A urea solution storage tank anti-crystallization heat preservation system

Abstract

The application discloses a urea solution storage tank anti-crystallization heat preservation system, comprising a storage tank body, a heat preservation layer, an electric heat tracing unit, a temperature sensing unit, a state monitoring unit and an intelligent controller; the intelligent controller is electrically connected with the electric heat tracing unit, the temperature sensing unit and the state monitoring unit, is used for executing a predictive intelligent temperature control strategy, and carries out fault diagnosis and redundancy switching according to monitoring data. According to the application, the electric heat tracing circuits controlled independently are arranged in different regions according to the crystallization risk difference in the storage tank, higher power density or denser wiring is adopted in the high-risk region, the 'on-demand heating' is realized, the intelligent controller is combined to set independent temperature set points and PID parameters for each region, the overall system energy consumption can be significantly reduced while ensuring the absolute safety of key positions, and energy waste caused by uniform heating is avoided.

Description

Technical Field

[0001] This application belongs to the field of urea solution storage technology, specifically relating to an anti-crystallization and heat preservation system for urea solution storage tanks. Background Technology

[0002] With the full implementation of the China VI emission standard for diesel vehicles, the storage and stable supply of automotive urea solution (AdBlue) has become crucial. Urea solution is prone to crystallization at low temperatures (usually below -11°C), leading to blockages in storage tanks, pipelines, and nozzles, severely affecting the normal operation of the vehicle's aftertreatment system, and even causing equipment damage.

[0003] Currently, to prevent urea solution crystallization, a common approach is to use electric heat tracing combined with insulation. However, this traditional method has significant shortcomings: First, it typically uses a single-power-density heat tracing cable to uniformly heat the entire tank, failing to consider the differences in crystallization risk caused by varying heat loss rates and fluid states in different areas within the tank (such as the bottom sedimentation zone, the outlet pipeline, and the main solution zone). This "one-size-fits-all" approach can easily lead to insufficient heating in high-risk areas, energy waste in low-risk areas, and may even affect solution quality due to localized overheating. Second, heat tracing systems often use a single circuit. If a cable breaks, wiring fails, or electrical protection trips, the heat tracing function in that area is completely lost, posing a risk of crystallization due to a single point of failure, resulting in insufficient system reliability.

[0004] Therefore, there is an urgent need for a high-efficiency urea solution storage tank anti-crystallization insulation system that can achieve precise temperature control by zone, has high reliability redundancy, and integrates intelligent prediction and diagnostic functions. Summary of the Invention

[0005] This application provides a urea solution storage tank anti-crystallization insulation system, which aims to solve the problem of different crystallization risks in different areas of the existing storage tank due to different heat loss rates and fluid states, and the potential for crystallization due to single-point failure.

[0006] A urea solution storage tank anti-crystallization insulation system includes:

[0007] The storage tank body, insulation layer, electric heat tracing unit, temperature sensing unit, status monitoring unit, and intelligent controller;

[0008] The electric heat tracing unit includes multiple independently controlled electric heat tracing circuits, which are arranged in zones according to the differences in crystallization risk of the urea solution in the storage tank. At least in the high crystallization risk zone, there are dual-circuit electric heat tracing circuits for main use and backup.

[0009] The temperature sensing unit includes multiple temperature sensors arranged in different areas of the storage tank;

[0010] The status monitoring unit includes a current monitoring module for monitoring the operating current of each heat tracing circuit and an insulation monitoring module for monitoring the insulation to ground.

[0011] The intelligent controller is electrically connected to the electric heat tracing unit, the temperature sensing unit, and the status monitoring unit, respectively, and is used to execute predictive intelligent temperature control strategies and perform fault diagnosis and redundancy switching based on monitoring data.

[0012] Optionally, the high crystallization risk zone includes the bottom of the storage tank and the solution outlet pipeline. The electric heat tracing unit in this zone uses a dual-circuit constant power electric heat tracing cable with a main circuit and a backup circuit connected in parallel. The laying paths of the two circuits are spatially independent or staggered.

[0013] Optionally, the predictive intelligent temperature control strategy executed by the intelligent controller includes: dynamically calculating and outputting heating power control commands for each independent electric heat tracing circuit based on the current ambient temperature, the predicted ambient temperature change trend, and the thermal inertia model of the storage tank.

[0014] Optionally, the status monitoring unit further includes a multi-point temperature monitoring module for real-time monitoring of temperature changes in high-risk areas. The intelligent controller performs fault diagnosis based on the data from the current monitoring module, insulation monitoring module, and temperature monitoring module, and controls the switch to the backup circuit when a fault in the main circuit is detected or the temperature in the corresponding area drops abnormally.

[0015] Optionally, the temperature sensing unit includes multiple resistance temperature detectors arranged at the bottom of the tank, the main body of the cylinder, the outlet pipeline and the top gas phase space for zoned temperature acquisition.

[0016] Optionally, the predictive intelligent temperature control strategy is implemented through an improved proportional environmental sensing control algorithm, the output power command of which is dynamically determined by the current ambient temperature, the predicted trend of future ambient temperature changes, and the thermal inertia model of the storage tank.

[0017] Optionally, the intelligent controller is further configured to calculate a liquid level compensation factor based on the real-time liquid level and dynamically adjust the basic heating power of each zone based on the factor.

[0018] Optionally, the system further includes a crystallization risk warning module, which calculates a crystallization risk index based on the temperature drop rate, temperature safety margin, heating system load rate and historical data, and automatically increases the heating power or issues a warning when the index exceeds a preset threshold.

[0019] Optionally, the liquid level compensation factor is calculated based on the tank geometry and steady-state thermal balance principle, and the formula is:

[0020]

[0021] in, This is the current liquid level height. This is the maximum liquid level height in the storage tank. The diameter is the storage tank diameter.

[0022] Optionally, the thermal inertia model of the storage tank adopts a first-order plus pure time delay model, which is obtained by fitting step response test data through a system identification method. The model parameters include process gain, time constant and pure time delay.

[0023] Compared with the prior art, this application has at least the following beneficial effects:

[0024] This application achieves "heating on demand" by arranging independently controlled electric heat tracing circuits in different areas of the storage tank based on the differences in crystallization risk (high, medium, and low risk areas), and by using higher power density or denser wiring in high-risk areas (such as the tank bottom and outlet pipelines). Combined with intelligent controllers to set independent temperature setpoints and PID parameters for each zone, it can reduce the overall system energy consumption while ensuring the absolute safety of critical parts and avoid the energy waste caused by uniform heating.

[0025] This application deploys a dual-circuit parallel constant power electric heat tracing system with a main circuit and a backup circuit in high crystallization risk areas. The two circuits are independent in terms of electrical circuits and laying paths, forming 100% physical redundancy. When the intelligent controller diagnoses a fault such as an open circuit, abnormal power, or insulation degradation in the main circuit through the status monitoring unit, it can automatically switch to the backup circuit without disturbance, ensuring the continuity of the anti-crystallization function and fundamentally eliminating the risk of single-point failure. It is particularly suitable for extreme low temperature environments and long-term unattended scenarios.

[0026] This application integrates an ambient temperature prediction module and a storage tank thermal inertia model, and adopts an improved proportional ambient sensing control algorithm. This enables the system to not only respond to the current ambient temperature, but also to adjust the heating power in advance and smoothly based on future temperature change trends and the dynamic thermal characteristics of the storage tank. This predictive control effectively reduces temperature overshoot and fluctuations, making the solution temperature in the storage tank more stable, and further saving energy while ensuring the anti-crystallization effect. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the module connection of an anti-crystallization and heat preservation system for a urea solution storage tank, provided as an embodiment of this application. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments.

[0029] This application provides a urea solution storage tank anti-crystallization insulation system, comprising:

[0030] The storage tank body, insulation layer, electric heat tracing unit, temperature sensing unit, status monitoring unit, and intelligent controller;

[0031] The electric heat tracing unit includes multiple independently controlled electric heat tracing circuits, which are arranged in zones according to the differences in crystallization risk of the urea solution in the storage tank. At least in the high crystallization risk zone, there are dual-circuit electric heat tracing circuits for main use and backup.

[0032] Specifically, the anti-crystallization insulation system of the storage tank is based on an in-depth analysis of the physicochemical properties of urea solution (32.5% automotive urea solution) and its thermodynamic behavior within the tank, implementing a refined zoned temperature management strategy. The crystallization point of urea solution is approximately -11℃, but considering localized supercooling, impurity induction, and the influence of hydrostatic pressure, a higher safe temperature (e.g., 10-15℃) needs to be maintained in actual engineering. However, the heat loss rate, solution flow state, and crystallization risk vary significantly between different areas within the storage tank. For example:

[0033] High crystallization risk zone: This area includes, but is not limited to, the bottom of the storage tank (especially irregular areas or areas with deposits) and the solution outlet pipeline and nozzles. Due to density flow, deposit accumulation, and a relatively static state, the temperature in the bottom area can easily drop to a minimum; the outlet pipeline and nozzles, due to their small metal mass, large specific surface area, and direct connection to the outside, experience severe heat loss and are the primary sites for crystallization blockage.

[0034] Mid-crystallization risk zone: This mainly refers to the main solution area of ​​the storage tank body. This area has a large solution volume, high heat capacity, and relatively slow temperature changes, but it remains the primary area for insulation.

[0035] Low crystallization risk zone: This refers to the gas phase space at the top of the storage tank that is not filled with solution. The main risk lies in the potential for localized concentration changes caused by the reflux of condensed water vapor, but the risk of direct crystallization is relatively low.

[0036] To address the aforementioned differentiated risk characteristics, a modular and configurable zoned heat tracing architecture based on parallel constant power electric heat tracing units is adopted, as detailed below:

[0037] Firstly, in selecting the heat tracing unit, a parallel structure of constant power electric heat tracing cable is preferred. This type of cable allows for on-site cutting according to the design length, and its heating power per unit length (W / m) is constant, unaffected by ambient temperature. This is distinctly different from the power decay characteristic of self-regulating cables as temperature rises. This characteristic ensures that even if a temperature gradient occurs in the tank due to solution circulation or environmental changes at the design temperature, the heat tracing unit can still provide a stable rated power output, thereby achieving accurate and reliable protection of the preset maintenance temperature. Its structure typically includes two parallel insulated copper core busbars, with heating wires (resistance wires) connected continuously or intermittently to form a parallel resistance network. The outer layer is equipped with an insulating sheath, a metal shielding layer, and a corrosion-resistant outer sheath.

[0038] Secondly, based on the aforementioned risk zoning, differentiated layouts and power configurations of the heat tracing units are implemented. In high-crystallization-risk areas (such as the tank bottom and outlet short pipes), higher heat tracing power density or denser wiring spacing (heat tracing ratio) is used. For example, for the flat plate area at the tank bottom, a tight "U" or "S" shaped wiring pattern can be used, with the center-to-center spacing of the heat tracing cables designed to be 100mm to 200mm; for the vertical short pipes at the outlet, a 1:1 spiral winding or parallel straight laying method can be used. In medium-risk areas (the main tank wall), standard or slightly lower power density is used, for example, spiral winding with a center-to-center spacing of 300mm to 500mm for the heat tracing cables. In low-risk areas (the vapor space of the tank top head), the wiring density can be reduced as appropriate, or heat tracing can be arranged only in critical areas where condensation may occur (such as near the breather valve interface). The heat tracing cables for each area are set up as independent electrical circuits, equipped with separate power junction boxes, overcurrent protection devices, and control contacts.

[0039] Each independent loop is individually controlled by the intelligent controller via solid-state relays or contactors, or more preferably, phase angle adjustment. The controller incorporates multi-channel temperature control logic, allowing for the setting of independent temperature setpoints (SPs) and control parameters (such as PID parameters) for different zones. For example, the setpoint for the high-risk outlet pipeline can be set to 15°C, while the setpoint for the main solution zone can be set to 12°C, and the setpoint for the top vapor space can be set to 5°C (for condensation prevention only). Through this zoned, differentiated, independent temperature closed-loop control, the system can optimize overall energy consumption while ensuring absolute safety of critical components, avoiding energy waste and the risk of localized overheating caused by "one-size-fits-all" heating.

[0040] To ensure the effectiveness and economy of the multi-level temperature zone independent control system, accurate thermal calculations are required for each zone to determine the required power configuration and wiring density of the electric heat tracing unit. The specific calculations are performed according to the following steps and principles:

[0041] Step 1: Determine the basic design conditions;

[0042] Tank parameters: Obtain the precise geometric dimensions of the tank, including diameter, height, end cap type, wall thickness, and material (usually carbon steel or stainless steel).

[0043] Thermal insulation structure parameters: Specify the material (e.g., using rigid polyurethane foam) and thickness of the insulation layer in each area. ), and the thermal conductivity of the material at the design average temperature ( A protective layer (such as color steel plate or aluminum sheet) is usually installed outside the insulation layer.

[0044] Design environmental conditions: Determine the extreme minimum ambient temperature (Ta) that the system needs to withstand, for example, by taking the local historical extreme low temperature or a specific value required by the process (such as -25℃ or -30℃). At the same time, the ambient wind speed must be considered. The effect of convective heat transfer is usually calculated using a conservative value;

[0045] Process requirements: Determine the safe temperature (Ts) of the urea solution that needs to be maintained. Generally, Ts should be higher than its crystallization point (-11℃) by a certain margin, for example, set to 10℃.

[0046] Medium characteristics: The thermophysical properties of urea solution are considered, but in the steady-state heat loss calculation, the main factor affected is the convective heat transfer coefficient between the inner wall of the tank and the solution. This coefficient is usually large enough that the inner wall temperature can be approximated as equal to the solution temperature Ts.

[0047] Step 2: Calculate heat loss by region ( For the high, medium, and low risk zones, calculate their respective design conditions (Ta, Under the condition that the inner wall temperature is Ts, the amount of heat lost to the environment per unit time is calculated. The calculation formula follows the following general form:

[0048] For the curved walls (cylinder or head) of the storage tank, the heat dissipation The heat transfer can be estimated using a simplified one-dimensional flat-wall heat transfer formula, with a shape factor for correction, or directly using the cylindrical wall heat transfer formula. The following thermal resistances need to be considered in the calculation:

[0049] Thermal resistance of the insulation layer: , where A is the area of ​​the computational region;

[0050] Total thermal resistance (including convection and radiation) between the outer surface of the insulation layer and the atmospheric environment: ,in The surface convective-radiative heat transfer coefficient is the coefficient of heat transfer from the surface to the radiative surface, and its value is related to surface characteristics, ambient temperature, and wind speed.

[0051] Total heat loss in the region It can be represented as:

[0052] During calculations, different parts of the storage tank (flat bottom, cylinder wall, top cover, and nozzles) need to be treated separately due to their different geometries and heat dissipation conditions. In particular, for high-risk outlet short pipes and valves, their surface area and volume are relatively small, and insulation construction may be limited, so they need to be calculated separately. Usually, their heat loss per unit length is much greater than that of the main body of the storage tank.

[0053] Step 3: Determine the electric heat tracing compensation power ( The electric heat tracing system and its configuration must meet the following compensation power requirements: ;

[0054] Where K is the safety factor, which is usually taken as 1.1 to 1.3 to account for factors such as calculation error, material aging, voltage fluctuation and possible decline in thermal insulation performance after long-term operation;

[0055] Based on the calculated required compensation power Select and design the layout of the electric heat tracing unit:

[0056] Selection: Choose a parallel constant power electric heating cable with a suitable nominal linear power (W / m). This power value refers to the power stably dissipated per unit length of the heating cable under rated voltage and at the maintained temperature;

[0057] Layout design (determining the heat tracing ratio): based on the required total compensation power. and the linear power of the selected heat tracing cable This allows for a preliminary estimate of the total length of the required tracing cables. By combining the area of ​​the calculated region, the wiring spacing of the heat tracing cables (heat tracing ratio), i.e., the length of the heat tracing cables per unit area, can be determined. For high-risk areas, to ensure reliability and compensate for higher local heat loss (such as cold bridges caused by brackets), the design adopts... The value will be further increased based on the calculated value, resulting in a smaller wiring spacing (higher heat tracing ratio). For example, the bottom of the tank may use a 150mm spacing, while the main body of the cylinder may use a 300mm spacing;

[0058] Circuit division: Divide the heating cables arranged in the same risk level area with a reasonable total length into an independent electrical circuit, and ensure that the total power of the circuit does not exceed the rated capacity of the selected thermostat or circuit breaker;

[0059] Step 4: Verification and validation. After completing the preliminary design, a reverse verification is required: based on the final determined heat tracing cable model, spacing, and circuit division, calculate the maximum compensation power that the system can provide after actual installation. Then, considering the safety factor K, the performance was verified under the worst-case design conditions (…). , Under what conditions is it satisfied? In addition, thermal balance calculations or simulations are needed to verify whether the surface temperature of the heat tracing cable itself is within the maximum withstand temperature of its insulation material when the heat tracing system is working, and to ensure that the temperature will not have an adverse effect on the urea solution or the insulation material.

[0060] The purpose of the dual-circuit electric heat tracing system (main and backup) is to ensure the absolute reliability of the urea solution storage tank under extreme environments and long-term operation, and to prevent catastrophic consequences of local crystallization caused by a single electric heat tracing circuit failure.

[0061] Specifically, in the high-risk areas, the electric heat tracing units are deployed in a dual-circuit configuration of "primary-backup". Both circuits use identical parallel constant-power electric heat tracing cables, but their laying paths are spatially independent or staggered. For example, in the tank bottom area, the primary cable is laid in a "U" shape, while the backup cable is laid in an "S" shape, covering the same area but with non-overlapping paths; in the vertical pipe section at the outlet, the primary and backup cables are symmetrically spirally wound at 180° intervals. The power supply for the two circuits comes from different distribution branches or different circuit breakers within the same distribution box, ensuring electrical independence. Each circuit is equipped with an independent power junction box, overcurrent protection device, and independent control contacts (such as contactors or solid-state relays) driven by an intelligent controller. This dual-circuit design constitutes 100% physical redundancy, ensuring that any single fault point in a single circuit (cable breakage, loose wiring, circuit breaker tripping) will not cause a complete loss of heat tracing functionality in that area.

[0062] The system uses the following sensor network to monitor the health status and insulation effect of the redundant heat tracing system in real time and from multiple dimensions:

[0063] Loop current monitoring: Install high-precision current transformers or Hall effect current sensors at the power input terminals of each primary and backup circuit to measure the operating current of the circuit in real time. ;

[0064] Insulation resistance monitoring: The system integrates an insulation monitor that periodically (e.g., hourly) or continuously applies a safe DC test voltage between the live conductor of the heat tracing cable and the metal shield / ground to measure and calculate its insulation resistance. .

[0065] Multi-point temperature monitoring: Multiple resistance temperature detectors (RTDs) are deployed within and adjacent to high-risk areas. For example, 2-3 are placed at the bottom of the tank, and one each upstream and downstream of the outlet pipeline. These RTDs directly measure the temperature of the solution or the pipe wall. This is the most direct basis for judging the heat preservation effect;

[0066] Meanwhile, the intelligent controller has a built-in fault diagnosis algorithm that continuously analyzes the above monitoring data to determine the circuit status.

[0067] Open circuit fault: When a control contact of a certain circuit is closed, but the monitored current is not open... If the circuit remains open for more than a set time limit (e.g., 10 seconds), the circuit is considered to be open.

[0068] Power anomaly (aging / partial damage): Measure the current. With the rated current of the circuit Compare. If Significantly low (e.g., below 0.7×) This may indicate cable aging, localized damage, or increased contact resistance; if An abnormally high current level may indicate a short-circuit risk. The controller calculates the current deviation rate and performs trend analysis.

[0069] Insulation degradation fault: When the monitored insulation resistance Below the safety threshold (e.g.) When this occurs, it is determined to be insulation deterioration, and the system records a warning.

[0070] Abnormal temperature drop: When the temperature measured by the RTD in a high-risk area... If the rate of descent exceeds a threshold within a set time period (e.g., 15 minutes), or if the temperature value falls below the minimum safe temperature. (e.g., 5℃), while the current main circuit shows normal operating status, it may indicate that the main heat tracing is powered on but actually fails to heat up (e.g., partial cable damage but not complete circuit break), or the heat loss is far greater than the design value;

[0071] When the diagnostic algorithm determines that the primary circuit has an "open circuit" or "abnormal power" fault, or detects an "abnormal temperature drop" in the area, the controller immediately performs a seamless switching operation: First, it disconnects the control contacts of the primary circuit; then (usually within <100ms), it closes the control contacts of the backup circuit. Simultaneously, the controller sends a clear alarm signal through the human-machine interface (HMI), indicator lights, and a remote communication module (such as sending SMS or work orders), indicating the faulty circuit, the fault type (e.g., "A circuit open circuit"), and that the "switch to B circuit" operation has been performed. This process requires no manual intervention, ensuring the continuity of the anti-crystallization function.

[0072] The temperature sensing unit includes multiple temperature sensors arranged in different areas of the storage tank;

[0073] The status monitoring unit includes a current monitoring module for monitoring the operating current of each heat tracing circuit and an insulation monitoring module for monitoring the insulation to ground.

[0074] The intelligent controller is electrically connected to the electric heat tracing unit, the temperature sensing unit, and the status monitoring unit, respectively, and is used to execute a predictive intelligent temperature control strategy. The strategy includes: dynamically calculating and outputting heating power control commands for each independent electric heat tracing circuit based on the current ambient temperature, the predicted ambient temperature change trend, and the thermal inertia model of the storage tank; and performing fault diagnosis based on the data from the status monitoring unit and the temperature sensing unit, and controlling the switch to the backup circuit when a fault in the main circuit or an abnormal drop in temperature in the corresponding area is detected.

[0075] The implementation of the predictive intelligent temperature control strategy relies on two key software modules of the controller: the ambient temperature prediction module and the thermal inertia model of the storage tank, and is calculated and decided through an improved proportional ambient sensing control algorithm.

[0076] Key software modules include: an ambient temperature prediction module, which accesses regional weather forecast service data via communication interfaces (such as 4G or Ethernet) or obtains ambient temperature prediction curves for specific future time periods (such as the next 6-24 hours) based on historical data from micro-weather stations deployed on-site. This provides the controller with forward-looking information on external disturbances;

[0077] Tank Thermal Inertia Model: This model is a simplified dynamic thermodynamic model established based on the specific structure of the tank (geometry, materials, insulation layer), solution properties, and capacity. It characterizes the dynamic response characteristics and time delay of the solution temperature change within the tank under given heating power and ambient temperature variations. This model can be obtained through system identification methods (such as step response testing during the initial commissioning phase) and is used to quantify the thermal inertia of the system.

[0078] Improved Proportional Ambient Sensing Control Algorithm: Traditional proportional ambient sensing control (PASC) algorithms typically output power only proportional to the difference between the current ambient temperature (Ta) and the set sustaining temperature (Ts). This invention makes a significant improvement: the controller's power output command ( The following factors dynamically determine the ambient temperature: the current ambient temperature (Ta), the predicted downward trend of the ambient temperature in the next short period (e.g., the next 3 hours), and the current ambient temperature (Ta). ), and the system response characteristics reflected by the thermal inertia model of the storage tank.

[0079] The simplified expression of the algorithm can be described as follows:

[0080] Where: (Ts-Ta) represents the immediate compensation requirement needed to make up for the temperature difference;

[0081] This represents the need to compensate for unfavorable future temperature drops in advance. When the forecast shows that the ambient temperature will drop significantly, the algorithm will increase the heating power in advance and gradually before the temperature actually drops, so as to "store heat" for the system and offset the greater heat loss that is about to come.

[0082] This represents the output of the thermal inertia model, which constrains the rate and magnitude of power changes to prevent solution temperature overshoot (overheating) or drastic fluctuations due to excessive adjustment. For example, power adjustments can be smoother in the bulk solution region with a large heat capacity, while the power response can be faster in the outlet pipeline with a small heat capacity.

[0083] The controller periodically (e.g., every 15 minutes) executes the algorithm to calculate a dynamic, optimized power setpoint or duty cycle command for each independently controlled heat tracing loop, and executes it through the power adjustment module. This enables the system to not only respond to the current situation, but also to anticipate changes and act in advance, thereby achieving small temperature overshoot and smooth adjustment process, and ultimately reducing cumulative energy consumption while ensuring absolute anti-crystallization.

[0084] The thermal inertia model of the storage tank was established through a systematic combination of experiments and data fitting. Its purpose was to obtain a mathematical description that accurately reflects the dynamic temperature response characteristics of each zone of the tank (especially the main solution zone), providing key parameters for predictive control algorithms. The specific implementation steps of this method are as follows:

[0085] Step 1: Model Structure Selection and Experimental Preparation. Based on the tank's excellent insulation and the relatively uniform temperature distribution of the internal solution due to natural convection, the classic first-order plus pure time delay (FOPTD) model is typically used as the foundation for the thermal inertia models of each zone. The transfer function of this model is as follows: ;

[0086] Wherein, K is the process gain (characterizing the temperature rise caused by a unit heating power in steady state). It is the time constant (characterizing the system response speed, which is related to heat capacity and thermal resistance). This is the pure time lag (reflecting the delay in heat transfer from the heating tape to the temperature sensor measurement point). For parameter identification, during the initial system commissioning or specific maintenance period, a typical risk zone (such as the main solution zone) should be selected to ensure that the urea solution in that zone is at the normal operating level and the temperature is relatively stable. Disconnect the original closed-loop control of the electric heating circuit in that zone and place it in manual test mode.

[0087] Step 2: Open-loop step response test and data acquisition. A step heating power with a known and constant amplitude is applied to the test loop. (Typically 30%-70% of rated power to avoid excessive overshoot). Simultaneously, two key time-series data points are recorded at a high sampling frequency (e.g., once per second): 1) the applied heating power P(t); 2) the temperature response T(t) at a representative temperature measurement point within the zone (e.g., a resistance temperature detector (RTD) located in the middle of the tank wall, deep inside the solution). The test continues until the temperature rises close to the new steady-state value or reaches the safety upper limit. Afterward, a reverse cooling observation phase can be implemented (i.e., heating is turned off, and the natural cooling curve is recorded) to obtain more complete dynamic characteristics.

[0088] Step 3: Parameter identification and model fitting. Based on the collected step response data T(t), the system identification method is applied to extract the parameters K of the FOPTD model. , Specifically, a combination of graphical and numerical fitting methods can be used:

[0089] Steady-state gain K calculation: ,in The initial steady-state temperature, The new steady-state temperature after applying a step power;

[0090] Lag time With time constant Estimate: On the temperature response curve, find the starting point where the temperature begins to change significantly; the time difference between this point and the moment the power step is applied is the initial value. The estimated value. Then, the time point corresponding to the temperature change reaching 63.2% of the final total change was found; this time point is related to ( They are equal, from which we can solve for... To achieve higher accuracy, numerical optimization algorithms such as the least squares method can be used to globally fit the response curve, thereby simultaneously and optimally estimating K. , Three parameters;

[0091] Step 4: Model Validation and Regional Expansion. The identified model parameters are substituted into the FOPTD model, and the model is used to simulate calculations under the same step input. The theoretical temperature response was calculated and compared with the measured T(t) curve. The model's fit was verified by calculating indicators such as root mean square error. For other sections of the tank (such as the bottom and outlet pipelines), due to differences in heat capacity, insulation conditions, and heat transfer paths, the above steps (or appropriate adjustments to the step power amplitude) need to be repeated for independent identification, thereby obtaining a set of thermal inertia models with different parameters corresponding to each independent control loop. For cases with extremely complex geometry or higher requirements for model accuracy, three-dimensional unsteady-state heat transfer simulation of the tank and insulation structure can be performed in advance using computational fluid dynamics (CFD) software to obtain its dynamic response data. Then, a simplified lumped parameter model (such as the FOPTD model) can be fitted based on this data for use in the embedded controller.

[0092] The intelligent controller not only executes temperature control strategies based on environmental predictions, but also has the ability to dynamically fine-tune the heating power according to the actual operating conditions of the storage tank, and introduces a crystallization risk early warning mechanism to further optimize energy efficiency and improve system safety.

[0093] Specifically, the heat capacity of the urea solution in the storage tank is directly related to its total mass, which is determined by the real-time liquid level. Furthermore, inflow and outflow operations directly lead to energy exchange within the tank: injecting the cryogenic solution introduces a cooling load, while outputting the solution removes heat. Therefore, the system achieves real-time dynamic power adjustment through the following mechanism:

[0094] Liquid level compensation factor ( Calculation: The controller reads the level gauge signal in real time and calculates the current liquid level height h relative to the design maximum liquid level. The ratio. Based on the tank's geometry, it can be converted into a percentage of the current solution volume relative to the total volume. Define a liquid level compensation factor. Its value varies continuously between 0 and 1. For example, it can be set to... It has a linear or specific functional relationship with the liquid level percentage (e.g.) When calculating the basic heating power requirements for each zone, β is introduced for correction: (when (When less than 1). This means that at low liquid levels, due to the decrease in the total heat capacity of the solution, the heating power per unit mass required to maintain the same temperature needs to be increased accordingly. However, the system will also consider the change in heat loss caused by the reduction in the exposed inner surface of the tank wall at low liquid levels and perform comprehensive calculations.

[0095] Thermal disturbance feedforward compensation for liquid inflow / outflow events: When a flow meter or pump start / stop signal indicates a liquid inflow or outflow event, the controller treats this as a known thermal disturbance. For liquid outflow events, the system estimates the heat removed based on the outflow flow rate and duration, and appropriately increases the heating power setpoint in the relevant areas (especially near the outlet and the main solution area) for compensatory heating during the event and for a period afterward. For liquid inflow events (usually at lower inflow temperatures), the system estimates the additional cooling load requiring compensation based on the difference between the inflow flow rate, temperature, and the current temperature inside the tank, and increases the heating power in advance or simultaneously to prevent the newly injected low-temperature solution from causing a sudden drop in local temperature below the crystallization point. This compensation is added to the original control output as a feedforward term and decays exponentially to zero after the event ends.

[0096] To proactively mitigate crystallization risks, the system has constructed a "Crystallization Risk Index" (CRI) based on real-time data. This index integrates the calculation of the following key parameters:

[0097] instantaneous temperature drop rate ( The controller performs real-time differential calculations on the RTD temperature data of each high-risk area to obtain the rate of temperature change over time. (°C / min). The larger the negative value, the faster the cooling.

[0098] Temperature safety margin ( ): Calculate the current measured temperature With preset crystallization safety temperature The difference (e.g., 0℃, leaving a margin from the actual crystallization point): The smaller the value, the higher the risk;

[0099] Heating system load rate ( ): Calculate the percentage of the actual output power of the electric heat tracing in the current area relative to its maximum rated power. High load operation may mean excessive heat loss or that the heating capacity is close to its limit.

[0100] Historical operating condition data: The system records historical power and temperature data that successfully maintained temperature stability under similar ambient temperature, liquid level and liquid inlet / outlet conditions as a baseline;

[0101] The Crystallization Risk Index (CRI) is calculated using a multi-parameter weighted model, and can be assessed in real-time using a simplified formula, for example:

[0102] Where f(), g(), and h() are functions that normalize the original parameters to the risk score (e.g., The faster the output, the larger the value of f(). The smaller the value, the larger the output value of g(); The higher the value, the larger the output value of h(). , , These are the weighting coefficients for each factor. This is a correction term based on the degree of deviation from the historical baseline;

[0103] The intelligent controller continuously calculates and monitors the CRI values ​​of each high-risk area. When the CRI value of any area exceeds the first threshold (early warning threshold), the system determines that the crystallization risk has increased and will automatically perform one or more of the following operations: 1) Increase the heating power setting value of that area to increase the safety margin; 2) Issue an "increased risk" warning message to the operator to alert them to pay attention. When the CRI value exceeds a higher second threshold (action threshold), the system determines that there is an imminent crystallization risk and will immediately take stronger measures, such as: switching the heating power of that area to maximum; activating the backup heat tracing circuit (even if the main circuit is normal) to implement dual-circuit maximum power heating; issuing a high-level alarm, requiring immediate manual intervention and verification.

[0104] The liquid level compensation factor The calculation is based on an analytical-empirical coupled model established by the specific geometry of the storage tank and the principle of steady-state thermal balance. Its core lies in the fact that real-time liquid level changes simultaneously alter two key parameters: the total heat capacity of the solution (…). ) and effective heat loss surface area ( This needs to be coupled and calculated to determine the net impact on sustaining power;

[0105] Assume the storage tank is a vertical cylinder with a diameter of D and a total height of... Flat bottom. Let the current real-time liquid level height be h (0 ≤ h ≤ H_max). Then the current solution volume... Total heat capacity of the solution ,in The density of the solution, Here, is the specific heat capacity of the solution; both can be considered constants in engineering calculations.

[0106] Effective heat loss surface area Analytical calculations show that the heat loss of the storage tank mainly occurs through three pathways: the wetted portion of the tank wall (wet wall), the tank bottom (which is always in contact with the solution), and the gas phase space at the top of the tank (this is less affected by the liquid level and usually has small heat loss, so it can be ignored or treated separately in this model). Therefore, the liquid level h directly affects the wetted wall area;

[0107] Wet wall area: ;

[0108] Can bottom area: ;

[0109] At extremely low liquid levels (such as) , When the dead zone height at the bottom of the tank is typically 0.1 to 0.2 meters, the bottom of the tank may not be completely covered by the solution, and the heat transfer pattern is complex. This area should be treated as a special operating condition. Under normal operating conditions, the effective heat loss surface area is:

[0110] The theoretical heating power required to maintain the set temperature under steady-state conditions. It should be equal to the effective surface area. Heat lost to the environment. According to the principle of steady-state heat conduction, the amount of heat dissipated... , where U is the overall heat transfer coefficient of the storage tank insulation structure (considered a constant). To set the temperature difference between the ambient temperature and the set temperature (a constant under the worst design conditions), the system is typically designed with the highest liquid level ( Based on the operating condition, determine the maximum sustaining power required under that operating condition. ,Right now Therefore, at any liquid level h, considering only the change in heat loss area, the required power is proportional to the area:

[0111] However, this only considers the heat dissipation side. From the heat capacity side, the total heat capacity of the solution at low liquid levels... The temperature change inertia is small, but this effect is already included in the dynamic response of the aforementioned thermal inertia model. For steady-state power maintenance, the primary challenge is compensating for ongoing heat loss, rather than overcoming thermal inertia. Therefore, the liquid level compensation factor... It primarily reflects the rate of change of effective heat loss area, but its definition needs to be convenient for controller application. This invention will... Defined as the relative heat loss load coefficient corresponding to a unit volume of solution at the current liquid level, its expression is constructed as follows:

[0112] After simplification, we get:

[0113] This function It is a nonlinear decreasing function of the liquid level h (the smaller h is, the lower the liquid level h becomes). The larger (the greater). When hour, =1; When the liquid level drops >1 means that the heat loss load that needs to be compensated per unit volume of solution increases, so the base power needs to be adjusted upwards;

[0114] In the final dynamic power adjustment, the base power (Calculated by a predictive temperature control strategy, corresponding to the ideal operating condition at full liquid level) First, through Perform steady-state correction of liquid level:

[0115] This correction has been coupled with the change in effective heat dissipation area caused by the liquid level (via... ) and the change in solution volume (reflected through the reciprocal relationship of V(h) in (In the construction). Dynamic thermal disturbances caused by liquid inflow and outflow are handled by an independent feedforward compensation term, as described above.

[0116] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A urea solution storage tank anti-crystallization insulation system, characterized in that, include: The storage tank body, insulation layer, electric heat tracing unit, temperature sensing unit, status monitoring unit, and intelligent controller; The electric heat tracing unit includes multiple independently controlled electric heat tracing circuits, which are arranged in zones according to the differences in crystallization risk of the urea solution in the storage tank. At least in the high crystallization risk zone, there are dual-circuit electric heat tracing circuits for main use and backup. The temperature sensing unit includes multiple temperature sensors arranged in different areas of the storage tank; The status monitoring unit includes a current monitoring module for monitoring the operating current of each heat tracing circuit and an insulation monitoring module for monitoring the insulation to ground. The intelligent controller is electrically connected to the electric heat tracing unit, the temperature sensing unit, and the status monitoring unit, respectively, and is used to execute predictive intelligent temperature control strategies and perform fault diagnosis and redundancy switching based on monitoring data.

2. The urea solution storage tank anti-crystallization insulation system according to claim 1, characterized in that, The high crystallization risk area includes the bottom of the storage tank and the solution outlet pipeline. The electric heat tracing unit in this area adopts a dual-circuit constant power electric heat tracing cable with a main circuit and a backup circuit. The laying paths of the two circuits are spatially independent or staggered.

3. The urea solution storage tank anti-crystallization insulation system according to claim 1, characterized in that, The predictive intelligent temperature control strategy executed by the intelligent controller includes: dynamically calculating and outputting heating power control commands for each independent electric heat tracing circuit based on the current ambient temperature, the predicted ambient temperature change trend, and the thermal inertia model of the storage tank.

4. The urea solution storage tank anti-crystallization insulation system according to claim 1, characterized in that, The status monitoring unit also includes a multi-point temperature monitoring module for real-time monitoring of temperature changes in high-risk areas. The intelligent controller performs fault diagnosis based on the data from the current monitoring module, insulation monitoring module, and temperature monitoring module, and controls the switch to the backup circuit when a fault in the main circuit is detected or the temperature in the corresponding area drops abnormally.

5. The urea solution storage tank anti-crystallization insulation system according to claim 1, characterized in that, The temperature sensing unit includes multiple resistance temperature detectors arranged at the bottom of the tank, the main body of the cylinder, the outlet pipeline and the top gas phase space for zoned temperature acquisition.

6. The urea solution storage tank anti-crystallization insulation system according to claim 3, characterized in that, The predictive intelligent temperature control strategy is implemented through an improved proportional environmental sensing control algorithm. The output power command of this algorithm is dynamically determined by the current ambient temperature, the predicted trend of future ambient temperature changes, and the thermal inertia model of the storage tank.

7. The urea solution storage tank anti-crystallization insulation system according to claim 1, characterized in that, The intelligent controller is also configured to calculate a liquid level compensation factor based on the real-time liquid level and dynamically adjust the basic heating power of each zone based on the factor.

8. The urea solution storage tank anti-crystallization insulation system according to claim 1, characterized in that, The system also includes a crystallization risk warning module, which calculates a crystallization risk index based on the temperature drop rate, temperature safety margin, heating system load rate and historical data, and automatically increases heating power or issues a warning when the index exceeds a preset threshold.

9. The urea solution storage tank anti-crystallization insulation system according to claim 7, characterized in that, The liquid level compensation factor is calculated based on the tank geometry and steady-state thermal balance principle, and the formula is: in, This is the current liquid level height. This is the maximum liquid level height in the storage tank. The diameter is the storage tank diameter.

10. The urea solution storage tank anti-crystallization insulation system according to claim 3, characterized in that, The thermal inertia model of the storage tank adopts a first-order plus pure time delay model, which is obtained by fitting step response test data through system identification method. The model parameters include process gain, time constant and pure time delay.

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