Method and system for predicting service life of noble metal catalyst, optimization method and application

Abstract

The invention provides a noble metal catalyst life prediction method and system, an optimization method and application, and the method comprises the following steps: intrinsic kinetics testing: determining reaction conditions and evaluation indexes, screening a steam reforming-methanol decomposition double-rate model in a methanol steam reforming reaction, and taking a methanol reaction rate as an activity attenuation evaluation index; performing continuous operation test: determining that the noble metal catalyst has long-term stability according to a continuous operation test result, and performing further regular start-stop durability test; regular start-stop durability test: correcting the initial model by monitoring the position change of a reforming cold point of a catalyst bed, establishing an axial-reaction time coupling model, and predicting the service life of the catalyst; the core problems of insufficient precision, neglect of axial inactivation, lack of multi-mechanism coupling analysis and the like of a traditional method under a dynamic working condition are solved, a high-precision life prediction tool is provided for industrial application of a noble metal catalyst, and the method is particularly suitable for distributed hydrogen production industrial application scenes with frequent start and stop.

Description

A method, system, optimization method, and application for predicting the lifetime of a noble metal catalyst. Technical Field

[0001] This invention relates to the field of catalyst technology, and specifically to a method, system, optimization method, and application for predicting the lifetime of noble metal catalysts. Background Technology

[0002] Noble metal catalysts (such as Pt-based catalysts) are highly efficient and irreplaceable in energy conversion processes such as methanol steam reforming for hydrogen production. However, due to their high cost and the fact that their lifespan is affected by various factors, accurately predicting catalyst lifespan has become a key challenge for industrial applications. Existing technologies have the following limitations: 1. Insufficiency of traditional lifespan prediction methods: Static model dominance: Existing methods are mostly based on intrinsic kinetic tests under fixed operating conditions (such as reaction rate monitoring under isothermal and isobaric conditions), which cannot reflect the dynamic changes in actual industrial scenarios (such as frequent start-stop and temperature fluctuations), resulting in significant prediction bias (errors can reach 30%-50%).

[0003] Axial deactivation is neglected: There is a temperature gradient in the catalyst bed in industrial reactors, but traditional models assume that deactivation is uniformly distributed and do not consider the dynamic impact of reforming cold point migration on the activity distribution, resulting in the prediction results being out of sync with the actual operating conditions.

[0004] 2. Unique Challenges of Methanol Steam Reforming Catalysts: Dynamic Stress from Frequent Start-up and Shutdown: In distributed hydrogen production scenarios, catalysts must withstand periodic start-up and shutdown (e.g., every 8 hours), leading to localized overheating or migration of reforming cold spots, accelerating carbon deposition and sintering. Deactivation caused by short-duration high-temperature sintering, poisons introduced into the system, and abrupt catalyst pulverization / coating peeling exhibits no clear pattern. Therefore, deactivation caused by carbon deposition has attracted researchers' attention.

[0005] Interference from complex reaction networks: Methanol reforming involves multiple competing reactions such as steam reforming (SR), decomposition reaction (DE), and water-gas shift (WGS). Traditional models distort the activity evaluation index because they ignore the non-independence of WGS (the measured CO content is higher than the equilibrium value).

[0006] 3. The shortcomings of existing solutions are the lack of axial-time coupling analysis: the migration of reforming cold points reflects the dynamic decay of the catalyst active layer, but existing technologies do not correlate it with the cumulative reaction time, and cannot accurately predict the evolution of the effective catalyst amount over time.

[0007] The above background information is disclosed only to assist in understanding the inventive concept and technical solution of this invention. It does not necessarily belong to the prior art of this patent application, nor does it necessarily provide technical teachings. In the absence of clear evidence, the novelty and inventiveness of the above application shall be deemed to be incomplete. Summary of the Invention

[0008] To address the aforementioned technical problems, this invention proposes a method, system, optimization method, and application for predicting the lifetime of precious metal catalysts. This application solves the core problems of traditional methods, such as insufficient accuracy under dynamic operating conditions, neglect of axial deactivation, and lack of multi-mechanism coupling analysis, by using a dual-rate model screening (excluding interference from water-gas shift reaction) and axial correction of reforming cold point (dynamically correlating effective catalyst amount with reaction time). This provides a high-precision lifetime prediction tool for the industrial application of precious metal catalysts, and is especially suitable for distributed hydrogen production industrial application scenarios with frequent start-stop cycles.

[0009] To achieve the above objectives, the technical solution of the present invention is as follows: On one hand, the present invention provides a method for predicting the lifetime of a noble metal catalyst, comprising the following steps: Intrinsic kinetic testing: determining reaction conditions and evaluation indicators, screening a dual-rate model of steam reforming-methanol decomposition in methanol steam reforming reaction, and using the methanol reaction rate as an evaluation indicator of activity decay; Continuous operation testing: determining the long-term stability of the noble metal catalyst based on the results of continuous operation testing, for further regular start-stop durability testing; Regular start-stop durability testing: by monitoring the change in the reforming cold point position of the catalyst bed, correcting the initial model, establishing an axial-reaction time coupling model, and predicting the catalyst lifetime.

[0010] This invention proposes a method, system, optimization method, and application for predicting the lifetime of precious metal catalysts. By using a dual-rate model screening (excluding interference from water-gas shift reaction) and axial correction of the reforming cold point (dynamically correlating the effective catalyst amount with the reaction time), it solves the core problems of traditional methods, such as insufficient accuracy under dynamic operating conditions, neglect of axial deactivation, and lack of multi-mechanism coupling analysis. It provides a high-precision lifetime prediction tool for the industrial application of precious metal catalysts, and is especially suitable for distributed hydrogen production industrial application scenarios with frequent start-stop cycles.

[0011] As a preferred technical solution, the axial-reaction time coupling model corrects the effective catalyst usage using reforming cold point migration data, and the expression of the axial-reaction time coupling model is as follows: Where z is the distance from the reforming cold point of the catalyst bed to the reactor inlet, t is the cumulative reaction time (proportional to the number of start-ups and shutdowns), in hours; z0 is the initial effective height of the catalyst bed, in centimeters; W cat,0 The catalyst loading mass is expressed in kg; F R0 X is the feed flow rate of reactant R, in kg / h; R (t,z) represents the methanol conversion rate, in %; z(t) is the expression for the migration of the reforming cold point location with the cumulative reaction time or the number of start-stop cycles, obtained by fitting the measured distance to the cumulative reaction time t.

[0012] As a preferred technical solution, the lifetime prediction adopts a power-law decay model, the expression of which is: Where A and B are fitting parameters, and t is the cumulative reaction time.

[0013] As a preferred technical solution, in the regular start-stop durability test, the start-stop frequency is once every 8 hours.

[0014] As a preferred technical solution, the reaction conditions in the intrinsic kinetic test are as follows: reaction pressure is atmospheric pressure, reaction temperature is 325-375℃, water-carbon molar ratio of water vapor to carbon in methanol is 1-2, and mass hourly space velocity (WHSV) is 3-16 h⁻¹. -1 .

[0015] As a preferred technical solution, the noble metal catalyst is a platinum-based noble metal component type catalyst.

[0016] On the other hand, the present invention provides a lifetime prediction system for precious metal catalysts, comprising: a data acquisition module for acquiring actual feed volume data, catalyst bed temperature data, condensate mass and concentration data, reforming dry gas flow rate data, and composition determination and analysis and concentration data; a reactor module for receiving partial catalyst bed temperature data fed back from the data acquisition module and adjusting the heating strategy in real time for performing intrinsic kinetic tests, continuous operation tests, and regular start-stop durability tests; and a model calculation module for receiving the acquired catalyst bed temperature data, condensate concentration data, reforming dry gas flow rate data, and composition determination and analysis concentration data to calculate the cold spot migration location, methanol conversion rate, and actual feed flow rate, and generating lifetime prediction results based on the lifetime prediction method for precious metal catalysts as described above.

[0017] As a preferred technical solution, the model calculation module supports the fitting comparison and judgment of the exponential decay model and the power-law decay model, and selects the power-law decay model as the lifetime prediction model of the catalyst under the condition of activity decay caused by carbon deposition.

[0018] On the other hand, the present invention provides an optimization method for a precious metal catalyst, based on the results of the precious metal catalyst lifetime prediction method as described in any of the preceding claims, including: determining the initial stage of use, avoiding frequent start-ups and shutdowns during the initial stage of use to slow down activity decay; determining the stable period, being able to introduce an oxygen mixture during the stable period to remove carbon deposits and achieve partial regeneration; and optimizing any one or more of the following: reactor inlet design, catalyst inlet arrangement, and temperature control feedback conditions.

[0019] Furthermore, the optimization method for noble metal catalysts described above is applied in a distributed methanol hydrogen production system.

[0020] This invention provides a method, system, optimization method, and application for predicting the lifetime of precious metal catalysts, which has the following beneficial effects: This application solves the core problems of traditional methods such as insufficient accuracy under dynamic operating conditions, neglect of axial deactivation, and lack of multi-mechanism coupling analysis by screening with a dual-rate model (excluding interference from water-gas shift reaction) and axial correction of reforming cold point (dynamically correlated with effective catalyst amount and reaction time). It provides a high-precision lifetime prediction tool for the industrial application of precious metal catalysts, and is especially suitable for distributed hydrogen production industrial application scenarios with frequent start-stop. Attached Figure Description

[0021] Figure 1 shows the results of continuous operation testing of the noble metal catalyst provided by the present invention; Figure 2 shows the direct fitting of reaction rate-time / number of start-stop cycles in the regular start-stop durability test provided by the present invention - Model I - exponential decay model; Figure 3 shows the direct fitting of reaction rate-time / number of start-stop cycles in the regular start-stop durability test provided by the present invention - Model I - power-law decay model; Figure 4 shows the fitting of reaction rate-time / number of start-stop cycles after reforming cold point correction in the regular start-stop durability test provided by the present invention - Model II - exponential decay model; Figure 5 shows the fitting of reaction rate-time / number of start-stop cycles after reforming cold point correction in the regular start-stop durability test provided by the present invention - Model II - power-law decay model. Detailed Implementation

[0022] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0023] This invention provides a method for predicting the lifetime of noble metal catalysts, comprising the following steps: Intrinsic kinetic testing: determining reaction conditions and evaluation indicators, screening a dual-rate model of steam reforming-methanol decomposition in methanol steam reforming reaction, and using the methanol reaction rate as an evaluation indicator of activity decay; Continuous operation testing: determining the long-term stability of the noble metal catalyst based on the results of continuous operation testing, for further regular start-stop durability testing; Regular start-stop durability testing: modifying the initial model by monitoring the change in the reforming cold point position of the catalyst bed, establishing an axial-reaction time coupling model, and predicting the catalyst lifetime.

[0024] This invention proposes a method, system, optimization method, and application for predicting the lifetime of precious metal catalysts. This application solves the core problems of traditional methods, such as insufficient accuracy under dynamic operating conditions, neglect of axial deactivation, and lack of multi-mechanism coupling analysis, by screening with a dual-rate model (excluding interference from water-gas shift reaction) and correcting the reforming cold point axially (dynamically correlating the effective catalyst amount with the reaction time). It provides a high-precision lifetime prediction tool for the industrial application of precious metal catalysts, and is especially suitable for distributed hydrogen production industrial application scenarios with frequent start-stop cycles.

[0025] In the regular start-stop durability test, regular frequent start-stop (start-stop once every 8 hours, so the total test duration t: number of start-stops = 8) was introduced on the basis of long-term continuous operation to modify the model and verify the effects of the reforming cold point shift and the cumulative time of methanol reaction on the methanol reaction rate during the test.

[0026] The methanol reaction rate is used as an indicator of catalyst activity, while catalyst lifetime is usually determined by activity decay. The lowest temperature point inside the reaction tube is the reforming cold point (Note: After excluding other causes of catalyst deactivation, catalyst deactivation due to carbon buildup generally starts from the reactor inlet and gradually moves towards the outlet. In the initial stage of the reaction, because the reactant concentration is highest at the inlet, it is the main region of the reforming reaction, with the fastest reaction rate and the largest heat absorption. Even with dual heating methods of external heating and internal high-temperature reactant steam heating, the effect of heat transfer lagging behind the reaction rate cannot be overcome, resulting in a "cold point" at the catalyst bed inlet; as the reaction time increases, the catalyst at the inlet of the reaction tube becomes less active, leading to a decrease in activity. As the catalyst's activity decreases and insufficient reaction occurs at the inlet, the reforming reaction zone gradually shifts backward to maintain conversion. The cold spot follows suit, moving towards the reaction tube outlet. Monitoring the location of the "cold spot" in the catalyst bed during testing helps determine the main reaction area (i.e., the active region). The movement speed and location changes of the cold spot reflect changes in catalyst activity. Therefore, an axial-reaction-time coupling model was established between the methanol reaction rate and the cumulative reaction time (proportional to the number of start-stop cycles). This model predicts the catalyst's lifetime under these operating conditions, providing a theoretical basis for optimizing the use and predicting the lifetime of distributed hydrogen production catalysts.

[0027] Preferably, the axial-reaction-time coupling model corrects the effective catalyst usage using reforming cold point migration data, and the expression for the axial-reaction-time coupling model is: Where z is the distance from the reforming cold point of the catalyst bed to the reactor inlet, t is the cumulative reaction time (proportional to the number of start-ups and shutdowns), in hours; z0 is the initial effective height of the catalyst bed, in centimeters; W cat,0 The catalyst loading mass is expressed in kg; F R0 X is the feed flow rate of reactant R, in kg / h; R (t,z) represents the methanol conversion rate, in %; z(t) is the expression for the migration of the reforming cold point location with the cumulative reaction time or the number of start-stop cycles, obtained by fitting the measured distance to the cumulative reaction time t.

[0028] Preferably, the lifetime prediction employs a power-law decay model, the expression of which is: Where A and B are fitting parameters, and t is the cumulative reaction time.

[0029] Preferably, in the regular start-stop durability test, the start-stop frequency is once every 8 hours.

[0030] Preferably, in the intrinsic kinetic test, the reaction conditions are: atmospheric pressure, reaction temperature of 325–375°C, water-to-carbon molar ratio of water vapor to carbon in methanol of 1–2, and WHSV of 3–16 h⁻¹. -1 In the continuous operation test and the regular start-stop endurance test, the mass air velocity (WHSV) is preferably 4 hours. -1 8h -1 12h -1 16h -1 Due to space limitations and for the sake of brevity, this invention will not exhaustively list all the specific values ​​included in the scope of protection; the molar ratio of carbon in the water vapor and methanol is preferably 1, 1.3, 1.5 or 1.7. Due to space limitations and for the sake of brevity, this invention will not exhaustively list all the specific values ​​included in the scope of protection.

[0031] Preferably, the noble metal catalyst is a platinum-based noble metal component catalyst.

[0032] On the other hand, the present invention provides a catalyst lifetime prediction system, comprising: a data acquisition module for acquiring actual feed volume data, catalyst bed temperature data, condensate mass and concentration data, reforming dry gas flow rate data, and composition determination and analysis and concentration data; a reactor module for receiving partial catalyst bed temperature data fed back from the data acquisition module and adjusting the heating strategy in real time for performing intrinsic kinetic tests, continuous operation tests, and regular start-stop durability tests; and a model calculation module for receiving the acquired catalyst bed temperature data, condensate concentration data, reforming dry gas flow rate data, and composition determination and analysis concentration data to calculate the cold spot migration location, methanol conversion rate, and actual feed flow rate, and generating lifetime prediction results based on the lifetime prediction method for precious metal catalysts as described in any of the preceding claims.

[0033] On the other hand, the present invention provides a catalyst optimization method based on the results of the precious metal catalyst lifetime prediction method as described in any of the preceding claims, including: determining the initial stage of use, avoiding frequent start-ups and shutdowns during the initial stage of use to slow down activity decay; determining the stable period, being able to introduce an oxygen mixture during the stable period to remove carbon deposits and achieve partial regeneration; and optimizing any one or more of the following: reactor inlet design, catalyst inlet arrangement, and temperature control feedback conditions.

[0034] Furthermore, the catalyst optimization method described above is applied to a distributed methanol hydrogen production system.

[0035] Example 1: This invention provides a method for predicting the lifetime of noble metal catalysts, comprising the following steps: Intrinsic kinetic testing: determining reaction conditions and evaluation indicators, screening a dual-rate model of steam reforming-methanol decomposition in methanol steam reforming reaction, and using the methanol reaction rate as the evaluation indicator for activity decay. Specifically, the method includes the following steps: The testing device is a tubular fixed-bed reactor with an inner diameter equivalent to the outer diameter of the component-type catalyst, with the outlet connected to the atmosphere for direct exhaust, no back pressure, and an atmospheric pressure system. After eliminating the influence of the device on the reaction and further eliminating the influence of internal and external diffusion, the feed flow rate and reaction temperature are adjusted to determine suitable reaction conditions. The final reaction conditions for long-term continuous testing are: reaction pressure at atmospheric pressure, reaction temperature at 350±25℃, molar ratio of water vapor to carbon in methanol (S / C) of 1.5, and mass hourly space velocity (WHSV) of 3–16 h⁻¹. -1 Methanol steam reforming is generally considered to involve the following reactions: SR DE WGS At a given reaction temperature, as the mass hourly space velocity (MHSV) increases, the methanol conversion rate gradually decreases, the CO content in the product gas gradually increases, and the hydrogen production rate gradually increases.

[0036] During continuous operation testing, when the molar ratio of carbon in water vapor to methanol (S / C) was 1.5, the reaction temperature was 325-375℃, and the WHSV was 8.42h. -1 When comparing the CO content in the product with the CO content at the water-gas shift (WGS) equilibrium at the given temperature, the measured CO content in the reaction product (3.33%-4.82% as shown in Figure 1) is higher than the calculated value (1.25%-1.54%), indicating that the water-gas shift (WGS) is not suitable as an independent reaction in the reaction model. Therefore, the methanol steam reforming (SR)-methanol decomposition (DE) dual-rate model adopted in this application is established.

[0037] Meanwhile, intrinsic kinetic test results show that CO selectivity increases with increasing temperature, indicating that methanol decomposition (DE) occurs preferentially over steam reforming (SR) with increasing temperature.

[0038] In summary, the actual reactions involve simultaneous steam reforming (SR) and methanol decomposition (DE), while water-gas shift (WGS) is not considered an independent reaction. Since both SR and DE use methanol as a reactant, the methanol reaction rate is used as the evaluation index for catalyst activity change (lifetime).

[0039] Continuous run test: As shown in Figure 1, WHSV=8.42h -1At 350±25℃, the reaction was conducted continuously for 200 hours. During the test, there was no significant migration of the catalyst bed cold point, and the performance indicators of the catalytic reaction, including methanol conversion rate, CO content in the product gas, and hydrogen production rate, remained relatively stable. The long-term continuous operation test results indicate that the catalyst has good continuous reaction activity and long-term stability, making it suitable for regular start-stop durability testing. Regular start-stop durability test: WHSV = 7.5±0.3h -1 Durability experiments were conducted at 350±25℃ with regular start-up and shutdown. By monitoring changes in the reforming cold point of the catalyst bed, the initial model was revised, and an axial-reaction-time coupled model was established to predict catalyst lifetime. This included the following steps: Assuming the reaction system was in a quasi-steady state during sampling analysis, the macroscopic average reaction rate equation for the fixed-bed reactor, based on catalyst mass, was given as follows: in, The mass of the catalyst is expressed in kg. Let R be the consumption rate of reactant R, expressed in kg / h; the relationship between conversion rate and consumption rate is as follows: in, The feed flow rate of reactant R is expressed in kg / h. Let R be the flow rate of reactant R at the outlet, in kg / h. From this, the formula for calculating the methanol reaction rate under each quasi-steady state is obtained: (1) As the running time increases, the reaction rate of reactant R gradually decreases, and the cold point gradually shifts towards the outlet, indicating that the actual effective catalyst amount gradually decreases. To correct for the effective catalyst usage, an axial-reaction time coupling model is established: Where z is the distance from the cold point of the catalyst bed to the reactor inlet, t is the cumulative reaction time (proportional to the number of start-ups and shutdowns) in hours; z0 is the initial effective height of the catalyst bed in centimeters; W cat,0 The catalyst loading mass is expressed in kg; F R0 X is the feed flow rate of reactant R, in kg / h; R (t,z) represents the methanol conversion rate, in %; obtained by fitting the cumulative reaction time t with data returned from the real-time temperature monitoring thermocouple indicating the cold point location. In summary, (2).

[0040] As shown in Figures 2 and 3, the methanol reaction rate at each test point of the regular start-stop durability test was calculated according to the above formula (1) - Model I. The methanol reaction rate was plotted against the cumulative reaction time during the test (the algorithm is LM method) to obtain the mathematical function relationship between the two. In order to confirm the decay mode, two commonly used models were compared: the exponential decay model and the power law decay model. The fitting results of the reaction rate-time / number of start-stops direct fitting-Model I-exponential decay model in the regular start-stop durability test are shown in Figure 2. The fitting results of the reaction rate-time / number of start-stops direct fitting-Model I-power law decay model in the regular start-stop durability test are shown in Figure 3. As can be seen from Figures 2 and 3, as the cumulative reaction time increases (i.e., the number of regular start-stops increases), when the methanol reaction rate calculated by the above formula (1) is fitted against the cumulative reaction time, the fitting degree (R2) of the two decay models using the LM (least squares) algorithm is not high. The exponential decay model is 0.310 and the power law decay model is 0.303, indicating that the model does not conform to the actual working conditions.

[0041] It is worth noting that when using ODR (orthogonal regression algorithm), the goodness of fit for both decay models is 1, which may indicate overfitting. Considering that LM only considers the error of the dependent variable, while ODR considers the errors of both the independent and dependent variables, this indirectly suggests that regardless of which decay model is used, the methanol reaction rate, the dependent variable, is not only affected by the cumulative reaction time (regular start-stop) of the independent variable, but also requires further correction of the independent variable in Model I.

[0042] As shown in Figures 4 and 5, the methanol reaction rate at each test point during the start-up and shutdown durability test was calculated according to the above formula (2) - Model II. The process is as follows: The data of the change in the position of the reforming cold point with reaction time were fitted to obtain: Substitute into formula (2) above to calculate the reaction rate at each point: Where z is the distance from the cold point of the catalyst bed to the reactor inlet, t is the cumulative reaction time (proportional to the number of start-ups and shutdowns), in hours; z0 is the initial effective height of the catalyst bed, in centimeters; W cat,0 The catalyst loading mass is expressed in kg; F R0 X is the feed flow rate of reactant R, in kg / h; R(t, z) represents the methanol conversion rate, expressed as %; a mathematical function relationship between the reaction rate and the cumulative reaction time during the test was obtained by plotting the reaction rate against the cumulative reaction time (LM method for all algorithms). To confirm the decay mode, the fitting results of exponential decay and power-law decay were compared. Figure 4 shows the results of the reaction rate-time / number of start-stop cycles fitting model II-exponential decay model after cold point correction in the regular start-stop durability test, and Figure 5 shows the results of the reaction rate-time / number of start-stop cycles fitting model II-power-law decay model after reforming cold point correction in the regular start-stop durability test.

[0043] As shown in Figures 4 and 5, with the increase of the cumulative reaction time (i.e., the increase of the number of regular start-stop cycles), the methanol reaction rate calculated using the above formula (2) is fitted to the cumulative reaction time, and the power-law model is: The exponential model is as follows: Based on a comprehensive assessment of the correlation and fit between the fitted curve and the actual curve, the power-law model is deemed effective and can be used as a lifetime prediction model for catalysts under carbon deposition conditions. This aligns with the fact that the power-law model is more suitable for the degradation caused by carbon deposition.

[0044] The precious metal catalyst lifetime prediction method provided by this invention is directly used to predict the catalyst's usable time data, as shown in Table 1 below: Table 1 Predicting the precious metal catalyst lifetime of this invention is directly used to predict the catalyst's usable time data On the other hand, the present invention provides an optimization method for a precious metal catalyst, based on the results of the precious metal catalyst lifetime prediction method as described in any of the preceding claims, including: determining the initial stage of use and avoiding frequent start-ups and shutdowns during the initial stage of use to slow down the activity decay; determining the stable period and being able to introduce an oxygen mixture during the stable period to remove carbon deposits and achieve partial regeneration; and optimizing any one or more of the following: reactor inlet design, catalyst inlet arrangement, and temperature control feedback conditions.

[0045] Optimizing one or more of the following factors—reactor inlet design, catalyst inlet arrangement, and temperature control feedback conditions—includes ensuring that the performance indicators (methanol conversion rate, CO content in product gas, hydrogen production rate) do not change drastically with cumulative reaction time, and that the indicators of the precious metal catalyst change regularly with cumulative time throughout the entire test period. After introducing cold-point correction, both the exponential and power-law models show a significant decline in performance at the beginning of the reaction, followed by a turning point and a stable period where the decline rate slows down. By combining the correlation between the trend lines of the two models and the actual curves, the initial rapid deactivation period and the stable performance period of the catalyst can be determined. Meanwhile, it is believed that the initial instability is due to rapid poisoning or sintering leading to rapid activity decay, while the stable period is mainly due to carbon buildup causing activity decay. The rapid deactivation in the early stage of the reaction is due to the fact that the possibility of introducing poisons was fully ruled out during the catalyst preparation and testing system establishment. Analysis of the original experimental data shows that the high catalyst activity and short preheating channel of the reaction gas in the early stage made the temperature control at the inlet unstable, resulting in a vicious cycle of "rapid reaction of high active catalyst at the inlet → local endothermic overheating and over-cooling → feedback temperature control overshoot heating → inlet overheating may lead to partial sintering". This exacerbated the rapid deactivation in the early stage of the reaction. The reactor design, catalyst inlet arrangement or catalyst inlet temperature control feedback conditions can be optimized in subsequent use. The stable period is due to carbon buildup. It is speculated that the catalyst deactivation process under this condition is mainly caused by carbon buildup, accompanied by catalyst deactivation caused by long-term testing and frequent start-stop. This is because, based on a comprehensive analysis of other performance indicators during long-term testing, as carbon deposits increase, CO content increases and methanol conversion rate decreases. It is speculated that, similar to the increased CO selectivity due to rising temperature, when deactivation is primarily caused by carbon deposits, methanol decomposition (DE) occurs preferentially over steam reforming (SR). Furthermore, carbon deposits randomly cover active sites and simultaneously adsorb some reactants, interfering with the reactant composition while further generating carbon deposits.

[0046] To mitigate activity decay during the initial use period, frequent start-stop cycles should be avoided. Table 1 shows that the model indicates catalyst instability during the initial use period. Comparing this with long-term continuous testing results, it is generally believed that initial changes are mainly caused by frequent, regular start-stop cycles. Therefore, frequent start-stop cycles are not suitable for the catalyst during the initial use period. Avoiding frequent start-stop cycles during this stage can improve the rapid initial activity decay. Furthermore, the initial activity decay may be due to frequent start-stop cycles causing preferential deactivation of acidic sites, leading to an exponential decay rate. The preparation and use processes can be optimized.

[0047] Introducing oxygen during the stabilization period to remove carbon deposits and achieve partial regeneration includes: intentionally introducing oxygen during the stabilization period to remove carbon deposits, achieving partial catalyst regeneration, and extending the stabilization period.

[0048] This invention provides a catalyst lifetime prediction system, comprising: a data acquisition module for acquiring actual feed volume data, catalyst bed temperature data, condensate mass and concentration data, reforming dry gas flow rate data, and composition analysis and concentration data; a reactor module for receiving partial catalyst bed temperature data from the data acquisition module and adjusting the heating strategy in real time to perform intrinsic kinetic tests, continuous operation tests, and regular start-stop durability tests; and a model calculation module for receiving the acquired catalyst bed temperature data, condensate concentration data, reforming dry gas flow rate data, and composition analysis and concentration data to calculate the cold spot migration location, methanol conversion rate, and actual feed flow rate, and generating lifetime prediction results based on the lifetime prediction method for precious metal catalysts as described above.

[0049] The method, system, optimization method, and application for predicting the lifetime of precious metal catalysts proposed in this invention solve the core problems of traditional methods, such as insufficient accuracy under dynamic operating conditions, neglect of axial deactivation, and lack of multi-mechanism coupling analysis, through dual-rate model screening (excluding interference from water-gas shift reaction) and axial correction of reforming cold point (dynamically correlated with effective catalyst amount and reaction time). It provides a high-precision lifetime prediction tool for the industrial application of precious metal catalysts, and is especially suitable for distributed hydrogen production industrial application scenarios with frequent start-stop.

[0050] It is understood that this invention has been described through some embodiments, and those skilled in the art will recognize that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of this invention. Furthermore, under the teachings of this invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of this invention. Therefore, this invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are protected by this invention. Furthermore, under the teachings of this invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of this invention. Therefore, this invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the scope of protection of this invention.

Claims

1. A method for predicting the lifetime of a noble metal catalyst, characterized in that, Includes the following steps: Intrinsic kinetics testing: Determine reaction conditions and evaluation indicators, screen a dual-rate model of steam reforming-methanol decomposition in methanol steam reforming reaction, and use methanol reaction rate as the evaluation index of activity decay; Continuous operation testing: Based on the results of continuous operation testing, determine that the noble metal catalyst has long-term stability, and use it for further regular start-stop durability testing; Regular start-stop durability testing: By monitoring the change of reforming cold point position of the catalyst bed, correct the initial model, establish an axial-reaction time coupling model, and predict the catalyst lifetime.

2. The method for predicting the lifetime of a noble metal catalyst according to claim 1, characterized in that, The axial-reaction-time coupling model corrects for the effective catalyst usage using reforming cold point migration data. The expression for the axial-reaction-time coupling model is as follows: Where z is the distance from the reforming cold point of the catalyst bed to the reactor inlet, t is the cumulative reaction time (proportional to the number of start-ups and shutdowns) in hours; z0 is the initial effective height of the catalyst bed in centimeters; W cat,0 The catalyst loading mass is expressed in kg; F R0 X is the feed flow rate of reactant R, in kg / h; R (t,z) represents the methanol conversion rate in %; z(t) is the expression for the migration of the reforming cold point location with the cumulative reaction time or the number of start-stop cycles, obtained by fitting the measured distance to the cumulative reaction time t.

3. The method for predicting the lifetime of a noble metal catalyst according to claim 1, characterized in that, The lifetime prediction employs a power-law decay model, the expression of which is: Where A and B are fitting parameters, and t is the cumulative reaction time.

4. The method for predicting the lifetime of a noble metal catalyst according to claim 3, characterized in that, In the aforementioned start-stop durability test, the start-stop frequency was once every 8 hours.

5. The method for predicting the lifetime of a noble metal catalyst according to claim 1, characterized in that, In the intrinsic kinetics test, the reaction conditions were: atmospheric pressure, reaction temperature of 325–375 °C, water-to-carbon molar ratio of water vapor to carbon in methanol of 1–2, and WHSV of 3–16 h⁻¹. -1 .

6. The method for predicting the lifetime of a noble metal catalyst according to claim 1, characterized in that, The noble metal catalyst is a platinum-based noble metal component type catalyst.

7. A lifetime prediction system for a noble metal catalyst, characterized in that, include: The data acquisition module collects actual liquid inflow data, catalyst bed temperature data, condensate mass and concentration data, reforming dry gas flow rate data, and composition analysis and concentration data; the reactor module receives partial catalyst bed temperature data fed back from the data acquisition module and adjusts the heating strategy in real time for intrinsic kinetic testing, continuous operation testing, and regular start-stop durability testing. The model calculation module receives and collects catalyst bed temperature data, condensate concentration data, reforming dry gas flow rate data, and composition determination and analysis concentration data to calculate the cold point migration location, methanol conversion rate, and actual feed flow rate, and generates lifetime prediction results based on the lifetime prediction method for noble metal catalysts according to any one of claims 1-6.

8. The lifetime prediction system for noble metal catalysts according to claim 7, characterized in that, The model calculation module supports the fitting comparison and judgment of the exponential decay model and the power-law decay model, and selects the power-law decay model as the lifetime prediction model of the catalyst under the condition of activity decay caused by carbon deposition.

9. A method for optimizing a noble metal catalyst, characterized in that, Based on the results of the precious metal catalyst lifetime prediction method according to any one of claims 1-6, the method includes: determining the initial stage of use, avoiding frequent start-ups and shutdowns during the initial stage of use to slow down the activity decay; determining the stable period, being able to introduce an oxygen mixture during the stable period to remove carbon deposits and achieve partial regeneration; and optimizing any one or more of the reactor inlet design, catalyst inlet arrangement, and temperature control feedback conditions.

10. The application of the optimization method of the noble metal catalyst according to claim 9 in a distributed methanol hydrogen production system.

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