A multi-dimensional blending method for heating lubricating oil

Abstract

This invention discloses a multi-dimensional blending method for heating lubricating oil. The method first initializes data such as the viscosity-temperature characteristic curve of the base oil, the dissolution activation energy of additives, and the thermal degradation threshold. Then, it constructs a multi-dimensional coupled model encompassing temperature, rheology, and time dimensions. The main heating unit maintains the base oil's basic flow temperature and performs low-speed pre-blending. During additive injection, an auxiliary heating unit rapidly heats the local fluid at the instantaneous optimal dissolution temperature calculated by the model. Apparent viscosity is calculated based on mixing torque feedback. Shear rate and heating power are dynamically adjusted according to the blending efficiency function. The blending endpoint is determined using a "viscosity-energy consumption" feedback loop, and parameters are optimized through an adaptive learning module. This method achieves efficient dispersion, energy saving, low thermal damage, and improves product mixing uniformity and batch quality stability.

Description

Technical Field

[0001] This invention relates to the fields of lubricating oil processing and petrochemical technology, specifically to a method for multi-dimensional blending of lubricating oil through heating. Background Technology

[0002] Blending is a crucial step in the lubricant production process. Its core lies in uniformly mixing base oil with various functional additives (such as detergents, dispersants, antioxidants, corrosion inhibitors, viscosity index improvers, etc.) to form a stable colloidal system.

[0003] Existing lubricating oil blending processes primarily employ "pulse blending" or "mechanical stirring blending." Regarding heat control, current technologies typically use a static isothermal control strategy, heating the entire tank of base oil to a fixed process temperature (usually 60-70°C), then adding additives and maintaining a constant stirring speed until homogeneous. However, this traditional method has the following significant drawbacks: The contradiction between the risk of thermal damage and dissolution efficiency: Different additives have vastly different dissolution characteristics. Some polymeric additives (such as viscosity index improvers) require higher temperatures for rapid swelling and dispersion, while some active additives (such as antioxidants) are extremely sensitive to temperature and will undergo thermal decomposition or oxidation when exposed to high temperatures for extended periods, resulting in damage to the oil's performance before it leaves the factory. Traditional constant-temperature heating cannot meet both of these requirements.

[0004] Significant energy waste: To ensure the mixing of poorly soluble additives, traditional processes often force the overall oil temperature to be increased and the stirring time to be extended. This not only leads to a large waste of thermal energy, but excessive mechanical shearing can also cause physical breakage of polymer chains, reducing the oil's viscosity retention capacity.

[0005] Lack of multi-dimensional coupled control: The temperature control system and stirring control system of existing blending equipment usually operate independently (i.e., PID temperature control only controls heating, and frequency converter only controls speed). The system lacks real-time analysis of fluid rheological properties (such as the non-Newtonian fluid properties of viscosity as a function of temperature and shear rate), and cannot dynamically adjust process parameters according to the real-time mixing state, resulting in low blending efficiency and difficulty in ensuring batch-to-batch quality stability. Summary of the Invention

[0006] Purpose of the invention: In order to overcome the shortcomings of the prior art, the present invention provides a multi-dimensional blending method for heating lubricating oil. By constructing a multi-dimensional coupled model that includes temperature, rheology and time dimensions, it implements graded heating and dynamic instantaneous fine-tuning, and performs variable shear coordinated control based on the blending efficiency function, thereby achieving intelligent blending of lubricating oil with high efficiency, energy saving and low thermal damage.

[0007] A method for heating and blending lubricating oil in multiple dimensions, the method comprising the following steps: S1: Basic data initialization: Obtain the viscosity-temperature characteristic curve of the base oil, the dissolution activation energy parameters of the additives to be added, and the thermal degradation threshold to provide a data basis for personalized blending; S2: Establish a multi-dimensional coupling model: Construct a harmonic control model that includes temperature, rheological, and time dimensions to achieve multi-parameter coordinated regulation; S3: Staged Heating and Pre-blending: The base oil is delivered to the blending tank, and the main heating unit maintains the oil temperature at the base flow temperature. At the same time, low-speed stirring is turned on to achieve energy-saving premixing; S4: Dynamic Instantaneous Fine-tuning: During the additive injection stage, the instantaneous optimal dissolution temperature is calculated based on the model in S2 using an auxiliary heating unit located on the injection pipeline. Rapid heating of localized fluids promotes dissolution without affecting the overall oil temperature; S5: Variable Shear Synergistic Control: Based on real-time monitoring of mixing torque feedback, the current apparent viscosity of the fluid is calculated, and the shear rate of the agitator is dynamically adjusted according to the harmonic efficiency function. The power of the auxiliary heating unit is adjusted until it is uniform, and the shear rate and heating power are dynamically adjusted through the harmonic efficiency function. The harmonic efficiency function in step S5 The following relationship must be satisfied: in, For the effective dispersion factor, The input power is represented by the denominator, which characterizes the loss of additive activity due to the cumulative thermal history. This is the thermal sensitivity coefficient.

[0008] The present invention provides a multi-dimensional blending method for heating lubricating oil, wherein the instantaneous optimal dissolution temperature in step S4 is... The calculation method is as follows: The system collects the current temperature inside the blending tank in real time. and fluid viscosity Combined with the solubility parameters of the additives Solubility parameters of base oil Determined by the following formula in The preset compatibility threshold is determined by the difference in solubility parameters. - Determine the compatibility of the oil-based agent, and Restricted to Within the range, This is the thermal decomposition temperature of the additive, ensuring optimal dissolution within a safe temperature range.

[0009] The present invention provides a multi-dimensional blending method for heating lubricating oil, wherein the effective dispersion coefficient in step S5 is... Improved shear correction Model calculation: in, Pre-exponential factor, For dissolution activation energy, The gas constant is... The critical shear rate. The fluid's non-Newtonian index; the control system is based on the calculated... The frequency of the stirring motor is adjusted in real time. When the temperature is below the preset threshold, prioritize increasing the temperature. ;when When the heat loss exceeds the preset threshold but the thermal history loss is too large, the shear rate should be increased preferentially. And lower the temperature. Establish a dispersion kinetic model that incorporates the effects of temperature and shear rate, based on... The value is compared with a preset threshold, and the "heating up" or "speeding up" strategy is dynamically selected.

[0010] The present invention discloses a multi-dimensional blending method for heating lubricating oil. The main heating unit uses heat transfer oil heating in a tank jacket to provide a basic constant temperature with a large heat capacity. The auxiliary heating unit uses an electromagnetic induction heater connected in series in the circulation pipeline to provide instantaneous temperature rise with millisecond-level response.

[0011] The present invention provides a multi-dimensional blending method for heating lubricating oil, wherein step S5 further includes a viscosity-energy consumption feedback loop: Real-time monitoring of current changes in the stirring motor The mixing uniformity index can be calculated using the following formula. : in The standard deviation of the current fluctuation. The mean current is used to indirectly characterize fluid uniformity through the current fluctuation statistic (standard deviation / mean); when And the duration exceeds the set value When the mixing is complete, the system automatically stops heating and enters the cooling process.

[0012] The present invention discloses a multi-dimensional blending method for heating lubricating oil, the method further comprising an adaptive learning module, which records the process of blending each time. The correspondence between the curve and the final product quality data is established, and the weighting coefficients in the formula of claim 1 are corrected using the gradient descent method. It enables continuous self-optimization of process parameters, possesses a certain AI learning capability, improves the system's adaptability and robustness to different raw materials and formulations, and gradually approaches the globally optimal blending strategy.

[0013] As can be seen from the above technical solution, the present invention has the following beneficial effects: This invention discloses a multi-dimensional blending method for heating lubricating oil. First, basic data initialization is achieved by collecting the viscosity-temperature characteristic curve of the base oil, the dissolution activation energy of the additive, and the thermal degradation threshold. Then, a multi-dimensional coupled model integrating temperature, rheology, and time dimensions is constructed. The main heating unit, using heat transfer oil in the tank jacket, maintains the basic flow temperature and performs low-speed pre-blending. An electromagnetic induction auxiliary heating unit connected in series in the circulation pipeline instantly raises the temperature of the local fluid in the additive injection section to millisecond levels based on the instantaneous optimal dissolution temperature calculated by the solubility parameter model. An improved shear-corrected Arrhenius model is used to calculate the effective dispersion coefficient in real time. The blending efficiency function dynamically balances the effective dispersion efficiency, input energy consumption, and cumulative thermal damage. Variable shear synergistic control is achieved by dynamically adjusting the stirring shear rate and heating power, combined with a viscosity-energy consumption approach. The feedback loop (based on the standard deviation and mean of the current fluctuation of the stirring motor to calculate the uniformity index) accurately determines the mixing endpoint. At the same time, the adaptive learning module records the correspondence between the temperature change curve and the product quality. The gradient descent method is used to correct the weight coefficient of the mixing efficiency function, ultimately achieving efficient dispersion, energy saving and consumption reduction, and low thermal damage in the lubricating oil mixing process, significantly improving the product mixing uniformity and batch quality stability. Attached Figure Description

[0014] Figure 1 This is a flowchart of a multi-dimensional blending method for heating lubricating oil according to the present invention. Detailed Implementation

[0015] Example 1 To realize the multi-dimensional blending method for heating lubricating oil of the present invention, a corresponding hardware system needs to be constructed first. This system mainly includes: a blending tank equipped with a jacketed heat transfer oil heating system (main heating unit) to provide a constant temperature environment with high heat capacity for the base oil; and a circulation pipeline connecting the bottom outlet and top inlet of the tank, with an electromagnetic induction heater (auxiliary heating unit) connected in series to precisely control the temperature of the local fluid flowing through the pipeline with millisecond-level response. The stirring system employs a frame-type or turbine-type stirring paddle driven by a variable frequency motor, which can precisely adjust the rotation speed to control the shear rate. Sensing and control unit: Includes an online viscometer, temperature sensor, torque sensor, and central PLC controller. The PLC controller has the core algorithm model of this invention pre-installed.

[0016] The blending process for 5W-30 fully synthetic motor oil is shown in the flowchart below. Figure 1 As shown, 1. Basic data initialization Raw materials: PAO6 (polyalphaolefin) is selected as the base oil; a composite additive package (containing detergent dispersant, antioxidant, ZDDP, etc.) is selected.

[0017] Parameter settings: base oil Set to 50 degrees.

[0018] Thermal decomposition threshold of additives It is 110 degrees.

[0019] The system measures the kinematic viscosity of the base oil at 40 degrees Celsius and records the data.

[0020] Algorithm weight coefficient setting: efficiency weight = 0.6, energy consumption weight = 0.3, thermal damage weight = 0.1.

[0021] 2. Detailed Explanation of the Harmonization Process Phase A: Basic Heating Pump 5000L of base oil into the blending tank, turn on the jacket heating, and slowly raise and maintain the oil temperature at 50 degrees Celsius. At this time, start low-speed stirring (30 rpm) to ensure uniform temperature.

[0022] Phase B: Additive Injection and Instantaneous Fine-tuning Additive injection begins. The system calculates the optimal instantaneous dissolution temperature of the current additive based on the solubility parameter model. = 75 degrees.

[0023] Action: The electromagnetic induction heater on the circulation pipeline is activated, instantly heating the oil flowing through the pipeline to 75 degrees Celsius, and mixing it with the injected additives at this high temperature.

[0024] Effect: The additives have achieved optimal dispersion kinetic energy before entering the large tank, but the temperature of the main body of the large tank is still maintained at 50 degrees, avoiding overall overheating.

[0025] Stage C: Variable Shear Cooperative Control After the additive injection is complete, the system enters the cyclic blending phase. The PLC controller performs a calculation every 5 seconds: Input: Current viscosity reading, motor torque.

[0026] Calculation: According to the formula Calculate the effective dispersion coefficient.

[0027] Judgment and Execution: Scenario 1: In the initial mixing stage (first 10 minutes), the additives agglomerate significantly. The system calculates that increasing the temperature will increase the agglomeration rate. The energy cost is too high, so the strategy tends to be "high shear". The system commands the stirring speed to increase to 120 rpm, while turning off the auxiliary heating, using only shear heat and main heating to maintain 55 degrees.

[0028] Scenario 2: During the middle stage of mixing (10-25 minutes), to prevent the long-chain polymer from breaking due to high shear (damage to the viscosity index improver), the thermal history integral term... The speed is not yet exceeded. The system automatically reduces the rotation speed to 60 rpm and intermittently turns on the auxiliary heater to provide heat energy in a pulse manner to maintain the activity of micro Brownian motion.

[0029] Phase D: Endpoint Judgment The system monitored the standard deviation of the current fluctuation of the stirring motor. The uniformity index is calculated to be close to 0. If the value is greater than 0.98 for three consecutive minutes, the system determines that the reconciliation is complete and automatically shuts down.

[0030] Comparative experimental data To verify the effectiveness of the present invention, we compared the above-described Example 1 (experimental group) with the traditional blending process (control group).

[0031] Control group (existing technology): Process: Heat the entire tank of base oil to a constant 70 degrees Celsius and maintain a constant rotation speed of 100 rpm until the sample passes the test.

[0032] Raw materials and total quantities: exactly the same as in Example 1.

[0033] Table 1: Comparison of performance indicators between the experimental group and the control group The specific calculation process of the algorithm parameters: To help those skilled in the art better understand the application of the formula, the following provides a specific calculation process at a certain moment: Assume that at t=15 minutes: 1. Data Acquisition: Real-time temperature T=328K (55 degrees), current shear rate .

[0034] 2. Constant setting: The activation energy of the additive system is determined in advance. gas constant Non-Newtonian exponent Critical shear rate .

[0035] 3. Calculation : Decision logic: If the system only increases the temperature to 65 degrees (338K), the calculated... It only increases by about 1.5 times, but energy consumption increases by 20%; while if the shear rate is increased... Increase to According to the formula The shearing term in the process will increase significantly, while the energy consumption will increase only slightly. Therefore, the control algorithm will prioritize the strategy of "increasing speed without increasing temperature" in the next time step.

[0036] The above embodiments are exemplary and are intended to illustrate the technical concept and features of the present invention, so that those skilled in the art can understand the content of the present invention and implement it accordingly. They should not be construed as limiting the scope of protection of the present invention. All changes or modifications made according to the spirit and essence of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for multi-dimensional blending of lubricating oil by heating, characterized in that, The method includes the following steps: S1: Basic data initialization: Obtain the viscosity-temperature characteristic curve of the base oil, the dissolution activation energy parameters of the additives to be added, and the thermal degradation threshold. S2: Establish a multidimensional coupling model: Construct a harmonic control model that includes temperature, rheological, and time dimensions; S3: Staged Heating and Pre-blending: The base oil is delivered to the blending tank, and the main heating unit maintains the oil temperature at the base flow temperature. At the same time, start the low-speed stirring. S4: Dynamic Instantaneous Fine-tuning: During the additive injection stage, the instantaneous optimal dissolution temperature is calculated based on the model in S2 using an auxiliary heating unit located on the injection pipeline. Rapid heating of localized fluids; S5: Variable Shear Synergistic Control: Based on real-time monitoring of mixing torque feedback, the current apparent viscosity of the fluid is calculated, and the shear rate of the agitator is dynamically adjusted according to the harmonic efficiency function. Adjust the power of the auxiliary heating unit until it is evenly mixed; The harmonic efficiency function in step S5 The following relationship must be satisfied: in, For the effective dispersion factor, The input power is represented by the denominator, which characterizes the loss of additive activity due to the cumulative thermal history. This is the thermal sensitivity coefficient.

2. The method for multi-dimensional blending of lubricating oil heating according to claim 1, characterized in that, The instantaneous optimal dissolution temperature in step S4 The calculation method is as follows: The system collects the current temperature inside the blending tank in real time. and fluid viscosity Combined with the solubility parameters of the additives Solubility parameters of base oil Determined by the following formula in The preset compatibility threshold is used, and Restricted to Within the range, This refers to the thermal decomposition temperature of the additive.

3. The method for multi-dimensional blending of lubricating oil heating according to claim 1, characterized in that, The effective dispersion coefficient in step S5 Improved shear correction Model calculation: in, Pre-exponential factor, For dissolution activation energy, The gas constant is... The critical shear rate. The fluid's non-Newtonian index; the control system is based on the calculated... The frequency of the stirring motor is adjusted in real time. When the temperature is below the preset threshold, prioritize increasing the temperature. ;when When the heat loss exceeds the preset threshold but the thermal history loss is too large, the shear rate should be increased preferentially. And lower the temperature.

4. The method for multi-dimensional blending of lubricating oil heating according to claim 1, characterized in that, The main heating unit uses a tank jacket for heating with heat transfer oil to provide a basic constant temperature with a large heat capacity; the auxiliary heating unit uses an electromagnetic induction heater connected in series in the circulation pipeline to provide instantaneous heating with a millisecond-level response.

5. The method for multi-dimensional blending of lubricating oil heating according to claim 1, characterized in that, Step S5 also includes a viscosity-energy consumption feedback loop: Real-time monitoring of current changes in the stirring motor The mixing uniformity index can be calculated using the following formula. : in The standard deviation of the current fluctuation. The average current; when And the duration exceeds the set value When the mixing is complete, the system automatically stops heating and enters the cooling process.

6. The method for multi-dimensional blending of lubricating oil heating according to claim 1, characterized in that, The method also includes an adaptive learning module that records the reconciliation process at each stage. The correspondence between the curve and the final product quality data is established, and the weighting coefficients in the formula of claim 1 are corrected using the gradient descent method. .

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