A method for online estimation of state of charge of lithium-ion battery

Abstract

The invention discloses an SOC (state of charge) online estimation method for a lithium ion battery. The SOC online estimation method comprises the following steps: recognizing characteristic parameter values of the battery online; recognizing real-time SOC of the battery online; revising the battery SOC through ampere-hour integral estimation to obtain revised SOC; and weighing the real-time SOC and the revised SOC to obtain final SOC of the battery. By the SOC online estimation method, online estimation capability of battery characteristic parameters can be improved; evaluation self-adaptive capability of the SOC is stronger, and reliability is higher.

Description

technical field [0001] The invention relates to the technical field of lithium-ion batteries for new energy vehicles, and more specifically, relates to an online estimation method for the state of charge of a lithium-ion battery. Background technique [0002] With the gradual deterioration of the global climate, the increase of urban air pollution and the excessive consumption of oil resources, more and more people in the automotive field are turning their attention to new energy vehicles. Lithium-ion batteries have excellent performances such as small size, high energy density, long storage life, no memory effect, high voltage and low self-discharge rate, and have gradually become the winners of new energy vehicle power batteries. How to make good use of batteries has become a key technology in the field of batteries and their integration, among which accurate monitoring of battery state of charge (State of Charge, SOC) has become a difficult and hot issue in the research o...

AI Technical Summary

Problems solved by technology

However, there are several main problems in the application: (1) It is greatly affected by the initial SOC value, current acquisition accuracy, and charge-discharge efficiency; (2) This method will seriously fail after the aging capacity of the battery decays, so it is often used in practical applications. Combined use of methods

The open circuit voltage method mainly uses the corresponding relationship between the open circuit voltage (OCV, OpenCircuitVoltage) and SOC to estimate, but because the open circuit voltage is difficult to measure during the working process of the power battery, the use of this method is limited

The neural network method needs to use a large number of data samples to simulate the algorithm offline, the method is complex and difficult to implement and apply, and it cannot be used for online monitoring of SOC

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