Research On Satellite Lithium-ion Battery Pack In-orbit State Of Health Estimation

Lithium-ion battery pack is one of the core components of the satellite platform,which realizes the storage and release of electric energy during the whole life cycle of satellite operation.During the continuous charge and discharge process,the performance of the battery pack degrades gradually in-orbit.State of health(SOH),is an important parameter that reflects the current performance degradation of the battery pack.Accurate estimation of the satellite lithium-ion battery pack ’s SOH is of great importance and significance for its ground management and control,as well as in-orbit intelligent operation and maintenance.The SOH of a lithium-ion battery(pack)can be defined by its maximum available capacity.Generally,the measurement of the maximum available capacity requires the full discharge process from a full charge state.Hence,it cannot be directly measured during in-orbit operation.Therefore,extracting the degradation characterization parameters which strongly relate to the maximum available capacity variation,and estimating the maximum available capacity based on these measurable parameters in orbit has become a feasible way to estimate the SOH of lithium-ion battery(pack)in orbit.At the same time,the satellite lithium-ion battery(pack)needs to be tested according to the in-orbit operating conditions in the ground in-orbit-simulation test.It is also difficult to measure the maximum available capacity under the conditions during the shallow charge-discharge process.Therefore,realizing the accurate equivalent measurement of the maximum available capacity of the battery(pack)in the ground in-orbit-simulation test and providing applicable training samples for the in-orbit SOH estimation model is also an urgent problem that has to be solved simultaneously.Furthermore,compared with battery cells,the inconsistency within the battery pack also makes it more challenging to the measurement and estimation of the maximum available capacity.Focusing on the challenging issues above,this dissertation researches the satellite lithium-ion battery SOH estimation from the following three aspects,namely,the measurement of maximum available capacity during the ground in-orbit-simulation test,in orbit performance degradation characterization,and long-term SOH estimation model development.Firstly,focusing on the difficulties of measuring the maximum available capacity under the constraints of the ground test conditions and cell inconsistency,a ground equivalent measurement method for the maximum available capacity of satellite lithium-ion battery pack under the shallow charge-discharge process is proposed.A battery pack discharge behavior model is developed considering the testing stresses of ground test and cell inconsistency.By setting the battery cell initial state and discharge current rate,a virtual fully discharge is simulated from a full charge state to satisfy requirements of maximum available capacity measurement.Hence,the equivalent maximum available capacity measurement can be realized.Experimental results show that the proposed method has better measuring accuracy and stability compared with the methods based on first-order and second-order equivalent circuit models.And the proposed method can realize the continuous equivalent measurement of maximum available capacity under the constraints of shallow charge-discharge conditions of the ground-simulated in-orbit test,which can provide available training samples for in orbit maximum av ailable capacity estimation model.Secondly,focusing on the difficulties of performance degradation characterization under constraints of in orbit operating conditions,an in-orbit performance degradation characterization method is proposed based on the measurable parameters.A cluster of in-orbit performance degradation characterization parameters is developed based on the time difference,voltage difference,and current integral so that the satellite performance degradation can be observed in orbit.And then,these high-dimensional performance degradation characterization parameters are fused and transformed to decrease the information redundancy and unobservable noise.Hence,accuracy and adaptability are promoted.Experimental results indicate that the proposed method has higher relevance with maximum available capacity than incremental capacity analysis,mean voltage falloff,and sample entropy.The proposed method can provide observable performance degradation characterization parameters as the input of the in-orbit maximum available capacity estimation model.Thirdly,focusing on the maximum available capacity estimation under the feature of slowly-degrading,an event-driven hybrid maximum available capacity in-orbit estimation model of the satellite lithium-ion battery pack is developed.According to Lebesgue sampling theory,the dynamic adaptive optimization of the time scale for the maximum available capacity estimation is realized driven by the in-orbit observation of performance degradation characterization parameter.This directly reduces the accumulation error from long-term estimation.On this basis,a variable time scale maximum available capacity estimation state-space model is established.The fusion of the "degradation characterization param eter-maximum available capacity" regression model and performance degradation empirical model is realized to further reduce estimation error due to limited ground test samples and observation errors of in orbit degradation characterization parameters.Expe rimental results indicate that the proposed method has higher SOH estimation accuracy compared with direct estimation methods based on typical machine learning and deep learning methods.Finally,the validation and verification are conducted based on the ground-simulated in-orbit test data of “2P11S” and “3P11S” lithium-ion battery packs for two actual spacecraft correspondingly.The validation results show that the proposed “ground-in-orbit” related method can realize the maximum available capacity estimation and SOH estimation under the constraints of ground testing conditions and in orbit operating conditions.The proposed method can provide effective key technical support focusing on the requirement of battery pack performance degradation assessment and prediction for both ground test and in-orbit application.