalent circuit model

Abstract

The invention relates to the technical field of power batteries of electric automobiles, and discloses a composite estimating method of a power battery SOC based on a PNGV equivalent circuit model. The composite estimating method comprises the following steps that A, the open-circuit voltage of the power battery is detected; B, an open-circuit voltage method is used for calculating the primary SOC (t0) of the power battery; C, in the time period of t0-t1, an EKF algorithm is used for correcting the primary SOC (t0), and an SOC (t1) is obtained; D, in the time period of t1-t2, an improved ampere-hour integral method is used for estimating; E, when the power battery is continuously used, the steps from the step C to the step D are circulated; the t0 represents the primary time, and the t1 and t2 represent the time points after the t0. According to the composite estimating method of the power battery SOC based on the PNGV equivalent circuit model, the correction coefficients of influencing factors such as the charging and discharging currents of the power battery, the environment temperatures, the battery health state are considered, the improved ampere-hour internal method is used, and the defect that the influence from outside factors is large when the ampere-hour internal method is used for estimating the power battery SOC can be overcome. The advantage that an EKF method has a powerful correcting effect on initial errors of the SOC is fully used.

Description

technical field [0001] The invention relates to the technical field of electric vehicle power batteries, in particular to a composite estimation method for power battery SOC based on a PNGV equivalent circuit model. Background technique [0002] The battery management system is an important part of electric vehicles, and the state of charge (State of Charge, SOC) estimation of power batteries is one of the key technologies of this system. The real-time estimation of SOC involves the charging and discharging control of the power battery and the optimal management of electric vehicles, which directly affects the service life of the power battery and the performance of the power system. Therefore, accurate estimation of the SOC of the power battery is very critical for the operation of electric vehicles. [0003] At present, SOC estimation methods mainly include ampere-hour integral method, internal resistance method, open circuit voltage method, neural network method and Kalma...

AI Technical Summary

Problems solved by technology

However, there are some defects in the ampere-hour integration method that will lead to inaccurate estimates. For example, the method itself cannot estimate the initial value of SOC, and the capacity of the power battery is greatly affected by external factors. The open circuit voltage method requires the battery to stand for a long time and is not suitable for real-time prediction; The neural network method is susceptible to interference, and its accuracy is greatly affected by the training method and training data; the Kalman filter method has a strong correction effect on the initial error of the SOC, and is especially suitable for power batteries with rapid current changes, but it is not effective for battery Model accuracy requirements are relatively high

Images