Energy storage system and calibration method and device for current-voltage detection function thereof

Abstract

The application discloses a kind of energy storage system and its current voltage detection function calibration method, device, wherein method includes: obtaining the current sampling value and voltage sampling value of energy storage system;Current sampling value and voltage sampling value are rectified and are calculated, and the BMS of energy storage system is calibrated offline, and BMS is regularly self-checked and self-calibration. Therefore, the voltage current detection accuracy in the whole life cycle of energy storage system can be realized, so as to improve the reliability and life of energy storage system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage, and in particular to an energy storage system and a method and device for calibrating current and voltage detection functions of the energy storage system. BACKGROUND

[0002] An energy storage system mainly comprises a battery cluster, a battery management system, a filter, an energy storage converter and electrical devices. The battery cluster, as a key component of the energy storage system, serves to store and release energy. The energy storage system has several important indicators, such as cycle efficiency, available capacity efficiency, charge and discharge rate, charge and discharge power, output DC voltage range, constant current and constant power mode, and DCDC converter power and energy storage converter power matched with battery power. The current and voltage detection functions of the battery management system are closely related to these indicators. Therefore, the current and voltage detection functions of the battery management system for energy storage have the following indicators:

[0003] (1) For total voltage: for lithium ion batteries and lead-acid batteries, the total voltage detection error of the battery cluster should be no more than ±1% FS (less than 1000V) and no more than ±0.5% FS (less than 1000V), and the maximum error should be no more than ±5V, and the sampling period should be no more than 100ms.

[0004] (2) For total current: for lithium ion batteries and lead-acid batteries, the total current detection error of the battery cluster should be no more than ±0.5% FS, and the maximum error should be no more than ±3A, and the sampling period should be no more than 50ms.

[0005] At present, the mainstream energy storage system is a 1500V DC high voltage, and the DC current is several tens of amperes to several hundred amperes. The voltage detection accuracy and current detection accuracy of ±0.5% FS put high requirements on the battery management system. In related technologies, the voltage detection and current detection are generally calibrated when the battery management system (i.e. BMS board) is offline. However, this method cannot be done once and for all. With the increase of the use time of the battery management system and the change of the environment, the physical changes of the voltage sampling circuit and the current sampling circuit will occur, which will affect the calibration effect set by the battery management system when it is shipped. SUMMARY

[0006] The present application aims to at least solve one of the technical problems in the related art. To this end, the first object of the present application is to propose a method for calibrating the current and voltage detection functions of an energy storage system. By performing deviation correction calculation on the current sampling value and the voltage sampling value, offline calibration on the battery management system, and regular self-checking and self-calibration on the battery management system, the voltage and current detection accuracy of the energy storage system throughout its life cycle can be realized, thereby improving the reliability and life of the energy storage system.

[0007] A second object of the present application is to provide a computer-readable storage medium.

[0008] A third object of the present application is to provide an energy storage system.

[0009] A fourth object of the present application is to provide a calibration device for current-voltage detection function of an energy storage system.

[0010] A fifth object of the present application is to provide a power station.

[0011] To achieve the above objects, the first aspect of the present application provides a calibration method for current-voltage detection function of an energy storage system, comprising: obtaining current sampling values and voltage sampling values of the energy storage system; performing offset correction calculation on the current sampling values and the voltage sampling values, and performing offline calibration on a BMS of the energy storage system, and performing regular self-checking and self-calibration on the BMS.

[0012] According to the calibration method for current-voltage detection function of the energy storage system of the present application, by performing offset correction calculation on the current sampling values and the voltage sampling values of the energy storage system, and performing offline calibration on the BMS of the energy storage system, and performing regular self-checking and self-calibration on the BMS, the voltage and current detection accuracy of the energy storage system throughout its life cycle can be realized, thereby improving the reliability and life of the energy storage system.

[0013] According to an embodiment of the present application, the offset correction calculation on the current sampling values and the voltage sampling values comprises: determining at least one larger current value and at least one smaller current value in M continuous current sampling values, and determining at least one larger voltage value and at least one smaller voltage value in N continuous voltage sampling values, wherein M and N are integers greater than 2; removing the at least one larger current value and the at least one smaller current value from the M current sampling values and performing filtering processing to obtain a current offset value, and removing the at least one larger voltage value and the at least one smaller voltage value from the N voltage sampling values and performing filtering processing to obtain a voltage offset value.

[0014] According to an embodiment of the present application, the offline calibration on the BMS of the energy storage system comprises: determining an analog voltage value corresponding to the current offset value and an analog voltage value corresponding to the voltage offset value, respectively; determining a first analog quantity range in which the analog voltage value corresponding to the current offset value is located, and determining a second analog quantity range in which the analog voltage value corresponding to the voltage offset value is located; determining a first proportional coefficient according to the first analog quantity range, and determining a second proportional coefficient according to the second analog quantity range; calibrating the current offset value according to the first proportional coefficient, and calibrating the voltage offset value according to the second proportional coefficient.

[0015] According to one embodiment of the present application, the first and second proportional coefficients are determined according to the following steps: dividing the analog quantity range of the current sample of the energy storage system into A segments and dividing the analog quantity range of the voltage sample of the energy storage system into B segments; calibrating the upper limit analog quantity of the A segments to obtain A calibration current digital quantities and calibrating the upper limit analog quantity of the B segments to obtain B calibration voltage digital quantities; determining the corresponding first proportional coefficient of each segment in the A segments according to the A calibration current digital quantities, the corresponding original current digital quantities and the upper limit analog quantity of the A segments, and determining the corresponding second proportional coefficient of each segment in the B segments according to the B calibration voltage digital quantities, the corresponding original voltage digital quantities and the upper limit analog quantity of the B segments.

[0016] According to one embodiment of the present application, the BMS is periodically self-checked, including: obtaining the voltage value of each cell in the battery cluster of the energy storage system when the energy storage system is powered on, and determining the first total voltage of the battery cluster according to the voltage value of each cell; when the voltage error between the first total voltage and the second total voltage corresponding to the voltage sample value is greater than or equal to the first preset voltage threshold, it is determined that the voltage detection function of the energy storage system fails, and when the total current corresponding to the current sample value is not zero, it is determined that the current detection function of the energy storage system fails.

[0017] According to one embodiment of the present application, the BMS is self-calibrated, including: calibrating the voltage detection function of the BMS according to the first total voltage when the energy storage system starts charging and / or discharging ends; determining the operating power of the energy storage system when the energy storage system operates in a constant power mode, and determining the first current according to the operating power and the second total voltage, and obtaining the output current of the energy storage system, and when the total current corresponding to the current sample value is not between the first current and the output current, the current detection function of the BMS is self-calibrated according to the first current and the output current.

[0018] According to one embodiment of the present application, the method further comprises: performing hardware error analysis on the current sampling circuit and the voltage sampling circuit of the BMS.

[0019] To achieve the above-mentioned purpose, the second aspect of the embodiment of the present application provides a computer readable storage medium, which stores the calibration program of the current and voltage detection function of the energy storage system, and the calibration program of the current and voltage detection function of the energy storage system is executed by the processor to realize the calibration method of the current and voltage detection function of the energy storage system.

[0020] The computer readable storage medium according to the embodiment of the present application can realize the voltage and current detection accuracy of the energy storage system in the whole life cycle of the energy storage system through the calibration method of the current and voltage detection function of the energy storage system, thereby improving the reliability and service life of the energy storage system.

[0021] To achieve the above objectives, a third aspect of the present invention provides an energy storage system, including a memory, a processor, and a calibration program for the current and voltage detection function of the energy storage system stored in the memory and executable on the processor. When the processor executes the calibration program for the current and voltage detection function of the energy storage system, the aforementioned calibration method for the current and voltage detection function of the energy storage system is implemented.

[0022] According to the energy storage system of the present invention, by means of the aforementioned calibration method for the current and voltage detection function of the energy storage system, the voltage and current detection accuracy throughout the entire life cycle of the energy storage system can be achieved, thereby improving the reliability and lifespan of the energy storage system.

[0023] To achieve the above objectives, a fourth aspect of the present invention provides a calibration device for the current and voltage detection function of an energy storage system, comprising: an acquisition module for acquiring current and voltage sample values ​​of the energy storage system; and a calibration module for performing correction calculations on the current and voltage sample values, performing offline calibration on the BMS of the energy storage system, and performing periodic self-testing and self-calibration on the BMS.

[0024] The calibration device for the current and voltage detection function of the energy storage system according to an embodiment of the present invention can improve the reliability and lifespan of the energy storage system by performing correction calculations on the current and voltage sampling values ​​of the energy storage system, performing offline calibration of the BMS of the energy storage system, and performing periodic self-testing and self-calibration of the BMS.

[0025] To achieve the above objectives, a fifth aspect of the present invention provides a power plant including the aforementioned energy storage system.

[0026] According to the power plant of the present invention, the aforementioned energy storage system enables the voltage and current detection accuracy throughout the entire life cycle of the energy storage system, thereby improving the reliability and lifespan of the energy storage system.

[0027] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating a calibration method for the current and voltage detection function of an energy storage system according to an embodiment of the present invention.

[0029] Figure 2 A circuit diagram of a current detection circuit and a voltage detection circuit according to an embodiment of the present invention;

[0030] Figure 3This is a flowchart of a process for calculating the correction of current and voltage sample values ​​according to an embodiment of the present invention;

[0031] Figure 4 This is a flowchart illustrating the offline calibration of a BMS according to an embodiment of the present invention;

[0032] Figure 5 A flowchart illustrating the acquisition of a first scaling factor and a second scaling factor according to an embodiment of the present invention;

[0033] Figure 6 This is a flowchart of a self-test for a BMS according to an embodiment of the present invention;

[0034] Figure 7 This is a flowchart illustrating the self-calibration of a BMS according to an embodiment of the present invention;

[0035] Figure 8 This is a schematic diagram illustrating the design and calibration process of the current and voltage detection function of an energy storage system according to an embodiment of the present invention.

[0036] Figure 9 This is a schematic diagram of a computer-readable storage medium according to an embodiment of the present invention;

[0037] Figure 10 This is a schematic diagram of an energy storage system according to an embodiment of the present invention;

[0038] Figure 11 This is a schematic diagram of the structure of a calibration device for the current and voltage detection function of an energy storage system according to an embodiment of the present invention;

[0039] Figure 12 This is a schematic diagram of a power plant according to an embodiment of the present invention. Detailed Implementation

[0040] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0041] The following description, with reference to the accompanying drawings, outlines an energy storage system and its calibration method, apparatus, storage medium, and power station according to embodiments of the present invention, including current and voltage detection functions.

[0042] Figure 1 This is a flowchart illustrating a calibration method for the current and voltage detection function of an energy storage system according to an embodiment of the present invention. Figure 1 As shown, the calibration method for the current and voltage detection function includes:

[0043] S101, acquire the current and voltage sampling values ​​of the energy storage system.

[0044] Specifically, an energy storage system may include components such as battery clusters, a BMS (Battery Management System), filters, DC-DC converters, and energy storage inverters. A battery cluster can be composed of multiple cells connected in series, parallel, or series-parallel. The current sampling value of the energy storage system refers to the total current of the battery cluster, which can be obtained by the BMS through a current sampling circuit. The voltage sampling value of the energy storage system refers to the total voltage of the battery cluster, which can be obtained by the BMS through a voltage sampling circuit.

[0045] It should be noted that when designing the hardware for the current and voltage sampling circuits, hardware error analysis can be performed to ensure that the current and voltage detection errors meet the standard and usage requirements as much as possible. For example, the hardware design goal is that the total voltage detection error of the battery cluster is no greater than ±1%FS and no greater than ±0.5%FS, with a maximum error of no greater than ±5V, and the total current detection error of the battery cluster is no greater than ±0.5%FS, with a maximum error of no greater than ±3A.

[0046] For example, the hardware design of the current sampling circuit and the voltage sampling circuit is as follows: Figure 2 As shown.

[0047] For current sampling circuits, shunts are well-suited for high-current detection due to their small resistance (Rs), low temperature drift, high accuracy, and low cost. Therefore, the shunt can be placed on either the main positive or negative line of the battery cluster, converting the large current into a small voltage to achieve current sampling of the battery cluster. Simultaneously, because the shunt's resistance (Rs) is very small, the voltage (Vs) across the shunt is very small (typically in the mV range) when the current (Is) passes through it. Therefore, operational amplification of the voltage (Vs) across the shunt is necessary. Furthermore, since the battery cluster side is high-voltage while the BMS side is low-voltage, an operational amplifier with isolation function, i.e., a first isolation operational amplifier, is used to perform isolated operational amplification of the voltage (Vs) across the shunt. Since the A / D (analog-to-digital conversion) reference voltage of the BMS is Vf, and the amplification factor of the first isolation operational amplifier is limited, in order to improve the sampling accuracy, an operational amplifier, namely the first operational amplifier, can be added after the first isolation operational amplifier to make the total operational amplification factor N, and then the signal enters the A / D port of the BMS. The BMS obtains the digital current sampling value AI by sampling through the A / D port.

[0048] For the voltage sampling circuit, since the total voltage U of the battery cluster is thousands of volts, it is not possible to directly sample the high voltage in the hardware. Therefore, the voltage of the battery cluster needs to be divided by a voltage divider circuit. For example, the voltage is divided by a voltage divider circuit composed of voltage divider resistors R1, R2 and R3. Then, the voltage VR across the voltage divider resistor R3 is acquired by the second isolation operational amplifier and amplified by the second operational amplifier. The total operational amplification factor is N, and then it enters the A / D port of the BMS. The BMS obtains the digital voltage sampling value AU by sampling through the A / D port.

[0049] Assuming the BMS's A / D converter is n bits, then the A / D resolution is Vf ÷ 2. n ,based on Figure 2 The hardware design shown can obtain the current sampling value AI and the voltage sampling value AU as shown in formulas (1)-(2):

[0050] AI = Is × Rs × N ÷ Vf × 2 n (1)

[0051] AU = VR × N ÷ Vf × 2 n (2)

[0052] Therefore, by rationally designing the current sampling circuit and the voltage sampling circuit, the current and voltage detection errors can be made to meet the standard requirements and usage requirements in the hardware design as soon as possible.

[0053] S102 performs error correction calculations on current and voltage sample values, performs offline calibration of the BMS of the energy storage system, and performs periodic self-testing and self-calibration of the BMS.

[0054] It should be noted that the current and voltage sample values ​​obtained based on the above formulas are ideal sampling values. In reality, the sampling accuracy of current and voltage is affected by a variety of factors, such as:

[0055] 1) The accuracy error of the resistors involved in the calculation;

[0056] 2) Errors caused by current and voltage sampling lines;

[0057] 3) Errors caused by the circuit board layout and routing of the current sampling circuit and voltage sampling circuit;

[0058] 4) The operational amplifier itself has quantization error, integral nonlinearity error, differential nonlinearity error, offset error, and gain error;

[0059] 5) Errors caused by changes in temperature and humidity, and physical and chemical changes in the device.

[0060] If the software only uses the current and voltage sampling values ​​obtained from the above formulas to calculate the analog current and voltage values, it will be very difficult to ensure that the current sampling circuit and voltage sampling circuit maintain the total voltage detection error of the battery cluster at no more than ±1%FS and no more than ±0.5%FS, with a maximum error of no more than ±5V, and the total current detection error of the battery cluster at no more than ±0.5%FS, with a maximum error of no more than ±3A, throughout the entire life cycle of the energy storage system. Therefore, certain measures need to be taken.

[0061] For example, current and voltage detection errors can be reduced through software. Specifically, this can be achieved through two levels: a first level that performs correction calculations on the current and voltage sample values, and a second level that performs offline calibration of the BMS (Battery Management System) of the energy storage system. These two levels of software processing address the current and voltage detection errors caused by factors 1)-4) mentioned above. Furthermore, periodic self-testing and self-calibration of the BMS can address the current and voltage detection errors caused by factor 5) mentioned above. This ensures that the current and voltage detection errors meet standard and usage requirements. For instance, throughout the entire lifespan of the energy storage system, the total voltage detection error of the battery cluster should not exceed ±1%FS and ±0.5%FS, with a maximum error not exceeding ±5V; the total current detection error of the battery cluster should not exceed ±0.5%FS, with a maximum error not exceeding ±3A.

[0062] Therefore, by performing correction calculations on current and voltage sampling values, calibrating the BMS offline, and conducting regular self-tests and self-calibrations of the BMS, the voltage and current detection accuracy throughout the entire lifecycle of the energy storage system can be achieved, thereby improving the reliability and lifespan of the energy storage system.

[0063] The following examples illustrate how to perform error correction calculations on current and voltage sample values, perform offline calibration of the BMS, and perform periodic self-tests and self-calibrations of the BMS.

[0064] In some embodiments, such as Figure 3 As shown, the error correction calculation for the current and voltage sample values ​​includes:

[0065] S201, determine at least one larger current value and at least one smaller current value among the M consecutively acquired current sample values, and determine at least one larger voltage value and at least one smaller voltage value among the N consecutively acquired voltage sample values, where M and N are integers greater than 2.

[0066] S202, remove at least one larger current value and at least one smaller current value from M current sample values ​​and perform filtering to obtain current correction value; and remove at least one larger voltage value and at least one smaller voltage value from N voltage sample values ​​and perform filtering to obtain voltage correction value.

[0067] For example, during the operation of the energy storage system, the BMS samples the current and voltage of the battery cluster in real time through current sampling circuits and voltage sampling circuits to obtain current sampling values ​​and voltage sampling values. The M consecutively sampled current sampling values ​​are grouped together, and then the a largest current values ​​Dimax and b smallest current values ​​Dimin are found from the M current sampling values, where a and b are integers greater than or equal to 1, but less than M, and generally take values ​​of 1 to 3. Then, the a largest current values ​​Dimax and b smallest current values ​​Dimin are removed from the M current sampling values, and the average value of the remaining current sampling values ​​is calculated to correct the current sampling values, and the current correction value is obtained as shown in the following formula (3):

[0068] Diavg=[(Di1+Di2+…+DiM)-(Dimax1+Dimax2+…+Dimaxa)-(Dimin1+Dimin2+…+Diminb)] / (Mab)(3)

[0069] Similarly, N consecutively sampled voltage values ​​can be grouped together, and then the c largest voltage values ​​Dvmax and d smallest voltage values ​​Dvmin can be found from the N voltage samples, where c and d are integers greater than or equal to 1, but less than N, and are generally taken as 1 to 3. Then, the c largest voltage values ​​Dvmax and d smallest voltage values ​​Dvmin are removed from the N voltage samples, and the average value of the remaining voltage samples is calculated to correct the voltage sample values, and the voltage correction value is obtained as shown in the following formula (4):

[0070] Dvavg=[(Dv1+Dv2+…+DvN)-(Dvmax1+Dvmax2+…+Dvmaxc)-(Dvmin1+Dvmin2+…+Dvmind)] / (Ncd)(4)

[0071] It should be noted that the mean value is used here as the filtering method to correct the current and voltage sample values. In practical applications, other filtering methods, such as median filtering, can also be used. Specific examples will not be given here.

[0072] Therefore, by performing correction calculations on the current and voltage sample values ​​through filtering, the sampling accuracy of current and voltage can be improved to a certain extent, ensuring that the current and voltage detection errors meet standard and usage requirements. However, correction calculations on the current and voltage sample values ​​do not necessarily guarantee that the current and voltage detection errors will completely meet standard and usage requirements. Therefore, after performing correction calculations on the current and voltage sample values, the BMS can be calibrated when it is taken offline. This two-stage software processing—correction calculation and BMS offline calibration—can improve the sampling accuracy of current and voltage.

[0073] In some embodiments, such as Figure 4 As shown, the offline calibration of the BMS of the energy storage system includes:

[0074] S301, determine the analog voltage values ​​corresponding to the current correction value and the voltage correction value respectively.

[0075] It should be noted that since both the current correction value and the voltage correction value are digital voltage values, they can be converted from digital to analog to obtain the corresponding analog voltage values.

[0076] S302, determine the first analog quantity range in which the analog voltage value corresponding to the current correction value is located, and determine the second analog quantity range in which the analog voltage value corresponding to the voltage correction value is located.

[0077] Specifically, the analog quantity range for current sampling of the BMS can be determined first, and then segmented to obtain multiple first analog quantity ranges. Simultaneously, the analog quantity range for voltage sampling of the BMS can be determined, and then segmented to obtain multiple second analog quantity ranges. When obtaining the analog voltage value corresponding to the current correction value, the corresponding first analog quantity range is determined based on the analog voltage value corresponding to the current correction value; when obtaining the analog voltage value corresponding to the voltage correction value, the corresponding second analog quantity range is determined based on the analog voltage value corresponding to the voltage correction value.

[0078] S303, determine the first proportional coefficient based on the first analog quantity range, and determine the second proportional coefficient based on the second analog quantity range.

[0079] Specifically, different first analog quantity ranges correspond to different first proportional coefficients, and different second analog quantity ranges correspond to different second proportional coefficients. After determining the first analog quantity range, the corresponding first proportional coefficient can be obtained, and after determining the second analog quantity range, the corresponding second proportional coefficient can be obtained.

[0080] In some embodiments, such as Figure 5 As shown, the first and second scaling factors are determined according to the following steps:

[0081] S401 divides the analog range of the current sampling of the energy storage system into segment A and the analog range of the voltage sampling of the energy storage system into segment B.

[0082] S402 calibrates the upper limit analog quantity of segment A to obtain A calibration current digital quantities, and calibrates the upper limit analog quantity of segment B to obtain B calibration voltage digital quantities.

[0083] S403, determine the first proportional coefficient corresponding to each segment in segment A based on A calibration current digital quantities and the corresponding original current digital quantities, as well as the upper limit analog quantity of segment A, and determine the second proportional coefficient corresponding to each segment in segment B based on B calibration voltage digital quantities and the corresponding original voltage digital quantities, as well as the upper limit analog quantity of segment B.

[0084] Specifically, taking current sampling as an example, first determine the analog range of the BMS current sampling [0, C]. A Then, the analog range of the current sampled is [0, C]. A The array is divided into A segments, resulting in A first analog quantity ranges, namely [0, C1], (C1, C2], ... ... A-1 C A ].

[0085] Then, the upper limit analog quantity of segment A is calibrated, that is, the upper limit analog quantities C1, C2, ..., C of each of the A first analog quantity ranges are calibrated. A After calibration, A digital calibration current values ​​are obtained, denoted as d. 11 d 12 ... d 1A Optionally, a higher-precision current source can be used to control the upper limit analog quantities C1, C2, ..., C. A Calibration is then performed. Specifically, a more precise adjustable current source is connected to the current sampling circuit. The adjustable current source is then set so that its output current is C1, and the BMS samples the current through the current sampling circuit to obtain the corresponding current correction value, which is denoted as the calibration current digital quantity d. 11 Next, the adjustable current source is configured so that its output current is C2, and the BMS samples the current through the current sampling circuit to obtain the corresponding current correction value, which is denoted as the calibration current digital quantity d. 12 ; and so on, until the upper limit analog quantity C is completed. A The calibration yields the digital value d of the calibration current. 1A .

[0086] Then, the BMS obtains the upper limit analog quantities C1, C2, ..., C. AThe corresponding raw digital current, i.e., the analog values ​​C1, C2, ..., C obtained by the BMS through the current sampling circuit of the battery cluster, are the upper limit analog values ​​C1, C2, ..., C. A The corresponding current correction value is denoted as d. 21 d 22 ... d 2A Finally, the BMS calculates the calibration current based on A digital values ​​d. 11 d 12 ... d 1A A raw current digital quantity d 21 d 22 ... d 2A And the upper limit analog quantities C1, C2, ..., C A Calculate the first proportional coefficient corresponding to each segment in segment A, that is, the first proportional coefficient corresponding to each first analog quantity range. For example, it can be calculated using formula (5):

[0087] K 1i =(d 1i -d 2i ) / C i (5)

[0088] Among them, K 1i d is the first proportionality coefficient. 1i For the i-th calibration current digital quantity, d 2i For the i-th original digital current quantity, C i Let A be the i-th upper limit analog quantity, 1≤i≤A.

[0089] It should be noted that the process of determining the second proportional coefficient is the same as that of determining the first proportional coefficient, except that the current source is replaced by a voltage source, and the voltage sampling circuit is calibrated by the voltage source.

[0090] S304 calibrates the current correction value according to the first proportional coefficient and calibrates the voltage correction value according to the second proportional coefficient.

[0091] Specifically, when calibrating the current correction value according to the first proportional coefficient, the calibration current digital value corresponding to the upper limit analog value of segment A (i.e., the original current digital value) can be replaced by the calibration current digital value corresponding to the upper limit analog value of segment A. Simultaneously, the current correction value in each segment is adjusted according to the corresponding first proportional coefficient; that is, for each range of first analog values, the current correction value within that range is adjusted using the corresponding first proportional coefficient. For example, using upper limit analog values ​​C1, C2, ..., C... A The corresponding calibration current digital quantity d 11 d 12 ... d 1A Replace the original digital current quantity d respectively21 d 22 ... d 2A Meanwhile, the current correction value within each first analog quantity range can be adjusted according to the first proportional coefficient using the following formula:

[0092] Diavg'=K 1i *C i +Diavg (6)

[0093] Where Diavg' is the calibrated current correction value.

[0094] It should be noted that the process of calibrating the voltage correction value according to the second proportional coefficient is the same as the process of calibrating the current correction value according to the first proportional coefficient, and will not be elaborated here.

[0095] Therefore, offline calibration of the BMS can improve the sampling accuracy of current and voltage. By correcting the current and voltage sampling values ​​and performing offline calibration of the BMS, the current and voltage detection errors can be effectively made to meet the standard requirements and usage requirements.

[0096] In some embodiments, such as Figure 6 As shown, regular self-checks of the BMS include:

[0097] S501: When the energy storage system is powered on, the voltage value of each cell in the battery cluster of the energy storage system is obtained, and the first total voltage of the battery cluster is determined based on the voltage value of each cell.

[0098] S502, when the voltage error between the first total voltage and the second total voltage corresponding to the voltage sampling value is greater than or equal to the first preset voltage threshold, the voltage detection function of the energy storage system is determined to be faulty, and when the total current corresponding to the current sampling value is not zero, the current detection function of the energy storage system is determined to be faulty.

[0099] Specifically, the BMS can perform self-tests on voltage and current detection functions each time the energy storage system is powered on. Assuming no other system faults, and that the battery cluster consists of J cells, the BMS can obtain the voltage of each cell based on its corresponding voltage detection circuit. The total voltage of the battery cluster is then summed, denoted as the first total voltage V1. It should be noted that since the voltage detection error of a single cell is relatively small, typically 5mV, the error of the first total voltage V1 is 5*JmV. Then, the BMS compares the first total voltage V1 with the second total voltage V2, which is the total voltage of the battery cluster sampled by the voltage sampling circuit corresponding to the battery cluster. If the voltage error between the two is greater than or equal to a first preset voltage threshold, such as ±(5*Jm+5)V, the BMS's voltage detection function is considered to have failed.

[0100] When the energy storage system is powered on, the battery clusters have no current. The total current of the battery clusters sampled by the BMS through the current sampling circuit should be zero. Therefore, when the sampled current value of the battery clusters is not zero, the current detection function of the BMS is considered to be faulty.

[0101] Therefore, by performing a self-test on the BMS every time the energy storage system is powered on, it is possible to promptly detect whether the voltage detection function and current detection function are malfunctioning, thus avoiding the large current and voltage sampling errors caused by continuing to sample current and voltage in a malfunctioning state, thereby ensuring the sampling accuracy of current and voltage.

[0102] In some embodiments, such as Figure 7 As shown, the BMS self-calibration includes:

[0103] S601 calibrates the voltage detection function of the BMS based on the first total voltage at the start of charging and / or the end of discharging of the energy storage system.

[0104] It should be noted that the voltage detection function of the BMS can be calibrated based on the first total voltage at the beginning or end of each charge of the energy storage system, or at both the beginning and end of each charge. The principle is the same as that of offline calibration of the BMS.

[0105] Specifically, let's take the start of charging an energy storage system as an example. Normally, when the BMS detects that the voltage of the battery cluster is less than or equal to a preset low-voltage threshold, it starts charging the battery cluster. At this time, the total voltage of the battery cluster is relatively low, so the voltage detection function of the BMS can be calibrated at this time to improve the accuracy of the calibration.

[0106] During calibration, the BMS samples the voltage correction value (i.e., the original voltage digital value) corresponding to the preset low voltage threshold through the voltage sampling circuit corresponding to the battery cluster, and simultaneously samples the voltage of the battery cell through the voltage sampling circuit corresponding to the cell. These samples are then summed to obtain the total voltage of the battery cluster, i.e., the first total voltage V1. Then, the BMS internally obtains the voltage correction value (i.e., the calibration voltage digital value) corresponding to the first total voltage V1 obtained through the voltage sampling circuit corresponding to the battery cluster. Finally, a third proportional coefficient is calculated based on the preset low voltage threshold, the voltage correction value corresponding to the preset low voltage threshold, and the voltage correction value corresponding to the first total voltage V1. The voltage detection function of the BMS is calibrated based on this third proportional coefficient. The third proportional coefficient is determined by the following formula (7):

[0107] K3=(d4-d3) / C L (7)

[0108] Where K3 is the third proportional coefficient, d4 is the voltage correction value corresponding to the first total voltage V1 (i.e., the digital value of the calibration voltage), d3 is the voltage correction value corresponding to the preset low voltage threshold (i.e., the digital value of the original voltage), and C L This is the preset low-voltage threshold.

[0109] When calibrating the voltage detection function of the BMS based on the third proportional coefficient, d4 can be used instead of d3, and the remaining voltage correction value can be adjusted according to the third proportional coefficient using the following formula:

[0110] Dvavg'=K3*C L +Dvavg (8)

[0111] Where Dvavg' is the calibrated voltage correction value.

[0112] Therefore, by calibrating the voltage detection function of the BMS based on the first total voltage at the start of charging and / or the end of discharging of the energy storage system, the voltage sampling accuracy can be effectively improved.

[0113] S602, when the energy storage system is running in constant power mode, determines the operating power of the energy storage system, determines the first current based on the operating power and the second total voltage, and obtains the output current of the energy storage system. When the total current corresponding to the current sampling value is not between the first current and the output current, the current detection function of the BMS is self-calibrated based on the first current and the output current.

[0114] Specifically, when the energy storage system operates in constant power mode, several time points can be set. At each time point, the BMS calculates the first current I1 based on the operating power of the energy storage system and the second total voltage V2 of the battery cluster obtained by the voltage sampling circuit corresponding to the battery cluster. Simultaneously, the energy storage inverter or DC-DC converter in the energy storage system detects the output current I2 of the energy storage system, and the total current I3 of the battery cluster is sampled by the current sampling circuit corresponding to the battery cluster. Then, the current detection function of the BMS is calibrated based on the first current I1, the output current I2, and the total current I3 of the battery cluster. If I3 is between I1 and I2, no calibration is performed; if I3 is not between I1 and I2, I3 is calibrated based on I1 and I2, such as I3 = (I1 + I2) / 2.

[0115] Therefore, when the energy storage system operates in constant power mode, self-calibrating the current detection function of the BMS can effectively improve the current sampling accuracy. Thus, self-testing and self-calibrating the BMS can effectively eliminate random and unavoidable errors that may be caused by changes in temperature and humidity, or physical and chemical changes in components, ensuring that current and voltage detection errors meet compliance and usage requirements.

[0116] It should be noted that if the current and voltage detection errors after self-calibrating the BMS do not meet the standards and usage requirements, the shunt and battery management system should be replaced, and self-calibration should be performed again.

[0117] The following is combined with Figure 8 To illustrate the design and calibration process of the current and voltage detection function of the energy storage system, such as... Figure 8 As shown, the process may include the following:

[0118] S701, design the current sampling circuit and voltage sampling circuit corresponding to the battery cluster.

[0119] S702 performs hardware error calculations on the current and voltage sampling circuits to determine whether the current and voltage detection errors meet the requirements, such as a current and voltage detection error of no more than ±0.5%FS, a maximum voltage detection error of no more than ±5V, and a maximum current detection error of no more than ±3A. If the requirements are met, proceed to S704; otherwise, proceed to S703.

[0120] The S703 performs hardware error analysis and adjustment on the current sampling circuit and voltage sampling circuit until the hardware cannot be adjusted or the requirements are met.

[0121] S704 uses software sampling to obtain current and voltage sample values.

[0122] S705 performs software error calculation on the current and voltage sample values ​​to determine whether the current and voltage detection errors meet the requirements. If the requirements are met, the process ends; otherwise, proceed to S706.

[0123] S706, design a corresponding correction algorithm to correct the current sampling value and voltage sampling value.

[0124] S707 performs offline calibration of the BMS.

[0125] S708 performs regular self-tests and self-calibrations of the BMS during the use of the energy storage system.

[0126] If self-calibration fails for S709, replace the shunt or BMS board.

[0127] S710 performs self-calibration of the BMS.

[0128] As can be seen from the above process, the current and voltage detection errors are first addressed through hardware and software processing to ensure they meet the requirements. However, if these methods fail to guarantee the accuracy of the current and voltage detection errors, the BMS is taken offline for calibration. Since the offline calibration is based on the environmental conditions at that time, and the actual operating environment of the BMS is subject to various possibilities, as well as long-term hardware physicochemical changes, the sampling accuracy of voltage and current may be affected. Therefore, these two functions can be periodically self-tested and self-calibrated. If the calibration fails, the shunt or BMS board can be replaced, and a secondary calibration of the current and voltage detection functions can be performed after replacement to achieve accurate voltage and current detection throughout the entire lifecycle of the energy storage system.

[0129] In summary, the calibration method for the current and voltage detection function of the energy storage system according to the embodiments of the present invention, by performing correction calculations on the current and voltage sampling values ​​of the energy storage system, performing offline calibration of the BMS of the energy storage system, and performing periodic self-testing and self-calibration of the BMS, can achieve the voltage and current detection accuracy throughout the entire life cycle of the energy storage system. This provides more accurate data statistics for the state of charge, cycle efficiency, available energy efficiency, charge / discharge rate, charge / discharge power, output DC voltage range, constant current and constant power mode of the battery cluster, thereby improving the reliability and lifespan of the energy storage system.

[0130] like Figure 9 As shown, embodiments of the present invention also provide a computer-readable storage medium 800, on which a calibration program for the current and voltage detection function of an energy storage system is stored. When the calibration program for the current and voltage detection function of the energy storage system is executed by a processor, the aforementioned calibration method for the current and voltage detection function of the energy storage system is implemented.

[0131] According to the computer-readable storage medium of the present invention, the voltage and current detection accuracy of the energy storage system can be achieved throughout its entire life cycle by means of the aforementioned calibration method for the current and voltage detection function of the energy storage system, thereby improving the reliability and lifespan of the energy storage system.

[0132] like Figure 10 As shown, an embodiment of the present invention proposes an energy storage system 900, including a memory 910, a processor 920, and a calibration program for the current and voltage detection function of the energy storage system stored in the memory 910 and executable on the processor 920. When the processor 920 executes the calibration program for the current and voltage detection function of the energy storage system, the aforementioned calibration method for the current and voltage detection function of the energy storage system is implemented.

[0133] According to the energy storage system of the present invention, by means of the aforementioned calibration method for the current and voltage detection function of the energy storage system, the voltage and current detection accuracy throughout the entire life cycle of the energy storage system can be achieved, thereby improving the reliability and lifespan of the energy storage system.

[0134] like Figure 11 As shown, an embodiment of the present invention proposes a calibration device 1000 for the current and voltage detection function of an energy storage system, comprising: an acquisition module 1100 and a calibration module 1200.

[0135] The acquisition module 1100 is used to acquire the current sampling value and voltage sampling value during the operation of the energy storage system; the calibration module 1200 is used to perform correction calculations on the current sampling value and voltage sampling value when it is determined that there is a current and voltage detection error in the energy storage system based on the current sampling value and voltage sampling value, and to perform offline calibration of the BMS of the energy storage system, as well as to perform periodic self-testing and self-calibration of the BMS.

[0136] According to one embodiment of the present invention, the calibration module 1200 is configured to: determine at least one larger current value and at least one smaller current value among M consecutively acquired current sample values, and determine at least one larger voltage value and at least one smaller voltage value among N consecutively acquired voltage sample values, wherein M and N are integers greater than 2; remove at least one larger current value and at least one smaller current value from the M current sample values ​​and perform filtering processing to obtain a current correction value; and remove at least one larger voltage value and at least one smaller voltage value from the N voltage sample values ​​and perform filtering processing to obtain a voltage correction value.

[0137] According to one embodiment of the present invention, the calibration module 1200 is configured to: determine the analog voltage values ​​corresponding to the current correction value and the voltage correction value respectively; determine a first analog quantity range in which the analog voltage value corresponding to the current correction value is located, and determine a second analog quantity range in which the analog voltage value corresponding to the voltage correction value is located; determine a first proportional coefficient according to the first analog quantity range, and determine a second proportional coefficient according to the second analog quantity range; calibrate the current correction value according to the first proportional coefficient, and calibrate the voltage correction value according to the second proportional coefficient.

[0138] According to one embodiment of the present invention, the calibration module 1200 is configured to: divide the analog quantity range of the current sampling of the energy storage system into segment A, and divide the analog quantity range of the voltage sampling of the energy storage system into segment B; calibrate the upper limit analog quantity of segment A to obtain A calibration current digital quantities, and calibrate the upper limit analog quantity of segment B to obtain B calibration voltage digital quantities; determine a first proportional coefficient corresponding to each segment in segment A based on the A calibration current digital quantities, the corresponding original current digital quantities, and the upper limit analog quantity of segment A, and determine a second proportional coefficient corresponding to each segment in segment B based on the B calibration voltage digital quantities, the corresponding original voltage digital quantities, and the upper limit analog quantity of segment B.

[0139] According to one embodiment of the present invention, the calibration module 1200 is configured to: acquire the voltage value of each cell in the battery cluster of the energy storage system when the energy storage system is powered on, and determine the first total voltage of the battery cluster based on the voltage value of each cell; determine that the voltage detection function of the energy storage system is faulty when the voltage error between the first total voltage and the second total voltage corresponding to the voltage sampling value is greater than or equal to a first preset voltage threshold, and determine that the current detection function of the energy storage system is faulty when the total current corresponding to the current sampling value is not zero.

[0140] According to one embodiment of the present invention, the calibration module 1200 is configured to: calibrate the voltage detection function of the BMS based on a first total voltage at the start of charging and / or the end of discharging of the energy storage system; determine the operating power of the energy storage system when the energy storage system is running in constant power mode, determine a first current based on the operating power and a second total voltage, acquire the output current of the energy storage system, and perform self-calibration of the current detection function of the BMS based on the first current and the output current when the total current corresponding to the current sampling value is not between the first current and the output current.

[0141] According to one embodiment of the present invention, the calibration module 1200 is further configured to perform hardware error analysis on the current sampling circuit and voltage sampling circuit of the BMS.

[0142] It should be noted that for details regarding the calibration device for the current and voltage detection function that are not disclosed, please refer to the details disclosed in the calibration method for the current and voltage detection function.

[0143] The calibration device for the current and voltage detection function of the energy storage system according to an embodiment of the present invention can improve the reliability and lifespan of the energy storage system by performing correction calculations on the current and voltage sampling values ​​of the energy storage system, performing offline calibration of the BMS of the energy storage system, and performing periodic self-testing and self-calibration of the BMS.

[0144] like Figure 12As shown, an embodiment of the present invention proposes a power plant 2000, including the aforementioned energy storage system 900. The power plant 2000 can be a photovoltaic power plant or a wind power plant, and there is no limitation here.

[0145] According to the power plant of the present invention, the aforementioned energy storage system enables the voltage and current detection accuracy throughout the entire life cycle of the energy storage system, thereby improving the reliability and lifespan of the energy storage system.

[0146] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0147] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0148] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0149] Furthermore, the terms "first," "second," etc., used in the embodiments of this invention are for descriptive purposes only and should not be construed as indicating or implying relative importance, or implicitly specifying the number of technical features indicated in this embodiment. Therefore, features defined with terms such as "first" and "second" in the embodiments of this invention can explicitly or implicitly indicate that the embodiment includes at least one of those features. In the description of this invention, the word "multiple" means at least two or more, such as two, three, four, etc., unless otherwise explicitly specified in the embodiments.

[0150] In this invention, unless otherwise explicitly specified or limited in the embodiments, the terms "installation," "connection," "joining," and "fixing" appearing in the embodiments should be interpreted broadly. For example, a connection can be a fixed connection, a detachable connection, or an integral part; it can also be a mechanical connection, an electrical connection, etc. Of course, it can also be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components, or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific implementation.

[0151] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method of calibrating a current-voltage detection function of an energy storage system, characterized by, The method comprises the following steps: obtaining current sampling values and voltage sampling values of the energy storage system; performing offset correction calculation on the current sampling values and the voltage sampling values to obtain current offset correction values and voltage offset correction values, and performing offline calibration on the BMS of the energy storage system, and performing regular self-checking and self-calibration on the BMS; performing offline calibration on the BMS of the energy storage system, comprising: determining the analog voltage values corresponding to the current offset correction values and the voltage offset correction values, respectively; determining the first analog quantity range in which the analog voltage value corresponding to the current offset correction value is located, and determining the second analog quantity range in which the analog voltage value corresponding to the voltage offset correction value is located; determining a first proportional coefficient according to the first analog quantity range, and determining a second proportional coefficient according to the second analog quantity range; calibrating the current offset correction values according to the first proportional coefficient, and calibrating the voltage offset correction values according to the second proportional coefficient; The first proportional coefficient and the second proportional coefficient are determined according to the following steps: Divide the analog quantity range of the current sampling of the energy storage system into A segments, and divide the analog quantity range of the voltage sampling of the energy storage system into B segments; calibrate the upper limit analog quantity of the A segment by using an adjustable current source to obtain A calibration current digital quantities, and calibrate the upper limit analog quantity of the B segment by using an adjustable voltage source to obtain B calibration voltage digital quantities; determine the first proportional coefficient corresponding to each segment in the A segment according to the A calibration current digital quantities, the corresponding original current digital quantities, and the upper limit analog quantity of the A segment, and determine the second proportional coefficient corresponding to each segment in the B segment according to the B calibration voltage digital quantities, the corresponding original voltage digital quantities, and the upper limit analog quantity of the B segment, wherein the original current digital quantity is the current offset correction value corresponding to the upper limit analog quantity of the A segment, and the original voltage digital quantity is the voltage offset correction value corresponding to the upper limit analog quantity of the B segment.

2. The calibration method of claim 1, wherein, The offset correction calculation on the current sampling values and the voltage sampling values comprises: determining at least one larger current value and at least one smaller current value in M continuous current sampling values, and determining at least one larger voltage value and at least one smaller voltage value in N continuous voltage sampling values, wherein M and N are integers greater than 2, respectively; remove the at least one larger current value and the at least one smaller current value from the M current sampling values, and perform filtering processing to obtain the current offset correction values, and remove the at least one larger voltage value and the at least one smaller voltage value from the N voltage sampling values, and perform filtering processing to obtain the voltage offset correction values.

3. The calibration method according to any one of claims 1-2, characterized in that, The regular self-checking on the BMS comprises: when the energy storage system is powered on, obtaining the voltage value of each battery cell in the battery cluster of the energy storage system, and determining the first total voltage of the battery cluster according to the voltage value of each battery cell; determining that the voltage detection function of the energy storage system is failed when a voltage error between the first total voltage and a second total voltage corresponding to the voltage sampling value is greater than or equal to a first preset voltage threshold, and determining that the current detection function of the energy storage system is failed when the total current corresponding to the current sampling value is not zero.

4. The calibration method of claim 3, wherein, The self-calibration of the BMS comprises: calibrating the voltage detection function of the BMS according to the first total voltage when the charging of the energy storage system starts and / or the discharging of the energy storage system ends; determining the running power of the energy storage system when the energy storage system runs in a constant power mode, determining a first current according to the running power and the second total voltage, and obtaining an output current of the energy storage system, and self-calibrating the current detection function of the BMS according to the first current and the output current when the total current corresponding to the current sampling value is not between the first current and the output current.

5. The method of calibration of claim 1, wherein, The method further comprises: analyzing the hardware error of the current sampling circuit and the voltage sampling circuit of the BMS.

6. A computer-readable storage medium, characterized in that, A storage medium having stored thereon a calibration program of current and voltage detection functions of an energy storage system, which, when executed by a processor, implements the calibration method of the current and voltage detection functions of the energy storage system according to any one of claims 1-5.

7. An energy storage system characterized by, A computer device comprising a memory, a processor, and a calibration program of current and voltage detection functions of an energy storage system stored in the memory and executable on the processor, which, when executed by the processor, implements the calibration method of the current and voltage detection functions of the energy storage system according to any one of claims 1-5.

8. A calibration device for current-voltage detection function of an energy storage system, characterized in that, comprises: an obtaining module for obtaining a current sampling value and a voltage sampling value of the energy storage system; a calibration module for performing deviation correction calculation on the current sampling value and the voltage sampling value to obtain a current deviation value and a voltage deviation value, performing offline calibration on a BMS of the energy storage system, and performing periodic self-checking and self-calibration on the BMS; the calibration module is configured to determine an analog voltage value corresponding to the current deviation value and an analog voltage value corresponding to the voltage deviation value, respectively; determine a first analog range in which the analog voltage value corresponding to the current deviation value is located, and a second analog range in which the analog voltage value corresponding to the voltage deviation value is located; determine a first proportional coefficient according to the first analog range, and determine a second proportional coefficient according to the second analog range; calibrate the current deviation value according to the first proportional coefficient, and calibrate the voltage deviation value according to the second proportional coefficient; the first proportional coefficient and the second proportional coefficient are determined according to the following steps: divide the analog range of the current sampling of the energy storage system into A segments, and divide the analog range of the voltage sampling of the energy storage system into B segments; calibrate the upper limit analog quantity of the A segments by using an adjustable current source to obtain A calibration current digital quantities, and calibrate the upper limit analog quantity of the B segments by using an adjustable voltage source to obtain B calibration voltage digital quantities; According to the A calibration current digital quantity and the corresponding original current digital quantity, and the upper limit analog quantity of the A segments, the corresponding first proportional coefficient of each segment in the A segments is determined, and according to the B calibration voltage digital quantity and the corresponding original voltage digital quantity, and the upper limit analog quantity of the B segments, the corresponding second proportional coefficient of each segment in the B segments is determined, wherein the original current digital quantity is a current correction value corresponding to the upper limit analog quantity of the A segments, and the original voltage digital quantity is a voltage correction value corresponding to the upper limit analog quantity of the B segments.

9. A power plant, characterized in that An energy storage system comprising the system of claim 7. An energy storage system comprising the system of claim 7.

Images