Online Diagnosis Based On Variation Characteristics Of The Internal Resistance For Power Lithium-ion Battery Module Fault

Battery system,the power source element of the Electric Vehicles(EVs),is the key part in Electric Vehicles.The accidents of EVs are mainly caused by the battery system fault.Battery system failure could not only reduce the dynamic performance of the system,shorten the remaining useful life,but also cause the occurrence of security problems in battery system,such as thermal runaway,deflated or leakage,spontaneous combustion or explosion and etc.As the basic element in a battery pack,parallel-connected battery modules(PCBM)can increase the system current and improve system capacity,which is widely used in the battery system.The faults in the PCBM mainly includes: short circuit,open circuit,cell loose contact,and cell aging inconsistency.The first two faults can be detected based on the threshold judgment of the terminal voltage and the load current.The core problems of existing fault diagnosis research mainly focus on the identification and separation of the latter two faults.Due to the fact that these two faults will cause the battery internal resistance value changes,this paper will adopt the fault diagnosis method for parallel-connected battery module based on the variation of internal resistance.On the one hand,both of these faults will lead to an increase in internal resistance.Therefore,it is necessary to conduct a reliable and accurate separation of the two by analyzing the variation characteristics of internal resistance values and distribution rules.On the other hand,there is also difficulty in obtaining small internal resistance online.Under dynamic working conditions,there may be an imaginary number solution in the internal resistance identification results of the faulty parallel-connected battery module based on the system’s own dynamic process information,and thus this can lead to erroneous fault diagnosis.However,under steady working condition,the system parameters cannot be effectively identified by obtaining the relationship between excitation and response due to the lack of excitation or excitation single.Therefore,an external measurement module is needed to measure the internal resistance online of the battery.The existing measurement method for internal resistance of battery based on AC excitation is limited by the voltage and current measurement errors together and it is difficult to accurately measure the milliohm class internal resistance of batteries.To solve the problems above,the main research contents of this paper are as follows:First,to solve the problem that the cell loose contact fault and cell aging inconsistency fault can not be effectively distinguished in the parallel modules,a fault recognition and fault separation method for batteries based on analysis of discrete distribution for DC internal resistance of parallel module is proposed.By describing the distribution of DC internal resistance in parallel modules of battery pack,the difference between different fault types and the overall characteristics of battery pack is characterized,and the corresponding relationship between the internal resistance of modules and the failure modes is established.At the same time,combined with the internal resistance of the online recognition technology based on dynamic change of voltage and current for parallel module,solving the possible divergence problem of imaginary numbers for identification result by adding recursive constraints in the filtering process,the identification accuracy of internal resistance is ensured,and reliability of on-line fault mode diagnosis for parallel module in battery pack is further ensured.It is proved by experiments that for battery packs with cell loose contact fault and cell aging inconsistency fault,the method can efficiently identify faulty battery model and accurately distinguish the cause of failure.Secondly,aiming at the problem that the internal resistance measurement module for battery package fault diagnosis under stable condition is limited by the measurement error of voltage and current together,a measurement method based on time-sharing comparison of voltage response for AC internal resistance is proposed.By extracting the proportional relationship of voltage response under the same current excitation condition between the battery and the standard resistor,the method realizes the accurate measurement of the internal resistance of the battery,and it theoretically avoids the influence of the occurrence or the measurement error for excitation current on the measurement error of the final battery internal resistance.At the same time,by time-sharing measuring the battery internal resistance and the standard resistance,the interference that the circuit fault may cause to the battery failure is avoided.The experimental results show that the relative error of the proposed method is within 0.3% under the condition of static and 1C constant current discharge,which is 0.7% higher than that of the existing method.Combined with distribution of AC resistance for parallel-connected battery modules,fault parallel module is accurately positioned and the cause of the malfunction is reliably separated under steady operating conditions.Parallel module fault diagnosis method is proposed in this paper,which can effectively ensure the battery system safety,improve battery system performance,reduce battery system cost,thus it is very important for the popularization of the electric vehicle.At the same time,it has reference to the other application of battery modules in parallel.