Online SOC (State of Charge) measurement and diagnosis system and method for flow battery

Abstract

The invention belongs to the technical field of electrochemical energy storage, and discloses an online SOC (State of Charge) measurement and diagnosis system and method for a flow battery. Through a dynamic compensation OCV algorithm, a UV-Vis measurement method, a coulomb metering correction algorithm, a battery health factor algorithm and other technologies, the online SOC measurement precision, stability and real-time performance of the flow battery are remarkably improved, the defects in the prior art are overcome, the operation efficiency of the flow battery is improved, and the service life of the flow battery is prolonged.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of electrochemical energy storage, and particularly relates to a flow battery online SOC measurement and diagnosis system and method. BACKGROUND

[0002] Flow batteries are widely used in grid peak shaving, renewable energy storage and other scenarios due to their long service life, fast response and strong scalability. However, the state of charge (SOC) of the flow battery cannot be directly measured by voltage, and is affected by many factors such as fluid concentration, electrolyte flow rate, battery temperature, etc. Traditional coulomb counting method, open circuit voltage method, etc. are difficult to accurately apply in the flow system. Lack of accurate SOC estimation will lead to decreased system control accuracy, reduced capacity utilization, and even cause abnormal aging or safety accidents of the battery. Therefore, there is an urgent need for a method that can achieve high-precision, real-time SOC estimation and battery health state diagnosis in combination with data analysis based on the operating characteristics of the flow battery.

[0003] The existing measurement system usually faces the following problems: 1. The coulomb counting method can achieve continuous monitoring, but its error will accumulate over time. Due to the measurement error of the current sensor and the influence of the side reaction, the cumulative error of 24 hours may exceed 8%. The biggest problem of this method is that it assumes that the battery capacity is constant, which cannot identify the loss of electrolyte active material and cannot adapt to the change of current efficiency caused by flow rate change, and has poor reliability in long-term operation.

[0004] 2. The battery health state will directly affect the accuracy of SOC measurement, and electrolyte imbalance (such as abnormal valence state of vanadium ions or permeation) will cause OCV deviation, resulting in 5-10% SOC error; membrane aging will increase internal resistance and polarization voltage; and pump efficiency decline will cause uneven flow, which will cause significant deviation of traditional SOC measurement methods.

[0005] Therefore, it is of great engineering value and application prospect to develop a high-precision, high-real-time, and battery health factor considering SOC online monitoring method. SUMMARY

[0006] In order to overcome the shortcomings of the prior art, the application provides a flow battery online SOC measurement and diagnosis system and method, which significantly improves the online SOC measurement accuracy, stability and real-time of the flow battery by using dynamic compensation OCV algorithm, UV-Vis measurement method, coulomb counting correction algorithm, battery health factor algorithm and other technologies, to solve the shortcomings in the prior art and enhance the operation efficiency of the flow battery and prolong its service life.

[0007] The above object of the application is achieved by the following technical solutions: a flow battery online SOC measurement and diagnosis system, comprising a dynamic compensation OCV algorithm module, a UV-Vis measurement module, a coulomb counting correction module, a battery health monitoring module, and a comprehensive dynamic weight module; the flow battery stack is provided with a positive electrolyte circulation line, a negative electrolyte circulation line, and an OCV circulation line; the UV-Vis measurement module is connected to the branch of the line from the stack to the positive electrolyte line and the line from the negative electrolyte to the stack; the dynamic compensation OCV algorithm module is connected to the branch of the line from the positive electrolyte to the stack, the line from the stack to the negative electrolyte, the OCV, the line from the OCV to the stack, and the battery health monitoring module; the battery health monitoring module is connected to the branch of the line from the positive electrolyte circulation line to the UV-Vis measurement module, the line from the negative electrolyte circulation line to the UV-Vis measurement module, and the coulomb counting correction module; the coulomb counting correction module is connected to the branch of the line from the positive electrolyte circulation line to the dynamic compensation OCV algorithm module, the line from the negative electrolyte circulation line to the dynamic compensation OCV algorithm module, and the line from the OCV circulation line to the dynamic compensation OCV algorithm module; and the dynamic compensation OCV algorithm module, the coulomb counting correction module, and the battery health monitoring module are each connected to the line of the comprehensive dynamic weight module.

[0008] Another object of the application is to protect the measurement and diagnosis method of the above-mentioned flow battery online SOC measurement and diagnosis system, and the steps are as follows: 1. Collecting the open circuit voltage on the line from the OCV to the dynamic compensation OCV algorithm module, the current on the line from the OCV circulation line to the dynamic compensation OCV algorithm module, the positive flow rate on the line from the positive electrolyte circulation line to the dynamic compensation OCV algorithm module, and the negative flow rate on the line from the negative electrolyte circulation line to the dynamic compensation OCV algorithm module; 2. Measuring the V 4+ , V 5+ concentration of the positive electrolyte circulation line by the UV-Vis measurement module, measuring the V 2+ , V 3+ concentration of the negative electrolyte circulation line, calculating the ion concentration ratio in the electrolyte, and obtaining the electrolyte health state EHF and the size of ; 3. Calculating the dynamic OCV compensation by the open circuit voltage, current, and positive and negative electrode pipeline flow rate collected in step 1, and obtaining the size of calculated by the compensated OCV; 4. Calculating the deviation of the coulomb counting module by the positive and negative flow rates collected in step 1, and obtaining the size of of the module; 5. Calculating the SOC of the system by the comprehensive weight.

[0009] Further, the step 2 electrolyte health state calculation formula is: EHF = Wherein, [V 5+ ] is +5 valence vanadium ion concentration, unit is mol / L, [V 4+ ] is +5 valence vanadium ion concentration, unit is mol / L, [V 2+ ] is +5 valence vanadium ion concentration, unit is mol / L, [V 3+ ] is +5 valence vanadium ion concentration, unit is mol / L, EHF is electrolyte health state, calculated by battery health monitoring module.

[0010] Further, the step 2 is calculated as follows: The calculation formula is: Wherein, [V 5+ ] is +5 valence vanadium ion concentration, unit is mol / L, [V 4+ ] is +5 valence vanadium ion concentration, unit is mol / L, [V 2+ ] is +5 valence vanadium ion concentration, unit is mol / L, [V 3+ ] is +5 valence vanadium ion concentration, unit is mol / L, [V total ] is total vanadium ion concentration, unit is mol / L.

[0011] Further, the step 3 specific calculation formula is: Wherein: Is the compensated open circuit voltage (V); Is the measured battery terminal voltage (V); Is the polarization compensation coefficient (Ω·s), the value range is 0.01-0.05; Is the current change rate (A / s); Is the temperature compensation coefficient (mV / ℃), the calculation formula is: Is the real-time electrolyte temperature (℃); Is the reference temperature (25℃); Relaxation compensation coefficient (mV), the calculation formula is: Is the dynamic adjustment of mixing degree coefficient, the calculation formula is: t is the time from the last current mutation (s).

[0012] The final SOC calculation formula is:

[0013] Further, the step 4 calculation formula is: Wherein is the initial SOC reference value, which is reset regularly (every 4 hours or when the SOC changes by 5%) by UV-Vis spectrum or dynamic OCV; is the dynamic current efficiency coefficient, which is adjusted according to the electrolyte health state (EHF), and the calculation formula is: is the total capacity of the system, and the calibrated value decays with the number of cycles: The formula is , N is the number of cycles; is the real-time current, 50HZ sampling; is the flow rate compensation function, and the calculation formula is:

[0014] Further, the step 5 calculation formula is:

[0015] Further, the UV-Vis measurement module in step 2 detects the absorbance at 510 nm and 650 nm, wherein the absorbance at 510 nm is detected by V 2+ , V 3+ concentration, and the absorbance at 650 nm is detected by V 4+ , V 5+ concentration.

[0016] The beneficial effects of the present application compared with the prior art are: · Breakthrough the limitation of traditional OCV measurement, realize millisecond level dynamic compensation The dynamic compensation OCV algorithm proposed in the present application realizes real-time correction of polarization, electrolyte temperature drift and relaxation effect by introducing parameters such as current change rate, temperature and running time, and the dynamic error of OCV-SOC estimation is significantly reduced compared with traditional methods, which significantly improves the SOC estimation accuracy of flow battery in dynamic charging and discharging process.

[0017] · Adopt UV-Vis dual-wavelength detection to realize second-level SOC estimation response Compared with the traditional voltage estimation or coulomb meter method, the present application realizes direct spectral analysis of SOC by detecting the concentration ratio of vanadium ions in electrolyte at 510 nm and 650 nm, significantly improves the measurement and calculation speed, greatly improves the system response speed and real-time performance, and is suitable for frequent variable load working conditions.

[0018] · Multi-dimensional compensation mechanism effectively suppresses the accumulation of coulomb integral error In the "Battery Charging Capacity Measurement Method and Device" (CN106483462A), the SOC calculation process does not consider the deviation caused by current change and flow rate, while the present application introduces a dynamic current efficiency coefficient and a flow rate compensation function in the coulomb meter correction module, and periodically forces the calibration of the integral initial value through the UV-Vis or OCV module, which controls the long-term running SOC error within a very low range, solves the key problems of error accumulation with time and constant capacity assumption in traditional coulomb meter, and improves the long-term stability of the system.

[0019] · Introducing health factor to improve model adaptability and estimation robustness Traditional SOC algorithms ignore the influence of battery health status (such as ion permeation, membrane aging, and pump efficiency decline) on estimation accuracy, such as in "Battery Display SOC Follow Correction Method and System" (CN119805236A), although an online SOC calculation method is proposed, the influence of health factor (EHF) during long-term operation of the battery is not considered. In the present application, the health factor (EHF) dynamically adjusts key parameters such as polarization coefficient and current efficiency, realizes automatic adaptation of the model according to the current running state, and improves the adaptability and robustness of SOC estimation under actual complex working conditions.

[0020] · Multi-algorithm fusion and dynamic weight allocation to ensure optimal and reliable results The present application allocates weights to the results of dynamic OCV calculation, UV-Vis measurement and coulomb correction through a comprehensive dynamic weight module, automatically adjusts the proportion according to real-time error, confidence and data consistency, effectively suppresses the instability of a single algorithm under certain working conditions, and finally the SOC estimation result is more stable and reliable. BRIEF DESCRIPTION OF DRAWINGS

[0021] The present application will be further described below in conjunction with the drawings and specific embodiments Figure 1 The structure diagram of the present application liquid flow battery online SOC measurement and diagnosis system.

[0022] Figure 1. Stack; 2. Positive electrolyte; 3. Negative electrolyte; 4. OCV; 5. Dynamic compensation OCV algorithm module; 6. UV-Vis measurement module; 7. Battery health monitoring module; 8. Coulomb counting correction module; 9. Comprehensive dynamic weight module. DETAILED DESCRIPTION

[0023] The application will be described in detail below through specific examples, but the protection scope of the application is not limited. Unless otherwise specified, the experimental methods used in the application are conventional methods, and the experimental equipment, materials, reagents, etc. used can be obtained from commercial channels.

[0024] Example 1 The flow battery online SOC measurement and diagnosis method is measured and diagnosed by a flow battery online SOC measurement and diagnosis system. The system structure includes a dynamic compensation OCV algorithm module 5, a UV-Vis measurement module 6, a coulomb counting correction module 8, a battery health monitoring module 7, and a comprehensive dynamic weight module 9. The flow battery stack 1 is provided with a positive electrolyte circulation line 2, a negative electrolyte circulation line 3, and an OCV circulation line 4. Branches are connected to the UV-Vis measurement module 6 on the line from the stack 1 to the positive electrolyte line 2 and the line from the negative electrolyte 3 to the stack 1. Branches are connected to the dynamic compensation OCV algorithm module 5 on the line from the positive electrolyte 2 to the stack 1, the line from the stack 1 to the negative electrolyte 3, the OCV 4, the line from the OCV 4 to the stack 1, and the battery health monitoring module 7. Branches are connected to the battery health monitoring module 7 on the line from the positive electrolyte circulation line 2 to the UV-Vis measurement module 6, the line from the negative electrolyte circulation line 3 to the UV-Vis measurement module 6, and the coulomb counting correction module 8. Branches are connected to the coulomb counting correction module 8 on the line from the positive electrolyte circulation line 2 to the dynamic compensation OCV algorithm module 5, the line from the negative electrolyte circulation line 3 to the dynamic compensation OCV algorithm module 5, and the line from the OCV circulation line 4 to the dynamic compensation OCV algorithm module 5. The dynamic compensation OCV algorithm module 5, the coulomb counting correction module 8, and the battery health monitoring module 7 each have a line connected to the comprehensive dynamic weight module 9.

[0025] 1. Dynamic compensation OCV algorithm module: This module is responsible for collecting the OCV of the stack. It breaks through the limitation of traditional OCV methods that must be measured statically. By real-time acquisition of current change rate, temperature, running time and other parameters, millisecond-level dynamic compensation is achieved. The algorithm can automatically adapt to transient conditions such as charge-discharge switching and load mutation, reducing dynamic error from more than 15% in traditional methods to within 3%.

[0026] 2. UV-Vis measurement module: Through 510nm (V² + / V³) and 650nm (V 4+ / V 5Dual-wavelength absorbance detection, direct access to the electrolyte of each valence state vanadium ion concentration ratio, to achieve the SOC seconds response (≤3s), break through the delay limit of the traditional electrochemical method.

[0027] 3. Coulomb counting correction module: using variable current efficiency coefficient to compensate for the loss of side reactions such as hydrogen evolution and vanadium penetration in real time, and the efficiency value is automatically adjusted with the electrolyte health factor (EHF); The flow rate compensation function is introduced to eliminate the influence of flow fluctuation; Every 4 hours, the integral reference is forced to calibrate by UV-Vis spectrum measurement to avoid error accumulation. At the same time, the total capacity parameter Q_total linearly decays with the number of cycles, accurately reflecting the battery aging. This correction term and dynamic OCV, UV-Vis data form a triple check system, which controls the long-term running error within ±1%, solving the key problem of error accumulation in traditional coulomb counting in flow battery.

[0028] 4. Battery health monitoring module: The main function of this module is to calculate the battery health factor, which directly affects the polarization coefficient and relaxation coefficient, dynamically adjusts the OCV-SOC mapping relationship or replaces the estimated model weight, ensuring that the estimation adapts to the current battery state and improves long-term accuracy and robustness.

[0029] 5. Comprehensive dynamic weight module: This module assigns weights to the SOC calculated by dynamic OCV calculation, UV-Vis monitoring, and coulomb counting correction, and the final SOC obtained takes into account the SOC deviation calculated under various conditions, achieving online accurate monitoring and health diagnosis of SOC.

[0030] Measurement and diagnosis method: By collecting open circuit voltage, current and positive and negative electrode flow rate, dynamic OCV compensation calculation is performed to obtain the size of SOC calculated by compensated OCV , and by collecting the positive and negative flow rates to measure the deviation of the coulomb calculation module, and obtain the size of , and UV-Vis measurement is performed at the same time, the ion concentration ratio in the electrolyte is calculated, and the size of is obtained, wherein the health factor affects the dynamic adjustment coefficients and the size of the dynamic current efficiency coefficient of coulomb calculation , and finally the SOC of the system is calculated by comprehensive weight calculation.

[0031] The specific calculation method of each module is as follows: Dynamic compensation OCV algorithm module: ① Among them: is the compensated open circuit voltage (V); is the measured battery terminal voltage (V); is the polarization compensation coefficient (Ω·s), and the value range is 0.01-0.05; is the current change rate (A / s); is the temperature compensation coefficient (mV / ℃), and the calculation formula is: ② is the real-time electrolyte temperature (℃); is the reference temperature (25℃); is the relaxation compensation coefficient (mV), and the calculation formula is: ③ is the dynamic adjustment mixing degree coefficient, and the calculation formula is: ④ t is the time from the last current mutation (s).

[0032] The final SOC calculation formula is: ⑤ UV-Vis measurement module: ⑥ Coulomb calculation correction module: ⑦ wherein is the initial SOC reference value, which is reset regularly (every 4 hours or when the SOC changes by 5%) by UV-Vis spectrum or dynamic OCV; is the dynamic current efficiency coefficient, which is adjusted according to the electrolyte health state (EHF), and the calculation formula is: ⑧ is the total capacity of the system, and the calibrated value decays with the cycle number: The formula is , and N is the cycle number.

[0033] is the real-time current, 50HZ sampling; is the flow rate compensation function, and the calculation formula is: ⑨ Health factor calculation module: ⑩ EHF ​The comprehensive dynamic weight module: Through the above calculation, the dynamic error of OCV-SOC estimation is reduced from more than 15% in the traditional method to within 3%; the direct spectral analysis of SOC completes the measurement and calculation within 3 seconds, and the SOC error is within ±1%.

[0034] The above-described embodiments are only preferred embodiments of the present application, and not all the embodiments that can be implemented by the present application. Any obvious modifications made by those skilled in the art without departing from the principles and spirit of the present application should be considered within the scope of protection of the claims of the present application.

Claims

1. A flow battery on-line SOC measurement, diagnostic system, characterized in that, The system comprises a dynamic compensation OCV algorithm module, a UV-Vis measurement module, a Coulomb meter correction module, a battery health monitoring module and a comprehensive dynamic weight module. The flow battery stack is provided with a positive electrolyte circulation line, a negative electrolyte circulation line and an OCV circulation line. Branches are connected to the UV-Vis measurement module on the stack to the positive electrolyte line and the negative electrolyte to the stack line. Branches are connected to the dynamic compensation OCV algorithm module on the positive electrolyte to the stack line, the stack to the negative electrolyte line, the OCV, the OCV to the stack line and the battery health monitoring module. Branches are connected to the battery health monitoring module on the positive electrolyte circulation line to the UV-Vis measurement module, the negative electrolyte circulation line to the UV-Vis measurement module and the Coulomb meter correction module. Branches are connected to the Coulomb meter correction module on the positive electrolyte circulation line to the dynamic compensation OCV algorithm module, the negative electrolyte circulation line to the dynamic compensation OCV algorithm module and the OCV circulation line to the dynamic compensation OCV algorithm module. The dynamic compensation OCV algorithm module, the Coulomb meter correction module and the battery health monitoring module are each connected to the comprehensive dynamic weight module.

2. A method for online SOC measurement, diagnosis of a flow battery, characterized in that, The system is measured and diagnosed by using the online SOC measurement and diagnosis system of the flow battery as claimed in claim 1, and the steps are: S1. Collecting the open circuit voltage on the line from OCV to the dynamic compensation OCV algorithm module, the current on the line from the OCV circulation line to the dynamic compensation OCV algorithm module, the positive flow rate on the line from the positive electrolyte circulation line to the dynamic compensation OCV algorithm module and the negative flow rate on the line from the negative electrolyte circulation line to the dynamic compensation OCV algorithm module; S2. Measure V by UV-Vis measurement module for positive electrolyte circulation line 4+ , V 5+ concentration, measure V by UV-Vis measurement module for negative electrolyte circulation line 2+ , V 3+ concentration, calculate ion concentration ratio in electrolyte, obtain the size of electrolyte health state EHF from this ; S3. Perform dynamic OCV compensation calculation by open circuit voltage, current and positive and negative electrode pipeline flow rate collected in step S1, to obtain size; S4. Measure the deviation of the coulomb counting module by the positive and negative flow rates collected in step S1, and obtain the size of this module ; S5. Calculating the SOC of the system by comprehensive weight.

3. The flow battery on-line SOC measurement, diagnostic method of claim 2, wherein, The formula for calculating the electrolyte health state in step S2 is: EHF = wherein, [V 5+ ] is the +5 valence vanadium ion concentration, unit is mol / L, [V 4+ ] is the +5 valence vanadium ion concentration, unit is mol / L, [V 2+ ] is the +5 valence vanadium ion concentration, unit is mol / L, [V 3+ ] is the +5 valence vanadium ion concentration, unit is mol / L, and EHF is the electrolyte health state, which is calculated by the battery health monitoring module.

4. The flow battery on-line SOC measurement, diagnostic method of claim 2, wherein, The formula for calculating in step S2 is: wherein [V 5+ ] is the concentration of vanadium ions in the +5 valence state, in mol / L, [V 4+ ] is the concentration of vanadium ions in the +5 valence state, in mol / L, [V 2+ ] is the concentration of vanadium ions in the +5 valence state, in mol / L, [V 3+ ] is the concentration of vanadium ions in the +5 valence state, in mol / L, [V total ] is the total concentration of vanadium ions, in mol / L.

5. The flow battery on-line SOC measurement, diagnostic method of claim 2, wherein, The specific formula for calculating in step S3 is: Wherein: is the compensated open-circuit voltage, unit is V; is the measured battery terminal voltage, unit is V; is the polarization compensation coefficient, unit is Ω·s, the value range is 0.01-0.05; is the current change rate, A / s; is the temperature compensation coefficient, unit is mV / ℃, the calculation formula is: is the real-time electrolyte temperature, in °C; is the reference temperature, in 25 °C; is the relaxation compensation coefficient, in mV, calculated by the formula: To dynamically adjust the mixing degree coefficient, the calculation formula is: t is the time from the last current mutation, and the unit is s; The final SOC calculation formula is: 。 6. The flow battery on-line SOC measurement, diagnostic method of claim 2, wherein, The formula for calculating in step S4 is: wherein is the initial SOC reference value, reset periodically from UV-Vis spectrum or dynamic OCV; is the dynamic current efficiency coefficient, adjusted according to electrolyte health status (EHF), calculated as: The total capacity of the system, the calibration value decays with the number of cycles: The formula is N is the number of cycles; For real-time current, 50HZ sampling; For the flow rate compensation function, the calculation formula is: 。 7. The flow battery on-line SOC measurement, diagnostic method of claim 6, wherein, The Reset by UV-Vis spectrum or dynamic OCV periodically, reset reference is every 4 hours or SOC change 5%.

8. The flow battery online SOC measurement, diagnostic method of claim 2, wherein, The formula for calculating in step S5 is: 。 9. The flow battery online SOC measurement, diagnostic method of claim 2, wherein, The UV-Vis measurement module detects the absorbance at 510 nm and 650 nm in step S2.

10. The flow battery on-line SOC measurement, diagnostic method of claim 9, wherein, Where 510 nm wavelength absorbance is measured V 2+ , V 3+ Concentration, 650 nm wavelength absorbance is measured V 4+ , V 5+ Concentration.

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