Biodiesel reaction equipment with AI model and methanol flow rate control
Patent Information
- Application Number
- CN202522616070.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-10
- Publication Date
- 2026-10-30
- Estimated Expiration
- 2035-12-10
AI Technical Summary
然而，在酶法生物柴油工业生产实践中，一个长期存在的关键技术挑战是甲醇对脂肪酶的毒害和抑制作用，高浓度的甲醇环境会迅速破坏脂肪酶的活性，导致其不可逆失活，这不仅严重影响反应效率和转化率，更由于酶制剂成本昂贵，显著增加了生物柴油的生产成本
[0015]与现有技术相比，本实用新型的有益效果是：具备根据多维实时数据自主决策甲醇流速的能力，可动态调整甲醇流速，使得反应体系内的甲醇浓度始终维持在不抑制脂肪酶活性的最佳区间，提高酶的使用寿命、反应效率和生物柴油转化率，整个反应过程中，甲醇的添加自动化进行，提升了反应过程的稳定性和安全性。
Smart Images
Figure CN224917803U_ABST
Abstract
Description
Technical Field
[0001] This utility model relates to the field of enzymatic biodiesel industrial production technology, specifically to a biodiesel reaction device that uses an AI model to coordinate methanol flow rate control. Background Technology
[0002] Biodiesel, as a renewable and clean fuel, has attracted widespread attention for its production technology. Among these technologies, the enzymatic process, which uses lipases to catalyze the transesterification reaction of animal and vegetable oils with short-chain alcohols (such as methanol), has become an important research direction and development trend due to its advantages such as mild reaction conditions, environmental friendliness, and high product purity. However, in the industrial production of enzymatic biodiesel, a long-standing key technical challenge is the toxic and inhibitory effect of methanol on lipases. High concentrations of methanol can rapidly destroy the activity of lipases, leading to irreversible inactivation. This not only seriously affects reaction efficiency and conversion rate but also significantly increases the production cost of biodiesel due to the high cost of enzyme preparations.
[0003] To address the issue of methanol toxicity, existing technologies typically employ either batch addition or constant-rate dripping of methanol. Batch addition relies on operator experience, which carries the risks of significant human error, cumbersome operation, and the potential for localized high methanol concentrations. While constant-rate dripping achieves automation, the quality of the feedstock (e.g., acid value, moisture content) varies significantly from batch to batch, and the methanol requirements and tolerance differ at different reaction stages (e.g., early esterification, peak transesterification, and late equilibrium). A single constant flow rate cannot adapt to the complex dynamic reaction process, often resulting in excessive methanol in the early stages causing enzyme inhibition, or insufficient methanol in the later stages limiting the reaction rate, neither of which achieves optimal reaction results. Therefore, both batch and constant-rate methanol addition methods suffer from lag and imprecision in methanol flow control. Utility Model Content
[0004] The purpose of this invention is to provide a biodiesel reaction device that uses an AI model to coordinate methanol flow rate control, which can intelligently and adaptively adjust the methanol flow rate according to the real-time state of the reaction system and the characteristics of the raw materials, accurately control the methanol concentration in the reaction environment, effectively protect enzyme activity and improve production efficiency, so as to solve the problems mentioned in the background art.
[0005] To achieve the above objectives, this utility model provides the following technical solution: a biodiesel reaction device with AI model-coordinated methanol flow rate control, comprising a reaction vessel; the reaction device further comprises: A methanol supply unit for supplying methanol to the reactor; Raw material oil supply unit for conveying raw materials to the reactor; A multi-dimensional parameter acquisition unit for acquiring data from the reactor; and A central intelligent control cabinet; wherein, the central intelligent control cabinet integrates a data processor and a non-volatile memory; the non-volatile memory is pre-loaded with firmware for an AI flow rate decision model generated based on historical experimental data.
[0006] As a further improvement to the above scheme, the reactor is equipped with a stirring mechanism.
[0007] As a further improvement to the above scheme, the methanol supply unit includes a methanol storage tank, a controllable flow rate actuator, and two pipes I for connecting the methanol storage tank, the controllable flow rate actuator, and the reactor.
[0008] As a further improvement to the above solution, the controllable flow rate actuator is an explosion-proof variable frequency precision metering pump.
[0009] As a further improvement to the above scheme, a pipe I used to connect the controllable flow rate actuator and the reactor extends from the discharge end to the feed inlet at the top of the reactor.
[0010] As a further improvement to the above scheme, the feedstock oil supply unit includes a feedstock tank and a pipeline II for connecting the feedstock tank and the reactor.
[0011] As a further improvement to the above scheme, the multi-dimensional parameter acquisition unit includes a weighing sensor group for monitoring the total weight of materials in the reactor, a timing module for recording the current reaction time, and a human-machine interaction terminal for receiving and storing the initial acid value data of the raw materials.
[0012] As a further improvement to the above solution, the weighing sensor is assembled below the reactor support structure, and the human-machine interface terminal is installed on the central intelligent control cabinet.
[0013] As a further improvement to the above solution, a signal line S is connected between the central intelligent control cabinet and the weighing sensor group, a communication line S is connected between the central intelligent control cabinet and the human-machine interaction terminal, and a control signal line S is connected between the central intelligent control cabinet and the controllable flow rate actuator.
[0014] As a further improvement to the above scheme, the data processor is used to periodically read the real-time parameters provided by the multi-dimensional parameter acquisition unit.
[0015] Compared with the prior art, the beneficial effects of this utility model are: it has the ability to autonomously decide the methanol flow rate based on multi-dimensional real-time data, and can dynamically adjust the methanol flow rate so that the methanol concentration in the reaction system is always maintained in the optimal range that does not inhibit lipase activity, thereby improving the enzyme's lifespan, reaction efficiency and biodiesel conversion rate. In the entire reaction process, the addition of methanol is automated, which improves the stability and safety of the reaction process. Attached Figure Description
[0016] Figure 1 The diagram shown is a structural schematic of the biodiesel reaction equipment provided by this utility model.
[0017] Figure 2 As shown Figure 1 Module block diagram of the central intelligent control cabinet.
[0018] Explanation of main component symbols 1. Reactor; 2. Stirring mechanism; 3. Methanol storage tank; 4. Controllable flow rate actuator; 5. Pipeline I; 6. Raw material oil supply unit; 7. Pipeline II; 8. Multidimensional parameter acquisition unit; 81. Weighing sensor group; 82. Human-machine interaction terminal; 9. Central intelligent control cabinet; 10. Data processor; 11. Non-volatile memory.
[0019] The above description of the main component symbols, together with the accompanying drawings and specific embodiments, provides a further detailed explanation of this utility model. Detailed Implementation
[0020] To make the objectives, technical solutions, and advantages of this utility model clearer, the following detailed description is provided in conjunction with embodiments. Additional aspects and advantages of this utility model will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the utility model. It should be understood that the following description is merely illustrative and not intended to limit the utility model.
[0021] The specific embodiments of this utility model are described in detail below.
[0022] Please see Figure 1 This embodiment provides a biodiesel reaction device with AI model-coordinated methanol flow rate control, which includes a reaction vessel 1, a methanol supply unit for supplying methanol to the reaction vessel 1, a feed oil supply unit 6 for supplying raw materials to the reaction vessel 1, a multi-dimensional parameter acquisition unit 8 for acquiring data of the reaction vessel 1, and a central intelligent control cabinet 9.
[0023] The reactor 1 is equipped with a stirring mechanism 2, which acts on the material in the reaction chamber to promote the esterification reaction. In this embodiment, the reactor 1 is made of 316L stainless steel and provides a reaction chamber for carrying the raw material oil and enzyme catalyst for esterification / transesterification reaction. In actual design, in order to maintain the optimal temperature range (40°C) for the enzyme catalytic reaction, the outer wall of the reactor 1 is also equipped with a jacket, which controls the reaction temperature by circulating a heat transfer medium such as hot water or heat transfer oil to facilitate the enzyme catalytic reaction. The methanol supply unit includes a methanol storage tank 3, a controllable flow rate actuator 4, and two pipes I5 connecting the methanol storage tank 3, the controllable flow rate actuator 4, and the reactor 1. The controllable flow rate actuator 4 is an explosion-proof variable frequency precision metering pump. The metering pump adjusts its motor speed by receiving external electrical signals, thereby achieving precise control of the methanol delivery flow rate. One pipe I5 connecting the controllable flow rate actuator 4 and the reactor 1 extends its outlet end to the feed inlet at the top of the reactor 1, allowing methanol to be stably and uniformly added into the reactor 1. The feedstock supply unit 6 includes a feedstock tank and a pipe II7 connecting the feedstock tank and the reactor 1. In this embodiment, pretreated waste animal and vegetable oils and enzyme catalysts in the feedstock tank are transported to the reactor 1 through pipe II7.
[0024] The multi-dimensional parameter acquisition unit 8 includes a weighing sensor group 81 for monitoring the total weight of materials in the reactor 1, a timing module for recording the current reaction time, and a human-machine interface terminal 82 for receiving and storing the initial acid value data of the raw materials. The weighing sensor group 81 is installed below the support structure of the reactor 1, and the human-machine interface terminal 82 is installed on the central intelligent control cabinet 9. The human-machine interface terminal 82 is an industrial touch screen. Operators use this terminal to input the initial acid value of each batch of raw material oil obtained from laboratory testing, and to set system parameters and monitor the operating status. In this embodiment, the multi-dimensional parameter acquisition unit 8 is used to acquire real-time characteristic parameters of the reaction system, such as the initial acid value of the raw materials, the total weight of the mixture in the reactor, and the reaction time, thereby providing real-time change data for the AI model.
[0025] Please refer to the following: Figure 2 The central intelligent control cabinet 9 integrates a data processor 10 and a non-volatile memory 11. The data processor 10 is used to periodically read real-time parameters provided by the multi-dimensional parameter acquisition unit 8. The non-volatile memory 11 contains firmware for an AI flow rate decision model trained based on historical experimental data. A signal line S1 connects the central intelligent control cabinet 9 and the weighing sensor group 81. A communication line S2 connects the central intelligent control cabinet 9 and the human-machine interface terminal 82. A control signal line S3 connects the central intelligent control cabinet 9 and the controllable flow rate actuator 4. In this embodiment, the analog weight signal (e.g., 4~20mA) converted by the transmitter from the weighing sensor group 81 is received through the signal line S1. Data interaction is performed with the human-machine interface terminal 82 through the communication line S2. A standard analog control signal (e.g., 4~20mA) is output to the controllable flow rate actuator 4 through the control signal line S3 to adjust the methanol flow rate accordingly.
[0026] In this embodiment, the central intelligent control cabinet 9 employs an industrial control computer. Utilizing AI flow rate decision-making model firmware trained and optimized with extensive laboratory and pilot-scale data, the entire reaction system can dynamically adjust the methanol addition rate based on real-time conditions, effectively solving the problem of methanol's toxic inhibition of lipase. Specifically, the data processor 10 periodically reads real-time parameters provided by the multi-dimensional parameter acquisition unit 8, runs the AI flow rate decision-making model firmware based on these parameters to calculate the optimal methanol flow rate at the current moment, and converts this value into a corresponding control signal, sending it to the controllable flow rate actuator 4. This allows for real-time and dynamic adjustment of the rate at which methanol enters the reaction vessel 1. In this embodiment, the powerful industrial control computer runs an optimized and trained AI model program, enabling the equipment to autonomously decide the methanol flow rate based on multi-dimensional real-time data (such as acid value, oil weight, and time), avoiding errors and lags in human experience-based judgment.
[0027] The biodiesel reactor in this embodiment is used in the following steps: S1 Preliminary preparation and data input: The operator adds a fixed amount of raw oil and enzyme preparation to the reaction vessel 1 through the raw oil supply unit 6 and starts the stirring device 2. Before the reaction starts, the operator inputs the initial acid value of the batch of raw oil (for example, the acid value is 10mgKOH / g) through the human-machine interaction terminal 82. S2 Start-up of reaction and initial data acquisition: The operator confirms and starts the reaction program on the human-machine interface terminal 82. The timing module inside the central intelligent control cabinet 9 starts timing from zero (reaction time t=0). At the same time, the data processor 10 reads the initial total weight in the current reaction vessel 1 fed back by the weighing sensor group 81 through the signal line S1. S3AI model-driven methanol feed-in circulation control; S3AI model-driven methanol feed-and-circulation control: S31 Real-time parameter acquisition: Throughout the reaction process, the central intelligent control cabinet 9 acquires data once at a preset cycle (e.g., 30s / time). The acquired parameters include the current reaction time (provided by the timing module), the real-time total weight in the reactor 1 obtained through the signal line S1 (provided by the weighing sensor group 81), and the initial acid value of the feed oil that has been pre-input and stored. S32AI Decision Calculation: The data processor 10 takes the above three real-time parameters (reaction time, real-time total weight, and initial acid value) as an input vector and calls the AI flow rate decision model firmware stored in the non-volatile memory 11. The AI model calculates and outputs a theoretically optimal methanol flow rate setpoint (e.g., 20 mL / min) under the current operating conditions in real time based on the complex mapping relationship established internally (which is obtained by learning and training a large amount of historical production data). S33 command output and execution: The data processor 10 converts the optimal methanol flow rate setting into the corresponding standard analog control signal (e.g., 20 mL / min corresponds to 10 mA), and sends it to the frequency converter of the controllable flow rate actuator 4 through the signal line S3.
[0028] S34 Flow rate regulation: After receiving the control signal, the variable frequency metering pump in the controllable flow rate actuator 4 immediately adjusts its motor speed, thereby adding methanol from the methanol storage tank 3 to the reaction vessel 1 at a calculated precise flow rate of 20 mL / min.
[0029] The S31~S34 cycle control process will continue throughout the entire reaction cycle. The AI model will continuously adjust the methanol addition rate according to the progress of the reaction time and the changes in the weight in the reactor (i.e., the amount of reactants and the amount of methanol added), ensuring that the methanol concentration in the reaction system is always maintained at the optimal dynamic equilibrium point that neither inhibits lipase activity nor fails to effectively promote the transesterification reaction. This significantly improves the utilization efficiency of lipase and the economics of biodiesel production.
[0030] In summary, the biodiesel reaction equipment of this embodiment has the following advantages: it has the ability to autonomously decide the methanol flow rate based on multidimensional real-time data, and can dynamically adjust the methanol flow rate so that the methanol concentration in the reaction system is always maintained in the optimal range that does not inhibit lipase activity, thereby improving enzyme lifespan, reaction efficiency and biodiesel conversion rate. The addition of methanol is automated throughout the reaction process, which improves the stability and safety of the reaction process.
[0031] The above embodiments are merely preferred embodiments of this utility model. Any simple modifications, alterations, and substitutions made to the above embodiments based on the technical essence of this utility model shall fall within the scope of the technical solution of this utility model.
Claims
1. A biodiesel reaction device with AI model-assisted methanol flow rate control, comprising a reaction vessel (1); Its features are, The reaction apparatus also includes: A methanol supply unit for supplying methanol to the reactor (1); Raw material oil supply unit (6) for supplying raw materials to reactor (1); A multi-dimensional parameter acquisition unit (8) for acquiring data from the reactor (1); and Central intelligent control cabinet (9); wherein, the central intelligent control cabinet (9) integrates a data processor (10) and a non-volatile memory (11); the non-volatile memory (11) is pre-loaded with the firmware of an AI flow rate decision model generated based on historical experimental data training.
2. The biodiesel reactor with AI model-assisted methanol flow rate control according to claim 1, characterized in that: The reactor (1) is equipped with a stirring mechanism (2).
3. The biodiesel reaction equipment with AI model-assisted methanol flow rate control according to claim 1, characterized in that: The methanol supply unit includes a methanol storage tank (3), a controllable flow rate actuator (4), and two pipes I (5) for connecting the methanol storage tank (3), the controllable flow rate actuator (4), and the reactor (1).
4. The biodiesel reaction equipment with AI model-assisted methanol flow rate control according to claim 3, characterized in that: The controllable flow rate actuator (4) is an explosion-proof variable frequency precision metering pump; A pipe I (5) is used to connect the controllable flow rate actuator (4) and the reactor (1), with its outlet end extending into the feed port at the top of the reactor (1).
5. The biodiesel reactor with AI model-assisted methanol flow rate control according to claim 1, characterized in that: The raw material supply unit (6) includes a raw material tank and a pipeline II (7) for connecting the raw material tank and the reactor (1).
6. The biodiesel reactor with AI model-assisted methanol flow rate control according to claim 1, characterized in that: The multidimensional parameter acquisition unit (8) includes a weighing sensor group (81) for monitoring the total weight of materials in the reactor (1), a timing module for recording the current reaction time, and a human-machine interaction terminal (82) for receiving and storing the initial acid value data of the raw materials.
7. The biodiesel reactor with AI model-assisted methanol flow rate control according to claim 6, characterized in that: The weighing sensor group (81) is installed below the support structure of the reactor (1), and the human-machine interaction terminal (82) is installed on the central intelligent control cabinet (9).
8. The biodiesel reaction apparatus with AI model-assisted methanol flow rate control according to claim 7, characterized in that: A signal line S1 is connected between the central intelligent control cabinet (9) and the weighing sensor group (81). A communication line S2 is connected between the central intelligent control cabinet (9) and the human-machine interaction terminal (82). A control signal line S3 is connected between the central intelligent control cabinet (9) and the controllable flow rate actuator (4).
9. The biodiesel reactor with AI model-assisted methanol flow rate control according to claim 1, characterized in that: The data processor (10) is used to periodically read the real-time parameters provided by the multi-dimensional parameter acquisition unit (8).