Reluctance motor and paddle energy-saving adaptation method and device

Abstract

The invention belongs to the technical field of reluctance energy-saving stirring, and particularly relates to a reluctance motor and paddle energy-saving adaptation method and device. The reluctance motor and paddle energy-saving adaptation method comprises the following steps: S1, obtaining an original stirring scheme; step S2, optimizing a CFD (Computational Fluid Dynamics) paddle; s3, actually measuring the mechanical no-load power of a plurality of reluctance motors to be selected; and S4, adapting a plurality of reluctance motors to be selected to the blades to obtain an optimal scheme. In other words, according to the reluctance motor and paddle energy-saving adaptation method, CFD paddle optimization and motor power actual measurement are adopted, the precision of an optimization scheme is improved, and meanwhile the test cost is reduced; and the reluctance motor is accurately matched with the paddle, so that the loss of a low-load motor is avoided, and the production cost and the use cost are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of reluctance energy-saving stirring, and in particular relates to a method and device for energy-saving adaptation of a reluctance motor and a blade. Background Art

[0002] In the mixing industry, suspension is one of the core goals of achieving efficient mixing and reaction. Butyl particles are the "invisible cornerstone" of high-quality development in multiple industries. From deep-seated mineral development to life-saving vaccine purification, from tire manufacturing to green resource recycling, butyl particles, in their diverse forms, have become an indispensable core material in the industrial chain. The preparation of butyl particles requires agitation and suspension. In achieving effective suspension, precise matching of motor and propeller power is crucial.

[0003] Energy consumption in a mixing system primarily comes from motor losses, paddle losses, and friction losses, with the first two being the primary sources of power consumption. The mixing effect and power consumption are essentially determined by the motor and paddle power selections. However, an improper match between the two can lead to unnecessary power loss. Traditional motors and paddles are typically matched based on empirical design. To ensure proper operation, excessive power redundancy is often designed, often exceeding 60% of the input power. This results in a "big horse pulling a small cart" phenomenon, with high-power motors generating greater heat losses during operation.

[0004] Low viscosity industrial mixing devices generally use an asynchronous motor + a paddle-type pitched blade combination, and the selection and matching of the two are based entirely on experience. Figure 7 The three-phase asynchronous motor and paddle-type pitched-blade mixing equipment shown has a shaft power of only 0.2 kW, an input power of 0.5 kW, and a motor rated power of 1.5 kW. It has at least the following defects: First, the motor and paddles consume a lot of power. The motor often operates at low load, and the heat loss at low load is too large. The paddle-type blades have a simple structure but high power consumption, which often does not meet the input working conditions. Second, the motor and blades do not match. The selection of the two is heavily dependent on experience, and the motor rated power redundancy is as high as 60% of the input power, increasing the motor heat loss and customization cost. If the shaft power obtained by CFD simulation optimization of the blades alone cannot be accurately adapted to the motor; if the paddle shaft power is tested by experiment, although an accurate matching result can be obtained, the R&D and mold opening costs are high. Summary of the Invention

[0005] The object of the present invention is to provide a method and device for energy-saving adaptation of a reluctance motor and blades.

[0006] In a first aspect, the present application provides a method for energy-saving adaptation of a reluctance motor and a blade, comprising: Step S1, obtaining the original mixing plan, including: collecting the customer's original working condition data, performing CFD simulation, and obtaining the original mixing plan; Step S2, CFD blade optimization, includes: preliminarily determining the blade type according to the stirring medium and stirring purpose; optimizing the blade using CFD, and selecting the optimal blade solution based on the CFD optimization results; Step S3, measuring the mechanical no-load power of several selected reluctance motors; Step S4, adapting several candidate reluctance motors to the blades to obtain the optimal solution, including: obtaining the selected power and load after each candidate reluctance motor is adapted to the blade, selecting a reluctance motor with a rated power not less than the selected power and a load within a preset range to adapt to the blade to obtain the optimal solution.

[0007] In one embodiment of the present application, the customer's original working condition data includes: customer process parameters, stirring purpose, medium physical properties, equipment geometric parameters, blade type, and motor type, power, and current; The CFD simulation includes: performing fluid simulation on the customer's original working conditions based on a multiphase flow model and a turbulence model.

[0008] In one embodiment of the present application, obtaining the original stirring scheme includes: The mixing time, blade torque, average shaft power, average motor mechanical no-load power, actual measurement of average power with stirring medium, and motor heat loss of the original mixing scheme.

[0009] In one embodiment of the present application, in step S2, the types of blades preliminarily determined include paddle blades, turbine blades, swept blades, propeller blades, anchor frame blades, and their variants; The selecting of the optimal blade scheme according to the CFD optimization result includes: determining the optimal blade scheme by comparing flow field velocity, vortex distribution, shaft power and mixing time.

[0010] In one embodiment of the present application, in step S3, the method of measuring the mechanical no-load power of a plurality of selected reluctance motors includes: Without adding any stirring medium in the mixing tank, the motor drives the blades mechanically without load, and the mechanical no-load power of the motor is recorded.

[0011] In one embodiment of the present application, the selected power = input power * standard margin coefficient; wherein the standard margin coefficient has a value range of 1.1 to 1.15; The input power = (optimal blade shaft power + mechanical no-load power) * system mechanical friction consumption correction coefficient; wherein the system mechanical friction consumption correction coefficient is set to 1.1.

[0012] In a second aspect, the present application provides a reluctance motor and blade energy-saving adaptation device, comprising: The original mixing scheme acquisition module is used to obtain the original mixing scheme; CFD blade optimization module, used to optimize and select the optimal blade solution; A mechanical no-load power acquisition module is used to obtain the measured mechanical no-load power of several candidate reluctance motors; The optimal adaptation solution acquisition module is used to adapt several candidate reluctance motors to the blades to obtain the optimal solution.

[0013] The beneficial effects of the present invention are: Different from the existing technology, the present application provides a method for energy-saving adaptation of a reluctance motor and blades. The method for energy-saving adaptation of a reluctance motor and blades includes: step S1, obtaining the original stirring scheme; step S2, CFD blade optimization; step S3, measuring the mechanical no-load power of several candidate reluctance motors; step S4, adapting several candidate reluctance motors to the blades to obtain the optimal scheme. In other words, the method for energy-saving adaptation of a reluctance motor and blades of the present invention uses CFD blade optimization + motor power measurement to improve the accuracy of the optimization scheme while reducing the test cost; the precise adaptation of the reluctance motor and blades avoids low-load motor losses and reduces production and use costs.

[0014] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and the drawings.

[0015] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 This is a flow chart of a method for energy-saving adaptation of a reluctance motor and a blade according to a preferred embodiment of the present invention; Figure 2 The blade form, flow field velocity distribution and Q-criterion vortex distribution of the original stirring scheme of a preferred embodiment of the present invention are as follows; Figure 3 The blade form, flow field velocity distribution and Q-criterion vortex distribution of the optimization scheme 1 of a preferred embodiment of the present invention are as follows; Figure 4The blade form, flow field velocity distribution and Q-criterion vortex distribution of the optimization solution 2 of a preferred embodiment of the present invention are shown; Figure 5 The blade form, flow field velocity distribution and Q-criterion vortex distribution of the optimization solution 3 of a preferred embodiment of the present invention are as follows; Figure 6 This is a mechanical no-load measurement mode of a reluctance motor according to a preferred embodiment of the present invention; Figure 7 It is a schematic diagram of a three-phase asynchronous motor and a paddle-type inclined-blade stirring device in the prior art. DETAILED DESCRIPTION

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0019] This application provides a method and device for energy-saving adaptation of a reluctance motor and a blade, which are described in detail below. It should be noted that the order of description of the following embodiments does not limit the preferred order of the embodiments of this application. In addition, in the following embodiments, the description of each embodiment has its own focus. For parts not detailed in a particular embodiment, please refer to the relevant description of other embodiments.

[0020] See also Figure 1 In one embodiment, a method for energy-saving adaptation of a reluctance motor and a blade includes: Step S1, obtaining the original mixing plan, including: collecting the customer's original working condition data, performing CFD simulation, and obtaining the original mixing plan; Step S2, CFD blade optimization, includes: preliminarily determining the blade type according to the stirring medium and stirring purpose; optimizing the blade using CFD, and selecting the optimal blade solution based on the CFD optimization results; Step S3, measuring the mechanical no-load power of several selected reluctance motors; Step S4, adapting several candidate reluctance motors to the blades to obtain the optimal solution, including: obtaining the selected power and load after each candidate reluctance motor is adapted to the blade, selecting a reluctance motor with a rated power not less than the selected power and a load within a preset range to adapt to the blade to obtain the optimal solution.

[0021] Optionally, in step S1, the customer's original operating condition data includes: collecting customer process parameters (Reynolds number Re, Froude number Fr, power number Np), stirring purpose (homogenization, heat transfer, suspension, etc.), medium physical properties (dynamic viscosity μ, density ρ) and equipment geometric parameters (blade diameter D, height from the bottom H), blade type, as well as motor type, power, and current; performing CFD simulation includes: performing fluid simulation of the customer's original operating conditions based on a multiphase flow model and a turbulence model. In step S1, obtaining the original stirring scheme includes: the mixing time of the original stirring scheme, blade torque, average shaft power, average no-load power of the motor, measured average power of the stirring medium, and motor heat loss of approximately.

[0022] Specifically, in one embodiment, the asynchronous motor and 45° pitched blades of the display tank are used as the original working conditions to demonstrate the state of suspended particles in stirring, and the stirring parameters are recorded and the original stirring scheme is obtained through CFD: See also Figure 2 The original mixing solution used a 1.5 kW three-phase asynchronous motor with a 45° pitched blade. The stirring medium had a density of 1000 kg / m³ and a viscosity of 0.5 cp. 3 mm diameter butyl particles were suspended in the liquid with a particle density of 920 kg / m³. In CFD calculations, the standard for complete mixing was a generally accepted particle concentration test method: the solids content at N sampling points in the flow field is αs, the average solids content is αavg, and the ratio is b = αs / αavg. When 0.95 ≤ b ≤ 1.05, the solid particles are completely suspended. The time to achieve complete suspension is called the mixing time. CFD calculations showed a mixing time of 9.5 seconds, with an average shaft power of 0.18 kW (consistent with the shaft power measured using a torque flange). The average motor power at no load (no medium in the mixing tank) was 0.46 kW (measured by a high-precision smart meter). The average power with stirring medium was measured to be 0.67 kW, and the motor heat loss was 40%. The motor's mechanical no-load + shaft power is essentially equal to the measured input power (the error is due to mechanical friction during measurement with a medium). The cumulative power consumption over 20 hours is 10.6 kWh.

[0023] Furthermore, in step 2, the types of blades preliminarily determined include paddle blades, turbine blades, swept blades, spiral blades, anchor frame blades and their variations; the selection of the optimal blade scheme based on the CFD optimization results includes: determining the optimal blade scheme by comparing flow field velocity, vortex distribution, shaft power and mixing time.

[0024] In this embodiment, commonly used blade types include paddle blades, turbine blades, swept blades, spiral blades, anchor frame blades and their variants, etc. Select a suitable stirring blade according to the stirring medium and stirring purpose, and preliminarily determine the type of blade. The blades preliminarily selected are optimized and designed by CFD to achieve the purpose of energy saving equivalence. The flow field velocity distribution can be optimized by changing the blade curvature, aspect ratio, blade position, etc., and the turbulence and vortex energy loss can be reduced to achieve the purpose of reducing shaft power. At the same time, the mixing indicators such as mixing time, circulation volume, and video effect of the original scheme are optimized and designed, and finally the purpose of reducing shaft power while benchmarking the stirring effect of the original scheme is achieved. Through optimization, the standard paddle-type inclined blades can usually reduce the shaft power by more than 30% without changing the stirring effect. Using CFD for blade optimization design can reduce 80% of experiments and greatly reduce R&D costs. At the same time, the shaft power and flow field calculation accuracy of CFD have been verified to be highly reliable.

[0025] Specifically, the complete CFD blade optimization process in step 2 may include: (1) preliminarily determining the blade form based on experience and working conditions → (2) optimizing the blade using CFD → (3) selecting the optimal solution based on the CFD optimization results and comparing them with the original solution.

[0026] (1) Commonly used blade types include paddle blades, turbine blades, swept blades, spiral blades, anchor frame blades and their variants. The original working condition is a low viscosity, low speed stirring process, so paddle blades and swept blades are given priority.

[0027] (2) Using CFD to optimize blades Predicted results: 1) Low efficiency, high power 2) Low efficiency, low power 3) Equal / high efficiency, high power 4) Equal / high efficiency, low power. The results are determined by velocity flow field, vortex energy, and mixing time, and compared with shaft power.

[0028] Optimization solution 1: See Figure 3 The original four-blade, 45° pitched impeller was modified to have a 20° twist angle from tip to tip, and a gradually narrowing cross-section. Shaft power was 0.048 kW, and mixing time was 14.2 seconds. The vortex energy was low, and the velocity distribution was inferior to the original design. While vortex losses in the flow field were reduced, the mixing effect was poor, representing prediction 2.

[0029] Optimization solution 2: See Figure 4 A four-blade, swept-back impeller with a uniform cross-section was designed. The shaft power was 0.19 kW, and the mixing time was 8.6 seconds. The vortex energy was greater, and the velocity distribution was stronger than the original design. The mixing effect was better, but the power was higher, which falls under Result 3.

[0030] Optimization solution 3: See Figure 5The original 45° pitched impeller design exhibited deformation, with a -20° twist angle from tip to tip and four blades of uniform cross-section. Shaft power was 0.12 kW, and mixing time was 9.7 seconds. The curved impeller exhibited low vortex energy and a reasonable velocity distribution. This reduced flow field vortex losses, reduced shaft power by 33%, and achieved equivalent mixing performance, representing prediction 4.

[0031] In the blade optimization step (2), by comparing the flow field velocity, vortex distribution, shaft power, and mixing time, it can be determined that Optimization Scheme 3 is the optimal solution for this working condition. The stirring effect is comparable to the original solution, and the shaft power is reduced by 33%.

[0032] Furthermore, in step S3, the method for measuring the mechanical no-load power of several selected reluctance motors includes: without adding any stirring medium in the stirring tank, the motor drives the blades to be mechanically no-loaded, and recording the mechanical no-load power of the motor.

[0033] Optionally, a super-efficient reluctance motor with IE5 efficiency (>96%) and low heat dissipation can be selected. This motor, coupled with a variable frequency speed control system (vector control), maintains high efficiency even under low-load conditions. The selected motor's mechanical no-load power at various speeds is measured using a smart meter and an accumulated timer.

[0034] In some existing technologies, CFD power calculations only consider the power required for the blades to overcome fluid resistance, without considering the motor's own losses, the mechanical friction losses of the mixing system, and the power required to overcome the blade's weight (the weight difference between optimized and unoptimized blades in the same mixing system is not significant). Therefore, the mechanical no-load power of the mixing tank must take into account the motor's own losses, the mechanical friction losses of the mixing system, and the power required to overcome the blade's weight. Figure 6 No stirring medium is added to the mixing tank, the motor drives the stirring paddle mechanically without load, and a high-precision ammeter is used to record the motor input power (the weight difference between the optimized and unoptimized blades of the same stirring system is not large, so it is not necessary to test each optimized blade, and only the 45° inclined blade of the original solution is required).

[0035] Furthermore, the mechanical no-load power of reluctance motors produced by different manufacturers varies, making step 3 essential. Taking a conventional reluctance motor as an example, based on experience, the rated power for the original operating conditions might be 0.37 kW, 0.75 kW, and 1.5 kW. After stable operation, the mechanical no-load power of these three motors, measured with the original propellers, was 0.24 kW, 0.29 kW, and 0.37 kW, respectively. (The average mechanical no-load power of the original motor was 0.46 kW.)

[0036] Furthermore, in step S4, the selected power = input power * standard margin coefficient; wherein, the value range of the standard margin coefficient is 1.1 to 1.15; the input power = (optimal blade shaft power + mechanical no-load power) * system mechanical friction consumption correction coefficient; wherein, the value of the system mechanical friction consumption correction coefficient is 1.1.

[0037] In this embodiment, the power loss of the stirring system is typically comprised of motor power, blade power, and friction loss. Combining the equivalent energy-saving blade shaft power obtained through CFD optimization in step 2, which is equivalent to the original solution, with the measured mechanical no-load power at the same motor speed in step 3, the input power of the entire stirring system can be calculated as follows: input power = (optimal blade shaft power + mechanical no-load power) * system mechanical friction loss correction factor. The load can be calculated based on the input power: load = input power / rated power. Furthermore, a 10% to 15% margin is reserved according to the ISO / IEC 60034-30-1 standard to determine the selected power: selected power = input power * standard margin factor. The optimal solution for this operating condition is to select the motor with the minimum rated power that meets the load requirements within the golden load range (55%-85%) and the selected power requirements, paired with the optimized blade.

[0038] Specifically, in this embodiment, the CFD-optimized blade shaft power is 0.12 Kw, which is added to the mechanical no-load power of the three motor groups to be 0.36 Kw, 0.41 Kw, and 0.49 Kw, respectively.

[0039] According to the calculation of input power = (optimal blade shaft power + mechanical no-load power) * system mechanical friction consumption correction coefficient, the input power of the three motors is 0.396 kW, 0.451 kW, and 0.539 kW.

[0040] According to the ISO / IEC 60034-30-1 standard, a 15% margin is reserved, that is, the standard margin coefficient is 1.15. Then, according to the formula selected power = input power * standard margin coefficient, the selected power of each motor is 0.455 kW, 0.578 kW, and 0.693 kW respectively.

[0041] It can be seen that the rated power of the motor with a rated power of 0.37 Kw is too small, and the load reaches 107%; the rated power of the motor with a rated power of 1.5 Kw is too large and the load is only 36%; the rated power of the motor with a rated power of 0.75 Kw is suitable for a load of 60%, which is in the golden load range of the reluctance motor.

[0042] After actual measurement, for the original working conditions, compared with the original stirring solution, the 0.75Kw reluctance motor + optimized blade input power is reduced by 33%, the motor heat loss is about 21%, which is reduced by 50%, and the cumulative power consumption measured in 20 hours is 6.8 degrees, which is a decrease of 35%.

[0043] In summary, the proposed energy-saving adaptation method for reluctance motors and propellers reduces propeller torque (shaft power) through CFD optimization while maintaining the same stirring performance as the original solution. This method then pairs the motor with a suitable engine to ensure consistent operation within the optimal load range. While maintaining the same stirring performance, this method avoids high motor losses under low-load operation, reduces propeller torque (shaft power), and accurately adapts the input power by combining CFD propeller optimization with measured motor power. This reduces testing costs while also achieving accurate results.

[0044] It should be noted that the various devices selected in this application (components whose specific structures are not described) are all universal standard parts or components known to those skilled in the art, and their structures and principles can be known to those skilled in the art through technical manuals or through conventional experimental methods.

[0045] Based on the above-mentioned ideal embodiment of the present invention, and through the above description, relevant personnel can make various changes and modifications without departing from the scope of the technical concept of the present invention. The technical scope of the present invention is not limited to the contents of the specification.

Claims

1. A method for energy-saving adaptation of a reluctance motor and a blade, characterized in that: include: Step S1, obtaining the original mixing plan, including: collecting the customer's original working condition data, performing CFD simulation, and obtaining the original mixing plan; Step S2, CFD blade optimization, includes: preliminarily determining the blade type according to the stirring medium and stirring purpose; optimizing the blade using CFD, and selecting the optimal blade solution based on the CFD optimization results; Step S3, measuring the mechanical no-load power of several selected reluctance motors; Step S4, adapting several candidate reluctance motors to the blades to obtain the optimal solution, including: obtaining the selected power and load after each candidate reluctance motor is adapted to the blade, selecting a reluctance motor with a rated power not less than the selected power and a load within a preset range to adapt to the blade to obtain the optimal solution.

2. The energy-saving adaptation method for a reluctance motor and a blade according to claim 1, characterized in that: In step S1, the customer's original working condition data includes: customer process parameters, stirring purpose, medium physical properties, equipment geometric parameters, blade type, and motor type, power, and current; The CFD simulation includes: performing fluid simulation on the customer's original working conditions based on a multiphase flow model and a turbulence model.

3. The energy-saving adaptation method for a reluctance motor and a blade according to claim 1, characterized in that: In step S1, obtaining the original stirring scheme includes: The mixing time, blade torque, average shaft power, average motor mechanical no-load power, actual measurement of average power with stirring medium, and motor heat loss of the original mixing scheme.

4. The method for energy-saving adaptation of a reluctance motor and a blade according to claim 1, characterized in that: In step S2, the blade types preliminarily determined include paddle blades, turbine blades, swept blades, spiral blades, anchor frame blades, and their variants; The selecting of the optimal blade scheme according to the CFD optimization result includes: determining the optimal blade scheme by comparing flow field velocity, vortex distribution, shaft power and mixing time.

5. The energy-saving adaptation method for a reluctance motor and a blade according to claim 1, characterized in that: In step S3, the method for measuring the mechanical no-load power of several selected reluctance motors includes: Without adding any stirring medium in the mixing tank, the motor drives the blades mechanically without load, and the mechanical no-load power of the motor is recorded.

6. The energy-saving adaptation method for a reluctance motor and a blade according to claim 1, characterized in that: In step S4, the selected power = input power * standard margin coefficient; wherein the standard margin coefficient has a value range of 1.1 to 1.15; The input power = (optimal blade shaft power + mechanical no-load power) * system mechanical friction consumption correction coefficient; wherein the system mechanical friction consumption correction coefficient is set to 1.

1.

7. A reluctance motor and blade energy-saving adaptation device, characterized in that: include: The original mixing scheme acquisition module is used to obtain the original mixing scheme; CFD blade optimization module, used to optimize and select the optimal blade solution; A mechanical no-load power acquisition module is used to obtain the measured mechanical no-load power of several candidate reluctance motors; The optimal adaptation solution acquisition module is used to adapt several candidate reluctance motors to the blades to obtain the optimal solution.

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