SOC estimation method for solar power supply system of monitoring device

Abstract

The invention discloses a solar power supply system SOC estimation method of a monitoring device, and belongs to the technical field of electric power. According to charge and discharge curve characteristics of a lithium battery, on the basis of traditional ampere-hour integral estimation of the SOC, the SOC estimation method of variable-speed correction ampere-hour integral is provided; in the estimation process, the maximum available capacity of the battery is corrected regularly according to the battery temperature and the total charge-discharge cycle number of the battery; charging and discharging efficiency and current sampling precision are considered, and variable-speed ampere-hour integration is adopted; an initial SOC is estimated from the open circuit voltage and the polarization voltage. The method is simple, easy to implement, low in hardware cost, good in real-time performance and high in applicability, and the precision and robustness of battery SOC estimation are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a SOC estimation method for a solar power supply system of a monitoring device. Background Art

[0002] At present, the power supply system of the power monitoring device for intelligent inspection of transmission lines generally adopts a power supply system composed of solar panels and lithium batteries. In continuous rainy weather, in order to prevent the lithium battery from being damaged due to over-discharge and affecting the normal operation of the equipment, it is necessary to estimate the remaining power SOC of the lithium battery in order to adopt corresponding measures to ensure the normal operation of the battery and monitoring equipment.

[0003] The remaining capacity (SOC) of existing lithium batteries is defined as the percentage of the remaining battery capacity to the maximum available capacity; SOC estimation generally adopts the open circuit voltage plus ampere-hour integration algorithm for estimation. The ampere-hour integration method calculates the battery's state of charge by integrating the battery current over time. This method has a certain accuracy in calculating the amount of electricity discharged by the battery.

[0004] But its shortcomings are also obvious: because the lithium battery is a complex electrochemical system, the relationship between its working state and internal parameters is a complex nonlinear relationship. In order to accurately estimate the initial SOC, the battery needs to be fully stationary, and the battery state and its external environment (temperature, humidity, etc.) and its working state (charging and discharging voltage, current) will affect the battery capacity and power output capability. Therefore, it is necessary to consider the above factors to accurately estimate the initial SOC; if the initial SOC estimation is inaccurate, it will also lead to a huge difference between the estimated SOC and the actual SOC.

[0005] In addition, the ampere-hour integration needs to rely on high-precision current sampling to ensure that the collected current flowing into and out of the battery is equal to the actual current. High-precision current can reduce the cumulative error of the ampere-hour integration. If the current measurement is inaccurate in the current integration method, it will also cause SOC calculation errors, and the error is cumulative, and will gradually increase with the increase of time, seriously deviating from the true value. Summary of the invention

[0006] The present invention provides a SOC estimation method for a solar power supply system of a monitoring device, which effectively improves the accuracy and robustness of battery SOC estimation.

[0007] The present invention provides the following technical solutions:

[0008] A method for estimating the SOC of a solar power supply system of a monitoring device, wherein the solar power supply system comprises a battery and a solar panel, wherein the battery is connected to a high-precision current sampling circuit, a high-precision voltage sampling circuit and a high-precision temperature sampling circuit, and the SOC estimation method comprises:

[0009] S10: Obtain the number of charge and discharge cycles of the battery, and determine the influence coefficient K of the charge and discharge cycle number on the maximum available capacity of the battery according to the charge and discharge cycle number N ;

[0010] S20: Obtain the current temperature of the battery through a high-precision temperature sampling circuit, and determine the influence coefficient K of the current temperature on the maximum available capacity of the battery based on the current temperature T ;

[0011] S30: According to the influence coefficient K N and K T Calculate the maximum available capacity factor K at the current temperature and number of charge and discharge cycles C ;

[0012] K C =(1-δ)K T +δK N

[0013] Among them, δ is the set weight coefficient;

[0014] S40: Determine the calibration coefficient K of the initial SOC of the battery K ;

[0015] S50: Estimating the SOC of the battery outside the charging end and the discharging end by the following formula;

[0016]

[0017] Among them, SOC(t) is the estimated SOC at time t, SOC (t0) is the initial SOC, C max is the maximum available capacity of the battery, I bat (t) is the current sampling value at time t, K i The speed coefficient to be set.

[0018] Further, S10 includes:

[0019] S11: Calculate the total number of charges N1 and the total number of discharges N2, and calculate the number of charge and discharge cycles N through N1 and N2;

[0020] Wherein, N1 = total charge capacity / maximum available capacity, N2 = total discharge capacity / maximum available capacity, N = (N1+N2) / 2;

[0021] S12: Determine the influence coefficient K through the following piecewise function N ;

[0022] .

[0023] Further, the S20 includes:

[0024] S21: Use a brand new battery to conduct charge and discharge capacity experiments in different temperature ranges, and measure the maximum available capacity at different temperatures;

[0025] S22: using data fitting method to obtain the relationship between maximum available capacity and temperature;

[0026] S23: Obtain the current temperature T of the battery through a high-precision temperature sampling circuit, and obtain the maximum available capacity C at the current temperature based on the fitted relationship between the maximum available capacity and temperature. max (T);

[0027] S23: Calculate the influence coefficient K by the following formula T ;

[0028]

[0029] Among them, C max (Room temperature) is the maximum available capacity at the indicated temperature.

[0030] Further, the S40 includes:

[0031] S41: The internal resistance of the battery is measured by experiments at different charge and discharge states, different temperatures, different currents and different SOC values;

[0032] S42: Measure the charge and discharge state, temperature and current of the battery in real time, obtain the SOC value stored when the battery was powered off last time, obtain the internal resistance of the battery in the current state by looking up the internal resistance table, and calculate the polarization voltage V of the battery according to the obtained internal resistance polar ;

[0033] S43: Calculate the calibration coefficient K by the following formula K ;

[0034]

[0035] V sample is the voltage sampling value.

[0036] Furthermore, the SOC is estimated by the following formula in the interval at the end of battery charging:

[0037] SOC(t)=SOC threshold1 +K M ·(V charge_cutoff -V bat )

[0038]

[0039] Among them, KM is the charging calibration coefficient for the battery charging end segment, V threshold1 is the charging end inflection point voltage, SOC threshhold1 is the charging end inflection point voltage V threshold1 The corresponding remaining power, V charge_cutoff is the charging cut-off voltage, V bat is the battery voltage at time t, SOC 100 Indicates full charge.

[0040] Furthermore, the SOC is estimated by the following formula in the interval at the end of battery discharge:

[0041] SOC(t)=K' M ·(V bat -V discharge_cutoff )

[0042]

[0043] Among them, K' M is the charge calibration coefficient for the battery discharge end segment, V threshold2 is the discharge end inflection point voltage, SOC threshold2 is the discharge end inflection point voltage V threshold2 The corresponding remaining power, V discharge_off is the discharge cut-off voltage, and SOC0 represents zero charge.

[0044] Furthermore, the method further comprises:

[0045] S60: In the interval between the battery charging end and the battery discharging end, if the difference between the SOC estimated value at the current moment and the previous moment is greater than the set threshold, the SOC value is displayed in a variable step size to avoid a jump in the SOC value.

[0046] The present invention has the following beneficial effects:

[0047] According to the characteristics of the charge and discharge curves of lithium batteries, the present invention proposes a SOC estimation method of variable speed corrected ampere-hour integration on the basis of the traditional ampere-hour integration estimation of SOC; during the estimation process, the maximum available capacity of the battery is regularly corrected according to the battery temperature and the total number of charge and discharge cycles of the battery; variable speed ampere-hour integration is adopted considering the charge and discharge efficiency and the current sampling accuracy; the initial SOC is estimated according to the open circuit voltage and the polarization voltage. The method of the present invention is simple, easy to implement, low in hardware cost, good in real time, strong in applicability, and effectively improves the accuracy and robustness of battery SOC estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A flow chart of a method for estimating SOC of a solar power supply system of a monitoring device of the present invention;

[0049] Figure 2 Schematic diagram of a solar power supply system. DETAILED DESCRIPTION

[0050] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0051] The embodiment of the present invention provides a method for estimating SOC of a solar power supply system of a monitoring device, such as Figure 2 As shown, the solar power supply system includes a battery and a solar panel. The battery is connected to a sampling module and a parameter estimation module, etc. The sampling module includes a high-precision current sampling circuit, a high-precision voltage sampling circuit and a high-precision temperature sampling circuit.

[0052] The battery can be a lithium battery, such as a lithium iron phosphate battery and a ternary lithium battery module, etc., and can be a battery pack with different numbers of strings and capacities. After the single lithium battery is grouped into a battery pack and placed in a battery box, the battery control board can select the open circuit voltage-SOC comparison table corresponding to the battery type according to the battery type. The comparison table is based on the battery being fully charged and fully resting before discharging at a current of 0.5C; the SOC step is 5%, that is, after each 5% of the power is discharged, the battery is fully rested, and the open circuit voltage corresponding to the SOC is measured; the open circuit voltage-SOC comparison table can be obtained by following the steps in sequence.

[0053] The sampling module is a high-precision sampling circuit, including high-precision sampling of voltage, current, and battery temperature. A high-precision ADC (analog-to-digital converter, A / D converter) is used to achieve accurate sampling of battery external parameters. The data after ADC sampling is digitally filtered using a weighted sliding average filtering algorithm to obtain accurate battery voltage, current, and temperature values.

[0054] The parameter estimation module mainly realizes the estimation of the initial related parameters of the current ampere-hour integration algorithm: initial SOC, battery charge and discharge cycle number, battery maximum available capacity, battery charge and discharge polarization voltmeter, etc.

[0055] The estimation accuracy of the initial SOC directly determines the accuracy of the ampere-hour integration algorithm. Accurate and reliable initial SOC estimation has always been a difficult problem because it is affected by many factors: the static time of the battery determines whether the open circuit voltage estimation of the battery is accurate, the battery temperature and the number of charge and discharge cycles affect the maximum available capacity of the battery, and the charge and discharge polarization voltage V of the battery. ploar The internal resistance of the battery is mainly formed under the action of the charge and discharge current; the interaction of these factors jointly affects the estimation accuracy of the initial SOC. In order to accurately estimate the initial SOC, it is necessary to consider the accuracy of the open circuit voltage, the temperature of the battery, the number of charge and discharge cycles of the battery, and the influence of the charge and discharge polarization voltage of the battery.

[0056] To solve the above problems, Figure 1 As shown, the SOC estimation method of the present invention includes:

[0057] S10: Obtain the number of charge and discharge cycles of the battery, and determine the influence coefficient K of the charge and discharge cycle number on the maximum available capacity of the battery according to the charge and discharge cycle number. N .

[0058] Specifically, one implementation of this step includes:

[0059] S11: Calculate the total number of charges N1 and the total number of discharges N2, and calculate the number of charge and discharge cycles N through N1 and N2.

[0060] Among them, N1=total charging capacity / maximum available capacity, N2=total discharging capacity / maximum available capacity, N=(N1+N2) / 2.

[0061] Determine the maximum available capacity of the current battery based on N, and assume that the influence coefficient of the number of cycles on the maximum available capacity of the battery is K N , which can be expressed as

[0062] S12: Determine the influence coefficient K through the following piecewise function N ;

[0063]

[0064] The power consumption of power monitoring equipment is shallow charging and discharging for the battery. For a new lithium battery, the number of charge and discharge cycles can reach thousands. When the battery capacity decays by 80% relative to the initial maximum capacity, it is considered that the battery life has ended. In each period, the maximum available capacity of the battery can be considered unchanged. Therefore, in practical applications, K N The value of can be adopted as above equation.

[0065] The above value range of N is only an example and is not fixed, and needs to be re-divided and revalued according to the actual battery situation.

[0066] S20: Obtain the current temperature of the battery through a high-precision temperature sampling circuit, and determine the influence coefficient K of the current temperature on the maximum available capacity of the battery based on the current temperature T .

[0067] The maximum available capacity of the battery is more easily affected by temperature. To determine the influence coefficient K T , the present invention adopts the following method:

[0068] S21: Using a new battery, we conducted charge and discharge capacity experiments at different temperature ranges and measured the maximum available capacity at different temperatures.

[0069] S22: The relationship between the maximum available capacity and temperature is obtained using a data fitting method.

[0070] S23: Obtain the current temperature T of the battery through a high-precision temperature sampling circuit, and obtain the maximum available capacity C at the current temperature based on the fitted relationship between the maximum available capacity and temperature. max (T).

[0071] S23: Calculate the influence coefficient K by the following formula T ;

[0072]

[0073] Among them, C max (Room temperature) is the maximum available capacity at the indicated temperature.

[0074] The relationship between available capacity and temperature varies for different types of batteries. In practice, it is necessary to re-measure and obtain the fitting curve before applying it.

[0075] S30: According to the influence coefficient K N and K T Calculate the maximum available capacity factor K at the current temperature and number of charge and discharge cycles C ;

[0076] K C =(1-δ)K T +δK N

[0077] The maximum available capacity of the battery is affected by temperature at a certain number of cycles, which is much greater than the number of cycles. Therefore, the present invention uses a weighted method to determine the maximum available capacity coefficient of the battery at the current temperature and number of cycles. δ is a set weight coefficient.

[0078] S40: Determine the calibration coefficient K of the initial SOC of the battery K .

[0079] The estimation accuracy of the initial SOC of the battery is the basis for the accuracy of the entire ampere-hour integral estimation of the power. It is a common method to estimate the initial SOC based on the open circuit voltage, but this method is heavily dependent on the static time of the battery. The static time is generally measured in days to obtain a more accurate value, which is unrealistic in practical applications. When the battery is charged and discharged, different SOCs correspond to different battery internal resistances, which in turn leads to different charge and discharge polarization voltages, which also leads to inaccurate estimates of the open circuit voltage. Therefore, the calibration coefficient K of the initial SOC is KIt is a coefficient related to the battery state (charging, discharging state), battery SOC, battery current, and battery temperature. Obtain coefficient K K The specific steps include:

[0080] S41: The internal resistance of the battery is measured through experiments at different charge and discharge states, different temperatures, different currents and different SOC values.

[0081] This step requires measuring the resistance of the battery during charge and discharge, and using the DC internal resistance test method given by the HPPC test experiment to obtain the charge and discharge internal resistance table of the battery under different SOC states.

[0082] S42: Measure the charge and discharge state, temperature and current of the battery in real time, obtain the SOC value stored when the battery was powered off last time, obtain the internal resistance of the battery in the current state by looking up the internal resistance table, and calculate the polarization voltage V of the battery according to the obtained internal resistance polar .

[0083] The battery status, temperature, and current can be obtained in real time. The SOC is the SOC stored when the power was last turned off. Based on these parameters, the internal resistance of the battery in this state can be obtained by looking up the table, and then the polarization voltage V of the battery can be obtained. polar .

[0084] S43: Calculate the calibration coefficient K by the following formula K ;

[0085]

[0086] V sample is the voltage sampling value, and the initial SOC corrected by this coefficient is K K SOC (t0) .

[0087] S50: Estimating the SOC of the battery outside the charging end and the discharging end by the following formula;

[0088]

[0089] Among them, SOC(t) is the estimated SOC at time t, SOC (t0) is the initial SOC, C max The maximum available capacity of the battery is I bat (t) is the current sampling value at time t.

[0090] After the parameter estimation is completed, the formula for estimating the power by integrating ampere-hours is as above, K i is the speed-changing coefficient of the speed-changing ampere-hour integral. Considering the charging and discharging efficiency and current sampling accuracy, when integrating the sampled current, it is necessary to multiply it by a charging and discharging efficiency coefficient K. iIn general, K i Set it as a constant and range from 0.9 to 0.95.

[0091] When using the above formula to estimate SOC, the maximum available capacity of the battery and the initial SOC are calibrated regularly. The calibration method is carried out according to the above principle to make the estimation more accurate.

[0092] When the above-mentioned ampere-hour integral formula with calibration parameters is used to estimate the remaining power, it has good accuracy in the interval segment except the end of charging and discharging, but at the two ends of charging and discharging, the estimation using the above formula will result in a large error; according to the charging and discharging SOC-OCV curve of the lithium battery, it can be known that the curve can be approximately equivalent to a three-segment curve: a flat area in the middle and a linear area at the end; therefore, the present invention proposes a segmented estimation strategy, the flat area in the middle is estimated by the above-mentioned ampere-hour integral formula, and a linear calibration method is used at the end of charging and discharging to estimate the SOC based on the voltage.

[0093] The SOC is estimated in the battery charging terminal section using the following formula:

[0094] SOC(t)=SOC threshold1 +K M ·(V charge_cutoff -V bat )

[0095]

[0096] Among them, K M is the charging calibration coefficient for the battery charging end segment, V threshold1 is the charging end inflection point voltage, SOC threshhold1 is the charging end inflection point voltage V threshold1 The corresponding remaining power, V charge_cutoff is the charging cut-off voltage, V bat is the battery voltage at time t, SOC 100 Indicates full charge.

[0097] The SOC is estimated by the following formula in the interval at the end of battery discharge:

[0098] SOC(t)=K' M ·(V bat -V discharge_cutoff )

[0099]

[0100] Among them, K' M is the charge calibration coefficient for the battery discharge end segment, V threshold2 is the discharge end inflection point voltage, SOCthreshold2 is the discharge end inflection point voltage V threshold2 The corresponding remaining power, V discharge_off is the discharge cut-off voltage, and SOC0 represents zero charge.

[0101] In practice, batteries work in different temperature ranges. When calibrating at the end of charge and discharge, if a set of terminal calibration point voltage data is used, SOC jump will occur. The reason is that the voltage platform of lithium batteries is different at high and low temperatures. The voltage platform is high at high temperature and low at low temperature, resulting in a set of parameters that are not suitable for estimation accuracy in the full temperature range. The present invention uses two different sets of calibration parameters K in the high and low temperature ranges according to the working temperature of the battery. M and K' M , to adapt to the SOC estimation correction of the battery under low temperature conditions and achieve higher estimation accuracy in a wide temperature range.

[0102] In practice, there is also a situation where after the battery is fully charged or discharged, the remaining power needs to be calibrated to 100% or 0%; however, the SOC obtained by integrating ampere-hours is far from the calibration point, which will cause a jump in power at the end of charging and discharging, affecting the user experience. To solve the above problem, the method of the present invention also includes:

[0103] S60: In the interval between the battery charging end and the battery discharging end, if the difference between the SOC estimated value at the current moment and the previous moment is greater than the set threshold, the SOC value is displayed in a variable step size, which effectively avoids the problem of SOC jump.

[0104] Specifically, first, determine whether it is the first time to power on; if so, display according to display strategy 1: according to the charge and discharge mode of the battery, the battery temperature, the battery capacity and the battery current, and according to the charge and discharge polarization voltage table, obtain the polarization voltage V ploar ; At this time, the sampling voltage V sample ; Open circuit voltage V ocv =V sample -V ploar ; Based on this voltage, check the open circuit voltage-SOC table to get SOC_temp; coefficient K K is the correction factor of the initial SOC, which is related to the maximum available capacity of the battery, the number of charge and discharge cycles, and the temperature; then the displayed SOC0 when powering on is K K *SOC_temp; then estimate according to the gear shift ampere-hour integral; the displayed SOC is equal to the estimated SOC.

[0105] Secondly, determine whether it is at the end of charging; if so, display according to display strategy 2: at the end of charging, a linear calibration method is used; the data point composed of the voltage and SOC at the inflection point at the end of the charging curve is (V threshhold1, SOC threshold1 ); Assume that the voltage and SOC data points at the charging end are (V charge_cutoff , SOC 100 ); the slope between the two points is the slope M of the linear calibration; during the charging process, the displayed SOC cannot be reduced; if the calibration SOC-displayed SOC>=0.5%*displayed SOC, that is, SOC cali (t)-SOC dis (t)>=0.5%*SOC dis (t), the SOC is displayed according to the variable step size rule.

[0106] Finally, it is determined whether it is at the end of discharge; if so, display strategy 3 is used to display: at the end of discharge, a linear calibration method is used, and the voltage at the inflection point at the end of the discharge curve and the data point composed of SOC (V threshold2 , SOC threshold2 ); Let the data points of the voltage and SOC at the end of discharge be (V discharge_cutoff , SOC0); the slope between the two points is the slope M of the linear calibration; during the discharge process, the displayed SOC cannot increase; if the calibration SOC is equal to SOC threshold2 The difference between them is >=0.5%, that is, SOC cali (t)-SOC threshold2 >=0.5%*SOC threshold2 , it is displayed according to the variable step size rule.

[0107] The standard for judging the end of charge and discharge is that the open circuit voltage of the battery reaches the open circuit voltage corresponding to the SOC at the end inflection point; the method for obtaining the open circuit voltage at the end inflection point is: the value of the SOC at the end inflection point is known, and the voltage, current, and temperature of the battery can be sampled in real time; through these values, the internal resistance of the battery at this time can be obtained, and then the polarization voltage of the battery can be obtained, and the calculated open circuit voltage of the battery V OCV =V sample -V ploar , determine whether this open circuit voltage reaches the inflection point voltage, and then enter the terminal linear calibration stage.

[0108] The change rule of SOC step size is: due to the error of voltage sampling in the terminal linear calibration stage, SOC cali (t) When a large jump occurs, the current calibration SOC minus the calibration value at the previous moment is greater than a certain threshold, SOC dis (t) is equal to SOC cali (t) plus SOC step ;SOC step It is adjusted in real time according to the sampled voltage and battery current, but its maximum value is not greater than the threshold.

[0109] According to the characteristics of the charge and discharge curves of lithium batteries, the present invention proposes a SOC estimation method of variable speed corrected ampere-hour integration on the basis of the traditional ampere-hour integration estimation of SOC; during the estimation process, the maximum available capacity of the battery is regularly corrected according to the battery temperature and the total number of charge and discharge cycles of the battery; variable speed ampere-hour integration is adopted considering the charge and discharge efficiency and the current sampling accuracy; the initial SOC is estimated according to the open circuit voltage and the polarization voltage. The method of the present invention is simple, easy to implement, low in hardware cost, good in real time, strong in applicability, and effectively improves the accuracy and robustness of battery SOC estimation.

[0110] The SOC linear calibration method is used at the end of the battery charge and discharge, and the SOC estimation method of segmented estimation strategy + variable speed corrected ampere-hour integration solves the SOC jump problem of the traditional algorithm at the end. The present invention also proposes a variable step tracking and display method for the terminal SOC, which effectively avoids the problem of SOC jump and improves the user experience.

[0111] The entire method of the present invention operates automatically during the entire life cycle of the battery without manual intervention, and the working parameters of the battery are adaptively adjusted online without manual disassembly and setting. During the estimation process, the voltage, current and temperature are monitored in real time, and multiple protection measures are taken to ensure the safe operation of the battery.

[0112] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for estimating SOC of a solar power supply system of a monitoring device, characterized in that: The solar power supply system includes a battery and a solar panel. The battery is connected to a high-precision current sampling circuit, a high-precision voltage sampling circuit and a high-precision temperature sampling circuit. The SOC estimation method includes: S10: Obtain the number of charge and discharge cycles of the battery, and determine the influence coefficient K of the charge and discharge cycle number on the maximum available capacity of the battery according to the charge and discharge cycle number N ; S20: Obtain the current temperature of the battery through a high-precision temperature sampling circuit, and determine the influence coefficient K of the current temperature on the maximum available capacity of the battery based on the current temperature T ; S30: According to the influence coefficient K N and K T Calculate the maximum available capacity factor K at the current temperature and number of charge and discharge cycles C ; K C =(1-δ)K T +δK N Among them, δ is the set weight coefficient; S40: Determine the calibration coefficient K of the initial SOC of the battery K ; S50: Estimating the SOC of the battery outside the charging end and the discharging end by the following formula; Among them, SOC(t) is the estimated SOC at time t, SOC (t0) is the initial SOC, C max is the maximum available capacity of the battery, I bat (t) is the current sampling value at time t, K i The speed coefficient to be set.

2. The SOC estimation method of a solar power supply system of a monitoring device according to claim 1, characterized in that: The S10 includes: S11: Calculate the total number of charges N1 and the total number of discharges N2, and calculate the number of charge and discharge cycles N through N1 and N2; Wherein, N1 = total charge capacity / maximum available capacity, N2 = total discharge capacity / maximum available capacity, N = (N1+N2) / 2; S12: Determine the influence coefficient K through the following piecewise function N ; 。 3. The SOC estimation method of a solar power supply system of a monitoring device according to claim 2, characterized in that: The S20 includes: S21: Use a brand new battery to conduct charge and discharge capacity experiments in different temperature ranges, and measure the maximum available capacity at different temperatures; S22: using data fitting method to obtain the relationship between maximum available capacity and temperature; S23: Obtain the current temperature T of the battery through a high-precision temperature sampling circuit, and obtain the maximum available capacity C at the current temperature based on the fitted relationship between the maximum available capacity and temperature. max (T); S23: Calculate the influence coefficient K by the following formula T ; Among them, C max (Room temperature) is the maximum available capacity at the indicated temperature.

4. The SOC estimation method of a solar power supply system of a monitoring device according to claim 3, characterized in that: The S40 includes: S41: The internal resistance of the battery is measured by experiments at different charge and discharge states, different temperatures, different currents and different SOC values; S42: Measure the charge and discharge state, temperature and current of the battery in real time, obtain the SOC value stored when the battery was powered off last time, obtain the battery internal resistance of the current state by looking up the internal resistance table, and calculate the polarization voltage V of the battery according to the obtained battery internal resistance. polar ; S43: Calculate the calibration coefficient K by the following formula K ; V sample is the voltage sampling value.

5. The SOC estimation method of a solar power supply system of a monitoring device according to claim 4, characterized in that: The SOC is estimated in the battery charging terminal section using the following formula: SOC(t)=SOC threshold1 +K M ·(V charge_cutoff -V bat ) Among them, K M is the charging calibration coefficient for the battery charging end segment, V threshold1 is the charging end inflection point voltage, SOC threshhold1 is the charging end inflection point voltage V threshold1 The corresponding remaining power, V charge_cutoff is the charging cut-off voltage, V bat is the battery voltage at time t, SOC 100 Indicates full charge.

6. The SOC estimation method of a solar power supply system of a monitoring device according to claim 5, characterized in that: The SOC is estimated by the following formula in the interval at the end of battery discharge: SOC(t)=K' M ·(V bat -V discharge_cutoff ) Among them, K' M is the charge calibration coefficient for the battery discharge end segment, V threshold2 is the discharge end inflection point voltage, SOC threshold2 is the discharge end inflection point voltage V threshold2 The corresponding remaining power, V discharge_off is the discharge cut-off voltage, and SOC0 represents zero charge.

7. The SOC estimation method of a solar power supply system of a monitoring device according to claim 6, characterized in that: The method further comprises: S60: In the interval between the battery charging end and the battery discharging end, if the difference between the SOC estimated value at the current moment and the previous moment is greater than the set threshold, the SOC value is displayed in a variable step size to avoid a jump in the SOC value.

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