SOC (state of charge) estimation method for controlling equivalent charging and discharging of lithium battery

Abstract

The invention provides an SOC (state of charge) estimation method for controlling equivalent charging and discharging of a lithium battery. The SOC estimation method includes: establishing a first-order RC (resistor and capacitor) equivalent circuit model of a single lithium battery, and determining a state equation and an observation equation of a lithium battery system; determining a Kalman filtering discrete state space model, a state parameter variable and an observation parameter variable; updating an predicted value of the state parameter variable and a covariance matrix of measuring errors, and acquiring an innovation sequence according to an observed voltage value at the end of the lithium battery; introducing a self-adaptive fading factor to track and correct a predicted covariance matrix of the lithium battery system; calculating a Kalman filtering gain matrix of the discrete state space model, and updating the optimal estimated value and an error covariance matrix value at the present moment; acquiring a statistical property of process noise; acquiring an SOC estimation value at the present moment, and putting the parameters of the present moment in recursive iteration calculation of strong-tracking self-adaptive Kalman filtering for the next moment. By the aid of the SOC estimation method, real-time and precise estimation of SOC of the lithium battery is realized.

Description

technical field [0001] The invention belongs to the technical field of lithium batteries, in particular to an SOC estimating method for balanced charging and discharging control of lithium batteries. Background technique [0002] At present, in the hybrid power system, the research on the estimation method of the state of charge (State Of Charge, SOC) of the battery pack is a core point. The SOC value can provide a basis for the battery management system to adopt an accurate control strategy. Therefore, the accurate estimation of lithium battery SOC is the key to the study of lithium battery balance charge and discharge control strategy. [0003] The mainstream SOC estimation method at this stage mainly adopts the extended Kalman filter method. The extended Kalman filter method is a recursive linear minimum variance estimation method. The state vector is optimally estimated on the minimum variance, so as to obtain the SOC estimation value with high precision. However, the...

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Problems solved by technology

[0004] (1) The error of the lithium battery model itself cannot be eliminated and there are a large number of uncertain errors in the model; (2) The initial value and statistical characteristics of the process noise and observation noise of the system are inaccurate, causing the filter to diverge; (3) In the recursive process of the extended Kalman filter, as the number of iterations increases, the rounding error gradually accumulates, causing the system to generate calculation divergence

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