Lithium ion battery health state estimation method applying sliding window optimization strategy

Abstract

The invention belongs to the technical field of battery management, and particularly relates to a lithium ion battery health state estimation method applying a sliding window optimization strategy. Firstly, an aging feature relationship, i.e., a SOH-Pf relationship, of the type of battery is acquired by a multi-cell entire life-cycle accelerated aging test; and then a feature parameter Pf of a to-be-tested battery is calculated according to a constant-current charging voltage characteristic of the to-be-tested battery, so as to acquire SOH of the to-be-tested battery by adopting a table look-up method. The lithium ion battery health state estimation method disclosed by the invention is sufficiently suitable for the capacity fading different phenomenon among multiple cells in the lithium ion battery aging process, gets rid of influence of a cycle index of a battery, carries out accurate online estimation on the SOH of each cell, and can reach an expected SOH estimation accuracy of 5%; acharging mechanism of an electric vehicle in the actual working condition is considered, the lithium ion battery health state estimation method is high in adaptability to actual charging equipment, and SOH estimation on the battery can be implemented under the conditions of multi-magnification charging and nonzero charging initial SOC; and the SOH online estimation scheme designed by the invention is simple, easy to operate and convenient to carry out engineering implementation by adopting a conventional MCU.

Description

technical field [0001] The invention belongs to the technical field of battery management, and in particular relates to a method for estimating the state of health of a lithium-ion battery using a sliding window optimization strategy. Background technique [0002] At present, lithium-ion batteries are widely used in fields such as electric vehicle energy storage. Although lithium-ion batteries have many advantages, at the same time, the industry has gradually noticed the aging difference between lithium-ion battery cells: when using the same working mechanism to continuously cycle and charge different cells of the same brand When discharging, as the number of cycles increases, the decay speed of the available capacity of each monomer will show obvious differences, which will cause the cycle life of some monomers in the series battery pack to end prematurely, which is affected by the short board effect (also known as the barrel effect) ) constraints, the overall life of the ...

AI Technical Summary

Problems solved by technology

Although lithium-ion batteries have many advantages, at the same time, the industry has gradually noticed the aging difference between lithium-ion battery cells: when using the same working mechanism to continuously cycle and charge different cells of the same brand When discharging, as the number of cycles increases, the decay speed of the available capacity of each monomer will show obvious differences, which will cause the cycle life of some monomers in the series battery pack to end prematurely, which is affected by the short board effect (also known as the barrel effect) ) constraints, the overall life of the battery pack will also be terminated

The difference in capacity attenuation exhibited by the battery is of great significance to systems that use battery packs in engineering practice, such as electric vehicles, new energy power generation and energy storage, and unmanned aerial vehicles. The aging difference of lithium batteries will lead to battery packs The overall life is shortened; in actual working conditions, these aging differences may gradually expand over time, causing the internal structure of the battery to be destroyed at an accelerated rate, and the overall working performance of the battery pack deteriorates rapidly, which may lead to failure of the entire power system, or even a serious accident

[0003] A related technology is the invention patent "A Method for Real-time Evaluation of Battery Health Status" by Feng Xuning of Tsinghua University and others. The accuracy is guaranteed to be optimal; and the scheme does not explicitly consider the capacity fading difference between multiple cells, and simply uses the characteristics of a single battery sample as the common characteristics of the same type of battery; in addition, the scheme does not consider the battery application system (such as electric vehicles) Actual working conditions; for different types of batteries, this solution has poor versatility and heavy workload

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