A rapid detection method for the battery state of health

The purpose of this paper is to develop a rapid detector for the battery state-of-health (SOH) in field applications. The research focuses on the detection principle and implementation technology of the instrument, which differs from machine learning methods based on data mining and equivalent-circuit model methods based on state space modeling and parameter estimation. The charge transfer factor and lithium-ion diffusion factor are introduced to represent the battery SOH in the active material and lithium-ion inventory inside the battery respectively. The relationship between the two indicators and battery impedance is established, which is independent of SOC. Two indicators are obtained by measuring the charging current at a particular single frequency point within seconds. The charge current, which comprises a fixed-amplitude DC current and variant AC current is employed to provide a unified comparison base and shortens the measurement time. The rapid detector is implemented on a microcontrol unit with HRPWM technology.

Automated summary

The aim of this paper is to create a rapid detector for battery state-of-health (SOH) in field applications. The research focuses on the detection principle and implementation technology of the instrument, which differentiates it from machine learning methods and equivalent-circuit model methods. The paper introduces charge transfer factor and lithium-ion diffusion factor to represent the battery SOH in the active material and lithium-ion inventory respectively. The relationship between these factors and battery impedance is established, independent of state of charge (SOC). The rapid detector, implemented on a microcontrol unit with HRPWM technology, obtains two indicators by measuring the charging current at a specific single frequency point within seconds. The use of fixed-amplitude DC current and variant AC current provides a unified comparison base and shortens the measurement time.