Cathode inlet temperature and humidity cooperative control method for dual-module intercooler type fuel cell

Abstract

The invention relates to a dual-module intercooler type fuel cell cathode inlet temperature and humidity cooperative control method. The method comprises the steps that fuel cell cathode air inlet real-time state parameters and operation parameters are obtained, a multivariable coupling prediction model is constructed after preprocessing, and a temperature and humidity reference and an oxygen stoichiometric ratio target reference are set in combination with heat exchange characteristics of a dual-module intercooler; then the core body heat exchange distribution proportion is regulated and controlled, humidification adjustment is matched, and the core body heat exchange distribution proportion and the humidification adjustment intensity are dynamically adjusted according to the real-time working condition; comparing the deviation between the adjusted actual temperature and humidity and the target temperature and humidity reference, and correcting the heat exchange distribution proportion and the humidifying adjustment parameter through a dynamic constraint correction model; cooperative regulation and control of cathode inlet temperature and humidity are realized, dynamic change of working conditions is adapted, and stable operation of the fuel cell is guaranteed.

Description

Technical Field

[0001] This invention belongs to the field of fuel cell system control technology, specifically relating to a method for coordinated control of cathode inlet temperature and humidity in a dual-module intercooler fuel cell. Background Technology

[0002] The PEMFC cathode air supply subsystem has a decisive impact on the performance and lifespan of the fuel cell stack. Its core control objective is to provide the fuel cell cathode with intake air of suitable pressure, temperature, humidity, flow rate, and oxygen concentration according to different power requirements. However, these parameters are subject to complex coupling relationships: the air compressor speed directly affects flow rate and pressure, and its compression process significantly increases air temperature; the intercooler regulates temperature but alters relative humidity and introduces pressure drop; the humidifier increases humidity, but its effectiveness is affected by inlet temperature and flow rate. Traditional control schemes typically use single-input, single-output PID control loops to regulate the air compressor, intercooler cooling valve, and humidifier separately, which struggles to handle multivariable coupling and dynamic constraints, leading to slow system response, overshoot, oscillation, and even slow temperature rise during cold starts or flooding or membrane drying under varying loads.

[0003] In existing technologies, to improve cold-start performance, some solutions employ fuel cell stack bypass or intercooler bypass to reduce heat dissipation. However, bypass air is typically unhumidified, potentially leading to humidity control imbalances. Other solutions utilize complex segmented heating strategies, but these are energy-intensive and require complex control. Humidity control largely relies on humidifiers or cathode recirculation, lacking a coordinated mechanism with temperature regulation. Therefore, there is an urgent need for an integrated solution that provides greater flexibility in hardware architecture and achieves multi-objective collaborative optimization at the control algorithm level. Summary of the Invention

[0004] To address the aforementioned problems in the prior art, this invention provides a method for coordinated control of cathode inlet temperature and humidity in a dual-module intercooler fuel cell. The objective of this invention can be achieved through the following technical solution: A method for coordinated control of cathode inlet temperature and humidity in a dual-module intercooler fuel cell, comprising: S1: Obtain the real-time status parameters of the fuel cell cathode air intake and the operating parameters of the fuel cell, perform preprocessing on the parameters, generate a parameter dataset, construct a multivariate coupled prediction model, and set the target temperature and humidity benchmark and oxygen stoichiometric ratio target for the fuel cell cathode air intake by combining the heat exchange characteristics of the dual-module intercooler. S2: Based on the target temperature and humidity benchmark, and combined with the output results of the multivariate coupled prediction model, adjust the core heat exchange distribution ratio of the dual-module intercooler, and simultaneously coordinate with the humidification adjustment operation of the fuel cell cathode air intake. S3: Monitor the real-time operating conditions of the fuel cell, and dynamically adjust the heat exchange regulation range of the dual-module intercooler based on the monitoring results, while correspondingly changing the intensity of cathode intake humidification regulation. S4: Obtain the actual temperature and humidity parameters of the intake air entering the cathode of the fuel cell after adjustment, compare the deviation of the actual temperature and humidity parameters with the target temperature and humidity benchmark, construct a dynamic constraint correction model, and correct the core heat exchange distribution ratio of the dual-module intercooler and the humidification adjustment parameters of the cathode intake air based on the temperature and humidity deviation value generated by the comparison.

[0005] Specifically, the preprocessing of the parameters is as follows: the real-time status parameters and the running parameters are dimensionally normalized to unify the representation of the parameters; redundancy removal is performed on the parameters to eliminate duplicate feature information; the normalized parameters are smoothed and then normalized to generate the parameter dataset.

[0006] Specifically, the process of constructing the multivariate coupled prediction model is as follows: based on the parameter dataset, combined with the differences in heat transfer characteristics between the main and auxiliary cores of the dual-module intercooler, a mapping relationship between the parameters and the cathode inlet air temperature and humidity output is established to generate an initial prediction model. By continuously acquiring real-time monitoring data of the cathode inlet air and dynamic operating data of the fuel cell, the model parameters are iteratively corrected to generate the multivariate coupled prediction model.

[0007] Specifically, the iterative correction process for the model parameters is as follows: the real-time monitoring data and the dynamic operating data are used as verification samples and input into the initial prediction model to generate temperature and humidity prediction values, which are then compared with the actual temperature and humidity monitoring values ​​of the cathode inlet to calculate the temperature and humidity prediction error value; based on the difference in heat transfer characteristics between the main and auxiliary cores of the dual-module intercooler, and combined with the mapping relationship between the parameters and the temperature and humidity output of the cathode inlet, the associated parameters of the initial prediction model are corrected according to the magnitude and direction of the error value.

[0008] Specifically, the process of setting the target temperature and humidity benchmark and oxygen stoichiometry target for the fuel cell cathode inlet is as follows: based on the parameter dataset and the output results of the multivariate coupled prediction model, the target oxygen stoichiometry value is set according to the current power requirements of the fuel cell stack; combined with the correlation characteristics between temperature and saturated water vapor pressure in the relative humidity calculation formula, the target relative humidity value and the target inlet temperature value for the cathode inlet are set to form the target temperature and humidity benchmark.

[0009] Specifically, the process of adjusting the heat exchange distribution ratio of the core of the dual-module intercooler is as follows: based on the target temperature and humidity benchmark and the output results of the multivariate coupled prediction model, the air intake flow ratio of the main and auxiliary cores is distributed by adjusting the opening of the combination valve. The temperature of the cathode air intake after mixing is controlled by utilizing the difference in characteristics between the strong cooling of the main core and the low heat dissipation of the auxiliary core.

[0010] Specifically, the process of synchronously coordinating the humidification adjustment operation of the fuel cell cathode air intake is as follows: based on the real-time temperature of the cathode air intake after the core heat exchange distribution adjustment, combined with the correlation characteristics between temperature and saturated water vapor pressure in the relative humidity calculation formula, and based on the target temperature and humidity benchmark, the humidification intensity of the humidifier is dynamically adjusted by calculating the water vapor partial pressure difference required for the current air intake.

[0011] Specifically, the process of dynamically adjusting the heat exchange regulation range of the dual-module intercooler is as follows: based on the monitoring results, the opening adjustment range of the combination valve connected to the main and auxiliary cores is adjusted, the adjustment step of the air intake flow ratio of the main and auxiliary cores is changed, and the air intake flow distribution adjustment range of the main and auxiliary cores is increased and decreased.

[0012] Specifically, the process of simultaneously changing the intensity of cathode intake humidification adjustment is as follows: combining real-time operating condition changes, synchronously associating the adjustment of the heat exchange adjustment amplitude of the dual-module intercooler, obtaining the actual temperature and humidity parameters of the cathode intake in real time, comparing them with the target temperature and humidity benchmark, and calculating the current humidity deviation value; dynamically changing the humidification intensity of the humidifier according to the magnitude and trend of the deviation.

[0013] Specifically, the process of constructing the dynamic constraint correction model is as follows: input the temperature and humidity deviation values, based on the parameter dataset, and combining the heat exchange characteristics of the dual-module intercooler and the adjustment characteristics of the humidifier as the basic constraints of the model; set the two-dimensional correction direction of the model, including: core heat exchange distribution ratio correction and humidification adjustment parameter correction; establish a dynamic mapping relationship between deviation characteristics and correction amount by quantitatively analyzing the magnitude and trend of the temperature and humidity deviation values; set the correction amount constraint boundary of the core heat exchange distribution ratio and humidification adjustment parameter in combination with the parameter requirements for stable operation of fuel cell, and limit the adjustment range of the correction operation; integrate and generate the dynamic constraint correction model.

[0014] Specifically, the process of establishing the dynamic mapping relationship between deviation features and correction amounts is as follows: Based on the numerical magnitude, polarity, rate of change, and trend of the temperature and humidity deviation values, combined with the parameter dataset, and simultaneously coupling the heat exchange regulation characteristics of the dual-module intercooler and the humidification regulation characteristics of the humidifier, the temperature deviation and humidity deviation are first subjected to feature extraction and quantification characterization to generate deviation feature indices. Single-dimensional quantitative association rules are then established between the temperature deviation features and the core heat exchange allocation ratio correction amount, and between the humidity deviation features and the humidification regulation parameter correction amount. The basic value standard for the correction amount under the deviation features is set. Combined with the parameter coupling characteristics of temperature and humidity, the single-dimensional quantitative association rules are collaboratively calibrated.

[0015] Specifically, the process of correcting the core heat exchange distribution ratio and the humidification adjustment parameters of the cathode intake air in the dual-module intercooler is as follows: Based on the quantitative correction amount of the core heat exchange distribution ratio and the quantitative correction amount of the humidification adjustment parameters output by the dynamic constraint correction model, and combined with the temperature and humidity deviation characteristics, the parameters are synchronously and in conjunction with each other; based on the core heat exchange distribution ratio and according to the heat exchange distribution ratio correction amount corresponding to the temperature deviation, the opening degree of the corresponding combination valves of the main and auxiliary cores of the dual-module intercooler is adjusted to dynamically adjust the intake flow ratio ratio of the main and auxiliary cores; based on the cathode intake humidification adjustment parameters and according to the humidification adjustment parameter correction amount corresponding to the humidity deviation, and combined with the correlation characteristics between the real-time temperature of the cathode intake air and the saturated water vapor pressure, the humidification adjustment parameters of the humidifier are adjusted.

[0016] The beneficial effects of this invention are: Overcoming the challenges of multivariable coupling and improving control precision: By using hardware decoupling of the dual-module intercooler and a multivariable collaborative control algorithm, the problem of strong coupling between parameters such as cathode inlet temperature, humidity, and flow is effectively solved, avoiding the shortcomings of traditional PID control such as slow response and overshoot, and achieving rapid and accurate tracking of target parameters.

[0017] Optimize cold start performance and solve the core problem: Utilize the low heat dissipation characteristics of the sub-core to rapidly raise the temperature while maintaining basic membrane wetting. At the same time, avoid cathode icing through low relative humidity, solving the problem of "not being able to balance heating and humidification" in traditional solutions, shortening start-up time and reducing energy consumption.

[0018] Strengthen water management capabilities and mitigate risks in both directions: When the water is too wet, increase the proportion of the secondary circuit for rapid dehumidification and eliminate the risk of membrane drying; when the water is too dry, adjust the proportion of the main circuit to increase humidity, dynamically balance the dry and wet state of the membrane electrode, significantly reduce the probability of flooding and membrane drying failures, and extend the life of the fuel cell stack.

[0019] Optimized system structure and energy efficiency: The compact dual-module integrated design reduces flow resistance and installation space; the main core has efficient heat dissipation under high power conditions, and the main and auxiliary circuit ratio is optimized under partial load to reduce air compressor energy consumption, balancing system performance and economy.

[0020] Adaptable to multiple operating conditions and improved robustness: It can dynamically respond to different operating conditions such as cold start and steady-state operation. Through model iteration correction and parameter linkage adjustment, it ensures the optimal operating state under different environments and power requirements, thereby enhancing system adaptability. Attached Figure Description

[0021] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0022] Figure 1 This is a schematic flowchart of the dual-module intercooler fuel cell cathode inlet temperature and humidity coordinated control method of the present invention; Figure 2 This is a structural block diagram of the dual-module intercooler fuel cell cathode inlet temperature and humidity coordinated control method in this invention; Figure 3 This diagram shows the core components of the cathode air intake system for a dual-module intercooler fuel cell. like Figure 3 : 1-Air filter, 2-Air flow meter, 3-Air compressor, 4-Intercooler, 5-Combination valve, 6-Humidifier, 7-Pressure sensor P21, 8-Temperature sensor T21, 9-Ambient temperature sensor. Detailed Implementation

[0023] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0024] Please see Figures 1-3 A method for coordinated control of cathode inlet temperature and humidity in a dual-module intercooler fuel cell includes: S1: Obtain the real-time status parameters of the fuel cell cathode air intake and the operating parameters of the fuel cell, perform preprocessing on the parameters, generate a parameter dataset, construct a multivariate coupled prediction model, and set the target temperature and humidity benchmark and oxygen stoichiometric ratio target for the fuel cell cathode air intake by combining the heat exchange characteristics of the dual-module intercooler. S2: Based on the target temperature and humidity benchmark, and combined with the output results of the multivariate coupled prediction model, adjust the core heat exchange distribution ratio of the dual-module intercooler, and simultaneously coordinate with the humidification adjustment operation of the fuel cell cathode air intake. S3: Monitor the real-time operating conditions of the fuel cell, and dynamically adjust the heat exchange regulation range of the dual-module intercooler based on the monitoring results, while correspondingly changing the intensity of cathode intake humidification regulation. S4: Obtain the actual temperature and humidity parameters of the intake air entering the cathode of the fuel cell after adjustment, compare the deviation of the actual temperature and humidity parameters with the target temperature and humidity benchmark, construct a dynamic constraint correction model, and correct the core heat exchange distribution ratio of the dual-module intercooler and the humidification adjustment parameters of the cathode intake air based on the temperature and humidity deviation value generated by the comparison.

[0025] Specifically, the preprocessing of the parameters is as follows: the real-time status parameters and the running parameters are dimensionally normalized to unify the representation of the parameters; redundancy removal is performed on the parameters to eliminate duplicate feature information; the normalized parameters are smoothed and then normalized to generate the parameter dataset.

[0026] Specifically, the process of constructing the multivariate coupled prediction model is as follows: based on the parameter dataset, combined with the differences in heat transfer characteristics between the main and auxiliary cores of the dual-module intercooler, a mapping relationship between the parameters and the cathode inlet air temperature and humidity output is established to generate an initial prediction model. By continuously acquiring real-time monitoring data of the cathode inlet air and dynamic operating data of the fuel cell, the model parameters are iteratively corrected to generate the multivariate coupled prediction model.

[0027] Specifically, the iterative correction process for the model parameters is as follows: the real-time monitoring data and the dynamic operating data are used as verification samples and input into the initial prediction model to generate temperature and humidity prediction values, which are then compared with the actual temperature and humidity monitoring values ​​of the cathode inlet to calculate the temperature and humidity prediction error value; based on the difference in heat transfer characteristics between the main and auxiliary cores of the dual-module intercooler, and combined with the mapping relationship between the parameters and the temperature and humidity output of the cathode inlet, the associated parameters of the initial prediction model are corrected according to the magnitude and direction of the error value.

[0028] Specifically, the process of setting the target temperature and humidity benchmark and oxygen stoichiometry target for the fuel cell cathode inlet is as follows: based on the parameter dataset and the output results of the multivariate coupled prediction model, the target oxygen stoichiometry value is set according to the current power requirements of the fuel cell stack; combined with the correlation characteristics between temperature and saturated water vapor pressure in the relative humidity calculation formula, the target relative humidity value and the target inlet temperature value for the cathode inlet are set to form the target temperature and humidity benchmark.

[0029] In this embodiment, two types of core parameters are simultaneously collected through the sensing devices and control module of the fuel cell cathode air intake system to ensure data real-time performance and synchronization: Cathode intake real-time status parameters: flow rate a is collected via 2 (air flow meter); pressure b is collected via 7 (pressure sensor); ambient temperature c is collected via 9 (ambient temperature sensor); water vapor partial pressure d is derived via humidity detection correlation module; Fuel cell operating parameters: stack power e is collected through the stack control unit; stack temperature f is collected through the stack built-in temperature detection component; speed g is fed back through 3 (air compressor); current opening h is fed back through 5 (combination valve).

[0030] Parameter preprocessing: Dimensional standardization: The representation forms and units of flow rate (a), pressure (b), ambient temperature (c), and fuel cell temperature (f) are standardized to eliminate dimensional differences and adapt to the calculation requirements of subsequent models. Redundancy removal: Calculate the mutual information value between each parameter and set a threshold k. After detection, the mutual information value between rotational speed g and flow rate a is higher than k, and the variance contribution rate of g is lower than the benchmark m. Remove the feature information corresponding to g, and retain the core features such as a, b, c, d, e, f, and h. Smoothing: A sliding window weighted average mechanism is adopted, and the window length is dynamically adjusted according to the operating conditions. When the operating conditions fluctuate, the number of data points is set to p2, and after the parameters stabilize, it is adjusted to p1 data points (p1>p2). Abnormal values ​​of sudden changes in the parameters after normalization are corrected to eliminate interference noise. Normalization: Using extreme value standardization, the extreme value interval is determined based on the range of each parameter (e.g., the interval for flow rate a is [q, r]). The normalized value is mapped to the set interval using the formula "normalized value = (actual parameter value - minimum parameter value) / (maximum parameter value - minimum parameter value)", and the parameter dataset s is generated.

[0031] Construction of multivariate coupled prediction models: Establish mapping relationships: Based on the parameter dataset s, and combining the characteristic differences between the main core (strong heat transfer and strong cooling capacity) and the secondary core (weak heat transfer and weak cooling capacity) of the 4 (integrated dual-module structure), the core parameters (a, b, c, selection of the main / secondary core of 4) and the related parameters (e, f) are divided; a nonlinear correlation equation is constructed: temperature output = t(a, b, c, main / secondary core of 4, e), humidity output = h(a, d, f, main / secondary core of 4), and the initial prediction model m0 is generated through feature dimensionality reduction; Model Iteration and Correction: Continuously collect real-time monitoring data of cathode air intake (derive actual humidity h_actual by collecting actual temperature t_actual and humidity detection module) and dynamic operation data of fuel cell (stack power change value e_variable and stack temperature change value f_variable), and use them as verification samples to input m0 to generate predicted temperature and humidity values ​​t_predict and h_predict; calculate the comprehensive prediction error e_error. If e_error is higher than the threshold e0 and is a positive deviation (t_predict > t_actual, h_predict > h_actual), then the heat transfer weight coefficient of the four main cores in m0 is reduced; if e_error is higher than e0 and is a negative deviation (t_predict < t_actual, h_predict < h_actual), then the heat transfer weight coefficient of the four auxiliary cores in m0 is increased. After multiple rounds of iteration, a multivariate coupled prediction model m1 is generated.

[0032] Target temperature and humidity baselines and oxygen saturation ratio target settings: Oxygen stoichiometry target value o is set based on the output results of parameter datasets s and m1. The range is divided according to the stack power e. When e is in the low power range, the optimal value range of o is [o1, o2]; when e is in the medium power range, the optimal value range of o is [o3, o4]; when e is in the high power range, the optimal value range of o is [o5, o6]. The oxygen stoichiometry target value o is matched within the corresponding range to ensure that the reactant supply is adapted to the current power demand. Target temperature and humidity baseline (t_target, h_target): Based on the relative humidity calculation formula "RH=d / p_saturated(t)×100%" (d is the partial pressure of water vapor, p_saturated(t) is the saturated water vapor pressure at temperature t), and the optimal temperature and humidity range output by parameter datasets s and m1, the target relative humidity value h_target and the target inlet temperature value t_target are set to meet the requirements of the stack operating temperature and the hydration characteristics of the membrane electrode. The two constitute the target temperature and humidity baseline.

[0033] Specifically, the process of adjusting the heat exchange distribution ratio of the core of the dual-module intercooler is as follows: based on the target temperature and humidity benchmark and the output results of the multivariate coupled prediction model, the air intake flow ratio of the main and auxiliary cores is distributed by adjusting the opening of the combination valve. The temperature of the cathode air intake after mixing is controlled by utilizing the difference in characteristics between the strong cooling of the main core and the low heat dissipation of the auxiliary core.

[0034] Specifically, the process of synchronously coordinating the humidification adjustment operation of the fuel cell cathode air intake is as follows: based on the real-time temperature of the cathode air intake after the core heat exchange distribution adjustment, combined with the correlation characteristics between temperature and saturated water vapor pressure in the relative humidity calculation formula, and based on the target temperature and humidity benchmark, the humidification intensity of the humidifier is dynamically adjusted by calculating the water vapor partial pressure difference required for the current air intake.

[0035] In this embodiment, the parameter definitions and model outputs are continued from the previous embodiment: Adjusting the core heat exchange distribution ratio of the dual-module intercooler: Based on the target temperature and humidity baseline t_target, and combined with the t_predicted output from the multivariate coupled prediction model m1, the following steps are used to allocate the ratio of main and auxiliary core air inlet flow rates and regulate the cathode air inlet temperature after mixing: Deviation judgment: Compare tpreset and ttarget to determine the direction of temperature adjustment—if tpreset is higher than ttarget, the cooling effect needs to be enhanced; if tpreset is lower than ttarget, the cooling effect needs to be weakened. Combination valve opening adjustment: By adjusting the opening of valve 5 (combination valve), the intake flow ratio between the main core and the auxiliary core of valve 4 is distributed. When tpre is higher than tmesh, the opening ratio of valve 5 to the main core of valve 4 is increased (denoted as kmain), and the opening ratio to the auxiliary core is decreased (denoted as kauxiliary, kmain + kauxiliary = 1). The strong cooling characteristics of the main core are used to enhance heat exchange and reduce the intake temperature after mixing. When tpre is lower than tmesh, kmain is decreased and kauxiliary is increased. The low heat dissipation characteristics of the auxiliary core are used to reduce heat loss and increase the intake temperature after mixing. Temperature closed-loop control: The real-time temperature t of the mixed cathode air intake is continuously collected by 8 and fed back to the control module. The opening ratio of 5 is dynamically fine-tuned until t approaches t_target, thus completing the precise control of the core heat exchange distribution.

[0036] The humidification and regulation operation is synchronized with the cathode air intake of the fuel cell: After the core heat exchange distribution is stabilized, based on the real-time temperature t and combined with the relative humidity calculation formula "RH=d / p_saturated(t)×100%", the humidification intensity of 6 (humidifier) ​​is dynamically adjusted according to the following steps: Calculate the target water vapor partial pressure: Based on the target relative humidity h_mo and the real-time temperature t_t, derive the target water vapor partial pressure d_mo using the formula, i.e., d_mo = (h_mo / 100%) × p_saturated(t_t), where p_saturated(t_t) is the saturated water vapor pressure corresponding to t_t. Calculate the partial pressure difference: Collect the actual water vapor partial pressure dactual of the cathode air intake after core adjustment through the humidity detection and correlation module, and calculate the partial pressure difference Δd = dvisible - dactual. Dynamically adjust the humidification intensity: If Δd>0, it means that the current water vapor partial pressure is insufficient, and the humidification intensity of 6 needs to be increased to supplement water vapor and reduce the partial pressure difference; if Δd≤0, it means that the current water vapor partial pressure meets or exceeds the target requirement, and the humidification intensity of 6 should be decreased or the current state should be maintained. Humidity closed-loop calibration: Continuously monitor the adjusted relative humidity h_actual (derived by combining t_adjustment and d_actual with the formula), compare h_actual with h_object, dynamically correct the humidification intensity of 6, and ensure that the cathode intake humidity is stably close to h_object, so as to achieve coordinated control of temperature and humidity.

[0037] Specifically, the process of dynamically adjusting the heat exchange regulation range of the dual-module intercooler is as follows: based on the monitoring results, the opening adjustment range of the combination valve connected to the main and auxiliary cores is adjusted, the adjustment step of the air intake flow ratio of the main and auxiliary cores is changed, and the air intake flow distribution adjustment range of the main and auxiliary cores is increased and decreased.

[0038] Specifically, the process of simultaneously changing the intensity of cathode intake humidification adjustment is as follows: combining real-time operating condition changes, synchronously associating the adjustment of the heat exchange adjustment amplitude of the dual-module intercooler, obtaining the actual temperature and humidity parameters of the cathode intake in real time, comparing them with the target temperature and humidity benchmark, and calculating the current humidity deviation value; dynamically changing the humidification intensity of the humidifier according to the magnitude and trend of the deviation.

[0039] In this embodiment, the scenario described in the previous embodiment is continued, and the specific process is as follows: Excessive humidity operation (low temperature and medium power operation): Monitor real-time operating conditions of fuel cells: The control module continuously monitors key parameters and captures characteristics of excessively humid conditions: Temperature and humidity feedback: The actual relative humidity h_actual is derived from the humidity detection and correlation module. Continuous monitoring found that h_actual continuously exceeds the humidity alarm threshold h_alarm, and the deviation from the target relative humidity h_target gradually increases. Battery stack condition: The standard deviation of the voltage of a single battery stack cell has increased, showing significant fluctuations; Operating parameters: The fuel cell power e is maintained in the medium power range, the ambient temperature c is in the low temperature range (fitting the "low temperature operation" scenario), and the intake air flow a and pressure b remain stable.

[0040] Dynamically adjust the heat exchange regulation range of the dual-module intercooler: Based on the monitoring results of the over-humidity condition, the heat exchange regulation guided by dehumidification is enhanced by adjusting the operating parameters of the combination valve 5. The specific process is as follows: Determine the adjustment direction: Under excessively humid conditions, the low heat dissipation and high temperature output characteristics of the secondary core of component 4 need to be utilized to quickly reduce the relative humidity of the mixed intake air. Therefore, the flow rate ratio of the secondary core needs to be increased. Adjust the opening adjustment range of the combination valve: Previously, during steady-state operation, the opening of combination valve 5 to the main core was k_main_normal (normal main circuit opening). Now, it is switched to "rapid dehumidification adjustment mode", which increases the single opening adjustment range from the normal Δk_normal to Δk_maximum (Δk_maximum > Δk_normal), shortening the adjustment response time. Adjusting the flow ratio step size: Adopting the strategy of "large step start + small step calibration", initially, the opening of the combination valve 5 to the main core is quickly adjusted from k main normal to k main wet (main circuit opening under over-wet conditions) with a large step size s large, so that the proportion of the secondary circuit is increased from k secondary normal to k secondary wet (k secondary wet = 1 - k main wet). Subsequently, the opening size is finely adjusted with a small step size s small (s small < s large) to avoid sudden temperature changes. Optimize the flow distribution adjustment range: Temporarily expand the adjustment boundary of the secondary core flow ratio from the conventional k-sub-low to k-sub-high to k-sub-wet-low to k-sub-wet-high, so as to give full play to the dehumidification effect of the high temperature and low humidity gas in the secondary circuit.

[0041] The intensity of the cathode intake humidification adjustment is adjusted accordingly: By adjusting the heat exchange rate, the humidification intensity of humidifier 6 is simultaneously optimized to meet the needs of overhumidified conditions. Related heat exchange regulation status: Real-time tracking of the opening change of combination valve 5 (main line opening decreases from k main normal to k main wet), clarifying that the increase in the proportion of secondary line flow will lead to an increase in the mixed intake temperature t, thereby reducing the relative humidity; Calculate humidity deviation and trend: Currently, h_actual > h_alarm, h_actual > h_mesh, calculate the humidity deviation value Δh = h_actual - h_mesh, and Δh shows a continuous increasing trend; Dynamically adjust the humidification intensity: Since Δh > 0 and the deviation is increasing, and the heat exchange regulation has started the dehumidification mechanism, immediately reduce the humidification intensity of humidifier 6 to the lowest operating level z (to avoid continuous humidification aggravating overhumidification). If h does not decrease, stop the humidification operation. Collaborative closed-loop calibration: Continuously monitor tactual (tactual increases significantly after mixing with high-temperature gas in the secondary circuit) and hactual. As the proportion of the secondary circuit increases, hactual gradually decreases. When hactual approaches htarget, restore the humidification intensity to the normal fine-tuning level. At the same time, adjust the opening of the combination valve 5 in small steps to finally stabilize hactual at hstable (safe humidity for over-humidified conditions), thus improving the consistency of the fuel cell stack voltage.

[0042] Excessive dryness risk conditions (long-distance, high-speed, high-power operation): Monitor real-time operating conditions of fuel cells: The control module continuously monitors key parameters and captures characteristics of excessive dryness risk: Temperature and humidity feedback: The actual relative humidity of the cathode intake air h continues to decrease and is below h mesh, indicating that the membrane electrode shows a drying trend; Operating parameters: The vehicle is running at high speed over long distances. The fuel cell power e is in the high power range. The ambient temperature c is a dry ambient temperature. The intake air flow a is maintained at a high level due to high power demand. System status: The current opening of combination valve 5 is k main line (initial main line opening under over-dry conditions). The main core body has a low proportion of strong cooling effect, and the actual mixed intake temperature t is relatively high, resulting in low relative humidity.

[0043] Dynamically adjust the heat exchange regulation range of the dual-module intercooler: Based on the results of the over-drying risk monitoring, the heat exchange regulation guided by humidification is enhanced by adjusting the operating parameters of the combination valve 5. The specific process is as follows: Determine the adjustment direction: Under excessively dry conditions, the strong cooling characteristics of the main core body of 4 need to be used to reduce the mixed intake air temperature t. Combined with the relative humidity calculation formula "RH=d / psaturated(t)×100%" (d is the partial pressure of water vapor, psaturated(t) is the saturated water vapor pressure at temperature t), the temperature reduction can increase the relative humidity, so the flow rate ratio of the main core body needs to be increased. Adjust the opening range of the combination valve: Switch to "mild humidification adjustment mode" and reduce the single opening adjustment range from Δk large in the over-humidity condition to Δk micro (Δk micro < Δk normal) to avoid humidity overshoot caused by rapid temperature drop; Change the flow ratio adjustment step size: adopt the "small step gradual adjustment" strategy, gradually increase the opening of the combination valve 5 to the main core from k main to k main + Δk micro with a step size s micro (s micro < s small), the proportion of the main road slowly increases, and the proportion of the secondary road decreases accordingly; Optimize the flow distribution adjustment range: Expand the adjustment boundary of the main core flow ratio from the conventional k-main low-k-main high to k-main low-k-main high, while ensuring the heat dissipation requirements of high power operation and enhancing the effect of the low temperature characteristics of the main circuit on humidity improvement.

[0044] The intensity of the cathode intake humidification adjustment is adjusted accordingly: By adjusting the heat exchange rate, the humidification intensity of humidifier 6 is simultaneously optimized to meet the needs of operating conditions with a risk of excessive dryness. Related heat exchange regulation status: Real-time tracking of the opening change of combination valve 5 (main line opening gradually increases), clarifying that the increase in the proportion of main line flow will lead to a decrease in the actual mixed intake temperature t, creating conditions for increased humidity; Calculate humidity deviation and trend: Currently, hactual < hmesh, calculate the humidity deviation value Δh = hmesh - hactual (Δh > 0), and Δh shows a continuous increasing trend (the film drying trend intensifies). Dynamically adjust the humidification intensity: Since Δh > 0 and the deviation increases, the humidification intensity of humidifier 6 is simultaneously increased, gradually rising from the lowest operating level z to a medium-high intensity z, to replenish water vapor partial pressure; combined with the low temperature characteristics of the main circuit (the actual t decreases, causing p saturation (t) to decrease), the relative humidity is further increased; Collaborative closed-loop calibration: Continuously monitor t_actual and h_actual. As the proportion of the main path increases and the humidification intensity increases, the humidification amount and relative humidity of the gas entering the reactor gradually increase, the membrane drying trend is alleviated, and finally h_actual stabilizes near h_mesh, ensuring that the membrane electrode is fully wetted and the system returns to stable operation.

[0045] Specifically, the process of constructing the dynamic constraint correction model is as follows: input the temperature and humidity deviation values, based on the parameter dataset, and combining the heat exchange characteristics of the dual-module intercooler and the adjustment characteristics of the humidifier as the basic constraints of the model; set the two-dimensional correction direction of the model, including: core heat exchange distribution ratio correction and humidification adjustment parameter correction; establish a dynamic mapping relationship between deviation characteristics and correction amount by quantitatively analyzing the magnitude and trend of the temperature and humidity deviation values; set the correction amount constraint boundary of the core heat exchange distribution ratio and humidification adjustment parameter in combination with the parameter requirements for stable operation of fuel cell, and limit the adjustment range of the correction operation; integrate and generate the dynamic constraint correction model.

[0046] Specifically, the process of establishing the dynamic mapping relationship between deviation features and correction amounts is as follows: Based on the numerical magnitude, polarity, rate of change, and trend of the temperature and humidity deviation values, combined with the parameter dataset, and simultaneously coupling the heat exchange regulation characteristics of the dual-module intercooler and the humidification regulation characteristics of the humidifier, the temperature deviation and humidity deviation are first subjected to feature extraction and quantification characterization to generate deviation feature indices. Single-dimensional quantitative association rules are then established between the temperature deviation features and the core heat exchange allocation ratio correction amount, and between the humidity deviation features and the humidification regulation parameter correction amount. The basic value standard for the correction amount under the deviation features is set. Combined with the parameter coupling characteristics of temperature and humidity, the single-dimensional quantitative association rules are collaboratively calibrated.

[0047] Specifically, the process of correcting the core heat exchange distribution ratio and the humidification adjustment parameters of the cathode intake air in the dual-module intercooler is as follows: Based on the quantitative correction amount of the core heat exchange distribution ratio and the quantitative correction amount of the humidification adjustment parameters output by the dynamic constraint correction model, and combined with the temperature and humidity deviation characteristics, the parameters are synchronously and in conjunction with each other; based on the core heat exchange distribution ratio and according to the heat exchange distribution ratio correction amount corresponding to the temperature deviation, the opening degree of the corresponding combination valves of the main and auxiliary cores of the dual-module intercooler is adjusted to dynamically adjust the intake flow ratio ratio of the main and auxiliary cores; based on the cathode intake humidification adjustment parameters and according to the humidification adjustment parameter correction amount corresponding to the humidity deviation, and combined with the correlation characteristics between the real-time temperature of the cathode intake air and the saturated water vapor pressure, the humidification adjustment parameters of the humidifier are adjusted.

[0048] In this embodiment, the above embodiment continues, and the specific process is as follows: Obtain actual temperature and humidity parameters and compare them with the deviations: Actual parameter acquisition: After dynamic adjustment, the control module continuously acquires the actual temperature t of the fuel cell cathode through 8, and derives the actual relative humidity h in real time through the humidity detection and correlation module to ensure the real-time performance and accuracy of parameter acquisition. Deviation calculation: The collected actual temperature t is compared with the preset target temperature t_object and the actual humidity h is compared with the preset target humidity h_object to generate temperature deviation Δt and humidity deviation Δh, which fully characterize the degree of deviation between the actual temperature and humidity and the target reference.

[0049] Construct a dynamic constraint correction model: Input basic data: Temperature deviation Δt and humidity deviation Δh are used as core input parameters, combined with parameter dataset s, and the heat transfer characteristics of 4 (the differentiated characteristics of strong cooling of the main core and low heat dissipation of the secondary core) and the adjustment characteristics of 6 (adjustable range of humidification intensity, response rate and adjustment accuracy) are also included as the basic constraints of the model. Define the correction objectives: Clearly define the two-dimensional correction objectives of the model, namely, the correction of the core heat exchange distribution ratio (closed-loop correction for temperature deviation Δt) and the correction of the humidification adjustment parameters (closed-loop correction for humidity deviation Δh), to ensure the targeted nature of the correction operations. Quantitative deviation characteristics: Comprehensive feature extraction and quantitative characterization are performed on Δt and Δh respectively to generate complete deviation characteristic indicators—including the numerical amplitude (t amplitude), positive and negative polarity (t polarity), rate of change (t velocity), and trend of change (t potential) of Δt, and the numerical amplitude (h amplitude), positive and negative polarity (h polarity), rate of change (h velocity), and trend of change (h potential) of Δh, providing a quantitative basis for the subsequent establishment of mapping relationships; Establish dynamic mapping relationships: Single-dimensional correlation: Combining the heat transfer regulation characteristics of parameter datasets s and 4, and the humidification regulation characteristics of 6, the deviation characteristics of Δt and Δh are analyzed respectively. A single-dimensional quantitative correlation rule is established between the temperature deviation characteristics and the core heat transfer distribution ratio correction amount Δk, and the basic value standard of Δk under different combinations of t amplitude, t pole, t speed, and t potential is clarified. At the same time, a single-dimensional quantitative correlation rule is established between the humidity deviation characteristics and the humidification regulation parameter correction amount Δz, and the basic value standard of Δz under different combinations of h amplitude, h pole, h speed, and h potential is clarified. Collaborative calibration: Considering the parameter coupling characteristics of temperature and humidity (the change of t_actual will affect the calculation result of h_actual, and the change of h_actual will also indirectly affect the heat exchange efficiency of the stack), the above two sets of single-dimensional quantitative correlation rules are collaboratively calibrated by introducing a coupling coefficient μ to correct possible correction conflicts and ensure that the values ​​of Δk and Δz are compatible with each other. Set constraint boundaries: Combining the parameter requirements for stable operation of fuel cells (to avoid system oscillation or performance degradation due to over-adjustment), and the hardware performance limits of 4, 5, and 6, set correction constraint boundaries—core heat exchange distribution ratio constraint (k_main limit is the minimum-maximum allowable value of the flow rate ratio of 4 main cores, k_sub-limit is the minimum-maximum allowable value of the flow rate ratio of 4 sub-cores, and k_main + k_sub-limit = 1), humidification adjustment parameter constraint (z_limit is the minimum-maximum allowable value of 6 humidification intensity), limiting the adjustment range of correction operations; Integrated Generative Model: The basic constraints, two-dimensional correction orientation, dynamic mapping relationship, and correction amount constraint boundary are integrated to form a complete dynamic constraint correction model m4, which provides algorithmic support for subsequent accurate correction.

[0050] Correct the core heat exchange distribution ratio and humidification adjustment parameters: Obtain the quantitative correction amount: Input the deviation characteristic indexes of Δt and Δh into the dynamic constraint correction model m4. Based on the preset constraint conditions and mapping relationship, the model outputs the quantitative correction amount Δk of the core heat exchange distribution ratio and the quantitative correction amount Δz of the humidification adjustment parameter. Synchronous and coordinated correction operations: Core heat exchange distribution ratio correction: Based on the current main core opening degree kmain of the combined valve 5, and according to the characteristics of Δk and temperature deviation, the opening degree of 5 is adjusted to adjust the main core flow ratio to kmain = kmain + Δk, and the secondary core flow ratio is simultaneously adjusted to ksecondary = 1 - kmain, ensuring that kmain is within the kmain limit and ksecondary is within the ksecondary limit. By dynamically adjusting the intake flow ratio of the main and secondary cores, a closed-loop correction of tactual is achieved. Humidification adjustment parameter correction: Based on the current humidification intensity zcurrent, according to the characteristics of Δz and humidity deviation, and combined with the correlation characteristics between the real-time cathode intake temperature tactual and the saturated water vapor pressure psaturated(t) (tactual affects psaturated(t), and thus affects the relative humidity calculation result), the humidification intensity is adjusted to znew = zcurrent + Δz to ensure that znew is within the z-limit range. By supplementing or reducing the water vapor partial pressure, a closed-loop correction of hactual is achieved. Closed-loop verification and iteration: continuously collect the corrected treal and hreal, recalculate the deviations Δtreal and Δhreal. If Δtreal and Δhreal still exceed the allowable range, input the new deviation characteristic index into m4 again and repeat the above correction process until treal stably approaches tobject and hreal stably approaches hobject, so as to achieve precise control of cathode inlet temperature and humidity.

[0051] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for coordinated control of cathode inlet temperature and humidity in a dual-module intercooler fuel cell, characterized in that, include: S1: Obtain the real-time status parameters of the fuel cell cathode air intake and the operating parameters of the fuel cell, perform preprocessing on the parameters, generate a parameter dataset, construct a multivariate coupled prediction model, and set the target temperature and humidity benchmark and oxygen stoichiometric ratio target for the fuel cell cathode air intake by combining the heat exchange characteristics of the dual-module intercooler. S2: Based on the target temperature and humidity benchmark, and combined with the output results of the multivariate coupled prediction model, adjust the core heat exchange distribution ratio of the dual-module intercooler, and simultaneously coordinate with the humidification adjustment operation of the fuel cell cathode air intake. S3: Monitor the real-time operating conditions of the fuel cell, and dynamically adjust the heat exchange regulation range of the dual-module intercooler based on the monitoring results, while correspondingly changing the intensity of cathode intake humidification regulation. S4: Obtain the actual temperature and humidity parameters of the intake air entering the cathode of the fuel cell after adjustment, compare the deviation of the actual temperature and humidity parameters with the target temperature and humidity benchmark, construct a dynamic constraint correction model, and correct the core heat exchange distribution ratio of the dual-module intercooler and the humidification adjustment parameters of the cathode intake air based on the temperature and humidity deviation value generated by the comparison.

2. The method according to claim 1, characterized in that, The specific process of performing preprocessing on the parameters is as follows: dimensional regularization is performed on the real-time status parameters and the running parameters to unify the representation form of the parameters, redundancy removal is performed on the parameters, and duplicate feature information in the parameters is removed. The normalized parameters are smoothed and then normalized to generate the parameter dataset.

3. The method according to claim 1, characterized in that, The specific process of constructing the multivariate coupled prediction model is as follows: Based on the parameter dataset, combined with the differences in heat transfer characteristics between the main and auxiliary cores of the dual-module intercooler, a mapping relationship between the parameters and the cathode inlet air temperature and humidity output is established to generate an initial prediction model. By continuously acquiring real-time monitoring data of the cathode inlet air and dynamic operating data of the fuel cell, the model parameters are iteratively corrected to generate the multivariate coupled prediction model.

4. The method according to claim 1, characterized in that, The specific process of iteratively correcting the model parameters is as follows: the real-time monitoring data and the dynamic operation data are used as verification samples, input into the initial prediction model to generate temperature and humidity prediction values, and compared with the actual temperature and humidity monitoring values ​​of the cathode inlet to calculate the temperature and humidity prediction error value; based on the difference in heat transfer characteristics between the main and auxiliary cores of the dual-module intercooler, combined with the mapping relationship between the parameters and the temperature and humidity output of the cathode inlet, the associated parameters of the initial prediction model are corrected according to the magnitude and direction of the error value.

5. The method according to claim 1, characterized in that, The specific process for setting the target temperature and humidity benchmark and oxygen stoichiometry target for the fuel cell cathode inlet is as follows: Based on the parameter dataset and the output results of the multivariate coupled prediction model, the target oxygen stoichiometry value is set according to the current power requirements of the fuel cell stack; combined with the correlation characteristics between temperature and saturated water vapor pressure in the relative humidity calculation formula, the target relative humidity value and the target inlet temperature value for the cathode inlet are set to form the target temperature and humidity benchmark.

6. The method according to claim 1, characterized in that, The specific process of regulating the heat exchange distribution ratio of the core of the dual-module intercooler is as follows: based on the target temperature and humidity benchmark and the output results of the multivariate coupled prediction model, the air intake flow ratio of the main and auxiliary cores is distributed by adjusting the opening of the combination valve. The temperature of the cathode air intake after mixing is controlled by utilizing the difference in characteristics between the strong cooling of the main core and the low heat dissipation of the auxiliary core.

7. The method according to claim 1, characterized in that, The specific process of the synchronous humidification adjustment operation of the fuel cell cathode air intake is as follows: based on the real-time temperature of the cathode air intake after the core heat exchange distribution adjustment, combined with the correlation characteristics between temperature and saturated water vapor pressure in the relative humidity calculation formula, and based on the target temperature and humidity benchmark, the humidification intensity of the humidifier is dynamically adjusted by calculating the water vapor partial pressure difference required for the current air intake.

8. The method according to claim 1, characterized in that, The specific process of dynamically adjusting the heat exchange regulation range of the dual-module intercooler is as follows: based on the monitoring results, the opening regulation range of the combination valve connected to the main and auxiliary cores is adjusted, the adjustment step of the intake flow ratio of the main and auxiliary cores is changed, and the adjustment range of the intake flow distribution of the main and auxiliary cores is increased or decreased.

9. The method according to claim 1, characterized in that, The specific process of simultaneously changing the intensity of cathode intake humidification adjustment is as follows: combining real-time operating condition changes, synchronously associating the adjustment of the heat exchange adjustment amplitude of the dual-module intercooler, obtaining the actual temperature and humidity parameters of the cathode intake in real time, comparing them with the target temperature and humidity benchmark, and calculating the current humidity deviation value; dynamically changing the humidification intensity of the humidifier according to the magnitude and trend of the deviation.

10. The method according to claim 1, characterized in that, The specific process of constructing the dynamic constraint correction model is as follows: input the temperature and humidity deviation value, and based on the parameter dataset, combine the heat exchange characteristics of the dual-module intercooler and the adjustment characteristics of the humidifier as the basic constraint conditions of the model. The model is set to have two dimensions for correction, including: core heat exchange distribution ratio correction and humidification adjustment parameter correction; By quantitatively analyzing the magnitude and trend of the temperature and humidity deviation values, a dynamic mapping relationship between deviation characteristics and correction amounts is established; combined with the parameter requirements for stable operation of fuel cells, the correction amount constraint boundaries of the core heat exchange distribution ratio and humidification adjustment parameters are set to limit the adjustment range of the correction operation; and the dynamic constraint correction model is integrated to generate the model.

11. The method according to claim 10, characterized in that, The specific process for establishing the dynamic mapping relationship between deviation features and correction amounts is as follows: Based on the numerical magnitude, positive and negative polarity, rate of change, and trend of the temperature and humidity deviation values, combined with the parameter dataset, and simultaneously coupling the heat exchange regulation characteristics of the dual-module intercooler and the humidification regulation characteristics of the humidifier, the temperature deviation and humidity deviation are first subjected to feature extraction and quantification characterization to generate deviation feature indices. Single-dimensional quantitative association rules are then established between the temperature deviation features and the core heat exchange distribution ratio correction amount, and between the humidity deviation features and the humidification regulation parameter correction amount. The basic value standard for the correction amount under the deviation features is set. Combined with the parameter coupling characteristics of temperature and humidity, the single-dimensional quantitative association rules are collaboratively calibrated.

12. The method according to claim 1, characterized in that, The specific process for correcting the core heat exchange distribution ratio and the humidification adjustment parameters of the cathode intake air in the dual-module intercooler is as follows: Based on the quantitative correction amount of the core heat exchange distribution ratio and the quantitative correction amount of the humidification adjustment parameters output by the dynamic constraint correction model, and combined with the temperature and humidity deviation characteristics, the parameters are synchronously and in conjunction with each other; based on the core heat exchange distribution ratio, and according to the heat exchange distribution ratio correction amount corresponding to the temperature deviation, the opening degree of the corresponding combination valves of the main and auxiliary cores of the dual-module intercooler is adjusted to dynamically adjust the intake flow ratio ratio of the main and auxiliary cores; based on the cathode intake humidification adjustment parameters, and according to the humidification adjustment parameter correction amount corresponding to the humidity deviation, and combined with the correlation characteristics between the real-time temperature of the cathode intake air and the saturated water vapor pressure, the humidification adjustment parameters of the humidifier are adjusted.

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