An online real-time monitoring system and method for internal resistance of energy storage battery

Abstract

The present invention proposes an online real-time monitoring system and method for the internal resistance of an energy storage battery, and belongs to the technical field of battery internal resistance monitoring. The present invention utilizes a bridge circuit to avoid the battery internal resistance measurement method being affected by a charger or a power load during the online measurement process, so that the excitation source reference condition and the withstand voltage condition are not affected by the operating state of the battery and the number of batteries in the battery string and the open circuit voltage, thereby reducing the state adjustment of the excitation source, reducing the closed-loop control process of the excitation source and the battery, and realizing online detection of the battery internal resistance under unchanged reference conditions; solving the problem of being unable to measure the entire battery module at one time, and realizing simultaneous detection of multiple battery internal resistances, thereby improving the detection efficiency of battery internal resistance parameters, reducing the time required for battery detection, and reducing operating costs. The present invention can be applied not only to battery internal resistance detection technology, but also to corresponding electrical detection fields, and is widely extended with broad application prospects.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery internal resistance monitoring, and in particular relates to an online monitoring system and method for the internal resistance of an energy storage battery based on a bridge circuit. Background Art

[0002] As a power source, lithium-ion batteries must be used in series to meet voltage requirements. If one of the batteries in a series battery system fails, the entire battery string will be scrapped if not discovered in time. Not only the expensive batteries are lost, but also the system paralysis and data loss caused by the uncertainty of the battery status are disastrous. In order to ensure good battery performance and extend battery life, the battery must be managed and controlled reasonably and effectively. The size of the battery internal resistance determines the quality of the battery performance, so the detection of the battery internal resistance becomes particularly important.

[0003] When existing detection methods are used to detect batteries or battery packs, most of them need to be tested offline, or even performed battery by battery. This method is not only time-consuming and laborious, but also inefficient, and seriously affects the detection efficiency of energy storage batteries. When existing online detection methods are used to detect batteries or battery packs online, the excitation source needs to be excited at a certain battery string voltage reference, but the open circuit voltage of the battery string changes with the change of the battery's state of charge. The existing excitation source cannot guarantee the online measurement of the battery internal resistance without changing the voltage reference condition.

[0004] For example, CN 113740751 A discloses a battery internal resistance detection device and method, which improves the detection accuracy of the battery internal resistance by combining the direct current method and the alternating current method. However, considering that the use of storage batteries is often powered in the form of battery packs, if the condition of each battery is to be monitored, the cost issue needs to be considered. CN216209746 U discloses a portable battery internal resistance detection device. The internal resistance is detected by constant current resistor discharge, but this method can only analyze system faults offline and cannot detect the internal resistance of the battery in an online state. CN1036050000A discloses an online detection method for the internal resistance of parallel storage batteries. The internal resistance is detected by using a constant current generator to excite the battery, but the excitation source of this method cannot change the voltage reference, so one excitation source can only measure a single battery, and the influence of frequency on the internal resistance of the battery is ignored, so the information obtained is not comprehensive enough.

[0005] Therefore, based on the purpose of high efficiency, accuracy and economy, it has become a necessary research topic to carry out revolutionary innovative design for the problems existing in the above-mentioned monitoring methods of the internal resistance of energy storage batteries, which has important theoretical significance and practical application value. Summary of the invention

[0006] In order to solve the problems that the battery internal resistance measurement method is affected by the load during the online measurement process, the reference conditions and voltage resistance conditions of the excitation source need to be constantly changed, and the entire battery module cannot be measured at one time, the present invention innovates the traditional battery internal resistance measurement design idea and proposes an online real-time monitoring method for the internal resistance of an energy storage battery. This method has the advantages of being simple, safe, easy to operate, low cost, capable of online measurement, and having accurate data.

[0007] To achieve the above object, the technical solution of the present invention is:

[0008] An online real-time monitoring system for the internal resistance of an energy storage battery comprises a battery string, an MCU (Microcontroller Unit), a response signal measuring device and a host computer.

[0009] The MCU includes an excitation source, a current sampling circuit, a wireless communication module and an internal resistance calculation module. Among them, the excitation source is connected to the balance position in the middle of the two battery strings to form a Wheatstone bridge circuit; the program parameters of the MCU are modified through the serial port to change the frequency of the excitation source, and a constant AC excitation current signal of 0.01 to 10kHz is generated. The current sampling circuit is connected to the A / D port of the MCU, and the current excitation signal of the excitation source and the current signals of the upper and lower half bridges (with the excitation source circuit as the boundary, the circuit above the excitation source is called the upper half bridge, and the circuit below the excitation source is called the lower half bridge) are sampled in real time by the current continuous sampling algorithm and the current sampling waveform is recorded and stored in the internal resistance calculation module to provide a data source for subsequent internal resistance calculation. The wireless communication module communicates with the wireless communication module of the response signal measurement device in an asynchronous communication manner, sends the frequency information of the excitation source to the response signal measurement device, and receives the voltage response signal and phase difference information measured by the response signal measurement device at this frequency, which are stored in the internal resistance calculation module to provide a data source for subsequent internal resistance calculation. The internal resistance calculation module processes the stored data to calculate the battery internal resistance, which is then stored in the host computer to provide a data source for subsequent drawing of the electrochemical impedance spectrum of the host computer.

[0010] The response signal measuring device comprises a voltage sampling circuit, an AC transmitter and a wireless communication module. The voltage sampling circuit is connected to the A / D port of the single-chip microcomputer in the response signal measuring device, and the voltage response signal of the battery is sampled in real time using a voltage continuous sampling algorithm and the voltage sampling waveform is recorded. The AC transmitter is connected to the A / D port of the single-chip microcomputer in the response signal measuring device, and the phase difference θ between the battery current and the battery response voltage is obtained through the battery current and the battery response voltage. The wireless communication module is used to communicate with the wireless communication module of the MCU.

[0011] The voltage sampling circuit includes an AC differential circuit connected in parallel at both ends of the single battery of the battery string. The secondary amplifier circuit connected to the AC differential circuit removes the common mode noise in the noise environment, leaving the tiny signal to be detected, and inputs it to the signal end of the phase-locked amplifier circuit. At the same time, the voltage signal at both ends of the other battery current sampling resistor is input to the reference voltage end of the phase-locked amplifier circuit after amplification. After the two signals are amplified by the phase-locked amplifier circuit, a voltage signal including DC and multi-frequency components will be generated. This signal is filtered out of the multi-frequency components by a low-pass filter to obtain a DC voltage. The DC voltage is converted into a digital signal by AD sampling in the single-chip microcomputer, and the voltage amplitude is obtained after Fourier analysis, filtering and data processing. The AC transmitter is connected to the secondary amplifier circuit (shared with the voltage sampling circuit) to obtain the response voltage. The voltage signal at both ends of the other battery current sampling resistor is input to the AC transmitter after amplification. The AC transmitter contains a multiplier to process the two input signals. The output signal is filtered out of the multi-frequency components by a low-pass filter, and the input single-chip microcomputer obtains the phase difference of the two signals through calculation.

[0012] The monitoring method using the above-mentioned online real-time monitoring system comprises the following steps:

[0013] Step 1: Connect the excitation source to the balance position between the two battery strings to form a Wheatstone bridge circuit; use the current shunt principle to excite the two battery strings simultaneously.

[0014] Step 2: Modify the MCU program parameters through the serial port to set the excitation amplitude and frequency of the excitation source to generate a constant AC excitation current signal of 0.01 to 10 kHz.

[0015] Step 3: The wireless communication module in the MCU sends the frequency information of the excitation source to the wireless communication module in the response signal measurement device; at the same time, the current continuous sampling algorithm is used to sample the current excitation signal of the excitation source in real time through the current sampling circuit and record the current sampling waveform, which is stored in the internal resistance calculation module.

[0016] Step 4: After the wireless communication module in the response signal measurement device receives the frequency information of the excitation source, it uses the voltage continuous sampling algorithm to sample the voltage response signal and phase difference signal of the battery in real time through the voltage sampling circuit and the AC transmitter and records the voltage sampling waveform.

[0017] Step 5: The wireless communication module in the response signal measurement device sends the frequency information of the excitation source, the voltage response signal of the battery and the phase difference signal to the wireless communication module in the MCU, and stores them in the internal resistance calculation module of the MCU.

[0018] Step 6: The internal resistance calculation module in the MCU calculates and processes the current excitation signal of the excitation source, the voltage response signal of the battery, and the phase difference signal to determine the internal resistance Re(Z) and Im(Z) of the battery. Specifically, the following steps are included:

[0019] Step 6.1: Traverse the sampling point data within a period t=1 / f to calculate the voltage effective value U[i], current effective value I[j] and voltage-current phase difference θ[k], and define the starting points as i, j, k, m, n, where i=1, j=1, k=1, m=1, n=1.

[0020] Step 6.2: Determine the internal resistance Re(Z)[m] and Im(Z)[n] of the battery using the impedance formula Z=U[i] / I[j] and Re(Z)=Zcosθ[k], Im(Z)=Zsinθ[k].

[0021] Step 6.3: Let i'=i+1, j'=j+1, k'=k+1, m'=m+1, n'=n+1, traverse all sampling points, obtain the voltage effective value U[i], current effective value I[j], voltage and current phase difference θ[k] within multiple cycles t=1 / f, repeat step 6.2 to calculate the internal resistance Re(Z)[m] and Im(Z)[n]; then take the average value of the internal resistance respectively and To reduce the error.

[0022] Step 7: Use MCU to change the excitation source frequency. If the accuracy requirement is not met, change the step frequency and repeat steps 3-6.

[0023] Step 8: MCU uses the wireless communication module to send the battery internal resistance information to the host computer.

[0024] Step 9: The host computer draws the electrochemical impedance spectrum.

[0025] Step 10: The host computer analyzes the battery health; the specific steps are as follows:

[0026] Step 10.1: Determine the characteristic frequency f by electrochemical impedance spectroscopy 1 ,f 2 and f 3 .

[0027] Step 10.2: Calculate the ohmic internal resistance R using formulas (1)-(3) respectively 0 , contact internal resistance R c and SEI film internal resistance R sei ;

[0028] R 0 ≈Real(Z(f 1 )) (1)

[0029] R c ≈Real(Z(f 2 ))-Real(Z(f 1 )) (2)

[0030] R sei ≈Real(Z(f 3 ))-Real(Z(f 2 )) (3)

[0031] Step 10.3: Compare the ohmic internal resistance, contact internal resistance and SEI film internal resistance with the set thresholds to determine the health status of the battery.

[0032] Furthermore, the principle of the phase difference between the response voltage and the excitation current obtained by the AC transmitter in step 4 is: let f 1 (t) is the voltage input signal with noise, that is, f 1 (t) = Vsin(ωt+α)+N(t), where Vsin(ωt+α) is a known signal. The amplitude of this voltage input signal is V, the angular frequency is ω, the phase angle is α, and N(t) is random noise; the current signal is f 2 (t) = Csin(ωt+β), C is the current signal amplitude, and the phase angle is β.

[0033] Then after the multiplier, we have

[0034]

[0035] Since the current signal f 2 (t) is uncorrelated with the noise N(t), so it can be filtered out by a low-pass filter. and C·n(t)sin(ωt+β), we can get If the amplitude of the voltage and current signals is known, then the phase difference between the two signals is θ = α-β.

[0036] Furthermore, in step 7, the step frequency f is changed (1) =0.9f (0) , calculate the internal resistance value U[i]*cosθ[k] / I[j] within a period t=1 / f. If |U[i-1]*cosθ[k-1] / I[j-1]-U[i]*cosθ[k] / I[j]|>ε does not meet the accuracy requirements, then reduce the measurement step value to 1 / 10 of the original value, that is, f (1) =0.99f (0) ; If |U[i-1]*cosθ[k-1] / I[j-1]-U[i]*cosθ[k] / I[j]≤ε meets the accuracy requirement, the measurement step value remains the original value, that is, f (1) =0.9f(0) ; where ε is the step threshold.

[0037] Furthermore, in step 10.1, the characteristic frequency point f 1 ,f 2 and f 3 The method for determining f is as follows: 1 is determined as the frequency value corresponding to any point on the electrochemical impedance spectrum that coincides with the Re(Z) axis; f 2 The frequency value corresponding to the maximum value of Im(Z) on the small capacitive loop is determined as follows; f 3 is determined as the frequency value corresponding to the maximum value of Im(Z) on the large capacitive loop.

[0038] Beneficial effects of the present invention: The online real-time monitoring method of the internal resistance of the energy storage battery described in the present invention utilizes a bridge circuit to avoid the battery internal resistance measurement method being affected by the charger or power load during the online measurement process, so that the excitation source reference condition and the withstand voltage condition are not affected by the operating state of the battery and the number of batteries in the battery string and the open circuit voltage, reducing the state adjustment of the excitation source, reducing the closed-loop control process of the excitation source and the battery, and realizing online detection of the battery internal resistance under unchanged reference conditions; solving the problem of being unable to measure the entire battery module at one time, realizing simultaneous detection of multiple battery internal resistances, improving the detection efficiency of battery internal resistance parameters, reducing the time required for battery detection, and reducing operating costs. The present invention can be applied not only to battery internal resistance detection technology, but also to corresponding electrical detection fields, and is widely extended and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a general schematic diagram of the present invention.

[0040] Figure 2 The invention relates to a voltage sampling circuit and an AC transmitter connection circuit.

[0041] Figure 3 It is a data processing communication flow chart of the present invention.

[0042] Figure 4 This is a functional diagram of the MCU of the present invention.

[0043] Figure 5 This is a functional diagram of the response signal measurement device of the present invention.

[0044] Figure 6 This is a flow chart of the internal resistance measurement of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0046] like Figure 1 As shown, the present invention provides an online real-time monitoring method for the internal resistance of an energy storage battery. The method connects an excitation source capable of generating a constant AC excitation current signal of 0.01 to 10kHz to a balanced position between two battery strings to form a Wheatstone bridge circuit. Ignoring the condition of inconsistent batteries, the voltage balance of the bridge circuit is utilized, the voltage at both ends of the middle branch is 0, and the current flowing through the middle branch is 0, so that the excitation source voltage reference value is always 0, and there is no need to adjust the excitation source reference voltage according to the operating state of the battery and the number of batteries in the battery string and the open circuit voltage. The bridge circuit has the characteristic of 0 current flowing through the middle branch, and at the same time, it can avoid being affected by the charger or the power load, so as to achieve online measurement. According to the principle of current shunting, two battery strings can be excited simultaneously, thus realizing online real-time monitoring of the internal resistance of multiple energy storage batteries; modify the program parameters of the MCU through the serial port to set the excitation amplitude and frequency of the excitation source, and generate a constant AC excitation current signal of 0.01-10kHz; send the frequency information of the excitation source to the wireless communication module in the response signal measurement device through the wireless communication module in the MCU, and use the current continuous sampling algorithm to sample the current excitation signal of the excitation source in real time through the current sampling circuit and record the current sampling waveform, which is stored in the internal resistance calculation module; after receiving the frequency information of the excitation source, the wireless communication module in the response signal measurement device uses the voltage continuous sampling The sample algorithm samples the voltage response signal and phase difference signal of the battery in real time through the voltage sampling circuit and AC transmitter and records the voltage sampling waveform; the wireless communication module in the response signal measurement device sends the frequency information of the excitation source, the voltage response signal and the phase difference signal of the battery to the wireless communication module in the MCU, and stores them in the internal resistance calculation module of the MCU; the internal resistance calculation module in the MCU calculates and processes the current excitation signal of the excitation source, the voltage response signal and the phase difference signal of the battery, and determines the internal resistance Re(Z) and Im(Z) of the battery by the impedance formula. Due to the use of the bridge circuit, when the internal resistance test of a battery in the system is completed, the internal resistance of all batteries in the system is also measured. The process is as described above, until all batteries in the entire system complete the internal resistance test, the battery internal resistance test process of the entire system is completed, and the obtained battery internal resistance information will be used by the host computer to draw the electrochemical impedance spectrum for analyzing the health of the battery, locating unqualified single cells, and quantifying the integrity of the battery pack.

[0047] The above-mentioned online real-time monitoring method of the internal resistance of the energy storage battery has the following specific implementation steps:

[0048] Step 1: Connect the excitation source to the balance position between the two battery strings to form a Wheatstone bridge circuit; use the current shunt principle to excite the two battery strings simultaneously.

[0049] Step 2: Modify the MCU program parameters through the serial port to set the excitation amplitude and frequency of the excitation source to generate a constant AC excitation current signal of 0.01 to 10 kHz.

[0050] Step 3: Send the frequency information of the excitation source to the wireless communication module in the response signal measurement device through the wireless communication module in the MCU; at the same time, use the current continuous sampling algorithm to sample the current excitation signal of the excitation source in real time through the current sampling circuit and record the current sampling waveform, which is stored in the internal resistance calculation module.

[0051] Step 4: After the wireless communication module in the response signal measurement device receives the frequency information of the excitation source, it uses the voltage continuous sampling algorithm to sample the voltage response signal and phase difference signal of the battery in real time through the voltage sampling circuit and the AC transmitter and records the voltage sampling waveform.

[0052] Step 5: The wireless communication module in the response signal measurement device sends the frequency information of the excitation source, the voltage response signal of the battery and the phase difference signal to the wireless communication module in the MCU, and stores them in the internal resistance calculation module of the MCU.

[0053] Step 6: The internal resistance calculation module in the MCU calculates and processes the current excitation signal of the excitation source, the voltage response signal of the battery, and the phase difference signal, and determines the internal resistance Re(Z) and Im(Z) of the battery by the impedance formula. Specifically, the following steps are included:

[0054] Step 6.1: Traverse the sampling point data within a period t=1 / f to calculate the voltage effective value U[i], current effective value I[j] and voltage-current phase difference θ[k], and define the starting points as i, j, k, m, n, where i=1, j=1, k=1, m=1, n=1.

[0055] Step 6.2: Determine the internal resistance Re(Z)[m] and Im(Z)[n] of the battery using the impedance formula Z=U[i] / I[j] and Re(Z)=Zcosθ[k], Im(Z)=Zsinθ[k].

[0056] Step 6.3: Let i'=i+1, j'=j+1, k'=k+1, m'=m+1, n'=n+1, traverse all sampling points, obtain the voltage effective value U[i], current effective value I[j], voltage and current phase difference θ[k] within multiple cycles t=1 / f, repeat step 6.2 to calculate the internal resistance Re(Z)[m] and Im(Z)[n]; then take the average value of the internal resistance respectively and To reduce the error.

[0057] Step 7: Use MCU to change the excitation source frequency. If the accuracy requirement is not met, change the step frequency f (1) =0.9f (0) , calculate the internal resistance value U[i]*cosθ[k] / I[j] within a period t=1 / f. If |U[i-1]*cosθ[k-1] / I[j-1]-U[i]*cosθ[k] / I[j]>ε does not meet the accuracy requirements, reduce the measurement step value to 1 / 10 of the original value, that is, f (1) =0.99f (0) ; If |U[i-1]*cosθ[k-1] / I[j-1]-U[i]*cosθ[k] / I[j]|≤ε meets the accuracy requirement, the measurement step value remains the original value, that is, f (1) =0.9f (0) ; Repeat steps 3-6.

[0058] Step 8: MCU uses the wireless communication module to send the battery internal resistance information to the host computer.

[0059] Step 9: The host computer draws the electrochemical impedance spectrum.

[0060] Step 10: The host computer analyzes the battery health; the specific steps are as follows:

[0061] Step 10.1: Determine the characteristic frequency f by electrochemical impedance spectroscopy 1 ,f 2 and f 3 ; Characteristic frequency f 1 ,f 2 and f 3 The method for determining f is as follows: 1 It is confirmed that the frequency value corresponding to any point on the electrochemical impedance spectrum that coincides with the Re(Z) axis; f 2 Confirm the frequency value corresponding to the maximum value of Im(Z) on the small capacitive loop; f 3 Confirm the frequency value corresponding to the maximum value of Im(Z) on the large capacitive loop.

[0062] Step 10.2: Calculate the ohmic internal resistance R using formulas (1)-(3) respectively 0 , contact internal resistance R c and SEI film internal resistance R sei ;

[0063] R 0 ≈Real(Z(f 1 )) (1)

[0064] R c ≈Real(Z(f2 ))-Real(Z(f 1 )) (2)

[0065] R sei ≈Real(Z(f 3 ))-Real(Z(f 2 )) (3)

[0066] Step 10.3: Compare the ohmic internal resistance, contact internal resistance and SEI film internal resistance with the set thresholds to determine the health status of the battery.

[0067] like Figure 2 As shown, the voltage sampling circuit includes an AC differential circuit connected in parallel at both ends of the single battery. The secondary amplifier circuit connected to the AC differential circuit removes the common mode noise in the noise environment, leaving the tiny signal to be detected, which is input to the signal end of the phase-locked amplifier circuit. At the same time, the voltage signal at both ends of the battery current sampling resistor is input to the reference voltage end of the phase-locked amplifier circuit after amplification. After the two signals are phase-locked amplified by the phase-locked amplifier circuit, a voltage signal including DC and multi-frequency components will be generated. This signal is then filtered out of the multi-frequency components by a low-pass filter to obtain a DC voltage. The DC voltage is converted into a digital signal by AD sampling in the single-chip microcomputer. After Fourier analysis, filtering and data processing, the voltage amplitude is obtained. The AC transmitter is connected to the secondary amplifier circuit to obtain the phase difference between the response voltage and the excitation current; let f 1 (t) is the voltage input signal with noise, that is, f 1 (t) = Vsin(ωt+α)+N(t), where Vsin(ωt+α) is a known signal. The amplitude of this voltage input signal is A, the angular frequency is ω, the phase angle is α, and N(t) is random noise; the current signal is f 2 (t) = Csin(ωt+β), the phase angle is β. Then after the multiplier, we have

[0068]

[0069] Since the current signal f 2 (t) is uncorrelated with the noise N(t), so it can be filtered out by a low-pass filter. and C·n(t)sin(ωt+β), we can get If the amplitude of the voltage and current signals is known, it is easy to calculate the phase difference θ = α-β between the two signals.

[0070] like Figure 3As shown, the response signal measuring device and the MCU use an asynchronous communication method, which does not require high clock synchronization between the sender and the receiver, making the entire device simpler and more convenient. The MCU first transmits the frequency information to the response signal measuring device. After the response signal measuring device successfully receives the response signal, it measures the response signal and sends the measurement information together with the previously received frequency information to the MCU, so as to achieve the correspondence between the frequency information and the voltage response signal measured at the frequency and the phase difference information.

[0071] The set amplitude, frequency value, characteristic point, set threshold, and step threshold ε are respectively fixed reference values, which are set according to those skilled in the art and the actual implementation conditions, that is, they need to be adjusted according to the specific type of the battery to be measured. For example, different reference values ​​are set for different ranges of the battery to be measured, which is feasible and reasonable within the protection scope of the present invention.

[0072] In summary, the present invention solves the problems of the battery internal resistance measurement method being affected by the load during the online measurement process, the reference conditions and withstand voltage conditions of the excitation source needing to be constantly changed, and the measurement error caused by the change of the battery electromotive force, thereby realizing the online detection of the battery internal resistance; solves the problem of not being able to measure the entire battery module at one time, and realizes the simultaneous detection of multiple battery internal resistances; the present invention can be applied not only to battery internal resistance detection technology, but also to corresponding electrical detection fields, and is widely extended and has broad application prospects.

Claims

1. An online real-time monitoring system for the internal resistance of an energy storage battery, characterized in that: The system includes a battery string, an MCU, a response signal measurement device and a host computer; The MCU comprises an excitation source, a current sampling circuit, a wireless communication module and an internal resistance calculation module; wherein the excitation source is connected to a balance position in the middle of two battery strings to form a Wheatstone bridge circuit; the program parameters of the MCU are modified through the serial port to change the frequency of the excitation source, and a constant AC excitation current signal of 0.01 to 10 kHz is generated; the current sampling circuit is connected to the A / D port of the MCU, and the current excitation signal of the excitation source and the current signal of the upper and lower half bridges are sampled in real time by a current continuous sampling algorithm, and the current sampling waveform is recorded and stored in the internal resistance calculation module, providing a data source for subsequent internal resistance calculation; the wireless communication module communicates with the wireless communication module of the response signal measurement device in an asynchronous communication manner, sends the frequency information of the excitation source to the response signal measurement device, and receives the voltage response signal and phase difference information measured by the response signal measurement device at the frequency, and stores them in the internal resistance calculation module, providing a data source for subsequent internal resistance calculation; the internal resistance calculation module processes and calculates the stored data to obtain the battery internal resistance, and stores it in the host computer, providing a data source for the subsequent drawing of the electrochemical impedance spectrum of the host computer; The response signal measuring device comprises a voltage sampling circuit, an AC transmitter and a wireless communication module; wherein the voltage sampling circuit is connected to the A / D port of the single-chip microcomputer in the response signal measuring device, and uses a voltage continuous sampling algorithm to sample the voltage response signal of the battery in real time and record the voltage sampling waveform; the AC transmitter is connected to the A / D port of the single-chip microcomputer in the response signal measuring device, and obtains the phase difference between the battery current and the battery response voltage through the battery current and the battery response voltage; and the wireless communication module is used to communicate with the wireless communication module of the MCU.

2. The online real-time monitoring system of the internal resistance of an energy storage battery according to claim 1, characterized in that: The voltage sampling circuit includes an AC differential circuit connected in parallel at both ends of the single battery of the battery string. The secondary amplifier circuit connected to the AC differential circuit removes the common mode noise in the noise environment, leaving the tiny signal to be detected, and inputs it into the signal end of the phase-locked amplifier circuit. At the same time, the voltage signal at both ends of the battery current sampling resistor is input into the reference voltage end of the phase-locked amplifier circuit after amplification. After the two signals are amplified by the phase-locked amplifier circuit, a voltage signal including DC and multi-frequency components will be generated. The signal is filtered out of the multi-frequency components by a low-pass filter to obtain a DC voltage. The DC voltage is converted into a digital signal by AD sampling in the single-chip microcomputer, and the voltage amplitude is obtained after Fourier analysis, filtering and data processing. The AC transmitter is connected to the secondary amplifier circuit to obtain the response voltage, and the voltage signal at both ends of the battery current sampling resistor is input into the AC transmitter after amplification. The AC transmitter contains a multiplier to process the two input signals, and the output signal is filtered out of the multi-frequency components by a low-pass filter, and the input single-chip microcomputer obtains the phase difference of the two signals through calculation.

3. A monitoring method using the online real-time monitoring system according to claim 1 or 2, characterized in that: The method comprises the following steps: Step 1: Connect the excitation source to the balance position between the two battery strings to form a Wheatstone bridge circuit; use the current shunt principle to excite the two battery strings simultaneously; Step 2: Modify the program parameters of the MCU through the serial port to set the excitation amplitude and frequency of the excitation source to generate a constant AC excitation current signal of 0.01 to 10 kHz; Step 3: The wireless communication module in the MCU sends the frequency information of the excitation source to the wireless communication module in the response signal measurement device; at the same time, the current continuous sampling algorithm is used to sample the current excitation signal of the excitation source in real time through the current sampling circuit and record the current sampling waveform, which is stored in the internal resistance calculation module; Step 4: After the wireless communication module in the response signal measurement device receives the frequency information of the excitation source, it uses the voltage continuous sampling algorithm to sample the voltage response signal and phase difference signal of the battery in real time through the voltage sampling circuit and the AC transmitter and records the voltage sampling waveform; Step 5: The wireless communication module in the response signal measurement device sends the frequency information of the excitation source, the voltage response signal of the battery, and the phase difference signal to the wireless communication module in the MCU, and stores them in the internal resistance calculation module of the MCU; Step 6: The internal resistance calculation module in the MCU calculates and processes the current excitation signal of the excitation source, the voltage response signal of the battery, and the phase difference signal to determine the internal resistance Re(Z) and Im(Z) of the battery; Step 7: Use MCU to change the excitation source frequency. If the accuracy requirement is not met, change the step frequency and repeat steps 3-6. Step 8: MCU uses the wireless communication module to send the battery internal resistance information to the host computer; Step 9: The host computer draws the electrochemical impedance spectrum; Step 10: The host computer analyzes the battery health.

4. The method according to claim 3, characterized in that The step 6 specifically comprises the following steps: Step 6.1: Traverse the sampling point data within a period t = 1 / f to calculate, calculate the voltage effective value U[i], current effective value I[j] and voltage and current phase difference θ[k], define the starting point as i, j, k, m, n, where i = 1, j = 1, k = 1, m = 1, n = 1; Step 6.2: Determine the internal resistance Re(Z)[m] and Im(Z)[n] of the battery by using the impedance formula Z=U[i] / I[j] and Re(Z)=Zcosθ[k], Im(Z)=Zsinθ[k]; Step 6.3: Let i'=i+1, j'=j+1, k'=k+1, m'=m+1, n'=n+1, traverse all sampling points, obtain the voltage effective value U[i], current effective value I[j], voltage and current phase difference θ[k] within multiple cycles t=1 / f, repeat step 6.2 to calculate the internal resistance Re(Z)[m] and Im(Z)[n]; then take the average value of the internal resistance respectively and To reduce the error.

5. The method according to claim 3 or 4, characterized in that: In step 7, change the step frequency f (1) =0.9f (0) , calculate the internal resistance value U[i]*cosθ[k] / I[j] within a period t=1 / f. If |U[i-1]*cosθ[k-1] / I[j-1]-U[i]*cosθ[k] / I[j]|>ε does not meet the accuracy requirements, then reduce the measurement step value to 1 / 10 of the original value, that is, f (1) =0.99f (0) ; where ε is the step threshold.

6. The method according to claim 3 or 4, characterized in that: The step 10 specifically includes the following steps: Step 10.1: Determine the characteristic frequencies f1, f2 and f3 by electrochemical impedance spectroscopy; Step 10.2: Calculate the ohmic internal resistance R0 and contact internal resistance R by using formulas (1)-(3) respectively. c and SEI film internal resistance R sei ; R0≈Real(Z(f1)) (1) R c ≈Real(Z(f2))-Real(Z(f1)) (2) R sei ≈Real(Z(f3))-Real(Z(f2)) (3) Step 10.3: Compare the ohmic internal resistance, contact internal resistance and SEI film internal resistance with the set thresholds to determine the health status of the battery.

7. The method according to claim 5, characterized in that The step 10 specifically includes the following steps: Step 10.1: Determine the characteristic frequencies f1, f2 and f3 by electrochemical impedance spectroscopy; Step 10.2: Calculate the ohmic internal resistance R0 and contact internal resistance R by using formulas (1)-(3) respectively. c and SEI film internal resistance R sei ; R0≈Real(Z(f1)) (1) R c ≈Real(Z(f2))-Real(Z(f1)) (2) R sei ≈Real(Z(f3))-Real(Z(f2)) (3) Step 10.3: Compare the ohmic internal resistance, contact internal resistance and SEI film internal resistance with the set thresholds to determine the health status of the battery.

8. The method according to claim 6, characterized in that In step 10.1, the characteristic frequency points f1, f2 and f3 are determined as follows: f1 is determined as the frequency value corresponding to any point on the electrochemical impedance spectrum that coincides with the Re(Z) axis; f2 is determined as the frequency value corresponding to the maximum value of Im(Z) on the small capacitive loop; f3 is determined as the frequency value corresponding to the maximum value of Im(Z) on the large capacitive loop.

9. The method according to claim 3, 4, 7 or 8, characterized in that The principle of the phase difference between the response voltage and the excitation current obtained by the AC transmitter in step 4 is: let f1(t) be a voltage input signal accompanied by noise, that is, f1(t)=Vsin(ωt+α)+N(t), where Vsin(ωt+α) is a known signal, the amplitude of this voltage input signal is V, the angular frequency is ω, the phase angle is α, and N(t) is random noise; the current signal is f2(t)=Csin(ωt+β), C is the current signal amplitude, and the phase angle is β; then after the multiplier, there is Since the current signal f2(t) is unrelated to the noise N(t), it is filtered out by a low-pass filter. and C·n(t)sin(ωt+β), we get If the amplitude of the voltage and current signals is known, then the phase difference between the two signals is θ = α-β.

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