State-of-charge estimation method and system for compensating non-smooth hysteresis in power batteries

Abstract

The invention relates to state-of-charge estimation method and system for compensating non-smooth hysteresis in power batteries. The method includes: firstly, acquiring battery output voltage and current, establishing a neural network OCV (k), (open circuit voltage) (k), prediction model according to the relation of parameters obtained by a battery equivalent circuit model, solving the parameters, and estimating OCV (k) online; and secondly, serially connecting an SDH (simple dynamic hysteresis) model with an RBF2 (radial basic function 2) to form a dynamic hysteresis hybrid model. The SDH model using the OCV (k) obtained in the first step as input outputs y(k), OCV (k) and OCV (k-1); the RBF2 using the y(k), the OCV (k) and the OCV (k-1) as input is weighted to learn so as to indirectly adjust parameters of the SDH model; approximately actual complex hysteresis relation is obtained; online-estimated SOC (k), (state of charge) (k), is output finally. The system comprises a microprocessor and other parts installed on a battery circuit, such as current and voltage sensors, stores a program executing the method, and obtains an SOC (k) estimate. Non-smooth hysteresis in power batteries is compensated by the aid of a neural network, and precision in online estimation of the SOC (k) is increased.

Description

technical field [0001] The invention relates to the technical field of charge state estimation of automobile power batteries, in particular to a charge state estimation method and system for non-smooth hysteresis characteristic compensation of power batteries. Background technique [0002] In new energy electric vehicles, power batteries are one of the three key technologies. Batteries have developed from lead-acid batteries, nickel-metal hydride batteries to lithium-ion batteries, and the theoretical and technical research on the high efficiency, safety and long-life use of batteries has always attracted much attention. The charging and discharging process of automotive power batteries is completely different from that of batteries used in other devices such as mobile phones. Under the random dynamic alternate charge and discharge state of electric vehicle power batteries, overcharging and deep discharging may cause irreversible damage to the battery, which also involves sa...

AI Technical Summary

Problems solved by technology

[0006] 3) Impedance method: large amount of calculation, difficult to implement online

[0007] 4) The SOC estimation method based on the battery equivalent circuit model cannot fully describe the complex hysteresis characteristics of the battery during the dynamic change process of charging and discharging.

[0008] 5) In the SOC estimation method based on intelligent modeling, the models adopted fail to fully consider the complex hysteresis characteristics of SOC in the two processes of charging and discharging

The complexity of the electrochemical process of the electric vehicle power battery leads to the consistency problem of SOC estimation, that is, the drift problem; the complex hysteresis nonlinear characteristics and compensation problems of SOC and battery open circuit terminal voltage OCV appear; the SOC is estimated by the SOC-OCV hysteresis relationship, Corresponding to the OCV online rapid estimation problem that needs to be solved

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