Research On The State Of Health Estimation And Internal Short Circuit Fault Diagnosis Of Lithium-ion Battery

Lithium-ion batteries are widely used in electric vehicles(EVs)and battery energy storage systems(BESSs)which are connected in series.However,owing to the difference in environment and manufacturing process,the inconsistency of cells capacity,internal resistance and open circuit voltage(OCV)restricts the performance of the pack power and capacity.In addition,the batteries also have the potential of the internal short circuit(ISC)failure.These factors make it difficult to measure the state of health(SOH)and diagnose the ISC fault effectively without disassembling the pack.While the SOH estimation and ISC diagnosis of the battery are important to ensure the safe and reliable operation of the system in EVs and BESSs.Therefore,this paper focuses on the SOH estimation and ISC fault diagnosis of lithium-ion batteries which are connected in series,and the main research is as follow.Firstly,to address the ageing performance degradation of Lithium-ion batteries,ageing cycle experiments with different currents and temperature stresses are designed,and the battery performance parameters are obtained through capacity,incremental capacity analysis(ICA)and hybrid pulse power characteristic(HPPC)experiments.Then the effects of current and temperature on battery capacity and internal resistance are analysed.The battery ageing mechanism is identified by using the ICA method.Combined with ageing experiments,the battery decline evolution process is analysed to reveal the internal ageing decline pattern of the battery.Secondly,a SOH estimation method of cells in series-connected battery packs is proposed based on the partial reconstruction of the OCV curve.The inconsistencies in the seriesconnected battery pack leading to residual OCV curves of batteries are analysed.Then the OCV feature points(FPs)which represent the battery ageing mechanism are extracted from the residual OCV curve by the ICA method.The battery voltage curve transformation theory is chosen to match the transformation of the FPs.The transformation coefficients are optimized by using the multipopulation genetic algorithm(MPGA).Finally,the reconstruction of cell OCV curves in the series-connected battery pack is implemented based on the optimal transformation coefficients.Based on this,the SOH and the initial discharge electric quantity(DEQ)estimation method of cells in the battery pack is proposed.Thirdly,to diagnose the battery with the ISC fault in series-connected battery packs,a multi-characteristic parameter method is proposed.The common causes of ISC faults and evolutionary mechanisms are analysed,and the equivalent circuit model(ECM)of the battery with the ISC fault is constructed.Considering the differences of ISC fault characteristics in different periods,the characteristic parameter of voltage variation rate f’(u)is proposed to identify the medium-term ISC fault.Considering that cells with the early ISC fault may be misclassified as the normal or aged cells,the characteristic parameters of DV curve valley DV＿Valley and the difference of the Δ in the DV curve are proposed.Based on the above two characteristic parameters,ageing cells and cells with the early ISC fault in series-connected battery packs are jointly diagnostically distinguished.Finally,further research is carried out on identifying the battery with ISC early fault,and a estimation method of the ISC equivalent resistance is proposed to analyse the battery with the early ISC fault quantitatively.Finally,the proposed cell SOH estimation and ISC fault diagnosis methods in seriesconnected battery pack are experimentally validated.The effectiveness of the proposed method for estimating the cell SOH based on the partial reconstruction of the OCV curve is verified by using six single cells with different degrees of aging.The experimental results show that the SOH estimation error of the battery is less than 2.5% when the initial DEQ of the battery pack is consistent,and the SOH estimation error is less than 4.8% when the initial DEQ of the battery pack is inconsistent.In the experiment of the cell ISC fault diagnosis in the series-connected battery pack,the proposed three characteristic parameters accurately identify early and medium ISC faults,but also they can distinguish aged cells and early ISC faulty cells in the battery pack.For the battery with the early ISC fault,the estimation error of the ISC equivalent resistance value is less than 5.44%.The experimental results verify the effectiveness of the proposed qualitative and quantitative diagnostic ISC fault methods.