SOC estimation method and system with parameter correction based on gas-liquid kinetic model

Abstract

The invention provides an SOC estimation method and system with parameter correction based on a gas-liquid kinetic model. The method comprises the following steps of carrying out the HPPC experiment of a lithium ion battery, and recording the battery datafor estimating the model parameters and obtaining an OCV-SOC relational expression, identifying parameters of the gas-liquid kinetic model, fitting the open-circuit voltage data obtained in the step 1 with SOC to obtain an OCV-SOC relational curve, building a gas-liquid dynamic model, obtaining an open-circuit voltage of the battery through the gas-liquid dynamic model, and obtaining an estimated value of the SOC through a relation curve of the open-circuit voltage OCV and the state of charge SOC of the battery, and building an ampere-hourintegral method model. The real value of the SOC and the estimated value of the SOC form a control deviation, the deviation forms a controlled quantity through linear combination according to proportion, integration and differentiation through a PID module, and a correction coefficient of a model parameter k3 is output; the correction coefficients obtained under different SOCs are added to the parameter k3 and then input into the gas-liquid dynamic model, the model is corrected, the corrected SOC value is obtained, and the SOC estimation precision is improved.

Description

technical field [0001] The invention belongs to the technical field of batteries, and in particular relates to an SOC estimation method and system with parameter correction based on an aero-hydraulic dynamics model. Background technique [0002] In order to solve the global shortage of oil resources and the deteriorating climate and environment, and to seek mutual promotion and coordinated development of society, economy, resources, and environment, electric vehicles have become the first choice for future transportation due to their unique advantages in energy saving and environmental protection. As the key technology of electric vehicles, the power battery can accurately estimate and monitor the state of charge, which is very important in terms of battery safety and battery efficiency. [0003] Accurate estimation of battery SOC, on the one hand, comes from the requirements of electric vehicles, and efficiently manages batteries from the perspectives of giving full play to...

AI Technical Summary

Problems solved by technology

For example, using the ampere-hour counting method (coulomb counting method or current integration method), the calculation is simple and easy to implement, but it requires high accuracy of the initial SOC, and there is accumulation of noise and measurement errors

The open circuit voltage (OCV) method has high accuracy, but it requires the battery to rest for a long time to estimate the SOC, so it cannot be applied in real time

There are also intelligent algorithms such as artificial neural network and fuzzy logic that use the battery as a black box system. It has a strong ability to approximate nonlinear functions. These methods can usually estimate SOC very well. However, the calculation process of these intelligent algorithms is more complicated. Realization Difficult to apply online

In terms of improving the accuracy of parameter identification, it is mostly necessary to identify multiple sets of parameter values ​​at specific SOC values ​​or at different magnifications, establish a discrete parameter space, or obtain several functional relations through data fitting methods. These methods can improve the accuracy of estimation. Accuracy, but adds a lot of work

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