Estimation method and system of state of charge (SOC) of power battery

Abstract

The invention discloses an estimation method of state of charge (SOC) of a power battery. The method comprises the following steps: estimating the SOC estimated value SOC2 of the power battery by an electricity accumulative method; taking a Sigma-point Kalman filter (SPKF) as a basic estimation tool, taking a dual-RC circuit battery model as a time and measurement update engine of the SPKF, and estimating the SOC estimated value SOC1 of the power battery by a Kalman filter method; and obtaining the final SOC estimated value SOC based on the SOC estimated value SOC2 by the electricity accumulative method and the SOC estimated value SOC1 by the Kalman filter method by utilizing a weighted average method. Correspondingly, the invention further discloses an estimation system of the SOC of thepower battery. The invention has the advantages of high SOC estimation accuracy, stable operation and the like, and is convenient in real-time estimation, thus being applicable to pure electric vehicles and hybrid electric vehicles in need of the power battery.

Description

technical field [0001] The present invention relates to a method and system for estimating power battery SOC (State of Charge, state of charge) with high accuracy, which is suitable for all vehicles that need to use power batteries, especially vehicles that need to estimate power battery SOC in real time . Background technique [0002] With the deepening of the energy crisis, it has increasingly affected people's production and consumption concepts, and clean and environmentally friendly pure electric vehicles (Electric Vehicle, EV) and hybrid electric vehicles (Hybrid Electric Vehicle, HEV) are also increasingly popular. People's favorite. [0003] The driver of a pure electric vehicle needs to know the SOC of the power battery in real time to determine his itinerary and whether and when to charge the vehicle power battery. The battery management system (Battery Management System, BMS) of a hybrid electric vehicle needs to know the power battery SOC accurately and in real...

AI Technical Summary

Problems solved by technology

Due to the limitation of power battery technology at this stage, the consistency of the battery is still low, so whether it is a pure electric vehicle or a hybrid electric vehicle, its battery management system needs to know the accurate SOC to determine when to balance the battery cells , and to what extent is the equilibrium

[0004] Traditional power battery SOC estimation methods include power accumulation method (that is, ampere-hour measurement method), open circuit voltage method, neural network method, fuzzy logic method, etc., all of which have unsatisfactory results or cannot be used due to problems of one kind or another. real time use

Some researchers also use the Extended Kalman Filter (EKF) method for real-time estimation, but they often use a simple battery model or use an arbitrarily specified SOC initial value, resulting in the Kalman filter failing to converge or even oscillating , the estimated value of SOC may deviate greatly from the true value, even if an accurate battery model and a Kalman filter with an effective initial value of SOC are used, due to the shortcomings of the extended Kalman filter itself, its algorithm may run in some cases Unstable, not suitable for use in vehicles with relatively high reliability requirements

[0005] In summary, the existing power battery SOC estimation technology obviously has inconvenience and defects in actual use, so it is necessary to improve it

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