New method for estimating SoC of power lithium battery

A technology of lithium battery and new method, applied in the field of estimating power lithium battery SoC, can solve the problems affecting SoC estimation accuracy, affecting model accuracy, model parameter error, etc., to simplify formula derivation and calculation process, reduce errors, and achieve high accuracy sexual effect

Inactive Publication Date: 2018-04-24
CHONGQING THREE GORGES UNIV
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Problems solved by technology

Due to the dynamic nonlinear characteristics of lithium batteries, and the influence of different working conditions, ambient temperature and other factors during the working process, it is difficult to reflect these factors into the required model parameters in the actual mod

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  • New method for estimating SoC of power lithium battery
  • New method for estimating SoC of power lithium battery
  • New method for estimating SoC of power lithium battery

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[0038] 1. Establish ARX model of lithium battery

[0039] At present, the equivalent circuit models of lithium batteries mainly include Rint model, Thevenin model, PNGV model and multi-order dynamics model. The n-order model can more accurately reflect the dynamic nonlinear characteristics of lithium batteries. The equivalent circuit structure is shown in figure 1 Shown.

[0040] For ease of description, the ARX model of a lithium battery is derived from a first-order equivalent circuit. According to Kirchhoff’s law, by figure 1 The following formula can be obtained:

[0041]

[0042] Where V L Indicates the load voltage of the battery; V OC Indicates the open circuit voltage of the lithium battery; V 1 Represents polarization capacitance C 1 Terminal voltage; R 0 Is the ohmic resistance of the battery; R 1 Is the equivalent polarization internal resistance of the battery, C 1 Is the equivalent polarization capacitance of the battery; I represents the load current.

[0043] First,...

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Abstract

The invention discloses a new method for estimating a SoC of a power lithium battery. The method comprises the steps of: adopting an autoregressive exogenous (ARX) model to establish a lithium batteryequivalent model, then adopting a genetic algorithm based on an AIC criterion to determine order of the lithium battery equivalent model, and calculating model coefficients by utilizing a recursive least-squares method after determining the model order; establishing a spatial state equation required by Kalman filtering according to the acquired ARX model coefficients and a lithium battery state equation; and finally realizing estimation of the SoC of the lithium battery by utilizing a Kalman prediction iterative equation. The method just needs to determine the order and coefficients of the ARX model without calculating specific equivalent circuit parameter values, simplifies the tedious formula derivation and calculation process so as to avoid the subsequent calculation of e indexes of aKalman filtering state transfer matrix and an input control matrix, and reduces the error introduced because the equivalent circuit parameters are affected by complicated operating conditions of the lithium battery.

Description

technical field [0001] The invention relates to the field of estimating the state of charge of a battery, in particular to a new method for estimating the SoC of a power lithium battery. Background technique [0002] This year, the development of new energy electric vehicles has developed from the initial embryonic stage to the bottleneck stage, and the power management system (Battery Management System, BMS) has become a key technology that restricts its breakthrough development. The power management system mainly includes battery state of charge (SoC) estimation, battery temperature monitoring, and battery overvoltage, overcurrent, overcharge, overdischarge, and overtemperature protection. Among them, the battery SoC mainly completes the estimation of the remaining capacity of the battery and provides information such as cruising range for the driver. Due to the complex structure of the lithium battery itself, the work is affected by factors such as different working condi...

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Application Information

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IPC IPC(8): G01R31/36G06N3/12
CPCG06N3/126G01R31/367G01R31/387
Inventor 聂文亮季海婷李春莉邱刚
Owner CHONGQING THREE GORGES UNIV
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