Satellite storage battery charge state monitoring method and system

Abstract

The invention discloses a satellite storage battery charge state monitoring method and system, and the method comprises the following steps: S1, constructing a second-order RC equivalent circuit model, and constructing a system equation and an observation equation of the second-order RC equivalent circuit model; s2, acquiring ohm internal resistance parameters and polarization resistance-capacitance parameters of the battery according to response characteristics of mixed short-time pulse discharge of the lithium battery; s3, carrying out discretization expression on the system equation; and S4, calculating the state of charge of the satellite storage battery through an EKF method. According to the invention, a feasible technical solution is provided for monitoring the SOC of the storage battery of the orbit satellite.

Description

Technical Field

[0001] The present invention relates to a circuit monitoring system, and in particular to a method and system for monitoring the state of charge of a satellite battery. Background Art

[0002] Currently, on-orbit batteries are monitored using a coulomb meter, and the coulomb meter needs to be sent an instruction to start. The initial value of the coulomb meter is the nominal capacity of the battery, with the unit of Ah. The current common monitoring method for satellite battery capacity is the ampere-hour integration method. However, the ampere-hour integration method has problems such as difficulty in accurately obtaining the initial value of SOC (State Of Charge), and inaccurate current measurement will cause the SOC estimation error to continuously accumulate and increase. There is also such a situation that when the battery is not fully charged, but after sending the coulomb meter function start instruction, the displayed value of the battery coulomb meter is the nominal capacity, which obviously does not conform to the actual situation. Therefore, it is particularly necessary to adopt a method that can reflect the state of charge of the satellite battery in real time. Considering that the ambient temperature of the satellite battery is relatively stable, usually 15-20 °C, therefore, in the method of the present invention, for the method of monitoring the battery SOC, only the relatively stable ambient temperature is considered, and the influence of ambient temperature change on the battery capacity is ignored. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for monitoring the state of charge of a satellite battery to solve the problems raised in the above background art.

[0004] To achieve the above object of the invention, one aspect of the present invention provides a method for monitoring the state of charge of a satellite battery, including the following steps:

[0005] Step S1, construct a second-order RC (Resistor-Capacitance circuit) equivalent circuit model, and construct the system equation and observation equation of the second-order RC equivalent circuit model. The circuit model is formed by connecting an ideal voltage source U in series OC , and resistors R 0 , R 1 , R 2 , where R 0 is the ohmic internal resistance, R 1 and R 2 are polarization resistances, R 1 and the polarization capacitance C 1 , R 2 and the polarization capacitance C 2 respectively form RC parallel circuits, and the terminal voltage of the battery is U T ; the system equation is expressed as the following formula:

[0006] ,

[0007] The observation equation formula is as follows:

[0008] ,

[0009] where U T is the terminal voltage of the storage battery, I T is the charge / discharge current of the storage battery, Q n is the rated capacity of the storage battery, R 0 is the internal resistance of the storage battery, U 1 is the terminal voltage of the internal polarization resistance R 1 of the storage battery, U 2 is the terminal voltage of the internal polarization resistance R 2 of the storage battery;

[0010] Step S2: Obtain the battery ohmic internal resistance parameter and polarization resistance-capacitance parameter through the response characteristics of the lithium battery hybrid short-time pulse discharge;

[0011] Step S3: Discretize the system equation;

[0012] Step S4: Calculate the state of charge of the satellite storage battery through the EKF method.

[0013] Furthermore, in step S2, a discharge curve graph is fitted according to the system equation to obtain the storage battery parameter values under various states of charge.

[0014] Furthermore, the discretization expression in step S3 includes the following steps:

[0015] Step S301: Discretize the system equation at time k:

[0016] ,

[0017] After simplification, it is obtained:

[0018] ,

[0019] Step S302: Let , , then the above formula is expressed as the following formula:

[0020] , where:

[0021] ,

[0022] where R 1 、R 2 are the internal polarization resistances of the storage battery, R 0 is the internal resistance of the storage battery, C 1 、C 2is the internal polarization capacitance of the storage battery, T S is the test sampling period, I T is the charging / discharging current of the storage battery, Q n is the rated capacity of the storage battery, U T is the terminal voltage of the storage battery, U OC (SOC) is the internal electromotive force of the storage battery.

[0023] Furthermore, the nonlinear system:

[0024] ,

[0025] wherein, is the system noise value, which follows a normal distribution with a mean of 0 and a variance of Q; is the measurement noise value, which follows a normal distribution with a mean of 0 and a variance of R; The process of performing the EKF algorithm on the nonlinear system includes the following steps:

[0026] Step S401, initialize the assignment, let SOC = 1, U 0 = 0, U 1 = 0, U 2 = 0, and the initial state quantity is expressed as:

[0027] ;

[0028] Let the initial value of the error covariance P k-1 = 0.1;

[0029] The initial value of the state noise variance Q k-1 = [1e -9 0 0; 0 1e -9 0; 0 0 1e -9 ;

[0030] The initial value of the observation noise variance R k-1 = 5e -6 ;

[0031] Step S402, perform a priori prediction according to the state equation, and the formula is as follows:

[0032] ;

[0033] Step S403, update the error covariance, and the formula is as follows:

[0034] ;

[0035] Step S404, calculate the Kalman gain, and the formula is as follows:

[0036] ;

[0037] Step S405, calculate the optimal estimated value x k + , the state estimation update formula is as follows:

[0038] ;

[0039] Step S406, update the error covariance state, and the formula is as follows:

[0040] ,

[0041] where E is the identity matrix.

[0042] Another aspect of the present invention provides a satellite battery state of charge monitoring system, including a circuit model module, a parameter acquisition module, a discretization module, and an EKF module, where:

[0043] The circuit model module is used to construct a second-order RC equivalent circuit model, and construct the system equation and the observation equation of the second-order RC equivalent circuit model. The circuit model is formed by connecting an ideal voltage source U in series OC , and a resistor R 0 , R 1 , R 2 , where R 0 is the ohmic internal resistance, R 1 and R 2 are polarization resistors, R 1 is connected in parallel with the polarization capacitor C 1 , R 2 is connected in parallel with the polarization capacitor C 2 , the terminal voltage of the battery is U T ; the system equation is expressed as the following formula:

[0044] ,

[0045] The observation equation formula is:

[0046] ,

[0047] where U T is the battery terminal voltage, I T is the battery charge / discharge current, Q n is the battery rated capacity, R 0 is the battery internal resistance, U 1 is the terminal voltage of the battery internal polarization resistor R 1 , U 2 is the terminal voltage of the battery internal polarization resistor R 2 ;

[0048] The parameter acquisition module is used to obtain the battery ohmic internal resistance parameter and the polarization resistance-capacitance parameter by the response characteristics of the lithium battery to the hybrid short-time pulse discharge;

[0049] The discretization module is used to discretize the system equation;

[0050] The EKF module is used to calculate the state of charge of the satellite battery by the EKF method. Compared with the prior art, the present system and method have the following advantages:

[0051] The EKF algorithm can effectively solve the problems such as the continuous accumulation and increase of the SOC estimation error caused by the ampere-hour integration method, has a strong correction ability for the SOC initial value, and can quickly eliminate the initial error; the EKF forms a closed-loop system based on the feedback control idea, can correct the SOC value in real time, effectively avoid the error accumulation, and maintain the estimation accuracy. Description of the Drawings

[0052] Figure 1 It is a flowchart of a method for monitoring the state of charge of a satellite battery.

[0053] Figure 2 It is a block diagram of a second-order RC equivalent circuit model.

[0054] Figure 3 It is a pulse discharge curve diagram of the battery.

[0055] Figure 4 It is an error diagram of the battery SOC under different charging currents by using the present method. Detailed Embodiment

[0056] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0057] As Figure 1 shown in the flowchart of the method of the present invention, the embodiments of the present invention provide a method for monitoring the state of charge of a satellite battery, and the specific steps are as follows:

[0058] Step S1, construct an equivalent circuit model of a second-order RC equivalent circuit, as Figure 2 shown in the block diagram of the equivalent circuit model. Among them, U oc represents an ideal voltage source, which has a non-linear relationship with the SOC; R 0 represents the ohmic internal resistance, R 1 R 2 is the polarization resistance, C 1 C2 is a polarization capacitor, U t represents the terminal voltage of the battery. By connecting an ideal voltage source U in series OC , and a resistor R 0 , R 1 , R 2 , R 1 and the polarization capacitor C 1 , R 2 and the polarization capacitor C 2 respectively form RC parallel circuits. According to Kirchhoff's law, the system equation and the observation equation can be obtained as follows. Define the discharge current direction as positive and the charge current as negative.

[0059] The formula of the system equation is:

[0060] ,

[0061] The formula of the observation equation is:

[0062] ,

[0063] where U T is the terminal voltage of the storage battery, I T is the charge / discharge current of the storage battery, Q n is the rated capacity of the storage battery, R 0 is the internal resistance of the storage battery, U 1 is the terminal voltage of the internal polarization resistance R 1 of the storage battery, U 2 is the terminal voltage of the internal polarization resistance R 2 of the storage battery;

[0064] Step S2, obtain the satellite battery model parameters.

[0065] Select to test the hybrid pulse charge and discharge characteristics (HPPC, Hybrid Pulse Power Characteristic) of the lithium battery, explore the battery polarization phenomenon through the response characteristics of short-time pulse discharge, and identify the ohmic internal resistance parameters and polarization resistance-capacitance parameters of the battery accordingly. As Figure 3 shown, for a single storage battery with a capacity of 5 Ah, perform a discharge of 0.5C, i.e., 2.5 A, and the SOC discharges from 100% to 95%. According to the system equation, fit the transient characteristics of the discharge curve at SOC = 95% to obtain the values of R 0 , R 1 , R 2 , C 1 , C 2 , U oc .

[0066] According to this method, record the values of the battery parameters at various SOC states when the SOC drops from 100% to 10%, as shown in Table 1:

[0067] Table 1 Values of each battery parameter at different SOC states (ambient temperature 15°C)

[0068]

[0069] Step S3, discretize the system equation. It includes the following steps:

[0070] Step S301, discretize the system equation at time k:

[0071] ,

[0072] After simplification, we get:

[0073] .

[0074] Step S302, let , , then the above equation can be written as:

[0075] ,

[0076] where, , , , .

[0077] Step S4, use the EKF method to calculate the SOC of the satellite battery.

[0078] For a nonlinear system:

[0079] ,

[0080] where, is the system noise value, which follows a normal distribution with a mean of 0 and a variance of Q, i.e., ; is the measurement noise value, which follows a normal distribution with a mean of 0 and a variance of R, i.e., P(υ) ~ N(0, R).

[0081] The EKF algorithm includes the following steps:

[0082] Step S401, initialize the assignment:

[0083] Let SOC = 1, U 0 = 0, U 1 = 0, U 2 = 0, that is, the initial state quantity is ;

[0084] Let the initial value of the error covariance be P k-1 = 0.1;

[0085] Let the initial value of the state noise variance be Q k-1 = [1e -9 0 0; 0 1e -9 0; 0 0 1e -9 ;

[0086] Let the initial value of the observation noise variance be R k-1 = 5e -6 ;

[0087] Step S402, perform a priori prediction according to the state equation, and the formula is as follows:

[0088] ;

[0089] Step S403, update the error covariance, and the formula is as follows:

[0090] ;

[0091] Step S404, calculate the Kalman gain, and the formula is as follows:

[0092] ;

[0093] Step S405, calculate the optimal estimated value x k + , and the state estimation update formula is as follows: ;

[0094] Step S406, the error covariance state update equation, and the formula is as follows:

[0095] ,

[0096] where E is the identity matrix.

[0097] Step S5, verify the EKF algorithm.

[0098] Select the EKF algorithm to calculate the SOC of the battery and evaluate the accuracy and feasibility of the algorithm. As Figure 4 shown, by using different charging currents to charge a single battery and through the EKF algorithm, it can be found that after rapid iteration, the steady-state error of the SOC does not exceed 1%. Therefore, this method provides a feasible technical solution for the on-orbit satellite battery SOC monitoring.

[0099] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A satellite battery charge state monitoring method, characterized in that: The following steps are involved: Step S1, constructing a second-order RC equivalent circuit model, and constructing a system equation and an observation equation of the second-order RC equivalent circuit model. The circuit model is constructed by connecting an ideal voltage source U OC , and resistors R0, R1, R2, where R0 is the ohmic internal resistance, R1 and R2 are polarization resistors, R1 and polarization capacitor C1, R2 and polarization capacitor C2 form RC parallel circuits respectively, and the terminal voltage of the battery is U T ; The system equation is expressed as the following formula: ， The observation equation formula is: ， Among them U T is the battery terminal voltage, I T is the battery charge / discharge current, Q n is the rated capacity of the battery, R0 is the internal resistance of the battery, U1 is the terminal voltage of the internal polarization resistance R1 of the battery, and U2 is the terminal voltage of the internal polarization resistance R2 of the battery; Step S2, obtaining the battery ohmic internal resistance parameter and polarization resistance and capacitance parameter by analyzing the response characteristics of the lithium battery mixed short-time pulse discharge; Step S3, discretizing the system equation; Step S4, calculating the state of charge of the satellite battery by using the EKF method.

2. A satellite battery charge state monitoring method according to claim 1, characterized in that: Step S2 is to fit the discharge curve according to the system equation to obtain the battery parameter values ​​under various charge states.

3. A satellite battery charge state monitoring method according to claim 1, characterized in that: The discretization expression in step S3 includes the following steps: Step S301, discretize the system equation at time k: ， After simplification, we get: ， Step S302: , , then the above formula is expressed as the following formula: ,in: Where R1 and R2 are the internal polarization resistance of the battery, R0 is the internal resistance of the battery, C1 and C2 are the internal polarization capacitance of the battery, and T S is the test sampling period, I T is the battery charge / discharge current, Q n is the rated capacity of the battery, U T is the battery terminal voltage, U OC (SOC) is the internal potential of the battery.

4. A satellite battery charge state monitoring method according to claim 1, characterized in that: Nonlinear Systems: , in, is the system noise value, which obeys the normal distribution, has a mean of 0 and a variance of Q; is the measurement noise value, which obeys the normal distribution, has a mean of 0 and a variance of R; the EKF algorithm process for the nonlinear system includes the following steps: Step S401, initialization assignment, let SOC=1, U0=0, U1=0, U2=0, the initial state quantity is expressed as: ； Let the initial value of error covariance be P k-1 =0.1; Initial value of state noise variance Q k-1 = [1e -9 0 0; 0 1e -9 0; 0 0 1e -9 ]; Initial value of observation noise variance R k-1 =5e -6 ; Step S402, perform a priori prediction based on the state equation, the formula is as follows: ； Step S403, update the error covariance, the formula is as follows: ； Step S404, calculate the Kalman gain, the formula is as follows: ； Step S405, calculate the optimal estimate x k + ,The state estimation update formula is as follows: ； Step S406, update the error covariance state, the formula is as follows: ， Where E is the identity matrix.

5. A satellite battery charge state monitoring system, characterized in that: It includes circuit model module, parameter acquisition module, discrete module and EKF module, among which: The circuit model module is used to construct a second-order RC equivalent circuit model, and to construct the system equation and observation equation of the second-order RC equivalent circuit model. The circuit model is connected in series with an ideal voltage source U OC , and resistors R0, R1, R2, where R0 is the ohmic internal resistance, R1 and R2 are polarization resistors, R1 is connected in parallel with polarization capacitor C1, R2 is connected in parallel with polarization capacitor C2, and the terminal voltage of the battery is U T ; The system equation is expressed as the following formula: ， The observation equation formula is: ， Among them U T is the battery terminal voltage, I T is the battery charge / discharge current, Q n is the rated capacity of the battery, R0 is the internal resistance of the battery, U1 is the terminal voltage of the internal polarization resistance R1 of the battery, and U2 is the terminal voltage of the internal polarization resistance R2 of the battery; The parameter acquisition module is used to obtain the battery ohmic internal resistance parameters and polarization resistance and capacitance parameters through the response characteristics of the lithium battery mixed short-time pulse discharge; The discrete module is used to discretize the system equations; The EKF module is used to calculate the state of charge of the satellite battery using the EKF method.

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