CN114200311A - GEO satellite nickel-hydrogen storage battery on-orbit performance analysis method based on telemetering data - Google Patents
GEO satellite nickel-hydrogen storage battery on-orbit performance analysis method based on telemetering data Download PDFInfo
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Abstract
The invention provides an in-orbit performance analysis method of a GEO satellite hydrogen-nickel storage battery based on telemetering data, which is used for analyzing each charge and discharge process of the GEO satellite storage battery during the in-orbit period, acquiring a charge and discharge electric quantity value sequence of the storage battery according to charge and discharge current telemetering data, establishing a correlation model between the electric quantity of the storage battery and the temperature, pressure and voltage of the storage battery on the basis of the correlation model, performing model parameter fitting according to the telemetering sequence value of the temperature, pressure and voltage of the storage battery and the charge and discharge electric quantity sequence value of the storage battery during each charge and discharge process, and performing long trend analysis on the fitting parameter value of each charge and discharge process during the in-orbit period, thereby providing a new technical approach for the abnormality detection of the hydrogen-nickel satellite storage battery and providing technical support for the in-orbit management and the service life evaluation of the storage battery.
Description
Technical Field
The invention relates to an in-orbit performance analysis method for a GEO satellite nickel-hydrogen storage battery based on telemetering data, and belongs to the field of spacecraft in-orbit performance evaluation.
Background
With the increase of the on-orbit time of the satellite, the performance of the satellite-borne storage battery is gradually reduced, and when the situation is serious, the energy balance state of the whole satellite can be influenced. The accurate grasp of the performance degradation degree of the storage battery influences the result of energy balance evaluation, and is an important basis for making and modifying the satellite energy use strategy. The on-track performance change of the storage battery is usually monitored by using the discharging final voltage and the charging-discharging ratio of the storage battery at present, but the two indexes are greatly influenced by the load change condition; the real charge capacity and the internal resistance of the satellite-borne hydrogen-nickel storage battery can not be effectively monitored through the measured data. On the basis of observing a large amount of satellite telemetering data, a correlation model between the electric quantity of the hydrogen-nickel storage battery and the voltage, the temperature and the pressure is provided, model parameter fitting is carried out through the telemetering data, a model parameter sequence value has a regular change trend, the change conditions of different service life stages of the satellite can be reflected, and a new thought is provided for storage battery performance change evaluation.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a GEO satellite hydrogen-nickel storage battery on-orbit performance analysis method based on telemetering data, which is used for analyzing each charge and discharge process of the GEO satellite storage battery during on-orbit, acquiring a charge and discharge electric quantity value sequence of the storage battery according to charge and discharge current telemetering data, establishing a correlation model between the electric quantity of the storage battery and the temperature, pressure and voltage of the storage battery on the basis of the correlation model, performing model parameter fitting according to the charge and discharge electric quantity sequence value and the telemetering sequence value of the storage battery during each charge and discharge process, and performing long trend analysis on the fitting parameter value of each charge and discharge process during on-orbit, so that a new technical approach can be provided for the abnormal detection of the hydrogen-nickel satellite storage battery, and technical support can be provided for on-orbit management and service life evaluation of the hydrogen-nickel storage battery.
The technical scheme adopted by the invention comprises the following steps:
step 1: the method for establishing the storage battery performance evaluation model mainly comprises the following steps of,
step 1.1: and establishing a correlation model of the electric quantity and the temperature of the storage battery.
Step 1.2: and establishing a correlation model of the electric quantity and the voltage of the storage battery.
Step 1.3: and establishing a correlation model of the electric quantity and the pressure of the storage battery.
step 2.1: obtaining satellite on-orbit charging and discharging time information sequence, timec＝{(ctb1,cte1),(ctb2,cte2),...,(ctbm,ctem)},timecFor charging time series, ctbiI is more than 0 and less than or equal to m and is the ith charging starting time cteiI is more than 0 and less than or equal to m and is the ith charging end time; timed＝{(dtb1,dte1),(dtb2,dte2),...,(dtbn,dten)},timecFor a discharge time sequence, dtbiI is more than 0 and less than or equal to n and is the ith discharge starting time, dteiI is more than 0 and less than or equal to n and is the ith discharge ending time;
step 2.2: acquiring a satellite-degree telemetry data sequence T { (T)1,time1),(t2,time2),...,(tk,timek) Where t isiI is more than 0 and less than or equal to k is a temperature value, timeiK is more than 0 and less than or equal to k is the temperature sampling time;
step 2.3: acquiring a satellite pressure telemetry data sequence U { (U)1,time1),(u2,time2),...,(ux,timex) In which uiX is a voltage value with i more than 0 and less than or equal to timeiX is more than 0 and less than or equal to 0 and is the sampling time;
step 2.4: acquiring a satellite force telemetry data sequence P { (P)1,time1),(p2,time2),...,(py,timey) In which p isiI is more than 0 and less than or equal to y is a pressure value, timeiI is more than 0 and is less than or equal to y, which is the sampling time;
step 2.5: obtaining satellite discharge electric quantity sequence Qc＝{(qc1,time1),(qc2,time2),...,(qcz,timez) Wherein q isci,0＜i≤z
For charging electric quantity value, timeiZ is more than 0 and less than or equal to z is sampling time; qd＝{(qd1,time1),(qd2,time2),...,(qds,times) Wherein q isdiS is a discharge electric quantity value when i is more than 0 and less than or equal to timeiAnd s is more than 0 and less than or equal to 0 and is the sampling time.
And step 3: performing model parameter fitting according to the storage battery performance evaluation model and the telemetering data information, wherein the method comprises the following aspects:
step 3.1: according to timec、QcSequence value fitted to T, ATc＝{aTc1,aTc2,...,aTcm}，aTciI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; b isTc＝{bTc1,bTc2,...,bTcm}，bTciI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; cTc＝{cTc1,cTc2,...,cTcm}，cTciAnd m is more than 0 and less than or equal to the ith charging process fitting value. According to timedSequence value fitted to T, ATd＝{aTd1,aTd2,...,aTdm}，aTdiI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; b isTd＝{bTd1,bTd2,...,bTdm}，bTdiAnd m is more than 0 and less than or equal to the ith charging process fitting value.
Step 3.2: according to timec、QdSequence value fitted to U, AUc＝{aUc1,aUc2,...,aUcm}，aUciM is more than 0 and less than or equal to the ith charging process fitting value, BUc＝{bUc1,bUc2,...,bUcm}，bUciM is more than 0 and less than or equal to the ith charging process fitting value, Cuc＝{cuc1,cuc2,...,cucm}，cTciAnd m is more than 0 and less than or equal to the ith charging process fitting value. According to timedSequence value fitted to U, AUd＝{aUd1,aUd2,...,aUdm}，aUdiI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; b isUd＝{bUd1,bUd2,...,bUdm}，bUdiM is more than 0 and less than or equal to the ith charging process fitting value, CUd＝{cUd1,cUd2,...,cUdm}，cUdiAnd m is more than 0 and less than or equal to the ith charging process fitting value.
Step 3.3: according to timec、QdSequence value of fitting to P, APc＝{aPc1,aPc2,...,aPcm}，aPciM is more than 0 and less than or equal to the ith charging process fitting value, BPc＝{bPc1,bPc2,...,bPcm}，bPciAnd m is more than 0 and less than or equal to the ith charging process fitting value.
According to timedSequence value of fitting to P, APd＝{aPd1,aPd2,...,aPdm}，aPdiI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; b isPd＝{bPd1,bPd2,...,bPdm}，bPdiAnd m is more than 0 and less than or equal to the ith charging process fitting value.
And 4, step 4: according to the result of model parameter fitting, the performance of the storage battery is analyzed, and the method mainly comprises the following aspects:
step 4.1: analyzing the change condition of the temperature along with the change of the electric quantity of the storage battery in the charging and discharging process of the storage battery according to the change trend of the M1 parameter sequence in the rail period;
step 4.2: analyzing the change condition of the voltage along with the change of the electric quantity of the storage battery in the charging and discharging process of the storage battery according to the change trend of the M2 parameter sequence in the rail period;
step 4.3: and analyzing the change condition of the pressure along with the change of the electric quantity of the storage battery in the charging and discharging processes of the storage battery according to the change trend of the M3 parameter sequence in the rail period.
Step 4.4: and analyzing the rule of the change of the on-rail performance of the storage battery according to the change trend of the M1, M2 and M3 parameter sequences during the on-rail period.
The invention has the beneficial effects that: the method solves the management problems that the existing satellite storage battery on-orbit performance changes, the final discharge voltage and the charge-discharge ratio of the storage battery are usually used for monitoring at present, but the two indexes are greatly influenced by the load change condition, and the real charge quantity and the internal resistance of the satellite-borne hydrogen-nickel storage battery can not be effectively monitored through measured data. The correlation model between the electric quantity of the hydrogen-nickel storage battery and the voltage, the temperature and the pressure is provided, model parameter fitting is carried out through telemetering data, the model parameter sequence value has a regular change trend, the change conditions of different service life stages of a satellite can be reflected, and a new thought is provided for storage battery performance change evaluation.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a flow chart for processing on-track information;
FIG. 3(a), (b), (c), (d), (e) model M1 parameter fitting sequence values;
FIG. 4(a), (b), (c), (d), (e) model M2 parameter fitting sequence values;
FIG. 5(a), (b), (c), (d) model M3 parameter fitting sequence values.
Detailed Description
The present invention is further illustrated by the following examples and figures, including but not limited to the following examples.
Referring to fig. 1 and fig. 2, the invention provides a correlation model between the electric quantity of a nickel-hydrogen storage battery and voltage, temperature and pressure, and model parameter fitting is performed through telemetering data, and a model parameter sequence value has a regular change trend, so that the change conditions of different service life stages of a satellite can be reflected, and a new idea is provided for storage battery performance change evaluation.
Selecting a satellite to be analyzed, for example, the satellite identification is SatA, and establishing a storage battery evaluation model of the SatA;
step two, acquiring data information of SatA, and performing processing and related calculation;
step three: processing satellite SatA in-orbit data information as in fig. 2, e.g., analyzing start and stop times 2014.05.0600.00.00, 2021.10.1000.00.00, where start time 2014.05.0600.00.00 is no earlier than the time of SatA in-orbit and stop time 2021.10.1000.00.00 is later than the start time;
step four: and fitting the model parameter values established in the first step according to the data information acquired in the second step.
The first step described above specifically includes the steps of:
step 1.1: and establishing a correlation model of the battery capacity and the temperature of SatA.
Step 1.2: and establishing a correlation model of the electric quantity and the voltage of the storage battery of SatA.
Step 1.3: and establishing a correlation model of the storage battery capacity and the pressure of SatA.
The second step as described above specifically includes the steps of:
step 2.1: all the charging and discharging start and end time sequences of the satellite SatA between time intervals 2014.03.2000.00.00 and 2021.10.1000.00.00 are obtained, for example, the 695 th charging start time is 2014.06.1308:05:114, the discharging end time is 2014.06.1311:23:16, the 862 nd discharging start time is 2014.07.1112:02:05, and the discharging end time is 2014.07.1112:25: 31.
Step 2.2: a data sequence of the satellites SatA between time intervals 2014.05.0600.00.00, 2021.10.1000.00.00 is acquired.
Step 2.3: a sequence of pressure data for satellite SatA between time intervals 2014.05.0600.00.00, 2021.10.1000.00.00 is acquired.
Step 2.4 acquires a force data sequence for satellite SatA between time intervals 2014.05.0600.00.00, 2021.10.1000.00.00.
Step 2.5: a charge capacity and discharge capacity data sequence of the satellite SatA between time intervals 2014.05.0600.00.00, 2021.10.1000.00.00 is acquired.
The third step described above specifically includes the following steps:
step 3.1: fitting the values of the parameters of the M1 model (fig. 3(a), (b), (c), (d), (e)) with the temperature data and the charging capacity sequence data between the charging start time and the end time for each time, for example, fitting the M1 model with the temperature data and the charging capacity sequence data between the 695 th charging start time 2014.06.1308:05:114 and the discharging end time 2014.06.1311:23:16 to obtain a set of values 0.001828, -0.379658 and 4.440489; values of parameters of the M1 model are fitted by using temperature data and discharge electric quantity sequence data between the discharge starting time and the discharge ending time of each time, for example, a set of values obtained by fitting M1 by using data between 862 nd discharge starting time of 2014.07.1112:02:05 and discharge ending time of 2014.07.1112:25:31 are 0.063832 and-4.810924 respectively.
Step 3.2: fitting values of parameters of an M2 model (fig. 4(a), (b), (c), (d), (e)) by using voltage data and charging capacity sequence data between the charging start time and the end time of each time, for example, fitting the M2 model by using voltage data and charging capacity sequence data between the 695 th charging start time of 2014.06.1308:05:114 and the discharging end time of 2014.06.1311:23:16 to obtain a set of values of 0.000662, 0.753298 and 37.229508; values of parameters of the M2 model are fitted by voltage data and discharge electric quantity sequence data between the discharge starting time and the discharge ending time of each time, for example, a set of values obtained by fitting M2 by data between 862 nd discharge starting time of 2014.07.1112:02:05 and discharge ending time of 2014.07.1112:25:31 are-2.921488, 0.133153 and 38.267563 respectively.
Step 3.3: fitting values of parameters of an M3 model (fig. 5(a), (b), (c), (d)) with pressure data and charging capacity sequence data between the charging start time and the end time of each time, for example, fitting an M3 model with pressure data and charging capacity sequence data between the 695 th charging start time 2014.06.1308:05:114 and the discharging end time 2014.06.1311:23:16, respectively, to obtain a set of values 0.0616630 and 4.114601; values of parameters of the M3 model are fitted by pressure data and discharge electric quantity sequence data between the starting time and the ending time of each discharge, for example, a set of values obtained by fitting M3 by data between 862 nd time of discharge beginning 2014.07.1112:02:05 and 2014.07.1112:25:31 are-0.055107 and 4.408120 respectively.
The fourth step as described above specifically includes the steps of:
step 4.1: the on-orbit performance condition of the SatA storage battery is analyzed according to the sequence value of the M1 model parameter, as shown in FIG. 3, the main distribution range of the SatA value is 0.005-0.02, the SatA value is regularly distributed in each geographical shadow season, the charging time is short, and the charging time is long. The main distribution range of the coefficients is-1 to 0.55, the coefficients are regularly distributed in each earth shadow season, the discharge time is short, and the discharge time is short. The main distribution range of the coefficient values is-6-10, the coefficients are regularly distributed in each earth shadow season, the discharge time is long, and the discharge time is short. The main distribution range of the SatA is 0.2-0.41, and the SatA shows a slow rising trend. The main distribution range of the coefficients is between-6 and-4, and the coefficients are basically uniformly distributed. This means that the rate of temperature increase during the discharge of the satellite SatA battery becomes faster with increasing on-track time, per unit of discharged charge.
Step 4.2: the on-orbit performance condition of the SatA storage battery is analyzed according to the sequence value of the M2 model parameter, as shown in FIG. 4, the value of SatA is mainly distributed in the range of 0-0.001, the coefficient is mainly distributed in the range of 0.6-1, the coefficient and the main distribution range are 35-39, the coefficients are regularly distributed in each geographical shadow season, and the coefficients can observe an obvious rising trend. This means that the rate of increase of the satellite battery voltage per unit charge increases with increasing on-orbit time. The main distribution range of SatA is between-4 and-0.5, the main distribution range of coefficient is between 0.1 and 0.5, the main distribution range of coefficient is between 37 and 41, the coefficients are regularly distributed in each geographical shadow season, and the coefficient can be observed to obviously rise. This means that the rate of voltage drop of the satellite battery increases with increasing on-track time for a unit amount of discharged power.
Step 4.3: analyzing the on-orbit performance condition of the SatA storage battery according to the sequence value of the M3 model parameter, as shown in FIG. 5, the coefficient of the SatA is mainly distributed in the range of 0.056-0.06, and is regularly distributed in each geographical shadow season, and the whole SatA storage battery is in a descending trend. This means that the rate of increase in satellite battery pressure per unit charge slows as the on-orbit time increases. The main distribution range of the coefficients of SatA is-0.056-0.052, the ground shadows of spring in 2013 are regularly distributed in every ground shadow, the discharge time is short (the pressure is fast to decrease along with the increase of the discharge capacity), the discharge time is short and large (the pressure is slow to decrease along with the increase of the discharge capacity), and the overall tendency of rising is realized, namely the absolute value is reduced. The distribution range of the coefficients is between 4.7 and 5.5, the coefficients are regularly distributed in each earth shadow season, the discharge time is long, the discharge time is short, and the discharge time is short, so that the overall distribution trend is up. This means that the rate of pressure drop of the satellite battery per unit of discharged charge decreases with increasing on-orbit time.
Step 4.4, by synthesizing the parameter sequence values of M1, M2 and M3, it can be seen that the temperature rising rate of the SatA storage battery is slowly increased along with the increase of the on-track time of the SatA storage battery in the charging and discharging process under the condition of the same discharging electric quantity; the rate of voltage drop is increasing; the rate of pressure drop is increasing. Under the same charging capacity condition, the voltage rising rate is increased, and the pressure rising rate is reduced.
Claims (2)
1. An in-orbit performance analysis method of GEO satellite hydrogen-nickel storage batteries based on telemetering data is characterized by comprising the following steps:
step 1: establishing a correlation model M1 of the electric quantity and the temperature of the storage battery;
step 2: establishing a correlation model M2 of the electric quantity and the voltage of the storage battery;
and step 3: establishing a correlation model M3 of the electric quantity and the pressure of the storage battery;
and 4, step 4: obtaining satellite on-orbit charging and discharging time information sequence, timec＝{(ctb1,cte1),(ctb2,cte2),...,(ctbm,ctem)},timecFor charging time series, ctbiI is more than 0 and less than or equal to m and is the ith charging starting time cteiI is more than 0 and less than or equal to m and is the ith charging end time; timed＝{(dtb1,dte1),(dtb2,dte2),...,(dtbn,dten)},timecFor a discharge time sequence, dtbiI is more than 0 and less than or equal to n and is the ith discharge starting time, dteiI is more than 0 and less than or equal to n and is the ith discharge ending time;
and 5: acquiring a satellite-degree telemetry data sequence T { (T)1,time1),(t2,time2),...,(tk,timek) Where t isiI is more than 0 and less than or equal to k is a temperature value, timeiK is more than 0 and less than or equal to k is the temperature sampling time;
step 6: acquiring a satellite pressure telemetry data sequence U { (U)1,time1),(u2,time2),...,(ux,timex) In which uiX is a voltage value with i more than 0 and less than or equal to timeiX is more than 0 and less than or equal to 0 and is the sampling time;
and 7: acquiring a satellite force telemetry data sequence P { (P)1,time1),(p2,time2),...,(py,timey) In which p isiI is more than 0 and less than or equal to y is a pressure value, timeiI is more than 0 and is less than or equal to y, which is the sampling time;
and 8: obtaining satellite discharge electric quantity sequence Qc＝{(qc1,time1),(qc2,time2),...,(qcz,timez) Wherein q isciZ is a charging electric quantity value with i more than 0 and less than or equal to timeiZ is more than 0 and less than or equal to z is sampling time; qd＝{(qd1,time1),(qd2,time2),...,(qds,times) Wherein q isdiS is a discharge electric quantity value when i is more than 0 and less than or equal to timeiS is more than 0 and less than or equal to 0 and is the sampling time;
and step 9: according to timec、QcSequence value fitted to T, ATc＝{aTc1,aTc2,...,aTcm}，aTciM is more than 0 and less than or equal to the ith charging process fitting value, BTc＝{bTc1,bTc2,...,bTcm}，bTciM is more than 0 and less than or equal to the ith charging process fitting value, CTc＝{cTc1,cTc2,...,cTcm}，cTciM is more than 0 and less than or equal to i is the fitting value of the ith charging process according to timedSequence value fitted to T, ATd＝{aTd1,aTd2,...,aTdm}，aTdiI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; b isTd＝{bTd1,bTd2,...,bTdm}，bTdiI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained;
step 10: according to timec、QdSequence value fitted to U, AUc＝{aUc1,aUc2,...,aUcm}，aUciM is more than 0 and less than or equal to the ith charging process fitting value, BUc＝{bUc1,bUc2,...,bUcm}，bUciM is more than 0 and less than or equal to the ith charging process fitting value, Cuc＝{cuc1,cuc2,...,cucm}，cTciI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; according to timedSequence value fitted to U, AUd＝{aUd1,aUd2,...,aUdm}，aUdiI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; b isUd＝{bUd1,bUd2,...,bUdm}，bUdiM is more than 0 and less than or equal to the ith charging process fitting value, CUd＝{cUd1,cUd2,...,cUdm}，cUdiI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained;
step 11: according to timec、QdSequence value fitted to P, APc＝{aPc1,aPc2,...,aPcm}，aPciI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; b isPc＝{bPc1,bPc2,...,bPcm}，bPciI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; according to timedSequence value of fitting to P, APd＝{aPd1,aPd2,...,aPdm}，aPdiI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained; b isPd＝{bPd1,bPd2,...,bPdm}，bPdiI is more than 0 and is not more than m, and the fitting value of the ith charging process is obtained;
step 12: and analyzing the on-orbit performance of the storage battery according to the parameter fitting value sequences of M1, M2 and M3.
2. The in-orbit performance analysis method for GEO satellite nickel-hydrogen storage batteries based on the telemetry data as claimed in claim 1, wherein the step 12 comprises: analyzing the change condition of the temperature along with the change of the electric quantity of the storage battery in the charging and discharging process of the storage battery according to the change trend of the M1 parameter sequence in the rail period; analyzing the change condition of the voltage along with the change of the electric quantity of the storage battery in the charging and discharging process of the storage battery according to the change trend of the M2 parameter sequence in the rail period; analyzing the change condition of the pressure along with the change of the electric quantity of the storage battery in the charging and discharging process of the storage battery according to the change trend of the M3 parameter sequence in the rail period; and analyzing the rule of the change of the on-rail performance of the storage battery according to the change trend of the M1, M2 and M3 parameter sequences during the on-rail period.
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