LS-SVM power cell SOC estimation method and system

Abstract

The invention provides an LS-SVM (Least squares support vector machine) power cell SOC (State of Charge) estimation method and system, comprising the steps of: I, obtaining a Uoc based on a power cell model and parameters through an FFRLS (Forgetting factor least squares algorithm); II, fitting a Uoc-SOC relation through the FFRLS; III, building an on-line LS-SVM SOC training model; IV, estimating an SOC initial value, and estimating an SOC through an Ah method (Ampere-hour Counting method); and V, correcting and compensating the SOC estimated through the Ah method. In the system, real-time signals of voltage and current sensors access to a microprocessor; processing modules used for executing the method are stored in a program memory, and calculate and directly display real-time SOC estimation values. The method and system can effectively compensate for fitting errors and Ah method accumulative errors, and adjust model parameters on line and in real time, and have the characteristics of fast operation speed, high traceability, and accurate estimation; according to experiments, the SOC estimation precision through the method is high, and the mean absolute error is only 1.28%.

Description

technical field [0001] The present invention relates to the field of electric vehicle power battery charge state estimation, specifically a least squares support vector machine (Least squares support vector machine, LS-SVM) power battery charge state estimation method and system, using an online least squares support vector machine (LS-SVM) Estimate the open circuit voltage OCV of the battery, estimate the state of charge SOC according to the ampere-hour integral method, and use the deviation of the open circuit voltage OCV to correct the state of charge SOC to improve the estimation accuracy of the state of charge SOC. Background technique [0002] As environmental pollution, energy crisis and energy security become increasingly prominent, the research on new energy electric vehicles has become the focus of attention all over the world. In the power battery management system of electric vehicles, the prediction of battery state of charge (SOC) plays a decisive role in charg...

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Problems solved by technology

[0025] However, there is no report on the use of the least squares support vector machine in the state of charge estimation method of the power battery.

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