Parameter and full-interval SOC joint estimation method of power battery

Abstract

The invention provides a parameter and full-interval SOC joint estimation method of a power battery. Power battery parameter identification is performed by adopting an adaptive recursive square root algorithm, a parameter updating rate can be adaptively changed based on a working condition and a system state, meanwhile, a problem of numerical instability caused by rounding errors of an embedded system is avoided, and a convergence rate of parameter identification and stability and reliability of a result are improved. Controllable correction of SOC is achieved through a correction starting judgment module, a SOC correction amount is restrained under conditions of an open-circuit voltage platform period, a low SOC interval, a low temperature and the like, and stability of SOC estimation isguaranteed. A SOC correction function is started in a non-platform period, and a SOC error is rapidly corrected so that the method has relatively high applicability and relatively high estimation precision for a whole system battery in a whole SOC interval.

Description

technical field [0001] The invention relates to the technical field of power battery management, in particular to a method for parameter identification and state estimation of a vehicle power battery. Background technique [0002] Battery state of charge (SOC) estimation is one of the basic functions of battery management system (BMS), and it is also an important prerequisite for energy management, balance management and fault diagnosis. The existing common power battery SOC estimation methods can be roughly divided into two categories: one is the definition method, which uses the ampere-hour integral and calculates based on the definition formula of the state of charge: SOC=remaining power / capacity*100%. However, due to the lack of closed-loop correction of this method, and the corresponding increase in the SOC estimation error when the capacity estimation error increases, it is difficult to apply directly. The various corrected ampere-hour integration methods derived from...

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Problems solved by technology

Compared with the definition method, this type of method has stronger robustness and environmental applicability, and can realize online closed-loop correction for the estimation error, but the traditional model method is very easy to solve at low temperature, low SOC interval and power battery voltage "plateau period". The calculation error increases and even the results diverge. Therefore, it is difficult to apply to some batteries with relatively flat open circuit voltage curves, such as lithium iron phosphate batteries, and it is also difficult to maintain high accuracy in the full SOC range.

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