Method and system for estimating state of charge of dual-variable structured filtering power battery

Abstract

The invention discloses a method and a system for estimating the state of charge (SOC) of a dual-variable structured filter power battery. The method comprises the following steps: firstly, establishing a battery equivalent model, identifying parameters of the power battery model by adopting first variable structure filtering, fitting the relationship of open circuit voltage (OCV) and the SOC of the power battery, and furthermore estimating the SOC by adopting second variable structure filtering. A variable structure filtering parameter beta beta value has relatively large influence on modification increment, and beta beta is adjusted by introducing fuzzy rules in a self-adaptive manner. A voltage and current sensor of the estimation system is mounted on a power battery to be detected, a computing module for implementing the method is arranged inside a microprocessor, and the microprocessor is used for displaying the SOC value which is estimated at present on line, and can be connected with a CAN controller of an automobile. By adopting the method and the system, the parameters of the power battery can be identified on line; the modification increment of the variable structure filtering parameters can be adjusted in a self-adaptive fuzzy manner, the method is concise, small in calculating amount, easy to achieve, high in precision and small in dependency on SOC initial values.

Description

technical field [0001] The invention relates to the field of state estimation of power batteries of electric vehicles, in particular to a method and system for estimating the state of charge of power batteries with double variable structure filtering. Background technique [0002] New energy vehicles are an effective way to solve the environmental pollution caused by traditional vehicles, and power batteries are one of the core technologies of new energy vehicles. The estimated value of the state of charge (SOC) of the high-precision power battery is an important parameter in the driving process of the power vehicle, and it is also an important basis for the driving state of the electric vehicle. [0003] The commonly used methods for estimating the state of charge of power batteries include: ampere-hour integral method, open circuit voltage method, Kalman filter method and particle filter method. These methods have insurmountable defects in actual use. The ampere-hour int...

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Problems solved by technology

[0004] In short, the existing SOC estimation method of the power battery is due to the influence of error accumulation and nonlinearity of the power battery on the estimation accuracy. At present, there is no SOC online estimation with high accuracy, fast convergence speed, and low dependence on the initial value accuracy. State of Charge SOC Estimation Method for Traction Batteries

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